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Andrew C. Harvey

Not to be confused with: Andrew Sydney Harvey

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Andrew Harvey & Jared Bernstein, 2003. "Measurement and Testing of Inequality from Time Series of Deciles with an Application to U.S. Wages," The Review of Economics and Statistics, MIT Press, vol. 85(1), pages 141-152, February.

    Mentioned in:

    1. Forecasting and Tomorrow’s Jobs Report
      by Jared Bernstein in On the Economy on 2012-07-06 00:56:08

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Andrew C. Harvey & Vasco M. Carvalho, 2005. "Convergence in the trends and cycles of Euro-zone income," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 275-289.

    Mentioned in:

    1. Convergence in the trends and cycles of Euro-zone income (Journal of Applied Econometrics 2005) in ReplicationWiki ()
  2. Jukka Nyblom & Andrew Harvey, 2001. "Testing against smooth stochastic trends," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 415-429.

    Mentioned in:

    1. Testing against smooth stochastic trends (Journal of Applied Econometrics 2001) in ReplicationWiki ()
  3. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-247, July-Sept.

    Mentioned in:

    1. Detrending, stylized facts and the business cycle (Journal of Applied Econometrics 1993) in ReplicationWiki ()
  4. Author Profile
    1. Andrew Harvey in Wikipedia (German)

Working papers

  1. Harvey, A. & Palumbo, D., 2021. "Regime switching models for directional and linear observations," Cambridge Working Papers in Economics 2123, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.

  2. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Harvey, Andew & Liao, Yin, 2023. "Dynamic Tobit models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 72-83.

  3. Andrew C. Harvey, 2020. "Time series models for epidemics: leading indicators, control groups and policy assessment," National Institute of Economic and Social Research (NIESR) Discussion Papers 517, National Institute of Economic and Social Research.

    Cited by:

    1. Monika Baloda, 2023. "The Tech Decoupling," Papers 2304.00510, arXiv.org.

  4. Harvey, A. & Palumbo, D., 2019. "Score-Driven Models for Realized Volatility," Cambridge Working Papers in Economics 1950, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Alanya-Beltran, Willy, 2022. "Modelling stock returns volatility with dynamic conditional score models and random shifts," Finance Research Letters, Elsevier, vol. 45(C).

  5. Harvey, A. & Liao, Y., 2019. "Dynamic Tobit models," Cambridge Working Papers in Economics 1913, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Giuseppe Buccheri & Stefano Grassi & Giorgio Vocalelli, 2021. "Estimating Risk in Illiquid Markets: a Model of Market Friction with Stochastic Volatility," CEIS Research Paper 506, Tor Vergata University, CEIS, revised 08 Nov 2021.
    2. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.

  6. Harvey, A. & Hurn, S. & Thiele, S., 2019. "Modeling directional (circular) time series," Cambridge Working Papers in Economics 1971, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Petra Tomanová & Vladimír Holý, 2021. "Clustering of arrivals in queueing systems: autoregressive conditional duration approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(3), pages 859-874, September.
    2. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
    3. Harvey, A. & Palumbo, D., 2021. "Regime switching models for directional and linear observations," Cambridge Working Papers in Economics 2123, Faculty of Economics, University of Cambridge.

  7. Andrew Harvey & Ryoko Ito, 2017. "Modeling time series with zero observations," Economics Papers 2017-W01, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Leopoldo Catania & Roberto Di Mari & Paolo Santucci de Magistris, 2019. "Dynamic discrete mixtures for high frequency prices," Discussion Papers 19/05, University of Nottingham, Granger Centre for Time Series Econometrics.

  8. Harvey, A. & Thiele, S., 2017. "Co-integration and control: assessing the impact of events using time series data," Cambridge Working Papers in Economics 1731, Faculty of Economics, University of Cambridge.

    Cited by:

    1. C. Vladimir Rodríguez-Caballero & J. Eduardo Vera-Valdés, 2020. "Long-Lasting Economic Effects of Pandemics:Evidence on Growth and Unemployment," Econometrics, MDPI, vol. 8(3), pages 1-16, September.
    2. Heather M. Anderson & Jiti Gao & Guido Turnip & Farshid Vahid & Wei Wei, 2022. "Estimating the Effect of an EU-ETS Type Scheme in Australia Using a Synthetic Treatment Approach," Monash Econometrics and Business Statistics Working Papers 12/22, Monash University, Department of Econometrics and Business Statistics.
    3. Takamitsu Kurita & Bent Nielsen, 2019. "Partial Cointegrated Vector Autoregressive Models with Structural Breaks in Deterministic Terms," Econometrics, MDPI, vol. 7(4), pages 1-35, October.
    4. Farid, Moatazbellah, 2020. "The Effect of Brexit on UK Productivity: Synthetic Control Analysis," MPRA Paper 103165, University Library of Munich, Germany.
    5. Kim, Hyejin & Lee, Jungmin, 2019. "Can employment subsidies save jobs? Evidence from a shipbuilding city in South Korea," Labour Economics, Elsevier, vol. 61(C).
    6. Peter Dreuw, 2023. "Structural time series models and synthetic controls—assessing the impact of the euro adoption," Empirical Economics, Springer, vol. 64(2), pages 681-725, February.

  9. Andrew Harvey & Rutger-Jan Lange, 2015. "Volatility Modeling with a Generalized t-distribution," Cambridge Working Papers in Economics 1517, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Buccheri, Giuseppe & Corsi, Fulvio & Flandoli, Franco & Livieri, Giulia, 2021. "The continuous-time limit of score-driven volatility models," Journal of Econometrics, Elsevier, vol. 221(2), pages 655-675.
    2. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
    3. Alexander Georges Gretener & Matthias Neuenkirch & Dennis Umlandt, 2022. "Dynamic Mixture Vector Autoregressions with Score-Driven Weights," Research Papers in Economics 2022-02, University of Trier, Department of Economics.
    4. Alexander, Carol & Lazar, Emese & Stanescu, Silvia, 2021. "Analytic moments for GJR-GARCH (1, 1) processes," International Journal of Forecasting, Elsevier, vol. 37(1), pages 105-124.
    5. Ryoko Ito, 2016. "Asymptotic Theory for Beta-t-GARCH," Cambridge Working Papers in Economics 1607, Faculty of Economics, University of Cambridge.
    6. Giuseppe Buccheri & Stefano Grassi & Giorgio Vocalelli, 2021. "Estimating Risk in Illiquid Markets: a Model of Market Friction with Stochastic Volatility," CEIS Research Paper 506, Tor Vergata University, CEIS, revised 08 Nov 2021.
    7. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
    8. Harvey, A. & Palumbo, D., 2019. "Score-Driven Models for Realized Volatility," Cambridge Working Papers in Economics 1950, Faculty of Economics, University of Cambridge.
    9. Catania, Leopoldo & Grassi, Stefano, 2022. "Forecasting cryptocurrency volatility," International Journal of Forecasting, Elsevier, vol. 38(3), pages 878-894.
    10. Ruijie Guan & Xu Zhao & Weihu Cheng & Yaohua Rong, 2021. "A New Generalized t Distribution Based on a Distribution Construction Method," Mathematics, MDPI, vol. 9(19), pages 1-36, September.
    11. Harvey, Andew & Liao, Yin, 2023. "Dynamic Tobit models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 72-83.
    12. Ayala Astrid & Blazsek Szabolcs & Escribano Alvaro, 2023. "Anticipating extreme losses using score-driven shape filters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(4), pages 449-484, September.
    13. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Maximum Likelihood Estimation for Score-Driven Models," Tinbergen Institute Discussion Papers 14-029/III, Tinbergen Institute, revised 23 Oct 2017.
    14. Harvey, Andrew & Ito, Ryoko, 2020. "Modeling time series when some observations are zero," Journal of Econometrics, Elsevier, vol. 214(1), pages 33-45.
    15. Ito, R., 2016. "Spline-DCS for Forecasting Trade Volume in High-Frequency Finance," Cambridge Working Papers in Economics 1606, Faculty of Economics, University of Cambridge.
    16. Bram van Os, 2023. "Information-Theoretic Time-Varying Density Modeling," Tinbergen Institute Discussion Papers 23-037/III, Tinbergen Institute.
    17. Harvey, A. & Palumbo, D., 2021. "Regime switching models for directional and linear observations," Cambridge Working Papers in Economics 2123, Faculty of Economics, University of Cambridge.
    18. Andrew Harvey & Ryoko Ito, 2017. "Modeling time series with zero observations," Economics Papers 2017-W01, Economics Group, Nuffield College, University of Oxford.
    19. Kamil Makieła & Błażej Mazur, 2022. "Model uncertainty and efficiency measurement in stochastic frontier analysis with generalized errors," Journal of Productivity Analysis, Springer, vol. 58(1), pages 35-54, August.
    20. Astrid Ayala & Szabolcs Blazsek & Adrian Licht, 2022. "Score-driven stochastic seasonality of the Russian rouble: an application case study for the period of 1999 to 2020," Empirical Economics, Springer, vol. 62(5), pages 2179-2203, May.
    21. Mazur Błażej & Pipień Mateusz, 2018. "Time-varying asymmetry and tail thickness in long series of daily financial returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-21, December.
    22. Kamil Makieła & Błażej Mazur, 2020. "Bayesian Model Averaging and Prior Sensitivity in Stochastic Frontier Analysis," Econometrics, MDPI, vol. 8(2), pages 1-22, April.
    23. Stephen Thiele, 2020. "Modeling the conditional distribution of financial returns with asymmetric tails," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 46-60, January.
    24. Astrid Ayala & Szabolcs Blazsek, 2018. "Equity market neutral hedge funds and the stock market: an application of score-driven copula models," Applied Economics, Taylor & Francis Journals, vol. 50(37), pages 4005-4023, August.
    25. Dennis Umlandt, 2020. "Likelihood-based Dynamic Asset Pricing: Learning Time-varying Risk Premia from Cross-Sectional Models," Working Paper Series 2020-06, University of Trier, Research Group Quantitative Finance and Risk Analysis.
    26. Victor Korolev, 2023. "Analytic and Asymptotic Properties of the Generalized Student and Generalized Lomax Distributions," Mathematics, MDPI, vol. 11(13), pages 1-27, June.
    27. Rutger-Jan Lange & Bram van Os & Dick van Dijk, 2022. "Robust Observation-Driven Models Using Proximal-Parameter Updates Abstract We propose an observation-driven modelling framework that permits time variation in the model’s parameters using a proximal-p," Tinbergen Institute Discussion Papers 22-066/III, Tinbergen Institute, revised 20 Dec 2022.
    28. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2019. "Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index," UC3M Working papers. Economics 28133, Universidad Carlos III de Madrid. Departamento de Economía.
    29. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2017. "Dynamic conditional score models with time-varying location, scale and shape parameters," UC3M Working papers. Economics 25043, Universidad Carlos III de Madrid. Departamento de Economía.
    30. Karol Kielak & Robert Ślepaczuk, 2020. "Value-at-risk — the comparison of state-of-the-art models on various assets," Working Papers 2020-28, Faculty of Economic Sciences, University of Warsaw.
    31. Andrew Harvey & Rutger‐Jan Lange, 2018. "Modeling the Interactions between Volatility and Returns using EGARCH‐M," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 909-919, November.
    32. Kamil Makie{l}a & B{l}a.zej Mazur, 2020. "Stochastic Frontier Analysis with Generalized Errors: inference, model comparison and averaging," Papers 2003.07150, arXiv.org, revised Oct 2020.
    33. Palumbo, D., 2021. "Testing and Modelling Time Series with Time Varying Tails," Cambridge Working Papers in Economics 2111, Faculty of Economics, University of Cambridge.
    34. Harvey, A. & Liao, Y., 2019. "Dynamic Tobit models," Cambridge Working Papers in Economics 1913, Faculty of Economics, University of Cambridge.
    35. Fabrizio Leisen & Luca Rossini & Cristiano Villa, 2020. "Loss-based approach to two-piece location-scale distributions with applications to dependent data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(2), pages 309-333, June.
    36. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2019. "Maximum likelihood estimation of score-driven models with dynamic shape parameters : an application to Monte Carlo value-at-risk," UC3M Working papers. Economics 28638, Universidad Carlos III de Madrid. Departamento de Economía.

  10. Andrew Harvey & Rutger-Jan Lange, 2015. "Modeling the Interactions between Volatility and Returns," Cambridge Working Papers in Economics 1518, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Maximum Likelihood Estimation for Score-Driven Models," Tinbergen Institute Discussion Papers 14-029/III, Tinbergen Institute, revised 23 Oct 2017.
    2. Tata Subba Rao & Granville Tunnicliffe Wilson & Andrew Harvey & Rutger-Jan Lange, 2017. "Volatility Modeling with a Generalized t Distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(2), pages 175-190, March.
    3. Liu, Dehong & Gu, Hongmei & Lung, Peter, 2016. "The equity mispricing: Evidence from China's stock market," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 211-223.

  11. Andrew Harvey & Stephen Thiele, 2014. "Testing against Changing Correlation," Cambridge Working Papers in Economics 1439, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    2. Harvey, A. & Hurn, S. & Thiele, S., 2019. "Modeling directional (circular) time series," Cambridge Working Papers in Economics 1971, Faculty of Economics, University of Cambridge.
    3. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
    4. Sakurai, Yuji & Kurosaki, Tetsuo, 2023. "Have cryptocurrencies become an inflation hedge after the reopening of the U.S. economy?," Research in International Business and Finance, Elsevier, vol. 65(C).
    5. Harvey, Andew & Liao, Yin, 2023. "Dynamic Tobit models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 72-83.
    6. Petrella, Ivan & Delle Monache, Davide & De Polis, Andrea, 2022. "Modeling and Forecasting Macroeconomic Downside Risk," CEPR Discussion Papers 15109, C.E.P.R. Discussion Papers.
    7. Harvey, Andrew & Ito, Ryoko, 2020. "Modeling time series when some observations are zero," Journal of Econometrics, Elsevier, vol. 214(1), pages 33-45.
    8. Andrew Harvey & Ryoko Ito, 2017. "Modeling time series with zero observations," Economics Papers 2017-W01, Economics Group, Nuffield College, University of Oxford.
    9. Michel Ferreira Cardia Haddad & Szabolcs Blazsek & Philip Arestis & Franz Fuerst & Hsia Hua Sheng, 2023. "The two-component Beta-t-QVAR-M-lev: a new forecasting model," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 379-401, December.
    10. Song, Shijia & Tian, Fei & Li, Handong, 2021. "An intraday-return-based Value-at-Risk model driven by dynamic conditional score with censored generalized Pareto distribution," Journal of Asian Economics, Elsevier, vol. 74(C).
    11. Astrid Ayala & Szabolcs Blazsek, 2018. "Equity market neutral hedge funds and the stock market: an application of score-driven copula models," Applied Economics, Taylor & Francis Journals, vol. 50(37), pages 4005-4023, August.
    12. Song, Shijia & Li, Handong, 2022. "Predicting VaR for China's stock market: A score-driven model based on normal inverse Gaussian distribution," International Review of Financial Analysis, Elsevier, vol. 82(C).
    13. Andrew Harvey & Dario Palumbo, 2023. "Regime switching models for circular and linear time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(4), pages 374-392, July.
    14. Palumbo, D., 2021. "Testing and Modelling Time Series with Time Varying Tails," Cambridge Working Papers in Economics 2111, Faculty of Economics, University of Cambridge.
    15. Harvey, A. & Liao, Y., 2019. "Dynamic Tobit models," Cambridge Working Papers in Economics 1913, Faculty of Economics, University of Cambridge.

  12. Michele Caivano & Andrew Harvey, 2014. "Time series models with an EGB2 conditional distribution," Temi di discussione (Economic working papers) 947, Bank of Italy, Economic Research and International Relations Area.

    Cited by:

    1. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    2. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
    3. Szabolcs Blazsek & Hector Hernández, 2018. "Analysis of electricity prices for Central American countries using dynamic conditional score models," Empirical Economics, Springer, vol. 55(4), pages 1807-1848, December.
    4. Saissi Hassani, Samir & Dionne, Georges, 2021. "The new international regulation of market risk: Roles of VaR and CVaR in model validation," Working Papers 20-3, HEC Montreal, Canada Research Chair in Risk Management.
    5. Michele Caivano & Andrew Harvey, 2014. "Time-series models with an EGB2 conditional distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 558-571, November.
    6. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
    7. Michele Caivano & Andrew Harvey, 2014. "Two EGARCH models and one fat tail," Temi di discussione (Economic working papers) 954, Bank of Italy, Economic Research and International Relations Area.
    8. Harvey, A. & Palumbo, D., 2019. "Score-Driven Models for Realized Volatility," Cambridge Working Papers in Economics 1950, Faculty of Economics, University of Cambridge.
    9. Jingyu Ji & Hang Lin, 2022. "Evaluating Regional Carbon Inequality and Its Dependence with Carbon Efficiency: Implications for Carbon Neutrality," Energies, MDPI, vol. 15(19), pages 1-35, September.
    10. Harvey, Andew & Liao, Yin, 2023. "Dynamic Tobit models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 72-83.
    11. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Maximum Likelihood Estimation for Score-Driven Models," Tinbergen Institute Discussion Papers 14-029/III, Tinbergen Institute, revised 23 Oct 2017.
    12. Petrella, Ivan & Delle Monache, Davide & De Polis, Andrea, 2022. "Modeling and Forecasting Macroeconomic Downside Risk," CEPR Discussion Papers 15109, C.E.P.R. Discussion Papers.
    13. Michele Caivano & Andrew Harvey & Alessandra Luati, 2016. "Robust time series models with trend and seasonal components," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 7(1), pages 99-120, March.
    14. Michel Ferreira Cardia Haddad & Szabolcs Blazsek & Philip Arestis & Franz Fuerst & Hsia Hua Sheng, 2023. "The two-component Beta-t-QVAR-M-lev: a new forecasting model," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 379-401, December.
    15. Astrid Ayala & Szabolcs Blazsek & Adrian Licht, 2022. "Score-driven stochastic seasonality of the Russian rouble: an application case study for the period of 1999 to 2020," Empirical Economics, Springer, vol. 62(5), pages 2179-2203, May.
    16. Blasques, Francisco & Nientker, Marc, 2023. "Stochastic properties of nonlinear locally-nonstationary filters," Journal of Econometrics, Elsevier, vol. 235(2), pages 2082-2095.
    17. Sergio Contreras-Espinoza & Francisco Novoa-Muñoz & Szabolcs Blazsek & Pedro Vidal & Christian Caamaño-Carrillo, 2022. "COVID-19 Active Case Forecasts in Latin American Countries Using Score-Driven Models," Mathematics, MDPI, vol. 11(1), pages 1-17, December.
    18. Harvey, A. & Liao, Y., 2019. "Dynamic Tobit models," Cambridge Working Papers in Economics 1913, Faculty of Economics, University of Cambridge.

  13. Michele Caivano & Andrew Harvey, 2014. "Two EGARCH models and one fat tail," Temi di discussione (Economic working papers) 954, Bank of Italy, Economic Research and International Relations Area.

    Cited by:

    1. Giuseppe Ferrero & Marcello Miccoli & Sergio Santoro, 2014. "Informational Effects of Monetary Policy," Temi di discussione (Economic working papers) 982, Bank of Italy, Economic Research and International Relations Area.
    2. Andres, Philipp, 2014. "Maximum likelihood estimates for positive valued dynamic score models; The DySco package," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 34-42.
    3. Taneli M�kinen, 2014. "Informed trading and stock market efficiency," Temi di discussione (Economic working papers) 992, Bank of Italy, Economic Research and International Relations Area.

  14. Harvey, A. & Luati, A., 2012. "Filtering with heavy tails," Cambridge Working Papers in Economics 1255, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
    2. Sampi Bravo,James Robert Ezequiel & Jooste,Charl & Vostroknutova,Ekaterina, 2021. "Identification Properties for Estimating the Impact of Regulation on Markups and Productivity," Policy Research Working Paper Series 9523, The World Bank.
    3. Roman Frydman & Soeren Johansen & Anders Rahbek & Morten Nyboe, 2017. "The Qualitative Expectations Hypothesis: Model Ambiguity, Consistent Representations Of Market Forecasts, And Sentiment," Discussion Papers 17-10, University of Copenhagen. Department of Economics.
    4. Drew Creal & Siem Jan Koopman & André Lucas & Marcin Zamojski, 2015. "Generalized Autoregressive Method of Moments," Tinbergen Institute Discussion Papers 15-138/III, Tinbergen Institute, revised 06 Jul 2018.
    5. Catania, Leopoldo & Proietti, Tommaso, 2020. "Forecasting volatility with time-varying leverage and volatility of volatility effects," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
    6. Dalhaus, Tatjana & Schaumburg, Julia & Sekhposyan, Tatevik, 2021. "Networking the yield curve: implications for monetary policy," Working Paper Series 2532, European Central Bank.
    7. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    8. F Blasques & P Gorgi & S Koopman & O Wintenberger, 2016. "Feasible Invertibility Conditions for Maximum Likelihood Estimation for Observation-Driven Models," Papers 1610.02863, arXiv.org.
    9. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
    10. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2018. "Seasonal quasi-vector autoregressive models for macroeconomic data," UC3M Working papers. Economics 26316, Universidad Carlos III de Madrid. Departamento de Economía.
    11. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    12. P. Gorgi & Siem Jan (S.J.) Koopman & R. Lit, 2018. "The analysis and forecasting of ATP tennis matches using a high-dimensional dynamic model," Tinbergen Institute Discussion Papers 18-009/III, Tinbergen Institute.
    13. Telg, Sean & Dubinova, Anna & Lucas, Andre, 2023. "Covid-19, credit risk management modeling, and government support," Journal of Banking & Finance, Elsevier, vol. 147(C).
    14. Ryoko Ito, 2016. "Asymptotic Theory for Beta-t-GARCH," Cambridge Working Papers in Economics 1607, Faculty of Economics, University of Cambridge.
    15. Harvey, A. & Hurn, S. & Thiele, S., 2019. "Modeling directional (circular) time series," Cambridge Working Papers in Economics 1971, Faculty of Economics, University of Cambridge.
    16. Anna Dubinova & Andre Lucas & Sean Telg, 2021. "COVID-19, Credit Risk and Macro Fundamentals," Tinbergen Institute Discussion Papers 21-059/III, Tinbergen Institute.
    17. Gorgi, Paolo & Koopman, Siem Jan & Li, Mengheng, 2019. "Forecasting economic time series using score-driven dynamic models with mixed-data sampling," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1735-1747.
    18. Szabolcs Blazsek & Hector Hernández, 2018. "Analysis of electricity prices for Central American countries using dynamic conditional score models," Empirical Economics, Springer, vol. 55(4), pages 1807-1848, December.
    19. Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2016. "Time series analysis of volatility in the petroleum pricing markets: the persistence, asymmetry and jumps in the returns series," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 40(3), pages 235-262, September.
    20. Andre Lucas & Anne Opschoor, 2016. "Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns," Tinbergen Institute Discussion Papers 16-069/IV, Tinbergen Institute, revised 07 Jul 2017.
    21. Michele Caivano & Andrew Harvey, 2014. "Time-series models with an EGB2 conditional distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 558-571, November.
    22. André Lucas & Xin Zhang, 2014. "Score Driven exponentially Weighted Moving Average and Value-at-Risk Forecasting," Tinbergen Institute Discussion Papers 14-092/IV/DSF77, Tinbergen Institute, revised 09 Sep 2015.
    23. Marco Bazzi & Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2017. "Time-Varying Transition Probabilities for Markov Regime Switching Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 458-478, May.
    24. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Maximum Likelihood Estimation for correctly Specified Generalized Autoregressive Score Models: Feedback Effects, Contraction Conditions and Asymptotic Properties," Tinbergen Institute Discussion Papers 14-074/III, Tinbergen Institute.
    25. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Information Theoretic Optimality of Observation Driven Time Series Models," Tinbergen Institute Discussion Papers 14-046/III, Tinbergen Institute.
    26. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2018. "Seasonal Quasi-Vector Autoregressive Models with an Application to Crude Oil Production and Economic Activity in the United States and Canada," UC3M Working papers. Economics 27484, Universidad Carlos III de Madrid. Departamento de Economía.
    27. Saverio Ranciati & Alberto Roverato & Alessandra Luati, 2021. "Fused graphical lasso for brain networks with symmetries," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1299-1322, November.
    28. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    29. Diego Caballero & André Lucas & Bernd Schwaab & Xin Zhang, 2019. "Risk endogeneity at the lender/investor-of-last-resort," BIS Working Papers 766, Bank for International Settlements.
    30. Blasques, F. & Gorgi, P. & Koopman, S.J., 2021. "Missing observations in observation-driven time series models," Journal of Econometrics, Elsevier, vol. 221(2), pages 542-568.
    31. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024.
    32. Francisco (F.) Blasques & Andre (A.) Lucas & Andries van Vlodrop, 2017. "Finite Sample Optimality of Score-Driven Volatility Models," Tinbergen Institute Discussion Papers 17-111/III, Tinbergen Institute.
    33. F. Lilla, 2016. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models," Working Papers wp1084, Dipartimento Scienze Economiche, Universita' di Bologna.
    34. Lucas, André & Opschoor, Anne & Schaumburg, Julia, 2016. "Accounting for missing values in score-driven time-varying parameter models," Economics Letters, Elsevier, vol. 148(C), pages 96-98.
    35. Blasques, Francisco & Lucas, André & van Vlodrop, Andries C., 2021. "Finite Sample Optimality of Score-Driven Volatility Models: Some Monte Carlo Evidence," Econometrics and Statistics, Elsevier, vol. 19(C), pages 47-57.
    36. Giovanni Angelini & Paolo Gorgi, 2018. "DSGE Models with Observation-Driven Time-Varying parameters," Tinbergen Institute Discussion Papers 18-030/III, Tinbergen Institute.
    37. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Maximum Likelihood Estimation for Score-Driven Models," Tinbergen Institute Discussion Papers 14-029/III, Tinbergen Institute, revised 23 Oct 2017.
    38. Enzo D'Innocenzo & Alessandra Luati & Mario Mazzocchi, 2020. "A Robust Score-Driven Filter for Multivariate Time Series," Papers 2009.01517, arXiv.org, revised Aug 2022.
    39. Khalaf, Lynda & Saunders, Charles J., 2017. "Monte Carlo forecast evaluation with persistent data," International Journal of Forecasting, Elsevier, vol. 33(1), pages 1-10.
    40. Ito, R., 2016. "Spline-DCS for Forecasting Trade Volume in High-Frequency Finance," Cambridge Working Papers in Economics 1606, Faculty of Economics, University of Cambridge.
    41. Martin Weale & Paul Labonne, 2022. "Nowcasting in the presence of large measurement errors and revisions," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-05, Economic Statistics Centre of Excellence (ESCoE).
    42. Blasques, Francisco & Koopman, Siem Jan & Lucas, Andre & Schaumburg, Julia, 2016. "Spillover dynamics for systemic risk measurement using spatial financial time series models," Journal of Econometrics, Elsevier, vol. 195(2), pages 211-223.
    43. Francisco Blasques & Paolo Gorgi & Siem Jan Koopman & Olivier Wintenberger, 2016. "Feasible Invertibility Conditions and Maximum Likelihood Estimation for Observation-Driven Models," Tinbergen Institute Discussion Papers 16-082/III, Tinbergen Institute.
    44. Michele Caivano & Andrew Harvey & Alessandra Luati, 2016. "Robust time series models with trend and seasonal components," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 7(1), pages 99-120, March.
    45. Andre Lucas & Bernd Schwaab & Xin Zhang, 2013. "Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics," Tinbergen Institute Discussion Papers 13-063/IV/DSF56, Tinbergen Institute, revised 13 Oct 2014.
    46. Michel Ferreira Cardia Haddad & Szabolcs Blazsek & Philip Arestis & Franz Fuerst & Hsia Hua Sheng, 2023. "The two-component Beta-t-QVAR-M-lev: a new forecasting model," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 379-401, December.
    47. Tranberg, Bo & Hansen, Rasmus Thrane & Catania, Leopoldo, 2020. "Managing volumetric risk of long-term power purchase agreements," Energy Economics, Elsevier, vol. 85(C).
    48. Paolo Gorgi, 2020. "Beta–negative binomial auto‐regressions for modelling integer‐valued time series with extreme observations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(5), pages 1325-1347, December.
    49. Astrid Ayala & Szabolcs Blazsek & Adrian Licht, 2022. "Score-driven stochastic seasonality of the Russian rouble: an application case study for the period of 1999 to 2020," Empirical Economics, Springer, vol. 62(5), pages 2179-2203, May.
    50. Deniz Erer, 2023. "The Impact of News Related Covid-19 on Exchange Rate Volatility:A New Evidence From Generalized Autoregressive Score Model," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(38), pages 105-126, June.
    51. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
    52. Siem Jan Koopman & Rutger Lit & André Lucas, 2015. "Intraday Stock Price Dependence using Dynamic Discrete Copula Distributions," Tinbergen Institute Discussion Papers 15-037/III/DSF90, Tinbergen Institute.
    53. Anne Opschoor & André Lucas, 2019. "Observation-driven Models for Realized Variances and Overnight Returns," Tinbergen Institute Discussion Papers 19-052/IV, Tinbergen Institute.
    54. Francisco (F.) Blasques & Paolo Gorgi & Siem Jan (S.J.) Koopman, 2017. "Accelerating GARCH and Score-Driven Models: Optimality, Estimation and Forecasting," Tinbergen Institute Discussion Papers 17-059/III, Tinbergen Institute.
    55. Rutger Jan Lange, 2020. "Bellman filtering for state-space models," Tinbergen Institute Discussion Papers 20-052/III, Tinbergen Institute, revised 19 May 2021.
    56. Blasques, F. & Gorgi, P. & Koopman, S.J., 2019. "Accelerating score-driven time series models," Journal of Econometrics, Elsevier, vol. 212(2), pages 359-376.
    57. F. Lilla, 2017. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models - 2nd ed," Working Papers wp1099, Dipartimento Scienze Economiche, Universita' di Bologna.
    58. Kazim Azam & Andre Lucas, 2015. "Mixed Density based Copula Likelihood," Tinbergen Institute Discussion Papers 15-003/IV/DSF084, Tinbergen Institute.
    59. Blasques, Francisco & Ji, Jiangyu & Lucas, André, 2016. "Semiparametric score driven volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 58-69.
    60. Beaumont, Adrian N., 2014. "Data transforms with exponential smoothing methods of forecasting," International Journal of Forecasting, Elsevier, vol. 30(4), pages 918-927.
    61. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de Economía.
    62. Eric A. Beutner & Yicong Lin & Andre Lucas, 2023. "Consistency, distributional convergence, and optimality of score-driven filters," Tinbergen Institute Discussion Papers 23-051/III, Tinbergen Institute.
    63. Siem Jan Koopman & Rutger Lit & André Lucas & Anne Opschoor, 2018. "Dynamic discrete copula models for high‐frequency stock price changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 966-985, November.
    64. Pawel Janus & André Lucas & Anne Opschoor & Dick J.C. van Dijk, 2014. "New HEAVY Models for Fat-Tailed Returns and Realized Covariance Kernels," Tinbergen Institute Discussion Papers 14-073/IV, Tinbergen Institute, revised 19 Aug 2015.
    65. Enzo D'Innocenzo & André Lucas & Anne Opschoor & Xingmin Zhang, 2024. "Heterogeneity and dynamics in network models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 150-173, January.
    66. Anne Opschoor & André Lucas, 2019. "Time-varying tail behavior for realized kernels," Tinbergen Institute Discussion Papers 19-051/IV, Tinbergen Institute.
    67. Francisco Blasques & Enzo D'Innocenzo & Siem Jan Koopman, 2021. "Common and Idiosyncratic Conditional Volatility Factors: Theory and Empirical Evidence," Tinbergen Institute Discussion Papers 21-057/III, Tinbergen Institute.
    68. Blazsek Szabolcs & Licht Adrian & Escribano Alvaro, 2021. "Identification of Seasonal Effects in Impulse Responses Using Score-Driven Multivariate Location Models," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 53-66, January.
    69. Sergio Contreras-Espinoza & Francisco Novoa-Muñoz & Szabolcs Blazsek & Pedro Vidal & Christian Caamaño-Carrillo, 2022. "COVID-19 Active Case Forecasts in Latin American Countries Using Score-Driven Models," Mathematics, MDPI, vol. 11(1), pages 1-17, December.
    70. Rutger-Jan Lange & Bram van Os & Dick van Dijk, 2022. "Robust Observation-Driven Models Using Proximal-Parameter Updates Abstract We propose an observation-driven modelling framework that permits time variation in the model’s parameters using a proximal-p," Tinbergen Institute Discussion Papers 22-066/III, Tinbergen Institute, revised 20 Dec 2022.
    71. Opschoor, Anne & Lucas, André, 2021. "Observation-driven models for realized variances and overnight returns applied to Value-at-Risk and Expected Shortfall forecasting," International Journal of Forecasting, Elsevier, vol. 37(2), pages 622-633.
    72. Heil, Thomas L.A. & Peter, Franziska J. & Prange, Philipp, 2022. "Measuring 25 years of global equity market co-movement using a time-varying spatial model," Journal of International Money and Finance, Elsevier, vol. 128(C).

  15. Harvey, A. & Sucarrat, G., 2012. "EGARCH models with fat tails, skewness and leverage," Cambridge Working Papers in Economics 1236, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Catania, Leopoldo & Proietti, Tommaso, 2020. "Forecasting volatility with time-varying leverage and volatility of volatility effects," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
    2. Krenar AVDULAJ & Jozef BARUNIK, 2013. "Can We Still Benefit from International Diversification? The Case of the Czech and German Stock Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 425-442, November.
    3. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    4. Javed Farrukh & Podgórski Krzysztof, 2017. "Tail Behavior and Dependence Structure in the APARCH Model," Journal of Time Series Econometrics, De Gruyter, vol. 9(2), pages 1-48, July.
    5. Anne Péguin-Feissolle & Bilel Sanhaji, 2015. "Testing the Constancy of Conditional Correlations in Multivariate GARCH-type Models (Extended Version with Appendix)," AMSE Working Papers 1516, Aix-Marseille School of Economics, France.
    6. Gaete, Michael & Herrera, Rodrigo, 2023. "Diversification benefits of commodities in portfolio allocation: A dynamic factor copula approach," Journal of Commodity Markets, Elsevier, vol. 32(C).
    7. Alexander, Carol & Lazar, Emese & Stanescu, Silvia, 2021. "Analytic moments for GJR-GARCH (1, 1) processes," International Journal of Forecasting, Elsevier, vol. 37(1), pages 105-124.
    8. Ryoko Ito, 2016. "Asymptotic Theory for Beta-t-GARCH," Cambridge Working Papers in Economics 1607, Faculty of Economics, University of Cambridge.
    9. Zhang, Guofu & Liu, Wei, 2018. "Analysis of the international propagation of contagion between oil and stock markets," Energy, Elsevier, vol. 165(PA), pages 469-486.
    10. Laurent, Sébastien & Lecourt, Christelle & Palm, Franz C., 2016. "Testing for jumps in conditionally Gaussian ARMA–GARCH models, a robust approach," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 383-400.
    11. Rangan Gupta & Chi Keung Marco Lau & Seong-Min Yoon, 2017. "OPEC News Announcement Effect on Volatility in the Crude Oil Market: A Reconsideration," Working Papers 201754, University of Pretoria, Department of Economics.
    12. Escribano, Alvaro & Sucarrat, Genaro, 2018. "Equation-by-equation estimation of multivariate periodic electricity price volatility," Energy Economics, Elsevier, vol. 74(C), pages 287-298.
    13. Szabolcs Blazsek & Luis Antonio Monteros, 2017. "Dynamic conditional score models of degrees of freedom: filtering with score-driven heavy tails," Applied Economics, Taylor & Francis Journals, vol. 49(53), pages 5426-5440, November.
    14. Tobias Eckernkemper & Bastian Gribisch, 2021. "Intraday conditional value at risk: A periodic mixed‐frequency generalized autoregressive score approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 883-910, August.
    15. De Lira Salvatierra, Irving & Patton, Andrew J., 2015. "Dynamic copula models and high frequency data," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 120-135.
    16. Michele Caivano & Andrew Harvey, 2014. "Time-series models with an EGB2 conditional distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 558-571, November.
    17. Afees A. Salisu, 2016. "Modelling Oil Price Volatility with the Beta-Skew-t-EGARCH Framework," Economics Bulletin, AccessEcon, vol. 36(3), pages 1315-1324.
    18. Michele Caivano & Andrew Harvey, 2014. "Two EGARCH models and one fat tail," Temi di discussione (Economic working papers) 954, Bank of Italy, Economic Research and International Relations Area.
    19. Sucarrat, Genaro, 2018. "The Log-GARCH Model via ARMA Representations," MPRA Paper 100386, University Library of Munich, Germany.
    20. Avdulaj, Krenar & Barunik, Jozef, 2015. "Are benefits from oil–stocks diversification gone? New evidence from a dynamic copula and high frequency data," Energy Economics, Elsevier, vol. 51(C), pages 31-44.
    21. Charles, Amélie & Darné, Olivier, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Energy Economics, Elsevier, vol. 67(C), pages 508-519.
    22. Bala A. Dahiru & Pam W. Jim & Kalu N. Nwonyuku, 2017. "Equity markets volatility dynamics in developed and newly emerging economies: EGARCH-with-skewed-t density approach," Economics Bulletin, AccessEcon, vol. 37(4), pages 2394-2412.
    23. Szabolcs Blazsek & Vicente Mendoza, 2016. "QARMA-Beta- t -EGARCH versus ARMA-GARCH: an application to S&P 500," Applied Economics, Taylor & Francis Journals, vol. 48(12), pages 1119-1129, March.
    24. Catania, Leopoldo & Grassi, Stefano, 2022. "Forecasting cryptocurrency volatility," International Journal of Forecasting, Elsevier, vol. 38(3), pages 878-894.
    25. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024.
    26. Andrew Harvey & Alessandra Luati, 2014. "Filtering With Heavy Tails," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1112-1122, September.
    27. Ekong, Christopher N. & Onye, Kenneth U., 2017. "Application of Garch Models to Estimate and Predict Financial Volatility of Daily Stock Returns in Nigeria," MPRA Paper 88309, University Library of Munich, Germany.
    28. Bernardina Algieri, 2021. "Fast & furious: Do psychological and legal factors affect commodity price volatility?," The World Economy, Wiley Blackwell, vol. 44(4), pages 980-1017, April.
    29. Ayala Astrid & Blazsek Szabolcs & Escribano Alvaro, 2023. "Anticipating extreme losses using score-driven shape filters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(4), pages 449-484, September.
    30. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Maximum Likelihood Estimation for Score-Driven Models," Tinbergen Institute Discussion Papers 14-029/III, Tinbergen Institute, revised 23 Oct 2017.
    31. Parley Ruogu Yang, 2021. "Forecasting high-frequency financial time series: an adaptive learning approach with the order book data," Papers 2103.00264, arXiv.org.
    32. Andrew Harvey & Rutger-Jan Lange, 2015. "Modeling the Interactions between Volatility and Returns," Cambridge Working Papers in Economics 1518, Faculty of Economics, University of Cambridge.
    33. Georgios Bampinas & Panagiotis Konstantinou & Theodore Panagiotidis, 2021. "Reassessing the inflation uncertainty‐inflation relationship in the tails," Bulletin of Economic Research, Wiley Blackwell, vol. 73(4), pages 508-534, October.
    34. Ito, R., 2016. "Spline-DCS for Forecasting Trade Volume in High-Frequency Finance," Cambridge Working Papers in Economics 1606, Faculty of Economics, University of Cambridge.
    35. Bram van Os, 2023. "Information-Theoretic Time-Varying Density Modeling," Tinbergen Institute Discussion Papers 23-037/III, Tinbergen Institute.
    36. Kumar SANTOSH & Meher Kumar BHARAT & Ramona BIRAU & Mircea Laurentiu SIMION & Anand ABHISHEK & Singh MANOHAR, 2023. "Quantifying Long-Term Volatility for Developed Stock Markets: An Empirical Case Study Using PGARCH Model on Toronto Stock Exchange (TSX)," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 61-68.
    37. Trottier, Denis-Alexandre & Ardia, David, 2016. "Moments of standardized Fernandez–Steel skewed distributions: Applications to the estimation of GARCH-type models," Finance Research Letters, Elsevier, vol. 18(C), pages 311-316.
    38. Hasanov, Akram Shavkatovich & Poon, Wai Ching & Al-Freedi, Ajab & Heng, Zin Yau, 2018. "Forecasting volatility in the biofuel feedstock markets in the presence of structural breaks: A comparison of alternative distribution functions," Energy Economics, Elsevier, vol. 70(C), pages 307-333.
    39. Marimoutou, Vêlayoudom & Soury, Manel, 2015. "Energy markets and CO2 emissions: Analysis by stochastic copula autoregressive model," Energy, Elsevier, vol. 88(C), pages 417-429.
    40. Tata Subba Rao & Granville Tunnicliffe Wilson & Andrew Harvey & Rutger-Jan Lange, 2017. "Volatility Modeling with a Generalized t Distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(2), pages 175-190, March.
    41. Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Measuring Success: Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers 11-19, Association Française de Cliométrie (AFC).
    42. Fernanda Maria Müller & Fábio M Bayer, 2017. "Improved two-component tests in Beta-Skew-t-EGARCH models," Economics Bulletin, AccessEcon, vol. 37(4), pages 2364-2373.
    43. Fatih Kazova & Ayça Büyükyılmaz Ercan, 2021. "Comparative Analysis of the Volatility Structure of Cryptocurrencies," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(35), pages 33-57, December.
    44. Song, Shijia & Tian, Fei & Li, Handong, 2021. "An intraday-return-based Value-at-Risk model driven by dynamic conditional score with censored generalized Pareto distribution," Journal of Asian Economics, Elsevier, vol. 74(C).
    45. Tranberg, Bo & Hansen, Rasmus Thrane & Catania, Leopoldo, 2020. "Managing volumetric risk of long-term power purchase agreements," Energy Economics, Elsevier, vol. 85(C).
    46. Vêlayoudom Marimoutou & Manel Soury, 2015. "Energy Markets and CO2 Emissions: Analysis by Stochastic Copula Autoregressive Model," AMSE Working Papers 1520, Aix-Marseille School of Economics, France.
    47. Gao, Yang & Li, Yangyang & Zhao, Chengjie & Wang, Yaojun, 2022. "Risk spillover analysis across worldwide ESG stock markets: New evidence from the frequency-domain," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    48. Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Memory that Drives! New Insights into Forecasting Performance of Stock Prices from SEMIFARMA-AEGAS Model," Working Papers of BETA 2019-24, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    49. Virbickaite, Audrone & Nguyen, Hoang & Tran, Minh-Ngoc, 2023. "Bayesian Predictive Distributions of Oil Returns Using Mixed Data Sampling Volatility Models," Working Papers 2023:7, Örebro University, School of Business.
    50. Deniz Erer, 2023. "The Impact of News Related Covid-19 on Exchange Rate Volatility:A New Evidence From Generalized Autoregressive Score Model," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(38), pages 105-126, June.
    51. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    52. Hong Shaopeng, 2020. "Generalized Autoregressive Score asymmetric Laplace Distribution and Extreme Downward Risk Prediction," Papers 2008.01277, arXiv.org, revised Oct 2020.
    53. Roy Cerqueti & Massimiliano Giacalone & Raffaele Mattera, 2020. "Skewed non-Gaussian GARCH models for cryptocurrencies volatility modelling," Papers 2004.11674, arXiv.org.
    54. Yang, Lu & Hamori, Shigeyuki, 2021. "The role of the carbon market in relation to the cryptocurrency market: Only diversification or more?," International Review of Financial Analysis, Elsevier, vol. 77(C).
    55. Bharat Kumar Meher & Iqbal Thonse Hawaldar & Latasha Mohapatra & Adel M. Sarea, 2020. "The Impact of COVID-19 on Price Volatility of Crude Oil and Natural Gas Listed on Multi Commodity Exchange of India," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 422-431.
    56. Gao, Chun-Ting & Zhou, Xiao-Hua, 2016. "Forecasting VaR and ES using dynamic conditional score models and skew Student distribution," Economic Modelling, Elsevier, vol. 53(C), pages 216-223.
    57. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
    58. Stephen Thiele, 2020. "Modeling the conditional distribution of financial returns with asymmetric tails," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 46-60, January.
    59. Astrid Ayala & Szabolcs Blazsek, 2018. "Equity market neutral hedge funds and the stock market: an application of score-driven copula models," Applied Economics, Taylor & Francis Journals, vol. 50(37), pages 4005-4023, August.
    60. Mauro Bernardi & Leopoldo Catania, 2016. "Comparison of Value-at-Risk models using the MCS approach," Computational Statistics, Springer, vol. 31(2), pages 579-608, June.
    61. Szabolcs Blazsek & Han-Chiang Ho, 2017. "Markov regime-switching Beta--EGARCH," Applied Economics, Taylor & Francis Journals, vol. 49(47), pages 4793-4805, October.
    62. Szabolcs Blazsek & Marco Villatoro, 2015. "Is Beta- t -EGARCH(1,1) superior to GARCH(1,1)?," Applied Economics, Taylor & Francis Journals, vol. 47(17), pages 1764-1774, April.
    63. Song, Shijia & Li, Handong, 2022. "Predicting VaR for China's stock market: A score-driven model based on normal inverse Gaussian distribution," International Review of Financial Analysis, Elsevier, vol. 82(C).
    64. Alanya-Beltran Willy, 2023. "Modelling volatility dependence with score copula models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(5), pages 649-668, December.
    65. Mohamed CHIKHI & Claude DIEBOLT & Tapas MISHRA, 2019. "Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers of BETA 2019-43, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    66. Christian Francq & Olivier Wintenberger & Jean-Michel Zakoïan, 2018. "Goodness-of-fit tests for Log-GARCH and EGARCH models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(1), pages 27-51, March.
    67. Shijia Song & Handong Li, 2023. "A new model for forecasting VaR and ES using intraday returns aggregation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1039-1054, August.
    68. Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.
    69. Alanya-Beltran, Willy, 2022. "Modelling stock returns volatility with dynamic conditional score models and random shifts," Finance Research Letters, Elsevier, vol. 45(C).
    70. Sonia Benito Muela & Carmen López-Martín & Mª Ángeles Navarro, 2017. "The Role of the Skewed Distributions in the Framework of Extreme Value Theory (EVT)," International Business Research, Canadian Center of Science and Education, vol. 10(11), pages 88-102, November.
    71. Yacouba Boubacar Maïnassara & Othman Kadmiri & Bruno Saussereau, 2022. "Portmanteau test for the asymmetric power GARCH model when the power is unknown," Statistical Papers, Springer, vol. 63(3), pages 755-793, June.
    72. Gao, Yang & Li, Yangyang & Wang, Yaojun, 2021. "Risk spillover and network connectedness analysis of China’s green bond and financial markets: Evidence from financial events of 2015–2020," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    73. Andrew Harvey & Rutger‐Jan Lange, 2018. "Modeling the Interactions between Volatility and Returns using EGARCH‐M," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 909-919, November.
    74. Yingying Xu & Donald Lien, 2022. "Forecasting volatilities of oil and gas assets: A comparison of GAS, GARCH, and EGARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 259-278, March.
    75. David Ardia & Kris Boudt & Leopoldo Catania, 2016. "Generalized Autoregressive Score Models in R: The GAS Package," Papers 1609.02354, arXiv.org.
    76. Vêlayoudom Marimoutou & Manel Soury, 2015. "Energy Markets and CO2 Emissions: Analysis by Stochastic Copula Autoregressive Model," Working Papers halshs-01148746, HAL.

  16. Andres, P. & Harvey, A., 2012. "The Dyanamic Location/Scale Model: with applications to intra-day financial data," Cambridge Working Papers in Economics 1240, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Adam Clements & Joanne Fuller & Vasilios Papalexiou, 2015. "Public news flow in intraday component models for trading activity and volatility," NCER Working Paper Series 106, National Centre for Econometric Research.
    2. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Maximum Likelihood Estimation for Score-Driven Models," Tinbergen Institute Discussion Papers 14-029/III, Tinbergen Institute, revised 23 Oct 2017.
    3. Parley Ruogu Yang, 2021. "Forecasting high-frequency financial time series: an adaptive learning approach with the order book data," Papers 2103.00264, arXiv.org.
    4. Ng, Kok Haur & Peiris, Shelton & Chan, Jennifer So-kuen & Allen, David & Ng, Kooi Huat, 2017. "Efficient modelling and forecasting with range based volatility models and its application," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 448-460.
    5. Andres, Philipp, 2014. "Maximum likelihood estimates for positive valued dynamic score models; The DySco package," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 34-42.
    6. Ito, Ryoko, 2013. "Modeling Dynamic Diurnal Patterns in High-Frequency Financial Data," Cambridge Working Papers in Economics 1315, Faculty of Economics, University of Cambridge.
    7. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Chasing volatility - A persistent multiplicative error model with jumps," CREATES Research Papers 2014-29, Department of Economics and Business Economics, Aarhus University.

  17. Harvey, A., 2010. "Exponential Conditional Volatility Models," Cambridge Working Papers in Economics 1040, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Igor L. Kheifets, 2015. "Specification tests for nonlinear dynamic models," Econometrics Journal, Royal Economic Society, vol. 18(1), pages 67-94, February.
    2. Xin Zhang & Bernd Schwaab & Andre Lucas, 2011. "Conditional Probabilities and Contagion Measures for Euro Area Sovereign Default Risk," Tinbergen Institute Discussion Papers 11-176/2/DSF29, Tinbergen Institute, revised 28 Jun 2012.
    3. Schwaab, Bernd & Lucas, André & Zhang, Xin, 2013. "Conditional and joint credit risk," Working Paper Series 1621, European Central Bank.
    4. Andrew Harvey & Alessandra Luati, 2014. "Filtering With Heavy Tails," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1112-1122, September.
    5. Tommaso, Proietti & Alessandra, Luati, 2012. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," MPRA Paper 39600, University Library of Munich, Germany.
    6. Andres, P. & Harvey, A., 2012. "The Dyanamic Location/Scale Model: with applications to intra-day financial data," Cambridge Working Papers in Economics 1240, Faculty of Economics, University of Cambridge.
    7. Wintenberger, Olivier & Cai, Sixiang, 2011. "Parametric inference and forecasting in continuously invertible volatility models," MPRA Paper 31767, University Library of Munich, Germany.
    8. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2013. "Conditional euro area sovereign default risk," Working Paper Series 269, Sveriges Riksbank (Central Bank of Sweden).

  18. Harvey, A., 2008. "Dynamic distributions and changing copulas," Cambridge Working Papers in Economics 0839, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Henry Penikas, 2016. "Copula-Based Univariate Time Series Structural Shift Identification Test," Papers 1609.05056, arXiv.org.
    2. Busetti, F. & Harvey, A., 2008. "When is a copula constant? A test for changing relationships," Cambridge Working Papers in Economics 0841, Faculty of Economics, University of Cambridge.
    3. Harvey, Andrew, 2010. "Tracking a changing copula," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 485-500, June.

