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Marcus J. Chambers

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.

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Chambers, Marcus J, 1992. "Estimation of a Continuous-Time Dynamic Demand System," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(1), pages 53-64, Jan.-Marc.

    Mentioned in:

    1. Estimation of a continuous-time dynamic demand system (Journal of Applied Econometrics 1992) in ReplicationWiki ()

Working papers

  1. Chambers, Marcus J & Taylor, AM Robert, 2019. "Deterministic Parameter Change Models in Continuous and Discrete Time," Essex Finance Centre Working Papers 24072, University of Essex, Essex Business School.

    Cited by:

    1. Alessandro Casini & Pierre Perron, 2020. "Continuous Record Laplace-based Inference about the Break Date in Structural Change Models," Boston University - Department of Economics - Working Papers Series WP2020-014, Boston University - Department of Economics.

  2. Chambers, MJ, 2018. "Frequency Domain Estimation of Cointegrating Vectors with Mixed Frequency and Mixed Sample Data," Economics Discussion Papers 21144, University of Essex, Department of Economics.

    Cited by:

    1. Philipp Gersing & Leopold Soegner & Manfred Deistler, 2022. "Retrieval from Mixed Sampling Frequency: Generic Identifiability in the Unit Root VAR," Papers 2204.05952, arXiv.org, revised Jul 2023.
    2. Cleiton Guollo Taufemback, 2023. "Asymptotic Behavior of Temporal Aggregation in Mixed‐Frequency Datasets," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(4), pages 894-909, August.

  3. Chambers, MJ & Kyriacou, M, 2016. "Jackknife Bias Reduction in the Presence of a Near-Unit Root," Economics Discussion Papers 17623, University of Essex, Department of Economics.

    Cited by:

    1. Kruse, Robinson & Kaufmann, Hendrik & Wegener, Christoph, 2018. "Bias-corrected estimation for speculative bubbles in stock prices," Economic Modelling, Elsevier, vol. 73(C), pages 354-364.

  4. Chambers, MJ, 2016. "The Estimation of Continuous Time Models with Mixed Frequency Data," Economics Discussion Papers 15988, University of Essex, Department of Economics.

    Cited by:

    1. Philipp Gersing & Leopold Soegner & Manfred Deistler, 2022. "Retrieval from Mixed Sampling Frequency: Generic Identifiability in the Unit Root VAR," Papers 2204.05952, arXiv.org, revised Jul 2023.
    2. Yaoyuan Zhang & Dewen Xiong, 2023. "Optimal Strategy of the Dynamic Mean-Variance Problem for Pairs Trading under a Fast Mean-Reverting Stochastic Volatility Model," Mathematics, MDPI, vol. 11(9), pages 1-19, May.
    3. Chambers, Marcus J., 2020. "Frequency domain estimation of cointegrating vectors with mixed frequency and mixed sample data," Journal of Econometrics, Elsevier, vol. 217(1), pages 140-160.
    4. Deistler, Manfred & Koelbl, Lukas & Anderson, Brian D.O., 2017. "Non-identifiability of VMA and VARMA systems in the mixed frequency case," Econometrics and Statistics, Elsevier, vol. 4(C), pages 31-38.
    5. Antoine GODIN & Sakir-Devrim YILMAZ, 2020. "Modelling Small Open Developing Economies in a Financialized World: A Stock-Flow Consistent Prototype Growth Model," Working Paper 5eb7e0e8-560f-4ce6-91a5-5, Agence française de développement.
    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. 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. 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.

    Cited by:

    1. Antoine GODIN & Sakir-Devrim YILMAZ, 2020. "Modelling Small Open Developing Economies in a Financialized World: A Stock-Flow Consistent Prototype Growth Model," Working Paper 5eb7e0e8-560f-4ce6-91a5-5, Agence française de développement.
    2. Fasen-Hartmann, Vicky & Mayer, Celeste, 2023. "Empirical spectral processes for stationary state space models," Stochastic Processes and their Applications, Elsevier, vol. 155(C), pages 319-354.
    3. 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.
    4. 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.
    5. 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.
    6. Ralf Korn & Bilgi Yilmaz, 2022. "House Prices as a Result of Trading Activities: A Patient Trader Model," Computational Economics, Springer;Society for Computational Economics, vol. 60(1), pages 281-303, June.
    7. 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.
    8. Sikora, Grzegorz & Michalak, Anna & Bielak, Łukasz & Miśta, Paweł & Wyłomańska, Agnieszka, 2019. "Stochastic modeling of currency exchange rates with novel validation techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1202-1215.
    9. Szarek, Dawid & Bielak, Łukasz & Wyłomańska, Agnieszka, 2020. "Long-term prediction of the metals’ prices using non-Gaussian time-inhomogeneous stochastic process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).

  6. Chambers, MJ, 2013. "The Calculation of Some Limiting Distributions Arising in Near-Integrated Models with GLS Detrending," Economics Discussion Papers 8975, University of Essex, Department of Economics.

    Cited by:

    1. Chambers, MJ, 2016. "The Effects of Sampling Frequency on Detrending Methods for Unit Root Tests," Economics Discussion Papers 16062, University of Essex, Department of Economics.
    2. Neil Kellard & Denise Osborn & Jerry Coakley & Marcus J. Chambers, 2015. "Testing for a Unit Root in a Near-Integrated Model with Skip-Sampled Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 630-649, September.

  7. Chambers, Marcus J. & Kyriacou, Maria, 2012. "Jackknife bias reduction in autoregressive models with a unit root," MPRA Paper 38255, University Library of Munich, Germany.

    Cited by:

    1. Chambers, Marcus J., 2013. "Jackknife estimation of stationary autoregressive models," Journal of Econometrics, Elsevier, vol. 172(1), pages 142-157.
    2. Hendrik Kaufmannz & Robinson Kruse, 2013. "Bias-corrected estimation in potentially mildly explosive autoregressive models," CREATES Research Papers 2013-10, Department of Economics and Business Economics, Aarhus University.

  8. Chambers, MJ, 2010. "Jackknife Estimation of Stationary Autoregressive Models," Economics Discussion Papers 2786, University of Essex, Department of Economics.

    Cited by:

    1. Kanchana Nadarajah & Gael M Martin & Donald S Poskitt, 2019. "Optimal Bias Correction of the Log-periodogram Estimator of the Fractional Parameter: A Jackknife Approach," Monash Econometrics and Business Statistics Working Papers 7/19, Monash University, Department of Econometrics and Business Statistics.
    2. Iglesias, Emma M., 2014. "Testing of the mean reversion parameter in continuous time models," Economics Letters, Elsevier, vol. 122(2), pages 187-189.
    3. Arturas Juodis & Yiannis Karavias & Vasilis Sarafidis, 2020. "A Homogeneous Approach to Testing for Granger Non-Causality in Heterogeneous Panels," Monash Econometrics and Business Statistics Working Papers 32/20, Monash University, Department of Econometrics and Business Statistics.
    4. Aaron H. Anglin & Aaron F. McKenny & Jeremy C. Short, 2018. "The Impact of Collective Optimism on New Venture Creation and Growth: A Social Contagion Perspective," Entrepreneurship Theory and Practice, , vol. 42(3), pages 390-425, May.
    5. Kruse, Yves Robinson & Kaufmann, Hendrik, 2015. "Bias-corrected estimation in mildly explosive autoregressions," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112897, Verein für Socialpolitik / German Economic Association.
    6. Kruse, Robinson & Kaufmann, Hendrik & Wegener, Christoph, 2018. "Bias-corrected estimation for speculative bubbles in stock prices," Economic Modelling, Elsevier, vol. 73(C), pages 354-364.
    7. Diana Escandon-Barbosa & David Urbano-Pulido & Andrea Hurtado-Ayala, 2019. "Exploring the Relationship between Formal and Informal Institutions, Social Capital, and Entrepreneurial Activity in Developing and Developed Countries," Sustainability, MDPI, vol. 11(2), pages 1-20, January.
    8. Bork, Lasse & Kaltwasser, Pablo Rovira & Sercu, Piet, 2022. "Aggregation bias in tests of the commodity currency hypothesis," Journal of Banking & Finance, Elsevier, vol. 135(C).
    9. Chambers, MJ & Kyriacou, M, 2016. "Jackknife Bias Reduction in the Presence of a Near-Unit Root," Economics Discussion Papers 17623, University of Essex, Department of Economics.
    10. Marcus J. Chambers, 2015. "A Jackknife Correction to a Test for Cointegration Rank," Econometrics, MDPI, vol. 3(2), pages 1-21, May.
    11. Chambers, Marcus J. & Kyriacou, Maria, 2013. "Jackknife estimation with a unit root," Statistics & Probability Letters, Elsevier, vol. 83(7), pages 1677-1682.
    12. Yong Bao, 2013. "On Sample Skewness and Kurtosis," Econometric Reviews, Taylor & Francis Journals, vol. 32(4), pages 415-448, December.
    13. Gareth Liu-Evans, 2021. "Improving the Estimation and Predictions of Small Time Series Models," Working Papers 202106, University of Liverpool, Department of Economics.
    14. Ye Chen & Jun Yu, 2011. "Optimal Jackknife for Discrete Time and Continuous Time Unit Root Models," Working Papers 12-2011, Singapore Management University, School of Economics.
    15. Christian Weiß & Hee-Young Kim, 2013. "Parameter estimation for binomial AR(1) models with applications in finance and industry," Statistical Papers, Springer, vol. 54(3), pages 563-590, August.
    16. Chen, Ye & Yu, Jun, 2015. "Optimal jackknife for unit root models," Statistics & Probability Letters, Elsevier, vol. 99(C), pages 135-142.
    17. Christian Gouriéroux & Jean-Michel Zakoian, 2012. "Estimation Adjusted VaR," Working Papers 2012-16, Center for Research in Economics and Statistics.
    18. Marian Vavra, 2023. "Bias-Correction in Time Series Quantile Regression Models," Working and Discussion Papers WP 3/2023, Research Department, National Bank of Slovakia.
    19. Hendrik Kaufmannz & Robinson Kruse, 2013. "Bias-corrected estimation in potentially mildly explosive autoregressive models," CREATES Research Papers 2013-10, Department of Economics and Business Economics, Aarhus University.
    20. Arturas Juodis & Yiannis Karavias, 2019. "Partially heterogeneous tests for Granger non-causality in panel data," Bank of Lithuania Working Paper Series 59, Bank of Lithuania.
    21. 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.
    22. Chambers, MJ & Kyriacou, M, 2010. "Jackknife Bias Reduction in the Presence of a Unit Root," Economics Discussion Papers 2785, University of Essex, Department of Economics.

