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James Durbin

(deceased)

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.

Working papers

  1. J. Durbin and S.J. Koopman, 2001. "An efficient and simple simulation smoother for state space time series analysis," Computing in Economics and Finance 2001 52, Society for Computational Economics.

    Cited by:

    1. Bańbura, Marta & Giannone, Domenico & Lenza, Michele, 2015. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," International Journal of Forecasting, Elsevier, vol. 31(3), pages 739-756.
    2. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 29, pages 107-142, November.
    3. Michael Artis & Massimiliano Marcellino & Tommaso Proietti, 2004. "Characterising the Business Cycle for Accession Countries," Econometrics 0403006, University Library of Munich, Germany.
    4. Guglielmo Maria Caporale & Abdurrahman Nazif Catik & Gül Serife Huyugüzel Kisla & Mohamad Husam Helmi & Coskun Akdeniz, 2021. "Oil Prices, Exchange Rates and Sectoral Stock Returns in the BRICS-T Countries: A Time-Varying Approach," CESifo Working Paper Series 9322, CESifo.
    5. Domenico Giannone & Michele Lenza & Lucrezia Reichlin, 2019. "Money, Credit, Monetary Policy, and the Business Cycle in the Euro Area: What Has Changed Since the Crisis?," International Journal of Central Banking, International Journal of Central Banking, vol. 15(5), pages 137-173, December.
    6. C. Glocker & G. Sestieri & P. Towbin, 2017. "Time-varying fiscal spending multipliers in the UK," Working papers 643, Banque de France.
    7. Nazif Çatık, Abdurrahman & Huyugüzel Kışla, Gül & Akdeni̇z, Coşkun, 2020. "Time-varying impact of oil prices on sectoral stock returns: Evidence from Turkey," Resources Policy, Elsevier, vol. 69(C).

  2. 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," Discussion Paper 1998-142, Tilburg University, Center for Economic Research.

    Cited by:

    1. Marimoutou, Vêlayoudom & Soury, Manel, 2015. "Energy markets and CO2 emissions: Analysis by stochastic copula autoregressive model," Energy, Elsevier, vol. 88(C), pages 417-429.
    2. Siem Jan Koopman & Kai Ming Lee, 0000. "Seasonality with Trend and Cycle Interactions in Unobserved Components Models," Tinbergen Institute Discussion Papers 08-028/4, Tinbergen Institute.
    3. 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.
    4. Håvard Rue & Ingelin Steinsland & Sveinung Erland, 2004. "Approximating hidden Gaussian Markov random fields," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(4), pages 877-892, November.
    5. Tsionas, Mike, 2012. "Simple techniques for likelihood analysis of univariate and multivariate stable distributions: with extensions to multivariate stochastic volatility and dynamic factor models," MPRA Paper 40966, University Library of Munich, Germany, revised 20 Aug 2012.
    6. Christian Brinch, 2012. "Efficient simulated maximum likelihood estimation through explicitly parameter dependent importance sampling," Computational Statistics, Springer, vol. 27(1), pages 13-28, March.
    7. Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
    8. Dethlefsen, Claus & Lundbye-Christensen, Søren, 2006. "Formulating State Space Models in R with Focus on Longitudinal Regression Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 16(i01).
    9. Jun Yu & Zhenlin Yang & Xibin Zhang, 2002. "A Class of Nonlinear Stochastic Volatility Models and Its Implications on Pricing Currency Options," Monash Econometrics and Business Statistics Working Papers 17/02, Monash University, Department of Econometrics and Business Statistics.
    10. Junji Shimada & Yoshihiko Tsukuda, 2004. "Estimation of Stochastic Volatility Models : An Approximation to the Nonlinear State Space," Econometric Society 2004 Far Eastern Meetings 611, Econometric Society.
    11. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2016. "Global credit risk: world country and industry factors," Working Paper Series 1922, European Central Bank.
    12. Tommaso Proietti & Alessandra Luati, 2013. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 15, pages 334-362, Edward Elgar Publishing.
    13. Fiorentini, G. & Planas, C. & Rossi, A., 2012. "The marginal likelihood of dynamic mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 56(9), pages 2650-2662.
    14. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2002. "Range‐Based Estimation of Stochastic Volatility Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1047-1091, June.
    15. 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.
    16. 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.
    17. 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).
    18. 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.
    19. B.P.M. McCabe & G.M. Martin, 2003. "Coherent Predictions of Low Count Time Series," Monash Econometrics and Business Statistics Working Papers 8/03, Monash University, Department of Econometrics and Business Statistics.
    20. Ahn, Kwang Woo & Chan, Kung-Sik, 2014. "Approximate conditional least squares estimation of a nonlinear state-space model via an unscented Kalman filter," Computational Statistics & Data Analysis, Elsevier, vol. 69(C), pages 243-254.
    21. Siem Jan Koopman & Rutger Lit & Thuy Minh Nguyen, 2012. "Fast Efficient Importance Sampling by State Space Methods," Tinbergen Institute Discussion Papers 12-008/4, Tinbergen Institute, revised 16 Oct 2014.
    22. 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.
    23. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    24. Bidarkota, Prasad V. & Dupoyet, Brice V. & McCulloch, J. Huston, 2009. "Asset pricing with incomplete information and fat tails," Journal of Economic Dynamics and Control, Elsevier, vol. 33(6), pages 1314-1331, June.
    25. Kreuzer, Alexander & Dalla Valle, Luciana & Czado, Claudia, 2023. "Bayesian multivariate nonlinear state space copula models," Computational Statistics & Data Analysis, Elsevier, vol. 188(C).
    26. Chris M Strickland & Gael Martin & Catherine S Forbes, 2006. "Parameterisation and Efficient MCMC Estimation of Non-Gaussian State Space Models," Monash Econometrics and Business Statistics Working Papers 22/06, Monash University, Department of Econometrics and Business Statistics.
    27. Dominik Bertsche & Robin Braun, 2018. "Identification of Structural Vector Autoregressions by Stochastic Volatility," Working Paper Series of the Department of Economics, University of Konstanz 2018-03, Department of Economics, University of Konstanz.
    28. 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.