  19. Busetti, F. & Harvey, A., 2008. "When is a copula constant? A test for changing relationships," Cambridge Working Papers in Economics 0841, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Benos, Nikos & Stavrakoudis, Athanassios, 2020. "Okun's Law: Copula-based Evidence from G7 Countries," MPRA Paper 103318, University Library of Munich, Germany.
    2. Dimitrios Panagiotou & Athanassios Stavrakoudis, 2023. "Price dependence among the major EU extra virgin olive oil markets: a time scale analysis," Review of Agricultural, Food and Environmental Studies, Springer, vol. 104(1), pages 1-26, March.
    3. Harvey, A., 2008. "Dynamic distributions and changing copulas," Cambridge Working Papers in Economics 0839, Faculty of Economics, University of Cambridge.
    4. Fousekis, Panos & Grigoriadis, Vasilis, 2017. "Price co-movement and the crack spread in the US futures markets," Journal of Commodity Markets, Elsevier, vol. 7(C), pages 57-71.
    5. Dungey, Mardi & Flavin, Thomas J. & Lagoa-Varela, Dolores, 2020. "Are banking shocks contagious? Evidence from the eurozone," Journal of Banking & Finance, Elsevier, vol. 112(C).
    6. Ji, Qiang & Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Risk spillover between energy and agricultural commodity markets: A dependence-switching CoVaR-copula model," Energy Economics, Elsevier, vol. 75(C), pages 14-27.
    7. Dungey, Mardi & Gajurel, Dinesh, 2014. "Equity market contagion during the global financial crisis: Evidence from the world's eight largest economies," Economic Systems, Elsevier, vol. 38(2), pages 161-177.
    8. Chollete, Loran & Pena, Victor de la & Lu, Ching-Chih, 2009. "International Diversification: A Copula Approach," UiS Working Papers in Economics and Finance 2009/27, University of Stavanger.
    9. Dungey, Mardi & Harvey, John & Volkov, Vladimir, 2017. "The changing international network of sovereign debt and financial institutions," Working Papers 2017-04, University of Tasmania, Tasmanian School of Business and Economics.
    10. Renée Fry-McKibbin & Vance Martin & Chrismin Tang, 2013. "Financial Contagion and Asset Pricing," CAMA Working Papers 2013-61, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    11. Yangguang Zhu & Feng Yang & Wuyi Ye, 2018. "Financial contagion behavior analysis based on complex network approach," Annals of Operations Research, Springer, vol. 268(1), pages 93-111, September.
    12. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024.
    13. Zhu, Bo & Lin, Renda & Deng, Yuanyue & Chen, Pingshe & Chevallier, Julien, 2021. "Intersectoral systemic risk spillovers between energy and agriculture under the financial and COVID-19 crises," Economic Modelling, Elsevier, vol. 105(C).
    14. Mensi, Walid & Selmi, Refk & Al-Yahyaee, Khamis Hamed, 2020. "Switching dependence and systemic risk between crude oil and U.S. Islamic and conventional equity markets: A new evidence," Resources Policy, Elsevier, vol. 69(C).
    15. Dungey, Mardi & Matei, Marius & Treepongkaruna, Sirimon, 2014. "Identifying periods of financial stress in Asian currencies: the role of high frequency financial market data," Working Papers 2014-12, University of Tasmania, Tasmanian School of Business and Economics.
    16. Mardi Dungey & Eric Renault, 2018. "Identifying contagion," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(2), pages 227-250, March.
    17. Wenying Yao & Mardi Dungey & Vitali Alexeev, 2020. "Modelling Financial Contagion Using High Frequency Data," The Economic Record, The Economic Society of Australia, vol. 96(314), pages 314-330, September.
    18. Chevapatrakul, Thanaset & Tee, Kai-Hong, 2014. "The effects of news events on market contagion: Evidence from the 2007–2009 financial crisis," Research in International Business and Finance, Elsevier, vol. 32(C), pages 83-105.
    19. Mardi Dungey & Jet Holloway & Abdullah Yalaman & Wenying Yao, 2022. "Characterizing financial crises using high-frequency data," Quantitative Finance, Taylor & Francis Journals, vol. 22(4), pages 743-760, April.
    20. S Zhang & I Paya & D Peel, 2009. "Linkages between Shanghai and Hong Kong stock indices," Working Papers 599248, Lancaster University Management School, Economics Department.
    21. Cathy Q. Ning & Loran Chollete, 2009. "The Dependence Structure of Macroeconomic Variables in the US," Working Papers 005, Ryerson University, Department of Economics.
    22. Panagiotou, Dimitrios & Stavrakoudis, Athanassios, 2017. "Vertical price relationships between different cuts and quality grades in the U.S. beef marketing channel: A wholesale-retail analysis," The Journal of Economic Asymmetries, Elsevier, vol. 16(C), pages 53-63.
    23. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    24. Okyoung Na & Jiyeon Lee & Sangyeol Lee, 2013. "Change point detection in SCOMDY models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(3), pages 215-238, July.
    25. Bücher, Axel & Jäschke, Stefan & Wied, Dominik, 2015. "Nonparametric tests for constant tail dependence with an application to energy and finance," Journal of Econometrics, Elsevier, vol. 187(1), pages 154-168.
    26. Krämer, Walter & van Kampen, Maarten, 2011. "A simple nonparametric test for structural change in joint tail probabilities," Economics Letters, Elsevier, vol. 110(3), pages 245-247, March.
    27. Renée Fry-McKibbin & Cody Yu-Ling Hsiao & Vance L. Martin, 2017. "Joint tests of contagion with applications to financial crises," CAMA Working Papers 2017-65, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    28. Renée Fry-McKibbin & Cody Yu-Ling Hsiao, 2015. "Extremal dependence tests for contagion," CAMA Working Papers 2015-40, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    29. Liu, Xiaochun, 2015. "Modeling time-varying skewness via decomposition for out-of-sample forecast," International Journal of Forecasting, Elsevier, vol. 31(2), pages 296-311.
    30. Hee Soo Lee & Tae Yoon Kim, 2022. "A new analytical approach for identifying market contagion," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-35, December.
    31. Selmi, Refk & Hammoudeh, Shawkat & Kasmaoui, Kamal & Sousa, Ricardo M. & Errami, Youssef, 2022. "The dual shocks of the COVID-19 and the oil price collapse: A spark or a setback for the circular economy?," Energy Economics, Elsevier, vol. 109(C).
    32. Wang, Yi-Chiuan & Wu, Jyh-Lin & Lai, Yi-Hao, 2013. "A revisit to the dependence structure between the stock and foreign exchange markets: A dependence-switching copula approach," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1706-1719.
    33. Panagiotpu, Dimitrios & Stavrakoudis, Athanassios, 2021. "Price dependence among the major EU extra virgin olive oil markets: A time scale analysis," MPRA Paper 114656, University Library of Munich, Germany, revised Jun 2022.
    34. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    35. Thanaset Chevapatrakul & Kai-Hong Tee, 2014. "The Effects of News Events on Market Contagion: Evidence from the 2007-2009 Financial Crisis," Discussion Papers 2014/08, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
    36. Li, Fuchun & Zhu, Hui, 2014. "Testing for financial contagion based on a nonparametric measure of the cross-market correlation," Review of Financial Economics, Elsevier, vol. 23(3), pages 141-147.
    37. Chollete, Lorán & de la Peña, Victor & Lu, Ching-Chih, 2011. "International diversification: A copula approach," Journal of Banking & Finance, Elsevier, vol. 35(2), pages 403-417, February.
    38. Jin Xisong & Lehnert Thorsten, 2018. "Large portfolio risk management and optimal portfolio allocation with dynamic elliptical copulas," Dependence Modeling, De Gruyter, vol. 6(1), pages 19-46, February.
    39. Harvey, Andrew, 2010. "Tracking a changing copula," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 485-500, June.
    40. Atskanov, Isuf, 2015. "Dynamic optimization of an investment portfolio on European stock markets using pair copulas," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 40(4), pages 84-105.
    41. Fabio Busetti, 2012. "On detecting end-of-sample instabilities," Temi di discussione (Economic working papers) 881, Bank of Italy, Economic Research and International Relations Area.
    42. Stavrakoudis, Athanassios & Panagiotou, Dimitrios, 2016. "Price dependence and asymmetric responses between coffee varieties," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 17(2), June.
    43. Fousekis, Panos & Grigoriadis, Vasilis, 2016. "Spatial price dependence by time scale: Empirical evidence from the international butter markets," Economic Modelling, Elsevier, vol. 54(C), pages 195-204.
    44. Wied, Dominik & Dehling, Herold & van Kampen, Maarten & Vogel, Daniel, 2014. "A fluctuation test for constant Spearman’s rho with nuisance-free limit distribution," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 723-736.
    45. Tim Kutzker & Florian Stark & Dominik Wied, 2021. "Testing for relevant dependence change in financial data: a CUSUM copula approach," Empirical Economics, Springer, vol. 60(4), pages 1875-1894, April.
    46. Chollete, Loran & Ning, Cathy, 2010. "Asymmetric Dependence in US Financial Risk Factors?," UiS Working Papers in Economics and Finance 2011/2, University of Stavanger.
    47. Rezitis, Anthony N. & Rokopanos, Andreas & Tsionas, Mike G., 2021. "Investigating dynamic price co-movements in the international milk market using copulas: The role of trade agreements," Economic Modelling, Elsevier, vol. 95(C), pages 215-227.
    48. Selmi, Refk & Wohar, Mark & Deisting, Florent & Kasmaoui, Kamal, 2023. "Dynamic inflation hedging performance and downside risk: A comparison between Islamic and conventional stock indices," The Quarterly Review of Economics and Finance, Elsevier, vol. 91(C), pages 56-67.

  20. Harvey, A., 2008. "Modeling the Phillips curve with unobserved components," Cambridge Working Papers in Economics 0805, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Macchiarelli, Corrado, 2011. "Bond market co-movements, expected inflation and the equilibrium real exchange rate," Working Paper Series 1405, European Central Bank.
    2. Mallick, Debdulal, 2014. "A Spectral Representation of the Phillips Curve in Australia," MPRA Paper 59794, University Library of Munich, Germany.
    3. Basistha, Arabinda & Kurov, Alexander, 2010. "Estimating earnings trend using unobserved components framework," Economics Letters, Elsevier, vol. 107(1), pages 55-57, April.
    4. Panovska, Irina & Ramamurthy, Srikanth, 2022. "Decomposing the output gap with inflation learning," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).
    5. James McNeil & Gregor W. Smith, 2023. "The All‐Gap Phillips Curve," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(2), pages 269-282, April.
    6. Paradiso, Antonio & Rao, B. Bhaskara, 2011. "Flattening of the Phillips Curve and the Role of Oil Price: An Unobserved Components Model for the USA and Australia," MPRA Paper 29606, University Library of Munich, Germany.
    7. Antonio Paradiso & Saten Kumar & B. Bhaskara Rao, 2013. "A New Keynesian IS curve for Australia: is it forward looking or backward looking?," Applied Economics, Taylor & Francis Journals, vol. 45(26), pages 3691-3700, September.
    8. Luca Agnello & Vítor Castro & Ricardo M. Sousa, 2023. "Interest rate gaps in an uncertain global context: why “too” low (high) for “so” long?," Empirical Economics, Springer, vol. 64(2), pages 539-565, February.
    9. Winkelried, Diego, 2023. "Simple interpolations of inflation expectations," Economics Letters, Elsevier, vol. 229(C).
    10. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024.
    11. Kajuth Florian, 2016. "NAIRU Estimates for Germany: New Evidence on the Inflation–Unemployment Tradeoff," German Economic Review, De Gruyter, vol. 17(1), pages 104-125, February.
    12. Ivan Mendieta-Munoz & Mengheng Li, 2019. "The Multivariate Simultaneous Unobserved Compenents Model and Identification via Heteroskedasticity," Working Paper Series, Department of Economics, University of Utah 2019_06, University of Utah, Department of Economics.
    13. Kajuth, Florian, 2012. "Identifying the Phillips curve through shifts in volatility," Journal of Macroeconomics, Elsevier, vol. 34(4), pages 975-991.
    14. Mengheng Li & Irma Hindrayanto, 2018. "Looking for the stars: Estimating the natural rate of interest," Working Paper Series 51, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    15. Tallman, Ellis W. & Zaman, Saeed, 2017. "Forecasting inflation: Phillips curve effects on services price measures," International Journal of Forecasting, Elsevier, vol. 33(2), pages 442-457.
    16. Fabio Busetti & Michele Caivano, 2013. "The trend-cycle decomposition of output and the Phillips curve: Bayesian estimates for Italy," Temi di discussione (Economic working papers) 941, Bank of Italy, Economic Research and International Relations Area.
    17. Mohammad Naim Azimi, 2016. "Drawing on Phillips curve: does the inverse relation between inflation and unemployment persist in transitional economies," International Journal of Economics and Accounting, Inderscience Enterprises Ltd, vol. 7(2), pages 89-100.
    18. Hindrayanto, Irma & Samarina, Anna & Stanga, Irina M., 2019. "Is the Phillips curve still alive? Evidence from the euro area," Economics Letters, Elsevier, vol. 174(C), pages 149-152.
    19. Mallick, Debdulal, 2019. "Policy regimes and the shape of the Phillips curve in Australia," Journal of Policy Modeling, Elsevier, vol. 41(6), pages 1077-1094.
    20. Mengheng Li & Siem Jan Koopman, 2021. "Unobserved components with stochastic volatility: Simulation‐based estimation and signal extraction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 614-627, August.
    21. Altug, Sumru & Çakmaklı, Cem, 2015. "Forecasting Inflation using Survey Expectations and Target Inflation: Evidence for Brazil and Turkey," CEPR Discussion Papers 10419, C.E.P.R. Discussion Papers.
    22. Sumru Altug & Cem Cakmakli, 2014. "Inflation Targeting and Inflation Expectations: Evidence for Brazil and Turkey," Koç University-TUSIAD Economic Research Forum Working Papers 1413, Koc University-TUSIAD Economic Research Forum.
    23. Byron J. Idrovo-Aguirre & Javier E. Contreras-Reyes, 2019. "Backcasting cement production and characterizing cement’s economic cycles for Chile 1991–2015," Empirical Economics, Springer, vol. 57(5), pages 1829-1852, November.
    24. Pym Manopimoke, 2012. "Hong Kong Inflation Dynamics: Trend and Cycle Relationships with the U.S. and China," Working Papers 232012, Hong Kong Institute for Monetary Research.
    25. Kavtaradze, Lasha, 2014. "Inflation Dynamics in Georgia," MPRA Paper 59966, University Library of Munich, Germany.
    26. Fabio Busetti & Michele Caivano, 2016. "The trend–cycle decomposition of output and the Phillips curve: Bayesian estimates for Italy and the Euro area," Empirical Economics, Springer, vol. 50(4), pages 1565-1587, June.
    27. De la Serve, M-E. & Lemoine, M., 2011. "Measuring the NAIRU: a complementary approach," Working papers 342, Banque de France.
    28. Alicia N. Rambaldi & Ryan R. J. McAllister & Cameron S. Fletcher, 2015. "Decoupling land values in residential property prices: smoothing methods for hedonic imputed price indices," Discussion Papers Series 549, School of Economics, University of Queensland, Australia.
    29. Lena Vogel, 2008. "The Relationship between the Hybrid New Keynesian Phillips Curve and the NAIRU over Time," Macroeconomics and Finance Series 200803, University of Hamburg, Department of Socioeconomics.
    30. Idrovo Aguirre, Byron & Contreras, Javier, 2015. "Back-splicing of cement production and characterization of its economic cycle: The case of Chile (1991-2015)," MPRA Paper 67387, University Library of Munich, Germany, revised 20 Sep 2015.

  21. Busettti, F. & Harvey, A., 2007. "Tests of time-invariance," Cambridge Working Papers in Economics 0657, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Harvey, A., 2008. "Dynamic distributions and changing copulas," Cambridge Working Papers in Economics 0839, Faculty of Economics, University of Cambridge.
    2. Busetti, F. & Harvey, A., 2008. "When is a copula constant? A test for changing relationships," Cambridge Working Papers in Economics 0841, Faculty of Economics, University of Cambridge.
    3. Chevapatrakul, Thanaset & Tee, Kai-Hong, 2014. "The effects of news events on market contagion: Evidence from the 2007–2009 financial crisis," Research in International Business and Finance, Elsevier, vol. 32(C), pages 83-105.
    4. DeRossi, G. & Harvey, A., 2007. "Quantiles, Expectiles and Splines," Cambridge Working Papers in Economics 0660, Faculty of Economics, University of Cambridge.
    5. Thanaset Chevapatrakul & Kai-Hong Tee, 2014. "The Effects of News Events on Market Contagion: Evidence from the 2007-2009 Financial Crisis," Discussion Papers 2014/08, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).

  22. Fabio Busetti & Andrew Harvey, 2007. "Testing for trend," Temi di discussione (Economic working papers) 614, Bank of Italy, Economic Research and International Relations Area.

    Cited by:

    1. Gomez Zaldivar, M. & Ventosa-Santaularia, D., 2009. "Bilateral Relationship between Consumption and GDP in Mexico and the USA: A Comment," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 9(1).
    2. Shelley, Gary L. & Wallace, Frederick H., 2011. "Further evidence regarding nonlinear trend reversion of real GDP and the CPI," Economics Letters, Elsevier, vol. 112(1), pages 56-59, July.
    3. Cavaliere, Giuseppe & Taylor, A.M. Robert, 2008. "Testing for a change in persistence in the presence of non-stationary volatility," Journal of Econometrics, Elsevier, vol. 147(1), pages 84-98, November.
    4. Denis Kwiatkowski & Peter C.B. Phillips & Peter Schmidt, 1991. "Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root?," Cowles Foundation Discussion Papers 979, Cowles Foundation for Research in Economics, Yale University.
    5. Giuseppe Cavaliere & David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2009. "Testing for unit roots in the presence of a possible break in trend and non-stationary volatility," Discussion Papers 09/05, University of Nottingham, Granger Centre for Time Series Econometrics.
    6. Anton Skrobotov, 2015. "Trend and Initial Condition in Stationarity Tests: The Asymptotic Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(2), pages 254-273, April.
    7. Jushan Bai & Serena Ng, 2001. "A New Look at Panel Testing of Stationarity and the PPP Hypothesis," Boston College Working Papers in Economics 518, Boston College Department of Economics.
    8. Josep Lluís Carrion-i-Silvestre & Dukpa Kim & Pierre Perron, 2007. "GLS-based unit root tests with multiple structural breaks both under the null and the alternative hypotheses," Boston University - Department of Economics - Working Papers Series wp2008-019, Boston University - Department of Economics.
    9. Sauro Mocetti, 2008. "Educational choices and the selection process before and after compulsory schooling," Temi di discussione (Economic working papers) 691, Bank of Italy, Economic Research and International Relations Area.
    10. Reitz, Stefan & Ruelke, Jan C. & Taylor, Mark P., 2010. "On the nonlinear influence of Reserve Bank of Australia interventions on exchange rates," Discussion Paper Series 1: Economic Studies 2010,08, Deutsche Bundesbank.
    11. Anton Skrobotov, 2016. "On Trend Breaks and Initial Condition in Unit Root Testing," Working Papers 0097, Gaidar Institute for Economic Policy, revised 2016.
    12. Gadea Rivas, María Dolores & Gonzalo, Jesús, 2020. "Trends in distributional characteristics: Existence of global warming," Journal of Econometrics, Elsevier, vol. 214(1), pages 153-174.
    13. Peter C.B. Phillips & Tassos Magdalinos, 2008. "Unit Root and Cointegrating Limit Theory When Initialization Is in the Infinite Past," Cowles Foundation Discussion Papers 1655, Cowles Foundation for Research in Economics, Yale University.
    14. María Dolores Gadea Rivas & Jesús Gonzalo, 2022. "A tale of three cities: climate heterogeneity," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 475-511, May.
    15. James Morley & Tara M. Sinclair, 2005. "Testing for Stationarity and Cointegration in an Unobserved Components Framework," Computing in Economics and Finance 2005 451, Society for Computational Economics.
    16. Riccardo Corradini, 2005. "An Empirical Analysis of Permanent Income Hypothesis Applied to Italy using State Space Models with non zero correlation between trend and cycle," Econometrics 0509009, University Library of Munich, Germany.
    17. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2008. "Testing for unit roots in the presence of uncertainty over both the trend and initial condition," Discussion Papers 08/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    18. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2008. "Testing for unit roots and the impact of quadratic trends, with an application to relative primary commodity prices," Discussion Papers 08/04, University of Nottingham, Granger Centre for Time Series Econometrics.
    19. Nikolaos Giannellis & Minoas Koukouritakis, 2011. "Behavioural equilibrium exchange rate and total misalignment: evidence from the euro exchange rate," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 38(4), pages 555-578, November.
    20. Josep Carrion-i-Silvestre & Andreu Sansó, 2006. "A guide to the computation of stationarity tests," Empirical Economics, Springer, vol. 31(2), pages 433-448, June.
    21. David I. Harvey, & Stephen J. Leybourne, & A. M. Robert Taylor, 2007. "Testing for a unit root when uncertain about the trend [Revised to become 07/03 above]," Discussion Papers 06/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    22. María Presno & Anna López, 2003. "Testing for stationarity in series with a shift in the mean. A fredholm approach," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 12(1), pages 195-213, June.
    23. Westerlund, Joakim & Edgerton , David, 2006. "New Improved Tests for Cointegration with Structural Breaks," Working Papers 2006:3, Lund University, Department of Economics.
    24. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2007. "Unit root testing in practice: dealing with uncertainty over the trend and initial condition," Discussion Papers 07/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    25. Jushan Bai; Josep Lluís Carrion-i-Silvestre, 2004. "Structural changes, common stochastic trends and unit roots in panel data," Econometric Society 2004 North American Summer Meetings 345, Econometric Society.
    26. Fabio Busetti & Lorenzo Forni & Andrew Harvey & Fabrizio Venditti, 2007. "Inflation Convergence and Divergence within the European Monetary Union," International Journal of Central Banking, International Journal of Central Banking, vol. 3(2), pages 95-121, June.
    27. Josep Lluís Carrion-i-Silvestre & Andreu Sansó, 2005. "The KPSS Test with Two Structural Breaks," DEA Working Papers 13, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    28. Chevillon, Guillaume, 2012. "Local-Explosive Approximations to Null Distributions of the Johansen Cointegration Test, with an Application to Cyclical Concordance in the Euro Area," ESSEC Working Papers WP1210, ESSEC Research Center, ESSEC Business School.
    29. Josep Lluis Carrion Silvestre & Tomas del Barrio Castro & Enrique Lopez Bazo, 2003. "Breaking the panels. An application to the GDP per capita," Working Papers in Economics 97, Universitat de Barcelona. Espai de Recerca en Economia.
    30. Skrobotov, Anton (Скроботов, Антон), 2015. "About Trend, the Shift and the Initial Value in Testing of the Hypothesis of a Unit Root [О Тренде, Сдвиге И Начальном Значении В Тестировании Гипотезы О Наличии Единичного Корня]," Published Papers mak6, Russian Presidential Academy of National Economy and Public Administration.
    31. James H. Stock & Mark W. Watson, 1996. "Asymptotically Median Unbiased Estimation of Coefficient Variance in a Time Varying Parameter Model," NBER Technical Working Papers 0201, National Bureau of Economic Research, Inc.
    32. Chevillon, Guillaume, 2007. "Inference in the Presence of Stochastic and Deterministic Trends," ESSEC Working Papers DR 07021, ESSEC Research Center, ESSEC Business School.
    33. Chevillon, Guillaume, 2017. "Robustness of Multistep Forecasts and Predictive Regressions at Intermediate and Long Horizons," ESSEC Working Papers WP1710, ESSEC Research Center, ESSEC Business School.
    34. Xu, Ke-Li, 2016. "Multivariate trend function testing with mixed stationary and integrated disturbances," Journal of Multivariate Analysis, Elsevier, vol. 147(C), pages 38-57.

  23. DeRossi, G. & Harvey, A., 2007. "Quantiles, Expectiles and Splines," Cambridge Working Papers in Economics 0660, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Xiu Xu & Andrija Mihoci & Wolfgang Karl Hardle, 2020. "lCARE -- localizing Conditional AutoRegressive Expectiles," Papers 2009.13215, arXiv.org.
    2. Luciano Stefanini & Maria Letizia Guerra, 2016. "On Possibilistic Representations of Fuzzy Intervals," Working Papers 1602, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2016.
    3. Tobias Adrian & Markus K. Brunnermeier, 2008. "CoVaR," Staff Reports 348, Federal Reserve Bank of New York.
      • Tobias Adrian & Markus K. Brunnermeier, 2016. "CoVaR," American Economic Review, American Economic Association, vol. 106(7), pages 1705-1741, July.
      • Tobias Adrian & Markus K. Brunnermeier, 2011. "CoVaR," NBER Working Papers 17454, National Bureau of Economic Research, Inc.
    4. Harvey, A., 2008. "Dynamic distributions and changing copulas," Cambridge Working Papers in Economics 0839, Faculty of Economics, University of Cambridge.
    5. Patrick Schmidt & Matthias Katzfuss & Tilmann Gneiting, 2021. "Interpretation of point forecasts with unknown directive," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 728-743, September.
    6. Jakobsons Edgars, 2016. "Scenario aggregation method for portfolio expectile optimization," Statistics & Risk Modeling, De Gruyter, vol. 33(1-2), pages 51-65, September.
    7. Abdelaati Daouia & Stéphane Girard & Gilles Stupfler, 2018. "Estimation of tail risk based on extreme expectiles," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 80(2), pages 263-292, March.
    8. Luciano Stefanini, 2015. "Quantile and expectile smoothing by F-transform," Working Papers 1512, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2015.
    9. Chollete, Loran & Pena, Victor de la & Lu, Ching-Chih, 2009. "International Diversification: A Copula Approach," UiS Working Papers in Economics and Finance 2009/27, University of Stavanger.
    10. Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2018. "lCARE - localizing conditional autoregressive expectiles," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 198-220.
    11. Chan, Ngai Hang & Sit, Tony, 2016. "Artifactual unit root behavior of Value at risk (VaR)," Statistics & Probability Letters, Elsevier, vol. 116(C), pages 88-93.
    12. Chollete, Lorán & de la Peña, Victor & Lu, Ching-Chih, 2012. "International diversification: An extreme value approach," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 871-885.
    13. Busetti, F. & Harvey, A., 2008. "When is a copula constant? A test for changing relationships," Cambridge Working Papers in Economics 0841, Faculty of Economics, University of Cambridge.
    14. Fabio Busetti & Michele Caivano & Davide Delle Monache, 2019. "Domestic and global determinants of inflation: evidence from expectile regression," Temi di discussione (Economic working papers) 1225, Bank of Italy, Economic Research and International Relations Area.
    15. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024.
    16. P. Burdejova & W.K. Härdle & Kokoszka & Q.Xiong, 2015. "Change point and trend analyses of annual expectile curves of tropical storms," SFB 649 Discussion Papers SFB649DP2015-029, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    17. Daouia, Abdelaati & Paindaveine, Davy, 2019. "Multivariate Expectiles, Expectile Depth and Multiple-Output Expectile Regression," TSE Working Papers 19-1022, Toulouse School of Economics (TSE), revised Feb 2023.
    18. Bellini, Fabio & Klar, Bernhard & Müller, Alfred & Rosazza Gianin, Emanuela, 2014. "Generalized quantiles as risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 54(C), pages 41-48.
    19. Antonio Rubia Serrano & Lidia Sanchis-Marco, 2015. "Measuring Tail-Risk Cross-Country Exposures in the Banking Industry," Working Papers. Serie AD 2015-01, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    20. Bruzda, Joanna, 2019. "Quantile smoothing in supply chain and logistics forecasting," International Journal of Production Economics, Elsevier, vol. 208(C), pages 122-139.
    21. Dai, Sheng & Kuosmanen, Timo & Zhou, Xun, 2023. "Generalized quantile and expectile properties for shape constrained nonparametric estimation," European Journal of Operational Research, Elsevier, vol. 310(2), pages 914-927.
    22. Zhijie Xiao & Roger Koenker, 2009. "Conditional Quantile Estimation for GARCH Models," Boston College Working Papers in Economics 725, Boston College Department of Economics.
    23. Fabio Busetti & Michele Caivano & Lisa Rodano, 2015. "On the conditional distribution of euro area inflation forecast," Temi di discussione (Economic working papers) 1027, Bank of Italy, Economic Research and International Relations Area.
    24. Chollete, Loran & de la Pena , Victor & Lu, Ching-Chih, 2009. "International Diversification: An Extreme Value Approach," UiS Working Papers in Economics and Finance 2009/26, University of Stavanger.
    25. Jason Ng & Catherine S. Forbes & Gael M. Martin & Brendan P.M. McCabe, 2011. "Non-Parametric Estimation of Forecast Distributions in Non-Gaussian, Non-linear State Space Models," Monash Econometrics and Business Statistics Working Papers 11/11, Monash University, Department of Econometrics and Business Statistics.
    26. Harvey, Andrew & Oryshchenko, Vitaliy, 2012. "Kernel density estimation for time series data," International Journal of Forecasting, Elsevier, vol. 28(1), pages 3-14.
    27. Cathy Q. Ning & Loran Chollete, 2009. "The Dependence Structure of Macroeconomic Variables in the US," Working Papers 005, Ryerson University, Department of Economics.
    28. Rubia, Antonio & Sanchis-Marco, Lidia, 2013. "On downside risk predictability through liquidity and trading activity: A dynamic quantile approach," International Journal of Forecasting, Elsevier, vol. 29(1), pages 202-219.
    29. Marcus Alexander & Matthew Harding & Carlos Lamarche, 2011. "Quantifying the impact of economic crises on infant mortality in advanced economies," Applied Economics, Taylor & Francis Journals, vol. 43(24), pages 3313-3323.
    30. Busetti, Fabio & Caivano, Michele & Delle Monache, Davide & Pacella, Claudia, 2021. "The time-varying risk of Italian GDP," Economic Modelling, Elsevier, vol. 101(C).
    31. Caperoz, Marcelo & Marçal, Emerson Fernandes & Mattos, Enlinson, 2016. "A time series analysis of household income inequality in Brazil 1977-2013," Textos para discussão 434, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    32. Chao, Shih-Kang & Härdle, Wolfgang K. & Huang, Chen, 2018. "Multivariate factorizable expectile regression with application to fMRI data," Computational Statistics & Data Analysis, Elsevier, vol. 121(C), pages 1-19.
    33. Shuzhen Yang, 2021. "Compensatory model for quantile estimation and application to VaR," Papers 2112.07278, arXiv.org.
    34. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    35. Zongwu Cai & Ying Fang & Dingshi Tian, 2024. "CAViaR Model Selection Via Adaptive Lasso," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202403, University of Kansas, Department of Economics, revised Jan 2024.
    36. Zongwu Cai & Ying Fang & Dingshi Tian, 2018. "Assessing Tail Risk Using Expectile Regressions with Partially Varying Coefficients," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201804, University of Kansas, Department of Economics, revised Oct 2018.
    37. Voudouris, Vlasios & Matsumoto, Ken'ichi & Sedgwick, John & Rigby, Robert & Stasinopoulos, Dimitrios & Jefferson, Michael, 2014. "Exploring the production of natural gas through the lenses of the ACEGES model," Energy Policy, Elsevier, vol. 64(C), pages 124-133.
    38. James Ming Chen, 2018. "On Exactitude in Financial Regulation: Value-at-Risk, Expected Shortfall, and Expectiles," Risks, MDPI, vol. 6(2), pages 1-28, June.
    39. Zhang, Feipeng & Li, Qunhua, 2017. "A continuous threshold expectile model," Computational Statistics & Data Analysis, Elsevier, vol. 116(C), pages 49-66.
    40. Yuta Kurose & Yasuhiro Omori, 2012. "Bayesian Analysis of Time-Varying Quantiles Using a Smoothing Spline," CIRJE F-Series CIRJE-F-845, CIRJE, Faculty of Economics, University of Tokyo.
    41. Zhiping Chen & Qianhui Hu & Ruiyue Lin, 2016. "Performance ratio-based coherent risk measure and its application," Quantitative Finance, Taylor & Francis Journals, vol. 16(5), pages 681-693, May.
    42. Huang, Xiaolin & Shi, Lei & Suykens, Johan A.K., 2014. "Asymmetric least squares support vector machine classifiers," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 395-405.
    43. Garcia-Jorcano, Laura & Sanchis-Marco, Lidia, 2022. "Spillover effects between commodity and stock markets: A SDSES approach," Resources Policy, Elsevier, vol. 79(C).
    44. Mauro Bernardi & Ghislaine Gayraud & Lea Petrella, 2013. "Bayesian inference for CoVaR," Papers 1306.2834, arXiv.org, revised Nov 2013.
    45. C. Adam & I. Gijbels, 2022. "Local polynomial expectile regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(2), pages 341-378, April.
    46. Kneib, Thomas & Silbersdorff, Alexander & Säfken, Benjamin, 2023. "Rage Against the Mean – A Review of Distributional Regression Approaches," Econometrics and Statistics, Elsevier, vol. 26(C), pages 99-123.
    47. Chollete, Lorán & de la Peña, Victor & Lu, Ching-Chih, 2011. "International diversification: A copula approach," Journal of Banking & Finance, Elsevier, vol. 35(2), pages 403-417, February.
    48. Harvey, Andrew, 2010. "Tracking a changing copula," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 485-500, June.
    49. Fabio Busetti & Andrew Harvey, 2010. "Tests of strict stationarity based on quantile indicators," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(6), pages 435-450, November.
    50. Feng, Xiang-Nan & Wang, Yifan & Lu, Bin & Song, Xin-Yuan, 2017. "Bayesian regularized quantile structural equation models," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 234-248.
    51. Chollete, Loran & Ning, Cathy, 2010. "Asymmetric Dependence in US Financial Risk Factors?," UiS Working Papers in Economics and Finance 2011/2, University of Stavanger.

  24. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Clive G. Bowsher & Roland Meeks, 2008. "The dynamics of economics functions: modelling and forecasting the yield curve," Working Papers 0804, Federal Reserve Bank of Dallas.
    2. Harvey, A., 2008. "Dynamic distributions and changing copulas," Cambridge Working Papers in Economics 0839, Faculty of Economics, University of Cambridge.
    3. Michael Pfarrhofer, 2021. "Modeling tail risks of inflation using unobserved component quantile regressions," Papers 2103.03632, arXiv.org, revised Oct 2021.
    4. Busettti, F. & Harvey, A., 2007. "Tests of time-invariance," Cambridge Working Papers in Economics 0701, Faculty of Economics, University of Cambridge.
    5. Busetti, F. & Harvey, A., 2008. "When is a copula constant? A test for changing relationships," Cambridge Working Papers in Economics 0841, Faculty of Economics, University of Cambridge.
    6. Nieto, María Rosa & Ruiz Ortega, Esther, 2008. "Measuring financial risk : comparison of alternative procedures to estimate VaR and ES," DES - Working Papers. Statistics and Econometrics. WS ws087326, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Harvey, Andrew & Oryshchenko, Vitaliy, 2012. "Kernel density estimation for time series data," International Journal of Forecasting, Elsevier, vol. 28(1), pages 3-14.
    8. Daniel Mariño-Ustacara & Luis Fernando Melo-Velandia, 2016. "Relación entre los valores en riesgo de los principales mercados financieros colombianos: un enfoque a través de modelos multivariados de regresión cuantílica," Borradores de Economia 975, Banco de la Republica de Colombia.
    9. DeRossi, G. & Harvey, A., 2007. "Quantiles, Expectiles and Splines," Cambridge Working Papers in Economics 0660, Faculty of Economics, University of Cambridge.
    10. Caperoz, Marcelo & Marçal, Emerson Fernandes & Mattos, Enlinson, 2016. "A time series analysis of household income inequality in Brazil 1977-2013," Textos para discussão 434, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    11. Shuzhen Yang, 2021. "Compensatory model for quantile estimation and application to VaR," Papers 2112.07278, arXiv.org.
    12. Harvey, Andrew, 2010. "Tracking a changing copula," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 485-500, June.
    13. Ammy-Driss, Ayoub & Garcin, Matthieu, 2023. "Efficiency of the financial markets during the COVID-19 crisis: Time-varying parameters of fractional stable dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).

  25. Fabio Busetti & Silvia Fabiani & Andrew Harvey, 2006. "Convergences of prices and rates of inflation," Temi di discussione (Economic working papers) 575, Bank of Italy, Economic Research and International Relations Area.

    Cited by:

    1. Nagayasu, Jun, 2014. "Regional inflation, spatial location and the Balassa-Samuelson effect," MPRA Paper 59220, University Library of Munich, Germany.
    2. Garcia-Hiernaux, Alfredo & Gonzalez-Perez, Maria T. & Guerrero, David E., 2023. "Eurozone prices: A tale of convergence and divergence," Economic Modelling, Elsevier, vol. 126(C).
    3. Winkelried, Diego & Gutiérrez, José, 2012. "Dinámica inflacionaria regional y el esquema de metas de inflación en el Perú," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 24, pages 79-98.
    4. Davide Delle Monache & Ivan Petrella & Fabrizio Venditti, 2016. "Common Faith or Parting Ways? A Time Varying Parameters Factor Analysis of Euro-Area Inflation," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 539-565, Emerald Group Publishing Limited.
    5. Angelos Liontakis & Christos T. Papadas, 2010. "Distribution Dynamics of Food Price Inflation Rates in EU: An Alternative Conditional Density Estimator Approach," Working Papers 2010-6, Agricultural University of Athens, Department Of Agricultural Economics.
    6. Burcu ERDOGAN & Guglielmo MARIA CAPORALE & Vladimir KUZIN, 2010. "Testing Stock Market Convergence: A Non-linear Factor Approach," EcoMod2010 259600051, EcoMod.
    7. Kosfeld, Reinhold & Eckey, Hans-Friedrich & Lauridsen, Jørgen, 2007. "Disparities in prices and income across German NUTS 3 regions," Volkswirtschaftliche Diskussionsbeiträge 93, University of Kassel, Faculty of Economics and Management.
    8. Winkelried, Diego & Gutierrez, José Enrique, 2012. "Regional inflation dynamics and inflation targeting in Peru," Working Papers 2012-018, Banco Central de Reserva del Perú.
    9. Christian Dreger & Reinhold Kosfeld, 2007. "Do Regional Price Levels Converge?: Paneleconometric Evidence Based on German Districts," Discussion Papers of DIW Berlin 754, DIW Berlin, German Institute for Economic Research.
    10. Sauro Mocetti, 2008. "Educational choices and the selection process before and after compulsory schooling," Temi di discussione (Economic working papers) 691, Bank of Italy, Economic Research and International Relations Area.
    11. Garcia-Hiernaux, Alfredo & Guerrero, David E., 2021. "Price convergence: Representation and testing," Economic Modelling, Elsevier, vol. 104(C).
    12. Hiranya K. Nath & Jayanta Sarkar, 2014. "City Relative Price Dynamics in Australia: Are Structural Breaks Important?," The Economic Record, The Economic Society of Australia, vol. 90(288), pages 33-48, March.
    13. Fabio Busetti & Silvia Fabiani & Andrew Harvey, 2006. "Convergence of Prices and Rates of Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 863-877, December.
    14. Diego Winkelried & José Enrique Gutierrez, 2015. "Regional inflation dynamics and inflation targeting. The case of Peru," Journal of Applied Economics, Universidad del CEMA, vol. 18, pages 199-224, November.
    15. Arestis, Philip & Chortareas, Georgios & Magkonis, Georgios & Moschos, Demetrios, 2014. "Inflation targeting and inflation convergence: International evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 285-295.
    16. Alejandro C. García-Cintado & Diego Romero-Ávila & Carlos Usabiaga, 2016. "The economic integration of Spain: a change in the inflation pattern," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 25(1), pages 1-41, December.
    17. Alfredo García Hiernaux & David Esteban Guerrero Burbano, 2015. "Price-Level Convergence in the Eurozone," Documentos de Trabajo del ICAE 2015-05, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    18. Andrea Vaona & Guido Ascari, 2008. "Regional Inflation Persistence: Evidence from Italy," Quaderni della facoltà di Scienze economiche dell'Università di Lugano 0807, USI Università della Svizzera italiana.
    19. Pesavento, Elena & Rossi, Barbara, 2007. "Impulse response confidence intervals for persistent data: What have we learned?," Journal of Economic Dynamics and Control, Elsevier, vol. 31(7), pages 2398-2412, July.
    20. Yilmazkuday, Hakan, 2009. "Inflation Targeting and Inflation Convergence within Turkey," MPRA Paper 16770, University Library of Munich, Germany.
    21. Jun Nagayasu, 2017. "Regional inflation, spatial locations and the Balassa-Samuelson effect: Evidence from Japan," Urban Studies, Urban Studies Journal Limited, vol. 54(6), pages 1482-1499, May.
    22. Huang, Ho-Chuan (River) & Liu, Wei-Han & Yeh, Chih-Chuan, 2012. "Convergence in price levels across US cities," Economics Letters, Elsevier, vol. 114(3), pages 245-248.
    23. Busetti, Fabio, 2009. "Initial conditions and stationarity tests," Economics Letters, Elsevier, vol. 105(3), pages 296-299, December.
    24. Carla Massidda & Paolo Mattana, 2008. "Regional productivity and relative prices dynamics: the case of Italy," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(4), pages 945-966, December.
    25. Dreger Christian & Kosfeld Reinhold, 2010. "Do Regional Price Levels Converge?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 230(3), pages 274-286, June.
    26. Hwa-Taek Lee & Gawon Yoon, 2013. "Does purchasing power parity hold sometimes? Regime switching in real exchange rates," Applied Economics, Taylor & Francis Journals, vol. 45(16), pages 2279-2294, June.
    27. Matteo Bugamelli & Alfonso Rosolia, 2006. "Productivity and foreign competition," Temi di discussione (Economic working papers) 578, Bank of Italy, Economic Research and International Relations Area.
    28. Adebola, Solarin Sakiru & Gil-Alana, Luis A. & Madigu, Godfrey, 2019. "Gold prices and the cryptocurrencies: Evidence of convergence and cointegration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1227-1236.
    29. Liontakis, Angelos E. & Papadas, Christos T., 2009. "Distribution Dynamics of Food Price Inflation Rates in EU: An Alternative Conditional Density Estimator Approach," 113th Seminar, September 3-6, 2009, Chania, Crete, Greece 58084, European Association of Agricultural Economists.
    30. Carlos Carrasco & Jesus Ferreiro, 2013. "Inflation targeting in Mexico," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 35(3), pages 341-372.
    31. Ailenei, Dorel & Cristescu, Amalia, 2010. "Regional Distribution of Inflationary Pressures in Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 32-43, December.
    32. David Gray, 2021. "A simple measure of beta-convergence revisited," Urban Studies, Urban Studies Journal Limited, vol. 58(12), pages 2569-2583, September.

  26. Busetti, Fabio & Forni, Lorenzo & Harvey, Andrew & Venditti, Fabrizio, 2006. "Inflation convergence and divergence within the European Monetary Union," Working Paper Series 574, European Central Bank.

    Cited by:

    1. Jan Kubíček, 2006. "Úrokové diferenciály a zadlužení v eurozóně [Interest rate differentials and the debt in the euro-zone]," Politická ekonomie, Prague University of Economics and Business, vol. 2006(6), pages 816-833.
    2. Litsios, Ioannis & Pilbeam, Keith, 2017. "An empirical analysis of the nexus between investment, fiscal balances and current account balances in Greece, Portugal and Spain," Economic Modelling, Elsevier, vol. 63(C), pages 143-152.
    3. Lopez, Claude & Papell, David, 2010. "Testing for Group-Wise Convergence with an Application to Euro Area Inflation," MPRA Paper 20585, University Library of Munich, Germany.
    4. Joseph P. Byrne & Norbert Fiess, 2007. "Euro Area Inflation: Aggregation Bias and Convergence," Working Papers 2007_41, Business School - Economics, University of Glasgow.
    5. Fabio Busetti & Pietro Cova & Antonio Maria Conti & Filippo Scoccianti & Libero Monteforte & Giordano Zevi & Valentina Aprigliano & Andrea Gerali & Alberto Locarno & Alessandro Notarpietro & Massimili, 2014. "The effects of the crisis on production potential and household spending in Italy," Workshop and Conferences 18, Bank of Italy, Economic Research and International Relations Area.
    6. Nektarios A. Michail, 2020. "Convergence of consumption patterns in the European Union," Empirical Economics, Springer, vol. 58(3), pages 979-994, March.
    7. Garcia-Hiernaux, Alfredo & Gonzalez-Perez, Maria T. & Guerrero, David E., 2023. "Eurozone prices: A tale of convergence and divergence," Economic Modelling, Elsevier, vol. 126(C).
    8. Fabio C. Bagliano & Claudio Morana, 2010. "The effects of US economic and financial crises on euro area convergence," Working papers 15, Former Department of Economics and Public Finance "G. Prato", University of Torino.
    9. Moons, Cindy & Hellinckx, Kevin, 2019. "Did monetary policy fuel the housing bubble? An application to Ireland," Journal of Policy Modeling, Elsevier, vol. 41(2), pages 294-315.
    10. Adrian Petre, 2016. "The Analysis of the Nominal Convergence in the New Member States of the European Union," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 19(61), pages 245-254, September.
    11. Peter Bofinger & Eric Mayer, 2007. "Monetary and Fiscal Policy Interaction in the Euro Area with Different Assumptions on the Phillips Curve," Open Economies Review, Springer, vol. 18(3), pages 291-305, July.
    12. Davide Delle Monache & Ivan Petrella & Fabrizio Venditti, 2016. "Common Faith or Parting Ways? A Time Varying Parameters Factor Analysis of Euro-Area Inflation," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 539-565, Emerald Group Publishing Limited.
    13. Angelos Liontakis & Christos T. Papadas, 2010. "Distribution Dynamics of Food Price Inflation Rates in EU: An Alternative Conditional Density Estimator Approach," Working Papers 2010-6, Agricultural University of Athens, Department Of Agricultural Economics.
    14. A M Spiru, 2007. "Inflation convergence in the new EU member states," Working Papers 590260, Lancaster University Management School, Economics Department.
    15. Stefano IACUS & Giuseppe PORRO, 2013. "Does European Monetary Union make inflation dynamics more uniform?," Departmental Working Papers 2013-12, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    16. Alberto Montagnoli & Andros Gregoriou & Alexandros Kontonikas, 2007. "Euro Area Inflation Differentials: Unit Roots, Structural Breaks and Non-Linear Adjustment," Working Papers 2007_13, Business School - Economics, University of Glasgow.
    17. Iulia Traistaru-Siedschlag, 2006. "Macroeconomic Differentials and Adjustment in the Euro Area," Papers WP175, Economic and Social Research Institute (ESRI).
    18. PIROVANO, Mara & VAN POECK, André, 2011. "Eurozone inflation differentials and the ECB," Working Papers 2011014, University of Antwerp, Faculty of Business and Economics.
    19. Abban, Stanley, 2020. "On the Computation and Essence of the Nominal Convergence Criteria for Africa Currency Union: ECOWAS in Perspective," MPRA Paper 100215, University Library of Munich, Germany, revised 10 May 2020.
    20. Baskaran, Thushyanthan, 2009. "Did the Maastricht treaty matter for macroeconomic performance?," MPRA Paper 30106, University Library of Munich, Germany.
    21. Michele Caputo & Francesco Forte, 2015. "Difficult Convergence among the Five Main European Union Countries and the Crisis of the Euro Area," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 43(4), pages 415-430, December.
    22. Andrea Silvestrini, 2010. "Testing fiscal sustainability in Poland: a Bayesian analysis of cointegration," Empirical Economics, Springer, vol. 39(1), pages 241-274, August.
    23. Kamiar Mohaddes & Oral H. Williams, 2013. "Inflation Differentials In The Gcc: Does The Oil Cycle Matter?," Middle East Development Journal (MEDJ), World Scientific Publishing Co. Pte. Ltd., vol. 5(02), pages 1-23.
    24. André Van Poeck, 2010. "One Money and Sixteen Needs: Has the ECB’s Monetary Policy Become More Balanced Towards the Needs of the Member States?," De Economist, Springer, vol. 158(1), pages 43-60, April.
    25. Cavallero, Alessandro, 2011. "The convergence of inflation rates in the EU-12 area: A distribution dynamics approach," Journal of Macroeconomics, Elsevier, vol. 33(2), pages 341-357, June.
    26. Ahlgren, Niklas & Juselius, Mikael, 2009. "Tests for Cointegration Rank and the Initial Condition," Working Papers 539, Hanken School of Economics.
    27. GRENADE, Kari & MOORE, Winston, 2008. "Co-Movements Between Foreign And Domestic Interest Rates In A Fixed Exchange Rate Regime: The Case Of The Eccu And The Us," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 8(1), pages 119-130.
    28. Juan Carlos Cuestas & Luis A. Gil-Alana & Karl Taylor, 2016. "Inflation convergence in Central and Eastern Europe vs. the Eurozone: Non-linearities and long memory," Scottish Journal of Political Economy, Scottish Economic Society, vol. 63(5), pages 519-538, November.
    29. Gómez Múnoz, Wilman Arturo & Posada Posada, Carlos Esteban & Rhenals Monterrosa, Remberto, 2021. "Caída y convergencia mundial de las tasas de inflación," Borradores Departamento de Economía 19618, Universidad de Antioquia, CIE.
    30. Dreger, Christian, 2010. "Does the Nominal Exchange Rate Regime Affect the Real Interest Parity Condition?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 21(3), pages 274-285.
    31. Sandeep Mazumder, 2014. "European Monetary Union and the Cost of Disinflation," Economic Issues Journal Articles, Economic Issues, vol. 19(2), pages 1-20, September.
    32. Garcia-Hiernaux, Alfredo & Guerrero, David E., 2021. "Price convergence: Representation and testing," Economic Modelling, Elsevier, vol. 104(C).
    33. Ulrich Fritsche & Vladimir Kuzin, 2007. "Unit Labor Cost Growth Differentials in the Euro Area, Germany, and the US: Lessons from PANIC and Cluster Analysis," Discussion Papers of DIW Berlin 667, DIW Berlin, German Institute for Economic Research.
    34. Aycan HEPSAG, 2017. "Inflation convergence among the next eleven economies: Evidence from asymmetric nonlinear unit root test," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(4(613), W), pages 43-52, Winter.
    35. Sule Akkoyunlu & Boriss Siliverstovs, 2014. "Does the law of one price hold in a high-inflation environment? A tale of two cities in Turkey," Applied Economics, Taylor & Francis Journals, vol. 46(26), pages 3236-3245, September.
    36. König, Jörg & Ohr, Renate, 2012. "Messung ökonomischer Integration in der Europäischen Union: Entwicklung eines EU-Integrationsindexes," University of Göttingen Working Papers in Economics 135, University of Goettingen, Department of Economics.
    37. Bagnai, Alberto & Granville, Brigitte & Mongeau Ospina, Christian A., 2017. "Withdrawal of Italy from the euro area: Stochastic simulations of a structural macroeconometric model," Economic Modelling, Elsevier, vol. 64(C), pages 524-538.
    38. Giannellis, Nikolaos, 2013. "Asymmetric behavior of inflation differentials in the euro area: Evidence from a threshold unit root test," Research in Economics, Elsevier, vol. 67(2), pages 133-144.
    39. Thushyanthan Baskaran, 2009. "Did the Maastricht treaty matter for macroeconomic performance? A difference‐in‐difference investigation," Kyklos, Wiley Blackwell, vol. 62(3), pages 331-358, August.
    40. Ulrich Fritsche & Vladimir Kuzin, 2008. "Analysing Convergence in Europe Using a Non-linear Single Factor Model," Macroeconomics and Finance Series 200802, University of Hamburg, Department of Socioeconomics.
    41. Alberto Bagnai, 2016. "Italy’s decline and the balance-of-payments constraint: a multicountry analysis," International Review of Applied Economics, Taylor & Francis Journals, vol. 30(1), pages 1-26, January.
    42. Arestis, Philip & Chortareas, Georgios & Magkonis, Georgios & Moschos, Demetrios, 2014. "Inflation targeting and inflation convergence: International evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 285-295.
    43. Alejandro C. García-Cintado & Diego Romero-Ávila & Carlos Usabiaga, 2016. "The economic integration of Spain: a change in the inflation pattern," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 25(1), pages 1-41, December.
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    3. Kauermann Goeran & Krivobokova Tatyana & Semmler Willi, 2011. "Filtering Time Series with Penalized Splines," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(2), pages 1-28, March.
    4. Álvarez, Luis J. & Gómez-Loscos, Ana, 2018. "A menu on output gap estimation methods," Journal of Policy Modeling, Elsevier, vol. 40(4), pages 827-850.
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    6. Drew Creal & Siem Jan Koopman & Eric Zivot, 2010. "Extracting a robust US business cycle using a time-varying multivariate model-based bandpass filter," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 695-719.
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    8. Mihnea Constantinescu & Anh Dinh Minh Nguyen, 2017. "Unemployment or Credit: Who Holds The Potential? Results From a Small-Open Economy," Bank of Lithuania Discussion Paper Series 4, Bank of Lithuania.
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    24. Gonzalez, Rodrigo Barbone & Marinho, Leonardo Sousa Gomes & Lima, Joaquim Ignacio Alves de Vasconcellos e, 2017. "Re-anchoring countercyclical capital buffers: Bayesian estimates and alternatives focusing on credit growth," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1007-1024.
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    32. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
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    34. James Morley & Irina B Panovska, 2017. "Is Business Cycle Asymmetry Intrinsic in Industrialized Economies?," Discussion Papers 2016-12A, School of Economics, The University of New South Wales.
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    40. Bernardi, Mauro & Della Corte, Giuseppe & Proietti, Tommaso, 2008. "Extracting the Cyclical Component in Hours Worked: a Bayesian Approach," MPRA Paper 8967, University Library of Munich, Germany.
    41. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.
    42. Reusens Peter & Croux Christophe, 2017. "Detecting time variation in the price puzzle: a less informative prior choice for time varying parameter VAR models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-18, September.
    43. Harvey, A., 2008. "Modeling the Phillips curve with unobserved components," Cambridge Working Papers in Economics 0805, Faculty of Economics, University of Cambridge.
    44. Rodrigo Barbone Gonzalez & Joaquim Lima & Leonardo Marinho, 2015. "Countercyclical Capital Buffers: bayesian estimates and alternatives focusing on credit growth," Working Papers Series 384, Central Bank of Brazil, Research Department.
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    46. D.S. Prasada Rao & Alicia Rambaldi & Howard Doran, 2008. "A Method to Construct World Tables of Purchasing Power Parities and Real Incomes Based on Multiple Benchmarks and Auxiliary Information: Analytical and Empirical Results," CEPA Working Papers Series WP052008, School of Economics, University of Queensland, Australia.
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    54. Constantinescu, Mihnea & Nguyen, Anh D.M., 2018. "Unemployment or credit: Which one holds the potential? Results for a small open economy with a low degree of financialization," Economic Systems, Elsevier, vol. 42(4), pages 649-664.
    55. Oh, Kum Hwa & Zivot, Eric & Creal, Drew, 2008. "The relationship between the Beveridge-Nelson decomposition and other permanent-transitory decompositions that are popular in economics," Journal of Econometrics, Elsevier, vol. 146(2), pages 207-219, October.
    56. João Valle e Azevedo, 2007. "A Multivariate Band-Pass Filter," Working Papers w200717, Banco de Portugal, Economics and Research Department.
    57. Terence C. Mills, 2013. "Trends, cycles and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 3, pages 45-60, Edward Elgar Publishing.
    58. Ramis Khabibullin, 2019. "What measures of real economic activity slack are helpful for forecasting Russian inflation?," Bank of Russia Working Paper Series wps50, Bank of Russia.
    59. Paolo Guarda & Alban Moura, 2019. "Measuring real and financial cycles in Luxembourg: An unobserved components approach," BCL working papers 126, Central Bank of Luxembourg.
    60. Rodrigo Barbone Gonzalez & Joaquim Lima & Leonardo Marinho, 2015. "Business and Financial Cycles: an estimation of cycles’ length focusing on Macroprudential Policy," Working Papers Series 385, Central Bank of Brazil, Research Department.
    61. James Morley, 2014. "Measuring Economic Slack: A Forecast-Based Approach with Applications to Economies in Asia and the Pacific," BIS Working Papers 451, Bank for International Settlements.
    62. Andrew Harvey, 2010. "The local quadratic trend model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 94-108.
    63. Stefania Mignani & Marcello Pagnini, 2021. "How effective is financial education? Evidence from the Emilia-Romagna region," Working Paper series 21-08, Rimini Centre for Economic Analysis.

  28. Harvey, Andrew & Carvalho, Vasco, 2004. "Convergence and Cycles in the Euro Zone," CEPR Discussion Papers 4726, C.E.P.R. Discussion Papers.