  9. Chambers, MJ & Kyriacou, M, 2010. "Jackknife Bias Reduction in the Presence of a Unit Root," Economics Discussion Papers 2785, University of Essex, Department of Economics.

    Cited by:

    1. Marcus J. Chambers, 2015. "A Jackknife Correction to a Test for Cointegration Rank," Econometrics, MDPI, vol. 3(2), pages 1-21, May.
    2. Chambers, Marcus J. & Kyriacou, Maria, 2013. "Jackknife estimation with a unit root," Statistics & Probability Letters, Elsevier, vol. 83(7), pages 1677-1682.
    3. Ye Chen & Jun Yu, 2011. "Optimal Jackknife for Discrete Time and Continuous Time Unit Root Models," Working Papers 12-2011, Singapore Management University, School of Economics.
    4. Chambers, Marcus J., 2013. "Jackknife estimation of stationary autoregressive models," Journal of Econometrics, Elsevier, vol. 172(1), pages 142-157.

  10. Marcus J. Chambers & Joanne S. Ercolani & A. M. Robert Taylor, 2010. "Testing for seasonal unit roots by frequency domain regression," Discussion Papers 10/02, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. Eroğlu, Burak Alparslan, 2019. "Wavelet variance ratio cointegration test and wavestrapping," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 298-319.
    2. Burak Eroglu, 2017. "Wavelet Variance Ratio Test And Wavestrapping For The Determination Of The Cointegration Rank," Working Papers 1706, The Center for Financial Studies (CEFIS), Istanbul Bilgi University.
    3. Atle Oglend & Frank Asche, 2016. "Cyclical non-stationarity in commodity prices," Empirical Economics, Springer, vol. 51(4), pages 1465-1479, December.
    4. Burak Eroglu & Kemal Caglar Gogebakan & Mirza Trokic, 2017. "Fractional Seasonal Variance Ratio Unit Root Tests," Working Papers 1707, The Center for Financial Studies (CEFIS), Istanbul Bilgi University.
    5. Sheng-Hung Chen & Song-Zan Chiou-Wei & Zhen Zhu, 2022. "Stochastic seasonality in commodity prices: the case of US natural gas," Empirical Economics, Springer, vol. 62(5), pages 2263-2284, May.

  11. McCrorie, J.R. & Chambers, M.J., 2004. "Granger Causality and the Sampling of Economic Processes," Discussion Paper 2004-39, Tilburg University, Center for Economic Research.

    Cited by:

    1. Antonio Diez de los Rios & Enrique Sentana, 2011. "Testing Uncovered Interest Parity: A Continuous‐Time Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(4), pages 1215-1251, November.
    2. Chih-nan Chen & Tsutomu Watanabe & Tomoyoshi Yabu, 2009. "A New Method for Identifying the Effects of Foreign Exchange Interventions," IMES Discussion Paper Series 09-E-06, Institute for Monetary and Economic Studies, Bank of Japan.
    3. K. Lebedeva, 2015. "An Empirical Analysis of the Russian Financial Markets’ Liquidity and Returns," Review of Business and Economics Studies // Review of Business and Economics Studies, Финансовый Университет // Financial University, vol. 3(3), pages 5-31.
    4. Alessandro Gregorio & Francesco Iafrate, 2021. "Regularized bridge-type estimation with multiple penalties," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(5), pages 921-951, October.
    5. Petrović, Ljiljana & Dimitrijević, Sladjana, 2012. "Causality with finite horizon of the past in continuous time," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1219-1223.
    6. Salamaliki, Paraskevi K. & Venetis, Ioannis A., 2013. "Energy consumption and real GDP in G-7: Multi-horizon causality testing in the presence of capital stock," Energy Economics, Elsevier, vol. 39(C), pages 108-121.
    7. Ghysels, Eric, 2016. "Macroeconomics and the reality of mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 294-314.
    8. Ehlers, Stefan & Gürtler, Marc & Olboeter, Sven, 2010. "Financial crises and information transfer: An empirical analysis of the lead-lag relationship between equity and CDS iTraxx Indices," Working Papers IF34V1, Technische Universität Braunschweig, Institute of Finance.
    9. Ghysels, Eric & Hill, Jonathan B. & Motegi, Kaiji, 2013. "Testing for Granger Causality with Mixed Frequency Data," CEPR Discussion Papers 9655, C.E.P.R. Discussion Papers.
    10. 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.
    11. 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.
    12. Arie ten Cate, 2004. "Refinement of the partial adjustment model using continuous-time econometrics," CPB Discussion Paper 41, CPB Netherlands Bureau for Economic Policy Analysis.
    13. Daniel Ventosa-Santaulària & José Eduardo Vera-Valdés, 2008. "Granger-Causality in the presence of structural breaks," Economics Bulletin, AccessEcon, vol. 3(61), pages 1-14.

  12. Chambers, M.J. & McCrorie, J.R., 2004. "Identification and Estimation of Exchange Rate Models with Unobservable Fundamentals," Discussion Paper 2004-38, Tilburg University, Center for Economic Research.

    Cited by:

    1. 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.
    2. 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.
    3. 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.

  13. Chambers, MJ, 2001. "Testing for Unit Roots with Flow Data and Varying Sampling Frequency," Economics Discussion Papers 2761, University of Essex, Department of Economics.

    Cited by:

    1. Wang, Dabin & Tomek, William G., 2004. "Commodity Prices And Unit Root Tests," 2004 Annual meeting, August 1-4, Denver, CO 20141, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Uwe Hassler, 2011. "Estimation of fractional integration under temporal aggregation," Post-Print hal-00815563, HAL.
    3. Theodore Simos & Mike Tsionas, 2018. "Bayesian inference of the fractional Ornstein–Uhlenbeck process under a flow sampling scheme," Computational Statistics, Springer, vol. 33(4), pages 1687-1713, December.
    4. Wang, Dabin & Tomek, William G., 2004. "Commodity Prices And Unit Root Tests," Working Papers 127145, Cornell University, Department of Applied Economics and Management.
    5. Xuedong Wu & Jeffrey H. Dorfman & Berna Karali, 2018. "The impact of data frequency on market efficiency tests of commodity futures prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(6), pages 696-714, June.
    6. Chambers, MJ, 2016. "The Effects of Sampling Frequency on Detrending Methods for Unit Root Tests," Economics Discussion Papers 16062, University of Essex, Department of Economics.
    7. Chambers, Marcus J., 2004. "Testing for unit roots with flow data and varying sampling frequency," Journal of Econometrics, Elsevier, vol. 119(1), pages 1-18, March.