    29. Hans J. Skaug & Jun Yu, 2007. "Automated Likelihood Based Inference for Stochastic Volatility Models," Working Papers CoFie-01-2007, Singapore Management University, Sim Kee Boon Institute for Financial Economics.
    30. Yasuhiro Omori & Toshiaki Watanabe, 2007. "Block Sampler and Posterior Mode Estimation for A Nonlinear and Non-Gaussian State-Space Model with Correlated Errors," CARF F-Series CARF-F-104, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    31. Frühwirth-Schnatter, Sylvia & Wagner, Helga, 2008. "Marginal likelihoods for non-Gaussian models using auxiliary mixture sampling," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4608-4624, June.
    32. McCabe, B.P.M. & Martin, G.M., 2005. "Bayesian predictions of low count time series," International Journal of Forecasting, Elsevier, vol. 21(2), pages 315-330.
    33. Jin, Na & Lence, Sergio H & Hart, Chad & Hayes, Dermot J., 2012. "The Long-Term Structure of Commodity Futures," ISU General Staff Papers 201201010800001071, Iowa State University, Department of Economics.
    34. Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2012. "Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models," Tinbergen Institute Discussion Papers 12-020/4, Tinbergen Institute.
    35. Alexander Kreuzer & Luciana Dalla Valle & Claudia Czado, 2022. "A Bayesian non‐linear state space copula model for air pollution in Beijing," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 613-638, June.
    36. 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.
    37. McCAUSLAND, William, 2008. "The Hessian Method (Highly Efficient State Smoothing, In a Nutshell)," Cahiers de recherche 03-2008, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    38. Liang Yulan & Kelemen Arpad, 2016. "Bayesian state space models for dynamic genetic network construction across multiple tissues," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 15(4), pages 273-290, August.
    39. Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2011. "Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State Space Models," Tinbergen Institute Discussion Papers 11-057/4, Tinbergen Institute, revised 27 Jan 2012.
    40. Alexander Tsyplakov, 2011. "An introduction to state space modeling (in Russian)," Quantile, Quantile, issue 9, pages 1-24, July.
    41. Francesco Calvori & Drew Creal & Siem Jan Koopman & Andre Lucas, 2014. "Testing for Parameter Instability in Competing Modeling Frameworks," Tinbergen Institute Discussion Papers 14-010/IV/DSF71, Tinbergen Institute.
    42. Singh, Rakhi & Mukhopadhyay, Siuli, 2019. "Exact Bayesian designs for count time series," Computational Statistics & Data Analysis, Elsevier, vol. 134(C), pages 157-170.
    43. Catherine S. Forbes & Gael M. Martin & Jill Wright, 2007. "Inference for a Class of Stochastic Volatility Models Using Option and Spot Prices: Application of a Bivariate Kalman Filter," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 387-418.
    44. Eugenie Hol & Siem Jan Koopman, 2000. "Forecasting the Variability of Stock Index Returns with Stochastic Volatility Models and Implied Volatility," Tinbergen Institute Discussion Papers 00-104/4, Tinbergen Institute.
    45. 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.
    46. Eugenie Hol & Siem Jan Koopman & Borus Jungbacker, 2004. "Forecasting daily variability of the S\&P 100 stock index using historical, realised and implied volatility measurements," Computing in Economics and Finance 2004 342, Society for Computational Economics.
    47. 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.
    48. Djennad, Abdelmajid & Rigby, Robert & Stasinopoulos, Dimitrios & Voudouris, Vlasios & Eilers, Paul, 2015. "Beyond location and dispersion models: The Generalized Structural Time Series Model with Applications," MPRA Paper 62807, University Library of Munich, Germany.
    49. Siem Jan Koopman & Eugenie Hol Uspensky, 2000. "The Stochastic Volatility in Mean Model," Tinbergen Institute Discussion Papers 00-024/4, Tinbergen Institute.
    50. G. Mesters & S. J. Koopman & M. Ooms, 2016. "Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models," Econometric Reviews, Taylor & Francis Journals, vol. 35(4), pages 659-687, April.
    51. Khan Naushad Mamode & Sunecher Yuvraj & Jowaheer Vandna, 2017. "Analyzing the Full BINMA Time Series Process Using a Robust GQL Approach," Journal of Time Series Econometrics, De Gruyter, vol. 9(2), pages 1-12, July.
    52. 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.
    53. Yoonsuk Lee & B. Wade Brorsen, 2017. "Permanent shocks and forecasting with moving averages," Applied Economics, Taylor & Francis Journals, vol. 49(12), pages 1213-1225, March.