    Cited by:

    1. Jansen, W. Jos & Stokman, Ad C.J., 2004. "Foreign direct investment and international business cycle comovement," Working Paper Series 401, European Central Bank.
    2. Eickmeier, Sandra, 2005. "Common stationary and non-stationary factors in the euro area analyzed in a large-scale factor model," Discussion Paper Series 1: Economic Studies 2005,02, Deutsche Bundesbank.
    3. James H. Stock & Mark W. Watson, 2005. "Understanding Changes In International Business Cycle Dynamics," Journal of the European Economic Association, MIT Press, vol. 3(5), pages 968-1006, September.
    4. Bovi, M., 2005. "Economic Clubs and European Commitment. Evidence from the International Business Cycles," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 2(2), pages 101-122.
    5. James H. Stock & Mark W. Watson, 2003. "Has the business cycle changed?," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 9-56.
    6. Maurizio Bovi, 2003. "Nonparametric Analysis Of The International Business Cycles," ISAE Working Papers 37, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).

  29. Harvey, A.C. & Trimbur, T.M. & van Dijk, H.K., 2004. "Bayes estimates of the cyclical component in twentieth centruy US gross domestic product," Econometric Institute Research Papers EI 2004-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Ferroni, Filippo, 2009. "Trend agnostic one step estimation of DSGE models," MPRA Paper 14550, University Library of Munich, Germany.
    2. Harvey, A.C. & Trimbur, T.M. & van Dijk, H.K., 2005. "Trends and cycles in economic time series: A Bayesian approach," Econometric Institute Research Papers EI 2005-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. de Pooter, M.D. & Ravazzolo, F. & Segers, R. & van Dijk, H.K., 2008. "Bayesian near-boundary analysis in basic macroeconomic time series models," Econometric Institute Research Papers EI 2008-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  30. Andrew Harvey, 2004. "Trend estimation, signal-noise ratios and the frequency of observations," Econometric Society 2004 Australasian Meetings 343, Econometric Society.

    Cited by:

    1. Alain Noullez & Alessandra Iacobucci, 2004. "A Frequency-selective Filter for Short-Length Time Series," Computing in Economics and Finance 2004 128, Society for Computational Economics.
    2. Tucker S. McElroy & Thomas M. Trimbur, 2007. "Continuous time extraction of a nonstationary signal with illustrations in continuous low-pass and band-pass filtering," Finance and Economics Discussion Series 2007-68, Board of Governors of the Federal Reserve System (U.S.).

  31. Harvey, A. & Bates, D., 2003. "Multivariate Unit Root Tests and Testing for Convergence," Cambridge Working Papers in Economics 0301, Faculty of Economics, University of Cambridge.

    Cited by:

    1. David E.A. Giles & Hui Feng, 2003. "Testing For Convergence in Output and in 'Well-Being' in Industrialized Countries," Econometrics Working Papers 0302, Department of Economics, University of Victoria.
    2. Kristian Jönsson, 2005. "Cross‐sectional Dependency and Size Distortion in a Small‐sample Homogeneous Panel Data Unit Root Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(3), pages 369-392, June.
    3. Christophe Hurlin & Valérie Mignon, 2006. "Une Synthèse des Tests de Racine Unitaire sur Données de Panel," Post-Print halshs-00078770, HAL.
    4. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    5. GRENADE, Kari & MOORE, Winston, 2008. "Co-Movements Between Foreign And Domestic Interest Rates In A Fixed Exchange Rate Regime: The Case Of The Eccu And The Us," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 8(1), pages 119-130.
    6. Fischer, Christoph & Porath, Daniel, 2006. "A reappraisal of the evidence on PPP: a systematic investigation into MA roots in panel unit root tests and their implications," Discussion Paper Series 1: Economic Studies 2006,23, Deutsche Bundesbank.
    7. Fabio Busetti & Silvia Fabiani & Andrew Harvey, 2006. "Convergence of Prices and Rates of Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 863-877, December.
    8. Elliott, Graham & Muller, Ulrich K., 2006. "Minimizing the impact of the initial condition on testing for unit roots," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 285-310.
    9. Sandra Eickmeier, 2009. "Comovements and heterogeneity in the euro area analyzed in a non-stationary dynamic factor model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 933-959.
    10. Alina M. Spiru, 2008. "Inflation Convergence In Central And Eastern European Economies," Romanian Economic Business Review, Romanian-American University, vol. 3(4), pages 14-34, Winter.
    11. Andrew C. Harvey & Vasco M. Carvalho, 2005. "Convergence in the trends and cycles of Euro-zone income," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 275-289.
    12. Lorde, Troy & Moore, Winston, 2006. "Co-movement in tourist arrivals in the Caribbean," MPRA Paper 95598, University Library of Munich, Germany.
    13. Lyhagen, Johan & Rickne, Johanna, 2011. "Income Inequality between Chinese Regions: Newfound Harmony or Continued Discord?," Working Paper Series 872, Research Institute of Industrial Economics.
    14. Fischer, Christoph, 2007. "An assessment of the trends in international price competitiveness among EMU countries," Discussion Paper Series 1: Economic Studies 2007,08, Deutsche Bundesbank.
    15. Breitung, Jörg & Pesaran, Mohammad Hashem, 2005. "Unit roots and cointegration in panels," Discussion Paper Series 1: Economic Studies 2005,42, Deutsche Bundesbank.
    16. Eickmeier, Sandra, 2006. "Comovements and heterogeneity in the Comovements and heterogeneity in the dynamic factor model," Discussion Paper Series 1: Economic Studies 2006,31, Deutsche Bundesbank.
    17. Usman Khalid & Luke Okafor & Muhammad Shahbaz, 2022. "Economic reform and political stagnation: The inconsistent patterns of institutional change," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 30(4), pages 813-844, October.
    18. Carvalho, Vasco M. & Harvey, Andrew C., 2005. "Growth, cycles and convergence in US regional time series," International Journal of Forecasting, Elsevier, vol. 21(4), pages 667-686.
    19. Fabio Busetti & Lorenzo Forni & Andrew Harvey & Fabrizio Venditti, 2007. "Inflation Convergence and Divergence within the European Monetary Union," International Journal of Central Banking, International Journal of Central Banking, vol. 3(2), pages 95-121, June.
    20. Usman Khalid, 2016. "Catch-up in Institutional Quality: An Empirical Assessment," Discussion Papers 2016-04, University of Nottingham, CREDIT.
    21. Lorenzo Lucchese & Mikko Pakkanen & Almut Veraart, 2022. "The Short-Term Predictability of Returns in Order Book Markets: a Deep Learning Perspective," Papers 2211.13777, arXiv.org, revised Oct 2023.
    22. Ghassen El Montasser & Roula Inglesi-Lotz & Rangan Gupta, 2013. "Convergence of Greenhouse Gas Emissions among G7 Countries," Working Papers 201386, University of Pretoria, Department of Economics.
    23. Fabio Busetti & Michele Caivano, 2017. "Low frequency drivers of the real interest rate: a band spectrum regression approach," Temi di discussione (Economic working papers) 1132, Bank of Italy, Economic Research and International Relations Area.
    24. Alina M. Spiru, 2008. "Inflation Convergence In Central And Eastern European Economies," Journal of Information Systems & Operations Management, Romanian-American University, vol. 2(1), pages 289-316, July.

  32. Harvey, A. & TTrimbur, T. & van Dijk, H., 2003. "Cyclical Components in Economic Time Series: a Bayesian Approach," Cambridge Working Papers in Economics 0302, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Martha López P., 2003. "Efficient Policy Rule for Inflation Targeting in Colombia," Borradores de Economia 240, Banco de la Republica de Colombia.
    2. Gonzalo Llosa & Shirley Miller, 2005. "Using additional information in estimating the output gap in Peru: a multivariate unobserved component approach," Working Papers 2005-004, Banco Central de Reserva del Perú.
    3. Harm Bandholz & Gebhard Flaig & Johannes Mayr, 2005. "Growth and economic activity in OECD countries: A long-term perspective," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 58(04), pages 28-36, February.
    4. Thomas M. Trimbur, 2006. "Properties of higher order stochastic cycles," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(1), pages 1-17, January.
    5. Richard Kleijn & Herman K. van Dijk, 2006. "Bayes model averaging of cyclical decompositions in economic time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 191-212, March.
    6. Klaus Abberger & Gebhard Flaig & Wolfgang Nierhaus, 2007. "ifo Konjunkturumfragen und Konjunkturanalyse : ausgewählte methodische Aufsätze aus dem ifo Schnelldienst," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 33.
    7. Wayne Robinson, 2004. "Real Shocks, Credibility & Stabilization Policy in a Small Open Economy," Money Affairs, CEMLA, vol. 0(1), pages 39-55, January-J.
    8. Adriana Arreaza & Enid Blanco & Miguel Dorta, 2004. "A Small Scale Macroeconomic Model for Venezuela," Money Affairs, CEMLA, vol. 0(1), pages 25-38, January-J.

  33. Busettti, F. & Harvey, A., 2002. "Testing for Drift in a Time Series," Cambridge Working Papers in Economics 0237, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Fabio Busetti & Silvia Fabiani & Andrew Harvey, 2006. "Convergence of Prices and Rates of Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 863-877, December.
    2. Busetti, Fabio & Harvey, Andrew, 2008. "Testing For Trend," Econometric Theory, Cambridge University Press, vol. 24(1), pages 72-87, February.

  34. Andrew Harvey, 2002. "Trends, Cycles and Convergence," Working Papers Central Bank of Chile 155, Central Bank of Chile.

    Cited by:

    1. Massimiliano Affinito, 2011. "Convergence clubs, the euro-area rank and the relationship between banking and real convergence," Temi di discussione (Economic working papers) 809, Bank of Italy, Economic Research and International Relations Area.
    2. Lavan Mahadeva and Paul Robinson, 2004. "Unit Root Testing in a Central Bank," Handbooks, Centre for Central Banking Studies, Bank of England, number 22, April.

  35. Vasco M.Carvalho & Andrew C.Harvey, 2002. "Growth, Cycles and Convergence in US Regional Time Series," Cambridge Working Papers in Economics 0221, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Lo Cascio, Iolanda, 2021. "A wavelet analysis of the ripple effect in UK regional housing markets," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 1093-1105.
    2. Magdalena Osinska & Karolina Kluth, 2010. "Convergence of Greek Economy with the EU and Some Comparisons with Polish Experience," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 139-156.
    3. Dimitris, Chrsitopoulos & Miguel, Leon-Ledesma, 2009. "International Output Convergence, Breaks, and Asymmetric Adjustment," MPRA Paper 14566, University Library of Munich, Germany.
    4. Juan Gabriel Brida & Bibiana Lanzilotta & Lucía Rosich, 2019. "Common trends in producers’ expectations, the nonlinear linkage with Uruguayan GDP and its implications in economic growth forecasting," Documentos de Trabajo (working papers) 19-28, Instituto de Economía - IECON.
    5. Miles, William, 2020. "House price convergence in the euro zone: A pairwise approach," Economic Systems, Elsevier, vol. 44(3).
    6. Roberto Basile & Sergio de Nardis & Carmine Pappalardo, 2014. "Firm heterogeneity and regional business cycles differentials," Journal of Economic Geography, Oxford University Press, vol. 14(6), pages 1087-1115.
    7. Kiyotaka Sato & Junko Shimizu & Nagendra Shrestha & Shajuan Zhang, 2013. "Industry-specific Real Effective Exchange Rates and Export Price Competitiveness: The Cases of Japan, China, and Korea," Asian Economic Policy Review, Japan Center for Economic Research, vol. 8(2), pages 298-321, December.
    8. Breinlich, Holger & Ottaviano, Gianmarco I P & Temple, Jonathan R, 2013. "Regional Growth and Regional Decline," Economics Discussion Papers 8977, University of Essex, Department of Economics.
    9. Bernardina Algieri, 2015. "Price and non-price competitiveness in export demand: empirical evidence from Italy," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(1), pages 157-183, February.
    10. Miles, William, 2020. "Regional convergence-and divergence-in the US," Research in Economics, Elsevier, vol. 74(2), pages 131-139.
    11. David Gray, 2018. "An application of two non-parametric techniques to the prices of British dwellings: An examination of cyclicality," Urban Studies, Urban Studies Journal Limited, vol. 55(10), pages 2286-2299, August.
    12. Andrés Rodríguez‐Pose & Ugo Fratesi, 2007. "Regional Business Cycles and the Emergence of Sheltered Economies in the Southern Periphery of Europe," Growth and Change, Wiley Blackwell, vol. 38(4), pages 621-648, December.
    13. Andrew C. Harvey & Vasco M. Carvalho, 2005. "Convergence in the trends and cycles of Euro-zone income," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 275-289.
    14. Lyhagen, Johan & Rickne, Johanna, 2011. "Income Inequality between Chinese Regions: Newfound Harmony or Continued Discord?," Working Paper Series 872, Research Institute of Industrial Economics.
    15. Magrini, Stefano, 2004. "Regional (di)convergence," Handbook of Regional and Urban Economics, in: J. V. Henderson & J. F. Thisse (ed.), Handbook of Regional and Urban Economics, edition 1, volume 4, chapter 62, pages 2741-2796, Elsevier.
    16. Usman Khalid & Luke Okafor & Muhammad Shahbaz, 2022. "Economic reform and political stagnation: The inconsistent patterns of institutional change," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 30(4), pages 813-844, October.
    17. Mihai Nica, 2004. "Convergence in Mississippi: A Spatial Approach," Urban/Regional 0408007, University Library of Munich, Germany.
    18. Carvalho, Vasco M. & Harvey, Andrew C., 2005. "Growth, cycles and convergence in US regional time series," International Journal of Forecasting, Elsevier, vol. 21(4), pages 667-686.
    19. Usman Khalid, 2016. "Catch-up in Institutional Quality: An Empirical Assessment," Discussion Papers 2016-04, University of Nottingham, CREDIT.
    20. Robert Dixon, 2007. "Common Cycles in Labour Market Separation Rates for Australian States," Department of Economics - Working Papers Series 991, The University of Melbourne.
    21. Steven Clark & T. Coggin, 2009. "Trends, Cycles and Convergence in U.S. Regional House Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 39(3), pages 264-283, October.
    22. William Miles, 2015. "Regional House Price Segmentation and Convergence in the US: A New Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 50(1), pages 113-128, January.
    23. Terence C. Mills, 2013. "Trends, cycles and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 3, pages 45-60, Edward Elgar Publishing.
    24. Mateusz Tomal, 2022. "Testing for overall and cluster convergence of housing rents using robust methodology: evidence from Polish provincial capitals," Empirical Economics, Springer, vol. 62(4), pages 2023-2055, April.
    25. Richard Startz, 2020. "The next hundred years of growth and convergence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 99-113, January.

  36. Harvey, A. & Vasco Carvalho, 2002. "Models for Converging Economies," Cambridge Working Papers in Economics 0216, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Massimiliano Affinito, 2011. "Convergence clubs, the euro-area rank and the relationship between banking and real convergence," Temi di discussione (Economic working papers) 809, Bank of Italy, Economic Research and International Relations Area.
    2. Haldrup, Niels, "undated". "Empirical analysis of price data in the delineation of the relevant geographical market in competition analysis," Economics Working Papers 2003-9, Department of Economics and Business Economics, Aarhus University.
    3. Andrew Harvey, 2002. "Trends, Cycles and Convergence," Working Papers Central Bank of Chile 155, Central Bank of Chile.
    4. Mike Artis & Hans-Martin Krolzig & Juan Toro, 2002. "The European Business Cycle," Economic Working Papers at Centro de Estudios Andaluces E2002/19, Centro de Estudios Andaluces.
    5. Rob Luginbuhl & Siem Jan Koopman, 2004. "Convergence in European GDP series: a multivariate common converging trend-cycle decomposition," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(5), pages 611-636.
    6. Christian Proaño Acosta, 2007. "Inflation Differentials and Business Cycle Fluctuations in the European Monetary Union," IMK Working Paper 05-2007, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    7. Magrini, Stefano, 2004. "Regional (di)convergence," Handbook of Regional and Urban Economics, in: J. V. Henderson & J. F. Thisse (ed.), Handbook of Regional and Urban Economics, edition 1, volume 4, chapter 62, pages 2741-2796, Elsevier.
    8. Fabio Busetti & Lorenzo Forni & Andrew Harvey & Fabrizio Venditti, 2007. "Inflation Convergence and Divergence within the European Monetary Union," International Journal of Central Banking, International Journal of Central Banking, vol. 3(2), pages 95-121, June.
    9. Rob Luginbuhl & Siem Jan Koopman, 2003. "Convergence in European GDP Series," Tinbergen Institute Discussion Papers 03-031/4, Tinbergen Institute.
    10. Massimiliano Affinito & Fabio Farabullini, 2009. "Does the Law of One Price Hold in Euro-Area Retail Banking? An Empirical Analysis of Interest Rate Differentials across the Monetary Union," International Journal of Central Banking, International Journal of Central Banking, vol. 5(1), pages 5-37, March.
    11. Massimiliano Affinito & Fabio Farabullini, 2006. "An empirical analysis of national differences in the retail bank interest rates of the euro area," Temi di discussione (Economic working papers) 589, Bank of Italy, Economic Research and International Relations Area.

  37. Harvey, A.C. & Trimbur, T.M. & van Dijk, H.K., 2002. "Cyclical components in economic time series," Econometric Institute Research Papers EI 2002-20, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Harm Bandholz & Gebhard Flaig & Johannes Mayr, 2005. "Growth and economic activity in OECD countries: A long-term perspective," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 58(04), pages 28-36, February.
    2. Harvey, A.C. & Trimbur, T.M. & van Dijk, H.K., 2004. "Bayes estimates of the cyclical component in twentieth centruy US gross domestic product," Econometric Institute Research Papers EI 2004-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Richard Kleijn & Herman K. van Dijk, 2006. "Bayes model averaging of cyclical decompositions in economic time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 191-212, March.
    4. Klaus Abberger & Gebhard Flaig & Wolfgang Nierhaus, 2007. "ifo Konjunkturumfragen und Konjunkturanalyse : ausgewählte methodische Aufsätze aus dem ifo Schnelldienst," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 33.

  38. Harvey, A.C. & Trimbur, T.M., 2001. "General Model-based Filters for Extracting Cycles and Trends in Economic Time Series," Cambridge Working Papers in Economics 0113, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model," Tinbergen Institute Discussion Papers 08-069/4, Tinbergen Institute.
    2. José Luis Cendejas & Félix-Fernando Muñoz & Nadia Fernández-de-Pinedo, 2017. "A contribution to the analysis of historical economic fluctuations (1870–2010): filtering, spurious cycles, and unobserved component modeling," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 11(1), pages 93-125, January.
    3. Kauermann Goeran & Krivobokova Tatyana & Semmler Willi, 2011. "Filtering Time Series with Penalized Splines," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(2), pages 1-28, March.
    4. Álvarez, Luis J. & Gómez-Loscos, Ana, 2018. "A menu on output gap estimation methods," Journal of Policy Modeling, Elsevier, vol. 40(4), pages 827-850.
    5. Matthieu Lemoine, 2006. "Annex A5 : A model of the stochastic convergence between euro area business cycles," Working Papers hal-00972793, HAL.
    6. Trimbur, Thomas M., 2010. "Stochastic level shifts and outliers and the dynamics of oil price movements," International Journal of Forecasting, Elsevier, vol. 26(1), pages 162-179, January.
    7. Claudio Borio & Marco Jacopo Lombardi & Fabrizio Zampolli, 2016. "Fiscal sustainability and the financial cycle," BIS Working Papers 552, Bank for International Settlements.
    8. Mr. Thomas Helbling & Mr. Tamim Bayoumi, 2003. "Are they All in the Same Boat? the 2000-2001 Growth Slowdown and the G-7 Business Cycle Linkages," IMF Working Papers 2003/046, International Monetary Fund.
    9. Robert Dixon & David Shepherd, 2006. "The Cyclical Dynamics and Volatility of Australian Output and Employment," Department of Economics - Working Papers Series 968, The University of Melbourne.
    10. Guido Bulligan & Lorenzo Burlon & Davide Delle Monache & Andrea Silvestrini, 2017. "Real and financial cycles: estimates using unobserved component models for the Italian economy," Questioni di Economia e Finanza (Occasional Papers) 382, Bank of Italy, Economic Research and International Relations Area.
    11. Octavio Fernández-Amador & Martin Gächter & Friedrich Sindermann, 2016. "Finance-augmented business cycles: A robustness check," Economics Bulletin, AccessEcon, vol. 36(1), pages 132-144.
    12. Drew Creal & Siem Jan Koopman & Eric Zivot, 2010. "Extracting a robust US business cycle using a time-varying multivariate model-based bandpass filter," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 695-719.
    13. Alban Moura, 2022. "Why you should never use the Hodrick-Prescott Filter: Comment," BCL working papers 162, Central Bank of Luxembourg.
    14. Nuno Cassola & Claudio Morana, 2006. "Volatility of interest rates in the euro area: Evidence from high frequency data," The European Journal of Finance, Taylor & Francis Journals, vol. 12(6-7), pages 513-528.
    15. Barunik, Jozef & Krehlik, Tomas, 2016. "Measuring the frequency dynamics of financial and macroeconomic connectedness," FinMaP-Working Papers 54, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    16. Siem Jan Koopman & Joao Valle e Azevedo, 2003. "Measuring Synchronisation and Convergence of Business Cycles," Tinbergen Institute Discussion Papers 03-052/4, Tinbergen Institute.
    17. Luati, Alessandra & Proietti, Tommaso, 2009. "Hyper-spherical and Elliptical Stochastic Cycles," MPRA Paper 15169, University Library of Munich, Germany.
    18. Omar H. M. N. Bashar, 2015. "The Trickle‐down Effect of the Mining Boom in Australia: Fact or Myth?," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 94-108, June.
    19. Chen, Xiaoshan & Mills, Terence C., 2009. "Evaluating growth cycle synchronisation in the EU," Economic Modelling, Elsevier, vol. 26(2), pages 342-351, March.
    20. Gebhard Flaig & Timo Wollmershäuser, 2007. "Does the Euro-zone Diverge? A Stress Indicator for Analyzing Trends and Cycles in Real GDP and Inflation," CESifo Working Paper Series 1937, CESifo.
    21. Peter Martey Addo & Monica Billio & Dominique Guegan, 2013. "Turning point chronology for the Euro-Zone: A Distance Plot Approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00803457, HAL.
    22. Siem Jan Koopman & Marius Ooms & Irma Hindrayanto, 2009. "Periodic Unobserved Cycles in Seasonal Time Series with an Application to US Unemployment," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(5), pages 683-713, October.
    23. Martin Larch & João Nogueira Martins, 2007. "Fiscal indicators - Proceedings of the the Directorate-General for Economic and Financial Affairs Workshop held on 22 September 2006 in Brussels," European Economy - Economic Papers 2008 - 2015 297, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    24. Proietti, Tommaso, 2007. "Signal extraction and filtering by linear semiparametric methods," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 935-958, October.
    25. Michal Andrle & Miroslav Plašil, 2016. "System Priors for Econometric Time Series," IMF Working Papers 2016/231, International Monetary Fund.
    26. Alain Noullez & Alessandra Iacobucci, 2004. "A Frequency-selective Filter for Short-Length Time Series," Computing in Economics and Finance 2004 128, Society for Computational Economics.
    27. Perron, Pierre & Wada, Tatsuma, 2009. "Let's take a break: Trends and cycles in US real GDP," Journal of Monetary Economics, Elsevier, vol. 56(6), pages 749-765, September.
    28. Michael Artis & Massimiliano Marcellino & Tommaso Proietti, 2003. "Dating the Euro Area Business Cycle," Working Papers 237, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    29. Christophe Planas & Alessandro Rossi & Gabriele Fiorentini, 2008. "The marginal likelihood of Structural Time Series Models, with application to the euro area and US NAIRU," Working Paper series 21_08, Rimini Centre for Economic Analysis.
    30. Ángel Guillén & Gabriel Rodríguez, 2014. "Trend-cycle decomposition for Peruvian GDP: application of an alternative method," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 23(1), pages 1-44, December.
    31. Gabriele Galati & Irma Hindrayanto & Siem Jan Koopman & Marente Vlekke, 2016. "Measuring Financial Cycles in a Model-Based Analysis: Empirical Evidence for the United States and the Euro Area," Tinbergen Institute Discussion Papers 16-029/III, Tinbergen Institute.
    32. Beate Schirwitz, 2009. "A comprehensive German business cycle chronology," Empirical Economics, Springer, vol. 37(2), pages 287-301, October.
    33. Lechman, Ewa & Dominiak, Piotr, 2016. "Entrepreneurship vulnerability to business cycle. A new methodology for identification pro-cyclical and counter-cyclical patterns of entrepreneurial activity," MPRA Paper 68793, University Library of Munich, Germany.
    34. James Mitchell & Michael Massmann, 2004. "Reconsidering the evidence: are Eurozone business cycles converging?," Money Macro and Finance (MMF) Research Group Conference 2003 67, Money Macro and Finance Research Group.
    35. Didier Nibbering & Richard Paap & Michel van der Wel, 2015. "What Do Professional Forecasters Actually Predict?," Tinbergen Institute Discussion Papers 15-095/III, Tinbergen Institute, revised 13 Oct 2017.
    36. Siem Jan Koopman & Soon Yip Wong, 2006. "Extracting Business Cycles using Semi-parametric Time-varying Spectra with Applications to US Macroeconomic Time Series," Tinbergen Institute Discussion Papers 06-105/4, Tinbergen Institute.
    37. Tucker S. McElroy & Thomas M. Trimbur, 2007. "Continuous time extraction of a nonstationary signal with illustrations in continuous low-pass and band-pass filtering," Finance and Economics Discussion Series 2007-68, Board of Governors of the Federal Reserve System (U.S.).
    38. Pollock, D.S.G., 2006. "Econometric methods of signal extraction," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2268-2292, May.
    39. Alvaro Angeriz & Philip Arestis, 2008. "Assessing inflation targeting through intervention analysis," Oxford Economic Papers, Oxford University Press, vol. 60(2), pages 293-317, April.
    40. Siem Jan Koopman & Rutger Lit & Andre Lucas, 2016. "Model-based Business Cycle and Financial Cycle Decomposition for Europe and the U.S," Tinbergen Institute Discussion Papers 16-051/IV, Tinbergen Institute.
    41. Donadelli, Michael & Paradiso, Antonio, 2014. "Is there heterogeneity in financial integration dynamics? Evidence from country and industry emerging market equity indexes," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 32(C), pages 184-218.
    42. Hessler, Andrew, 2023. "Unobserved components model estimates of credit cycles: Tests and predictions," Journal of Financial Stability, Elsevier, vol. 66(C).
    43. Andrew Harvey, 2002. "Trends, Cycles and Convergence," Working Papers Central Bank of Chile 155, Central Bank of Chile.
    44. Xiaoyi Mu and Haichun Ye, 2015. "Small Trends and Big Cycles in Crude Oil Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    45. Dilip Nachane & Aditi Chaubal, 2022. "A Comparative Evaluation of Some DSP Filters vis-à-vis Commonly Used Economic Filters," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(1), pages 161-190, September.
    46. Donald Robertson & Anthony Garratt & Stephen Wright, 2006. "Permanent vs transitory components and economic fundamentals," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 521-542.
    47. James Morley & Irina B. Panovska & Tara M. Sinclair, 2014. "Testing Stationarity for Unobserved Components Models," Discussion Papers 2012-41B, School of Economics, The University of New South Wales.
    48. Diego J. Pedregal, 2003. "Filter-Design and Model-Based Analysis of Economic Cycles," Economic Working Papers at Centro de Estudios Andaluces E2003/13, Centro de Estudios Andaluces.
    49. Tucker S. McElroy & Thomas M. Trimbur, 2012. "Signal extraction for nonstationary multivariate time series with illustrations for trend inflation," Finance and Economics Discussion Series 2012-45, Board of Governors of the Federal Reserve System (U.S.).
    50. Bashar, Omar H.M.N. & Bhattacharya, Prasad Sankar & Wohar, Mark E., 2017. "The cyclicality of fiscal policy: New evidence from unobserved components approach," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 222-234.
    51. Ahmed Belhadjayed & Grégoire Loeper & Frédéric Abergel, 2016. "Forecasting Trends With Asset Prices," Post-Print hal-01512431, HAL.
    52. Martyna Marczak & Víctor Gómez, 2017. "Monthly US business cycle indicators: a new multivariate approach based on a band-pass filter," Empirical Economics, Springer, vol. 52(4), pages 1379-1408, June.
    53. David Grreasley, 2010. "Cliometrics and Time Series Econometrics: Some Theory and Applications," Working Papers in Economics 10/56, University of Canterbury, Department of Economics and Finance.
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    56. Jozef Barunik & Tomas Krehlik, 2015. "Measuring the frequency dynamics of financial connectedness and systemic risk," Papers 1507.01729, arXiv.org, revised Dec 2017.
    57. Pavel Vidal Alejandro & Lya Paola Sierra Suárez & Johana Sanabria Dominguez & Jaime Andres Collazos Rodríguez, 2015. "Indicador mensual de actividad económica (IMAE) para el Valle del Cauca," Borradores de Economia 900, Banco de la Republica de Colombia.
    58. Kristian Jönsson, 2020. "Cyclical Dynamics and Trend/Cycle Definitions: Comparing the HP and Hamilton Filters," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(2), pages 151-162, November.
    59. Tommaso Proietti, 2009. "Structural Time Series Models for Business Cycle Analysis," Palgrave Macmillan Books, in: Terence C. Mills & Kerry Patterson (ed.), Palgrave Handbook of Econometrics, chapter 9, pages 385-433, Palgrave Macmillan.
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    100. McElroy, Tucker & Sutcliffe, Andrew, 2006. "An iterated parametric approach to nonstationary signal extraction," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2206-2231, May.
    101. Warapong Wongwachara & Anusorn Minphimai, 2009. "Unobserved Component Models of the Phillips Relation in the ASEAN Economy," Journal of Economics and Management, College of Business, Feng Chia University, Taiwan, vol. 5(2), pages 241-256, July.
    102. de Carvalho, Miguel & Rodrigues, Paulo C. & Rua, António, 2012. "Tracking the US business cycle with a singular spectrum analysis," Economics Letters, Elsevier, vol. 114(1), pages 32-35.
    103. Xiaoshan Chen & Terence Mills, 2012. "Measuring the Euro area output gap using a multivariate unobserved components model containing phase shifts," Empirical Economics, Springer, vol. 43(2), pages 671-692, October.
    104. Arturo Estrella, 2007. "Extracting business cycle fluctuations: what do time series filters really do?," Staff Reports 289, Federal Reserve Bank of New York.
    105. Heijmans, Roweno J.R.K. & Gerlagh, Reyer, 2019. "Regulating Global Externalities," Discussion Paper 2019-001, Tilburg University, Center for Economic Research.
    106. Sandra Bilek-Steindl, 2011. "On the Change in the Austrian Business Cycle," WIFO Working Papers 384, WIFO.
    107. Galimberti, Jaqueson K. & Moura, Marcelo L., 2016. "Improving the reliability of real-time output gap estimates using survey forecasts," International Journal of Forecasting, Elsevier, vol. 32(2), pages 358-373.
    108. Andrew Lee-Poy, 2018. "Characterizing the Canadian Financial Cycle with Frequency Filtering Approaches," Staff Analytical Notes 2018-34, Bank of Canada.
    109. Gabriel RODRIGUEZ, 2010. "Estimating Output Gap, Core Inflation, And The Nairu For Peru, 1979-2007," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 10(1).
    110. Mark W. Watson, 2007. "How accurate are real-time estimates of output trends and gaps?," Economic Quarterly, Federal Reserve Bank of Richmond, vol. 93(Spr), pages 143-161.
    111. Rafael Doménech & Víctor Gómez, 2005. "Ciclo económico y desempleo estructural en la economía española," Investigaciones Economicas, Fundación SEPI, vol. 29(2), pages 259-288, May.
    112. Beate Schirwitz & Christian Seiler & Klaus Wohlrabe, 2009. "Regional business cycles in Germany - the dating problem," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(14), pages 24-31, July.
    113. Apergis, Nicholas & Lau, Marco Chi Keung, 2015. "Structural breaks and electricity prices: Further evidence on the role of climate policy uncertainties in the Australian electricity market," Energy Economics, Elsevier, vol. 52(PA), pages 176-182.
    114. Harvey, A., 2008. "Modeling the Phillips curve with unobserved components," Cambridge Working Papers in Economics 0805, Faculty of Economics, University of Cambridge.
    115. Rodrigo Barbone Gonzalez & Joaquim Lima & Leonardo Marinho, 2015. "Countercyclical Capital Buffers: bayesian estimates and alternatives focusing on credit growth," Working Papers Series 384, Central Bank of Brazil, Research Department.
    116. Thomas M. Trimbur, 2006. "Detrending economic time series: a Bayesian generalization of the Hodrick-Prescott filter," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(4), pages 247-273.
    117. Tobias Hartl & Rolf Tschernig & Enzo Weber, 2020. "Fractional trends and cycles in macroeconomic time series," Papers 2005.05266, arXiv.org, revised May 2020.
    118. Hall, Viv B & Thomson, Peter, 2022. "A boosted HP filter for business cycle analysis: evidence from New Zealand’s small open economy," Working Paper Series 21184, Victoria University of Wellington, School of Economics and Finance.
    119. Apergis, Nicholas, 2015. "Financial portfolio choice: Do business cycle regimes matter? Panel evidence from international household surveys," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 34(C), pages 14-27.
    120. Pelagatti, Matteo M., 2011. "State Space Methods in Ox/SsfPack," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 41(i03).
    121. Łukasz Lenart & Mateusz Pipień, 2017. "Non-Parametric Test for the Existence of the Common Deterministic Cycle: The Case of the Selected European Countries," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(3), pages 201-241, September.
    122. Stephen Pollock, 2005. "Econometric Methods of Signal Extraction," Working Papers 530, Queen Mary University of London, School of Economics and Finance.
    123. Fabio Busetti & Michele Caivano, 2016. "The trend–cycle decomposition of output and the Phillips curve: Bayesian estimates for Italy and the Euro area," Empirical Economics, Springer, vol. 50(4), pages 1565-1587, June.
    124. De la Serve, M-E. & Lemoine, M., 2011. "Measuring the NAIRU: a complementary approach," Working papers 342, Banque de France.
    125. Fritz, Marlon, 2019. "Steady state adjusting trends using a data-driven local polynomial regression," Economic Modelling, Elsevier, vol. 83(C), pages 312-325.
    126. Rodríguez, Gabriel, 2009. "Estimating Output Gap, Core Inflation, and the NAIRU for Peru," Working Papers 2009-011, Banco Central de Reserva del Perú.
    127. Agnieszka Gehringer & Thomas Mayer, 2021. "Measuring the Business Cycle Chronology with a Novel Business Cycle Indicator for Germany," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 71-89, April.
    128. Ciccarelli, Carlo & Fenoaltea, Stefano, 2007. "Business fluctuations in Italy, 1861-1913: The new evidence," Explorations in Economic History, Elsevier, vol. 44(3), pages 432-451, July.
    129. Oh, Kum Hwa & Zivot, Eric & Creal, Drew, 2008. "The relationship between the Beveridge-Nelson decomposition and other permanent-transitory decompositions that are popular in economics," Journal of Econometrics, Elsevier, vol. 146(2), pages 207-219, October.
    130. Matteo M. Pelagatti, 2005. "Business cycle and sector cycles," Econometrics 0503006, University Library of Munich, Germany.
    131. João Valle e Azevedo, 2007. "A Multivariate Band-Pass Filter," Working Papers w200717, Banco de Portugal, Economics and Research Department.
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  39. Jared Bernstein & Andrew Harvey, 2000. "Measurement and Testing of Inequality from Time Series of Deciles with an Application to U.S. Wages," Econometric Society World Congress 2000 Contributed Papers 0861, Econometric Society.

    Cited by:

    1. Alvaro Angeriz & Philip Arestis, 2008. "Assessing inflation targeting through intervention analysis," Oxford Economic Papers, Oxford University Press, vol. 60(2), pages 293-317, April.
    2. Higson, C. & Holly, S. & Kattuman, P. & S. Platis, 2001. "The Business Cycle, Macroeconomic Shocks and the Cross Section: The Growth of UK Quoted Companies," Cambridge Working Papers in Economics 0114, Faculty of Economics, University of Cambridge.
    3. Busettti, F. & Harvey, A., 2007. "Tests of time-invariance," Cambridge Working Papers in Economics 0701, Faculty of Economics, University of Cambridge.
    4. Tommaso Proietti, 2005. "Convergence in Italian regional per-capita GDP," Applied Economics, Taylor & Francis Journals, vol. 37(5), pages 497-506.
    5. Abraham, David & Barkai, Simcha, 2022. "Low wages aren't a growing problem," Working Papers 322, The University of Chicago Booth School of Business, George J. Stigler Center for the Study of the Economy and the State.
    6. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.

  40. A. C. Harvey & Siem Jan Koopman, 2000. "Computing Observation Weights for Signal Extraction and Filtering," Econometric Society World Congress 2000 Contributed Papers 0888, Econometric Society.

    Cited by:

    1. Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model," Tinbergen Institute Discussion Papers 08-069/4, Tinbergen Institute.
    2. Roberta Serafini & J. Bruha & B. Pierluigi, 2011. "Euro area labour markets: different reaction to shocks?," EcoMod2011 2970, EcoMod.
    3. Andrés González Gómez & Lavan Mahadeva & Diego Rodríguez & Luis Eduardo Rojas, 2009. "Monetary Policy Forecasting in a DSGE Model with Data that is Uncertain, Unbalanced and About the Future," Borradores de Economia 559, Banco de la Republica de Colombia.
    4. Terence Mills, 2007. "A Note on Trend Decomposition: The 'Classical' Approach Revisited with an Application to Surface Temperature Trends," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(8), pages 963-972.
    5. Robert J. Hill & Alicia N. Rambaldi & Michael Scholz, 2018. "Higher Frequency Hedonic Property Price Indices: A State Space Approach," Graz Economics Papers 2018-04, University of Graz, Department of Economics.
    6. Delle Monache, Davide & Petrella, Ivan, 2019. "Efficient Matrix Approach for Classical Inference in State Space Models," EMF Research Papers 19, Economic Modelling and Forecasting Group.
    7. Marc Francke, 2010. "Repeat Sales Index for Thin Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 41(1), pages 24-52, July.
    8. Siem Jan Koopman & Marius Ooms & Irma Hindrayanto, 2009. "Periodic Unobserved Cycles in Seasonal Time Series with an Application to US Unemployment," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(5), pages 683-713, October.
    9. Proietti, Tommaso, 2007. "Signal extraction and filtering by linear semiparametric methods," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 935-958, October.
    10. Raïsa Basselier & David Antonio Liedo & Geert Langenus, 2018. "Nowcasting Real Economic Activity in the Euro Area: Assessing the Impact of Qualitative Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 1-46, April.
    11. Dennis Kant & Andreas Pick & Jasper de Winter, 2022. "Nowcasting GDP using machine learning methods," Working Papers 754, DNB.
    12. Scotti, Chiara, 2016. "Surprise and uncertainty indexes: Real-time aggregation of real-activity macro-surprises," Journal of Monetary Economics, Elsevier, vol. 82(C), pages 1-19.
    13. Danilo Leiva-Leon & Lorenzo Ductor, 2019. "Fluctuations in Global Macro Volatility," ThE Papers 19/09, Department of Economic Theory and Economic History of the University of Granada..
    14. Poncela Blanco, Maria Pilar & Ruiz Ortega, Esther & Miranda Gualdrón, Karen Alejandra, 2020. "Factor extraction using Kalman filter and smoothing: this is not just another survey," DES - Working Papers. Statistics and Econometrics. WS 30644, Universidad Carlos III de Madrid. Departamento de Estadística.
    15. Angelini, Elena & Camba-Méndez, Gonzalo & Rünstler, Gerhard & Giannone, Domenico & Reichlin, Lucrezia, 2008. "Short-term forecasts of euro area GDP growth," Working Paper Series 949, European Central Bank.
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    25. Thomas Gilbert & Chiara Scotti & Georg H. Strasser & Clara Vega, 2015. "Is the Intrinsic Value of Macroeconomic News Announcements Related to Their Asset Price Impact?," Boston College Working Papers in Economics 874, Boston College Department of Economics, revised 23 Apr 2015.
    26. Tallman, Ellis W. & Zaman, Saeed, 2017. "Forecasting inflation: Phillips curve effects on services price measures," International Journal of Forecasting, Elsevier, vol. 33(2), pages 442-457.
    27. Rünstler, Gerhard & Bańbura, Marta, 2007. "A look into the factor model black box: publication lags and the role of hard and soft data in forecasting GDP," Working Paper Series 751, European Central Bank.
    28. Luis E. Rojas, 2011. "Professional Forecasters: How to Understand and Exploit Them Through a DSGE Model," Borradores de Economia 664, Banco de la Republica de Colombia.
    29. Deicy J. Cristiano-Botia & Manuel Dario Hernandez-Bejarano & Mario A. Ramos-Veloza, 2021. "Labor Market Indicator for Colombia (LMI)," Borradores de Economia 1152, Banco de la Republica de Colombia.
    30. Alain Galli, 2018. "Which Indicators Matter? Analyzing the Swiss Business Cycle Using a Large-Scale Mixed-Frequency Dynamic Factor Model," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(2), pages 179-218, November.
    31. Dias, Maria Helena Ambrosio & Dias, Joilson, 2010. "Measuring the Cyclical Component of a Time Series: a New Proposed Methodology," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 30(1), October.
    32. Harvey, Andrew & Oryshchenko, Vitaliy, 2012. "Kernel density estimation for time series data," International Journal of Forecasting, Elsevier, vol. 28(1), pages 3-14.
    33. Ductor, Lorenzo & Leiva-León, Danilo, 2022. "Fluctuations in global output volatility," Journal of International Money and Finance, Elsevier, vol. 120(C).
    34. Tóth, Máté, 2021. "A multivariate unobserved components model to estimate potential output in the euro area: a production function based approach," Working Paper Series 2523, European Central Bank.
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    39. Roberto Iannaccone & Edoardo Otranto, 2003. "Signal Extraction in Continuous Time and the Generalized Hodrick- Prescott Filter," Econometrics 0311002, University Library of Munich, Germany.
    40. Claudio Borio & Piti Disyatat & Mikael Juselius, 2014. "A parsimonious approach to incorporating economic information in measures of potential output," BIS Working Papers 442, Bank for International Settlements.
    41. Angelini, Elena & Rünstler, Gerhard & Bańbura, Marta, 2008. "Estimating and forecasting the euro area monthly national accounts from a dynamic factor model," Working Paper Series 953, European Central Bank.
    42. Sbrana, Giacomo & Silvestrini, Andrea, 2022. "Random coefficient state-space model: Estimation and performance in M3–M4 competitions," International Journal of Forecasting, Elsevier, vol. 38(1), pages 352-366.
    43. Andrle, Michal, 2012. "Understanding DSGE Filters in Forecasting and Policy Analysis," Dynare Working Papers 16, CEPREMAP.
    44. Long, Wen & Zhao, Manyi & Tang, Yeran, 2021. "Can the Chinese volatility index reflect investor sentiment?," International Review of Financial Analysis, Elsevier, vol. 73(C).
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    49. Andrew C. Harvey & Thomas M. Trimbur, 2003. "General Model-Based Filters for Extracting Cycles and Trends in Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 244-255, May.
    50. Weinert, Howard L., 2007. "Efficient computation for Whittaker-Henderson smoothing," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 959-974, October.
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    1. Yicong Lin & Hanno Reuvers, 2019. "Efficient Estimation by Fully Modified GLS with an Application to the Environmental Kuznets Curve," Papers 1908.02552, arXiv.org, revised Aug 2020.
    2. Won-Ki Seo, 2020. "Functional Principal Component Analysis for Cointegrated Functional Time Series," Papers 2011.12781, arXiv.org, revised Apr 2023.
    3. Aizenman, Joshua & Jinjarak, Yothin, 2009. "Current account patterns and national real estate markets," Journal of Urban Economics, Elsevier, vol. 66(2), pages 75-89, September.
    4. Tucker McElroy & Michael W. McCracken, 2017. "Multistep ahead forecasting of vector time series," Econometric Reviews, Taylor & Francis Journals, vol. 36(5), pages 495-513, May.
    5. Auci, Sabrina & Becchetti, Leonardo, 2006. "The instability of the adjusted and unadjusted environmental Kuznets curves," Ecological Economics, Elsevier, vol. 60(1), pages 282-298, November.
    6. Ricardo Batista Politi & Enlinson Mattos, 2011. "Ad-valorem tax incidence and after-tax price adjustments: evidence from Brazilian basic basket food," Canadian Journal of Economics, Canadian Economics Association, vol. 44(4), pages 1438-1470, November.
    7. Zanetti Chini, Emilio, 2010. "Does the purchasing power parity hypothesis hold after 1998?," MPRA Paper 27225, University Library of Munich, Germany.
    8. Giorgio Canarella & Rangan Gupta & Stephen M. Miller & Stephen K. Pollard, 2017. "Unemployment Rate Hysteresis and the Great Recession: Exploring the Metropolitan Evidence," Working Papers 201740, University of Pretoria, Department of Economics.
    9. Morten Ørregaard Nielsen, 2005. "Multivariate Lagrange Multiplier Tests for Fractional Integration," Journal of Financial Econometrics, Oxford University Press, vol. 3(3), pages 372-398.
    10. Apergis, Nicholas & Fafaliou, Irene & Stefanitsis, Marinos, 2016. "Asymmetric information and employment: evidence from the U.S. banking sector," The Journal of Economic Asymmetries, Elsevier, vol. 14(PB), pages 199-210.
    11. Harvey, A. & Vasco Carvalho, 2002. "Models for Converging Economies," Cambridge Working Papers in Economics 0216, Faculty of Economics, University of Cambridge.
    12. Kongsted, Hans Christian, 2005. "Testing the nominal-to-real transformation," Journal of Econometrics, Elsevier, vol. 124(2), pages 205-225, February.
    13. Haldrup, Niels, "undated". "Empirical analysis of price data in the delineation of the relevant geographical market in competition analysis," Economics Working Papers 2003-9, Department of Economics and Business Economics, Aarhus University.
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    16. Tucker S McElroy & Agnieszka Jach, 2019. "Testing collinearity of vector time series," The Econometrics Journal, Royal Economic Society, vol. 22(2), pages 97-116.
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    18. Poncela Blanco, Maria Pilar & Ruiz Ortega, Esther & Miranda Gualdrón, Karen Alejandra, 2020. "Factor extraction using Kalman filter and smoothing: this is not just another survey," DES - Working Papers. Statistics and Econometrics. WS 30644, Universidad Carlos III de Madrid. Departamento de Estadística.
    19. Busettti, F. & Harvey, A., 2007. "Tests of time-invariance," Cambridge Working Papers in Economics 0701, Faculty of Economics, University of Cambridge.
    20. Giancarlo Bruno & Marco Malgarini, 2002. "An Indicator of Economic Sentiment for the Italian Economy," ISAE Working Papers 28, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    21. Majid M. Al-Sadoon, 2015. "A General Theory of Rank Testing," Working Papers 750, Barcelona School of Economics.
    22. Khraief, Naceur & Shahbaz, Muhammad & Heshmati, Almas & Azam, Muhammad, 2015. "Are Unemployment Rates in OECD Countries Stationary? Evidence from Univariate and Panel Unit Root Tests," IZA Discussion Papers 9571, Institute of Labor Economics (IZA).
    23. Javier Gómez Biscarri & Javier Hualde, 2014. "Regression-based analysis of cointegration systems," Working Papers 780, Barcelona School of Economics.
    24. Tucker S. McElroy & Thomas M. Trimbur, 2012. "Signal extraction for nonstationary multivariate time series with illustrations for trend inflation," Finance and Economics Discussion Series 2012-45, Board of Governors of the Federal Reserve System (U.S.).
    25. Arvid Raknerud, 2001. "A State Space Approach for Estimating VAR Models for Panel Data with Latent Dynamic Components," Discussion Papers 295, Statistics Norway, Research Department.
    26. Jen-Je Su, 2003. "On the power of the multivariate KPSS test of stationarity against fractionally integrated alternatives," Applied Economics Letters, Taylor & Francis Journals, vol. 10(10), pages 637-641.
    27. Aizenman, Joshua & Pasricha, Gurnain Kaur, 2010. "Selective swap arrangements and the global financial crisis: Analysis and interpretation," International Review of Economics & Finance, Elsevier, vol. 19(3), pages 353-365, June.
    28. Focardi, Sergio M. & Fabozzi, Frank J. & Mitov, Ivan K., 2016. "A new approach to statistical arbitrage: Strategies based on dynamic factor models of prices and their performance," Journal of Banking & Finance, Elsevier, vol. 65(C), pages 134-155.
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    30. Müller, Ulrich K. & Watson, Mark W., 2013. "Low-frequency robust cointegration testing," Journal of Econometrics, Elsevier, vol. 174(2), pages 66-81.
    31. Morten {O}rregaard Nielsen & Won-Ki Seo & Dakyung Seong, 2023. "Inference on common trends in functional time series," Papers 2312.00590, arXiv.org, revised Dec 2023.
    32. Al-Sadoon, Majid M., 2017. "A unifying theory of tests of rank," Journal of Econometrics, Elsevier, vol. 199(1), pages 49-62.
    33. Shahriyar Mukhtarov & Sugra Humbatova & Natig Gadim-Oglu Hajiyev, 2021. "Is the Transition to Renewable Energy Consumption Hampered by High Oil Prices?," International Journal of Energy Economics and Policy, Econjournals, vol. 11(5), pages 377-380.
    34. MAGAZZINO, Cosimo & LEOGRANDE, Angelo, 2021. "Subjective Well-Being In Italian Regions: A Panel Data Approach," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 21(1), pages 1-18.
    35. James Morley & Tara M. Sinclair, 2005. "Testing for Stationarity and Cointegration in an Unobserved Components Framework," Computing in Economics and Finance 2005 451, Society for Computational Economics.
    36. Tommaso Proietti, 2005. "Convergence in Italian regional per-capita GDP," Applied Economics, Taylor & Francis Journals, vol. 37(5), pages 497-506.
    37. Riccardo Corradini, 2005. "An Empirical Analysis of Permanent Income Hypothesis Applied to Italy using State Space Models with non zero correlation between trend and cycle," Econometrics 0509009, University Library of Munich, Germany.
    38. Avalos, Roger & Fitzgerald, Timothy & Rucker, Randal R., 2016. "Measuring the effects of natural gas pipeline constraints on regional pricing and market integration," Energy Economics, Elsevier, vol. 60(C), pages 217-231.
    39. González-Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2023. "Modelling intervals of minimum/maximum temperatures in the Iberian Peninsula," DES - Working Papers. Statistics and Econometrics. WS 37968, Universidad Carlos III de Madrid. Departamento de Estadística.
    40. Nicholas Apergis & Beatrice D. Simo-Kengne & Rangan Gupta & Tsangyao Chang, 2013. "The Dynamic Relationship between House Prices and Output: Evidence from US Metropolitan Statistical Areas," Working Papers 201349, University of Pretoria, Department of Economics.
    41. Portier, Franck & Beaudry, Paul, 2003. "Stock Prices, News and Economic Fluctuations," CEPR Discussion Papers 3844, C.E.P.R. Discussion Papers.
    42. Fabio Busetti & A. M. Robert Taylor, 2003. "Testing against stochastic trend and seasonality in the presence of unattended breaks and unit roots," Temi di discussione (Economic working papers) 470, Bank of Italy, Economic Research and International Relations Area.
    43. Chen, Xiaoshan & MacDonald, Ronald, 2014. "Measuring the Euro-Dollar Permanent Equilibrium Exchange Rate using the Unobserved Components Model," SIRE Discussion Papers 2015-05, Scottish Institute for Research in Economics (SIRE).
    44. Karmous, Aida & Boubaker, Heni & Belkacem, Lotfi, 2019. "A dynamic factor model with stylized facts to forecast volatility for an optimal portfolio," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    45. Guglielmo Maria Caporale & Marinko Skare, 2011. "Employment Growth, Inflation and Output Growth: Was Phillips Right?: Evidence from a Dynamic Panel," Discussion Papers of DIW Berlin 1138, DIW Berlin, German Institute for Economic Research.
    46. Tommaso, Proietti & Alessandra, Luati, 2012. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," MPRA Paper 39600, University Library of Munich, Germany.
    47. Jönsson, Kristian, 2004. "Testing for Stationarity in Panel Data Models when Disturbances are Cross-Sectionally Correlated," Working Papers 2004:17, Lund University, Department of Economics, revised 26 Nov 2004.
    48. Hubrich, Kirstin & Lütkepohl, Helmut & Saikkonen, Pentti, 1998. "A review of systemscointegration tests," SFB 373 Discussion Papers 1998,101, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    49. Mikayilov, Jeyhun I. & Darandary, Abdulelah & Alyamani, Ryan & Hasanov, Fakhri J. & Alatawi, Hatem, 2020. "Regional heterogeneous drivers of electricity demand in Saudi Arabia: Modeling regional residential electricity demand," Energy Policy, Elsevier, vol. 146(C).
    50. Hans Christian Kongsted, 2002. "Testing the Nominal-to-Real Transformation," Discussion Papers 02-06, University of Copenhagen. Department of Economics.
    51. Choi, Chi-Young, 2004. "Searching for evidence of long-run PPP from a post-Bretton Woods panel: separating the wheat from the chaff," Journal of International Money and Finance, Elsevier, vol. 23(7-8), pages 1159-1186.
    52. Ralf Brüggemann, 2006. "Sources of German unemployment: a structural vector error correction analysis," Empirical Economics, Springer, vol. 31(2), pages 409-431, June.
    53. El Montasser, Ghassen, 2014. "The seasonal KPSS Test: some extensions and further results," MPRA Paper 54920, University Library of Munich, Germany.
    54. Jeyhun I. Mikayilov & Shahriyar Mukhtarov & Jeyhun Mammadov, 2020. "Gasoline Demand Elasticities at the Backdrop of Lower Oil Prices: Fuel-Subsidizing Country Case," Energies, MDPI, vol. 13(24), pages 1-18, December.
    55. Josep Lluís Carrion‐i‐Silvestre & Andreu Sansó, 2006. "Testing the Null of Cointegration with Structural Breaks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(5), pages 623-646, October.
    56. Carvalho, Vasco M. & Harvey, Andrew C., 2005. "Growth, cycles and convergence in US regional time series," International Journal of Forecasting, Elsevier, vol. 21(4), pages 667-686.
    57. Pelagatti, Matteo M. & Sen, Pranab K., 2013. "Rank tests for short memory stationarity," Journal of Econometrics, Elsevier, vol. 172(1), pages 90-105.
    58. Di Casola, Paola & Sichlimiris, Spyridon, 2020. "TFP news, stock market booms and the business cycle: Revisiting the evidence with VEC models," Working Paper Series 388, Sveriges Riksbank (Central Bank of Sweden).
    59. Shahriyar Mukhtarov & Jeyhun I. Mikayilov & Sugra Humbatova & Vugar Muradov, 2020. "Do High Oil Prices Obstruct the Transition to Renewable Energy Consumption?," Sustainability, MDPI, vol. 12(11), pages 1-16, June.
    60. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2019. "Co-integration and common trends analysis with score-driven models : an application to the federal funds effective rate and US inflation rate," UC3M Working papers. Economics 28451, Universidad Carlos III de Madrid. Departamento de Economía.
    61. John T. Barkoulas & Christopher F. Baum & Atreya Chakraborty, 2000. "Forward Premiums and Market Efficiency: Panel Unit-root Evidence from the Term Structure of Forward Premiums," Boston College Working Papers in Economics 461, Boston College Department of Economics, revised 13 Jun 2001.
    62. Guilhem Bentoglio & Jacky Fayolle & Matthieu Lemoine, 2001. "Unité et pluralité du cycle européen," Revue de l'OFCE, Presses de Sciences-Po, vol. 78(3), pages 9-73.
    63. Søren Johansen, 2014. "Times Series: Cointegration," CREATES Research Papers 2014-38, Department of Economics and Business Economics, Aarhus University.
    64. Fabio Busetti, 2006. "Tests of seasonal integration and cointegration in multivariate unobserved component models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 419-438, May.
    65. Auld, T., 2022. "Betting and financial markets are cointegrated on election night," Cambridge Working Papers in Economics 2263, Faculty of Economics, University of Cambridge.
    66. Esa Mangeloja, 2003. "Structural testing of Business Cycles," Macroeconomics 0308004, University Library of Munich, Germany.
    67. Jukka Nyblom & Andrew Harvey, 2001. "Testing against smooth stochastic trends," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 415-429.
    68. Jansson, Michael, 2004. "Stationarity Testing With Covariates," Econometric Theory, Cambridge University Press, vol. 20(1), pages 56-94, February.
    69. Lorenzo Lucchese & Mikko Pakkanen & Almut Veraart, 2022. "The Short-Term Predictability of Returns in Order Book Markets: a Deep Learning Perspective," Papers 2211.13777, arXiv.org, revised Oct 2023.
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    71. Ghassen El Montasser, 2015. "The Seasonal KPSS Test: Examining Possible Applications with Monthly Data and Additional Deterministic Terms," Econometrics, MDPI, vol. 3(2), pages 1-16, May.
    72. Rath, Deba Prasad & Misra, Biswa Swarup, 2006. "Examining Sustainability of Federal Finances in India: An Application of Non-stationary Panel Methods," MPRA Paper 21894, University Library of Munich, Germany.
    73. Nyblom, Jukka, 2001. "Invariant Tests for Covariance Structures in Multivariate Linear Model," Journal of Multivariate Analysis, Elsevier, vol. 76(2), pages 294-315, February.
    74. Ai, Xiaohui & Li, Wenbo V. & Liu, Guoqing, 2012. "Karhunen–Loeve expansions for the detrended Brownian motion," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1235-1241.
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  42. Harvey, A.C. & Koopman, S.J.M., 1999. "Signal Extraction and the Formulation of Unobserved Components Models," Discussion Paper 1999-44, Tilburg University, Center for Economic Research.