  14. Chambers, MJ, 2001. "Cointegration and Sampling Frequency," Economics Discussion Papers 2760, University of Essex, Department of Economics.

    Cited by:

    1. 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.
    2. Herzer, Dierk, 2009. "Cross-country heterogeneity and the trade-income relationship," Proceedings of the German Development Economics Conference, Frankfurt a.M. 2009 13, Verein für Socialpolitik, Research Committee Development Economics.
    3. Herzer, Dierk & Strulik, Holger, 2013. "Religiosity and income: A panel cointegration and causality analysis," University of Göttingen Working Papers in Economics 168, University of Goettingen, Department of Economics.
    4. Nicole Grunewald & Inmaculada Martínez-Zarzoso, 2014. "Green Growth in Mexico, Brazil and Chile: Policy strategies and future prospects," Ibero America Institute for Econ. Research (IAI) Discussion Papers 229, Ibero-America Institute for Economic Research.
    5. Herzer, Dierk & Nunnenkamp, Peter, 2014. "Income inequality and health: Evidence from developed and developing countries," Economics Discussion Papers 2014-45, Kiel Institute for the World Economy (IfW Kiel).
    6. Ghysels, Eric & Miller, J. Isaac, 2013. "Testing for Cointegration with Temporally Aggregated and Mixed-frequency Time Series," CEPR Discussion Papers 9654, C.E.P.R. Discussion Papers.
    7. Dierk Herzery & Holger Strulik & Sebastian Vollmer, 2010. "The Long-run Determinants of Fertility: One Century of Demographic Change 1900-1999," PGDA Working Papers 6310, Program on the Global Demography of Aging.
    8. Chambers, Marcus J., 2016. "The estimation of continuous time models with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 390-404.
    9. J. Isaac Miller, 2018. "Testing Cointegrating Relationships Using Irregular and Non-Contemporaneous Series with an Application to Paleoclimate Data," Working Papers 1809, Department of Economics, University of Missouri.
    10. 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.
    11. Chambers, MJ, 2016. "The Effects of Sampling Frequency on Detrending Methods for Unit Root Tests," Economics Discussion Papers 16062, University of Essex, Department of Economics.
    12. J. Isaac Miller & Xi Wang, 2016. "Implementing Residual-Based KPSS Tests for Cointegration with Data Subject to Temporal Aggregation and Mixed Sampling Frequencies," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(6), pages 810-824, November.
    13. Partha Ray & Vinodh Madhavan, 2014. "Price and Volatility Linkages between Indian Stocks and their European GDRs," Proceedings of International Academic Conferences 0300812, International Institute of Social and Economic Sciences.
    14. 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.
    15. J. Isaac Miller, 2016. "Conditionally Efficient Estimation of Long-Run Relationships Using Mixed-Frequency Time Series," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1142-1171, June.

  15. Chambers, MJ, 1998. "Gaussian estimation of temporally aggregated cointegrated systems," Economics Discussion Papers 2763, University of Essex, Department of Economics.

    Cited by:

    1. 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.

  16. Chambers, MJ, 1995. "Long Memory and Aggregation in Macroeconomic Time Series," Economics Discussion Papers 2766, University of Essex, Department of Economics.

    Cited by:

    1. Carlos Barros & Luis Gil-Alana, 2012. "Inflation forecasting in Angola: a fractional approach," CEsA Working Papers 103, CEsA - Centre for African and Development Studies.
    2. McHale, I.G. & Peel, D.A., 2010. "Habit and long memory in UK lottery sales," Economics Letters, Elsevier, vol. 109(1), pages 7-10, October.
    3. Maria Caporale, Guglielmo & A. Gil-Alana, Luis, 2011. "Multi-Factor Gegenbauer Processes and European Inflation Rates," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 26, pages 386-409.
    4. Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating Univariate Fractional Integration within a Large VAR(1)," AMSE Working Papers 1844, Aix-Marseille School of Economics, France.
    5. Christian Leschinski & Michelle Voges & Philipp Sibbertsen, 2021. "Integration and Disintegration of EMU Government Bond Markets," Econometrics, MDPI, vol. 9(1), pages 1-17, March.
    6. Leonardo Rocha Souza, 2005. "A Note On Chambers'S "Long Memory And Aggregation In Macroeconomic Time Series"," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 46(3), pages 1059-1062, August.
    7. Robinson Kruse & Christian Leschinski & Michael Will, 2016. "Comparing Predictive Accuracy under Long Memory - With an Application to Volatility Forecasting," CREATES Research Papers 2016-17, Department of Economics and Business Economics, Aarhus University.
    8. Man Kasing, 2010. "Extended Fractional Gaussian Noise and Simple ARFIMA Approximations," Journal of Time Series Econometrics, De Gruyter, vol. 2(1), pages 1-26, September.
    9. Katsumi Shimotsu, 2006. "Simple (but Effective) Tests Of Long Memory Versus Structural Breaks," Working Paper 1101, Economics Department, Queen's University.
    10. Chevillon, Guillaume & Mavroeidis, Sophocles, 2011. "Learning generates Long Memory," ESSEC Working Papers WP1113, ESSEC Research Center, ESSEC Business School.
    11. Christian Fischer & Luis Gil-Alana, 2009. "The nature of the relationship between international tourism and international trade: the case of German imports of Spanish wine," Applied Economics, Taylor & Francis Journals, vol. 41(11), pages 1345-1359.
    12. Souza, Leonardo R. & Smith, Jeremy, 2002. "Bias in the memory parameter for different sampling rates," International Journal of Forecasting, Elsevier, vol. 18(2), pages 299-313.
    13. Luis A. Gil-Alana, 2004. "Modelling the Japanese Exchange Rate in Terms of I(d) Statistical Models with Parametric and Semiparametric Techniques," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 3(2), pages 123-138, August.
    14. Davidson James & Rambaccussing Dooruj, 2015. "A Test of the Long Memory Hypothesis Based on Self-Similarity," Journal of Time Series Econometrics, De Gruyter, vol. 7(2), pages 115-141, July.
    15. L.A. Gil‐Alana, 2006. "Fractional integration in daily stock market indexes," Review of Financial Economics, John Wiley & Sons, vol. 15(1), pages 28-48.
    16. L.A. Gil-Alana & G.M. caporale, 2004. "Long-run and Cyclical Dynamics in the US Stock Market," Econometric Society 2004 Latin American Meetings 344, Econometric Society.
    17. Leonardo Rocha Souza, 2007. "Temporal Aggregation and Bandwidth selection in estimating long memory," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(5), pages 701-722, September.
    18. Taner Yigit, 2007. "Inflation Targeting : An Indirect Approach to Assess the Direct Impact," Working Papers 0706, Department of Economics, Bilkent University.
    19. Cuestas Juan Carlos & Gil-Alana Luis Alberiko, 2016. "Testing for long memory in the presence of non-linear deterministic trends with Chebyshev polynomials," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(1), pages 57-74, February.
    20. Robinson, Peter, 2019. "Spatial long memory," LSE Research Online Documents on Economics 102182, London School of Economics and Political Science, LSE Library.
    21. Morana, Claudio & Beltratti, Andrea, 2004. "Structural change and long-range dependence in volatility of exchange rates: either, neither or both?," Journal of Empirical Finance, Elsevier, vol. 11(5), pages 629-658, December.
    22. Juncal Cunado & Luis A. Gil-Alana & Fernando Pérez de Gracia, 2006. "Additional Empirical Evidence on Real Convergence: A Fractionally Integrated Approach," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 142(1), pages 67-91, April.
    23. Karim M. Abadir & Gabriel Talmain, 2012. "Beyond Co-Integration: Modelling Co-Movements in Macro finance," Working Paper series 25_12, Rimini Centre for Economic Analysis.
    24. Leschinski, Christian, 2017. "On the memory of products of long range dependent time series," Economics Letters, Elsevier, vol. 153(C), pages 72-76.
    25. Chevillon, G. & Hecq, A.W. & Laurent, S.F.J.A., 2015. "Long memory through marginalization of large systems and hidden cross-section dependence," Research Memorandum 014, Maastricht University, Graduate School of Business and Economics (GSBE).
    26. Manmohan S. Kumar & Tatsuyoshi Okimoto, 2007. "Dynamics of Persistence in International Inflation Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(6), pages 1457-1479, September.
    27. Susanne M. Schennach, 2013. "Long memory via networking," CeMMAP working papers CWP13/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    28. Souza, Leonardo Rocha, 2003. "The aliasing effect, the Fejer Kernel and temporally aggregated long memory processes," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 470, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    29. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2009. "Long Memory in US Real Output per Capita," Discussion Papers of DIW Berlin 891, DIW Berlin, German Institute for Economic Research.
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    63. Chevillon, Guillaume & Mavroeidis, Sophocles, 2017. "Learning can generate long memory," Journal of Econometrics, Elsevier, vol. 198(1), pages 1-9.
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    1. Lautier, Delphine & Raynaud, Franck, 2011. "Statistical properties of derivatives: A journey in term structures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 2009-2019.
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    78. Kleppe, Tore Selland & Oglend, Atle, 2017. "Estimating the competitive storage model: A simulated likelihood approach," Econometrics and Statistics, Elsevier, vol. 4(C), pages 39-56.
    79. Delphine Lautier & Yves Simon, 2004. "La volatilité des prix des matières premières," Revue d'Économie Financière, Programme National Persée, vol. 74(1), pages 45-84.
    80. Gleich, Benedikt & Achzet, Benjamin & Mayer, Herbert & Rathgeber, Andreas, 2013. "An empirical approach to determine specific weights of driving factors for the price of commodities—A contribution to the measurement of the economic scarcity of minerals and metals," Resources Policy, Elsevier, vol. 38(3), pages 350-362.
    81. Chatrath, Arjun & Adrangi, Bahram & Dhanda, Kanwalroop Kathy, 2002. "Are commodity prices chaotic?," Agricultural Economics, Blackwell, vol. 27(2), pages 123-137, August.
    82. He, Xue-Zhong & Westerhoff, Frank H., 2005. "Commodity markets, price limiters and speculative price dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 29(9), pages 1577-1596, September.
    83. Wang, Shu & Zhou, Baicheng & Gao, Tianshu, 2023. "Speculation or actual demand? The return spillover effect between stock and commodity markets," Journal of Commodity Markets, Elsevier, vol. 29(C).
    84. Mu, Xiaoyi, 2007. "Weather, storage, and natural gas price dynamics: Fundamentals and volatility," Energy Economics, Elsevier, vol. 29(1), pages 46-63, January.
    85. Jin, Hyun Joung & Frechette, Darren L., 2002. "Fractal Geometry In Agricultural Cash Price Dynamics," 2002 Annual meeting, July 28-31, Long Beach, CA 19696, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    86. Bu, Hui, 2014. "Effect of inventory announcements on crude oil price volatility," Energy Economics, Elsevier, vol. 46(C), pages 485-494.
    87. Chiou Wei, Song Zan & Zhu, Zhen, 2006. "Commodity convenience yield and risk premium determination: The case of the U.S. natural gas market," Energy Economics, Elsevier, vol. 28(4), pages 523-534, July.
    88. Ye, Michael & Zyren, John & Shore, Joanne, 2006. "Forecasting short-run crude oil price using high- and low-inventory variables," Energy Policy, Elsevier, vol. 34(17), pages 2736-2743, November.
    89. Chaudhry, Muhammad Imran & Katchova, Ani & Miranda, Mario Javier, 2016. "Examining pricing mechanics in the poultry value chain - empirical evidence from Pakistan," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235953, Agricultural and Applied Economics Association.
    90. Song-Zan Chiou-Wei & Sheng-Hung Chen & Wei-Hung Chen, 2023. "Asymmetric Effects of Prices and Storage on Rig Counts: Evidence from the US Natural Gas and Crude Oil Markets," Energies, MDPI, vol. 16(15), pages 1-25, August.
    91. Tomek, William G., 2000. "Commodity Prices Revisited," Staff Papers 121146, Cornell University, Department of Applied Economics and Management.
    92. Tomek, William G. & Peterson, Hikaru Hanawa, 2000. "Risk Management in Agricultural Markets: A Survey," Staff Papers 121140, Cornell University, Department of Applied Economics and Management.
    93. Chiou-Wei, Song-Zan & Chen, Sheng-Hung & Zhu, Zhen, 2020. "Natural gas price, market fundamentals and hedging effectiveness," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 321-337.
    94. Marvasti, Akbar & Lamberte, Antonio, 2016. "Commodity price volatility under regulatory changes and disaster," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 355-361.
    95. Lewis Evans & Graeme Guthrie, 2009. "How Options Provided by Storage Affect Electricity Prices," Southern Economic Journal, John Wiley & Sons, vol. 75(3), pages 681-702, January.
    96. Severin Borenstein & Meghan Busse & Ryan Kellogg, 2007. "Principal-agent Incentives, Excess Caution, and Market Inefficiency: Evidence From Utility Regulation," NBER Working Papers 13679, National Bureau of Economic Research, Inc.
    97. Delphine Lautier & Franck Raynaud, 2014. "Information Flows in the term structure of commodity prices," Post-Print hal-01655842, HAL.
    98. Hu, Min & Zhang, Dayong & Ji, Qiang & Wei, Lijian, 2020. "Macro factors and the realized volatility of commodities: A dynamic network analysis," Resources Policy, Elsevier, vol. 68(C).
    99. Hélyette Geman & Vu-Nhat Nguyen, 2005. "Soybean Inventory and Forward Curve Dynamics," Management Science, INFORMS, vol. 51(7), pages 1076-1091, July.
    100. Tomek, William G., 2000. "Commodity Prices Revisited," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 29(2), pages 1-13, October.
    101. Frode Brevik & Axel Kind, 2004. "What is going on in the oil market?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 18(4), pages 442-457, December.
    102. Ivar Ekeland & Delphine Lautier & Bertrand Villeneuve, 2013. "A simple equilibrium model for a commodity market with spot trades and futures contracts," Post-Print hal-01655807, HAL.

Articles

  1. Chambers, Marcus J., 2020. "Frequency domain estimation of cointegrating vectors with mixed frequency and mixed sample data," Journal of Econometrics, Elsevier, vol. 217(1), pages 140-160.
    See citations under working paper version above.
  2. Marcus J. Chambers & A. M. Robert Taylor, 2020. "Deterministic Parameter Change Models in Continuous and Discrete Time," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(1), pages 134-145, January.
    See citations under working paper version above.
  3. Marcus J. Chambers, 2019. "Frequency Domain Estimation of Continuous Time Cointegrated Models with Mixed Frequency and Mixed Sample Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 40(6), pages 887-913, November.

    Cited by:

    1. Chambers, Marcus J., 2020. "Frequency domain estimation of cointegrating vectors with mixed frequency and mixed sample data," Journal of Econometrics, Elsevier, vol. 217(1), pages 140-160.

  4. Marcus J. Chambers & Maria Kyriacou, 2018. "Jackknife Bias Reduction in the Presence of a Near-Unit Root," Econometrics, MDPI, vol. 6(1), pages 1-28, March.
    See citations under working paper version above.
  5. Thornton, Michael A. & Chambers, Marcus J., 2017. "Continuous time ARMA processes: Discrete time representation and likelihood evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 48-65.
    See citations under working paper version above.
  6. 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.

    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. 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.

  7. Chambers, Marcus J., 2016. "The estimation of continuous time models with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 390-404.
    See citations under working paper version above.
  8. Marcus J. Chambers, 2015. "A Jackknife Correction to a Test for Cointegration Rank," Econometrics, MDPI, vol. 3(2), pages 1-21, May.

    Cited by:

    1. Chambers, MJ & Kyriacou, M, 2016. "Jackknife Bias Reduction in the Presence of a Near-Unit Root," Economics Discussion Papers 17623, University of Essex, Department of Economics.

  9. Neil Kellard & Denise Osborn & Jerry Coakley & Marcus J. Chambers, 2015. "Testing for a Unit Root in a Near-Integrated Model with Skip-Sampled Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 630-649, September.

    Cited by:

    1. Chambers, MJ, 2016. "The Effects of Sampling Frequency on Detrending Methods for Unit Root Tests," Economics Discussion Papers 16062, University of Essex, Department of Economics.
    2. J. Isaac Miller, 2014. "Simple Robust Tests for the Specification of High-Frequency Predictors of a Low-Frequency Series," Working Papers 1412, Department of Economics, University of Missouri.

  10. Abouwafia, Hashem E. & Chambers, Marcus J., 2015. "Monetary policy, exchange rates and stock prices in the Middle East region," International Review of Financial Analysis, Elsevier, vol. 37(C), pages 14-28.