    54. Zheng, Nan & Cadigan, Noel, 2021. "Frequentist delta-variance approximations with mixed-effects models and TMB," Computational Statistics & Data Analysis, Elsevier, vol. 160(C).
    55. Roberto Casarin & Domenico Sartore, 2007. "Matrix-State Particle Filter for Wishart Stochastic Volatility Processes," Working Papers 2007_30, Department of Economics, University of Venice "Ca' Foscari".
    56. Trojan, Sebastian, 2014. "Modeling Intraday Stochastic Volatility and Conditional Duration Contemporaneously with Regime Shifts," Economics Working Paper Series 1425, University of St. Gallen, School of Economics and Political Science.
    57. Mikkelsen, Peter, 2001. "MCMC Based Estimation of Term Structure Models," Finance Working Papers 01-7, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    58. 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.
    59. 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.
    60. Robert A. Hill & Paulo M. M. Rodrigues, 2022. "Forgetting approaches to improve forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1356-1371, November.
    61. J.S.K. Chan & W.Y. Wan & P.L.H. Yu, 2014. "A Poisson geometric process approach for predicting drop-out and committed first-time blood donors," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(7), pages 1486-1503, July.
    62. 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.
    63. Macaro, Christian, 2010. "Bayesian non-parametric signal extraction for Gaussian time series," Journal of Econometrics, Elsevier, vol. 157(2), pages 381-395, August.
    64. Michael D. Hunter & Haya Fatimah & Marina A. Bornovalova, 2022. "Two Filtering Methods of Forecasting Linear and Nonlinear Dynamics of Intensive Longitudinal Data," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 477-505, June.
    65. Geert Mesters & Siem Jan Koopman, 2012. "Generalized Dynamic Panel Data Models with Random Effects for Cross-Section and Time," Tinbergen Institute Discussion Papers 12-009/4, Tinbergen Institute, revised 18 Mar 2014.
    66. 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.
    67. 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.
    68. Mauro Bernardi & Daniele Bianchi & Nicolas Bianco, 2022. "Smoothing volatility targeting," Papers 2212.07288, arXiv.org.
    69. Klingenberg, Bernhard, 2008. "Regression models for binary time series with gaps," Computational Statistics & Data Analysis, Elsevier, vol. 52(8), pages 4076-4090, April.
    70. Yao Rao & David Harris & Brendan McCabe, 2022. "A semi‐parametric integer‐valued autoregressive model with covariates," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 495-516, June.
    71. Strickland, Chris M. & Forbes, Catherine S. & Martin, Gael M., 2006. "Bayesian analysis of the stochastic conditional duration model," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2247-2267, May.
    72. Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
    73. Kleppe, Tore Selland & Liesenfeld, Roman, 2011. "Efficient high-dimensional importance sampling in mixture frameworks," Economics Working Papers 2011-11, Christian-Albrechts-University of Kiel, Department of Economics.
    74. Alzahrani, Naif & Neal, Peter & Spencer, Simon E.F. & McKinley, Trevelyan J. & Touloupou, Panayiota, 2018. "Model selection for time series of count data," Computational Statistics & Data Analysis, Elsevier, vol. 122(C), pages 33-44.
    75. Scharth, Marcel & Kohn, Robert, 2016. "Particle efficient importance sampling," Journal of Econometrics, Elsevier, vol. 190(1), pages 133-147.
    76. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.
    77. M. Shelton Peiris & Manabu Asai, 2016. "Generalized Fractional Processes with Long Memory and Time Dependent Volatility Revisited," Econometrics, MDPI, vol. 4(3), pages 1-21, September.
    78. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2013. "On the Stratonovich – Kalman - Bucy filtering algorithm application for accurate characterization of financial time series with use of state-space model by central banks," MPRA Paper 50235, University Library of Munich, Germany.
    79. Kleppe, Tore Selland & Liesenfeld, Roman, 2014. "Efficient importance sampling in mixture frameworks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 449-463.
    80. KIANI, Khurshid M., 2007. "Determination Of Volatility And Mean Returns: An Evidence From An Emerging Stock Market," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 4(1), pages 103-118.
    81. J. Huston McCulloch & Prasad V. Bidarkota, 2003. "Signal Extraction can Generate Volatility Clusters," Computing in Economics and Finance 2003 59, Society for Computational Economics.