    Cited by:

    1. Chin Nam Low & Heather Anderson & Ralph Snyder, 2006. "Beverridge Nelson Decomposition With Markov Switching," CAMA Working Papers 2006-18, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. Tommaso PROIETTI, 2002. "Some Reflections on Trend-Cycle Decompositions with Correlated Components," Economics Working Papers ECO2002/23, European University Institute.
    3. Breitung, Jorg & Hafner, Christian, 2016. "A simple model for now-casting volatility series," LIDAM Reprints ISBA 2016040, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. Rob J Hyndman & Maxwell L. King & Ivet Pitrun & Baki Billah, 2002. "Local Linear Forecasts Using Cubic Smoothing Splines," Monash Econometrics and Business Statistics Working Papers 10/02, Monash University, Department of Econometrics and Business Statistics.
    5. Marc Francke, 2010. "Repeat Sales Index for Thin Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 41(1), pages 24-52, July.
    6. Siem Jan Koopman & Marius Ooms & Irma Hindrayanto, 2009. "Periodic Unobserved Cycles in Seasonal Time Series with an Application to US Unemployment," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(5), pages 683-713, October.
    7. Proietti, Tommaso, 2007. "Signal extraction and filtering by linear semiparametric methods," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 935-958, October.
    8. Amy Y. Guisinger & Michael T. Owyang & Daniel Soques, 2020. "Industrial Connectedness and Business Cycle Comovements," Working Papers 2020-052, Federal Reserve Bank of St. Louis, revised 04 Aug 2021.
    9. Neil Shephard, 2013. "Martingale unobserved component models," Economics Papers 2013-W01, Economics Group, Nuffield College, University of Oxford.
    10. James Mitchell & Michael Massmann, 2004. "Reconsidering the evidence: are Eurozone business cycles converging?," Money Macro and Finance (MMF) Research Group Conference 2003 67, Money Macro and Finance Research Group.
    11. Luis Uzeda, 2018. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Staff Working Papers 18-14, Bank of Canada.
    12. Busettti, F. & Harvey, A., 2007. "Tests of time-invariance," Cambridge Working Papers in Economics 0701, Faculty of Economics, University of Cambridge.
    13. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
    14. Chen, Yen-Hsiao & Quan, Lianfeng & Liu, Yang, 2013. "An empirical investigation on the temporal properties of China's GDP," China Economic Review, Elsevier, vol. 27(C), pages 69-81.
    15. Heather M. Anderson & Chin Nam Low & Ralph Snyder, 2005. "Single source of error state space approach to the Beveridge Nelson decomposition," CAMA Working Papers 2005-11, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    16. Siem Jan Koopman & Charles S. Bos, 2002. "Time Series Models with a Common Stochastic Variance for Analysing Economic Time Series," Tinbergen Institute Discussion Papers 02-113/4, Tinbergen Institute.
    17. Charles S. Bos & Neil Shephard, 2004. "Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space form," Tinbergen Institute Discussion Papers 04-015/4, Tinbergen Institute.
    18. J Keith Ord & Ralph D Snyder & Anne B Koehler & Rob J Hyndman & Mark Leeds, 2005. "Time Series Forecasting: The Case for the Single Source of Error State Space," Monash Econometrics and Business Statistics Working Papers 7/05, Monash University, Department of Econometrics and Business Statistics.
    19. Victor M. Guerrero, 2008. "Estimating Trends with Percentage of Smoothness Chosen by the User," International Statistical Review, International Statistical Institute, vol. 76(2), pages 187-202, August.
    20. Tommaso Proietti, 2021. "Predictability, real time estimation, and the formulation of unobserved components models," Econometric Reviews, Taylor & Francis Journals, vol. 40(5), pages 433-454, April.
    21. Philip Kostov & John Lingard, 2004. "Recurrence analysis techniques for non-stationary and non-linear data," Microeconomics 0409003, University Library of Munich, Germany.
    22. Koopman, Siem Jan & Harvey, Andrew, 2003. "Computing observation weights for signal extraction and filtering," Journal of Economic Dynamics and Control, Elsevier, vol. 27(7), pages 1317-1333, May.
    23. Tommaso Proietti, 2007. "Band Spectral Estimation for Signal Extraction," CEIS Research Paper 104, Tor Vergata University, CEIS.
    24. Gary Koop & Simon M. Potter, 2007. "A flexible approach to parametric inference in nonlinear time series models," Staff Reports 285, Federal Reserve Bank of New York.
    25. Ralph D. Snyder, 2004. "Exponential Smoothing: A Prediction Error Decomposition Principle," Monash Econometrics and Business Statistics Working Papers 15/04, Monash University, Department of Econometrics and Business Statistics.
    26. Harvey, A.C. & Trimbur, T.M. & van Dijk, H.K., 2004. "Bayes estimates of the cyclical component in twentieth centruy US gross domestic product," Econometric Institute Research Papers EI 2004-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    27. Koop, Gary & Tobias, Justin L., 2006. "Semiparametric Bayesian inference in smooth coefficient models," Journal of Econometrics, Elsevier, vol. 134(1), pages 283-315, September.
    28. Mardi Dungey & Jan P.A.M. Jacobs & Jing Jian & Simon van Norden, 2013. "Trend-Cycle Decomposition: Implications from an Exact Structural Identification," CIRANO Working Papers 2013s-23, CIRANO.
    29. Ralph D Snyder, 2005. "A Pedant's Approach to Exponential Smoothing," Monash Econometrics and Business Statistics Working Papers 5/05, Monash University, Department of Econometrics and Business Statistics.
    30. Sbrana, Giacomo & Silvestrini, Andrea, 2020. "Forecasting with the damped trend model using the structural approach," International Journal of Production Economics, Elsevier, vol. 226(C).
    31. Kum Hwa Oh & Eric Zivot & Drew Creal, 2006. "The Relationship between the Beveridge-Nelson Decomposition andUnobserved Component Models with Correlated Shocks," Working Papers UWEC-2006-16-FC, University of Washington, Department of Economics.
    32. Cain, P.M., 2022. "Modelling short-and long-term marketing effects in the consumer purchase journey," International Journal of Research in Marketing, Elsevier, vol. 39(1), pages 96-116.
    33. DeRossi, G. & Harvey, A., 2007. "Quantiles, Expectiles and Splines," Cambridge Working Papers in Economics 0660, Faculty of Economics, University of Cambridge.
    34. Tommaso Proietti, 2006. "Measuring Core Inflation by Multivariate Structural Time Series Models," CEIS Research Paper 83, Tor Vergata University, CEIS.
    35. Franses, Ph.H.B.F., 2019. "IMA(1,1) as a new benchmark for forecast evaluation," Econometric Institute Research Papers EI2019-28, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    36. Thomas M. Trimbur, 2006. "Detrending economic time series: a Bayesian generalization of the Hodrick-Prescott filter," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(4), pages 247-273.
    37. A. Peyrache & A. N. Rambaldi, 2017. "Incorporating temporal and country heterogeneity in growth accounting—an application to EU-KLEMS," Journal of Productivity Analysis, Springer, vol. 47(2), pages 143-166, April.
    38. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.
    39. Thomas B. King, 2005. "Labor productivity and job-market flows: trends, cycles, and correlations," Supervisory Policy Analysis Working Papers 2005-04, Federal Reserve Bank of St. Louis.
    40. Gary Koop & Simon Potter, 2010. "A flexible approach to parametric inference in nonlinear and time varying time series models," Post-Print hal-00732535, HAL.
    41. B. Jungbacker & S.J. Koopman, 2005. "Model-based Measurement of Actual Volatility in High-Frequency Data," Tinbergen Institute Discussion Papers 05-002/4, Tinbergen Institute.
    42. Paul Alagidede, 2012. "Trends And Cycles In The Net Barter Terms Of Trade For Sub-Saharan Africa's Primary Commodity Exporters," Journal of Developing Areas, Tennessee State University, College of Business, vol. 46(2), pages 213-229, July-Dece.
    43. Oh, Kum Hwa & Zivot, Eric & Creal, Drew, 2008. "The relationship between the Beveridge-Nelson decomposition and other permanent-transitory decompositions that are popular in economics," Journal of Econometrics, Elsevier, vol. 146(2), pages 207-219, October.
    44. Alicia N. Rambaldi & Ryan R. J. McAllister & Cameron S. Fletcher, 2015. "Decoupling land values in residential property prices: smoothing methods for hedonic imputed price indices," Discussion Papers Series 549, School of Economics, University of Queensland, Australia.

  43. Busetti, Fabio & Harvey, Andrew, 1998. "Testing for the presence of a random walk in series with structural breaks," LSE Research Online Documents on Economics 6870, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Tommaso Proietti & Alberto Musso, 2012. "Growth accounting for the euro area," Empirical Economics, Springer, vol. 43(1), pages 219-244, August.
    2. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2013. "Testing for unit roots in the possible presence of multiple trend breaks using minimum Dickey–Fuller statistics," Journal of Econometrics, Elsevier, vol. 177(2), pages 265-284.
    3. Cavaliere, Giuseppe & Taylor, A.M. Robert, 2008. "Testing for a change in persistence in the presence of non-stationary volatility," Journal of Econometrics, Elsevier, vol. 147(1), pages 84-98, November.
    4. Elliott, Graham & Muller, Ulrich K., 2004. "Confidence Sets for the Date of a Single Break in Linear Time Series Regressions," University of California at San Diego, Economics Working Paper Series qt9hf4j4c2, Department of Economics, UC San Diego.
    5. Landajo, Manuel & Presno, María José, 2010. "Nonparametric pseudo-Lagrange multiplier stationarity testing," MPRA Paper 25659, University Library of Munich, Germany.
    6. Jungmittag Andre & Grupp Hariolf, 2006. "Wechselwirkungen zwischen Innovations- und Wachstumsprozessen in Deutschland 1951-1999 im Vergleich zu 1850-1913 / Dynamic Relationships Between Innovation Activities and Per Capita Income in Germany ," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 226(2), pages 180-207, April.
    7. Anton Skrobotov, 2013. "Local Structural Trend Break in Stationarity Testing," Working Papers 0074, Gaidar Institute for Economic Policy, revised 2013.
    8. Su, Chi-Wei & Tsangyao, Chang & Chang, Hsu-Ling, 2011. "Purchasing power parity for fifteen Latin American countries: Stationary test with a Fourier function," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 839-845, October.
    9. Yoichi Arai & Eiji Kurozumi, 2007. "Testing for the Null Hypothesis of Cointegration with a Structural Break," Econometric Reviews, Taylor & Francis Journals, vol. 26(6), pages 705-739.
    10. Francisco Delgado & Maria Jose Presno, 2011. "Convergence of fiscal pressure in the EU: a time series approach," Applied Economics, Taylor & Francis Journals, vol. 43(28), pages 4257-4267.
    11. David I. Harvey & Terence C. Mills, 2003. "A Note On Busetti–Harvey Tests For Stationarity In Series With Structural Breaks," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(2), pages 159-164, March.
    12. Kaddour Hadri & Rolf Larsson & Yao Rao, 2012. "Testing For Stationarity With A Break In Panels Where The Time Dimension Is Finite," Bulletin of Economic Research, Wiley Blackwell, vol. 64(Supplemen), pages 123-148, December.
    13. Kaddour Hadri & Yao Rao, 2008. "Panel Stationarity Test with Structural Breaks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(2), pages 245-269, April.
    14. Fabio Busetti & A. M. Robert Taylor, 2003. "Testing against stochastic trend and seasonality in the presence of unattended breaks and unit roots," Temi di discussione (Economic working papers) 470, Bank of Italy, Economic Research and International Relations Area.
    15. Manuel Landajo & María José Presno, 2010. "Stationarity testing under nonlinear models. Some asymptotic results," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(5), pages 392-405, September.
    16. Yoichi Arai & Eiji Kurozumi, 2005. "Testing for the Null Hypothesis of Cointegration with Structural Breaks (Subsequently published in "Econometric Reviews", Volume 26, Issue 6 November 2007, pages 705 - 739. )," CARF F-Series CARF-F-022, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    17. María Presno & Anna López, 2003. "Testing for stationarity in series with a shift in the mean. A fredholm approach," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 12(1), pages 195-213, June.
    18. Tommaso Proietti & Alberto Musso & Thomas Westermann, 2007. "Estimating potential output and the output gap for the euro area: a model-based production function approach," Empirical Economics, Springer, vol. 33(1), pages 85-113, July.
    19. Westerlund, Joakim & Edgerton , David, 2006. "New Improved Tests for Cointegration with Structural Breaks," Working Papers 2006:3, Lund University, Department of Economics.
    20. Muhammad Zeeshan Younas & Rashid Mehmood, 2018. "Examining the Efficiency of American Stock Exchange NASDAQ: An empirical analysis of the Market Efficiency Hypothesis," Bulletin of Business and Economics (BBE), Research Foundation for Humanity (RFH), vol. 7(3), pages 132-137, September.
    21. Carrion-i-Silvestre, Josep Lluis, 2003. "Breaking date misspecification error for the level shift KPSS test," Economics Letters, Elsevier, vol. 81(3), pages 365-371, December.
    22. Fabio Busetti & Andrew Harvey, 2003. "Further Comments On Stationarity Tests In Series With Structural Breaks At Unknown Points," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(2), pages 137-140, March.
    23. Anton Skrobotov, 2012. "Bias Correction of KPSS Test with Structural Break for Reducing of Size Distortion - in Russian," Working Papers 0044, Gaidar Institute for Economic Policy, revised 2012.
    24. Jushan Bai; Josep Lluís Carrion-i-Silvestre, 2004. "Structural changes, common stochastic trends and unit roots in panel data," Econometric Society 2004 North American Summer Meetings 345, Econometric Society.
    25. Cavaliere, Giuseppe & Taylor, A.M. Robert, 2005. "Stationarity Tests Under Time-Varying Second Moments," Econometric Theory, Cambridge University Press, vol. 21(6), pages 1112-1129, December.
    26. Fabio Busetti, 2006. "Tests of seasonal integration and cointegration in multivariate unobserved component models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 419-438, May.
    27. Emilian DOBRESCU, 2016. "Controversies over the Size of the Public Budget," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 5-34, December.
    28. A. M. Robert Taylor, 2005. "Fluctuation Tests for a Change in Persistence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(2), pages 207-230, April.
    29. Anton Skrobotov, 2014. "A simple modification of the Busetti-Harvey stationarity tests with structural breaks at unknown time," Working Papers 0102, Gaidar Institute for Economic Policy, revised 2014.
    30. Karsten Schweikert, 2019. "Asymmetric price transmission in the US and German fuel markets: a quantile autoregression approach," Empirical Economics, Springer, vol. 56(3), pages 1071-1095, March.
    31. Josep Lluís Carrion-i-Silvestre & Andreu Sansó, 2005. "The KPSS Test with Two Structural Breaks," DEA Working Papers 13, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    32. Corona, Francisco & Orraca, Pedro, 2016. "Remittances in Mexico and their unobserved components," DES - Working Papers. Statistics and Econometrics. WS 22674, Universidad Carlos III de Madrid. Departamento de Estadística.
    33. Dimpfl, Thomas & Peter, Franziska J., 2019. "Group transfer entropy with an application to cryptocurrencies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 543-551.
    34. Skrobotov Anton, 2013. "Bias Correction of KPSS Test with Structural Break for Reducing of Size Distortion," Journal of Time Series Econometrics, De Gruyter, vol. 6(1), pages 33-61, December.
    35. Josep Lluís Carrion‐i‐Silvestre & María Dolores Gadea, 2023. "Testing for multiple level shifts with an integrated or stationary noise component," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 801-819, September.
    36. Josep Lluis Carrion Silvestre & Tomas del Barrio Castro & Enrique Lopez Bazo, 2003. "Breaking the panels. An application to the GDP per capita," Working Papers in Economics 97, Universitat de Barcelona. Espai de Recerca en Economia.
    37. Jerome Geyer‐Klingeberg & Andreas W. Rathgeber, 2021. "Determinants of the WTI‐Brent price spread revisited," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(5), pages 736-757, May.
    38. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    39. Busetti, Fabio & Taylor, A. M. Robert, 2004. "Tests of stationarity against a change in persistence," Journal of Econometrics, Elsevier, vol. 123(1), pages 33-66, November.
    40. Harvey, A. & Thiele, S., 2017. "Co-integration and control: assessing the impact of events using time series data," Cambridge Working Papers in Economics 1731, Faculty of Economics, University of Cambridge.
    41. David I. Harvey & Terence C. Mills, 2004. "Tests for Stationarity in Series with Endogenously Determined Structural Change," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 863-894, December.
    42. María Presno & Manuel Landajo, 2010. "Computation of limiting distributions in stationarity testing with a generic trend," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 71(2), pages 165-183, March.
    43. Iacone, Fabrizio & Leybourne, Stephen J. & Robert Taylor, A.M., 2013. "Testing for a break in trend when the order of integration is unknown," Journal of Econometrics, Elsevier, vol. 176(1), pages 30-45.
    44. Banerjee, Anindya & Urga, Giovanni, 2005. "Modelling structural breaks, long memory and stock market volatility: an overview," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 1-34.
    45. Musso, Alberto & Proietti, Tommaso, 2007. "Growth accounting for the euro area: a structural approach," Working Paper Series 804, European Central Bank.

  44. Andrew C Harvey & Siem Jan Koopman, 1996. "Multivariate Structural Time Series Models - (Now published in 'System Dynamics in Economic and Financial Models', CHeij, H Schumacher, B Hanzon and C Praagman (eds.) John Wiley & Sons, Chichester (19," STICERD - Econometrics Paper Series 307, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Guilhem Bentoglio & Jacky Fayolle & Matthieu Lemoine, 2002. "Unity and Plurality of the European Cycle," Working Papers hal-03458584, HAL.

  45. Eric Ghysels & Andrew Harvey & Eric Renault, 1995. "Stochastic Volatility," CIRANO Working Papers 95s-49, CIRANO.

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    1. Per Frederiksen & Morten Orregaard Nielsen, 2008. "Bias-Reduced Estimation of Long-Memory Stochastic Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 6(4), pages 496-512, Fall.
    2. Audrino, Francesco & Fengler, Matthias, 2013. "Are classical option pricing models consistent with observed option second-order moments? Evidence from high-frequency data," Economics Working Paper Series 1311, University of St. Gallen, School of Economics and Political Science.
    3. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    4. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," Center for Financial Institutions Working Papers 99-08, Wharton School Center for Financial Institutions, University of Pennsylvania.
    5. Peter Bossaert & Eric Ghysels & Christian Gouriéroux, 1996. "Arbitrage Based Pricing When Volatility Is Stochastic," CIRANO Working Papers 96s-20, CIRANO.
    6. Luc Bauwens & Pierre Giot & Joachim Grammig & David Veredas, 2000. "A Comparison of Financial Duration Models via Density Forecasts," Econometric Society World Congress 2000 Contributed Papers 0810, Econometric Society.
    7. Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2011. "Modelling and Forecasting Noisy Realized Volatility," KIER Working Papers 758, Kyoto University, Institute of Economic Research.
    8. Casas, Isabel & Gao, Jiti, 2008. "Econometric estimation in long-range dependent volatility models: Theory and practice," Journal of Econometrics, Elsevier, vol. 147(1), pages 72-83, November.
    9. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Econometric Analysis of Realised Covariation: High Frequency Covariance, Regression and Correlation in Financial Economics," Economics Papers 2002-W13, Economics Group, Nuffield College, University of Oxford, revised 18 Mar 2002.
    10. Gallant, A. Ronald & Hsieh, David & Tauchen, George, 1995. "Estimation of Stochastic Volatility Models with Diagnostics," Working Papers 95-36, Duke University, Department of Economics.
    11. Ekaterini Panopoulou & B. Groom & P. Koundouri & Theologos Pantelidis, 2005. "Discounting the distant future: How much does model selection affect the certainty equivalent rate?," Economics Department Working Paper Series n1480105, Department of Economics, National University of Ireland - Maynooth.
    12. Manabu Asai & Michael McAleer, 2013. "Leverage and Feedback Effects on Multifactor Wishart Stochastic Volatility for Option Pricing," KIER Working Papers 840, Kyoto University, Institute of Economic Research.
    13. Veredas, David & Rodríguez Poo, Juan M. & Espasa, Antoni, 2001. "On the (intradaily) seasonality and dynamics of a financial point process: a semiparametric approach," DES - Working Papers. Statistics and Econometrics. WS ws013321, Universidad Carlos III de Madrid. Departamento de Estadística.
    14. René Garcia & Richard Luger & Eric Renault, 2001. "Asymmetric Smiles, Leverage Effects and Structural Parameters," CIRANO Working Papers 2001s-01, CIRANO.
    15. Alessandro Rossi & Giampiero M. Gallo, 2002. "Volatility Estimation via Hidden Markov Models," Econometrics Working Papers Archive wp2002_14, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    16. Nigel Wilkins, 2004. "Indirect Estimation of Long Memory Volatility Models," Econometric Society 2004 Far Eastern Meetings 459, Econometric Society.
    17. Bauwens, L. & Galli, F., 2009. "Efficient importance sampling for ML estimation of SCD models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1974-1992, April.
    18. Barone-Adesi, Giovanni & Fusari, Nicola & Mira, Antonietta & Sala, Carlo, 2020. "Option market trading activity and the estimation of the pricing kernel: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 216(2), pages 430-449.
    19. Pesaran, M. Hashem & Zaffaroni, Paolo, 2005. "Model Averaging and Value-at-Risk Based Evaluation of Large Multi-Asset Volatility Models for Risk Management," CEPR Discussion Papers 5279, C.E.P.R. Discussion Papers.
    20. Andrea Beltratti & Claudio Morana, 2005. "Structural Breaks and Common Factors in the Volatility of the Fama-French Factor Portfolios," ICER Working Papers 23-2005, ICER - International Centre for Economic Research.
    21. Mark Broadie & Jérôme Detemple & Eric Ghysels & Olivier Torrès, 1996. "Nonparametric Estimation of American Options Exercise Boundaries and Call Prices," CIRANO Working Papers 96s-24, CIRANO.
    22. Lucchetti, Riccardo & Palomba, Giulio, 2009. "Nonlinear adjustment in US bond yields: An empirical model with conditional heteroskedasticity," Economic Modelling, Elsevier, vol. 26(3), pages 659-667, May.
    23. Oleg Korenok & Stanislav Radchenko, 2005. "The smooth transition autoregressive target zone model with the Gaussian stochastic volatility and TGARCH error terms with applications," Working Papers 0505, VCU School of Business, Department of Economics.
    24. Taoufik Bouezmarni & Jeroen V.K. Rombouts, 2006. "Nonparametric Density Estimation for Positive Time Series," Cahiers de recherche 06-09, HEC Montréal, Institut d'économie appliquée.
    25. John M. Maheu & Thomas McCurdy, 2001. "Nonlinear Features of Realized FX Volatility," CIRANO Working Papers 2001s-42, CIRANO.
    26. Font, Begoña, 1998. "Modelización de series temporales financieras. Una recopilación," DES - Documentos de Trabajo. Estadística y Econometría. DS 3664, Universidad Carlos III de Madrid. Departamento de Estadística.
    27. Carnero, María Ángeles & Peña, Daniel & Ruiz Ortega, Esther, 2003. "Detecting level shifts in the presence of conditional heteroscedasticity," DES - Working Papers. Statistics and Econometrics. WS ws036313, Universidad Carlos III de Madrid. Departamento de Estadística.
    28. Liesenfeld, Roman & Richard, Jean-François, 2004. "Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models," Economics Working Papers 2004-12, Christian-Albrechts-University of Kiel, Department of Economics.
    29. Mendes, Rui Vilela & Oliveira, Maria J., 2008. "A Data-Reconstructed Fractional Volatility Model," Economics Discussion Papers 2008-22, Kiel Institute for the World Economy (IfW Kiel).
    30. Francis X. Diebold & Jinyong Hahn & Anthony S. Tay, 1998. "Real-Time Multivariate Density Forecast Evaluation and Calibration: Monitoring the Risk of High-Frequency Returns on Foreign Exchange," New York University, Leonard N. Stern School Finance Department Working Paper Seires 98-079, New York University, Leonard N. Stern School of Business-.
    31. Motta, Anderson C. O. & Hotta, Luiz K., 2003. "Exact Maximum Likelihood and Bayesian Estimation of the Stochastic Volatility Model," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 23(2), November.
    32. Javier De Peña & Luis A. Gil-Alana, 2002. "Do Spanish Stock Market Prices Follow a Random Walk?," Faculty Working Papers 01/02, School of Economics and Business Administration, University of Navarra.
    33. Arteche González, Jesús María, 2005. "Semiparametric estimation in perturbed long memory series," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    34. Nuno Cassola & Claudio Morana, 2006. "Volatility of interest rates in the euro area: Evidence from high frequency data," The European Journal of Finance, Taylor & Francis Journals, vol. 12(6-7), pages 513-528.
    35. Hidalgo, Javier & Zaffaroni, Paolo, 2007. "A goodness-of-fit test for ARCH([infinity]) models," Journal of Econometrics, Elsevier, vol. 141(2), pages 835-875, December.
    36. Hafner, C. & Preminger, A., 2010. "Deciding between GARCH and Stochastic Volatility via Strong Decision Rules," LIDAM Reprints ISBA 2010032, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    37. Eric Ghysels & Jean-Pierre Florens & Mikhail Chernov & Marine Carrasco, 2003. "Efficient Estimation of Jump Diffusions and General Dynamic Models with a Continuum of Moment Conditions," CIRANO Working Papers 2003s-02, CIRANO.
    38. Kanatani, Taro, 2004. "Iterative method for exponentially weighted rolling regression," Finance Research Letters, Elsevier, vol. 1(3), pages 196-201, September.
    39. Antonis Demos, 2002. "Moments and dynamic structure of a time-varying parameter stochastic volatility in mean model," Econometrics Journal, Royal Economic Society, vol. 5(2), pages 345-357, June.
    40. Jeremy Large, 2007. "Estimating Quadratic Variation When Quoted Prices Change by a Constant Increment," Economics Series Working Papers 340, University of Oxford, Department of Economics.
    41. Peter Christoffersen & Redouane Elkamhi & Bruno Feunou & Kris Jacobs, 2009. "Option Valuation with Conditional Heteroskedasticity and Non-Normality," CIRANO Working Papers 2009s-32, CIRANO.
    42. Karoll Gómez Portilla & Santiago Gallón Gómez, 2007. "Distribución condicional de los retornos de la tasa de cambio colombiana: un ejercicio empírico a partir de modelos GARCH multivariados," Revista de Economía del Rosario, Universidad del Rosario, December.
    43. Andersen, Torben G. & Bollerslev, Tim & Francis X. Diebold,, 2003. "Some Like it Smooth, and Some Like it Rough: Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset Return Volatility," CFS Working Paper Series 2003/35, Center for Financial Studies (CFS).
    44. Marcelo Fernandes & Joachim Grammig, 2000. "Non-Parametric Specification Tests For Conditional Duration Models," Computing in Economics and Finance 2000 40, Society for Computational Economics.
    45. Pesaran, M. Hashem & Schleicher, Christoph & Zaffaroni, Paolo, 2009. "Model averaging in risk management with an application to futures markets," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 280-305, March.
    46. Mr. Gene L. Leon & Mr. Rupert D Worrell, 2001. "Price Volatility and Financial Instability," IMF Working Papers 2001/060, International Monetary Fund.
    47. Philip Arestis, 2004. "Is there a trade-off between inflation variability and output-gap variability in the EMU countries?," National Institute of Economic and Social Research (NIESR) Discussion Papers 238, National Institute of Economic and Social Research.
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    29. Murali Adhikari & Krishna Paudel & Laxmi Paudel & James Bukenya, 2007. "Modelling swine supply response using a structural time series approach," Applied Economics Letters, Taylor & Francis Journals, vol. 14(7), pages 467-472.
    30. Moosa, Imad A., 1999. "Cyclical output, cyclical unemployment, and Okun's coefficient A structural time series approach," International Review of Economics & Finance, Elsevier, vol. 8(3), pages 293-304, September.
    31. Alan Carruth & Andrew Dickerson, 2003. "An asymmetric error correction model of UK consumer spending," Applied Economics, Taylor & Francis Journals, vol. 35(6), pages 619-630.
    32. Rude, James & Surry, Yves, 2013. "Canadian Hog Supply Respose: A Provincial Level Analysis," Working Papers 148590, Structure and Performance of Agriculture and Agri-products Industry (SPAA).
    33. Hunt, Lester C. & Judge, Guy & Ninomiya, Yasushi, 2003. "Underlying trends and seasonality in UK energy demand: a sectoral analysis," Energy Economics, Elsevier, vol. 25(1), pages 93-118, January.
    34. Abdullah Al-Awadhi & Ahmad Bash & Fouad Jamaani, 2021. "Ramadan Effect: A Structural Time-Series Test," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 12(1), pages 260-269, January.
    35. Girardin, Eric & Liu, Zhenya, 2005. "Bank credit and seasonal anomalies in China's stock markets," China Economic Review, Elsevier, vol. 16(4), pages 465-483.
    36. Stephen Bazen & Velayoudom Marimoutou, 2000. "Looking for a Needle in a Haystack? A Structural Time Series Model of the Relationship Between Teenage Employment and Minimum Wages in the United States," Econometric Society World Congress 2000 Contributed Papers 0495, Econometric Society.
    37. Hansen, Hermann-Josef, 1996. "Der Einfluß der Zinsen auf den privaten Verbrauch in Deutschland," Discussion Paper Series 1: Economic Studies 1996,03, Deutsche Bundesbank.
    38. Stephen Bazen & Velayoudom Marimoutou, 2018. "Federal Minimum Wage Hikes Do Reduce Teenage Employment," Working Papers halshs-01945777, HAL.
    39. Bernardina Algieri, 2011. "Modelling export equations using an unobserved component model: the case of the Euro Area and its competitors," Empirical Economics, Springer, vol. 41(3), pages 593-637, December.
    40. Blazsek Szabolcs & Licht Adrian & Escribano Alvaro, 2021. "Identification of Seasonal Effects in Impulse Responses Using Score-Driven Multivariate Location Models," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 53-66, January.
    41. Haiyan Song & Peter Romilly & Xiaming Liu, 1998. "The UK consumption function and structural instability: improving forecasting performance using a time-varying parameter approach," Applied Economics, Taylor & Francis Journals, vol. 30(7), pages 975-983.
    42. Lester C. Hunt & Guy Judge & Yashushi Ninomiya, 2000. "Modelling Technical Progress: An Application of the Stochastic Trend Model to UK Energy Demand," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 99, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    43. Paramsothy Silvapulle & Imad A. Moosa & Mervyn J. Silvapulle, 2004. "Asymmetry in Okun's law," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 37(2), pages 353-374, May.
    44. Dilaver, Zafer & Hunt, Lester C., 2021. "Modelling U.S. gasoline demand: A structural time series analysis with asymmetric price responses," Energy Policy, Elsevier, vol. 156(C).
    45. Hansen, Hermann-Josef, 1996. "The impact of interest rates on private consumption in Germany," Discussion Paper Series 1: Economic Studies 1996,03e, Deutsche Bundesbank.
    46. Taylor, A. M. Robert, 1997. "On the practical problems of computing seasonal unit root tests," International Journal of Forecasting, Elsevier, vol. 13(3), pages 307-318, September.
    47. Murali Adhikari & Krishna Paudel & Jack Houstan & James Bukenya, 2007. "Dairy supply response under stochastic trend and seasonality," Applied Economics Letters, Taylor & Francis Journals, vol. 14(12), pages 887-891.

  47. Andrew C Harvey & N.G. Shephard, 1993. "Estimation and Testing of Stochastic Variance Models," STICERD - Econometrics Paper Series 268, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Font, Begoña, 1998. "Modelización de series temporales financieras. Una recopilación," DES - Documentos de Trabajo. Estadística y Econometría. DS 3664, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Francis X. Diebold & Jose A. Lopez, 1995. "Measuring Volatility Dynamics," NBER Technical Working Papers 0173, National Bureau of Economic Research, Inc.
    3. Alejandro Islas Camargo & Francisco Venegas Martínez, 2003. "Pricing Derivatives Securities with Prior Information on Long- Memory Volatility," Economía Mexicana NUEVA ÉPOCA, CIDE, División de Economía, vol. 0(1), pages 103-134, January-J.
    4. G Sandmann & Siem Jan Koopman, 1996. "Maximum Likelihood Estimation of Stochastic Volatility Models," FMG Discussion Papers dp248, Financial Markets Group.
    5. Ramaprasad Bhar & Damien Lee, 2018. "Alternative characterization of volatility of short-term interest rate," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 5(02), pages 1-15, June.
    6. GHYSELS, Eric & HARVEY, Andrew & RENAULT, Eric, 1995. "Stochastic Volatility," LIDAM Discussion Papers CORE 1995069, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Peña, Juan Ignacio & Ruiz Ortega, Esther, 1994. "Stock market regulations and international financial integration: the case of Spain," DEE - Working Papers. Business Economics. WB 7083, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    8. Alexander Tsyplakov, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models (in Russian)," Quantile, Quantile, issue 8, pages 69-122, July.
    9. Yueh-Neng Lin & Ken Hung, 2008. "Is Volatility Priced?," Annals of Economics and Finance, Society for AEF, vol. 9(1), pages 39-75, May.
    10. P. Girardello & Orietta Nicolis & Giovanni Tondini, 2002. "Comparing conditional variance models: Theory and empirical evidence," Departmental Working Papers 2002-08, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    11. Alin Sima, 2008. "Stylized Facts and Discrete Stochastic Volatility Models," Advances in Economic and Financial Research - DOFIN Working Paper Series 10, Bucharest University of Economics, Center for Advanced Research in Finance and Banking - CARFIB.
    12. Ramaprasad Bhar, 2010. "Stochastic Filtering with Applications in Finance," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 7736, January.
    13. Ronald Mahieu & Peter C. Schotman, 1994. "Stochastic volatility and the distribution of exchange rate news," Discussion Paper / Institute for Empirical Macroeconomics 96, Federal Reserve Bank of Minneapolis.
    14. Grané, A. & Veiga, H., 2008. "Accurate minimum capital risk requirements: A comparison of several approaches," Journal of Banking & Finance, Elsevier, vol. 32(11), pages 2482-2492, November.
    15. Paolo Girardello & Orietta Nicolis & Giovanni Tondini, 2003. "Comparing Conditional Variance Models: Theory and Empirical Evidence," Multinational Finance Journal, Multinational Finance Journal, vol. 7(3-4), pages 177-206, September.
    16. Hwang, Soosung & Satchell, Stephen E., 2000. "Market risk and the concept of fundamental volatility: Measuring volatility across asset and derivative markets and testing for the impact of derivatives markets on financial markets," Journal of Banking & Finance, Elsevier, vol. 24(5), pages 759-785, May.
    17. Francis E. Warnock & Veronica C. Warnock, 2000. "The declining volatility of U.S. employment: was Arthur Burns right?," International Finance Discussion Papers 677, Board of Governors of the Federal Reserve System (U.S.).
    18. Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
    19. Ester Ruiz & Fernando Lorenzo, 1998. "The relation between the level and uncertainty of inflation," Documentos de Trabajo (working papers) 0698, Department of Economics - dECON.
    20. Sandmann, Gleb & Koopman, Siem Jan, 1998. "Estimation of stochastic volatility models via Monte Carlo maximum likelihood," Journal of Econometrics, Elsevier, vol. 87(2), pages 271-301, September.
    21. Soosung Hwang & Steve E. Satchell & Pedro L. Valls Pereira, 2004. "How Persistent is Volatility? An Answer with Stochastic Volatility Models with Markov Regime Switching State Equations," Econometric Society 2004 Latin American Meetings 198, Econometric Society.
    22. Bjorn Hansson & Peter Hordahl, 2005. "Forecasting variance using stochastic volatility and GARCH," The European Journal of Finance, Taylor & Francis Journals, vol. 11(1), pages 33-57.
    23. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.

Articles

  1. Andrew Harvey & Stephen Thiele, 2021. "Cointegration and control: Assessing the impact of events using time series data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 71-85, January.
    See citations under working paper version above.
  2. Harvey, Andrew & Ito, Ryoko, 2020. "Modeling time series when some observations are zero," Journal of Econometrics, Elsevier, vol. 214(1), pages 33-45.

    Cited by:

    1. Hiroyuki Kawakatsu, 2019. "Jointly Modeling Autoregressive Conditional Mean and Variance of Non-Negative Valued Time Series," Econometrics, MDPI, vol. 7(4), pages 1-19, December.
    2. De Rossi, Giuliano & Steliaros, Michael, 2022. "The Shift from Active to Passive and its Effect on Intraday Stock Dynamics," Journal of Banking & Finance, Elsevier, vol. 143(C).
    3. Petra Tomanová & Vladimír Holý, 2021. "Clustering of arrivals in queueing systems: autoregressive conditional duration approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(3), pages 859-874, September.
    4. Giuseppe Buccheri & Stefano Grassi & Giorgio Vocalelli, 2021. "Estimating Risk in Illiquid Markets: a Model of Market Friction with Stochastic Volatility," CEIS Research Paper 506, Tor Vergata University, CEIS, revised 08 Nov 2021.
    5. Song, Shijia & Li, Handong, 2023. "A method for predicting VaR by aggregating generalized distributions driven by the dynamic conditional score," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 203-214.
    6. Domenico Di Gangi & Giacomo Bormetti & Fabrizio Lillo, 2022. "Score Driven Generalized Fitness Model for Sparse and Weighted Temporal Networks," Papers 2202.09854, arXiv.org, revised Mar 2022.
    7. Kamil Makieła & Błażej Mazur, 2022. "Model uncertainty and efficiency measurement in stochastic frontier analysis with generalized errors," Journal of Productivity Analysis, Springer, vol. 58(1), pages 35-54, August.
    8. Song, Shijia & Li, Handong, 2022. "Predicting VaR for China's stock market: A score-driven model based on normal inverse Gaussian distribution," International Review of Financial Analysis, Elsevier, vol. 82(C).

  3. Andrew Harvey & Rutger‐Jan Lange, 2018. "Modeling the Interactions between Volatility and Returns using EGARCH‐M," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 909-919, November.

    Cited by:

    1. Buccheri, Giuseppe & Corsi, Fulvio & Flandoli, Franco & Livieri, Giulia, 2021. "The continuous-time limit of score-driven volatility models," Journal of Econometrics, Elsevier, vol. 221(2), pages 655-675.
    2. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    3. Fei, Tianlun & Liu, Xiaoquan, 2021. "Herding and market volatility," International Review of Financial Analysis, Elsevier, vol. 78(C).
    4. Harvey, Andew & Liao, Yin, 2023. "Dynamic Tobit models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 72-83.
    5. Elisa Navarra, 2022. "Stock Market Response to Firms’ Misconduct," Working Papers ECARES 2022-40, ULB -- Universite Libre de Bruxelles.
    6. Ayala Astrid & Blazsek Szabolcs & Escribano Alvaro, 2023. "Anticipating extreme losses using score-driven shape filters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(4), pages 449-484, September.
    7. Michel Ferreira Cardia Haddad & Szabolcs Blazsek & Philip Arestis & Franz Fuerst & Hsia Hua Sheng, 2023. "The two-component Beta-t-QVAR-M-lev: a new forecasting model," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 379-401, December.
    8. Astrid Ayala & Szabolcs Blazsek & Adrian Licht, 2022. "Score-driven stochastic seasonality of the Russian rouble: an application case study for the period of 1999 to 2020," Empirical Economics, Springer, vol. 62(5), pages 2179-2203, May.
    9. Ciarreta, Aitor & Pizarro-Irizar, Cristina & Zarraga, Ainhoa, 2020. "Renewable energy regulation and structural breaks: An empirical analysis of Spanish electricity price volatility," Energy Economics, Elsevier, vol. 88(C).
    10. Xu, Qifa & Chen, Lu & Jiang, Cuixia & Yu, Keming, 2020. "Mixed data sampling expectile regression with applications to measuring financial risk," Economic Modelling, Elsevier, vol. 91(C), pages 469-486.
    11. Palumbo, D., 2021. "Testing and Modelling Time Series with Time Varying Tails," Cambridge Working Papers in Economics 2111, Faculty of Economics, University of Cambridge.
    12. Harvey, A. & Liao, Y., 2019. "Dynamic Tobit models," Cambridge Working Papers in Economics 1913, Faculty of Economics, University of Cambridge.

  4. Tata Subba Rao & Granville Tunnicliffe Wilson & Andrew Harvey & Rutger-Jan Lange, 2017. "Volatility Modeling with a Generalized t Distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(2), pages 175-190, March.
    See citations under working paper version above.
  5. Michele Caivano & Andrew Harvey & Alessandra Luati, 2016. "Robust time series models with trend and seasonal components," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 7(1), pages 99-120, March.

    Cited by:

    1. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
    2. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2018. "Seasonal quasi-vector autoregressive models for macroeconomic data," UC3M Working papers. Economics 26316, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Szabolcs Blazsek & Hector Hernández, 2018. "Analysis of electricity prices for Central American countries using dynamic conditional score models," Empirical Economics, Springer, vol. 55(4), pages 1807-1848, December.
    4. Sarlo, Rodrigo & Fernandes, Cristiano & Borenstein, Denis, 2023. "Lumpy and intermittent retail demand forecasts with score-driven models," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1146-1160.
    5. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2018. "Seasonal Quasi-Vector Autoregressive Models with an Application to Crude Oil Production and Economic Activity in the United States and Canada," UC3M Working papers. Economics 27484, Universidad Carlos III de Madrid. Departamento de Economía.
    6. Enzo D'Innocenzo & Alessandra Luati & Mario Mazzocchi, 2020. "A Robust Score-Driven Filter for Multivariate Time Series," Papers 2009.01517, arXiv.org, revised Aug 2022.
    7. Martin Weale & Paul Labonne, 2022. "Nowcasting in the presence of large measurement errors and revisions," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-05, Economic Statistics Centre of Excellence (ESCoE).
    8. Astrid Ayala & Szabolcs Blazsek & Adrian Licht, 2022. "Score-driven stochastic seasonality of the Russian rouble: an application case study for the period of 1999 to 2020," Empirical Economics, Springer, vol. 62(5), pages 2179-2203, May.
    9. Blasques, Francisco & Nientker, Marc, 2023. "Stochastic properties of nonlinear locally-nonstationary filters," Journal of Econometrics, Elsevier, vol. 235(2), pages 2082-2095.
    10. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de Economía.
    11. Sergio Contreras-Espinoza & Francisco Novoa-Muñoz & Szabolcs Blazsek & Pedro Vidal & Christian Caamaño-Carrillo, 2022. "COVID-19 Active Case Forecasts in Latin American Countries Using Score-Driven Models," Mathematics, MDPI, vol. 11(1), pages 1-17, December.

  6. Harvey, Andrew & Thiele, Stephen, 2016. "Testing against changing correlation," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 575-589.
    See citations under working paper version above.
  7. Andrew Harvey & Alessandra Luati, 2014. "Filtering With Heavy Tails," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1112-1122, September.
    See citations under working paper version above.
  8. Michele Caivano & Andrew Harvey, 2014. "Time-series models with an EGB2 conditional distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 558-571, November.
    See citations under working paper version above.
  9. Harvey, Andrew & Sucarrat, Genaro, 2014. "EGARCH models with fat tails, skewness and leverage," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 320-338.
    See citations under working paper version above.
  10. Harvey, Andrew & Oryshchenko, Vitaliy, 2012. "Kernel density estimation for time series data," International Journal of Forecasting, Elsevier, vol. 28(1), pages 3-14.

    Cited by:

    1. Ayoub Ammy-Driss & Matthieu Garcin, 2021. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Working Papers hal-02903655, HAL.
    2. Ayoub Ammy-Driss & Matthieu Garcin, 2020. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Papers 2007.10727, arXiv.org, revised Nov 2021.
    3. Wang, Jianzhou & Hu, Jianming & Ma, Kailiang, 2016. "Wind speed probability distribution estimation and wind energy assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 881-899.
    4. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
    5. Yan, Hanhuan & Han, Liyan, 2019. "Empirical distributions of stock returns: Mixed normal or kernel density?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 473-486.
    6. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024.
    7. Matthieu Garcin & Jules Klein & Sana Laaribi, 2020. "Estimation of time-varying kernel densities and chronology of the impact of COVID-19 on financial markets," Papers 2007.09043, arXiv.org, revised Mar 2022.
    8. Matthieu Garcin & Jules Klein & Sana Laaribi, 2022. "Estimation of time-varying kernel densities and chronology of the impact of COVID-19 on financial markets," Working Papers hal-02901988, HAL.
    9. Bram van Os, 2023. "Information-Theoretic Time-Varying Density Modeling," Tinbergen Institute Discussion Papers 23-037/III, Tinbergen Institute.
    10. Semeyutin, Artur & O’Neill, Robert, 2019. "A brief survey on the choice of parameters for: “Kernel density estimation for time series data”," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    11. Marcin Dec, 2021. "From point through density valuation to individual risk assessment in the discounted cash flows method," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5621-5635, October.
    12. Fourier, Jean-Baptiste Joseph, 2022. "Indicador Bernardos: un nuevo indicador clave en el análisis del mercado de las criptomonedas y de la conducta humana ante lo desconocido," OSF Preprints 87brk, Center for Open Science.
    13. Liu, Wei & Semeyutin, Artur & Lau, Chi Keung Marco & Gozgor, Giray, 2020. "Forecasting Value-at-Risk of Cryptocurrencies with RiskMetrics type models," Research in International Business and Finance, Elsevier, vol. 54(C).
    14. Marcin Dec, 2019. "From point through density valuation to individual risk assessment in the discounted cash flows method," GRAPE Working Papers 35, GRAPE Group for Research in Applied Economics.
    15. Matthieu Garcin, 2023. "Complexity measure, kernel density estimation, bandwidth selection, and the efficient market hypothesis," Papers 2305.13123, arXiv.org.
    16. Gu, Wentao & Peng, Yiqing, 2019. "Forecasting the market return direction based on a time-varying probability density model," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    17. Ammy-Driss, Ayoub & Garcin, Matthieu, 2023. "Efficiency of the financial markets during the COVID-19 crisis: Time-varying parameters of fractional stable dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    18. Matthieu Garcin, 2023. "Complexity measure, kernel density estimation, bandwidth selection, and the efficient market hypothesis," Working Papers hal-04102815, HAL.
    19. Arora Siddharth & Little Max A. & McSharry Patrick E., 2013. "Nonlinear and nonparametric modeling approaches for probabilistic forecasting of the US gross national product," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 395-420, September.

  11. Fabio Busetti & Andrew Harvey, 2011. "When is a Copula Constant? A Test for Changing Relationships," Journal of Financial Econometrics, Oxford University Press, vol. 9(1), pages 106-131, Winter.
    See citations under working paper version above.
  12. Harvey, Andrew, 2010. "Tracking a changing copula," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 485-500, June.

    Cited by:

    1. Renée Fry-McKibbin & Vance Martin & Chrismin Tang, 2013. "Financial Contagion and Asset Pricing," CAMA Working Papers 2013-61, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024.
    3. Mensi, Walid & Selmi, Refk & Al-Yahyaee, Khamis Hamed, 2020. "Switching dependence and systemic risk between crude oil and U.S. Islamic and conventional equity markets: A new evidence," Resources Policy, Elsevier, vol. 69(C).
    4. Harvey, Andrew & Thiele, Stephen, 2016. "Testing against changing correlation," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 575-589.
    5. Harvey, Andrew & Oryshchenko, Vitaliy, 2012. "Kernel density estimation for time series data," International Journal of Forecasting, Elsevier, vol. 28(1), pages 3-14.
    6. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    7. Semeyutin, Artur & O’Neill, Robert, 2019. "A brief survey on the choice of parameters for: “Kernel density estimation for time series data”," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    8. Selmi, Refk & Hammoudeh, Shawkat & Kasmaoui, Kamal & Sousa, Ricardo M. & Errami, Youssef, 2022. "The dual shocks of the COVID-19 and the oil price collapse: A spark or a setback for the circular economy?," Energy Economics, Elsevier, vol. 109(C).
    9. Camirand Lemyre, Felix & Decrouez, Geoffrey, 2021. "Nonparametric recursive estimation of the copula," Statistics & Probability Letters, Elsevier, vol. 168(C).
    10. Wang, Yi-Chiuan & Wu, Jyh-Lin & Lai, Yi-Hao, 2013. "A revisit to the dependence structure between the stock and foreign exchange markets: A dependence-switching copula approach," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1706-1719.
    11. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    12. Rémillard, Bruno & Papageorgiou, Nicolas & Soustra, Frédéric, 2012. "Copula-based semiparametric models for multivariate time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 30-42.
    13. Selmi, Refk & Wohar, Mark & Deisting, Florent & Kasmaoui, Kamal, 2023. "Dynamic inflation hedging performance and downside risk: A comparison between Islamic and conventional stock indices," The Quarterly Review of Economics and Finance, Elsevier, vol. 91(C), pages 56-67.

  13. Fabio Busetti & Andrew Harvey, 2010. "Tests of strict stationarity based on quantile indicators," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(6), pages 435-450, November.

    Cited by:

    1. Lorenzo Trapani, 2021. "Testing for strict stationarity in a random coefficient autoregressive model," Econometric Reviews, Taylor & Francis Journals, vol. 40(3), pages 220-256, April.
    2. Fabio Busetti & Michele Caivano & Davide Delle Monache, 2019. "Domestic and global determinants of inflation: evidence from expectile regression," Temi di discussione (Economic working papers) 1225, Bank of Italy, Economic Research and International Relations Area.
    3. Fabio Busetti & Michele Caivano & Lisa Rodano, 2015. "On the conditional distribution of euro area inflation forecast," Temi di discussione (Economic working papers) 1027, Bank of Italy, Economic Research and International Relations Area.
    4. Lee, Sangyeol & Meintanis, Simos G. & Pretorius, Charl, 2022. "Monitoring procedures for strict stationarity based on the multivariate characteristic function," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    5. Hart, Jeffrey D., 2016. "A nonparametric test of stationarity for independent data," Statistics & Probability Letters, Elsevier, vol. 108(C), pages 40-44.
    6. Denys Pommeret & Laurence Reboul & Anne-francoise Yao, 2023. "Testing the equality of the laws of two strictly stationary processes," Statistical Inference for Stochastic Processes, Springer, vol. 26(1), pages 193-214, April.
    7. Fabio Busetti, 2012. "On detecting end-of-sample instabilities," Temi di discussione (Economic working papers) 881, Bank of Italy, Economic Research and International Relations Area.