    Cited by:

    1. Prabheesh, K.P. & Anglingkusumo, Reza & Juhro, Solikin M., 2021. "The dynamics of global financial cycle and domestic economic cycles: Evidence from India and Indonesia," Economic Modelling, Elsevier, vol. 94(C), pages 831-842.
    2. Yang, Sheng-Ping, 2017. "Exchange rate dynamics and stock prices in small open economies: Evidence from Asia-Pacific countries," Pacific-Basin Finance Journal, Elsevier, vol. 46(PB), pages 337-354.
    3. Abdullah M. H. Alharbi, 2023. "Oil Shocks, Monetary Policy, and Stock Returns: A Case of Oil-based Economy," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 56-63, November.
    4. Sakshi Saini & Sanjay Sehgal & Florent Deisting, 2020. "Monetary Policy,Risk Aversion and Uncertainty in an International Context," IEG Working Papers 385, Institute of Economic Growth.
    5. Chikashi Tsuji, 2015. "Exchange Rate Effects on Equity Prices: The Recent Case from Japan," Business and Management Research, Business and Management Research, Sciedu Press, vol. 4(4), pages 1-12, December.
    6. Prabheesh, K.P. & Vidya, C.T., 2018. "Do business cycles, investment-specific technology shocks matter for stock returns?," Economic Modelling, Elsevier, vol. 70(C), pages 511-524.
    7. Yip, Pick Schen & Brooks, Robert & Do, Hung Xuan & Vo, Xuan Vinh, 2022. "What drives cross-market correlations during the United States Q.E.?," International Review of Financial Analysis, Elsevier, vol. 83(C).
    8. Sanjeev Parmanand, 2022. "The impact of Philippine monetary policy on domestic prices and output: evaluating the country’s transmission channels," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 59(1), pages 46-76, June.
    9. Renata Legenzova & Otilija Jurakovaite & Agne Galinskaite, 2017. "The Analysis of Dividend Announcement Impact on Stock Prices of Baltic Companies," Central European Business Review, Prague University of Economics and Business, vol. 2017(1), pages 61-76.
    10. Arash Habibi & Chin Lee, 2019. "Asymmetric Effects of Exchange Rates on Stock Prices in G7 Countries," Capital Markets Review, Malaysian Finance Association, vol. 27(1), pages 19-33.

  11. Marcus J. Chambers, 2015. "The Calculation of Some Limiting Distributions Arising in Near-Integrated Models with GLS Detrending," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(4), pages 562-586, July.
    See citations under working paper version above.
  12. Chambers, Marcus J. & Ercolani, Joanne S. & Taylor, A.M. Robert, 2014. "Testing for seasonal unit roots by frequency domain regression," Journal of Econometrics, Elsevier, vol. 178(P2), pages 243-258.
    See citations under working paper version above.
  13. Chambers, Marcus J. & Kyriacou, Maria, 2013. "Jackknife estimation with a unit root," Statistics & Probability Letters, Elsevier, vol. 83(7), pages 1677-1682.

    Cited by:

    1. Kruse, Yves Robinson & Kaufmann, Hendrik, 2015. "Bias-corrected estimation in mildly explosive autoregressions," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112897, Verein für Socialpolitik / German Economic Association.
    2. Kruse, Robinson & Kaufmann, Hendrik & Wegener, Christoph, 2018. "Bias-corrected estimation for speculative bubbles in stock prices," Economic Modelling, Elsevier, vol. 73(C), pages 354-364.
    3. Chambers, MJ & Kyriacou, M, 2016. "Jackknife Bias Reduction in the Presence of a Near-Unit Root," Economics Discussion Papers 17623, University of Essex, Department of Economics.
    4. Marcus J. Chambers, 2015. "A Jackknife Correction to a Test for Cointegration Rank," Econometrics, MDPI, vol. 3(2), pages 1-21, May.
    5. Chen, Ye & Yu, Jun, 2015. "Optimal jackknife for unit root models," Statistics & Probability Letters, Elsevier, vol. 99(C), pages 135-142.
    6. 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. 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.

    Cited by:

    1. P. Brockwell, 2014. "Recent results in the theory and applications of CARMA processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(4), pages 647-685, August.
    2. Neil Kellard & Denise Osborn & Jerry Coakley & Marcus J. Chambers, 2015. "Testing for a Unit Root in a Near-Integrated Model with Skip-Sampled Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 630-649, September.

  15. Chambers, Marcus J., 2013. "Jackknife estimation of stationary autoregressive models," Journal of Econometrics, Elsevier, vol. 172(1), pages 142-157.
    See citations under working paper version above.
  16. Chambers, Marcus J. & Thornton, Michael A., 2012. "Discrete Time Representation Of Continuous Time Arma Processes," Econometric Theory, Cambridge University Press, vol. 28(1), pages 219-238, February.

    Cited by:

    1. D. Stephen G. Pollock, 2020. "Linear Stochastic Models in Discrete and Continuous Time," Econometrics, MDPI, vol. 8(3), pages 1-22, September.
    2. Fiorentini, Gabriele & Galesi, Alessandro & Sentana, Enrique, 2018. "A spectral EM algorithm for dynamic factor models," Journal of Econometrics, Elsevier, vol. 205(1), pages 249-279.
    3. Chambers, Marcus J., 2016. "The estimation of continuous time models with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 390-404.
    4. 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.
    5. 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.
    6. 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.
    7. Chambers, MJ, 2016. "The Effects of Sampling Frequency on Detrending Methods for Unit Root Tests," Economics Discussion Papers 16062, University of Essex, Department of Economics.
    8. 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.
    9. Neil Kellard & Denise Osborn & Jerry Coakley & Marcus J. Chambers, 2015. "Testing for a Unit Root in a Near-Integrated Model with Skip-Sampled Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 630-649, September.
    10. 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.

  17. Marcus J. Chambers, 2011. "Cointegration and sampling frequency," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 156-185, July.
    See citations under working paper version above.
  18. Chambers, Marcus J., 2009. "Discrete Time Representations Of Cointegrated Continuous Time Models With Mixed Sample Data," Econometric Theory, Cambridge University Press, vol. 25(4), pages 1030-1049, August.

    Cited by:

    1. 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.
    2. Chambers, Marcus J., 2016. "The estimation of continuous time models with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 390-404.
    3. Hernández, Juan R., 2016. "Unit Root Testing in ARMA Models: A Likelihood Ratio Approach," MPRA Paper 100857, University Library of Munich, Germany.
    4. J. Isaac Miller, 2014. "Mixed-frequency Cointegrating Regressions with Parsimonious Distributed Lag Structures," Journal of Financial Econometrics, Oxford University Press, vol. 12(3), pages 584-614.
    5. 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.
    6. 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.
    7. 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.
    8. Hernández Juan R., 2016. "Unit Root Testing in ARMA Models: A Likelihood Ratio Approach," Working Papers 2016-03, Banco de México.
    9. 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.

  19. Chambers, Marcus J., 2008. "Corrigendum to: "Testing for unit roots with flow data and varying sampling frequency" [J. Econom. 119 (1) (2004) 1-18]," Journal of Econometrics, Elsevier, vol. 144(2), pages 524-525, June.

    Cited by:

    1. Chambers, MJ, 2016. "The Effects of Sampling Frequency on Detrending Methods for Unit Root Tests," Economics Discussion Papers 16062, University of Essex, Department of Economics.

  20. Chambers, Marcus J. & Roderick McCrorie, J., 2007. "Frequency domain estimation of temporally aggregated Gaussian cointegrated systems," Journal of Econometrics, Elsevier, vol. 136(1), pages 1-29, January.

    Cited by:

    1. Chambers, Marcus J. & Ercolani, Joanne S. & Taylor, A.M. Robert, 2014. "Testing for seasonal unit roots by frequency domain regression," Journal of Econometrics, Elsevier, vol. 178(P2), pages 243-258.
    2. Chambers, Marcus J., 2016. "The estimation of continuous time models with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 390-404.
    3. Hernández, Juan R., 2016. "Unit Root Testing in ARMA Models: A Likelihood Ratio Approach," MPRA Paper 100857, University Library of Munich, Germany.
    4. 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.
    5. 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.
    6. Hernández Juan R., 2016. "Unit Root Testing in ARMA Models: A Likelihood Ratio Approach," Working Papers 2016-03, Banco de México.
    7. J. Isaac Miller, 2016. "Conditionally Efficient Estimation of Long-Run Relationships Using Mixed-Frequency Time Series," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1142-1171, June.

  21. 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.
    See citations under working paper version above.
  22. Marcus J. Chambers & J. Roderick McCrorie, 2006. "Identification And Estimation Of Exchange Rate Models With Unobservable Fundamentals," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 573-582, May.
    See citations under working paper version above.
  23. Ercolani, Joanne S. & Chambers, Marcus J., 2006. "Estimation Of Differential-Difference Equation Systems With Unknown Lag Parameters," Econometric Theory, Cambridge University Press, vol. 22(3), pages 483-498, June.