    82. J. Huston McCulloch & Prasad V. Bidarkota, 2002. "Signal Extraction Can Generate Volatility Clusters From IID Shocks," Working Papers 02-04, Ohio State University, Department of Economics.
    83. Frühwirth-Schnatter, Sylvia & Wagner, Helga, 2010. "Stochastic model specification search for Gaussian and partial non-Gaussian state space models," Journal of Econometrics, Elsevier, vol. 154(1), pages 85-100, January.
    84. Ruiz-Cárdenas, Ramiro & Krainski, Elias T. & Rue, Håvard, 2012. "Direct fitting of dynamic models using integrated nested Laplace approximations — INLA," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1808-1828.
    85. Alina Sima (Grigore) & Alin Sima, 2011. "Distance to Default Estimates for Romanian Listed Companies," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 3(2), pages 091-106, December.
    86. Eugenie Hol & Siem Jan Koopman, 2002. "Stock Index Volatility Forecasting with High Frequency Data," Tinbergen Institute Discussion Papers 02-068/4, Tinbergen Institute.
    87. 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.
    88. Yoonsuk Lee & B. Wade Brorsen, 2017. "Permanent Breaks and Temporary Shocks in a Time Series," Computational Economics, Springer;Society for Computational Economics, vol. 49(2), pages 255-270, February.
    89. Vurukonda Sathish & Siuli Mukhopadhyay & Rashmi Tiwari, 2022. "Autoregressive and moving average models for zero‐inflated count time series," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 76(2), pages 190-218, May.
    90. 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.
    91. 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.
    92. Danny Pfeffermann & Richard Tiller, 2005. "Bootstrap Approximation to Prediction MSE for State–Space Models with Estimated Parameters," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(6), pages 893-916, November.
    93. Ginger M. Davis & Katherine B. Ensor, 2007. "Multivariate Time‐Series Analysis With Categorical and Continuous Variables in an Lstr Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(6), pages 867-885, November.
    94. Garland Durham, 2004. "Likelihood-based estimation and specification analysis of one- and two-factor SV models with leverage effects," Econometric Society 2004 North American Summer Meetings 294, Econometric Society.
    95. Durham, Garland B., 2006. "Monte Carlo methods for estimating, smoothing, and filtering one- and two-factor stochastic volatility models," Journal of Econometrics, Elsevier, vol. 133(1), pages 273-305, July.
    96. Matti Vihola & Jouni Helske & Jordan Franks, 2020. "Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(4), pages 1339-1376, December.
    97. Mircea Cristian Gherman, 2011. "Analysis of GARCH Modeling in Financial Markets: An Approach Based on Technical Analysis Strategies," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 4(4), pages 158-171, August.
    98. P. Besbeas & S. N. Freeman & B. J. T. Morgan & E. A. Catchpole, 2002. "Integrating Mark–Recapture–Recovery and Census Data to Estimate Animal Abundance and Demographic Parameters," Biometrics, The International Biometric Society, vol. 58(3), pages 540-547, September.
    99. Jeongeun Kim & David S. Stoffer, 2008. "Fitting Stochastic Volatility Models in the Presence of Irregular Sampling via Particle Methods and the EM Algorithm," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(5), pages 811-833, September.
    100. Siem Jan Koopman & Rutger Lit & André Lucas, 2014. "The Dynamic Skellam Model with Applications," Tinbergen Institute Discussion Papers 14-032/IV/DSF73, Tinbergen Institute, revised 06 Jul 2015.
    101. Kleppe, Tore Selland & Skaug, Hans Julius, 2012. "Fitting general stochastic volatility models using Laplace accelerated sequential importance sampling," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3105-3119.
    102. Lee, Woojoo & Lim, Johan & Lee, Youngjo & del Castillo, Joan, 2011. "The hierarchical-likelihood approach to autoregressive stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 248-260, January.
    103. Vêlayoudom Marimoutou & Manel Soury, 2015. "Energy Markets and CO2 Emissions: Analysis by Stochastic Copula Autoregressive Model," Working Papers halshs-01148746, HAL.
    104. Durham, Garland B., 2007. "SV mixture models with application to S&P 500 index returns," Journal of Financial Economics, Elsevier, vol. 85(3), pages 822-856, September.
    105. Gabriele Fiorentini & Enrique Sentana, 2012. "Tests for Serial Dependence in Static, Non-Gaussian Factor Models," Working Papers wp2012_1211, CEMFI.