  14. Andrew Harvey, 2010. "The local quadratic trend model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 94-108.

    Cited by:

    1. José Luis Cendejas & Félix-Fernando Muñoz & Nadia Fernández-de-Pinedo, 2017. "A contribution to the analysis of historical economic fluctuations (1870–2010): filtering, spurious cycles, and unobserved component modeling," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 11(1), pages 93-125, January.
    2. Cendejas, José Luis & Castañeda, Juan E. & Muñoz, Félix-Fernando, 2014. "Business cycle, interest rate and money in the euro area: A common factor model," Economic Modelling, Elsevier, vol. 43(C), pages 136-141.
    3. Yoon, Gawon, 2015. "Locating change-points in Hodrick–Prescott trends with an application to US real GDP: A generalized unobserved components model approach," Economic Modelling, Elsevier, vol. 45(C), pages 136-141.
    4. Razek, Noha H.A. & Michieka, Nyakundi M., 2019. "OPEC and non-OPEC production, global demand, and the financialization of oil," Research in International Business and Finance, Elsevier, vol. 50(C), pages 201-225.
    5. Hall, Viv B & Thomson, Peter, 2022. "A boosted HP filter for business cycle analysis: evidence from New Zealand’s small open economy," Working Paper Series 21184, Victoria University of Wellington, School of Economics and Finance.

  15. De Rossi, Giuliano & Harvey, Andrew, 2009. "Quantiles, expectiles and splines," Journal of Econometrics, Elsevier, vol. 152(2), pages 179-185, October.
    See citations under working paper version above.
  16. Harvey, Andrew C. & Delle Monache, Davide, 2009. "Computing the mean square error of unobserved components extracted by misspecified time series models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 283-295, February.

    Cited by:

    1. Kristian Jönsson, 2017. "Restricted Hodrick–Prescott filtering in a state-space framework," Empirical Economics, Springer, vol. 53(3), pages 1243-1251, November.
    2. Theofilakou, Nancy & Stournaras, Yannis, 2012. "Current account adjustments in OECD countries revisited: The role of the fiscal stance," Journal of Policy Modeling, Elsevier, vol. 34(5), pages 719-734.
    3. Badarau-Semenescu, Cristina & Ndiaye, Cheikh Tidiane, 2010. "Politique économique et transmission des chocs dans la zone euro," L'Actualité Economique, Société Canadienne de Science Economique, vol. 86(1), pages 35-77, mars.
    4. Fresoli, Diego & Poncela, Pilar & Ruiz, Esther, 2023. "Ignoring cross-correlated idiosyncratic components when extracting factors in dynamic factor models," Economics Letters, Elsevier, vol. 230(C).
    5. McElroy, Tucker S. & Wildi, Marc, 2020. "The Multivariate Linear Prediction Problem: Model-Based and Direct Filtering Solutions," Econometrics and Statistics, Elsevier, vol. 14(C), pages 112-130.
    6. Flaig Gebhard, 2015. "Why We Should Use High Values for the Smoothing Parameter of the Hodrick-Prescott Filter," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 235(6), pages 518-538, December.
    7. Rodríguez, Alejandro & Ruiz Ortega, Esther, 2010. "Bootstrap prediction mean squared errors of unobserved states based on the Kalman filter with estimated parameters," DES - Working Papers. Statistics and Econometrics. WS ws100301, Universidad Carlos III de Madrid. Departamento de Estadística.

  17. Busetti, Fabio & Harvey, Andrew, 2008. "Testing For Trend," Econometric Theory, Cambridge University Press, vol. 24(1), pages 72-87, February.
    See citations under working paper version above.
  18. Fabio Busetti & Lorenzo Forni & Andrew Harvey & Fabrizio Venditti, 2007. "Inflation Convergence and Divergence within the European Monetary Union," International Journal of Central Banking, International Journal of Central Banking, vol. 3(2), pages 95-121, June.
    See citations under working paper version above.
  19. Carvalho, Vasco & Harvey, Andrew & Trimbur, Thomas, 2007. "A Note on Common Cycles, Common Trends, and Convergence," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 12-20, January.

    Cited by:

    1. Onour, Ibrahim, 2010. "Crude Oil Prices and Stock Markets in Major Oil Exporting Countries: Evidence on Decoupling Feature," MPRA Paper 23334, University Library of Munich, Germany.
    2. Guido Bulligan & Lorenzo Burlon & Davide Delle Monache & Andrea Silvestrini, 2017. "Real and financial cycles: estimates using unobserved component models for the Italian economy," Questioni di Economia e Finanza (Occasional Papers) 382, Bank of Italy, Economic Research and International Relations Area.
    3. Juan Gabriel Brida & Bibiana Lanzilotta & Lucía Rosich, 2019. "Common trends in producers’ expectations, the nonlinear linkage with Uruguayan GDP and its implications in economic growth forecasting," Documentos de Trabajo (working papers) 19-28, Instituto de Economía - IECON.
    4. Christian M. Dahl & Henrik Hansen & John Smidt, 2008. "The cyclical component factor model," CREATES Research Papers 2008-44, Department of Economics and Business Economics, Aarhus University.
    5. Omar H. M. N. Bashar, 2015. "The Trickle‐down Effect of the Mining Boom in Australia: Fact or Myth?," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 94-108, June.
    6. Carsten Trenkler & Enzo Weber, 2020. "Identifying shocks to business cycles with asynchronous propagation," Empirical Economics, Springer, vol. 58(4), pages 1815-1836, April.
    7. Breinlich, Holger & Ottaviano, Gianmarco I P & Temple, Jonathan R, 2013. "Regional Growth and Regional Decline," Economics Discussion Papers 8977, University of Essex, Department of Economics.
    8. Bashar, Omar H.M.N. & Bhattacharya, Prasad Sankar & Wohar, Mark E., 2017. "The cyclicality of fiscal policy: New evidence from unobserved components approach," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 222-234.
    9. Juan G Brida & Bibiana Lanzilotta & Lucia I Rosich, 2021. "On the empirical relations between producers expectations and economic growth," Economics Bulletin, AccessEcon, vol. 41(3), pages 1970-1982.
    10. Macchiarelli, Corrado, 2013. "GDP-Inflation cyclical similarities in the CEE countries and the euro area," Working Paper Series 1552, European Central Bank.
    11. Terence C. Mills, 2013. "Trends, cycles and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 3, pages 45-60, Edward Elgar Publishing.

  20. Harvey, Andrew C. & Trimbur, Thomas M. & Van Dijk, Herman K., 2007. "Trends and cycles in economic time series: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 140(2), pages 618-649, October.
    See citations under working paper version above.
  21. Fabio Busetti & Silvia Fabiani & Andrew Harvey, 2006. "Convergence of Prices and Rates of Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 863-877, December.
    See citations under working paper version above.
  22. Andrew C. Harvey & Vasco M. Carvalho, 2005. "Convergence in the trends and cycles of Euro-zone income," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 275-289.

    Cited by:

    1. Borsi, Mihály Tamás & Metiu, Norbert, 2013. "The evolution of economic convergence in the European Union," Discussion Papers 28/2013, Deutsche Bundesbank.
    2. Cesaroni, Tatiana & Maccini, Louis & Malgarini, Marco, 2011. "Business cycle stylized facts and inventory behaviour: New evidence for the Euro area," International Journal of Production Economics, Elsevier, vol. 133(1), pages 12-24, September.
    3. Alka Obadić & Vladimir Arčabić & Lucija Rogić Dumančić, 2021. "Labor market institutions convergence in the European Union," EFZG Working Papers Series 2102, Faculty of Economics and Business, University of Zagreb.
    4. Diegel, Max, 2022. "Time-varying credibility, anchoring and the Fed's inflation target," Discussion Papers 2022/9, Free University Berlin, School of Business & Economics.
    5. Carsten Trenkler & Enzo Weber, 2020. "Identifying shocks to business cycles with asynchronous propagation," Empirical Economics, Springer, vol. 58(4), pages 1815-1836, April.
    6. Paul Johnson & Chris Papageorgiou, 2020. "What Remains of Cross-Country Convergence?," Journal of Economic Literature, American Economic Association, vol. 58(1), pages 129-175, March.
    7. ALBU, Lucian – Liviu, 2017. "Budgetary Spending And Growth In The Eu," Journal of Financial and Monetary Economics, Centre of Financial and Monetary Research "Victor Slavescu", vol. 4(1), pages 11-17.
    8. Sandra Eickmeier, 2009. "Comovements and heterogeneity in the euro area analyzed in a non-stationary dynamic factor model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 933-959.
    9. Ismail H. GENC & Anil RUPASINGHA, 2009. "Time-series Tests of Stochastic Earnings Convergence across US Nonmetropolitan Counties, 1969-2004," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 9(2).
    10. Linda Glawe & Helmut Wagner, 2021. "Divergence Tendencies in the European Integration Process: A Danger for the Sustainability of the E(M)U?," JRFM, MDPI, vol. 14(3), pages 1-22, March.
    11. Ismail Genc & Jon Miller & Anil Rupasingha, 2011. "Stochastic convergence tests for US regional per capita personal income; some further evidence: a research note," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 46(2), pages 369-377, April.
    12. Eickmeier, Sandra, 2006. "Comovements and heterogeneity in the Comovements and heterogeneity in the dynamic factor model," Discussion Paper Series 1: Economic Studies 2006,31, Deutsche Bundesbank.
    13. Florentin GLÖTZL & Armon REZAI, 2016. "A sectoral net lending perspective on Europe," Ecological Economics Papers ieep12, Institute of Ecological Economics.
    14. Kozlova, Olesia & de Jesus Noguera, Jose, 2018. "Achievers or slackers? Per capita income trends in European countries," Journal of Policy Modeling, Elsevier, vol. 40(6), pages 1332-1345.
    15. Lucian Liviu Albu, 2016. "Trends in the relation between regional convergence and economic growth in EU," Working Papers of Institute for Economic Forecasting 161101, Institute for Economic Forecasting.
    16. Mihaela Simionescu, 2015. "About regional convergence clubs in the European Union," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 33(1), pages 67-80.
    17. Hwa-Taek Lee & Gawon Yoon, 2013. "Does purchasing power parity hold sometimes? Regime switching in real exchange rates," Applied Economics, Taylor & Francis Journals, vol. 45(16), pages 2279-2294, June.
    18. Obadić, Alka & Arčabić, Vladimir & Rogić Dumančić, Lucija, 2023. "Club convergence of labor market institutions in the European Union," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 876-896.
    19. Steven Clark & T. Coggin, 2009. "Trends, Cycles and Convergence in U.S. Regional House Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 39(3), pages 264-283, October.
    20. Shushanik Papanyan, 2015. "Digitization and Productivity: Measuring Cycles of Technological Progress," Working Papers 15/33, BBVA Bank, Economic Research Department.
    21. Massimiliano Affinito & Fabio Farabullini, 2009. "Does the Law of One Price Hold in Euro-Area Retail Banking? An Empirical Analysis of Interest Rate Differentials across the Monetary Union," International Journal of Central Banking, International Journal of Central Banking, vol. 5(1), pages 5-37, March.
    22. Peter Dreuw, 2023. "Structural time series models and synthetic controls—assessing the impact of the euro adoption," Empirical Economics, Springer, vol. 64(2), pages 681-725, February.

  23. Carvalho, Vasco M. & Harvey, Andrew C., 2005. "Growth, cycles and convergence in US regional time series," International Journal of Forecasting, Elsevier, vol. 21(4), pages 667-686.
    See citations under working paper version above.
  24. Andrew C. Harvey & Thomas M. Trimbur, 2003. "General Model-Based Filters for Extracting Cycles and Trends in Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 244-255, May.
    See citations under working paper version above.
  25. Busetti, Fabio & Harvey, Andrew, 2003. "Seasonality Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(3), pages 420-436, July.

    Cited by:

    1. Svend Hylleberg, 2006. "Seasonal Adjustment," Economics Working Papers 2006-04, Department of Economics and Business Economics, Aarhus University.
    2. Stefano Grassi & Tommaso Proietti, 2011. "Stochastic trends and seasonality in economic time series: new evidence from Bayesian stochastic model specification search," CREATES Research Papers 2011-30, Department of Economics and Business Economics, Aarhus University.
    3. Siem Jan Koopman & Marius Ooms & Irma Hindrayanto, 2009. "Periodic Unobserved Cycles in Seasonal Time Series with an Application to US Unemployment," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(5), pages 683-713, October.
    4. McElroy Tucker, 2021. "A Diagnostic for Seasonality Based Upon Polynomial Roots of ARMA Models," Journal of Official Statistics, Sciendo, vol. 37(2), pages 367-394, June.
    5. Tommaso Proietti & Eric Hillebrand, 2017. "Seasonal changes in central England temperatures," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(3), pages 769-791, June.
    6. Irma Hindrayanto & John A.D. Aston & Siem Jan Koopman & Marius Ooms, 2013. "Modelling trigonometric seasonal components for monthly economic time series," Applied Economics, Taylor & Francis Journals, vol. 45(21), pages 3024-3034, July.
    7. Fabio Busetti & A. M. Robert Taylor, 2003. "Testing against stochastic trend and seasonality in the presence of unattended breaks and unit roots," Temi di discussione (Economic working papers) 470, Bank of Italy, Economic Research and International Relations Area.
    8. E. Andersson & D. Bock & M. Frisen, 2006. "Some statistical aspects of methods for detection of turning points in business cycles," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(3), pages 257-278.
    9. Stefano Grassi & Tommaso Proietti, 2011. "Bayesian stochastic model specification search for seasonal and calendar effects," CREATES Research Papers 2011-08, Department of Economics and Business Economics, Aarhus University.
    10. Proietti, Tommaso & Pedregal, Diego J., 2023. "Seasonality in High Frequency Time Series," Econometrics and Statistics, Elsevier, vol. 27(C), pages 62-82.
    11. El Montasser, Ghassen, 2014. "The seasonal KPSS Test: some extensions and further results," MPRA Paper 54920, University Library of Munich, Germany.
    12. Fabio Busetti, 2006. "Tests of seasonal integration and cointegration in multivariate unobserved component models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 419-438, May.
    13. Hindrayanto, Irma & Koopman, Siem Jan & Ooms, Marius, 2010. "Exact maximum likelihood estimation for non-stationary periodic time series models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2641-2654, November.
    14. El Montasser, Ghassen, 2012. "The seasonal KPSS Test: some extensions and further results," MPRA Paper 45110, University Library of Munich, Germany, revised 04 Mar 2014.
    15. Tommaso Proietti & Cecilia Frale, 2007. "New proposals for the quantification of qualitative survey data," CEIS Research Paper 98, Tor Vergata University, CEIS.
    16. Ghassen El Montasser, 2015. "The Seasonal KPSS Test: Examining Possible Applications with Monthly Data and Additional Deterministic Terms," Econometrics, MDPI, vol. 3(2), pages 1-16, May.
    17. Webel, Karsten, 2016. "A data-driven selection of an appropriate seasonal adjustment approach," Discussion Papers 07/2016, Deutsche Bundesbank.
    18. Apergis, Nicholas & Lau, Marco Chi Keung, 2015. "Structural breaks and electricity prices: Further evidence on the role of climate policy uncertainties in the Australian electricity market," Energy Economics, Elsevier, vol. 52(PA), pages 176-182.
    19. Fabio Busetti & Silvestro di Sanzo, 2011. "Bootstrap LR tests of stationarity, common trends and cointegration," Temi di discussione (Economic working papers) 799, Bank of Italy, Economic Research and International Relations Area.

  26. Andrew Harvey & Jared Bernstein, 2003. "Measurement and Testing of Inequality from Time Series of Deciles with an Application to U.S. Wages," The Review of Economics and Statistics, MIT Press, vol. 85(1), pages 141-152, February.
    See citations under working paper version above.
  27. Koopman, Siem Jan & Harvey, Andrew, 2003. "Computing observation weights for signal extraction and filtering," Journal of Economic Dynamics and Control, Elsevier, vol. 27(7), pages 1317-1333, May.
    See citations under working paper version above.
  28. Fabio Busetti & Andrew Harvey, 2003. "Further Comments On Stationarity Tests In Series With Structural Breaks At Unknown Points," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(2), pages 137-140, March.

    Cited by:

    1. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2013. "Testing for unit roots in the possible presence of multiple trend breaks using minimum Dickey–Fuller statistics," Journal of Econometrics, Elsevier, vol. 177(2), pages 265-284.
    2. Anton Skrobotov, 2013. "Local Structural Trend Break in Stationarity Testing," Working Papers 0074, Gaidar Institute for Economic Policy, revised 2013.
    3. Kaddour Hadri & Rolf Larsson & Yao Rao, 2012. "Testing For Stationarity With A Break In Panels Where The Time Dimension Is Finite," Bulletin of Economic Research, Wiley Blackwell, vol. 64(Supplemen), pages 123-148, December.
    4. Kaddour Hadri & Yao Rao, 2008. "Panel Stationarity Test with Structural Breaks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(2), pages 245-269, April.
    5. Fabio Busetti & A. M. Robert Taylor, 2003. "Testing against stochastic trend and seasonality in the presence of unattended breaks and unit roots," Temi di discussione (Economic working papers) 470, Bank of Italy, Economic Research and International Relations Area.
    6. Arezki, Rabah & Hadri, Kaddour & Kurozumi, Eiji & Rao, Yao, 2012. "Testing the Prebish–Singer hypothesis using second-generation panel data stationarity tests with a break," Economics Letters, Elsevier, vol. 117(3), pages 814-816.
    7. Rabah Arezki & Kaddour Hadri & Eiji Kurozumi & Yao Rao, 2012. "Breaking the Prebish Singer Hypothesis using Panel Data Stationarity Tests," Economics Working Papers 12-01, Queen's Management School, Queen's University Belfast.
    8. Anton Skrobotov, 2012. "Bias Correction of KPSS Test with Structural Break for Reducing of Size Distortion - in Russian," Working Papers 0044, Gaidar Institute for Economic Policy, revised 2012.
    9. Anton Skrobotov, 2014. "A simple modification of the Busetti-Harvey stationarity tests with structural breaks at unknown time," Working Papers 0102, Gaidar Institute for Economic Policy, revised 2014.
    10. Skrobotov Anton, 2013. "Bias Correction of KPSS Test with Structural Break for Reducing of Size Distortion," Journal of Time Series Econometrics, De Gruyter, vol. 6(1), pages 33-61, December.
    11. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    12. Busetti, Fabio & Taylor, A. M. Robert, 2004. "Tests of stationarity against a change in persistence," Journal of Econometrics, Elsevier, vol. 123(1), pages 33-66, November.
    13. Massimiliano Affinito & Fabio Farabullini, 2009. "Does the Law of One Price Hold in Euro-Area Retail Banking? An Empirical Analysis of Interest Rate Differentials across the Monetary Union," International Journal of Central Banking, International Journal of Central Banking, vol. 5(1), pages 5-37, March.
    14. David I. Harvey & Terence C. Mills, 2004. "Tests for Stationarity in Series with Endogenously Determined Structural Change," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 863-894, December.
    15. Banerjee, Anindya & Urga, Giovanni, 2005. "Modelling structural breaks, long memory and stock market volatility: an overview," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 1-34.

  29. Jukka Nyblom & Andrew Harvey, 2001. "Testing against smooth stochastic trends," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 415-429.

    Cited by:

    1. Juan Gabriel Brida & Bibiana Lanzilotta & Lucía Rosich, 2019. "Common trends in producers’ expectations, the nonlinear linkage with Uruguayan GDP and its implications in economic growth forecasting," Documentos de Trabajo (working papers) 19-28, Instituto de Economía - IECON.
    2. Vujić Sunčica & Koopman Siem Jan & Commandeur J.F., 2012. "Economic Trends and Cycles in Crime: A Study for England and Wales," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(6), pages 652-677, December.
    3. C.S. Bos & S.J. Koopman & M. Ooms, 2007. "Long Memory Modelling of Inflation with Stochastic Variance and Structural Breaks," Tinbergen Institute Discussion Papers 07-099/4, Tinbergen Institute.
    4. Xiaoyi Mu and Haichun Ye, 2015. "Small Trends and Big Cycles in Crude Oil Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    5. Busettti, F. & Harvey, A., 2007. "Tests of time-invariance," Cambridge Working Papers in Economics 0701, Faculty of Economics, University of Cambridge.
    6. Busetti, F. & Harvey, A., 2008. "When is a copula constant? A test for changing relationships," Cambridge Working Papers in Economics 0841, Faculty of Economics, University of Cambridge.
    7. Ferrara, L. & Koopman, S J., 2010. "Common business and housing market cycles in the Euro area from a multivariate decomposition," Working papers 275, Banque de France.
    8. Guilhem Bentoglio & Jacky Fayolle & Matthieu Lemoine, 2002. "Unity and Plurality of the European Cycle," Working Papers hal-03458584, HAL.
    9. Mikayilov, Jeyhun I. & Darandary, Abdulelah & Alyamani, Ryan & Hasanov, Fakhri J. & Alatawi, Hatem, 2020. "Regional heterogeneous drivers of electricity demand in Saudi Arabia: Modeling regional residential electricity demand," Energy Policy, Elsevier, vol. 146(C).
    10. Jeyhun I. Mikayilov & Shahriyar Mukhtarov & Jeyhun Mammadov, 2020. "Gasoline Demand Elasticities at the Backdrop of Lower Oil Prices: Fuel-Subsidizing Country Case," Energies, MDPI, vol. 13(24), pages 1-18, December.
    11. Christopher Klein & Shea Slonaker, 2010. "Chart Turnover and Sales in the Recorded Music Industry: 1990–2005," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 36(4), pages 351-372, June.
    12. Shahriyar Mukhtarov & Jeyhun I. Mikayilov & Sugra Humbatova & Vugar Muradov, 2020. "Do High Oil Prices Obstruct the Transition to Renewable Energy Consumption?," Sustainability, MDPI, vol. 12(11), pages 1-16, June.
    13. Xiaoshan Chen & Terence Mills, 2012. "Measuring the Euro area output gap using a multivariate unobserved components model containing phase shifts," Empirical Economics, Springer, vol. 43(2), pages 671-692, October.
    14. Siem Jan Koopman & Marius Ooms & André Lucas & Kees van Montfort & Victor Van Der Geest, 2008. "Estimating systematic continuous‐time trends in recidivism using a non‐Gaussian panel data model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 62(1), pages 104-130, February.
    15. Juan G Brida & Bibiana Lanzilotta & Lucia I Rosich, 2021. "On the empirical relations between producers expectations and economic growth," Economics Bulletin, AccessEcon, vol. 41(3), pages 1970-1982.
    16. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.
    17. Chen, Xiaoshan & MacDonald, Ronald, 2010. "Revisiting the Dollar-Euro Permanent Equilibrium Exchange Rate: Evidence from Multivariate Unobserved Components Models," SIRE Discussion Papers 2010-41, Scottish Institute for Research in Economics (SIRE).
    18. Fabio Busetti & Andrew Harvey, 2010. "Tests of strict stationarity based on quantile indicators," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(6), pages 435-450, November.

  30. Harvey, Andrew, 2001. "Testing in Unobserved Components Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(1), pages 1-19, January.

    Cited by:

    1. Webel, Karsten & Smyk, Anna, 2023. "Towards seasonal adjustment of infra-monthly time series with JDemetra+," Discussion Papers 24/2023, Deutsche Bundesbank.
    2. Tommaso PROIETTI, 2002. "Some Reflections on Trend-Cycle Decompositions with Correlated Components," Economics Working Papers ECO2002/23, European University Institute.
    3. Stefano Grassi & Tommaso Proietti, 2010. "Characterizing economic trends by Bayesian stochastic model specification search," EERI Research Paper Series EERI_RP_2010_25, Economics and Econometrics Research Institute (EERI), Brussels.
    4. Christophe Planas & Alessandro Rossi & Gabriele Fiorentini, 2008. "The marginal likelihood of Structural Time Series Models, with application to the euro area and US NAIRU," Working Paper series 21_08, Rimini Centre for Economic Analysis.
    5. Hansen, Peter R. & Lunde, Asger, 2014. "Estimating The Persistence And The Autocorrelation Function Of A Time Series That Is Measured With Error," Econometric Theory, Cambridge University Press, vol. 30(1), pages 60-93, February.
    6. Giancarlo Bruno & Marco Malgarini, 2002. "An Indicator of Economic Sentiment for the Italian Economy," ISAE Working Papers 28, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    7. Harvey, A.C. & Trimbur, T.M. & van Dijk, H.K., 2005. "Trends and cycles in economic time series: A Bayesian approach," Econometric Institute Research Papers EI 2005-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Tommaso Proietti & Eric Hillebrand, 2017. "Seasonal changes in central England temperatures," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(3), pages 769-791, June.
    9. Irma Hindrayanto & John A.D. Aston & Siem Jan Koopman & Marius Ooms, 2013. "Modelling trigonometric seasonal components for monthly economic time series," Applied Economics, Taylor & Francis Journals, vol. 45(21), pages 3024-3034, July.
    10. González-Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2023. "Modelling intervals of minimum/maximum temperatures in the Iberian Peninsula," DES - Working Papers. Statistics and Econometrics. WS 37968, Universidad Carlos III de Madrid. Departamento de Estadística.
    11. Frits Bijleveld & Jacques Commandeur & Phillip Gould & Siem Jan Koopman, 2008. "Model‐based measurement of latent risk in time series with applications," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 265-277, January.
    12. Fabio Busetti & A. M. Robert Taylor, 2003. "Testing against stochastic trend and seasonality in the presence of unattended breaks and unit roots," Temi di discussione (Economic working papers) 470, Bank of Italy, Economic Research and International Relations Area.
    13. Tommaso, Proietti & Alessandra, Luati, 2012. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," MPRA Paper 39600, University Library of Munich, Germany.
    14. Proietti, Tommaso & Pedregal, Diego J., 2023. "Seasonality in High Frequency Time Series," Econometrics and Statistics, Elsevier, vol. 27(C), pages 62-82.
    15. Guro Børnes Ringlund & Knut Einar Rosendahl & Terje Skjerpen, 2004. "Does oilrig activity react to oil price changes? An empirical investigation," Discussion Papers 372, Statistics Norway, Research Department.
    16. Fabio Busetti, 2006. "Tests of seasonal integration and cointegration in multivariate unobserved component models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 419-438, May.
    17. Matei Demetrescu & Uwe Hassler & Adina Tarcolea, 2010. "Testing for stationarity in large panels with cross-dependence, and US evidence on unit labor cost," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(8), pages 1381-1397.
    18. Stefano Grassi & Miguel Leon-Ledesma & Filippo Ferroni, 2016. "Fundamental shock selection in DSGE models," 2016 Meeting Papers 47, Society for Economic Dynamics.
    19. Busetti, Fabio & Taylor, A. M. Robert, 2004. "Tests of stationarity against a change in persistence," Journal of Econometrics, Elsevier, vol. 123(1), pages 33-66, November.
    20. Patrick Wilson & Simon Stevenson & Ralf Zurbruegg, 2007. "Foreign Property Shocks and the Impact on Domestic Securitized Real Estate Markets: An Unobserved Components Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 34(3), pages 407-424, April.
    21. Stefania Mignani & Marcello Pagnini, 2021. "How effective is financial education? Evidence from the Emilia-Romagna region," Working Paper series 21-08, Rimini Centre for Economic Analysis.
    22. Chen, Xiaoshan & MacDonald, Ronald, 2015. "Measuring the dollar–euro permanent equilibrium exchange rate using the unobserved components model," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 20-35.

  31. Fabio Busetti & Andrew Harvey, 2001. "Testing for the Presence of a Random Walk in Series with Structural Breaks," Journal of Time Series Analysis, Wiley Blackwell, vol. 22(2), pages 127-150, March.
    See citations under working paper version above.
  32. Andrew Harvey & Siem Jan Koopman, 2000. "Signal extraction and the formulation of unobserved components models," Econometrics Journal, Royal Economic Society, vol. 3(1), pages 84-107.
    See citations under working paper version above.
  33. Nyblom, Jukka & Harvey, Andrew, 2000. "Tests Of Common Stochastic Trends," Econometric Theory, Cambridge University Press, vol. 16(2), pages 176-199, April.
    See citations under working paper version above.
  34. Proietti, Tommaso & Harvey, Andrew, 2000. "A Beveridge-Nelson smoother," Economics Letters, Elsevier, vol. 67(2), pages 139-146, May.

    Cited by:

    1. Álvarez, Luis J. & Gómez-Loscos, Ana, 2018. "A menu on output gap estimation methods," Journal of Policy Modeling, Elsevier, vol. 40(4), pages 827-850.
    2. Tommaso PROIETTI, 2002. "Some Reflections on Trend-Cycle Decompositions with Correlated Components," Economics Working Papers ECO2002/23, European University Institute.
    3. Proietti, Tommaso, 2011. "Direct and iterated multistep AR methods for difference stationary processes," International Journal of Forecasting, Elsevier, vol. 27(2), pages 266-280, April.
    4. Tommaso Proietti, 2005. "Forecasting and signal extraction with misspecified models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(8), pages 539-556.
    5. Tommaso Proietti, 2009. "The Multistep Beveridge-Nelson Decomposition," EERI Research Paper Series EERI_RP_2009_24, Economics and Econometrics Research Institute (EERI), Brussels.
    6. Stefano Grassi & Tommaso Proietti, 2010. "Characterizing economic trends by Bayesian stochastic model specification search," EERI Research Paper Series EERI_RP_2010_25, Economics and Econometrics Research Institute (EERI), Brussels.
    7. Rainer Metz, 2011. "Do Kondratieff waves exist? How time series techniques can help to solve the problem," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(3), pages 205-238, October.
    8. J Keith Ord & Ralph D Snyder & Anne B Koehler & Rob J Hyndman & Mark Leeds, 2005. "Time Series Forecasting: The Case for the Single Source of Error State Space," Monash Econometrics and Business Statistics Working Papers 7/05, Monash University, Department of Econometrics and Business Statistics.
    9. Kum Hwa Oh & Eric Zivot & Drew Creal, 2006. "The Relationship between the Beveridge-Nelson Decomposition andUnobserved Component Models with Correlated Shocks," Working Papers UWEC-2006-16-FC, University of Washington, Department of Economics.

  35. Andrew Harvey & Chia‐Hui Chung, 2000. "Estimating the underlying change in unemployment in the UK," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 163(3), pages 303-309.

    Cited by:

    1. Marco Cacciotti & Cecilia Frale & Serena Teobaldo, 2013. "A new methodology for a quarterly measure of the Output Gap," Working Papers LuissLab 13103, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    2. Cecilia Frale & Libero Monteforte, "undated". "FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure," Working Papers 3, Department of the Treasury, Ministry of the Economy and of Finance.
    3. Wanger, Susanne & Weigand, Roland & Zapf, Ines, 2014. "Revision der IAB-Arbeitszeitrechnung 2014 : Grundlagen, methodische Weiterentwicklungen sowie ausgewählte Ergebnisse im Rahmen der Revision der Volkswirtschaftlichen Gesamtrechnungen," IAB-Forschungsbericht 201409, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    4. Rolando Peláez, 2012. "The housing bubble in real-time: the end of innocence," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(1), pages 211-225, January.
    5. Fabio H. Nieto & Luis Fernando Melo, 2001. "About a Coincidente Index for the State of the Economy," Borradores de Economia 194, Banco de la Republica de Colombia.
    6. Bisio, Laura & Moauro, Filippo, 2017. "Temporal disaggregation by dynamic regressions: recent developments in Italian quarterly national accounts," MPRA Paper 80211, University Library of Munich, Germany, revised 14 Jul 2017.
    7. Veenstra, Joost, 2015. "Output growth in German manufacturing, 1907–1936. A reinterpretation of time-series evidence," Explorations in Economic History, Elsevier, vol. 57(C), pages 38-49.
    8. Tommaso Proietti, 2004. "Temporal Disaggregation by State Space Methods: Dynamic Regression Methods Revisited," Econometrics 0411011, University Library of Munich, Germany.
    9. Proietti, Tommaso, 2008. "Estimation of Common Factors under Cross-Sectional and Temporal Aggregation Constraints: Nowcasting Monthly GDP and its Main Components," MPRA Paper 6860, University Library of Munich, Germany.
    10. David Leuwer & Bernd Süssmuth, 2018. "Assessing Temporary Product-Specific Subsidies: A Time Series Intervention Analysis," CESifo Working Paper Series 6946, CESifo.
    11. Víctor Gómez & Félix Aparicio‐Pérez, 2009. "A new state–space methodology to disaggregate multivariate time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 97-124, January.
    12. Krieg, Sabine & van den Brakel, Jan A., 2012. "Estimation of the monthly unemployment rate for six domains through structural time series modelling with cointegrated trends," Computational Statistics & Data Analysis, Elsevier, vol. 56(10), pages 2918-2933.
    13. Joan Paredes & Diego J. Pedregal & Javier J. Pérez, 2009. "A quarterly fiscal database for the euro area based on intra-annual fiscal information," Working Papers 0935, Banco de España.
    14. Cecilia Frale, "undated". "Do Surveys Help in Macroeconomic Variables Disaggregation and Estimation?," Working Papers wp2008-2, Department of the Treasury, Ministry of the Economy and of Finance.
    15. Xinshuai Dong & Haoyue Dai & Yewen Fan & Songyao Jin & Sathyamoorthy Rajendran & Kun Zhang, 2023. "On the Three Demons in Causality in Finance: Time Resolution, Nonstationarity, and Latent Factors," Papers 2401.05414, arXiv.org, revised Jan 2024.
    16. Andrew Harvey, 2002. "Trends, Cycles and Convergence," Working Papers Central Bank of Chile 155, Central Bank of Chile.
    17. Eliana González & Luis F. Melo & Luis E. Rojas & Brayan Rojas, 2010. "Estimations of the natural rate of interest in Colombia," Borradores de Economia 7667, Banco de la Republica.
    18. Teresa Leal & Diego Pedregal & Javier Pérez, 2011. "Short-term monitoring of the Spanish government balance," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 2(1), pages 97-119, March.
    19. Grassi, Stefano & Proietti, Tommaso & Frale, Cecilia & Marcellino, Massimiliano & Mazzi, Gianluigi, 2015. "EuroMInd-C: A disaggregate monthly indicator of economic activity for the Euro area and member countries," International Journal of Forecasting, Elsevier, vol. 31(3), pages 712-738.
    20. Cecilia Frale, Serena Teobaldo, Marco Cacciotti, Alessandra Caretta, 2013. "A Quarterly Measure Of Potential Output In The New European Fiscal Framework," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 67(2), pages 181-197, April-Jun.
    21. Marcellino, Massimiliano & Proietti, Tommaso & Frale, Cecilia & Mazzi, Gian Luigi, 2008. "A Monthly Indicator of the Euro Area GDP," CEPR Discussion Papers 7007, C.E.P.R. Discussion Papers.
    22. Viv Hall & John McDermott, 2007. "A Quarterly Post-World War II Real GDP Series for New Zealand," Working Papers 07_13, Motu Economic and Public Policy Research.
    23. Cecilia Frale & Massimiliano Marcellino & Gian Luigi Mazzi & Tommaso Proietti, 2010. "Survey data as coincident or leading indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 109-131.
    24. Hanjo Odendaal & Monique Reid & Johann F. Kirsten, 2020. "Media‐Based Sentiment Indices as an Alternative Measure of Consumer Confidence," South African Journal of Economics, Economic Society of South Africa, vol. 88(4), pages 409-434, December.
    25. Javier Pérez & A. Sánchez, 2011. "Is there a signalling role for public wages? Evidence for the euro area based on macro data," Empirical Economics, Springer, vol. 41(2), pages 421-445, October.
    26. Jan A. Brakel & Sabine Krieg, 2016. "Small area estimation with state space common factor models for rotating panels," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(3), pages 763-791, June.
    27. Orair, Rodrigo Octávio & Silva, Wesley de Jesus, 2013. "Subnational Government Investment in Brazil: Estimation and Analysis by State Space Models," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 33(1), September.
    28. Caterina Schiavoni & Franz Palm & Stephan Smeekes & Jan van den Brakel, 2021. "A dynamic factor model approach to incorporate Big Data in state space models for official statistics," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 324-353, January.
    29. Koopman, Siem Jan & Harvey, Andrew, 2003. "Computing observation weights for signal extraction and filtering," Journal of Economic Dynamics and Control, Elsevier, vol. 27(7), pages 1317-1333, May.
    30. Tommaso, Proietti & Alessandra, Luati, 2012. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," MPRA Paper 39600, University Library of Munich, Germany.
    31. Tommaso Proietti, 2007. "Band Spectral Estimation for Signal Extraction," CEIS Research Paper 104, Tor Vergata University, CEIS.
    32. Lind, Jo Thori, 2004. "Repeated surveys and the Kalman filter," Memorandum 19/2004, Oslo University, Department of Economics.
    33. Danny Pfeffermann, 2022. "Time series modelling of repeated survey data for estimation of finite population parameters," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1757-1777, October.
    34. Weigand, Roland & Wanger, Susanne & Zapf, Ines, 2015. "Factor structural time series models for official statistics with an application to hours worked in Germany," IAB-Discussion Paper 201522, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    35. Marco Cacciotti & Cecilia Frale & Serena Teobaldo, 2013. "A new methodology for a quarterly measure of the output gap," Working Papers 6, Department of the Treasury, Ministry of the Economy and of Finance.
    36. Jo Thori Lind, 2002. "Small continuous surveys and the Kalman filter," Discussion Papers 333, Statistics Norway, Research Department.
    37. Tommaso Proietti & Alessandro Giovannelli, 2020. "Nowcasting Monthly GDP with Big Data: a Model Averaging Approach," CEIS Research Paper 482, Tor Vergata University, CEIS, revised 12 May 2020.
    38. Francisco de Castro & Francisco Martí & Antonio Montesinos & Javier J. Pérez & A. Jesús Sánchez-Fuentes, 2014. "Fiscal policies in Spain: Main stylises facts revisited," Working Papers 1408, Banco de España.
    39. Nicholas T. Longford, 2004. "Missing data and small area estimation in the UK Labour Force Survey," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(2), pages 341-373, May.
    40. Huang, Yu-Lieh, 2012. "Measuring business cycles: A temporal disaggregation model with regime switching," Economic Modelling, Elsevier, vol. 29(2), pages 283-290.
    41. Jaworski Stanisław, 2020. "A Few Remarks on the Stochastic Structure of the Unemployment Rate in Poland by Gender," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 24(2), pages 41-52, June.
    42. Pedregal, D.J. & Dejuán, O. & Gómez, N. & Tobarra, M.A., 2009. "Modelling demand for crude oil products in Spain," Energy Policy, Elsevier, vol. 37(11), pages 4417-4427, November.
    43. Diego J. Pedregal & Javier J. Pérez & Antonio Sánchez Fuentes, 2014. "A Tookit to strengthen Government," Hacienda Pública Española / Review of Public Economics, IEF, vol. 211(4), pages 117-146, December.
    44. Du, Rex Yuxing & Kamakura, Wagner A., 2015. "Improving the statistical performance of tracking studies based on repeated cross-sections with primary dynamic factor analysis," International Journal of Research in Marketing, Elsevier, vol. 32(1), pages 94-112.
    45. Andrew C. Harvey, 2020. "Time series models for epidemics: leading indicators, control groups and policy assessment," National Institute of Economic and Social Research (NIESR) Discussion Papers 517, National Institute of Economic and Social Research.
    46. Sieds, 2013. "Complete Volume LXVII n.2 2013," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 67(2), pages 1-197, April-Jun.
    47. Caio Gonçalves & Luna Hidalgo & Denise Silva & Jan van den Brakel, 2022. "Single‐month unemployment rate estimates for the Brazilian Labour Force Survey using state‐space models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1707-1732, October.
    48. Pérez, Javier J. & Pedregal, Diego J., 2008. "Should quarterly government finance statistics be used for fiscal surveillane in Europe?," Working Paper Series 937, European Central Bank.
    49. Moauro, Filippo, 2010. "A monthly indicator of employment in the euro area: real time analysis of indirect estimates," MPRA Paper 27797, University Library of Munich, Germany, revised 30 Dec 2010.
    50. Caterina Schiavoni & Siem Jan Koopman & Franz Palm & Stephan Smeekes & Jan van den Brakel, 2021. "Time-varying state correlations in state space models and their estimation via indirect inference," Tinbergen Institute Discussion Papers 21-020/III, Tinbergen Institute.
    51. David J. Hand, 2018. "Statistical challenges of administrative and transaction data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 555-605, June.

  36. Andrew Harvey & Mariane Streibel, 1998. "Tests for Deterministic Versus Indeterministic Cycles," Journal of Time Series Analysis, Wiley Blackwell, vol. 19(5), pages 505-529, September.

    Cited by:

    1. Martyna Marczak & Thomas Beissinger, 2013. "Real wages and the business cycle in Germany," Empirical Economics, Springer, vol. 44(2), pages 469-490, April.
    2. Palumbo, D., 2021. "Testing and Modelling Time Series with Time Varying Tails," Cambridge Working Papers in Economics 2111, Faculty of Economics, University of Cambridge.

  37. Harvey, Andrew & Streibel, Mariane, 1998. "Testing for a slowly changing level with special reference to stochastic volatility," Journal of Econometrics, Elsevier, vol. 87(1), pages 167-189, August.

    Cited by:

    1. Poncela, Pilar & Ruiz Ortega, Esther, 2012. "More is not always better : back to the Kalman filter in dynamic factor models," DES - Working Papers. Statistics and Econometrics. WS ws122317, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Ruiz Esther & Pérez Ana, 2012. "Maximally Autocorrelated Power Transformations: A Closer Look at the Properties of Stochastic Volatility Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(3), pages 1-33, September.
    3. Harvey, A. & Chakravarty, T., 2008. "Beta-t-(E)GARCH," Cambridge Working Papers in Economics 0840, Faculty of Economics, University of Cambridge.
    4. Busettti, F. & Harvey, A., 2007. "Tests of time-invariance," Cambridge Working Papers in Economics 0701, Faculty of Economics, University of Cambridge.
    5. Busetti, F. & Harvey, A., 2008. "When is a copula constant? A test for changing relationships," Cambridge Working Papers in Economics 0841, Faculty of Economics, University of Cambridge.
    6. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024.
    7. Alin Sima, 2008. "Stylized Facts and Discrete Stochastic Volatility Models," Advances in Economic and Financial Research - DOFIN Working Paper Series 10, Bucharest University of Economics, Center for Advanced Research in Finance and Banking - CARFIB.
    8. Davide Delle Monache & Stefano Grassi & Paolo Santucci de Magistris, 2017. "Does the ARFIMA really shift?," CREATES Research Papers 2017-16, Department of Economics and Business Economics, Aarhus University.
    9. Petrella, Ivan & Delle Monache, Davide & De Polis, Andrea, 2022. "Modeling and Forecasting Macroeconomic Downside Risk," CEPR Discussion Papers 15109, C.E.P.R. Discussion Papers.
    10. Harvey, Andrew & Thiele, Stephen, 2016. "Testing against changing correlation," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 575-589.
    11. David McMillan, 2001. "Common stochastic volatility trend in European exchange rates," Applied Economics Letters, Taylor & Francis Journals, vol. 8(9), pages 605-608.
    12. M. Angeles Carnero, 2004. "Persistence and Kurtosis in GARCH and Stochastic Volatility Models," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 319-342.
    13. Carmen Broto & Esther Ruiz, 2004. "Estimation methods for stochastic volatility models: a survey," Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 613-649, December.
    14. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.
    15. Fabio Busetti & Andrew Harvey, 2010. "Tests of strict stationarity based on quantile indicators," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(6), pages 435-450, November.
    16. Mora Galán, Alberto & Pérez, Ana & Ruiz Ortega, Esther, 2004. "Stochastic volatility models and the Taylor effect," DES - Working Papers. Statistics and Econometrics. WS ws046315, Universidad Carlos III de Madrid. Departamento de Estadística.
    17. Pena, Daniel & Rodriguez, Julio, 2005. "Detecting nonlinearity in time series by model selection criteria," International Journal of Forecasting, Elsevier, vol. 21(4), pages 731-748.

  38. Harvey, Andrew, 1997. "Trends, Cycles and Autoregressions," Economic Journal, Royal Economic Society, vol. 107(440), pages 192-201, January.

    Cited by:

    1. Tehreem Fatima & Enjun Xia & Muhammad Ahad, 2019. "Oil demand forecasting for China: a fresh evidence from structural time series analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(3), pages 1205-1224, June.
    2. Joel Cariolle & Michaël Goujon, 2015. "Measuring macroeconomic instability: a critical survey illustrated with exports series," Post-Print halshs-01273229, HAL.
    3. David C Broadstock & Lester C Hunt, 2009. "Quantifying the Impact of Exogenous Non-Economic Factors on UK Transport Oil Demand," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 123, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    4. Carl Chiarella & Shenhuai Gao, 2002. "Type I Spurious Regression in Econometrics," Working Paper Series 114, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    5. R. Barrell & D. Karim & C. Macchiarelli, 2020. "Towards an understanding of credit cycles: do all credit booms cause crises?," The European Journal of Finance, Taylor & Francis Journals, vol. 26(10), pages 978-993, July.
    6. Terence C. Mills, 2004. "Time Series Modelling of Trends in Northern Hemispheric Average Temperature Series," Energy & Environment, , vol. 15(5), pages 743-753, September.
    7. Mauricio Mayorga Martínez & Evelyn Muñoz Salas, 2004. "¿Existe disciplina de mercado en el sistema bancario costarricense?," Monetaria, CEMLA, vol. 0(3), pages 263-289, julio-sep.
    8. Regina Kaiser & Agustín Maravall, 2002. "A Complete Model-Based Interpretation of the Hodrick-Prescott Filter: Spuriousness Reconsidered," Working Papers 0208, Banco de España.
    9. Maravall, A. & del Rio, A., 2007. "Temporal aggregation, systematic sampling, and the Hodrick-Prescott filter," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 975-998, October.
    10. Moreno, Manuel & Novales, Alfonso & Platania, Federico, 2019. "Long-term swings and seasonality in energy markets," European Journal of Operational Research, Elsevier, vol. 279(3), pages 1011-1023.
    11. Mehdi Mili & Jean‐Michel Sahut & Frédéric Teulon, 2020. "Shift‐contagion in energy markets and global crisis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 725-736, August.
    12. Rolando Peláez, 2012. "The housing bubble in real-time: the end of innocence," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(1), pages 211-225, January.
    13. Ron Smith, 1999. "Unit roots and all that: the impact of time-series methods on macroeconomics," Journal of Economic Methodology, Taylor & Francis Journals, vol. 6(2), pages 239-258.
    14. Dagher, Leila & El Hariri, Sadika, 2013. "The impact of global oil price shocks on the Lebanese stock market," Energy, Elsevier, vol. 63(C), pages 366-374.
    15. SHIRANI-FAKHR, Zohreh & KHOSHAKHLAGH, Rahman & SHARIFI, Alimorad, 2015. "Estimating Demand Function For Electricity In Industrial Sector Of Iran Using Structural Time Series Model (Stsm)," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 15(1), pages 143-160.
    16. Zafer Dilaver & Lester C Hunt, 2010. "Modelling and Forecasting Turkish Residential Electricity Demand," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 131, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    17. Koukouritakis, Minoas, 2013. "Expectations hypothesis in the context of debt crisis: Evidence from five major EU countries," Research in Economics, Elsevier, vol. 67(3), pages 243-258.
    18. Rodrigues, Niágara & Losekann, Luciano & Silveira Filho, Getulio, 2018. "Demand of automotive fuels in Brazil: Underlying energy demand trend and asymmetric price response," Energy Economics, Elsevier, vol. 74(C), pages 644-655.
    19. Mohammad Al Dubyan & Anwar Gasim, 2020. "Energy Price Reform in Saudi Arabia: Modeling the Economic and Environmental Impact and Understanding the Demand Response," Discussion Papers ks--2020-dp12, King Abdullah Petroleum Studies and Research Center.
    20. Lester C Hunt & Guy Judge & Yasushi Ninomiya, 2003. "Modelling Underlying Energy Demand Trends," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 105, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    21. Bhattacharyya, Subhes C. & Timilsina, Govinda R., 2010. "Modelling energy demand of developing countries: Are the specific features adequately captured?," Energy Policy, Elsevier, vol. 38(4), pages 1979-1990, April.
    22. Bhaskara Rao, 2005. "Estimating Short and Long Run Relationships: A Guide to the Applied Economist," Econometrics 0508013, University Library of Munich, Germany.
    23. Adeyemi, Olutomi I. & Broadstock, David C. & Chitnis, Mona & Hunt, Lester C. & Judge, Guy, 2010. "Asymmetric price responses and the underlying energy demand trend: Are they substitutes or complements? Evidence from modelling OECD aggregate energy demand," Energy Economics, Elsevier, vol. 32(5), pages 1157-1164, September.
    24. Aaron Smith, 2005. "Forecasting in the presence of level shifts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(8), pages 557-574.
    25. Markmann, Holger & Zietz, Joachim, 2017. "Determining the effectiveness of the Eurosystem’s Covered Bond Purchase Programs on secondary markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 314-327.
    26. Ackah, Ishmael, 2014. "Determinants of natural gas demand in Ghana," MPRA Paper 59214, University Library of Munich, Germany.
    27. Pelaez, Rolando F., 2004. "Dating the productivity slowdown with a structural time-series model," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(2), pages 253-264, May.
    28. Suzanne McCoskey & Chihwa Kao, 1999. "A Monte Carlo Comparison of Tests for Cointegration in Panel Data," Center for Policy Research Working Papers 3, Center for Policy Research, Maxwell School, Syracuse University.
    29. Rao, B. Bhaskara & Rao, Gyaneshwar, 2008. "Cointegration and the demand for gasoline," MPRA Paper 11396, University Library of Munich, Germany.
    30. Sulaiman T. Al-Abduljader, 2019. "Interdependence of Securitized Real Estate in Frontier Markets," International Real Estate Review, Global Social Science Institute, vol. 22(1), pages 83-108.
    31. Zietz, Joachim A. & Penn, David A., 2008. "An Unobserved Components Forecasting Model of Non-Farm Employment for the Nashville MSA," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 38(1), pages 1-10.
    32. Neha Seth & Monica Sighania, 2017. "Financial market contagion: selective review of reviews," Qualitative Research in Financial Markets, Emerald Group Publishing Limited, vol. 9(4), pages 391-408, November.
    33. Abdulnasser Hatemi-J & Eduardo Roca, 2006. "Calculating the optimal hedge ratio: constant, time varying and the Kalman Filter approach," Applied Economics Letters, Taylor & Francis Journals, vol. 13(5), pages 293-299.
    34. Zietz, Joachim & Traian, Anca, 2014. "When was the U.S. housing downturn predictable? A comparison of univariate forecasting methods," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 271-281.
    35. John Dimitropoulos & Lester C Hunt & Guy Judge, 2004. "Estimating Underlying Energy Demand Trends using UK Annual Data," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 108, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    36. Lester C Hunt & David L Ryan, 2014. "Economic Modelling of Energy Services: Rectifying Misspecified Energy Demand Functions," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 147, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    37. Homagni Choudhury & Zoltan Laszlo Kopacsi & Gunjan Saxena & Nishikant Mishra, 2021. "The Ethical Dimension in Political Market Orientation: A Framework for Evaluating the Impact of India’s Look East Policy on Regional Income Convergence," Journal of Business Ethics, Springer, vol. 168(2), pages 353-372, January.
    38. Gustavo Bussinger, 2004. "El canal de crédito como mecanismo de transmisión de la política monetaria en Brasil," Monetaria, CEMLA, vol. 0(3), pages 243-262, julio-sep.
    39. Nobuaki Hamaguchi & Silvio Miyazaki & Leonardo Correia, 2014. "State Space Application to Recent Automobile Sector Triangle Trade between Japan and Latin America," Discussion Paper Series DP2014-05, Research Institute for Economics & Business Administration, Kobe University.
    40. Gebhard Flaig & Claudia Plötscher, 2000. "Estimating the Output Gap Using Business Survey Data - A Bivariate Structural Time Series Model for the German Economy," CESifo Working Paper Series 233, CESifo.
    41. Zafer Dilaver & Lester C Hunt, 2010. "Industrial Electricity Demand for Turkey: A Structural Time Series Analysis," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 129, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    42. Imad Moosa & Jae Kim, 2004. "Direct and indirect forecasting of the money multiplier and velocity of circulation in the United Kingdom," International Economic Journal, Taylor & Francis Journals, vol. 18(1), pages 103-118.
    43. Maria J. Herrerias & Eric Girardin, 2013. "Seasonal Patterns of Energy in China," Post-Print hal-01499617, HAL.
    44. Rao, B. Bhaskara & Rao, Gyaneshwar, 2007. "Structural breaks and energy efficiency in Fiji," MPRA Paper 3258, University Library of Munich, Germany.
    45. Giannellis, Nikolaos & Koukouritakis, Minoas, 2013. "Exchange rate misalignment and inflation rate persistence: Evidence from Latin American countries," International Review of Economics & Finance, Elsevier, vol. 25(C), pages 202-218.
    46. Bruno Chiarini, 1998. "Cyclicality of real wages and adjustment costs," Applied Economics, Taylor & Francis Journals, vol. 30(9), pages 1239-1250.
    47. José R. Sánchez Fung, 2004. "Reglas monetarias, metas de inflación y sus aplicaciones potenciales de la República Dominicana," Monetaria, CEMLA, vol. 0(3), pages 291-323, julio-sep.
    48. António Afonso & João Jalles, 2014. "A longer-run perspective on fiscal sustainability," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 41(4), pages 821-847, November.
    49. Atul Anand & L. Suganthi, 2017. "Forecasting of Electricity Demand by Hybrid ANN-PSO Models," International Journal of Energy Optimization and Engineering (IJEOE), IGI Global, vol. 6(4), pages 66-83, October.
    50. Inglesi-Lotz, R., 2011. "The evolution of price elasticity of electricity demand in South Africa: A Kalman filter application," Energy Policy, Elsevier, vol. 39(6), pages 3690-3696, June.
    51. Byamugisha, Frank F.K., 1999. "How land registration affects financial development and economic growth in Thailand," Policy Research Working Paper Series 2241, The World Bank.
    52. Stephen Bazen & Velayoudom Marimoutou, 2002. "Looking for a Needle in a Haystack? A Re‐examination of the Time Series Relationship between Teenage Employment and Minimum Wages in the United States," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(supplemen), pages 699-725, December.
    53. Moosa, Imad, 2011. "Operational risk as a function of the state of the economy," Economic Modelling, Elsevier, vol. 28(5), pages 2137-2142, September.
    54. Mario Mazzocchi & Davide Delle Monache & Alexandra Lobb, 2006. "A structural time series approach to modelling multiple and resurgent meat scares in Italy," Applied Economics, Taylor & Francis Journals, vol. 38(14), pages 1677-1688.
    55. Javid, Muhammad & Khan, Farzana Naheed & Arif, Umaima, 2022. "Income and price elasticities of natural gas demand in Pakistan: A disaggregated analysis," Energy Economics, Elsevier, vol. 113(C).
    56. Atalla, Tarek N. & Hunt, Lester C., 2016. "Modelling residential electricity demand in the GCC countries," Energy Economics, Elsevier, vol. 59(C), pages 149-158.
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    1. Juan Sebastián Becerra C. & Luis Ceballos S. & Felipe Córdova F. & Michael Pedersen, 2010. "Market Interest Rate Dynamics in Times of Financial Turmoil," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 13(1), pages 5-22, April.
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    3. Chen Zhen & Mary Muth & Abigail Okrent & Shawn Karns & Derick Brown & Peter Siegel, 2019. "Do differences in reported expenditures between household scanner data and expenditure surveys matter in health policy research?," Health Economics, John Wiley & Sons, Ltd., vol. 28(6), pages 782-800, June.
    4. Dewenter, Ralf & Heimeshoff, Ulrich, 2016. "Predicting advertising volumes: A structural time series approach," DICE Discussion Papers 228, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    5. Joao Tovar Jalles, 2009. "Structural time series models and the Kalman filter: a concise review," Nova SBE Working Paper Series wp541, Universidade Nova de Lisboa, Nova School of Business and Economics.
    6. Rodriguez, Gloria Martin & Hernandez, Jose Juan Caceres, 2002. "Canary Island Tomato Exports: A Structural Analysis of Seasonality," 2002 International Congress, August 28-31, 2002, Zaragoza, Spain 24901, European Association of Agricultural Economists.
    7. Rishab Guha & Serena Ng, 2019. "A Machine Learning Analysis of Seasonal and Cyclical Sales in Weekly Scanner Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 403-436, National Bureau of Economic Research, Inc.
    8. Barend Abeln & Jan P.A.M. Jacobs, 2021. "COVID-19 and seasonal adjustment," CAMA Working Papers 2021-23, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. Ralf Dewenter & Ulrich Heimeshoff, 2017. "Predicting Advertising Volumes Using Structural Time Series Models: A Case Study," Economics Bulletin, AccessEcon, vol. 37(3), pages 1644-1652.
    10. Serena Ng, 2017. "Opportunities and Challenges: Lessons from Analyzing Terabytes of Scanner Data," NBER Working Papers 23673, National Bureau of Economic Research, Inc.
    11. Martin-Rodriguez, Gloria & Caceres-Hernandez, Jose Juan, 2009. "The Proportion of the Seasonal Period as a Season Index in Weekly Agricultural Data," 2009 Conference, August 16-22, 2009, Beijing, China 49956, International Association of Agricultural Economists.
    12. Kaushik Bhattacharya & Sunny Kumar Singh, 2016. "Impact of Payment Technology on Seasonality of Currency in Circulation: Evidence from the USA and India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(1), pages 117-136, June.
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    21. García, Juan R. & Pacce, Matías & Rodrigo, Tomasa & Ruiz de Aguirre, Pep & Ulloa, Camilo A., 2021. "Measuring and forecasting retail trade in real time using card transactional data," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1235-1246.
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    27. Martin-Rodriguez, Gloria & Caceres-Hernandez, Jose Juan, 2012. "Forecasting weekly Canary tomato exports from annual surface data," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126364, International Association of Agricultural Economists.
    28. Ollech, Daniel, 2018. "Seasonal adjustment of daily time series," Discussion Papers 41/2018, Deutsche Bundesbank.
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  40. Harvey, Andrew C & Shephard, Neil, 1996. "Estimation of an Asymmetric Stochastic Volatility Model for Asset Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 429-434, October.