    Cited by:

    1. Joanne S. Ercolani, 2014. "Cyclical Activity and Gestation Lags in Investment," Manchester School, University of Manchester, vol. 82(5), pages 620-630, September.
    2. Joanne S. Ercolani, 2007. "Cyclical Trends in Continuous Time Models," Discussion Papers 07-13, Department of Economics, University of Birmingham.
    3. Joanne S. Ercolani, 2010. "On the Asymptotic Properties of a Feasible Estimator of the Continuous Time Long Memory Parameter," Discussion Papers 10-09, Department of Economics, University of Birmingham.

  24. Chambers, Marcus J., 2005. "The purchasing power parity puzzle, temporal aggregation, and half-life estimation," Economics Letters, Elsevier, vol. 86(2), pages 193-198, February.

    Cited by:

    1. Mamingi Nlandu, 2017. "Beauty and Ugliness of Aggregation over Time: A Survey," Review of Economics, De Gruyter, vol. 68(3), pages 205-227, December.
    2. Michael Frömmel & Darko B. Vukovic & Jinyuan Wu, 2022. "The Dollar Exchange Rate, Adjustment to the Purchasing Power Parity, and the Interest Rate Differential," Mathematics, MDPI, vol. 10(23), pages 1-17, November.
    3. Chambers, MJ, 2016. "The Effects of Sampling Frequency on Detrending Methods for Unit Root Tests," Economics Discussion Papers 16062, University of Essex, Department of Economics.
    4. Ca' Zorzi, Michele & Chudik, Alexander, 2013. "Spatial considerations on the PPP debate," Working Paper Series 1534, European Central Bank.
    5. Kenneth W Clements & Yihui Lan & John Roberts, 2007. "Exchange-Rate Economics for the Resources Sector," Economics Discussion / Working Papers 07-13, The University of Western Australia, Department of Economics.
    6. Andres Elberg, 2014. "Temporal Aggregation and Convergence to the Law of One Price: Evidence from Micro Data," Working Papers 53, Facultad de Economía y Empresa, Universidad Diego Portales.
    7. Seong, Byeongchan & Mahbub Morshed, A.K.M. & Ahn, Sung K., 2006. "Additional sources of bias in half-life estimation," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 2056-2064, December.

  25. Chambers, Marcus J., 2004. "Testing for unit roots with flow data and varying sampling frequency," Journal of Econometrics, Elsevier, vol. 119(1), pages 1-18, March.
    See citations under working paper version above.
  26. Chambers, Marcus J., 2003. "The Asymptotic Efficiency Of Cointegration Estimators Under Temporal Aggregation," Econometric Theory, Cambridge University Press, vol. 19(1), pages 49-77, February.

    Cited by:

    1. Philipp Gersing & Leopold Soegner & Manfred Deistler, 2022. "Retrieval from Mixed Sampling Frequency: Generic Identifiability in the Unit Root VAR," Papers 2204.05952, arXiv.org, revised Jul 2023.
    2. Antonio Diez de los Rios & Enrique Sentana, 2011. "Testing Uncovered Interest Parity: A Continuous‐Time Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(4), pages 1215-1251, November.
    3. Hecq, A.W. & Götz, T.B. & Urbain, J.R.Y.J., 2012. "Forecasting Mixed Frequency Time Series with ECM-MIDAS Models," Research Memorandum 012, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    4. Eric Ghysels & J. Isaac Miller, 2014. "On the Size Distortion from Linearly Interpolating Low-frequency Series for Cointegration Tests," Working Papers 1403, Department of Economics, University of Missouri.
    5. Ghysels, Eric & Miller, J. Isaac, 2013. "Testing for Cointegration with Temporally Aggregated and Mixed-frequency Time Series," CEPR Discussion Papers 9654, C.E.P.R. Discussion Papers.
    6. Chambers, Marcus J., 2020. "Frequency domain estimation of cointegrating vectors with mixed frequency and mixed sample data," Journal of Econometrics, Elsevier, vol. 217(1), pages 140-160.
    7. Dierk Herzery & Holger Strulik & Sebastian Vollmer, 2010. "The Long-run Determinants of Fertility: One Century of Demographic Change 1900-1999," PGDA Working Papers 6310, Program on the Global Demography of Aging.
    8. Chambers, M.J. & McCrorie, J.R., 2004. "Frequency Domain Gaussian Estimation of Temporally Aggregated Cointegrated Systems," Other publications TiSEM 0d3ed468-36ef-4baf-8339-8, Tilburg University, School of Economics and Management.
    9. J. Isaac Miller, 2018. "Testing Cointegrating Relationships Using Irregular and Non-Contemporaneous Series with an Application to Paleoclimate Data," Working Papers 1809, Department of Economics, University of Missouri.
    10. J. Isaac Miller, 2014. "Mixed-frequency Cointegrating Regressions with Parsimonious Distributed Lag Structures," Journal of Financial Econometrics, Oxford University Press, vol. 12(3), pages 584-614.
    11. Chambers, MJ, 2016. "The Effects of Sampling Frequency on Detrending Methods for Unit Root Tests," Economics Discussion Papers 16062, University of Essex, Department of Economics.
    12. J. Isaac Miller & Xi Wang, 2016. "Implementing Residual-Based KPSS Tests for Cointegration with Data Subject to Temporal Aggregation and Mixed Sampling Frequencies," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(6), pages 810-824, November.
    13. Chambers, Marcus J. & Roderick McCrorie, J., 2007. "Frequency domain estimation of temporally aggregated Gaussian cointegrated systems," Journal of Econometrics, Elsevier, vol. 136(1), pages 1-29, January.

  27. Chambers, Marcus J. & McGarry, Joanne S., 2002. "Modeling Cyclical Behavior With Differential-Difference Equations In An Unobserved Components Framework," Econometric Theory, Cambridge University Press, vol. 18(2), pages 387-419, April.

    Cited by:

    1. Eliana González & Luis F. Melo & Luis E. Rojas & Brayan Rojas, 2010. "Estimations of the natural rate of interest in Colombia," Borradores de Economia 626, Banco de la Republica de Colombia.
    2. Joanne S. Ercolani, 2014. "Cyclical Activity and Gestation Lags in Investment," Manchester School, University of Manchester, vol. 82(5), pages 620-630, September.
    3. 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.).
    4. Webel, Karsten, 2022. "A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series," Discussion Papers 31/2022, Deutsche Bundesbank.
    5. Joanne S. Ercolani, 2007. "Cyclical Trends in Continuous Time Models," Discussion Papers 07-13, Department of Economics, University of Birmingham.
    6. Joanne S. Ercolani, 2010. "On the Asymptotic Properties of a Feasible Estimator of the Continuous Time Long Memory Parameter," Discussion Papers 10-09, Department of Economics, University of Birmingham.

  28. Chambers, Marcus J., 2001. "Temporal Aggregation And The Finite Sample Performance Of Spectral Regression Estimators In Cointegrated Systems," Econometric Theory, Cambridge University Press, vol. 17(3), pages 591-607, June.

    Cited by:

    1. Marcus J. Chambers, 2011. "Cointegration and sampling frequency," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 156-185, July.
    2. 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.
    3. Chambers, Marcus J. & Roderick McCrorie, J., 2007. "Frequency domain estimation of temporally aggregated Gaussian cointegrated systems," Journal of Econometrics, Elsevier, vol. 136(1), pages 1-29, January.

  29. 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.