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    9. Casas, Isabel & Lopes Moreira Da Veiga, María Helena, 2019. "Exploring option pricing and hedging via volatility asymmetry," DES - Working Papers. Statistics and Econometrics. WS 28234, Universidad Carlos III de Madrid. Departamento de Estadística.
    10. Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2009. "Asymmetry and Leverage in Realized Volatility," CARF F-Series CARF-F-167, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
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    1. Abanto-Valle, Carlos A. & Rodríguez, Gabriel & Garrafa-Aragón, Hernán B., 2021. "Stochastic Volatility in Mean: Empirical evidence from Latin-American stock markets using Hamiltonian Monte Carlo and Riemann Manifold HMC methods," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 272-286.

  42. Harvey, Andrew & Toulson, Sabine, 1994. "Review of '4thought'," International Journal of Forecasting, Elsevier, vol. 10(1), pages 35-41, June.

    Cited by:

    1. Wu, Yih-Jiuan, 1998. "Exchange rate forecasting: an application of radial basis function neural networks," ISU General Staff Papers 1998010108000013540, Iowa State University, Department of Economics.

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    Cited by:

    1. Kvamsdal, Sturla F., 2012. "Technological Change in Renewable Resource Industries: An Alternative Estimation Approach," Discussion Papers 2012/14, Norwegian School of Economics, Department of Business and Management Science.
    2. Sturla Furunes Kvamsdal, 2016. "Technical Change as a Stochastic Trend in a Fisheries Model," Marine Resource Economics, University of Chicago Press, vol. 31(4), pages 403-419.
    3. Martyn Duffy, 2006. "Tobacco consumption and policy in the United Kingdom," Applied Economics, Taylor & Francis Journals, vol. 38(11), pages 1235-1257.

  47. Harvey, Andrew C & Koopman, Siem Jan, 1992. "Diagnostic Checking of Unobserved-Components Time Series Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 377-389, October.

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      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
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    4. Marczak, Martyna & Proietti, Tommaso, 2015. "Outlier Detection in Structural Time Series Models: the Indicator Saturation Approach," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113137, Verein für Socialpolitik / German Economic Association.
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    6. George M. Constantinides & Anisha Ghosh, 2008. "Asset Pricing Tests with Long Run Risks in Consumption Growth," NBER Working Papers 14543, National Bureau of Economic Research, Inc.
    7. Satchell, Steve & Timmermann, Allan, 1995. "On the optimality of adaptive expectations: Muth revisited," International Journal of Forecasting, Elsevier, vol. 11(3), pages 407-416, September.
    8. Tommaso Proietti, 2004. "Temporal Disaggregation by State Space Methods: Dynamic Regression Methods Revisited," Econometrics 0411011, University Library of Munich, Germany.
    9. Proietti, Tommaso, 2007. "Signal extraction and filtering by linear semiparametric methods," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 935-958, October.
    10. Fabio Trojani & Markus Leippold & Paolo Vanini, 2005. "Learning and Asset Prices under Ambiguous Information," University of St. Gallen Department of Economics working paper series 2005 2005-03, Department of Economics, University of St. Gallen.
    11. Cecilia Frale, "undated". "Do Surveys Help in Macroeconomic Variables Disaggregation and Estimation?," Working Papers wp2008-2, Department of the Treasury, Ministry of the Economy and of Finance.
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    16. Hsu, Po-Hsuan, 2009. "Technological innovations and aggregate risk premiums," Journal of Financial Economics, Elsevier, vol. 94(2), pages 264-279, November.
    17. Davide Delle Monache & Stefano Grassi & Paolo Santucci de Magistris, 2017. "Does the ARFIMA really shift?," CREATES Research Papers 2017-16, Department of Economics and Business Economics, Aarhus University.
    18. Cecilia Frale & Massimiliano Marcellino & Gian Luigi Mazzi & Tommaso Proietti, 2010. "Survey data as coincident or leading indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 109-131.
    19. Banerjee, A. & Malik, S., 2012. "The changing role of expectations in US monetary policy: A new look using the Livingston Survey," Working papers 376, Banque de France.
    20. Massimiliano De Santis, 2005. "Interpreting Aggregate Stock Market Behavior: How Far Can the Standard Model Go?," Money Macro and Finance (MMF) Research Group Conference 2005 5, Money Macro and Finance Research Group.
    21. De Santis Massimiliano, 2010. "Demystifying the Equity Premium," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-33, May.
    22. Grammig, Joachim & Küchlin, Eva-Maria, 2017. "A two-step indirect inference approach to estimate the long-run risk asset pricing model," CFS Working Paper Series 572, Center for Financial Studies (CFS).
    23. Sanjoy Sinha & Abdus Sattar, 2015. "Inference in semi-parametric spline mixed models for longitudinal data," METRON, Springer;Sapienza Università di Roma, vol. 73(3), pages 377-395, December.
    24. Tae‐Hwan Kim & Stephan Pfaffenzeller & Tony Rayner & Paul Newbold, 2003. "Testing for Linear Trend with Application to Relative Primary Commodity Prices," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(5), pages 539-551, September.
    25. Gourieroux, Christian & Jasiak, Joann, 2010. "Inference for Noisy Long Run Component Process," MPRA Paper 98987, University Library of Munich, Germany.
    26. Nasir, Muhammad Ali, 2021. "Zero Lower Bound and negative interest rates: Choices for monetary policy in the UK," Journal of Policy Modeling, Elsevier, vol. 43(1), pages 200-229.
    27. Agbeyegbe, Terence D., 2020. "Bayesian analysis of output gap in Barbados," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
    28. Giuseppe Ciaburro & Gino Iannace, 2021. "Machine Learning-Based Algorithms to Knowledge Extraction from Time Series Data: A Review," Data, MDPI, vol. 6(6), pages 1-30, May.
    29. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2022. "An Alternative Estimation Method for Time-Varying Parameter Models," Econometrics, MDPI, vol. 10(2), pages 1-27, April.
    30. Grammig, Joachim & Küchlin, Eva-Maria, 2017. "A two-step indirect inference approach to estimate the long-run risk asset pricing model," CFR Working Papers 17-01, University of Cologne, Centre for Financial Research (CFR).
    31. Robert B. Barsky & J. Bradford De Long, 1992. "Why Does the Stock Market Fluctuate?," NBER Working Papers 3995, National Bureau of Economic Research, Inc.
    32. Kellard, Neil & Wohar, Mark E., 2006. "On the prevalence of trends in primary commodity prices," Journal of Development Economics, Elsevier, vol. 79(1), pages 146-167, February.
    33. Georg Kaltenbrunner & Lars Lochstoer, 2007. "Long-Run Risk through Consumption Smoothing," 2007 Meeting Papers 25, Society for Economic Dynamics.
    34. Luca Benzoni & Pierre Collin-Dufresne & Robert S. Goldstein, 2010. "Explaining asset pricing puzzles associated with the 1987 market crash," Working Paper Series WP-2010-10, Federal Reserve Bank of Chicago.
    35. Marc K. Francke & Siem Jan Koopman & Aart F. De Vos, 2010. "Likelihood functions for state space models with diffuse initial conditions," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(6), pages 407-414, November.
    36. Newbold, Paul & Leybourne, Stephen & Wohar, Mark E., 2001. "Trend-stationarity, difference-stationarity, or neither: further diagnostic tests with an application to U.S. Real GNP, 1875-1993," Journal of Economics and Business, Elsevier, vol. 53(1), pages 85-102.
    37. Kim, Chang-Jin & Kim, Jaeho, 2013. "The `Pile-up Problem' in Trend-Cycle Decomposition of Real GDP: Classical and Bayesian Perspectives," MPRA Paper 51118, University Library of Munich, Germany.
    38. Kellard, Neil & Mark E Wohar, 2003. "Trends and Persistence in Primary Commodity Prices," Royal Economic Society Annual Conference 2003 118, Royal Economic Society.
    39. James H. Stock & Mark W. Watson, 1996. "Asymptotically Median Unbiased Estimation of Coefficient Variance in a Time Varying Parameter Model," NBER Technical Working Papers 0201, National Bureau of Economic Research, Inc.
    40. Yang, Wei, 2011. "Long-run risk in durable consumption," Journal of Financial Economics, Elsevier, vol. 102(1), pages 45-61, October.
    41. Han, Yang & Liu, Zehao & Ma, Jun, 2020. "Growth cycles and business cycles of the Chinese economy through the lens of the unobserved components model," China Economic Review, Elsevier, vol. 63(C).
    42. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2017. "An Alternative Estimation Method of a Time-Varying Parameter Model," Papers 1707.06837, arXiv.org, revised Dec 2017.
    43. Caterina Schiavoni & Siem Jan Koopman & Franz Palm & Stephan Smeekes & Jan van den Brakel, 2021. "Time-varying state correlations in state space models and their estimation via indirect inference," Tinbergen Institute Discussion Papers 21-020/III, Tinbergen Institute.

  51. Fernandez, F Javier & Harvey, Andrew C, 1990. "Seemingly Unrelated Time Series Equations and a Test for Homogeneity," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 71-81, January.

    Cited by:

    1. Corberán-Vallet, Ana & Bermúdez, José D. & Vercher, Enriqueta, 2011. "Forecasting correlated time series with exponential smoothing models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 252-265.
    2. Alejandro Ferrer Pérez & José Casals Carro & Sonia Sotoca López, 2014. "Linking the problems of estimating and allocating unconditional capital," Documentos de Trabajo del ICAE 2014-13, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    3. Strickland, Chris M. & Turner, Ian. W. & Denham, Robert & Mengersen, Kerrie L., 2009. "Efficient Bayesian estimation of multivariate state space models," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4116-4125, October.
    4. Corberán-Vallet, Ana & Bermúdez, José D. & Vercher, Enriqueta, 2011. "Forecasting correlated time series with exponential smoothing models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 252-265, April.
    5. Iñaki Bildosola & Pilar Gonzalez & Paz Moral, 2017. "An approach for modelling and forecasting research activity related to an emerging technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 557-572, July.
    6. K. Triantafyllopoulos, 2007. "Covariance estimation for multivariate conditionally Gaussian dynamic linear models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(8), pages 551-569.
    7. Moauro, Filippo, 2010. "A monthly indicator of employment in the euro area: real time analysis of indirect estimates," MPRA Paper 27797, University Library of Munich, Germany, revised 30 Dec 2010.

  52. Harvey, A. C. & Stock, James H., 1989. "Estimating integrated higher-order continuous time autoregressions with an application to money-income causality," Journal of Econometrics, Elsevier, vol. 42(3), pages 319-336, November.

    Cited by:

    1. Michael Thornton & Marcus Chambers, 2016. "Continuous Time ARMA Processes: Discrete Time Representation and Likelihood Evaluation," Discussion Papers 16/10, Department of Economics, University of York.
    2. McCrorie, J. Roderick & Chambers, Marcus J., 2006. "Granger causality and the sampling of economic processes," Journal of Econometrics, Elsevier, vol. 132(2), pages 311-336, June.
    3. Vicky Fasen-Hartmann & Celeste Mayer, 2022. "Whittle estimation for continuous-time stationary state space models with finite second moments," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(2), pages 233-270, April.
    4. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    5. Jewitt, Giles & Roderick McCrorie, J., 2005. "Computing estimates of continuous time macroeconometric models on the basis of discrete data," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 397-416, April.
    6. Michael A. Thornton & Marcus J. Chambers, 2013. "Temporal aggregation in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 13, pages 289-310, Edward Elgar Publishing.
    7. Christensen, Bent Jesper & Posch, Olaf & van der Wel, Michel, 2016. "Estimating dynamic equilibrium models using mixed frequency macro and financial data," Journal of Econometrics, Elsevier, vol. 194(1), pages 116-137.
    8. Vicky Fasen‐Hartmann & Sebastian Kimmig, 2020. "Robust estimation of stationary continuous‐time arma models via indirect inference," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(5), pages 620-651, September.
    9. Mariusz Maziarz, 2015. "A review of the Granger-causality fallacy," The Journal of Philosophical Economics, Bucharest Academy of Economic Studies, The Journal of Philosophical Economics, vol. 8(2), May.

  53. Harvey, Andrew C & Fernandes, C, 1989. "Time Series Models for Count or Qualitative Observations," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(4), pages 407-417, October.

    Cited by:

    1. Durbin, J. & Koopman, S.J.M., 1998. "Time Series Analysis of Non-Gaussian Observations Based on State Space Models from Both Classical and Bayesian Perspectives," Other publications TiSEM 6338af09-6f2c-46d0-985b-d, Tilburg University, School of Economics and Management.
    2. Harvey, A., 2008. "Dynamic distributions and changing copulas," Cambridge Working Papers in Economics 0839, Faculty of Economics, University of Cambridge.
    3. Shang, Zuofeng, 2012. "On latent process models in multi-dimensional space," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1259-1266.
    4. Boris Aleksandrov & Christian H. Weiß, 2020. "Testing the dispersion structure of count time series using Pearson residuals," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(3), pages 325-361, September.
    5. Denuit, Michel & Lu, Yang, 2020. "Wishart-Gamma mixtures for multiperil experience ratemaking, frequency-severity experience rating and micro-loss reserving," LIDAM Discussion Papers ISBA 2020016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Yang Lu, 2020. "A simple parameter‐driven binary time series model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 187-199, March.
    7. Nobuhiko Terui & Masataka Ban & Toshihiko Maki, 2010. "Finding market structure by sales count dynamics—Multivariate structural time series models with hierarchical structure for count data—," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(1), pages 91-107, February.
    8. Robert Jung & A. Tremayne, 2011. "Useful models for time series of counts or simply wrong ones?," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(1), pages 59-91, March.
    9. Marcelo Bourguignon & Christian H. Weiß, 2017. "An INAR(1) process for modeling count time series with equidispersion, underdispersion and overdispersion," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(4), pages 847-868, December.
    10. Weiß Christian & Scherer Lukas & Aleksandrov Boris & Feld Martin, 2020. "Checking Model Adequacy for Count Time Series by Using Pearson Residuals," Journal of Time Series Econometrics, De Gruyter, vol. 12(1), pages 1-15, January.
    11. Vujić Sunčica & Koopman Siem Jan & Commandeur J.F., 2012. "Economic Trends and Cycles in Crime: A Study for England and Wales," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(6), pages 652-677, December.
    12. Shirozhan, M. & Bakouch, Hassan S. & Mohammadpour, M., 2023. "A flexible INAR(1) time series model with dependent zero-inflated count series and medical contagious cases," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 206(C), pages 216-230.
    13. Sean P. O'brien, 1996. "Foreign Policy Crises and the Resort to Terrorism," Journal of Conflict Resolution, Peace Science Society (International), vol. 40(2), pages 320-335, June.
    14. Kuk, Anthony Y. C., 1999. "The use of approximating models in Monte Carlo maximum likelihood estimation," Statistics & Probability Letters, Elsevier, vol. 45(4), pages 325-333, December.
    15. Godolphin, E.J. & Triantafyllopoulos, Kostas, 2006. "Decomposition of time series models in state-space form," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2232-2246, May.
    16. Ruben Loaiza-Maya & Michael Stanley Smith, 2017. "Variational Bayes Estimation of Discrete-Margined Copula Models with Application to Time Series," Papers 1712.09150, arXiv.org, revised Jul 2018.
    17. Ki Hong Kim & Young Jae Han & Sugil Lee & Sung Won Cho & Chulung Lee, 2019. "Text Mining for Patent Analysis to Forecast Emerging Technologies in Wireless Power Transfer," Sustainability, MDPI, vol. 11(22), pages 1-24, November.
    18. Fokianos, Konstantinos & Fried, Roland & Kharin, Yuriy & Voloshko, Valeriy, 2022. "Statistical analysis of multivariate discrete-valued time series," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    19. Jung, Robert C. & Kukuk, Martin & Liesenfeld, Roman, 2006. "Time series of count data: modeling, estimation and diagnostics," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2350-2364, December.
    20. J. Keith Ord, 2008. "Monitoring Processes with Changing Variances," Working Papers 2008-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    21. Abdallah, Anas & Boucher, Jean-Philippe & Cossette, Hélène, 2016. "Sarmanov family of multivariate distributions for bivariate dynamic claim counts model," Insurance: Mathematics and Economics, Elsevier, vol. 68(C), pages 120-133.
    22. Wagner Barreto-Souza, 2019. "Mixed Poisson INAR(1) processes," Statistical Papers, Springer, vol. 60(6), pages 2119-2139, December.
    23. Brannas, Kurt, 1995. "Prediction and control for a time-series count data model," International Journal of Forecasting, Elsevier, vol. 11(2), pages 263-270, June.
    24. Thiago R. Santos & Glaura C. Franco & Dani Gamerman, 2010. "Comparison of Classical and Bayesian Approaches for Intervention Analysis," International Statistical Review, International Statistical Institute, vol. 78(2), pages 218-239, August.
    25. Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "Forecasting the intermittent demand for slow-moving inventories: A modelling approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 485-496.
    26. Dani Gamerman & Thiago Rezende Santos & Glaura C. Franco, 2013. "A Non-Gaussian Family Of State-Space Models With Exact Marginal Likelihood," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(6), pages 625-645, November.
    27. Richard A. Davis & Thomas C. M. Lee & Gabriel A. Rodriguez‐Yam, 2008. "Break Detection for a Class of Nonlinear Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(5), pages 834-867, September.
    28. Yang Lu, 2018. "Dynamic Frailty Count Process in Insurance: A Unified Framework for Estimation, Pricing, and Forecasting," Post-Print halshs-02418950, HAL.
    29. Axel Groß-Klußmann & Nikolaus Hautsch, 2011. "Predicting Bid-Ask Spreads Using Long Memory Autoregressive Conditional Poisson Models," SFB 649 Discussion Papers SFB649DP2011-044, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    30. Youn Ahn, Jae & Jeong, Himchan & Lu, Yang, 2021. "On the ordering of credibility factors," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 626-638.
    31. Higuchi, Tomoyuki, 1999. "Applications of quasi-periodic oscillation models to seasonal small count time series," Computational Statistics & Data Analysis, Elsevier, vol. 30(3), pages 281-301, May.
    32. AKINYEMI, Emmanuel K & OGUNLEYE, Abiodun O & GUNSOLA, Obaseye A & Olaoye, Hakeem O, 2021. "Modelling Theft Criminal Offence in Kwara State Using ARIMA," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 8(4), pages 177-182, April.
    33. Heinen, Andreas, 2003. "Modelling Time Series Count Data: An Autoregressive Conditional Poisson Model," MPRA Paper 8113, University Library of Munich, Germany.
    34. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    35. Vujić, Sunčica & Commandeur, Jacques J.F. & Koopman, Siem Jan, 2016. "Intervention time series analysis of crime rates: The case of sentence reform in Virginia," Economic Modelling, Elsevier, vol. 57(C), pages 311-323.
    36. Ralph D. Snyder & Gael M. Martin & Phillip Gould & Paul D. Feigin, 2007. "An Assessment of Alternative State Space Models for Count Time Series," Monash Econometrics and Business Statistics Working Papers 4/07, Monash University, Department of Econometrics and Business Statistics.
    37. Eunsuk Chun & Sungchan Jun & Chulung Lee, 2021. "Identification of Promising Smart Farm Technologies and Development of Technology Roadmap Using Patent Map Analysis," Sustainability, MDPI, vol. 13(19), pages 1-22, September.
    38. Tevfik Aktekin & Nicholas G. Polson & Refik Soyer, 2020. "A family of multivariate non‐gaussian time series models," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(5), pages 691-721, September.
    39. J. K. Lindsey, 2001. "A family of repeated measurements models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 10(1), pages 3-9, January.
    40. Kostas Triantafyllopoulos, 2009. "Inference of Dynamic Generalized Linear Models: On‐Line Computation and Appraisal," International Statistical Review, International Statistical Institute, vol. 77(3), pages 430-450, December.
    41. de Pinho, Frank M. & Franco, Glaura C. & Silva, Ralph S., 2016. "Modeling volatility using state space models with heavy tailed distributions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 119(C), pages 108-127.
    42. Wu, Rongning, 2012. "On variance estimation in a negative binomial time series regression model," Journal of Multivariate Analysis, Elsevier, vol. 112(C), pages 145-155.
    43. Nobuhiko Terui & Masataka Ban, 2013. "Multivariate Time Series Model with Hierarchical Structure for Over-dispersed Discrete Outcomes," TMARG Discussion Papers 113, Graduate School of Economics and Management, Tohoku University, revised Aug 2013.
    44. Yelland, Phillip M., 2009. "Bayesian forecasting for low-count time series using state-space models: An empirical evaluation for inventory management," International Journal of Production Economics, Elsevier, vol. 118(1), pages 95-103, March.
    45. Suncica Vujic & Jacques Commandeur & Siem Jan Koopman, 2012. "Structural Intervention Time Series Analysis of Crime Rates: The Impact of Sentence Reform in Virginia," Tinbergen Institute Discussion Papers 12-007/4, Tinbergen Institute.
    46. Ralph Snyder & Adrian Beaumont & J. Keith Ord, 2012. "Intermittent demand forecasting for inventory control: A multi-series approach," Monash Econometrics and Business Statistics Working Papers 15/12, Monash University, Department of Econometrics and Business Statistics.
    47. Han, Yang & Liu, Zehao & Ma, Jun, 2020. "Growth cycles and business cycles of the Chinese economy through the lens of the unobserved components model," China Economic Review, Elsevier, vol. 63(C).
    48. Harvey, Andrew, 2010. "Tracking a changing copula," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 485-500, June.
    49. Marzo, Massimiliano & Zagaglia, Paolo, 2014. "Asymmetric information and term lending in the Euro money market: Evidence from the beginning of the turmoil," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(4), pages 487-499.
    50. McCausland, William J., 2012. "The HESSIAN method: Highly efficient simulation smoothing, in a nutshell," Journal of Econometrics, Elsevier, vol. 168(2), pages 189-206.
    51. Ralph D. Snyder & Adrian Beaumont, 2007. "A Comparison of Methods for Forecasting Demand for Slow Moving Car Parts," Monash Econometrics and Business Statistics Working Papers 15/07, Monash University, Department of Econometrics and Business Statistics.
    52. Brajendra C. Sutradhar, 2008. "On forecasting counts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 109-129.
    53. HEINEN, Andreas & RENGIFO, Erick, 2003. "Multivariate modelling of time series count data: an autoregressive conditional Poisson model," LIDAM Discussion Papers CORE 2003025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  54. Harvey, Andrew C & Fernandes, C, 1989. "Time Series Models for Count or Qualitative Observations: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(4), pages 422-422, October.

    Cited by:

    1. Durbin, J. & Koopman, S.J.M., 1998. "Time Series Analysis of Non-Gaussian Observations Based on State Space Models from Both Classical and Bayesian Perspectives," Other publications TiSEM 6338af09-6f2c-46d0-985b-d, Tilburg University, School of Economics and Management.
    2. Harvey, A., 2008. "Dynamic distributions and changing copulas," Cambridge Working Papers in Economics 0839, Faculty of Economics, University of Cambridge.
    3. Shang, Zuofeng, 2012. "On latent process models in multi-dimensional space," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1259-1266.
    4. Boris Aleksandrov & Christian H. Weiß, 2020. "Testing the dispersion structure of count time series using Pearson residuals," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(3), pages 325-361, September.
    5. Denuit, Michel & Lu, Yang, 2020. "Wishart-Gamma mixtures for multiperil experience ratemaking, frequency-severity experience rating and micro-loss reserving," LIDAM Discussion Papers ISBA 2020016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Yang Lu, 2020. "A simple parameter‐driven binary time series model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 187-199, March.
    7. Nobuhiko Terui & Masataka Ban & Toshihiko Maki, 2010. "Finding market structure by sales count dynamics—Multivariate structural time series models with hierarchical structure for count data—," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(1), pages 91-107, February.
    8. Robert Jung & A. Tremayne, 2011. "Useful models for time series of counts or simply wrong ones?," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(1), pages 59-91, March.
    9. Marcelo Bourguignon & Christian H. Weiß, 2017. "An INAR(1) process for modeling count time series with equidispersion, underdispersion and overdispersion," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(4), pages 847-868, December.
    10. Weiß Christian & Scherer Lukas & Aleksandrov Boris & Feld Martin, 2020. "Checking Model Adequacy for Count Time Series by Using Pearson Residuals," Journal of Time Series Econometrics, De Gruyter, vol. 12(1), pages 1-15, January.
    11. Vujić Sunčica & Koopman Siem Jan & Commandeur J.F., 2012. "Economic Trends and Cycles in Crime: A Study for England and Wales," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(6), pages 652-677, December.
    12. Shirozhan, M. & Bakouch, Hassan S. & Mohammadpour, M., 2023. "A flexible INAR(1) time series model with dependent zero-inflated count series and medical contagious cases," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 206(C), pages 216-230.
    13. Sean P. O'brien, 1996. "Foreign Policy Crises and the Resort to Terrorism," Journal of Conflict Resolution, Peace Science Society (International), vol. 40(2), pages 320-335, June.
    14. Kuk, Anthony Y. C., 1999. "The use of approximating models in Monte Carlo maximum likelihood estimation," Statistics & Probability Letters, Elsevier, vol. 45(4), pages 325-333, December.
    15. Godolphin, E.J. & Triantafyllopoulos, Kostas, 2006. "Decomposition of time series models in state-space form," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2232-2246, May.
    16. Ruben Loaiza-Maya & Michael Stanley Smith, 2017. "Variational Bayes Estimation of Discrete-Margined Copula Models with Application to Time Series," Papers 1712.09150, arXiv.org, revised Jul 2018.
    17. Ki Hong Kim & Young Jae Han & Sugil Lee & Sung Won Cho & Chulung Lee, 2019. "Text Mining for Patent Analysis to Forecast Emerging Technologies in Wireless Power Transfer," Sustainability, MDPI, vol. 11(22), pages 1-24, November.
    18. Fokianos, Konstantinos & Fried, Roland & Kharin, Yuriy & Voloshko, Valeriy, 2022. "Statistical analysis of multivariate discrete-valued time series," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    19. Jung, Robert C. & Kukuk, Martin & Liesenfeld, Roman, 2006. "Time series of count data: modeling, estimation and diagnostics," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2350-2364, December.
    20. J. Keith Ord, 2008. "Monitoring Processes with Changing Variances," Working Papers 2008-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    21. Abdallah, Anas & Boucher, Jean-Philippe & Cossette, Hélène, 2016. "Sarmanov family of multivariate distributions for bivariate dynamic claim counts model," Insurance: Mathematics and Economics, Elsevier, vol. 68(C), pages 120-133.
    22. Wagner Barreto-Souza, 2019. "Mixed Poisson INAR(1) processes," Statistical Papers, Springer, vol. 60(6), pages 2119-2139, December.
    23. Brannas, Kurt, 1995. "Prediction and control for a time-series count data model," International Journal of Forecasting, Elsevier, vol. 11(2), pages 263-270, June.
    24. Thiago R. Santos & Glaura C. Franco & Dani Gamerman, 2010. "Comparison of Classical and Bayesian Approaches for Intervention Analysis," International Statistical Review, International Statistical Institute, vol. 78(2), pages 218-239, August.
    25. Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "Forecasting the intermittent demand for slow-moving inventories: A modelling approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 485-496.
    26. Dani Gamerman & Thiago Rezende Santos & Glaura C. Franco, 2013. "A Non-Gaussian Family Of State-Space Models With Exact Marginal Likelihood," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(6), pages 625-645, November.
    27. Richard A. Davis & Thomas C. M. Lee & Gabriel A. Rodriguez‐Yam, 2008. "Break Detection for a Class of Nonlinear Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(5), pages 834-867, September.
    28. Yang Lu, 2018. "Dynamic Frailty Count Process in Insurance: A Unified Framework for Estimation, Pricing, and Forecasting," Post-Print halshs-02418950, HAL.
    29. Axel Groß-Klußmann & Nikolaus Hautsch, 2011. "Predicting Bid-Ask Spreads Using Long Memory Autoregressive Conditional Poisson Models," SFB 649 Discussion Papers SFB649DP2011-044, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    30. Youn Ahn, Jae & Jeong, Himchan & Lu, Yang, 2021. "On the ordering of credibility factors," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 626-638.
    31. Higuchi, Tomoyuki, 1999. "Applications of quasi-periodic oscillation models to seasonal small count time series," Computational Statistics & Data Analysis, Elsevier, vol. 30(3), pages 281-301, May.
    32. AKINYEMI, Emmanuel K & OGUNLEYE, Abiodun O & GUNSOLA, Obaseye A & Olaoye, Hakeem O, 2021. "Modelling Theft Criminal Offence in Kwara State Using ARIMA," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 8(4), pages 177-182, April.
    33. Heinen, Andreas, 2003. "Modelling Time Series Count Data: An Autoregressive Conditional Poisson Model," MPRA Paper 8113, University Library of Munich, Germany.
    34. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    35. Vujić, Sunčica & Commandeur, Jacques J.F. & Koopman, Siem Jan, 2016. "Intervention time series analysis of crime rates: The case of sentence reform in Virginia," Economic Modelling, Elsevier, vol. 57(C), pages 311-323.
    36. Eunsuk Chun & Sungchan Jun & Chulung Lee, 2021. "Identification of Promising Smart Farm Technologies and Development of Technology Roadmap Using Patent Map Analysis," Sustainability, MDPI, vol. 13(19), pages 1-22, September.
    37. Tevfik Aktekin & Nicholas G. Polson & Refik Soyer, 2020. "A family of multivariate non‐gaussian time series models," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(5), pages 691-721, September.
    38. J. K. Lindsey, 2001. "A family of repeated measurements models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 10(1), pages 3-9, January.
    39. Kostas Triantafyllopoulos, 2009. "Inference of Dynamic Generalized Linear Models: On‐Line Computation and Appraisal," International Statistical Review, International Statistical Institute, vol. 77(3), pages 430-450, December.
    40. de Pinho, Frank M. & Franco, Glaura C. & Silva, Ralph S., 2016. "Modeling volatility using state space models with heavy tailed distributions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 119(C), pages 108-127.
    41. Wu, Rongning, 2012. "On variance estimation in a negative binomial time series regression model," Journal of Multivariate Analysis, Elsevier, vol. 112(C), pages 145-155.
    42. Nobuhiko Terui & Masataka Ban, 2013. "Multivariate Time Series Model with Hierarchical Structure for Over-dispersed Discrete Outcomes," TMARG Discussion Papers 113, Graduate School of Economics and Management, Tohoku University, revised Aug 2013.
    43. Yelland, Phillip M., 2009. "Bayesian forecasting for low-count time series using state-space models: An empirical evaluation for inventory management," International Journal of Production Economics, Elsevier, vol. 118(1), pages 95-103, March.
    44. Suncica Vujic & Jacques Commandeur & Siem Jan Koopman, 2012. "Structural Intervention Time Series Analysis of Crime Rates: The Impact of Sentence Reform in Virginia," Tinbergen Institute Discussion Papers 12-007/4, Tinbergen Institute.
    45. Ralph Snyder & Adrian Beaumont & J. Keith Ord, 2012. "Intermittent demand forecasting for inventory control: A multi-series approach," Monash Econometrics and Business Statistics Working Papers 15/12, Monash University, Department of Econometrics and Business Statistics.
    46. Han, Yang & Liu, Zehao & Ma, Jun, 2020. "Growth cycles and business cycles of the Chinese economy through the lens of the unobserved components model," China Economic Review, Elsevier, vol. 63(C).
    47. Harvey, Andrew, 2010. "Tracking a changing copula," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 485-500, June.
    48. Marzo, Massimiliano & Zagaglia, Paolo, 2014. "Asymmetric information and term lending in the Euro money market: Evidence from the beginning of the turmoil," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(4), pages 487-499.
    49. McCausland, William J., 2012. "The HESSIAN method: Highly efficient simulation smoothing, in a nutshell," Journal of Econometrics, Elsevier, vol. 168(2), pages 189-206.
    50. Ralph D. Snyder & Adrian Beaumont, 2007. "A Comparison of Methods for Forecasting Demand for Slow Moving Car Parts," Monash Econometrics and Business Statistics Working Papers 15/07, Monash University, Department of Econometrics and Business Statistics.
    51. Brajendra C. Sutradhar, 2008. "On forecasting counts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 109-129.
    52. HEINEN, Andreas & RENGIFO, Erick, 2003. "Multivariate modelling of time series count data: an autoregressive conditional Poisson model," LIDAM Discussion Papers CORE 2003025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  55. A. C. Harvey & P. M. Robinson, 1988. "Efficient Estimation Of Nonstationary Time Series Regression," Journal of Time Series Analysis, Wiley Blackwell, vol. 9(3), pages 201-214, May.

    Cited by:

    1. Xu, Ke-Li & Phillips, Peter C.B., 2008. "Adaptive estimation of autoregressive models with time-varying variances," Journal of Econometrics, Elsevier, vol. 142(1), pages 265-280, January.
    2. Zhang, Erhua & Wu, Jilin, 2020. "Adaptive estimation of AR∞ models with time-varying variances," Economics Letters, Elsevier, vol. 197(C).
    3. Yoshihiro Usami & Mituaki Huzii, 1995. "Estimation Of Coefficients Of Time Series Regression With A Nonstationary Error Process," Journal of Time Series Analysis, Wiley Blackwell, vol. 16(1), pages 105-118, January.
    4. Dalla, Violetta & Giraitis, Liudas & Robinson, Peter M., 2020. "Asymptotic theory for time series with changing mean and variance," Journal of Econometrics, Elsevier, vol. 219(2), pages 281-313.

  56. Harvey, A. C. & Stock, James H., 1988. "Continuous time autoregressive models with common stochastic trends," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 365-384.

    Cited by:

    1. Antolin-Diaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2017. "Tracking the slowdown in long-run GDP growth," LSE Research Online Documents on Economics 81869, London School of Economics and Political Science, LSE Library.
    2. D. Stephen G. Pollock, 2020. "Linear Stochastic Models in Discrete and Continuous Time," Econometrics, MDPI, vol. 8(3), pages 1-22, September.
    3. Petrella, Ivan & Drechsel, Thomas & Antolin-Diaz, Juan, 2014. "Following the Trend: Tracking GDP when Long-Run Growth is Uncertain," CEPR Discussion Papers 10272, C.E.P.R. Discussion Papers.
    4. Lettau, Martin & Ludvigson, Sydney, 2001. "Understanding Trend and Cycle in Asset Values: Bulls, Bears and the Wealth Effect on Consumption," CEPR Discussion Papers 3104, C.E.P.R. Discussion Papers.
    5. Martin B. Schmidt, 2004. "Exogeneity within the M2 Demand Function: Evidence from a Large Macroeconomic System," Economic Inquiry, Western Economic Association International, vol. 42(4), pages 634-646, October.
    6. Michael Thornton & Marcus Chambers, 2016. "Continuous Time ARMA Processes: Discrete Time Representation and Likelihood Evaluation," Discussion Papers 16/10, Department of Economics, University of York.
    7. Vicky Fasen-Hartmann & Celeste Mayer, 2022. "Whittle estimation for continuous-time stationary state space models with finite second moments," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(2), pages 233-270, April.
    8. Joanne S. Ercolani, 2007. "Cyclical Trends in Continuous Time Models," Discussion Papers 07-13, Department of Economics, University of Birmingham.
    9. Schmidt, Martin B., 2001. "The long and short of money and prices: a market equilibrium approach," Journal of Economics and Business, Elsevier, vol. 53(6), pages 563-583.
    10. Francesco Giuli & Massimiliano Tancioni, 2012. "Prince-setting, monetary policy and the contractionary effects of productivity improvements," Departmental Working Papers of Economics - University 'Roma Tre' 0161, Department of Economics - University Roma Tre.
    11. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    12. Michael A. Thornton & Marcus J. Chambers, 2013. "Temporal aggregation in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 13, pages 289-310, Edward Elgar Publishing.
    13. Martin Schmidt, 2003. "Money and prices: evidence from the G7 countries," Applied Economics, Taylor & Francis Journals, vol. 35(17), pages 1799-1809.
    14. Martin Lettau & Sydney C. Ludvigson & Charles Steindel, 2002. "Monetary policy transmission through the consumption-wealth channel," Economic Policy Review, Federal Reserve Bank of New York, vol. 8(May), pages 117-133.
    15. Milena Hoyos, 2020. "Mixed First‐ and Second‐Order Cointegrated Continuous Time Models with Mixed Stock and Flow Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(2), pages 249-267, March.
    16. Joann Jasiak, 2003. "First‐Order Autoregressive Processes with Heterogeneous Persistence," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(3), pages 283-309, May.
    17. Thornton, Michael A. & Chambers, Marcus J., 2016. "The exact discretisation of CARMA models with applications in finance," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 739-761.
    18. Martin B. Schmidt, 2000. "The Dynamic Behavior of Wages and Prices: Cointegration Tests within a Large Macroeconomic System," Southern Economic Journal, John Wiley & Sons, vol. 67(1), pages 123-138, July.
    19. Martin Schmidt, 2003. "The relative adjustment of wages and prices: direct tests within a multiple-equation system," Applied Economics, Taylor & Francis Journals, vol. 35(8), pages 985-997.
    20. Chambers, Marcus J., 1999. "Discrete time representation of stationary and non-stationary continuous time systems," Journal of Economic Dynamics and Control, Elsevier, vol. 23(4), pages 619-639, February.
    21. Timothy Cogley, "undated". "How Fast Can the New Economy Grow? A Bayesian Analysis of the Evolution of Trend Growth," Working Papers 2133301, Department of Economics, W. P. Carey School of Business, Arizona State University.
    22. Dao, Chi-Mai & Wolters, Jürgen, 2008. "Common stochastic volatility trends in international stock returns," International Review of Financial Analysis, Elsevier, vol. 17(3), pages 431-445, June.

  57. F. Javier Fernandez Macho & Andrew C. Harvey & James H. Stock, 1987. "Forecasting and Interpolation Using Vector Autoregressions with Common Trends," Annals of Economics and Statistics, GENES, issue 6-7, pages 279-287.

    Cited by:

    1. Stefan Gerlach & Matthew S. Yiu, 2004. "A Dynamic Factor Model for Current-Quarter Estimates of Economic Activity in Hong Kong," Working Papers 162004, Hong Kong Institute for Monetary Research.
    2. Peter Fuleky & Carl Bonham, 2010. "Forecasting Based on Common Trends in Mixed Frequency Samples," Working Papers 2010-17R1, University of Hawaii Economic Research Organization, University of Hawaii at Manoa, revised Jul 2013.
    3. Francisco J. Goerlich-Gisbert, 1999. "Shocks agregados versus shocks sectoriales. Un análisis factorial dinámico," Investigaciones Economicas, Fundación SEPI, vol. 23(1), pages 27-53, January.
    4. Peter Fuleky & Carl, 2013. "Forecasting with Mixed Frequency Samples: The Case of Common Trends," Working Papers 2013-5, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    5. Fabio H. Nieto, 2007. "Ex post and ex ante prediction of unobserved multivariate time series: a structural-model based approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(1), pages 53-76.
    6. Juan Carlos Carlo Santos, 2019. "Pronósticos del PIB mediante modelos de factores dinámicos," Revista de Análisis del BCB, Banco Central de Bolivia, vol. 30(1), pages 125-174, January -.
    7. Ko, Byoung Wook, 2010. "An application of dynamic factor model to dry Bulk Market - focusing on the analysis of synchronicity and idiosyncrasy in the sub-markets with different ship - size," MPRA Paper 32572, University Library of Munich, Germany.
    8. James H. Stock & Mark W. Watson, 1988. "A Probability Model of The Coincident Economic Indicators," NBER Working Papers 2772, National Bureau of Economic Research, Inc.

  58. Harvey, A. C., 1986. "The effects of seat belt legislation on British road casualities: A case study in structural modelling : A.C. Harvey and J. Durbing, Journal of the Royal Statistical Society, Series A 149 (1986) (in p," International Journal of Forecasting, Elsevier, vol. 2(4), pages 496-497.

    Cited by:

    1. Mark Hon & Soo-Keong Yong, 2004. "The price of owning a car: an analysis of auction quota premium in Singapore," Applied Economics, Taylor & Francis Journals, vol. 36(7), pages 739-751.
    2. P. A. Scuffham, 2003. "Economic factors and traffic crashes in New Zealand," Applied Economics, Taylor & Francis Journals, vol. 35(2), pages 179-188.
    3. Atkinson, A. C. & Koopman, S. J. & Shephard, N., 1997. "Detecting shocks: Outliers and breaks in time series," Journal of Econometrics, Elsevier, vol. 80(2), pages 387-422, October.
    4. Naci H. Mocan & Kudret Topyan, 1993. "Illicit Drug Use and Health: Analysis and Projections of New York City Birth Outcomes Using a Kalman Filter Model," NBER Working Papers 4359, National Bureau of Economic Research, Inc.
    5. Manuel Salvador & Pilar Gargallo, 2003. "Automatic selective intervention in dynamic linear models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(10), pages 1161-1184.
    6. Yuehjen Shao & Yue-Fa Lin & Soe-Tsyr Yuan, 1999. "Integrated application of time series multiple-interventions analysis and knowledge-based reasoning," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(6), pages 755-766.
    7. OUERFELLI, Chokri, 1998. "La demande touristique européenne en Tunisie," LATEC - Document de travail - Economie (1991-2003) 1998-14, LATEC, Laboratoire d'Analyse et des Techniques EConomiques, CNRS UMR 5118, Université de Bourgogne.
    8. Victor Guerrero, 2005. "Restricted estimation of an adjusted time series: application to Mexico's industrial production index," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(2), pages 157-177.
    9. Ole E. Barndorff-Nielsen & Bent Nielsen & Neil Shephard & Carla Ysusi, 2002. "Measuring and forecasting financial variability using realised variance with and without a model," Economics Papers 2002-W21, Economics Group, Nuffield College, University of Oxford.

  59. A. C. Harvey, 1986. "Analysis and Generalisation of a Multivariate Exponential Smoothing Model," Management Science, INFORMS, vol. 32(3), pages 374-380, March.

    Cited by:

    1. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
    2. Bekiros, Stelios, 2014. "Forecasting with a state space time-varying parameter VAR model: Evidence from the Euro area," Economic Modelling, Elsevier, vol. 38(C), pages 619-626.
    3. Stelios D. Bekiros & Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2016. "Dealing with Financial Instability under a DSGE modeling approach with Banking Intermediation: a predictability analysis versus TVP-VARs," Open Access publications 10197/7323, School of Economics, University College Dublin.
    4. Stelios Bekiros & Alessia Paccagnini, 2013. "Policy-oriented macroeconomic forecasting with hybrid DGSE and time-varying parameter VAR models," Working Papers 236, University of Milano-Bicocca, Department of Economics, revised Feb 2013.
    5. Corberán-Vallet, Ana & Bermúdez, José D. & Vercher, Enriqueta, 2011. "Forecasting correlated time series with exponential smoothing models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 252-265.
    6. Mirko Kremer & Enno Siemsen & Douglas J. Thomas, 2016. "The Sum and Its Parts: Judgmental Hierarchical Forecasting," Management Science, INFORMS, vol. 62(9), pages 2745-2764, September.
    7. Bermúdez, José D. & Corberán-Vallet, Ana & Vercher, Enriqueta, 2009. "Multivariate exponential smoothing: A Bayesian forecast approach based on simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(5), pages 1761-1769.
    8. Stelios Bekiros & Alessia Paccagnini, 2013. "On the predictability of time-varying VAR and DSGE models," Empirical Economics, Springer, vol. 45(1), pages 635-664, August.
    9. Corberán-Vallet, Ana & Bermúdez, José D. & Vercher, Enriqueta, 2011. "Forecasting correlated time series with exponential smoothing models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 252-265, April.
    10. Sbrana, Giacomo & Silvestrini, Andrea, 2020. "Forecasting with the damped trend model using the structural approach," International Journal of Production Economics, Elsevier, vol. 226(C).
    11. George Athanasopoulos & Ashton de Silva, 2010. "Multivariate exponential smoothing for forecasting tourist arrivals to Australia and New Zealand," Monash Econometrics and Business Statistics Working Papers 11/09, Monash University, Department of Econometrics and Business Statistics.
    12. K. Triantafyllopoulos, 2007. "Covariance estimation for multivariate conditionally Gaussian dynamic linear models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(8), pages 551-569.
    13. Sbrana, Giacomo & Silvestrini, Andrea, 2022. "Random coefficient state-space model: Estimation and performance in M3–M4 competitions," International Journal of Forecasting, Elsevier, vol. 38(1), pages 352-366.
    14. Dimitrios D. Thomakos & Konstantinos Nikolopoulos, 2013. "Forecasting multivariate time series with the Theta Method," Working Papers 13004, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
    15. González, Fernando & Launonen, Simo, 2005. "Towards European monetary integration: the evolution of currency risk premium as a measure for monetary convergence prior to the implementation of currency unions," Working Paper Series 569, European Central Bank.
    16. Triantafyllopoulos, Kostas, 2006. "Multivariate discount weighted regression and local level models," Computational Statistics & Data Analysis, Elsevier, vol. 50(12), pages 3702-3720, August.
    17. Sbrana, Giacomo & Silvestrini, Andrea, 2023. "The RWDAR model: A novel state-space approach to forecasting," International Journal of Forecasting, Elsevier, vol. 39(2), pages 922-937.
    18. K. Triantafyllopoulos, 2008. "Multivariate stochastic volatility with Bayesian dynamic linear models," Papers 0802.0214, arXiv.org.
    19. Croux, Christophe & Gelper, Sarah & Mahieu, Koen, 2010. "Robust exponential smoothing of multivariate time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 2999-3006, December.
    20. Sbrana, Giacomo & Silvestrini, Andrea, 2019. "Random switching exponential smoothing: A new estimation approach," International Journal of Production Economics, Elsevier, vol. 211(C), pages 211-220.

  60. Harvey, A C, et al, 1986. "Stochastic Trends in Dynamic Regression Models: An Application to the Employment-Output Equations," Economic Journal, Royal Economic Society, vol. 96(384), pages 975-985, December.