    Cited by:

    1. D. Stephen G. Pollock, 2020. "Linear Stochastic Models in Discrete and Continuous Time," Econometrics, MDPI, vol. 8(3), pages 1-22, September.
    2. Marcus J. Chambers, 2011. "Cointegration and sampling frequency," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 156-185, July.
    3. Tilak Abeysinghe & Gulasekaran Rajaguru, 2004. "Temporal aggregation, causality distortions and a sign rule," Econometric Society 2004 Australasian Meetings 73, Econometric Society.
    4. Chambers, M.J. & McCrorie, J.R., 2004. "Frequency Domain Gaussian Estimation of Temporally Aggregated Cointegrated Systems," Other publications TiSEM 0d3ed468-36ef-4baf-8339-8, Tilburg University, School of Economics and Management.
    5. 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.
    6. 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.
    7. 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.
    8. Theodore Simos, 2008. "The exact discrete model of a system of linear stochastic differential equations driven by fractional noise," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(6), pages 1019-1031, November.
    9. J. McCrorie, 2002. "The Likelihood of the Parameters of a Continuous Time Vector Autoregressive Model," Statistical Inference for Stochastic Processes, Springer, vol. 5(3), pages 273-286, October.
    10. 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.
    11. 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.
    12. 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.
    13. Chen, Baoline & Zadrozny, Peter A., 2001. "Analytic derivatives of the matrix exponential for estimation of linear continuous-time models1," Journal of Economic Dynamics and Control, Elsevier, vol. 25(12), pages 1867-1879, December.
    14. 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.
    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. Arie ten Cate, 2004. "Refinement of the partial adjustment model using continuous-time econometrics," CPB Discussion Paper 41, CPB Netherlands Bureau for Economic Policy Analysis.
    17. Chambers, Marcus J. & Roderick McCrorie, J., 2007. "Frequency domain estimation of temporally aggregated Gaussian cointegrated systems," Journal of Econometrics, Elsevier, vol. 136(1), pages 1-29, January.

  30. Marcus J. Chambers & Roy E. Bailey, 1999. "A Statistical Analysis of Wheat Price Fluctuations in England: 1685–1850," Journal of Agricultural Economics, Wiley Blackwell, vol. 50(3), pages 564-588, September.

    Cited by:

    1. David Stead, 2004. "Risk and risk management in English agriculture, c. 1750–1850," Economic History Review, Economic History Society, vol. 57(2), pages 334-361, May.

  31. Marcus J. Chambers, 1999. "A Note on Modelling Seasonal Processes in Continuous Time," Journal of Time Series Analysis, Wiley Blackwell, vol. 20(2), pages 139-143, March.

    Cited by:

    1. Webel, Karsten, 2022. "A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series," Discussion Papers 31/2022, Deutsche Bundesbank.

  32. Chambers, Marcus J, 1998. "Long Memory and Aggregation in Macroeconomic Time Series," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 1053-1072, November.
    See citations under working paper version above.
  33. Chambers, Marcus J., 1998. "The estimation of systems of joint differential-difference equations," Journal of Econometrics, Elsevier, vol. 85(1), pages 1-31, July.
    See citations under working paper version above.
  34. Roy E. Bailey & Marcus J. Chambers, 1998. "The impact of real wage and mortality fluctuations on fertility and nuptiality in precensus England," Journal of Population Economics, Springer;European Society for Population Economics, vol. 11(3), pages 413-434.

    Cited by:

    1. Peter Grajzl & Peter Murrell, 2022. "Did Caselaw Foster England’s Economic Development during the Industrial Revolution? Data and Evidence," CESifo Working Paper Series 10088, CESifo.
    2. Francisco Climent Diranzo & Robert Meneu Gaya, "undated". "Relaciones de equilibrio entre demografía y crecimiento económico en Espana," Studies on the Spanish Economy 163, FEDEA.
    3. Marcus J. Chambers & Roy E. Bailey, 1999. "A Statistical Analysis of Wheat Price Fluctuations in England: 1685–1850," Journal of Agricultural Economics, Wiley Blackwell, vol. 50(3), pages 564-588, September.
    4. George Hondroyiannis, 2010. "Fertility Determinants and Economic Uncertainty: An Assessment Using European Panel Data," Journal of Family and Economic Issues, Springer, vol. 31(1), pages 33-50, March.
    5. Alam, Shamma Adeeb & Pörtner, Claus C., 2018. "Income shocks, contraceptive use, and timing of fertility," Journal of Development Economics, Elsevier, vol. 131(C), pages 96-103.

  35. Marcus Chambers & K. Ben Nowman, 1997. "Forecasting with the almost ideal demand system: evidence from some alternative dynamic specifications," Applied Economics, Taylor & Francis Journals, vol. 29(7), pages 935-943.

    Cited by:

    1. Chang, C-L. & Khamkaew, T. & McAleer, M.J., 2010. "Estimating Price Effects in an Almost Ideal Demand Model of Outbound Thai Tourism to East Asia," Econometric Institute Research Papers EI 2010-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Balcombe, Kelvin & Bailey, Alastair, 2006. "Bayesian inference of a smooth transition dynamic almost ideal model of food demand in the US," MPRA Paper 17305, University Library of Munich, Germany.
    3. Pesaran,H.M. & Shin,Y., 1995. "Long-Run Structural Modelling," Cambridge Working Papers in Economics 9419, Faculty of Economics, University of Cambridge.
    4. Dogbe, Wisdom, 2022. "Implications of increasing fruits and vegetable consumption in Scotland," 96th Annual Conference, April 4-6, 2022, K U Leuven, Belgium 321232, Agricultural Economics Society - AES.
    5. Chang, Hui-Shung (Christie) & Bettington, Nicholas, 2001. "Demand for Wine in Australia: Systems Versus Single Equation Approach," Working Papers 12923, University of New England, School of Economics.
    6. Wang, Zijun & Bessler, David A, 2002. "The Homogeneity Restriction and Forecasting Performance of VAR-Type Demand Systems: An Empirical Examination of US Meat Consumption," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(3), pages 193-206, April.
    7. Li, Gang & Song, Haiyan & Witt, Stephen F., 2006. "Time varying parameter and fixed parameter linear AIDS: An application to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 22(1), pages 57-71.
    8. Erkan Erdil, 2006. "Demand systems for agricultural products in OECD countries," Applied Economics Letters, Taylor & Francis Journals, vol. 13(3), pages 163-169.
    9. Chang, Hui-Shung (Christie), 2000. "An econometric analysis of the competitive position of Australian cotton in the Japanese market," Working Papers 12940, University of New England, School of Economics.
    10. Byers, S. L. & Nowman, K. B., 1998. "Forecasting U.K. and U.S. interest rates using continuous time term structure models," International Review of Financial Analysis, Elsevier, vol. 7(3), pages 191-206.
    11. Paul Preckel & J. A. L. Cranfield & Thomas Hertel, 2010. "A modified, implicit, directly additive demand system," Applied Economics, Taylor & Francis Journals, vol. 42(2), pages 143-155.
    12. Chang, Hui-Shung (Christie) & Nguyen, Chi, 1997. "The elasticity of demand for Australian cotton in Japan," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 46(1), pages 1-15.
    13. Chang, Hui-Shung & Griffith, Garry & Bettington, Nicholas, 2002. "The Demand for Wine in Australia Using a Systems Approach: Industry Implications," Australasian Agribusiness Review, University of Melbourne, Department of Agriculture and Food Systems, vol. 10, pages 1-12, September.
    14. J. M. Gil & B. Dhehibi & M. Ben Kaabia & A. M. Angulo, 2004. "Non-stationarity and the import demand for virgin olive oil in the European Union," Applied Economics, Taylor & Francis Journals, vol. 36(16), pages 1859-1869.
    15. Tonsor, Glynn T. & Marsh, Thomas L., 2005. "Comparing Heterogeneous Consumption in US and Japanese Meat and Fish Demand," 2005 Annual meeting, July 24-27, Providence, RI 19567, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    16. Athanasopoulos, George & Deng, Minfeng & Li, Gang & Song, Haiyan, 2014. "Modelling substitution between domestic and outbound tourism in Australia: A system-of-equations approach," Tourism Management, Elsevier, vol. 45(C), pages 159-170.

  36. Chambers, Marcus J., 1996. "Fractional integration, trend stationarity and difference stationarity Evidence from some U.K. macroeconomic time series," Economics Letters, Elsevier, vol. 50(1), pages 19-24, January.

    Cited by:

    1. Marmol, Francesc, 1997. "Fractional integration versus trend stationary in time series analysis," DES - Working Papers. Statistics and Econometrics. WS 10498, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Marmol, Francesc & Velasco, Carlos, 2002. "Trend stationarity versus long-range dependence in time series analysis," Journal of Econometrics, Elsevier, vol. 108(1), pages 25-42, May.

  37. Chambers, Marcus J., 1996. "The Estimation of Continuous Parameter Long-Memory Time Series Models," Econometric Theory, Cambridge University Press, vol. 12(2), pages 374-390, June.