    Cited by:

    1. Sturla Furunes Kvamsdal, 2019. "Indexing of Technical Change in Aggregated Data," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 901-920, March.
    2. Tehreem Fatima & Enjun Xia & Muhammad Ahad, 2019. "Oil demand forecasting for China: a fresh evidence from structural time series analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(3), pages 1205-1224, June.
    3. Yongkyun Chung, 1997. "Labor Hoarding and SRIRL Pardox: Some Evidences from United Kingdom and United States," International Area Studies Review, Center for International Area Studies, Hankuk University of Foreign Studies, vol. 1(1), pages 175-189, December.
    4. Richard Dickens & Stephen Machin & Alan Manning & David Metcalf & Jonathan Wadsworth & S Woodland, 1994. "The Effect of Minimum Wages on UK Agriculture," CEP Discussion Papers dp0204, Centre for Economic Performance, LSE.
    5. G. Everaert, 2007. "Estimating Long-Run Relationships between Observed Integrated Variables by Unobserved Component Methods," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/452, Ghent University, Faculty of Economics and Business Administration.
    6. SHIRANI-FAKHR, Zohreh & KHOSHAKHLAGH, Rahman & SHARIFI, Alimorad, 2015. "Estimating Demand Function For Electricity In Industrial Sector Of Iran Using Structural Time Series Model (Stsm)," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 15(1), pages 143-160.
    7. Zafer Dilaver & Lester C Hunt, 2010. "Modelling and Forecasting Turkish Residential Electricity Demand," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 131, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    8. Sa'ad, Suleiman, 2010. "Improved technical efficiency and exogenous factors in transportation demand for energy: An application of structural time series analysis to South Korean data," Energy, Elsevier, vol. 35(7), pages 2745-2751.
    9. Gardberg, Malin, 2020. "Aggregate Consumption and Wealth in the Long Run: The Impact of Financial Liberalization," Working Paper Series 1339, Research Institute of Industrial Economics.
    10. Lester C Hunt & Guy Judge & Yasushi Ninomiya, 2003. "Modelling Underlying Energy Demand Trends," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 105, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    11. Reneéa Koekemoer, 2001. "Variable Parameter Estimation Of Consumer Price Expectations For The South African Economy," South African Journal of Economics, Economic Society of South Africa, vol. 69(1), pages 1-39, March.
    12. Sturla Furunes Kvamsdal, 2016. "Technical Change as a Stochastic Trend in a Fisheries Model," Marine Resource Economics, University of Chicago Press, vol. 31(4), pages 403-419.
    13. Antoni, 2012. "Monetary policy and inflation targeting in a small open economy," Economic Journal of Emerging Markets, Universitas Islam Indonesia, vol. 4(2), pages 187-198, April.
    14. Kapombe, Crispin M. & Colyer, Dale, 1999. "A structural time series analysis of US broiler exports," Agricultural Economics, Blackwell, vol. 21(3), pages 295-307, December.
    15. Zafer Dilaver & Lester C Hunt, 2010. "Industrial Electricity Demand for Turkey: A Structural Time Series Analysis," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 129, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    16. Addison, John T. & Teixeira, Paulino, 1999. "Is Portugal really so arteriosclerotic? Results from a cross-country analysis of labor adjustment," ZEW Discussion Papers 99-30, ZEW - Leibniz Centre for European Economic Research.
    17. Martyn Duffy, 2006. "Tobacco consumption and policy in the United Kingdom," Applied Economics, Taylor & Francis Journals, vol. 38(11), pages 1235-1257.
    18. Wollmer, F.J. & Butter, F.A.G. den & Hassink, W.H.J., 1991. "Technical progress, endogenous growth and labour productivity : a survey," Serie Research Memoranda 0075, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    19. Chen, Xiaoshan & MacDonald, Ronald, 2014. "Measuring the Euro-Dollar Permanent Equilibrium Exchange Rate using the Unobserved Components Model," SIRE Discussion Papers 2015-05, Scottish Institute for Research in Economics (SIRE).
    20. Malin Gardberg & Lorenzo (L.C.G.) Pozzi, 2018. "Consumption and wealth in the long run: an integrated unobserved component approach," Tinbergen Institute Discussion Papers 18-046/VI, Tinbergen Institute, revised 13 Sep 2018.
    21. Stephen Bazen & Velayoudom Marimoutou, 2002. "Looking for a Needle in a Haystack? A Re‐examination of the Time Series Relationship between Teenage Employment and Minimum Wages in the United States," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(supplemen), pages 699-725, December.
    22. Atalla, Tarek N. & Hunt, Lester C., 2016. "Modelling residential electricity demand in the GCC countries," Energy Economics, Elsevier, vol. 59(C), pages 149-158.
    23. Streibel, Mariane & Harvey, Andrew, 1993. "Estimation of simultaneous equation models with stochastic trend components," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 263-287.
    24. Guro Børnes Ringlund & Knut Einar Rosendahl & Terje Skjerpen, 2004. "Does oilrig activity react to oil price changes? An empirical investigation," Discussion Papers 372, Statistics Norway, Research Department.
    25. Jaakko Pehkonen, 1994. "Testing weak exogeneity by multivariate cointegration techniques : the demand for labour in Finnish manufacturing," Finnish Economic Papers, Finnish Economic Association, vol. 7(2), pages 108-119, Autumn.
    26. Addison John T. & Teixeira Paulino, 2001. "Employment Adjustment in a “Sclerotic” Labour Market: Comparing Portugal with Germany, Spain, and the United Kingdom / Beschäftigungsanpassung in einem „sklerotischen“ Arbeitsmarkt: Ein Vergleich von ," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 221(4), pages 353-370, August.
    27. Hunt, Lester C. & Judge, Guy & Ninomiya, Yasushi, 2003. "Underlying trends and seasonality in UK energy demand: a sectoral analysis," Energy Economics, Elsevier, vol. 25(1), pages 93-118, January.
    28. Bajpai, Siddharth & Mohanty, Samarendu, 2008. "Impacts of Exchange Rate Volatility on the U.S. Cotton Exports," 2008 Annual Meeting, February 2-6, 2008, Dallas, Texas 6849, Southern Agricultural Economics Association.
    29. Stephen Bazen & Velayoudom Marimoutou, 2000. "Looking for a Needle in a Haystack? A Structural Time Series Model of the Relationship Between Teenage Employment and Minimum Wages in the United States," Econometric Society World Congress 2000 Contributed Papers 0495, Econometric Society.
    30. Abdul Karim, Zulkefly & Md. Said, Fathin Faezah & Jusoh, Mansor & Md. Thahir, Md. Zyadi, 2009. "Monetary policy and inflation targeting in a small open-economy," MPRA Paper 23949, University Library of Munich, Germany, revised 10 Jan 2010.
    31. Gorter, C. & Hassink, W. & Nijkamp, P., 1996. "On the endogeneity of output in dynamic labour-demand models," Serie Research Memoranda 0019, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    32. Everaert Gerdie, 2011. "Estimation and Inference in Time Series with Omitted I(1) Variables," Journal of Time Series Econometrics, De Gruyter, vol. 2(2), pages 1-28, January.
    33. Chew Lian Chua & G. C. Lim & Sarantis Tsiaplias, 2012. "A latent variable approach to forecasting the unemployment rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 31(3), pages 229-244, April.
    34. Lester C. Hunt & Guy Judge & Yashushi Ninomiya, 2000. "Modelling Technical Progress: An Application of the Stochastic Trend Model to UK Energy Demand," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 99, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    35. Chen, Xiaoshan & MacDonald, Ronald, 2010. "Revisiting the Dollar-Euro Permanent Equilibrium Exchange Rate: Evidence from Multivariate Unobserved Components Models," SIRE Discussion Papers 2010-41, Scottish Institute for Research in Economics (SIRE).
    36. Al-Rabbaie, Arqam & Alwaked, Ahmad & Altarawneh, Yaseen, 2009. "Underlying trends in employment-output equation: the case of Jordan," Perspectives of Innovations, Economics and Business (PIEB), Prague Development Center (PRADEC), vol. 3, pages 1-3, December.
    37. Rodrigo Fuentes & Marco Morales, 2007. "Measuring TFP: A Latent Variable Approach," Working Papers Central Bank of Chile 419, Central Bank of Chile.
    38. Dilaver, Zafer & Hunt, Lester C., 2021. "Modelling U.S. gasoline demand: A structural time series analysis with asymmetric price responses," Energy Policy, Elsevier, vol. 156(C).
    39. Colyer, Dale, 2000. "A Comparison Of Annual, Quarterly And Monthly Turkey Export Models," Conference Papers 19106, West Virginia University, Department of Agricultural Resource Economics.
    40. Chen, Xiaoshan & MacDonald, Ronald, 2015. "Measuring the dollar–euro permanent equilibrium exchange rate using the unobserved components model," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 20-35.

  61. Harvey, A C, 1985. "Trends and Cycles in Macroeconomic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 216-227, June.

    Cited by:

    1. Joshua C.C. Chan & Angelia L. Grant, 2016. "Reconciling output gaps: unobserved components model and Hodrick-Prescott filter," CAMA Working Papers 2016-44, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. Guglielmo Maria Caporale & Juncal Cunado & Luis A. Gil-Alana, 2008. "Modelling Long-Run Trends and Cycles in Financial Time Series Data," CESifo Working Paper Series 2330, CESifo.
    3. Carmen M. Reinhart & Peter Wickham, 1994. "Commodity Prices: Cyclical Weakness or Secular Decline?," IMF Staff Papers, Palgrave Macmillan, vol. 41(2), pages 175-213, June.
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    2. D. Stephen G. Pollock, 2020. "Linear Stochastic Models in Discrete and Continuous Time," Econometrics, MDPI, vol. 8(3), pages 1-22, September.
    3. Ghysels, E. & Jasiak, J., 1994. "Stochastic Volatility and time Deformation: An Application of trading Volume and Leverage Effects," Cahiers de recherche 9403, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    4. Hansen, Lars Peter & Scheinkman, Jose Alexandre, 1995. "Back to the Future: Generating Moment Implications for Continuous-Time Markov Processes," Econometrica, Econometric Society, vol. 63(4), pages 767-804, July.
    5. Andrew W. Lo, "undated". "Maximum Likelihood Estimation of Generalized Ito Processes with Discretely Sampled Data," Rodney L. White Center for Financial Research Working Papers 15-86, Wharton School Rodney L. White Center for Financial Research.
    6. Tucker S. McElroy & Thomas M. Trimbur, 2007. "Continuous time extraction of a nonstationary signal with illustrations in continuous low-pass and band-pass filtering," Finance and Economics Discussion Series 2007-68, Board of Governors of the Federal Reserve System (U.S.).
    7. Comte, F., 1998. "Discrete and continuous time cointegration," Journal of Econometrics, Elsevier, vol. 88(2), pages 207-226, November.
    8. Michael Thornton & Marcus Chambers, 2016. "Continuous Time ARMA Processes: Discrete Time Representation and Likelihood Evaluation," Discussion Papers 16/10, Department of Economics, University of York.
    9. Lars Peter Hansen & Thomas J. Sargent, 1993. "Recursive linear models of dynamic economies," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
    10. Michael A. Thornton & Marcus J. Chambers, 2013. "Continuous-time autoregressive moving average processes in discrete time: representation and embeddability," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(5), pages 552-561, September.
    11. Andrew Filardo & Marco Jacopo Lombardi & Marek Raczko, 2018. "Measuring financial cycle time," BIS Working Papers 755, Bank for International Settlements.
    12. Vicky Fasen-Hartmann & Celeste Mayer, 2022. "Whittle estimation for continuous-time stationary state space models with finite second moments," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(2), pages 233-270, April.
    13. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    14. Hermann Singer, 2003. "Simulated Maximum Likelihood in Nonlinear Continuous-Discrete State Space Models: Importance Sampling by Approximate Smoothing," Computational Statistics, Springer, vol. 18(1), pages 79-106, March.
    15. Michael A. Thornton & Marcus J. Chambers, 2013. "Temporal aggregation in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 13, pages 289-310, Edward Elgar Publishing.
    16. Hermann Singer, 2011. "Continuous-discrete state-space modeling of panel data with nonlinear filter algorithms," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 375-413, December.
    17. Milena Hoyos, 2020. "Mixed First‐ and Second‐Order Cointegrated Continuous Time Models with Mixed Stock and Flow Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(2), pages 249-267, March.
    18. Thornton, Michael A. & Chambers, Marcus J., 2016. "The exact discretisation of CARMA models with applications in finance," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 739-761.
    19. Vicky Fasen‐Hartmann & Sebastian Kimmig, 2020. "Robust estimation of stationary continuous‐time arma models via indirect inference," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(5), pages 620-651, September.
    20. Parra-Alvarez, Juan Carlos & Polattimur, Hamza & Posch, Olaf, 2021. "Risk matters: Breaking certainty equivalence in linear approximations," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
    21. Chambers, Marcus J., 1999. "Discrete time representation of stationary and non-stationary continuous time systems," Journal of Economic Dynamics and Control, Elsevier, vol. 23(4), pages 619-639, February.
    22. Stock, James H., 1987. "Measuring Business Cycle Time," Scholarly Articles 3425950, Harvard University Department of Economics.
    23. Roderick McCrorie, J., 2001. "Interpolating exogenous variables in continuous time dynamic models," Journal of Economic Dynamics and Control, Elsevier, vol. 25(9), pages 1399-1427, September.
    24. J. Roderick McCrorie, 2000. "The Likelihood of a Continuous-time Vector Autoregressive Model," Working Papers 419, Queen Mary University of London, School of Economics and Finance.

  64. Phillips, G. D. A. & Harvey, A. C., 1984. "A note on estimating and testing exogenous variable coefficient estimators in simultaneous equation models," Economics Letters, Elsevier, vol. 15(3-4), pages 301-307.

    Cited by:

    1. Hadri, Kaddour & Phillips, Garry D. A., 1999. "The accuracy of the higher order bias approximation for the 2SLS estimator," Economics Letters, Elsevier, vol. 62(2), pages 167-174, February.
    2. Cheung Ip, Wai & Phillips, Garry D. A., 1998. "The non-monotonicity of the bias and mean squared error of the two stage least squares estimators of exogenous variable coefficients," Economics Letters, Elsevier, vol. 60(3), pages 303-310, September.

  65. Harvey, A C & Todd, P H J, 1983. "Forecasting Economic Time Series with Structural and Box-Jenkins Models: A Case Study: Response," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(4), pages 313-315, October.

    Cited by:

    1. Nelson, Charles R., 1988. "Spurious trend and cycle in the state space decomposition of a time series with a unit root," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 475-488.
    2. Paolo Maranzano & Alessandro Fassò & Matteo Pelagatti & Manfred Mudelsee, 2020. "Statistical Modeling of the Early-Stage Impact of a New Traffic Policy in Milan, Italy," IJERPH, MDPI, vol. 17(3), pages 1-22, February.
    3. Sbrana, Giacomo, 2013. "The exact linkage between the Beveridge–Nelson decomposition and other permanent-transitory decompositions," Economic Modelling, Elsevier, vol. 30(C), pages 311-316.
    4. Franses, P.H. & McAleer, M., 1995. "Testing Nested and Non-Nested Periodically Integrated Autoregressive Models," Other publications TiSEM f6ea7d00-daeb-413b-a279-e, Tilburg University, School of Economics and Management.
    5. Constantinescu, Mihnea & Nguyen, Anh Dinh Minh, 2021. "A century of gaps: Untangling business cycles from secular trends," Economic Modelling, Elsevier, vol. 100(C).
    6. Bengtsson, Thomas & Cavanaugh, Joseph E., 2006. "An improved Akaike information criterion for state-space model selection," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2635-2654, June.
    7. Mihnea Constantinescu & Anh Dinh Minh Nguyen, 2017. "Unemployment or Credit: Who Holds The Potential? Results From a Small-Open Economy," Bank of Lithuania Discussion Paper Series 4, Bank of Lithuania.
    8. Guido Ascari & Paolo Bonomolo & Qazi Haque, 2023. "The Long-Run Phillips Curve is ... a Curve," Working Papers 789, DNB.
    9. Marczak, Martyna & Proietti, Tommaso, 2015. "Outlier Detection in Structural Time Series Models: the Indicator Saturation Approach," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113137, Verein für Socialpolitik / German Economic Association.
    10. Kosei Fukuda, 2010. "Three new empirical perspectives on the Hodrick–Prescott parameter," Empirical Economics, Springer, vol. 39(3), pages 713-731, December.
    11. Huishu Zhang & Jianrong Wei & Jiping Huang, 2014. "Scaling and Predictability in Stock Markets: A Comparative Study," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-5, March.
    12. Shah, Muhammad Ibrahim & Kirikkaleli, Dervis & Adedoyin, Festus Fatai, 2021. "Regime switching effect of COVID-19 pandemic on renewable electricity generation in Denmark," Renewable Energy, Elsevier, vol. 175(C), pages 797-806.
    13. Fanhua Yu & Huibowen Hao & Qingliang Li, 2021. "An Ensemble 3D Convolutional Neural Network for Spatiotemporal Soil Temperature Forecasting," Sustainability, MDPI, vol. 13(16), pages 1-16, August.
    14. Ester Ruiz & Fernando Lorenzo, 1997. "Prediction with univariate time series models: The Iberia case," Documentos de Trabajo (working papers) 0298, Department of Economics - dECON.
    15. Gómez, Víctor & Breitung, Jörg, 1998. "The Beveridge-Nelson decomposition: A different perspective with new results," SFB 373 Discussion Papers 1998,26, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    16. Pollock, D. S. G., 2003. "Recursive estimation in econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 37-75, October.
    17. Saligari, Grant R. & Snyder, Ralph D., 1997. "Trends, lead times and forecasting," International Journal of Forecasting, Elsevier, vol. 13(4), pages 477-488, December.
    18. Park, Gonyung, 1996. "The role of detrending methods in a model of real business cycles," Journal of Macroeconomics, Elsevier, vol. 18(3), pages 479-501.
    19. Marczak, Martyna & Proietti, Tommaso & Grassi, Stefano, 2015. "A data-cleaning augmented Kalman filter for robust estimation of state space models," Hohenheim Discussion Papers in Business, Economics and Social Sciences 13-2015, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    20. Ralf Dewenter & Ulrich Heimeshoff, 2017. "Predicting Advertising Volumes Using Structural Time Series Models: A Case Study," Economics Bulletin, AccessEcon, vol. 37(3), pages 1644-1652.
    21. Thornton, Michael A., 2013. "Removing seasonality under a changing regime: Filtering new car sales," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 4-14.
    22. Stephen Pollock, 2002. "Recursive Estimation in Econometrics," Working Papers 462, Queen Mary University of London, School of Economics and Finance.
    23. Walter Labys, 2005. "Commodity Price Fluctuations: A Century of Analysis," Working Papers Working Paper 2005-01, Regional Research Institute, West Virginia University.
    24. Antonio García Ferrer & Juan del Hoyo Bernat & Peter C. Young & Alfonso Novales Cinca, 1993. "Further evidence on forecasting international GNP growth rates using unobserved components transfer function models," Documentos de Trabajo del ICAE 9312, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    25. Sucharita Ghosh & Donald Lien, 2001. "Forecasting with preliminary data: a comparison of two methods," Applied Economics, Taylor & Francis Journals, vol. 33(6), pages 721-726.
    26. Naci H. Mocan & Kudret Topyan, 1993. "Illicit Drug Use and Health: Analysis and Projections of New York City Birth Outcomes Using a Kalman Filter Model," NBER Working Papers 4359, National Bureau of Economic Research, Inc.
    27. Pablo Marshall, 1998. "Prediccion De Series De Ventas: Un Analisis De Cointegracion Con El Pib," Abante, Escuela de Administracion. Pontificia Universidad Católica de Chile., vol. 1(1), pages 89-109.
    28. Sen Cheong Kon & Lindsay W. Turner, 2005. "Neural Network Forecasting of Tourism Demand," Tourism Economics, , vol. 11(3), pages 301-328, September.
    29. Mr. Sebastian Acevedo Mejia & Lu Han & Miss Marie S Kim & Ms. Nicole Laframboise, 2016. "Flying to Paradise: The Role of Airlift in the Caribbean Tourism Industry," IMF Working Papers 2016/033, International Monetary Fund.
    30. Pollock, D. S. G., 2001. "Methodology for trend estimation," Economic Modelling, Elsevier, vol. 18(1), pages 75-96, January.
    31. Garcia-Ferrer, Antonio & Queralt, Ricardo A., 1998. "Can univariate models forecast turning points in seasonal economic time series?," International Journal of Forecasting, Elsevier, vol. 14(4), pages 433-446, December.
    32. Candy Mei Fung Tang & Brian King & Stephen Pratt, 2017. "Predicting hotel occupancies with public data," Tourism Economics, , vol. 23(5), pages 1096-1113, August.
    33. Quanrui Song & Jianxu Liu & Songsak Sriboonchitta, 2019. "Risk Measurement of Stock Markets in BRICS, G7, and G20: Vine Copulas versus Factor Copulas," Mathematics, MDPI, vol. 7(3), pages 1-16, March.
    34. Johan Verbeeck & Christel Faes & Thomas Neyens & Niel Hens & Geert Verbeke & Patrick Deboosere & Geert Molenberghs, 2023. "A linear mixed model to estimate COVID‐19‐induced excess mortality," Biometrics, The International Biometric Society, vol. 79(1), pages 417-425, March.
    35. Hotta, Luiz K. & Morettin, Pedro A. & Pereira, Pedro L. Valls, 1992. "The Effect of Overlapping Aggregation on Time Series Models: An Application to the Unemployment Rate in Brazil," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 12(2), November.
    36. Thury, Gerhard & Witt, Stephen F., 1998. "Forecasting industrial production using structural time series models," Omega, Elsevier, vol. 26(6), pages 751-767, December.
    37. Kaiser Remiro, Regina, 1998. "Detection and estimation of structural changes and ouliers in unobserved components," DES - Working Papers. Statistics and Econometrics. WS 9847, Universidad Carlos III de Madrid. Departamento de Estadística.
    38. C. R. McKenzie & Michael McAleer, 2001. "Comparing Tests of Autoregressive Versus Moving Average Errors in Regression Models Using Bahadur's Asymptotic Relative Efficiency," ISER Discussion Paper 0537, Institute of Social and Economic Research, Osaka University.
    39. Panayotis G. Michaelides & Efthymios G. Tsionas & Angelos T. Vouldis & Konstantinos N. Konstantakis & Panagiotis Patrinos, 2018. "A Semi-Parametric Non-linear Neural Network Filter: Theory and Empirical Evidence," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 637-675, March.
    40. Kaiser Remiro, Regina & Maravall, Agustín, 1999. "Short-term and long-term trends, seasonal and the business cycle," DES - Working Papers. Statistics and Econometrics. WS 6291, Universidad Carlos III de Madrid. Departamento de Estadística.
    41. Philippe Goulet Coulombe & Maximilian Gobel, 2020. "Arctic Amplification of Anthropogenic Forcing: A Vector Autoregressive Analysis," Papers 2005.02535, arXiv.org, revised Mar 2021.
    42. Michael A. Kouparitsas, 1999. "Is there evidence of the new economy in the data?," Working Paper Series WP-99-22, Federal Reserve Bank of Chicago.
    43. [Reference to Proietti], Tommaso, 2000. "Comparing seasonal components for structural time series models," International Journal of Forecasting, Elsevier, vol. 16(2), pages 247-260.
    44. Paolo Guarda, 2002. "Potential output and the output gap in Luxembourg: some alternative methods," BCL working papers 4, Central Bank of Luxembourg.
    45. Andrés Bujosa Brun & Marcos Bujosa Brun & Antonio García-Ferrer, 2013. "Mathematical framework for pseudo-spectra of linear stochastic difference equations," Documentos de Trabajo del ICAE 2013-13, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised May 2015.
    46. Stephen Pollock, 2001. "Signal Extraction, Maximum Likelihood Estimation and the Start-up Problem," Working Papers 433, Queen Mary University of London, School of Economics and Finance.
    47. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    48. Agustín Maravall & Cristophe Planas, 1996. "Estimation Error and the Specification of Unobserved Component Models," Working Papers 9608, Banco de España.
    49. J. S. Shonkwiler, 1992. "A Structural Time Series Model Of Nevada Gross Taxable Gaming Revenues," The Review of Regional Studies, Southern Regional Science Association, vol. 22(3), pages 239-249, Winter.
    50. Constantinescu, Mihnea & Nguyen, Anh D.M., 2018. "Unemployment or credit: Which one holds the potential? Results for a small open economy with a low degree of financialization," Economic Systems, Elsevier, vol. 42(4), pages 649-664.
    51. Pollock, D. S. G., 2000. "Trend estimation and de-trending via rational square-wave filters," Journal of Econometrics, Elsevier, vol. 99(2), pages 317-334, December.
    52. Shujie Shen & Gang Li & Haiyan Song, 2009. "Effect of Seasonality Treatment on the Forecasting Performance of Tourism Demand Models," Tourism Economics, , vol. 15(4), pages 693-708, December.
    53. Fackler, Paul L., 1989. "Modeling Trend and Higher Moment Properties of U.S. Corn Yields," 1989 Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk Meeting, April 9-12, 1989, Sanibel Island, Florida 271523, Regional Research Projects > S-232: Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk.
    54. Chen, Chunhang, 1997. "Robustness properties of some forecasting methods for seasonal time series: A Monte Carlo study," International Journal of Forecasting, Elsevier, vol. 13(2), pages 269-280, June.
    55. Jo C. Vu, 2006. "Effect of Demand Volume on Forecasting Accuracy," Tourism Economics, , vol. 12(2), pages 263-276, June.
    56. Kaiser Remiro, Regina & Maravall, Agustín, 1999. "Seasonal outliers in time series," DES - Working Papers. Statistics and Econometrics. WS 6333, Universidad Carlos III de Madrid. Departamento de Estadística.
    57. Valadkhani, Abbas & Costello, Greg & Ratti, Ronald, 2016. "House price cycles in Australia’s four largest capital cities," Economic Analysis and Policy, Elsevier, vol. 52(C), pages 11-22.
    58. Rasi, Chris-Marie & Viikari, Jan-Markus, 1998. "The time-varying NAIRU and potential output in Finland," Bank of Finland Research Discussion Papers 6/1998, Bank of Finland.

  66. Harvey, A C & Todd, P H J, 1983. "Forecasting Economic Time Series with Structural and Box-Jenkins Models: A Case Study," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(4), pages 299-307, October.

    Cited by:

    1. Nelson, Charles R., 1988. "Spurious trend and cycle in the state space decomposition of a time series with a unit root," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 475-488.
    2. Paolo Maranzano & Alessandro Fassò & Matteo Pelagatti & Manfred Mudelsee, 2020. "Statistical Modeling of the Early-Stage Impact of a New Traffic Policy in Milan, Italy," IJERPH, MDPI, vol. 17(3), pages 1-22, February.
    3. Sbrana, Giacomo, 2013. "The exact linkage between the Beveridge–Nelson decomposition and other permanent-transitory decompositions," Economic Modelling, Elsevier, vol. 30(C), pages 311-316.
    4. Franses, P.H. & McAleer, M., 1995. "Testing Nested and Non-Nested Periodically Integrated Autoregressive Models," Other publications TiSEM f6ea7d00-daeb-413b-a279-e, Tilburg University, School of Economics and Management.
    5. Constantinescu, Mihnea & Nguyen, Anh Dinh Minh, 2021. "A century of gaps: Untangling business cycles from secular trends," Economic Modelling, Elsevier, vol. 100(C).
    6. Bengtsson, Thomas & Cavanaugh, Joseph E., 2006. "An improved Akaike information criterion for state-space model selection," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2635-2654, June.
    7. Mihnea Constantinescu & Anh Dinh Minh Nguyen, 2017. "Unemployment or Credit: Who Holds The Potential? Results From a Small-Open Economy," Bank of Lithuania Discussion Paper Series 4, Bank of Lithuania.
    8. Guido Ascari & Paolo Bonomolo & Qazi Haque, 2023. "The Long-Run Phillips Curve is ... a Curve," Working Papers 789, DNB.
    9. Marczak, Martyna & Proietti, Tommaso, 2015. "Outlier Detection in Structural Time Series Models: the Indicator Saturation Approach," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113137, Verein für Socialpolitik / German Economic Association.
    10. Kosei Fukuda, 2010. "Three new empirical perspectives on the Hodrick–Prescott parameter," Empirical Economics, Springer, vol. 39(3), pages 713-731, December.
    11. Huishu Zhang & Jianrong Wei & Jiping Huang, 2014. "Scaling and Predictability in Stock Markets: A Comparative Study," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-5, March.
    12. Shah, Muhammad Ibrahim & Kirikkaleli, Dervis & Adedoyin, Festus Fatai, 2021. "Regime switching effect of COVID-19 pandemic on renewable electricity generation in Denmark," Renewable Energy, Elsevier, vol. 175(C), pages 797-806.
    13. Harry M. Karamujic, 2011. "Comparative Analysis of Australian Residential Mortgage (Home Loan) Interest Rates," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 5(3), pages 311-341, August.
    14. Fanhua Yu & Huibowen Hao & Qingliang Li, 2021. "An Ensemble 3D Convolutional Neural Network for Spatiotemporal Soil Temperature Forecasting," Sustainability, MDPI, vol. 13(16), pages 1-16, August.
    15. Ester Ruiz & Fernando Lorenzo, 1997. "Prediction with univariate time series models: The Iberia case," Documentos de Trabajo (working papers) 0298, Department of Economics - dECON.
    16. Gómez, Víctor & Breitung, Jörg, 1998. "The Beveridge-Nelson decomposition: A different perspective with new results," SFB 373 Discussion Papers 1998,26, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    17. Saligari, Grant R. & Snyder, Ralph D., 1997. "Trends, lead times and forecasting," International Journal of Forecasting, Elsevier, vol. 13(4), pages 477-488, December.
    18. Park, Gonyung, 1996. "The role of detrending methods in a model of real business cycles," Journal of Macroeconomics, Elsevier, vol. 18(3), pages 479-501.
    19. Martyna Marczak & Tommaso Proietti & Stefano Grassi, 2016. "A Data–Cleaning Augmented Kalman Filter for Robust Estimation of State Space Models," CEIS Research Paper 374, Tor Vergata University, CEIS, revised 31 Mar 2016.
    20. Ralf Dewenter & Ulrich Heimeshoff, 2017. "Predicting Advertising Volumes Using Structural Time Series Models: A Case Study," Economics Bulletin, AccessEcon, vol. 37(3), pages 1644-1652.
    21. Thornton, Michael A., 2013. "Removing seasonality under a changing regime: Filtering new car sales," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 4-14.
    22. Stephen Pollock, 2002. "Recursive Estimation in Econometrics," Working Papers 462, Queen Mary University of London, School of Economics and Finance.
    23. Walter Labys, 2005. "Commodity Price Fluctuations: A Century of Analysis," Working Papers Working Paper 2005-01, Regional Research Institute, West Virginia University.
    24. Antonio García Ferrer & Juan del Hoyo Bernat & Peter C. Young & Alfonso Novales Cinca, 1993. "Further evidence on forecasting international GNP growth rates using unobserved components transfer function models," Documentos de Trabajo del ICAE 9312, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    25. Sucharita Ghosh & Donald Lien, 2001. "Forecasting with preliminary data: a comparison of two methods," Applied Economics, Taylor & Francis Journals, vol. 33(6), pages 721-726.
    26. Naci H. Mocan & Kudret Topyan, 1993. "Illicit Drug Use and Health: Analysis and Projections of New York City Birth Outcomes Using a Kalman Filter Model," NBER Working Papers 4359, National Bureau of Economic Research, Inc.
    27. Francis X. Diebold & Lutz Kilian & Marc Nerlove, 2006. "Time Series Analysis," PIER Working Paper Archive 06-019, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
      • Diebold, F.X. & Kilian, L. & Nerlove, Marc, 2006. "Time Series Analysis," Working Papers 28556, University of Maryland, Department of Agricultural and Resource Economics.
    28. Philippe Goulet Coulombe & Maximilian Gobel, 2021. "Arctic Amplification of Anthropogenic Forcing: A Vector Autoregressive Analysis," Working Papers 21-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    29. Pablo Marshall, 1998. "Prediccion De Series De Ventas: Un Analisis De Cointegracion Con El Pib," Abante, Escuela de Administracion. Pontificia Universidad Católica de Chile., vol. 1(1), pages 89-109.
    30. Sen Cheong Kon & Lindsay W. Turner, 2005. "Neural Network Forecasting of Tourism Demand," Tourism Economics, , vol. 11(3), pages 301-328, September.
    31. Mr. Sebastian Acevedo Mejia & Lu Han & Miss Marie S Kim & Ms. Nicole Laframboise, 2016. "Flying to Paradise: The Role of Airlift in the Caribbean Tourism Industry," IMF Working Papers 2016/033, International Monetary Fund.
    32. Pollock, D. S. G., 2001. "Methodology for trend estimation," Economic Modelling, Elsevier, vol. 18(1), pages 75-96, January.
    33. Garcia-Ferrer, Antonio & Queralt, Ricardo A., 1998. "Can univariate models forecast turning points in seasonal economic time series?," International Journal of Forecasting, Elsevier, vol. 14(4), pages 433-446, December.
    34. Candy Mei Fung Tang & Brian King & Stephen Pratt, 2017. "Predicting hotel occupancies with public data," Tourism Economics, , vol. 23(5), pages 1096-1113, August.
    35. Quanrui Song & Jianxu Liu & Songsak Sriboonchitta, 2019. "Risk Measurement of Stock Markets in BRICS, G7, and G20: Vine Copulas versus Factor Copulas," Mathematics, MDPI, vol. 7(3), pages 1-16, March.
    36. Johan Verbeeck & Christel Faes & Thomas Neyens & Niel Hens & Geert Verbeke & Patrick Deboosere & Geert Molenberghs, 2023. "A linear mixed model to estimate COVID‐19‐induced excess mortality," Biometrics, The International Biometric Society, vol. 79(1), pages 417-425, March.
    37. Hotta, Luiz K. & Morettin, Pedro A. & Pereira, Pedro L. Valls, 1992. "The Effect of Overlapping Aggregation on Time Series Models: An Application to the Unemployment Rate in Brazil," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 12(2), November.
    38. Thury, Gerhard & Witt, Stephen F., 1998. "Forecasting industrial production using structural time series models," Omega, Elsevier, vol. 26(6), pages 751-767, December.
    39. Kaiser Remiro, Regina, 1998. "Detection and estimation of structural changes and ouliers in unobserved components," DES - Working Papers. Statistics and Econometrics. WS 9847, Universidad Carlos III de Madrid. Departamento de Estadística.
    40. C. R. McKenzie & Michael McAleer, 2001. "Comparing Tests of Autoregressive Versus Moving Average Errors in Regression Models Using Bahadur's Asymptotic Relative Efficiency," ISER Discussion Paper 0537, Institute of Social and Economic Research, Osaka University.
    41. Panayotis G. Michaelides & Efthymios G. Tsionas & Angelos T. Vouldis & Konstantinos N. Konstantakis & Panagiotis Patrinos, 2018. "A Semi-Parametric Non-linear Neural Network Filter: Theory and Empirical Evidence," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 637-675, March.
    42. Kaiser Remiro, Regina & Maravall, Agustín, 1999. "Short-term and long-term trends, seasonal and the business cycle," DES - Working Papers. Statistics and Econometrics. WS 6291, Universidad Carlos III de Madrid. Departamento de Estadística.
    43. Philippe Goulet Coulombe & Maximilian Gobel, 2020. "Arctic Amplification of Anthropogenic Forcing: A Vector Autoregressive Analysis," Papers 2005.02535, arXiv.org, revised Mar 2021.
    44. Michael A. Kouparitsas, 1999. "Is there evidence of the new economy in the data?," Working Paper Series WP-99-22, Federal Reserve Bank of Chicago.
    45. [Reference to Proietti], Tommaso, 2000. "Comparing seasonal components for structural time series models," International Journal of Forecasting, Elsevier, vol. 16(2), pages 247-260.
    46. Paolo Guarda, 2002. "Potential output and the output gap in Luxembourg: some alternative methods," BCL working papers 4, Central Bank of Luxembourg.
    47. Andrés Bujosa Brun & Marcos Bujosa Brun & Antonio García-Ferrer, 2013. "Mathematical framework for pseudo-spectra of linear stochastic difference equations," Documentos de Trabajo del ICAE 2013-13, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised May 2015.
    48. Stephen Pollock, 2001. "Signal Extraction, Maximum Likelihood Estimation and the Start-up Problem," Working Papers 433, Queen Mary University of London, School of Economics and Finance.
    49. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    50. Agustín Maravall & Cristophe Planas, 1996. "Estimation Error and the Specification of Unobserved Component Models," Working Papers 9608, Banco de España.
    51. Breitung, Jörg, 1998. "On model based seasonal adjustment procedures," SFB 373 Discussion Papers 1998,12, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    52. J. S. Shonkwiler, 1992. "A Structural Time Series Model Of Nevada Gross Taxable Gaming Revenues," The Review of Regional Studies, Southern Regional Science Association, vol. 22(3), pages 239-249, Winter.
    53. Constantinescu, Mihnea & Nguyen, Anh D.M., 2018. "Unemployment or credit: Which one holds the potential? Results for a small open economy with a low degree of financialization," Economic Systems, Elsevier, vol. 42(4), pages 649-664.
    54. Pollock, D. S. G., 2000. "Trend estimation and de-trending via rational square-wave filters," Journal of Econometrics, Elsevier, vol. 99(2), pages 317-334, December.
    55. Shujie Shen & Gang Li & Haiyan Song, 2009. "Effect of Seasonality Treatment on the Forecasting Performance of Tourism Demand Models," Tourism Economics, , vol. 15(4), pages 693-708, December.
    56. Wright, Brian D. & Williams, Jeffrey C., 1990. "The Behavior of Markets for Storable Commodities," 1990 Conference (34th), February 13-15, 1990, Brisbane, Australia 145482, Australian Agricultural and Resource Economics Society.
    57. Ardeni, Pier Giorgio & Wright, Brian, 1990. "The long term behavior of commodity prices," Policy Research Working Paper Series 358, The World Bank.
    58. Fackler, Paul L., 1989. "Modeling Trend and Higher Moment Properties of U.S. Corn Yields," 1989 Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk Meeting, April 9-12, 1989, Sanibel Island, Florida 271523, Regional Research Projects > S-232: Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk.
    59. Chen, Chunhang, 1997. "Robustness properties of some forecasting methods for seasonal time series: A Monte Carlo study," International Journal of Forecasting, Elsevier, vol. 13(2), pages 269-280, June.
    60. Jo C. Vu, 2006. "Effect of Demand Volume on Forecasting Accuracy," Tourism Economics, , vol. 12(2), pages 263-276, June.
    61. Kaiser Remiro, Regina & Maravall, Agustín, 1999. "Seasonal outliers in time series," DES - Working Papers. Statistics and Econometrics. WS 6333, Universidad Carlos III de Madrid. Departamento de Estadística.
    62. Valadkhani, Abbas & Costello, Greg & Ratti, Ronald, 2016. "House price cycles in Australia’s four largest capital cities," Economic Analysis and Policy, Elsevier, vol. 52(C), pages 11-22.
    63. Rasi, Chris-Marie & Viikari, Jan-Markus, 1998. "The time-varying NAIRU and potential output in Finland," Bank of Finland Research Discussion Papers 6/1998, Bank of Finland.

  67. Harvey, Andrew C & Phillips, Garry D A, 1982. "Testing for Contemporaneous Correlation of Disturbances in Systems of Regression Equations," Bulletin of Economic Research, Wiley Blackwell, vol. 34(2), pages 79-91, November.

    Cited by:

    1. Christoph Strumann, 2019. "Hodges–Lehmann Estimation of Static Panel Models with Spatially Correlated Disturbances," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 141-168, January.
    2. Jean-Marie Dufour & Lynda Khalaf, 2000. "Exact Tests for Contemporaneous Correlation of Disturbances in Seemingly Unrelated Regressions," CIRANO Working Papers 2000s-16, CIRANO.
    3. DUFOUR, Jean-Marie & KHALAF, Lynda & BEAULIEU, Marie-Claude, 2003. "Finite-Sample Diagnostics for Multivariate Regressions with Applications to Linear Asset Pricing Models," Cahiers de recherche 06-2003, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    4. Mitze, Timo & Alecke, Björn & Untiedt, Gerhard, 2009. "Trade-FDI Linkages in a System of Gravity Equations for German Regional Data," Ruhr Economic Papers 84, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    5. Dufour, Jean-Marie & Khalaf, Lynda, 2001. "Finite-Sample Simulation-Based Tests in Seemingly Unrelated Regressions," Cahiers de recherche 0111, Université Laval - Département d'économique.
    6. Tsay, Wen-Jen, 2004. "Testing for contemporaneous correlation of disturbances in seemingly unrelated regressions with serial dependence," Economics Letters, Elsevier, vol. 83(1), pages 69-76, April.
    7. Mitze, Timo & Alecke, Björn & Untiedt, Gerhard, 2008. "Trade, FDI and Cross-Variable Linkages: A German (Macro-)Regional Perspective," MPRA Paper 12245, University Library of Munich, Germany.

  68. Harvey, A. C. & Phillips, G. D. A., 1981. "Testing for heteroscedasticity in simultaneous equation models," Journal of Econometrics, Elsevier, vol. 15(3), pages 311-340, April.

    Cited by:

    1. David E. A. Giles & Peter Hampton, 1985. "An Engel Curve Analysis of Household Expenditure in New Zealand," The Economic Record, The Economic Society of Australia, vol. 61(1), pages 450-462, March.
    2. Jenkins, Stephen & Austen-Smith, David, 1987. "Interdependent decision-making in non-profit industries: A simultaneous equation analysis of English provincial theatre," International Journal of Industrial Organization, Elsevier, vol. 5(2), pages 149-174.
    3. Song Jiang & Shuang Qiu & Hong Zhou & Meilan Chen, 2019. "Can FinTech Development Curb Agricultural Nonpoint Source Pollution?," IJERPH, MDPI, vol. 16(22), pages 1-22, November.

  69. A. C. Harvey, 1981. "Finite Sample Prediction And Overdifferencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 2(4), pages 221-232, July.

    Cited by:

    1. Ismael Sanchez & Daniel Pena, 2001. "Properties of Predictors in Overdifferenced Nearly Nonstationary Autoregression," Journal of Time Series Analysis, Wiley Blackwell, vol. 22(1), pages 45-66, January.

  70. G. Gardner & A. C. Harvey & G. D. A. Phillips, 1980. "An Algorithm for Exact Maximum Likelihood Estimation of Autoregressive–Moving Average Models by Means of Kaiman Filtering," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(3), pages 311-322, November.

    Cited by:

    1. Harvey, A. C. & Pereira, Pedro Luiz Valls, 1985. "The estimation of dynamic models with missing observations," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 5(2), November.
    2. Sophie Bercu & Fr�d�ric Proïa, 2013. "A SARIMAX coupled modelling applied to individual load curves intraday forecasting," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(6), pages 1333-1348, June.
    3. Joshua C C Chan & Cody Y L Hsiao, 2013. "Estimation of Stochastic Volatility Models with Heavy Tails and Serial Dependence," CAMA Working Papers 2013-74, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Sam Strong & Siew Ping Tan, 1991. "The Australian Business Cycle: Its Definition and Existence," The Economic Record, The Economic Society of Australia, vol. 67(2), pages 115-125, June.
    5. Pollock, D. S. G., 2003. "Recursive estimation in econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 37-75, October.
    6. Zijian Zeng & Meng Li, 2020. "Bayesian Median Autoregression for Robust Time Series Forecasting," Papers 2001.01116, arXiv.org, revised Dec 2020.
    7. Rui Pedro Brito & Pedro Alarcão Judice, 2021. "Efficient credit portfolios under IFRS 9," CeBER Working Papers 2021-07, Centre for Business and Economics Research (CeBER), University of Coimbra.
    8. Guy Melard & Roch Roy & Abdessamad Saidi, 2006. "Exact maximum likelihood estimation of structured or unit root multivariate time series models," ULB Institutional Repository 2013/13754, ULB -- Universite Libre de Bruxelles.
    9. Rui Da & Dacheng Xiu, 2021. "When Moving‐Average Models Meet High‐Frequency Data: Uniform Inference on Volatility," Econometrica, Econometric Society, vol. 89(6), pages 2787-2825, November.
    10. Stephen Pollock, 2002. "Recursive Estimation in Econometrics," Working Papers 462, Queen Mary University of London, School of Economics and Finance.
    11. Rajae Azrak & Guy Melard, 1998. "The exact quasi-likelihood of time dependent ARMA models," ULB Institutional Repository 2013/13740, ULB -- Universite Libre de Bruxelles.
    12. Amitava Mukherjee, 2013. "Nonparametric Phase-II monitoring for detecting monotone trend based on inverse sampling," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(2), pages 131-153, June.
    13. Kusiak, Andrew & Zhang, Zijun & Verma, Anoop, 2013. "Prediction, operations, and condition monitoring in wind energy," Energy, Elsevier, vol. 60(C), pages 1-12.
    14. Mauricio, Jose Alberto, 2008. "Computing and using residuals in time series models," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1746-1763, January.
    15. Zeng, Zijian & Li, Meng, 2021. "Bayesian median autoregression for robust time series forecasting," International Journal of Forecasting, Elsevier, vol. 37(2), pages 1000-1010.
    16. Che-Yu Hung & Chien-Chih Wang & Shi-Woei Lin & Bernard C. Jiang, 2022. "An Empirical Comparison of the Sales Forecasting Performance for Plastic Tray Manufacturing Using Missing Data," Sustainability, MDPI, vol. 14(4), pages 1-21, February.
    17. Chris Heaton & Natalia Ponomareva & Qin Zhang, 2020. "Forecasting models for the Chinese macroeconomy: the simpler the better?," Empirical Economics, Springer, vol. 58(1), pages 139-167, January.

  71. Harvey, A C & Phillips, G D A, 1980. "Testing for Serial Correlation in Simultaneous Equation Models," Econometrica, Econometric Society, vol. 48(3), pages 747-759, April.

    Cited by:

    1. Jean-Marie Dufour & Lynda Khalaf, 2000. "Exact Tests for Contemporaneous Correlation of Disturbances in Seemingly Unrelated Regressions," CIRANO Working Papers 2000s-16, CIRANO.
    2. Palm, F.C., 1981. "Structural econometric modelling and time series analysis towards an integrated approach," Serie Research Memoranda 0004, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    3. Phillips, G.D.A., 1999. "An Alternative Approach to Obtaining Nagar-Type Moment Approximations in Sumultaneous Equation Models," Discussion Papers 9905, University of Exeter, Department of Economics.
    4. Hwang, Mann-Fen Susan, 1983. "Testing the natural rate hypothesis under the assumption of rational expectations," ISU General Staff Papers 1983010108000017450, Iowa State University, Department of Economics.
    5. Liu-Evans, Gareth & Phillips, Garry D.A., 2018. "On the use of higher order bias approximations for 2SLS and k-class estimators with non-normal disturbances and many instruments," Econometrics and Statistics, Elsevier, vol. 6(C), pages 90-105.

  72. Harvey, A C, 1980. "On Comparing Regression Models in Levels and First Differences," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(3), pages 707-720, October.

    Cited by:

    1. Tomasz Wisniewski & Geoffrey Lightfoot & Simon Lilley, 2012. "Speculating on presidential success: exploring the link between the price–earnings ratio and approval ratings," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(1), pages 106-122, January.
    2. Franc{c}ois Lafond & Aimee Gotway Bailey & Jan David Bakker & Dylan Rebois & Rubina Zadourian & Patrick McSharry & J. Doyne Farmer, 2017. "How well do experience curves predict technological progress? A method for making distributional forecasts," Papers 1703.05979, arXiv.org, revised Sep 2017.
    3. Donyina-Ameyaw, Samuel, 2004. "A Small Macroeconmetric Model Of Trade And Inflation In Ghana," The Warwick Economics Research Paper Series (TWERPS) 696, University of Warwick, Department of Economics.
    4. Mahmood, Talat, 1990. "Die Dynamik der Rentabilität als stochastischer Prozess: eine empirische Zeitreihenanalyse von ausgewählten deutschen und amerikanischen Unternehmen. Vom Fachbereich 20 Informatik der Technischen Univ," EconStor Books, ZBW - Leibniz Information Centre for Economics, number 112236, July.
    5. Hassan, Aminu & Kouhy, Reza, 2013. "Gas flaring in Nigeria: Analysis of changes in its consequent carbon emission and reporting," Accounting forum, Elsevier, vol. 37(2), pages 124-134.
    6. Bennett T. McCallum, 1993. "Unit Roots in Macroeconomic Time Series: Some Critical Issues," NBER Working Papers 4368, National Bureau of Economic Research, Inc.
    7. Miyazaki, Shigetaka & Griffiths, William E., 1984. "The properties of some covariance matrix estimators in linear models with AR(1) errors," Economics Letters, Elsevier, vol. 14(4), pages 351-356.
    8. Eva Gutiérrez-i-Puigarnau & Jos N van Ommeren, 2015. "Commuting and labour supply revisited," Urban Studies, Urban Studies Journal Limited, vol. 52(14), pages 2551-2563, November.
    9. Asgeir Danielsson, 2021. "Wages and prices of foreign goods in the inflationary process in Iceland," Economics wp87, Department of Economics, Central bank of Iceland.

  73. Harvey, Andrew C, 1978. "Linear Regression in the Frequency Domain," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 19(2), pages 507-512, June.

    Cited by:

    1. Emmanuel Anoruo & Vasudeva N. R. Murthy, 2017. "An examination of the REIT return–implied volatility relation: a frequency domain approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(3), pages 581-594, July.
    2. Pierre Perron & Yohei Yamamoto, 2011. "Estimating and Testing Multiple Structural Changes in Linear Models Using Band Spectral Regressions," Boston University - Department of Economics - Working Papers Series WP2011-049, Boston University - Department of Economics.
    3. D.M. Nachane & Amlendu Kumar Dubey, 2008. "The vanishing role of money in the macroeconomy: An Empirical investigation based on spectral and wavelet analysis," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2008-022, Indira Gandhi Institute of Development Research, Mumbai, India.
    4. Fredy Gamboa-Estrada, 2023. "The Role of Foreign Investors and Local Agents in the Derivatives Market and their Impact on the Exchange Rate in Colombia: A Wavelet Analysis," IHEID Working Papers 12-2023, Economics Section, The Graduate Institute of International Studies.
    5. Patrick J. Wilson & L.J. Perry, 2004. "Forecasting Australian Unemployment Rates using Spectral Analysis," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 7(4), pages 459-480, December.
    6. Christoffersson, Jan, 1997. "A resampling method for regression models with serially correlated errors," Computational Statistics & Data Analysis, Elsevier, vol. 25(1), pages 43-53, July.
    7. Feng Zhu, 2005. "The fragility of the Phillips curve: A bumpy ride in the frequency domain," BIS Working Papers 183, Bank for International Settlements.
    8. Wei Yanfeng, 2013. "The Dynamic Relationships between Oil Prices and the Japanese Economy: A Frequency Domain Analysis," Review of Economics & Finance, Better Advances Press, Canada, vol. 3, pages 57-67, May.
    9. M. Azimmohseni & M. Khalafi & M. Kordkatuli, 2019. "Time series analysis of covariance based on linear transfer function models," Statistical Inference for Stochastic Processes, Springer, vol. 22(1), pages 1-16, April.
    10. Monteiro, Paulo Santos, 2008. "Testing Full Consumption Insurance in the Frequency Domain," Economic Research Papers 269910, University of Warwick - Department of Economics.
    11. Bjornson, Bruce & Hong Shik Kim & Lee, Kiseok, 1999. "Low and high frequency macroeconomic forces in asset pricing," The Quarterly Review of Economics and Finance, Elsevier, vol. 39(1), pages 77-100.
    12. Fabio Busetti & Michele Caivano, 2017. "Low frequency drivers of the real interest rate: a band spectrum regression approach," Temi di discussione (Economic working papers) 1132, Bank of Italy, Economic Research and International Relations Area.

  74. Harvey, Andrew C. & Collier, Patrick, 1977. "Testing for functional misspecification in regression analysis," Journal of Econometrics, Elsevier, vol. 6(1), pages 103-119, July.

    Cited by:

    1. Lumsdaine, Robin L. & Ng, Serena, 1999. "Testing for ARCH in the presence of a possibly misspecified conditional mean," Journal of Econometrics, Elsevier, vol. 93(2), pages 257-279, December.
    2. Mounts, Wm. Jr. & Sowell, Clifford, 1995. "A statistical note on possible institutional regimes in budget policy," Journal of Macroeconomics, Elsevier, vol. 17(1), pages 149-160.
    3. Bob Hart & Jim Malley, 1999. "On the Cyclicality and Stability of Real Earnings," Working Papers 1999_13, Business School - Economics, University of Glasgow.
    4. Pollock, D. S. G., 2003. "Recursive estimation in econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 37-75, October.
    5. Nigel Meade & Towhidul Islam, 1998. "Technological Forecasting---Model Selection, Model Stability, and Combining Models," Management Science, INFORMS, vol. 44(8), pages 1115-1130, August.
    6. Saralees Nadarajah & Stephen Chan & Emmanuel Afuecheta, 2014. "Extreme value analysis for emerging African markets," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(3), pages 1347-1360, May.
    7. Nicolau, Mihaela & Palomba, Giulio, 2015. "Dynamic relationships between spot and futures prices. The case of energy and gold commodities," Resources Policy, Elsevier, vol. 45(C), pages 130-143.
    8. Lampin, Laure B.A. & Nadaud, Franck & Grazi, Fabio & Hourcade, Jean-Charles, 2013. "Long-term fuel demand: Not only a matter of fuel price," Energy Policy, Elsevier, vol. 62(C), pages 780-787.
    9. John F. McDonald & Paul J. Prather, 1994. "Suburban Employment Centres: The Case of Chicago," Urban Studies, Urban Studies Journal Limited, vol. 31(2), pages 201-218, March.
    10. Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.
    11. Severini, Thomas A., 1998. "Some properties of inferences in misspecified linear models," Statistics & Probability Letters, Elsevier, vol. 40(2), pages 149-153, September.
    12. Oguz Ersan & Sagi Akron & Ender Demir, 2019. "The effect of European and global uncertainty on stock returns of travel and leisure companies," Tourism Economics, , vol. 25(1), pages 51-66, February.
    13. Abu N.M. Wahid & Mohammad Salahuddin & Abdullah M. Noman, 2010. "Savings and investment in South Asia," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 37(6), pages 658-666, November.
    14. EVRARD Olivier & LEJEUNE Bernard & THIRY Bernard, 1994. "COÛT DE LA DISTRIBUTION D'EAU EN WALLONIE ET À BRUXELLES Estimation d'une fonction de coût hdonique," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 65(2), pages 333-360, April.
    15. Kastens, Terry L. & Schroeder, Ted C., 1996. "Efficiency Tests Of July Kansas City Wheat Futures," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 21(2), pages 1-12, December.

  75. Harvey, A C, 1976. "Estimating Regression Models with Multiplicative Heteroscedasticity," Econometrica, Econometric Society, vol. 44(3), pages 461-465, May.

    Cited by:

    1. Santos Silva, Joao & Tenreyro, Silvana, 2009. "Trading partners and trading volumes: implementing the Helpman-Melitz-Rubinstein model empirically," LSE Research Online Documents on Economics 25505, London School of Economics and Political Science, LSE Library.
    2. Tauchmann, Harald & Reichert, Arndt, 2013. "When Outcome Heterogeneously matters for Selection: a Generalized Selection Correction Estimator," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79698, Verein für Socialpolitik / German Economic Association.
    3. Brown, Sarah & Greene, William H. & Harris, Mark N. & Taylor, Karl, 2015. "An inverse hyperbolic sine heteroskedastic latent class panel tobit model: An application to modelling charitable donations," Economic Modelling, Elsevier, vol. 50(C), pages 228-236.
    4. Qingfeng Liu & Qingsong Yao & Guoqing Zhao, 2020. "Model averaging estimation for conditional volatility models with an application to stock market volatility forecast," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 841-863, August.
    5. Jenkins, Robin R. & Martinez, Salvador A. & Palmer, Karen & Podolsky, Michael J., 2003. "The determinants of household recycling: a material-specific analysis of recycling program features and unit pricing," Journal of Environmental Economics and Management, Elsevier, vol. 45(2), pages 294-318, March.
    6. Panayi, Efstathios & Peters, Gareth W. & Danielsson, Jon & Zigrandd, Jean-Pierre, 2018. "Designating market maker behaviour in limit order book markets," LSE Research Online Documents on Economics 90424, London School of Economics and Political Science, LSE Library.
    7. Spierdijk, L. & Nijman, T.E. & van Soest, A.H.O., 2002. "Modeling Comovements in Trading Intensities to Distinguish Sector and Stock Specific News," Discussion Paper 2002-69, Tilburg University, Center for Economic Research.
    8. Zeba Anjum & Paul J. Burke & Reyer Gerlagh & David I. Stern, 2014. "Modeling the Emissions-Income Relationship Using Long-Run Growth Rates," CCEP Working Papers 1403, Centre for Climate & Energy Policy, Crawford School of Public Policy, The Australian National University.
    9. Ryan A. Decker & Pablo N. D'Erasmo & Hernan Moscoso Boedo, 2016. "Market Exposure and Endogenous Firm Volatility over the Business Cycle," American Economic Journal: Macroeconomics, American Economic Association, vol. 8(1), pages 148-198, January.
    10. Ansgar Belke & Robert Czudaj, 2010. "Is Euro Area Money Demand (Still) Stable?: Cointegrated VAR versus Single Equation Techniques," Discussion Papers of DIW Berlin 982, DIW Berlin, German Institute for Economic Research.
    11. Barabas, György & Kitlinski, Tobias & Schmidt, Christoph M. & Schmidt, Torsten & Siemers, Lars-H. & Brilon, Werner, 2010. "Verkehrsinfrastrukturinvestitionen: Wachstumsaspekte im Rahmen einer gestaltenden Finanzpolitik. Endbericht - Januar 2010. Forschungsprojekt im Auftrag des Bundesministeriums der Finanzen. Projektnumm," RWI Projektberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, number 72601.
    12. Rui Castro & Gian Luca Clementi & Glenn McDonald, 2007. "Legal Institutions, Sectoral Heterogeneity, and Economic Development," Working Paper series 05_07, Rimini Centre for Economic Analysis.
    13. Alexandra Ferreira‐Lopes & Pedro Linhares & Luís Filipe Martins & Tiago Neves Sequeira, 2022. "Quantitative easing and economic growth in Japan: A meta‐analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 36(1), pages 235-268, February.
    14. Katja Zajc Kej??ar, 2006. "The Role Of Foreign Direct Investment In The Firm Selection Process In A Host Country: Evidence From Slovenia," William Davidson Institute Working Papers Series wp841, William Davidson Institute at the University of Michigan.
    15. Rodriguez, Xose Anton & Arias, Carlos, 2008. "The effects of resource depletion on coal mining productivity," Energy Economics, Elsevier, vol. 30(2), pages 397-408, March.
    16. Stacy, Brian, 2014. "Ranking Teachers when Teacher Value-Added is Heterogeneous Across Students," EconStor Preprints 104743, ZBW - Leibniz Information Centre for Economics.
    17. Agrawal, Vipin & Kothare, Meeta & Rao, Ramesh K. S. & Wadhwa, Pavan, 2004. "Bid-ask spreads, informed investors, and the firm's financial condition," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(1), pages 58-76, February.
    18. Rasheda Khanam & Son Nghiem & Maisha Rahman, 2020. "The income gradient and child mental health in Australia: does it vary by assessors?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(1), pages 19-36, February.
    19. Jan Ondrich & J. David Richardson & Shuo Zhang, 2006. "A further investigation of the link between trade and income," International Economic Journal, Taylor & Francis Journals, vol. 20(1), pages 19-36.
    20. Luis Eduardo Arango & Carlos Esteban Posada, 2003. "La participación laboral en Colombia," Coyuntura Social 12933, Fedesarrollo.
    21. Asche, Frank & Guttormsen, Atle G. & Roll, Kristin H., 2006. "Modelling Production Risk in Small Scale Subsistence Agriculture," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25574, International Association of Agricultural Economists.
    22. Ferrara, Gerardo & Jurkatis, Simon, 2021. "Non-standard errors," Bank of England working papers 955, Bank of England.
      • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neussüs & Michael Razen & Utz Weitzel & Christian Brownlees & Javier Gil-Bazo, 2021. "Non-Standard Errors," Working Papers 1303, Barcelona School of Economics.
      • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Jürgen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-standard errors," IWH Discussion Papers 11/2021, Halle Institute for Economic Research (IWH).
      • Albert J. et al. Menkveld, 2021. "Non-Standard Errors," CESifo Working Paper Series 9453, CESifo.
      • Albert J Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard & David Abad-Dí, 2021. "Non-Standard Errors," Post-Print halshs-03500882, HAL.
      • Menkveld, A. & Dreber, A. & Holzmeister, F. & Huber, J. & Johannesson, M. & Kirchler, M. & Neusüss, S. & Razen, M. & Neusüss, S. & Neusüss, S., 2021. "Non-Standard Errors," Cambridge Working Papers in Economics 2182, Faculty of Economics, University of Cambridge.
      • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Jürgen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-standard errors," SAFE Working Paper Series 327, Leibniz Institute for Financial Research SAFE.
      • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Jürgen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & David Abad-Dí­az & Menachem Abudy & Tobi, 2021. "Non-Standard Errors," Working Papers 2021-31, Faculty of Economics and Statistics, Universität Innsbruck.
      • Wolff, Christian & Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüess, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-Standard Errors," CEPR Discussion Papers 16751, C.E.P.R. Discussion Papers.
      • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & David Abad-Díaz & Menachem Abudy & To, 2021. "Non-Standard Errors," Working Paper Series, Social and Economic Sciences 2021-11, Faculty of Social and Economic Sciences, Karl-Franzens-University Graz.
      • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neussüs & Michael Razen & Utz Weitzel & Christian T. Brownlees & Javier Gil-Baz, 2021. "Non-standard errors," Economics Working Papers 1807, Department of Economics and Business, Universitat Pompeu Fabra.
      • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz & Abad-Díaz, David & Abudy, Mena, 2021. "Non-Standard Errors," Working Papers 2021:17, Lund University, Department of Economics.
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      • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Jürgen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & David Abad-Dí­az & Menachem Abudy & Tobi, 2021. "Non-Standard Errors," Working Papers 2021-31, Faculty of Economics and Statistics, Universität Innsbruck.
      • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & David Abad-Díaz & Menachem Abudy & To, 2021. "Non-Standard Errors," Working Paper Series, Social and Economic Sciences 2021-11, Faculty of Social and Economic Sciences, Karl-Franzens-University Graz.
      • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neussüs & Michael Razen & Utz Weitzel & Christian T. Brownlees & Javier Gil-Baz, 2021. "Non-standard errors," Economics Working Papers 1807, Department of Economics and Business, Universitat Pompeu Fabra.
      • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz & Abad-Díaz, David & Abudy, Mena, 2021. "Non-Standard Errors," Working Papers 2021:17, Lund University, Department of Economics.
      • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Edwin Baidoo & Michael Frömmel & et al, 2021. "Non-Standard Errors," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1032, Ghent University, Faculty of Economics and Business Administration.
    245. Homan, M. Eitel & van Praag, Bernard M. S. & Hagenaars, Aldi J. M., 1985. "Household Cost Functions And The Value Of Home Production In One- And Two-Earner Families," Econometric Institute Archives 272324, Erasmus University Rotterdam.
    246. Tassos Anastasatos & Ian R. Davidson, 2004. "How Homogenous are Currency Crises? A Panel Study using Multiple-Response Models," Discussion Paper Series 2004_23, Department of Economics, Loughborough University, revised Dec 2004.
    247. Maria Grydaki & Stilianos Fountas, 2010. "What Explains Output Volatility? Evidence from the G3," Discussion Paper Series 2010_09, Department of Economics, University of Macedonia, revised Jul 2010.
    248. Badola, Shivani & Mukherjee, Sacchidananda, 2020. "Factors Influencing Access to Formal Credit of Unincorporated Enterprises in India: Analysis of NSSO's Unit-level Data," Working Papers 20/326, National Institute of Public Finance and Policy.
    249. Luis Eduardo Arango & Carlos Esteban Posada & Alejandro Charry, 2003. "La Participación Laboral en Colombia Según la Nueva Encuesta: ¿ Cambian sus Determinantes?," Borradores de Economia 3048, Banco de la Republica.
    250. Nick Wills-Johnson, 2010. "Lessons for sustainability from the world’s most sustainable culture," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 12(6), pages 909-925, December.
    251. Jean-Pierre Lachaud, 2001. "Modélisation des déterminants de la mortalité des enfants et pauvreté aux Comores," Documents de travail 53, Groupe d'Economie du Développement de l'Université Montesquieu Bordeaux IV.
    252. Pierre Nguimkeu, 2016. "Some effects of business environment on retail firms," Applied Economics, Taylor & Francis Journals, vol. 48(18), pages 1647-1654, April.
    253. Myoung‐jae Lee & Jin‐young Choi, 2022. "Finding mover–stayer quantile difference due to unobservables using quantile selection corrections," Bulletin of Economic Research, Wiley Blackwell, vol. 74(3), pages 704-721, July.
    254. Sucarrat, Genaro & Escribano, Álvaro, 2010. "The power log-GARCH model," UC3M Working papers. Economics we1013, Universidad Carlos III de Madrid. Departamento de Economía.
    255. Wesley M. Cohen & Richard C. Levin & David C. Mowery, 1987. "Firm Size and R&D Intensity: A Re-Examination," NBER Working Papers 2205, National Bureau of Economic Research, Inc.
    256. Andres Felipe Hoyos Martin, 2015. "Uso de los estimadores HC en presencia de heterocedasticidad multiplicativa," Icesi Economics Working Papers 14564, Universidad Icesi.
    257. Dong Jin Lee & Jai Hyung Yoon, 2012. "The New Keynesian Phillips Curves in Multiple Quantiles and the Asymmetry of Monetary Policy," Working papers 2012-03, University of Connecticut, Department of Economics.
    258. Osiyevskyy, Oleksiy & Shirokova, Galina & Ritala, Paavo, 2020. "Exploration and exploitation in crisis environment: Implications for level and variability of firm performance," Journal of Business Research, Elsevier, vol. 114(C), pages 227-239.
    259. Nwaeze, Emeka T., 2005. "Replacement versus adaptation investments and equity value," Journal of Corporate Finance, Elsevier, vol. 11(3), pages 523-549, June.
    260. Donald Hedeker & Robin J. Mermelstein & Hakan Demirtas, 2008. "An Application of a Mixed-Effects Location Scale Model for Analysis of Ecological Momentary Assessment (EMA) Data," Biometrics, The International Biometric Society, vol. 64(2), pages 627-634, June.
    261. J. R. Lockwood & Katherine E. Castellano & Benjamin R. Shear, 2018. "Flexible Bayesian Models for Inferences From Coarsened, Group-Level Achievement Data," Journal of Educational and Behavioral Statistics, , vol. 43(6), pages 663-692, December.
    262. Langche Zeng, 2000. "A Heteroscedastic Generalized Extreme Value Discrete Choice Model," Sociological Methods & Research, , vol. 29(1), pages 118-144, August.
    263. Christian Cordellier, 1998. "Dix ans de revenus des indépendants : effets temporels et individuels," Économie et Statistique, Programme National Persée, vol. 319(1), pages 53-87.

  76. Harvey, A. C. & Phillips, G. D. A., 1974. "A comparison of the power of some tests for heteroskedasticity in the general linear model," Journal of Econometrics, Elsevier, vol. 2(4), pages 307-316, December.

    Cited by:

    1. Magnus, J.R. & Sinha, A.K., 2003. "On Theil's Errors," Other publications TiSEM 9a72cd04-4426-470c-8ac1-b, Tilburg University, School of Economics and Management.
    2. Lumsdaine, Robin L. & Ng, Serena, 1999. "Testing for ARCH in the presence of a possibly misspecified conditional mean," Journal of Econometrics, Elsevier, vol. 93(2), pages 257-279, December.
    3. John F. McDonald & Paul J. Prather, 1994. "Suburban Employment Centres: The Case of Chicago," Urban Studies, Urban Studies Journal Limited, vol. 31(2), pages 201-218, March.
    4. Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.
    5. R Dunn, 1982. "Parameter Instability in Models of Local Unemployment Responses," Environment and Planning A, , vol. 14(1), pages 75-94, January.
    6. Godfrey, Leslie G., 1996. "Some results on the Glejser and Koenker tests for heteroskedasticity," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 275-299.
    7. Katherine A. Duliba & Robert J. Kauffman & Henry C. Lucas, 2001. "Appropriating Value from Computerized Reservation System Ownership in the Airline Industry," Organization Science, INFORMS, vol. 12(6), pages 702-728, December.
    8. Gignac, Gilles E. & Zajenkowski, Marcin, 2020. "The Dunning-Kruger effect is (mostly) a statistical artefact: Valid approaches to testing the hypothesis with individual differences data," Intelligence, Elsevier, vol. 80(C).

Chapters

  1. Harvey, Andrew, 2006. "Forecasting with Unobserved Components Time Series Models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 7, pages 327-412, Elsevier.

    Cited by:

    1. Hampel, Katharina & Kunz, Marcus & Schanne, Norbert & Wapler, Rüdiger & Weyh, Antje, 2007. "Regional employment forecasts with spatial interdependencies," IAB-Discussion Paper 200702, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    2. Branimir, Jovanovic & Magdalena, Petrovska, 2010. "Forecasting Macedonian GDP: Evaluation of different models for short-term forecasting," MPRA Paper 43162, University Library of Munich, Germany.
    3. David Kohns & Arnab Bhattacharjee, 2019. "Interpreting Big Data in the Macro Economy: A Bayesian Mixed Frequency Estimator," CEERP Working Paper Series 010, Centre for Energy Economics Research and Policy, Heriot-Watt University.
    4. El-Shagi, Makram & Giesen, Sebastian, 2013. "Money and inflation: Consequences of the recent monetary policy," Journal of Policy Modeling, Elsevier, vol. 35(4), pages 520-537.
    5. Kazi Abrar, Hossain & Syed Abul, Basher & A.K. Enamul, Haque, 2017. "Quantifying the impact of Ramadan on global raw sugar prices," MPRA Paper 75941, University Library of Munich, Germany.
    6. Kurmas Akdogan & Selen Baser & Meltem Gulenay Chadwick & Dilara Ertug & Timur Hulagu & Sevim Kosem & Fethi Ogunc & M. Utku Ozmen & Necati Tekatli, 2012. "Short-Term Inflation Forecasting Models For Turkey and a Forecast Combination Analysis," Working Papers 1209, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    7. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
    8. Goodness C. Aye & Mehmet Balcilar Author-Name-First Mehmet & Rangan Gupta & Anandamayee Majumdar, 2014. "Forecasting Aggregate Retail Sales: The Case of South Africa," Working Papers 15-21, Eastern Mediterranean University, Department of Economics.
    9. Garratt, Anthony & Mitchell, James & Vahey, Shaun, 2013. "Measuring Output Gap Nowcast Uncertainty," EMF Research Papers 01, Economic Modelling and Forecasting Group.
    10. Abhimanyu Dadu & Namrata Gulati, 2014. "Inequality, neighborhoods and variation in prices," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2014-001, Indira Gandhi Institute of Development Research, Mumbai, India.
    11. Luis Uzeda, 2018. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Staff Working Papers 18-14, Bank of Canada.
    12. Daniel Buncic, 2020. "Econometric issues with Laubach and Williams' estimates of the natural rate of interest," Papers 2002.11583, arXiv.org, revised Aug 2020.
    13. Jiawen Xu & Pierre Perron, 2023. "Forecasting in the presence of in-sample and out-of-sample breaks," Empirical Economics, Springer, vol. 64(6), pages 3001-3035, June.
    14. Chen, Yen-Hsiao & Quan, Lianfeng & Liu, Yang, 2013. "An empirical investigation on the temporal properties of China's GDP," China Economic Review, Elsevier, vol. 27(C), pages 69-81.
    15. Arvid Raknerud & Terje Skjerpen & Anders Rygh Swensen, 2007. "Forecasting key macroeconomic variables from a large number of predictors: A state space approach," Discussion Papers 504, Statistics Norway, Research Department.
    16. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024.
    17. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707.
    18. Chattopadhyay, Siddhartha & Sahu, Sohini & Jha, Saakshi, 2016. "Estimation of Unobserved Inflation Expectations in India using State-Space Model," MPRA Paper 72710, University Library of Munich, Germany.
    19. Sbrana, Giacomo & Silvestrini, Andrea, 2014. "Random switching exponential smoothing and inventory forecasting," International Journal of Production Economics, Elsevier, vol. 156(C), pages 283-294.
    20. Tallman, Ellis W. & Zaman, Saeed, 2017. "Forecasting inflation: Phillips curve effects on services price measures," International Journal of Forecasting, Elsevier, vol. 33(2), pages 442-457.
    21. Vipin Arora, 2013. "Comparisons of Chinese and Indian Energy Consumption Forecasting Models," Economics Bulletin, AccessEcon, vol. 33(3), pages 2110-2121.
    22. Jiawen Xu & Pierre Perron, 2015. "Forecasting in the presence of in and out of sample breaks," Boston University - Department of Economics - Working Papers Series wp2015-012, Boston University - Department of Economics.
    23. Chen, Xiaoshan & MacDonald, Ronald, 2014. "Measuring the Euro-Dollar Permanent Equilibrium Exchange Rate using the Unobserved Components Model," SIRE Discussion Papers 2015-05, Scottish Institute for Research in Economics (SIRE).
    24. Søren Johansen & Morten Nyboe Tabor, 2017. "Cointegration between Trends and Their Estimators in State Space Models and Cointegrated Vector Autoregressive Models," Econometrics, MDPI, vol. 5(3), pages 1-15, August.
    25. Harvey, Andrew & Oryshchenko, Vitaliy, 2012. "Kernel density estimation for time series data," International Journal of Forecasting, Elsevier, vol. 28(1), pages 3-14.
    26. Tóth, Máté, 2021. "A multivariate unobserved components model to estimate potential output in the euro area: a production function based approach," Working Paper Series 2523, European Central Bank.
    27. Danica Unevska-Andonova, 2018. "Inflation Decomposition Model: Application to Macedonian inflation," Working Papers 2018-06, National Bank of the Republic of North Macedonia.
    28. Mardi Dungey & Jan P.A.M. Jacobs & Jing Jian & Simon van Norden, 2013. "Trend-Cycle Decomposition: Implications from an Exact Structural Identification," CIRANO Working Papers 2013s-23, CIRANO.
    29. Katharina Hampel & Marcus Kunz & Norbert Schanne & Ruediger Wapler & Antje Weyh, 2006. "Regional Unemployment Forecasting Using Structural Component Models With Spatial Autocorrelation," ERSA conference papers ersa06p196, European Regional Science Association.
    30. David Kohns & Arnab Bhattacharjee, 2020. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," Papers 2011.00938, arXiv.org, revised May 2022.
    31. Gen Sakoda & Hideki Takayasu & Misako Takayasu, 2019. "Data Science Solutions for Retail Strategy to Reduce Waste Keeping High Profit," Sustainability, MDPI, vol. 11(13), pages 1-30, June.
    32. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    33. Branimir Jovanovic & Magdalena Petrovska, 2010. "Forecasting Macedonian GDP: Evaluation of different models for short-term forecasting," Working Papers 2010-02, National Bank of the Republic of North Macedonia, revised Aug 2010.
    34. Sbrana, Giacomo & Silvestrini, Andrea & Venditti, Fabrizio, 2017. "Short-term inflation forecasting: The M.E.T.A. approach," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1065-1081.
    35. Lozinskaia, Agata & Redkina, Anastasiia & Shenkman, Evgeniia, 2020. "Electricity consumption forecasting for integrated power system with seasonal patterns," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 60, pages 5-25.
    36. Parra-Alvarez, Juan Carlos & Polattimur, Hamza & Posch, Olaf, 2021. "Risk matters: Breaking certainty equivalence in linear approximations," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
    37. Steven Clark & T. Coggin, 2009. "Trends, Cycles and Convergence in U.S. Regional House Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 39(3), pages 264-283, October.
    38. Tsyplakov, Alexander, 2015. "Quasifiltering for time-series modeling," MPRA Paper 66453, University Library of Munich, Germany.
    39. A. Peyrache & A. N. Rambaldi, 2017. "Incorporating temporal and country heterogeneity in growth accounting—an application to EU-KLEMS," Journal of Productivity Analysis, Springer, vol. 47(2), pages 143-166, April.
    40. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.
    41. Garratt, Anthony & Mitchell, James & Vahey, Shaun P., 2014. "Probability Forecasting for Inflation Warnings from the Federal Reserve," EMF Research Papers 07, Economic Modelling and Forecasting Group.
    42. Marcus Cobb, 2009. "Forecasting Chilean Inflation From Disaggregate Components," Working Papers Central Bank of Chile 545, Central Bank of Chile.
    43. Marcin Bartkowiak, 2018. "Mortality modelling. Model specification and mortality forecast accuracy," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 51, pages 13-36.
    44. Filippo Gusella & Giorgio Ricchiuti, 2022. "A State-Space Approach for Time-Series Prediction of an Heterogeneous Agent Model," Working Papers - Economics wp2022_20.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    45. Cristea, R. G., 2020. "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics 20108, Faculty of Economics, University of Cambridge.
    46. Helmut Luetkepohl, 2009. "Forecasting Aggregated Time Series Variables: A Survey," Economics Working Papers ECO2009/17, European University Institute.
    47. Gen Sakoda & Hideki Takayasu & Misako Takayasu, 2019. "Tracking Poisson Parameter for Non-Stationary Discontinuous Time Series with Taylor’s Abnormal Fluctuation Scaling," Stats, MDPI, vol. 2(1), pages 1-15, January.
    48. El-Shagi, Makram & Giesen, Sebastian, 2010. "Money and Inflation: The Role of Persistent Velocity Movements," IWH Discussion Papers 2/2010, Halle Institute for Economic Research (IWH).
    49. Stefania Mignani & Marcello Pagnini, 2021. "How effective is financial education? Evidence from the Emilia-Romagna region," Working Paper series 21-08, Rimini Centre for Economic Analysis.
    50. Chen, Xiaoshan & MacDonald, Ronald, 2015. "Measuring the dollar–euro permanent equilibrium exchange rate using the unobserved components model," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 20-35.

  2. Andrew C. Harvey, 2002. "Trends, Cycles, and Convergence," Central Banking, Analysis, and Economic Policies Book Series, in: Norman Loayza & Raimundo Soto & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Series Editor) (ed.),Economic Growth: Sources, Trends, and Cycles, edition 1, volume 6, chapter 8, pages 221-250, Central Bank of Chile.
    See citations under working paper version above.

Books

  1. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107034723.

    Cited by:

    1. Matkovskyy, Roman & Jalan, Akanksha & Dowling, Michael, 2020. "Effects of economic policy uncertainty shocks on the interdependence between Bitcoin and traditional financial markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 150-155.
    2. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
    3. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2014. "Modeling Dependence Structure and Forecasting Portfolio Value-at-Risk with Dynamic Copulas," SIRE Discussion Papers 2015-25, Scottish Institute for Research in Economics (SIRE).
    4. Aknouche, Abdelhakim & Francq, Christian, 2023. "Two-stage weighted least squares estimator of the conditional mean of observation-driven time series models," Journal of Econometrics, Elsevier, vol. 237(2).
    5. Cathy Yi-Hsuan Chen & Christian M. Hafner, 2019. "Sentiment-Induced Bubbles in the Cryptocurrency Market," JRFM, MDPI, vol. 12(2), pages 1-12, April.
    6. Blazsek, Szabolcs & Escribano, Álvaro, 2022. "Score-driven threshold ice-age models: benchmark models for long-run climate forecasts," UC3M Working papers. Economics 34757, Universidad Carlos III de Madrid. Departamento de Economía.
    7. Drew Creal & Siem Jan Koopman & André Lucas & Marcin Zamojski, 2015. "Generalized Autoregressive Method of Moments," Tinbergen Institute Discussion Papers 15-138/III, Tinbergen Institute, revised 06 Jul 2018.
    8. Catania, Leopoldo & Proietti, Tommaso, 2020. "Forecasting volatility with time-varying leverage and volatility of volatility effects," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
    9. Krenar AVDULAJ & Jozef BARUNIK, 2013. "Can We Still Benefit from International Diversification? The Case of the Czech and German Stock Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 425-442, November.
    10. Kazeem Abimbola Sanusi & Zandri Dickason-Koekemoer, 2022. "Cryptocurrency Returns, Cybercrime and Stock Market Volatility: GAS and Regime Switching Approaches," International Journal of Economics and Financial Issues, Econjournals, vol. 12(6), pages 52-64, November.
    11. Neves, César & Fernandes, Cristiano & Hoeltgebaum, Henrique, 2017. "Five different distributions for the Lee–Carter model of mortality forecasting: A comparison using GAS models," Insurance: Mathematics and Economics, Elsevier, vol. 75(C), pages 48-57.
    12. Dalhaus, Tatjana & Schaumburg, Julia & Sekhposyan, Tatevik, 2021. "Networking the yield curve: implications for monetary policy," Working Paper Series 2532, European Central Bank.
    13. Andries C. van Vlodrop & Andre (A.) Lucas, 2018. "Estimation Risk and Shrinkage in Vast-Dimensional Fundamental Factor Models," Tinbergen Institute Discussion Papers 18-099/III, Tinbergen Institute.
    14. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
    15. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    16. F Blasques & P Gorgi & S Koopman & O Wintenberger, 2016. "Feasible Invertibility Conditions for Maximum Likelihood Estimation for Observation-Driven Models," Papers 1610.02863, arXiv.org.
    17. Buccheri, Giuseppe & Corsi, Fulvio & Flandoli, Franco & Livieri, Giulia, 2021. "The continuous-time limit of score-driven volatility models," Journal of Econometrics, Elsevier, vol. 221(2), pages 655-675.
    18. Daniele Massacci, 2017. "Tail Risk Dynamics in Stock Returns: Links to the Macroeconomy and Global Markets Connectedness," Management Science, INFORMS, vol. 63(9), pages 3072-3089, September.
    19. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
    20. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    21. Nguyen, Hoang & Javed, Farrukh, 2023. "Dynamic relationship between Stock and Bond returns: A GAS MIDAS copula approach," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 272-292.
    22. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2018. "Seasonal quasi-vector autoregressive models for macroeconomic data," UC3M Working papers. Economics 26316, Universidad Carlos III de Madrid. Departamento de Economía.
    23. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    24. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2015. "Modeling financial sector joint tail risk in the euro area," Working Paper Series 308, Sveriges Riksbank (Central Bank of Sweden).
    25. Anne Opschoor & André Lucas & István Barra & Dick van Dijk, 2021. "Closed-Form Multi-Factor Copula Models With Observation-Driven Dynamic Factor Loadings," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1066-1079, October.
    26. P. Gorgi & Siem Jan (S.J.) Koopman & R. Lit, 2018. "The analysis and forecasting of ATP tennis matches using a high-dimensional dynamic model," Tinbergen Institute Discussion Papers 18-009/III, Tinbergen Institute.
    27. Alexander Georges Gretener & Matthias Neuenkirch & Dennis Umlandt, 2022. "Dynamic Mixture Vector Autoregressions with Score-Driven Weights," Research Papers in Economics 2022-02, University of Trier, Department of Economics.
    28. Linton, O. & Wu, J., 2016. "A coupled component GARCH model for intraday and overnight volatility," Cambridge Working Papers in Economics 1671, Faculty of Economics, University of Cambridge.
    29. Alexander, Carol & Lazar, Emese & Stanescu, Silvia, 2021. "Analytic moments for GJR-GARCH (1, 1) processes," International Journal of Forecasting, Elsevier, vol. 37(1), pages 105-124.
    30. Sucarrat, Genaro & Grønneberg, Steffen & Escribano, Alvaro, 2016. "Estimation and inference in univariate and multivariate log-GARCH-X models when the conditional density is unknown," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 582-594.
    31. Udichibarna Bose & Ronald MacDonald & Serafeim Tsoukas, 2014. "The role of education in equity portfolios during the recent financial crisis," Working Papers 2014_17, Business School - Economics, University of Glasgow.
    32. Blazsek, Szabolcs & Escribano, Álvaro, 2016. "Score-driven dynamic patent count panel data models," UC3M Working papers. Economics 23458, Universidad Carlos III de Madrid. Departamento de Economía.
    33. Janus, Paweł & Koopman, Siem Jan & Lucas, André, 2014. "Long memory dynamics for multivariate dependence under heavy tails," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 187-206.
    34. Ryoko Ito, 2016. "Asymptotic Theory for Beta-t-GARCH," Cambridge Working Papers in Economics 1607, Faculty of Economics, University of Cambridge.
    35. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    36. Denisa BANULESCU-RADU & Elena Ivona DUMITRESCU, 2019. "Do High-frequency-based Measures Improve Conditional Covariance Forecasts?," LEO Working Papers / DR LEO 2709, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    37. Gabriele Fiorentini & Enrique Sentana, 2018. "New Testing Approaches for Mean-Variance Predictability," Working Papers wp2018_1814, CEMFI.
    38. Böhm, Hannes & Schaumburg, Julia & Tonzer, Lena, 2020. "Financial linkages and sectoral business cycle synchronisation: Evidence from Europe," IWH Discussion Papers 2/2020, Halle Institute for Economic Research (IWH).
    39. Abdelhakim Aknouche & Christian Francq, 2022. "Stationarity and ergodicity of Markov switching positive conditional mean models," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(3), pages 436-459, May.
    40. Massacci, Daniele, 2014. "A two-regime threshold model with conditional skewed Student t distributions for stock returns," Economic Modelling, Elsevier, vol. 43(C), pages 9-20.
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    42. Davide Delle Monache & Ivan Petrella & Fabrizio Venditti, 2016. "Common Faith or Parting Ways? A Time Varying Parameters Factor Analysis of Euro-Area Inflation," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 539-565, Emerald Group Publishing Limited.
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    174. Ito, Ryoko, 2013. "Modeling Dynamic Diurnal Patterns in High-Frequency Financial Data," Cambridge Working Papers in Economics 1315, Faculty of Economics, University of Cambridge.
    175. Luisa Bisaglia & Matteo Grigoletto, 2021. "A new time-varying model for forecasting long-memory series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 139-155, March.
    176. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2019. "Co-integration and common trends analysis with score-driven models : an application to the federal funds effective rate and US inflation rate," UC3M Working papers. Economics 28451, Universidad Carlos III de Madrid. Departamento de Economía.
    177. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
    178. Siem Jan Koopman & Rutger Lit & André Lucas, 2015. "Intraday Stock Price Dependence using Dynamic Discrete Copula Distributions," Tinbergen Institute Discussion Papers 15-037/III/DSF90, Tinbergen Institute.
    179. Sucarrat, Genaro & Grønneberg, Steffen, 2016. "Models of Financial Return With Time-Varying Zero Probability," MPRA Paper 68931, University Library of Munich, Germany.
    180. Anne Opschoor & André Lucas, 2019. "Observation-driven Models for Realized Variances and Overnight Returns," Tinbergen Institute Discussion Papers 19-052/IV, Tinbergen Institute.
    181. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2015. "US Monetary and Fiscal Policies - Conflict or Cooperation?," SIRE Discussion Papers 2015-78, Scottish Institute for Research in Economics (SIRE).
    182. Francisco (F.) Blasques & Paolo Gorgi & Siem Jan (S.J.) Koopman, 2017. "Accelerating GARCH and Score-Driven Models: Optimality, Estimation and Forecasting," Tinbergen Institute Discussion Papers 17-059/III, Tinbergen Institute.
    183. Blasques, F. & Gorgi, P. & Koopman, S.J., 2019. "Accelerating score-driven time series models," Journal of Econometrics, Elsevier, vol. 212(2), pages 359-376.
    184. Yang, Lu & Hamori, Shigeyuki, 2021. "The role of the carbon market in relation to the cryptocurrency market: Only diversification or more?," International Review of Financial Analysis, Elsevier, vol. 77(C).
    185. Leopoldo Catania & Alessandra Luati & Pierluigi Vallarino, 2021. "Economic vulnerability is state dependent," CREATES Research Papers 2021-09, Department of Economics and Business Economics, Aarhus University.
    186. Anna Gloria Billé & Leopoldo Catania, 2018. "Dynamic Spatial Autoregressive Models with Time-varying Spatial Weighting Matrices," BEMPS - Bozen Economics & Management Paper Series BEMPS55, Faculty of Economics and Management at the Free University of Bozen.
    187. Kazim Azam & Andre Lucas, 2015. "Mixed Density based Copula Likelihood," Tinbergen Institute Discussion Papers 15-003/IV/DSF084, Tinbergen Institute.
    188. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2013. "Conditional euro area sovereign default risk," Working Paper Series 269, Sveriges Riksbank (Central Bank of Sweden).
    189. Guizzardi, Andrea & Ballestra, Luca Vincenzo & D'Innocenzo, Enzo, 2022. "Hotel dynamic pricing, stochastic demand and covid-19," Annals of Tourism Research, Elsevier, vol. 97(C).
    190. Angelini, Giovanni & Gorgi, Paolo, 2018. "DSGE Models with observation-driven time-varying volatility," Economics Letters, Elsevier, vol. 171(C), pages 169-171.
    191. Blasques, Francisco & Ji, Jiangyu & Lucas, André, 2016. "Semiparametric score driven volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 58-69.
    192. Hoeltgebaum, Henrique & Borenstein, Denis & Fernandes, Cristiano & Veiga, Álvaro, 2021. "A score-driven model of short-term demand forecasting for retail distribution centers," Journal of Retailing, Elsevier, vol. 97(4), pages 715-725.
    193. Dong Hwan Oh & Andrew J. Patton, 2021. "Dynamic Factor Copula Models with Estimated Cluster Assignments," Finance and Economics Discussion Series 2021-029r1, Board of Governors of the Federal Reserve System (U.S.), revised 06 May 2022.
    194. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de Economía.
    195. Siem Jan Koopman & Rutger Lit & André Lucas & Anne Opschoor, 2018. "Dynamic discrete copula models for high‐frequency stock price changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 966-985, November.
    196. Jan van den Brakel & Martijn Souren & Sabine Krieg, 2022. "Estimating monthly labour force figures during the COVID‐19 pandemic in the Netherlands," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1560-1583, October.
    197. F. Blasques & S. J. Koopman & A. Lucas, 2015. "Information-theoretic optimality of observation-driven time series models for continuous responses," Biometrika, Biometrika Trust, vol. 102(2), pages 325-343.
    198. Yarovaya, Larisa & Matkovskyy, Roman & Jalan, Akanksha, 2021. "The effects of a “black swan” event (COVID-19) on herding behavior in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    199. Leopoldo Catania, 2016. "Dynamic Adaptive Mixture Models," Papers 1603.01308, arXiv.org, revised Jan 2023.
    200. Bram van Os & Dick van Dijk, 2020. "Accelerating Peak Dating in a Dynamic Factor Markov-Switching Model," Tinbergen Institute Discussion Papers 20-057/VI, Tinbergen Institute, revised 14 Dec 2020.
    201. Giuseppe Orlando & Michele Bufalo, 2021. "Empirical Evidences on the Interconnectedness between Sampling and Asset Returns’ Distributions," Risks, MDPI, vol. 9(5), pages 1-35, May.
    202. Giuseppe Storti & Chao Wang, 2021. "Modelling uncertainty in financial tail risk: a forecast combination and weighted quantile approach," Papers 2104.04918, arXiv.org, revised Jul 2021.
    203. Stephen Thiele, 2020. "Modeling the conditional distribution of financial returns with asymmetric tails," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 46-60, January.
    204. Astrid Ayala & Szabolcs Blazsek, 2018. "Equity market neutral hedge funds and the stock market: an application of score-driven copula models," Applied Economics, Taylor & Francis Journals, vol. 50(37), pages 4005-4023, August.
    205. Ding, Y., 2021. "Conditional Heteroskedasticity in the Volatility of Asset Returns," Janeway Institute Working Papers 2111, Faculty of Economics, University of Cambridge.
    206. Francisco Blasques & Vladimir Holy & Petra Tomanova, 2019. "Zero-Inflated Autoregressive Conditional Duration Model for Discrete Trade Durations with Excessive Zeros," Tinbergen Institute Discussion Papers 19-004/III, Tinbergen Institute.
    207. Dennis Umlandt, 2020. "Likelihood-based Dynamic Asset Pricing: Learning Time-varying Risk Premia from Cross-Sectional Models," Working Paper Series 2020-06, University of Trier, Research Group Quantitative Finance and Risk Analysis.
    208. Mauro Bernardi & Leopoldo Catania, 2016. "Comparison of Value-at-Risk models using the MCS approach," Computational Statistics, Springer, vol. 31(2), pages 579-608, June.
    209. Carlo Campajola & Domenico Di Gangi & Fabrizio Lillo & Daniele Tantari, 2020. "Modelling time-varying interactions in complex systems: the Score Driven Kinetic Ising Model," Papers 2007.15545, arXiv.org, revised Aug 2021.
    210. Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube, 2023. "Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 369-401, March.
    211. Pawel Janus & André Lucas & Anne Opschoor & Dick J.C. van Dijk, 2014. "New HEAVY Models for Fat-Tailed Returns and Realized Covariance Kernels," Tinbergen Institute Discussion Papers 14-073/IV, Tinbergen Institute, revised 19 Aug 2015.
    212. Szabolcs Blazsek & Marco Villatoro, 2015. "Is Beta- t -EGARCH(1,1) superior to GARCH(1,1)?," Applied Economics, Taylor & Francis Journals, vol. 47(17), pages 1764-1774, April.
    213. Doan, Bao & Papageorgiou, Nicolas & Reeves, Jonathan J. & Sherris, Michael, 2018. "Portfolio management with targeted constant market volatility," Insurance: Mathematics and Economics, Elsevier, vol. 83(C), pages 134-147.
    214. Anne Opschoor & André Lucas, 2019. "Time-varying tail behavior for realized kernels," Tinbergen Institute Discussion Papers 19-051/IV, Tinbergen Institute.
    215. Song, Shijia & Li, Handong, 2022. "Predicting VaR for China's stock market: A score-driven model based on normal inverse Gaussian distribution," International Review of Financial Analysis, Elsevier, vol. 82(C).
    216. Vladim'ir Hol'y & Petra Tomanov'a, 2021. "Modeling Price Clustering in High-Frequency Prices," Papers 2102.12112, arXiv.org, revised Mar 2021.
    217. Z. Sun & P. A. Hamill & Y. Li & Y. C. Yang & S. A. Vigne, 2019. "Did long-memory of liquidity signal the European sovereign debt crisis?," Annals of Operations Research, Springer, vol. 282(1), pages 355-377, November.
    218. Fung, Kennard & Jeong, Jiin & Pereira, Javier, 2022. "More to cryptos than bitcoin: A GARCH modelling of heterogeneous cryptocurrencies," Finance Research Letters, Elsevier, vol. 47(PA).
    219. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2020. "Prediction accuracy of bivariate score-driven risk premium and volatility filters: an illustration for the Dow Jones," UC3M Working papers. Economics 31339, Universidad Carlos III de Madrid. Departamento de Economía.
    220. Jos'e Vin'icius de Miranda Cardoso & Jiaxi Ying & Daniel Perez Palomar, 2020. "Algorithms for Learning Graphs in Financial Markets," Papers 2012.15410, arXiv.org.
    221. Tsyplakov, Alexander, 2015. "Quasifiltering for time-series modeling," MPRA Paper 66453, University Library of Munich, Germany.
    222. Szabolcs Blazsek & Alvaro Escribano, 2022. "Robust Estimation and Forecasting of Climate Change Using Score-Driven Ice-Age Models," Econometrics, MDPI, vol. 10(1), pages 1-29, February.
    223. Mohamed CHIKHI & Claude DIEBOLT & Tapas MISHRA, 2019. "Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers of BETA 2019-43, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    224. Francisco Blasques & Enzo D'Innocenzo & Siem Jan Koopman, 2021. "Common and Idiosyncratic Conditional Volatility Factors: Theory and Empirical Evidence," Tinbergen Institute Discussion Papers 21-057/III, Tinbergen Institute.
    225. Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).
    226. Blazsek Szabolcs & Licht Adrian & Escribano Alvaro, 2021. "Identification of Seasonal Effects in Impulse Responses Using Score-Driven Multivariate Location Models," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 53-66, January.
    227. Storti, Giuseppe & Wang, Chao, 2022. "Nonparametric expected shortfall forecasting incorporating weighted quantiles," International Journal of Forecasting, Elsevier, vol. 38(1), pages 224-239.
    228. Francesco Calvori & Drew Creal & Siem Jan Koopman & André Lucas, 2017. "Testing for Parameter Instability across Different Modeling Frameworks," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 223-246.
    229. Lin, Min-Bin & Wang, Bingling & Bocart, Fabian Y.R.P. & Hafner, Christian M. & Härdle, Wolfgang K., 2022. "DAI Digital Art Index : a robust price index for heterogeneous digital assets," LIDAM Discussion Papers ISBA 2022036, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    230. Sergio Contreras-Espinoza & Francisco Novoa-Muñoz & Szabolcs Blazsek & Pedro Vidal & Christian Caamaño-Carrillo, 2022. "COVID-19 Active Case Forecasts in Latin American Countries Using Score-Driven Models," Mathematics, MDPI, vol. 11(1), pages 1-17, December.
    231. Rutger-Jan Lange & Bram van Os & Dick van Dijk, 2022. "Robust Observation-Driven Models Using Proximal-Parameter Updates Abstract We propose an observation-driven modelling framework that permits time variation in the model’s parameters using a proximal-p," Tinbergen Institute Discussion Papers 22-066/III, Tinbergen Institute, revised 20 Dec 2022.
    232. Timo Dimitriadis & Julie Schnaitmann, 2019. "Forecast Encompassing Tests for the Expected Shortfall," Papers 1908.04569, arXiv.org, revised Aug 2020.
    233. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2019. "Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index," UC3M Working papers. Economics 28133, Universidad Carlos III de Madrid. Departamento de Economía.
    234. Cristea, R. G., 2020. "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics 20108, Faculty of Economics, University of Cambridge.
    235. Francisco (F.) Blasques & Marc Nientker, 2017. "A Stochastic Recurrence Equation Approach to Stationarity and phi-Mixing of a Class of Nonlinear ARCH Models," Tinbergen Institute Discussion Papers 17-072/III, Tinbergen Institute.
    236. Alanya-Beltran, Willy, 2022. "Modelling stock returns volatility with dynamic conditional score models and random shifts," Finance Research Letters, Elsevier, vol. 45(C).
    237. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2017. "Dynamic conditional score models with time-varying location, scale and shape parameters," UC3M Working papers. Economics 25043, Universidad Carlos III de Madrid. Departamento de Economía.
    238. Caterina Schiavoni & Siem Jan Koopman & Franz Palm & Stephan Smeekes & Jan van den Brakel, 2021. "Time-varying state correlations in state space models and their estimation via indirect inference," Tinbergen Institute Discussion Papers 21-020/III, Tinbergen Institute.
    239. Andrew Harvey & Rutger‐Jan Lange, 2018. "Modeling the Interactions between Volatility and Returns using EGARCH‐M," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 909-919, November.
    240. Giuseppe Buccheri & Giacomo Bormetti & Fulvio Corsi & Fabrizio Lillo, 2018. "A Score-Driven Conditional Correlation Model for Noisy and Asynchronous Data: an Application to High-Frequency Covariance Dynamics," Papers 1803.04894, arXiv.org, revised Mar 2019.
    241. Palumbo, D., 2021. "Testing and Modelling Time Series with Time Varying Tails," Cambridge Working Papers in Economics 2111, Faculty of Economics, University of Cambridge.
    242. David Ardia & Kris Boudt & Leopoldo Catania, 2016. "Generalized Autoregressive Score Models in R: The GAS Package," Papers 1609.02354, arXiv.org.
    243. Harvey, A. & Liao, Y., 2019. "Dynamic Tobit models," Cambridge Working Papers in Economics 1913, Faculty of Economics, University of Cambridge.
    244. Yao, Can-Zhong & Li, Min-Jian, 2023. "GARCH-MIDAS-GAS-copula model for CoVaR and risk spillover in stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
    245. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2018. "Seasonality Detection in Small Samples using Score-Driven Nonlinear Multivariate Dynamic Location Models," UC3M Working papers. Economics 27483, Universidad Carlos III de Madrid. Departamento de Economía.
    246. Francisco Blasques & Andre Lucas & Erkki Silde, 2013. "Stationarity and Ergodicity Regions for Score Driven Dynamic Correlation Models," Tinbergen Institute Discussion Papers 13-097/IV/DSF59, Tinbergen Institute.
    247. Troster, Victor & Tiwari, Aviral Kumar & Shahbaz, Muhammad & Macedo, Demian Nicolás, 2019. "Bitcoin returns and risk: A general GARCH and GAS analysis," Finance Research Letters, Elsevier, vol. 30(C), pages 187-193.
    248. Heil, Thomas L.A. & Peter, Franziska J. & Prange, Philipp, 2022. "Measuring 25 years of global equity market co-movement using a time-varying spatial model," Journal of International Money and Finance, Elsevier, vol. 128(C).
    249. Bonnier, Jean-Baptiste, 2022. "Forecasting crude oil volatility with exogenous predictors: As good as it GETS?," Energy Economics, Elsevier, vol. 111(C).
    250. Mauro Bernardi & Leopoldo Catania, 2016. "Portfolio Optimisation Under Flexible Dynamic Dependence Modelling," Papers 1601.05199, arXiv.org.
    251. Paul Labonne, 2020. "Capturing GDP nowcast uncertainty in real time," Papers 2012.02601, arXiv.org, revised Oct 2021.
    252. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Optimal Formulations for Nonlinear Autoregressive Processes," Tinbergen Institute Discussion Papers 14-103/III, Tinbergen Institute.
    253. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2019. "Maximum likelihood estimation of score-driven models with dynamic shape parameters : an application to Monte Carlo value-at-risk," UC3M Working papers. Economics 28638, Universidad Carlos III de Madrid. Departamento de Economía.

  2. Harvey, Andrew & Proietti, Tommaso (ed.), 2005. "Readings in Unobserved Components Models," OUP Catalogue, Oxford University Press, number 9780199278695.

    Cited by:

    1. Marco Cacciotti & Cecilia Frale & Serena Teobaldo, 2013. "A new methodology for a quarterly measure of the Output Gap," Working Papers LuissLab 13103, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    2. Tommaso Proietti & Marco Riani, 2009. "Transformations and seasonal adjustment," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 47-69, January.
    3. Vitor Leone, 2011. "From Property Companies to Real Estate Investment Trusts: The Impact of Economic and Property Factors on UK Listed Property Returns," Economic Issues Journal Articles, Economic Issues, vol. 16(1), pages 19-36, March.
    4. Jingjing Lyu & Bernd Süssmuth, 2024. "Global Linkages across Sectors and Frequency Bands: A Band Spectral Panel Regression Approach," CESifo Working Paper Series 10970, CESifo.
    5. Schreiber, Sven, 2014. "The estimation uncertainty of permanent-transitory decompositions in co-integrated systems," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100582, Verein für Socialpolitik / German Economic Association.
    6. Hansen, Peter R. & Lunde, Asger, 2014. "Estimating The Persistence And The Autocorrelation Function Of A Time Series That Is Measured With Error," Econometric Theory, Cambridge University Press, vol. 30(1), pages 60-93, February.
    7. Stefano Grassi & Nima Nonejad & Paolo Santucci De Magistris, 2017. "Forecasting With the Standardized Self‐Perturbed Kalman Filter," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 318-341, March.
    8. Cecilia Frale, "undated". "Do Surveys Help in Macroeconomic Variables Disaggregation and Estimation?," Working Papers wp2008-2, Department of the Treasury, Ministry of the Economy and of Finance.
    9. Alexander Tsyplakov, 2011. "An introduction to state space modeling (in Russian)," Quantile, Quantile, issue 9, pages 1-24, July.
    10. Cecilia Frale, Serena Teobaldo, Marco Cacciotti, Alessandra Caretta, 2013. "A Quarterly Measure Of Potential Output In The New European Fiscal Framework," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 67(2), pages 181-197, April-Jun.
    11. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    12. Davide Delle Monache & Stefano Grassi & Paolo Santucci de Magistris, 2015. "Testing for Level Shifts in Fractionally Integrated Processes: a State Space Approach," CREATES Research Papers 2015-30, Department of Economics and Business Economics, Aarhus University.
    13. Alexander Tsyplakov, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models (in Russian)," Quantile, Quantile, issue 8, pages 69-122, July.
    14. Tommaso Proietti, 2009. "Structural Time Series Models for Business Cycle Analysis," Palgrave Macmillan Books, in: Terence C. Mills & Kerry Patterson (ed.), Palgrave Handbook of Econometrics, chapter 9, pages 385-433, Palgrave Macmillan.
    15. Marcellino, Massimiliano & Proietti, Tommaso & Frale, Cecilia & Mazzi, Gian Luigi, 2008. "A Monthly Indicator of the Euro Area GDP," CEPR Discussion Papers 7007, C.E.P.R. Discussion Papers.
    16. Zafer Dilaver & Lester C Hunt, 2010. "Industrial Electricity Demand for Turkey: A Structural Time Series Analysis," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 129, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    17. Paulo M. Sánchez & Luis Fernando Melo, 2013. "Combinación de brechas del producto colombiano," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 31(72), pages 74-82, December.
    18. Davide Delle Monache & Stefano Grassi & Paolo Santucci de Magistris, 2017. "Does the ARFIMA really shift?," CREATES Research Papers 2017-16, Department of Economics and Business Economics, Aarhus University.
    19. Cecilia Frale & Massimiliano Marcellino & Gian Luigi Mazzi & Tommaso Proietti, 2010. "Survey data as coincident or leading indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 109-131.
    20. Tommaso Proietti, 2021. "Predictability, real time estimation, and the formulation of unobserved components models," Econometric Reviews, Taylor & Francis Journals, vol. 40(5), pages 433-454, April.
    21. Tommaso, Proietti & Alessandra, Luati, 2012. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," MPRA Paper 39600, University Library of Munich, Germany.
    22. Stefano Grassi & Paolo Santucci de Magistris, 2011. "When Long Memory Meets the Kalman Filter: A Comparative Study," CREATES Research Papers 2011-14, Department of Economics and Business Economics, Aarhus University.
    23. Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
    24. Marco Cacciotti & Cecilia Frale & Serena Teobaldo, 2013. "A new methodology for a quarterly measure of the output gap," Working Papers 6, Department of the Treasury, Ministry of the Economy and of Finance.
    25. Dissanayake, G.S. & Peiris, M.S. & Proietti, T., 2016. "State space modeling of Gegenbauer processes with long memory," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 115-130.
    26. Proietti, Tommaso & Riani, Marco, 2007. "Transformations and Seasonal Adjustment: Analytic Solutions and Case Studies," MPRA Paper 7862, University Library of Munich, Germany.
    27. Sieds, 2013. "Complete Volume LXVII n.2 2013," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 67(2), pages 1-197, April-Jun.
    28. Paulo Mauricio Sánchez Beltrán & Luis Fernando Melo Velandia, 2013. "Combinación de brechas del producto colombiano," Borradores de Economia 10973, Banco de la Republica.
    29. Prates, Daniela Magalhães & Cunha, André Moreira & Lélis, Marcos Tadeo Caputi, 2009. "Exchange-rate management in Brazil," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), December.
    30. Javid, Muhammad & Qayyum, Abdul, 2014. "Electricity consumption-GDP nexus in Pakistan: A structural time series analysis," Energy, Elsevier, vol. 64(C), pages 811-817.
    31. Cesar Rodrigues van der Laan & André Moreira Cunha & Marcos Tadeu Caputi Lélis, 2017. "On the effectiveness of capital controls during the Great Recession: The Brazilian experience (2007–2013)," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 40(2), pages 203-222, April.
    32. Mauro Bernardi & Leopoldo Catania, 2016. "Portfolio Optimisation Under Flexible Dynamic Dependence Modelling," Papers 1601.05199, arXiv.org.

  3. Harvey,Andrew & Koopman,Siem Jan & Shephard,Neil (ed.), 2004. "State Space and Unobserved Component Models," Cambridge Books, Cambridge University Press, number 9780521835954.

    Cited by:

    1. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    2. David T. Frazier & Gael M. Martin & Ruben Loaiza-Maya, 2022. "Variational Bayes in State Space Models: Inferential and Predictive Accuracy," Monash Econometrics and Business Statistics Working Papers 1/22, Monash University, Department of Econometrics and Business Statistics.
    3. Flavio Cunha & James J. Heckman, 2009. "The Economics and Psychology of Inequality and Human Development," Working Papers 200934, Geary Institute, University College Dublin.
    4. Koop, Gary & Poirier, Dale J., 2004. "Bayesian variants of some classical semiparametric regression techniques," Journal of Econometrics, Elsevier, vol. 123(2), pages 259-282, December.
    5. Svend Hylleberg, 2006. "Seasonal Adjustment," Economics Working Papers 2006-04, Department of Economics and Business Economics, Aarhus University.
    6. Tommaso Gabrieli & Keith Pilbeam & Tianyu Wang, 2018. "Estimation of bubble dynamics in the Chinese real estate market: a State space model," International Economics and Economic Policy, Springer, vol. 15(2), pages 483-499, April.
    7. Caporin, Massimiliano & Lisi, Francesco, 2013. "A Conditional Single Index model with Local Covariates for detecting and evaluating active portfolio management," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 236-249.
    8. Guizzardi, Andrea & Mazzocchi, Mario, 2010. "Tourism demand for Italy and the business cycle," Tourism Management, Elsevier, vol. 31(3), pages 367-377.
    9. Bitto, Angela & Frühwirth-Schnatter, Sylvia, 2019. "Achieving shrinkage in a time-varying parameter model framework," Journal of Econometrics, Elsevier, vol. 210(1), pages 75-97.
    10. Michel Culot & Valérie Goffin & Steve Lawford & Sébastien de Meten & Yves Smeers, 2013. "Practical stochastic modelling of electricity prices," Post-Print hal-01021603, HAL.
    11. Kristian Jönsson, 2017. "Restricted Hodrick–Prescott filtering in a state-space framework," Empirical Economics, Springer, vol. 53(3), pages 1243-1251, November.
    12. Fei Gu & Kristopher J. Preacher & Emilio Ferrer, 2014. "A State Space Modeling Approach to Mediation Analysis," Journal of Educational and Behavioral Statistics, , vol. 39(2), pages 117-143, April.
    13. Stefano Grassi & Tommaso Proietti, 2010. "Characterizing economic trends by Bayesian stochastic model specification search," EERI Research Paper Series EERI_RP_2010_25, Economics and Econometrics Research Institute (EERI), Brussels.
    14. Parley Ruogu Yang, 2020. "Using the yield curve to forecast economic growth," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1057-1080, November.
    15. Susanne M. Schennach, 2013. "Long memory via networking," CeMMAP working papers CWP13/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Bulat Gafarov, 2013. "Do unobserved components models forecast inflation in Russia?," HSE Working papers WP BRP 35/EC/2013, National Research University Higher School of Economics.
    17. Filippo Gusella & Engelbert Stockhammer, 2021. "Testing fundamentalist–momentum trader financial cycles: An empirical analysis via the Kalman filter," Metroeconomica, Wiley Blackwell, vol. 72(4), pages 758-797, November.
    18. Alexander Tsyplakov, 2011. "An introduction to state space modeling (in Russian)," Quantile, Quantile, issue 9, pages 1-24, July.
    19. Agustín Maravall Herrero & Domingo Pérez Cañete, 2011. "Applying and interpreting model-based seasonal adjustment. The euro-area industrial production series," Working Papers 1116, Banco de España.
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