    Cited by:

    1. Leonenko, Nikolai N. & Sharapov, Michail M. & El-Bassiouny, Ahmed H., 2000. "On the exactness of normal approximation of LSE of regression coefficient of long-memory random fields," Statistics & Probability Letters, Elsevier, vol. 48(2), pages 121-130, June.
    2. Souza, Leonardo R. & Smith, Jeremy, 2002. "Bias in the memory parameter for different sampling rates," International Journal of Forecasting, Elsevier, vol. 18(2), pages 299-313.
    3. Henghsiu Tsai & K. S. Chan, 2005. "Quasi‐Maximum Likelihood Estimation for a Class of Continuous‐time Long‐memory Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(5), pages 691-713, September.
    4. Uwe Hassler, 2011. "Estimation of fractional integration under temporal aggregation," Post-Print hal-00815563, HAL.
    5. Eduardo Rossi & Paolo Santucci de Magistris, 2011. "Estimation of long memory in integrated variance," CREATES Research Papers 2011-11, Department of Economics and Business Economics, Aarhus University.
    6. Theodore Simos & Mike Tsionas, 2018. "Bayesian inference of the fractional Ornstein–Uhlenbeck process under a flow sampling scheme," Computational Statistics, Springer, vol. 33(4), pages 1687-1713, December.
    7. Henghsiu Tsai & K. S. Chan, 2005. "Temporal Aggregation of Stationary And Nonstationary Discrete‐Time Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(4), pages 613-624, July.
    8. Comte, F., 1998. "Discrete and continuous time cointegration," Journal of Econometrics, Elsevier, vol. 88(2), pages 207-226, November.
    9. Theodore Simos, 2008. "The exact discrete model of a system of linear stochastic differential equations driven by fractional noise," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(6), pages 1019-1031, November.
    10. Wymer Clifford R., 2012. "Continuous-Tme Econometrics of Structural Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(2), pages 1-28, April.
    11. Anne Philippe & Caroline Robet & Marie-Claude Viano, 2021. "Random discretization of stationary continuous time processes," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(3), pages 375-400, April.
    12. Joanne S. Ercolani, 2010. "On the Asymptotic Properties of a Feasible Estimator of the Continuous Time Long Memory Parameter," Discussion Papers 10-09, Department of Economics, University of Birmingham.

  38. Chambers, Marcus J & Bailey, Roy E, 1996. "A Theory of Commodity Price Fluctuations," Journal of Political Economy, University of Chicago Press, vol. 104(5), pages 924-957, October.
    See citations under working paper version above.
  39. R. E. Bailey & M. J. Chambers, 1993. "Long‐Term Demographic Interactions in Precensus England," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 156(3), pages 339-362, May.

    Cited by:

    1. Robert McNown, 2003. "A Cointegration Model of Age‐Specific Fertility and Female Labor Supply in the United States," Southern Economic Journal, John Wiley & Sons, vol. 70(2), pages 344-358, October.
    2. Maja Pedersen & Claudia Riani & Paul Sharp, 2021. "Malthus in preindustrial Northern Italy?," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(3), pages 1003-1026, July.
    3. Maja Pedersen & Claudia Riani & Paul Sharp, 2019. "Malthus in Pre-industrial Northern Italy? A Cointegration Approach," Working Papers 0156, European Historical Economics Society (EHES).
    4. Madsen, Jakob B. & Robertson, Peter E. & Ye, Longfeng, 2019. "Malthus was right: Explaining a millennium of stagnation," European Economic Review, Elsevier, vol. 118(C), pages 51-68.
    5. Nicholas Crafts & Terence C Mills, 2022. "Considering the Counterfactual: Real Wages in the First Industrial Revolution," The Economic Journal, Royal Economic Society, vol. 132(645), pages 1994-2006.
    6. Ulrich Pfister & Georg Fertig, 2020. "From Malthusian Disequilibrium to the Post-Malthusian Era: The Evolution of the Preventive and Positive Checks in Germany, 1730–1870," Demography, Springer;Population Association of America (PAA), vol. 57(3), pages 1145-1170, June.
    7. Crafts, Nicholas & Mills, Terence, 2020. "The Race between Population and Technology: Real wages in the First Industrial Revolution," CEPR Discussion Papers 15174, C.E.P.R. Discussion Papers.
    8. Peter Grajzl & Peter Murrell, 2023. "Of families and inheritance: law and development in England before the Industrial Revolution," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 17(3), pages 387-432, September.

  40. Chambers, Marcus J, 1992. "Estimation of a Continuous-Time Dynamic Demand System," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(1), pages 53-64, Jan.-Marc.

    Cited by:

    1. Anton Bondarev, 2008. "Evaluation of Demand Functions for foodstuffs in Russian Economy in 1999–2004," Research Paper Series, Gaidar Institute for Economic Policy, issue 118P, pages 166-166.
    2. 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.

  41. Chambers, Marcus J., 1991. "Discrete Models for Estimating General Linear Continuous Time Systems," Econometric Theory, Cambridge University Press, vol. 7(4), pages 531-542, December.

    Cited by:

    1. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," CIRANO Working Papers 2004s-20, CIRANO.
    2. Byers, S. L. & Nowman, K. B., 1998. "Forecasting U.K. and U.S. interest rates using continuous time term structure models," International Review of Financial Analysis, Elsevier, vol. 7(3), pages 191-206.
    3. 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.

  42. Chambers, Marcus J., 1990. "Forecasting with demand systems : A comparative study," Journal of Econometrics, Elsevier, vol. 44(3), pages 363-376, June.

    Cited by:

    1. Toshinobu Matsuda, 2006. "Linear approximations to the quadratic almost ideal demand system," Empirical Economics, Springer, vol. 31(3), pages 663-675, September.
    2. Cranfield, J. A. L. & Pellow, Scott, 2004. "The role of global vs. local negativity in functional form selection: an application to Canadian consumer demands," Economic Modelling, Elsevier, vol. 21(2), pages 345-360, March.
    3. Wang, Zijun & Bessler, David A, 2002. "The Homogeneity Restriction and Forecasting Performance of VAR-Type Demand Systems: An Empirical Examination of US Meat Consumption," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(3), pages 193-206, April.
    4. Tridimas, George, 2000. "The analysis of consumer demand in Greece. Model selection and dynamic specification," Economic Modelling, Elsevier, vol. 17(4), pages 455-471, December.
    5. Li, Gang & Song, Haiyan & Witt, Stephen F., 2006. "Time varying parameter and fixed parameter linear AIDS: An application to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 22(1), pages 57-71.
    6. Rapanos, Vassilis T. & Polemis, Michael L., 2006. "The structure of residential energy demand in Greece," Energy Policy, Elsevier, vol. 34(17), pages 3137-3143, November.
    7. Shashika D. Rathnayaka & Saroja Selvanathan & E. A. Selvanathan, 2021. "Demand for animal‐derived food in selected Asian countries: A system‐wide analysis," Agricultural Economics, International Association of Agricultural Economists, vol. 52(1), pages 97-122, January.
    8. Arsenault, E. & Bernard, J. -T. & Carr, C. W. & Genest-Laplante, E., 1995. "A total energy demand model of Quebec : Forecasting properties," Energy Economics, Elsevier, vol. 17(2), pages 163-171, April.
    9. Mu, Jianhong E. & McCarl, Bruce A. & Bessler, David A., 2013. "Impacts of BSE and Avian Influenza on U.S. Meat Demand," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150392, Agricultural and Applied Economics Association.
    10. Chambers, Marcus J, 1992. "Estimation of a Continuous-Time Dynamic Demand System," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(1), pages 53-64, Jan.-Marc.
    11. Kostas Bithas & Chrysostomos Stoforos, 2006. "Estimating Urban Residential Water Demand Determinants and Forecasting Water Demand for Athens Metropolitan Area, 2000-2010," South-Eastern Europe Journal of Economics, Association of Economic Universities of South and Eastern Europe and the Black Sea Region, vol. 4(1), pages 47-59.
    12. Ingco, Merlinda D., 1991. "Is rice becoming an inferior good? Food demand in the Philippines," Policy Research Working Paper Series 722, The World Bank.
    13. Toshinobu Matsuda, 2007. "Linearizing the inverse quadratic almost ideal demand system," Applied Economics, Taylor & Francis Journals, vol. 39(3), pages 381-396.
    14. Zijun Wang & David A. Bessler, 2003. "Forecast evaluations in meat demand analysis," Agribusiness, John Wiley & Sons, Ltd., vol. 19(4), pages 505-523.

Chapters

  1. 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.

    Cited by:

    1. Du, Yingxin & Ju, Jiandong & Ramirez, Carlos D. & Yao, Xi, 2017. "Bilateral trade and shocks in political relations: Evidence from China and some of its major trading partners, 1990–2013," Journal of International Economics, Elsevier, vol. 108(C), pages 211-225.
    2. Bartsch, Zachary, 2019. "Economic policy uncertainty and dollar-pound exchange rate return volatility," Journal of International Money and Finance, Elsevier, vol. 98(C), pages 1-1.

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