  3. Koopman, S.J.M. & Durbin, J., 1998. "Fast Filtering and Smoothing for Multivariate State Space Models," Discussion Paper 1998-18, Tilburg University, Center for Economic Research.

    Cited by:

    1. Helske, Jouni, 2017. "KFAS: Exponential Family State Space Models in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 78(i10).
    2. Borus Jungbacker & Siem Jan Koopman & Michel van der Wel, 2009. "Smooth Dynamic Factor Analysis with an Application to the U.S. Term Structure of Interest Rates," CREATES Research Papers 2009-39, Department of Economics and Business Economics, Aarhus University.
    3. T. Berger & L. Pozzi, 2011. "A new model-based approach to measuring time-varying financial market integration," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 11/714, Ghent University, Faculty of Economics and Business Administration.
    4. 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.
    5. Monica Billio & Roberto Casarin & Anthony Osuntuyi, 2012. "Efficient Gibbs Sampling for Markov Switching GARCH Models," Working Papers 2012:35, Department of Economics, University of Venice "Ca' Foscari".
    6. 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.
    7. 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.
    8. Konstantinos Metaxoglou & Aaron Smith, 2007. "Efficiency of the California electricity reserves market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(6), pages 1127-1144.
    9. Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022. "Monitoring the Economy in Real Time: Trends and Gaps in Real Activity and Prices," SciencePo Working papers Main hal-03573080, HAL.
    10. Tommaso Proietti & Alessandra Luati, 2013. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 15, pages 334-362, Edward Elgar Publishing.
    11. T. Berger & B. Kempa & -, 2010. "Taylor rules and the Canadian-US equilibrium exchange rate," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 10/643, Ghent University, Faculty of Economics and Business Administration.
    12. Christian Bayer & Benjamin Born & Ralph Luetticke, 2020. "Shocks, Frictions, and Inequality in US Business Cycles," Discussion Papers 2003, Centre for Macroeconomics (CFM).
    13. Cecilia Frale & Massimiliano Marcellino & Gian Luigi Mazzi & Tommaso Proietti, 2009. "Survey Data as Coicident or Leading Indicators," Economics Working Papers ECO2009/19, European University Institute.
    14. Matteo Barigozzi & Matteo Luciani, 2017. "Common Factors, Trends, and Cycles in Large Datasets," Finance and Economics Discussion Series 2017-111, Board of Governors of the Federal Reserve System (U.S.).
    15. Snyder Ralph D & Forbes Catherine S, 2003. "Reconstructing the Kalman Filter for Stationary and Non Stationary Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(2), pages 1-20, July.
    16. Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2015. "EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area," CREATES Research Papers 2015-12, Department of Economics and Business Economics, Aarhus University.
    17. Petar Jevtić & Luca Regis, 2021. "A Square-Root Factor-Based Multi-Population Extension of the Mortality Laws," Mathematics, MDPI, vol. 9(19), pages 1-17, September.
    18. Catherine Doz & Laurent Ferrara & Pierre-Alain Pionnier, 2020. "Business cycle dynamics after the Great Recession: An Extended Markov-Switching Dynamic Factor Model," Working Papers halshs-02443364, HAL.
    19. 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.
    20. Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2020. "A Model of the Fed's View on Inflation," Papers 2006.14110, arXiv.org.
    21. Stéphane Adjemian & Houtan Bastani & Michel Juillard & Frédéric Karamé & Ferhat Mihoubi & Willi Mutschler & Johannes Pfeifer & Marco Ratto & Sébastien Villemot & Normann Rion, 2023. "Dynare: Reference Manual Version 5," PSE Working Papers hal-04219920, HAL.
      • Stéphane Adjemian & Houtan Bastani & Michel Juillard & Frédéric Karamé & Ferhat Mihoubi & Willi Mutschler & Johannes Pfeifer & Marco Ratto & Sébastien Villemot & Normann Rion, 2023. "Dynare: Reference Manual Version 5," Working Papers hal-04219920, HAL.
      • Adjemian, Stéphane & Bastani, Houtan & Juillard, Michel & Karamé, Fréderic & Mihoubi, Ferhat & Mutschler, Willi & Pfeifer, Johannes & Ratto, Marco & Rion, Normann & Villemot, Sébastien, 2022. "Dynare: Reference Manual Version 5," Dynare Working Papers 72, CEPREMAP, revised Mar 2023.
    22. Pozzi, Lorenzo & Wolswijk, Guido, 2012. "The time-varying integration of euro area government bond markets," European Economic Review, Elsevier, vol. 56(1), pages 36-53.
    23. 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.
    24. Lorenzo Boldrini & Eric Hillebrand, 2015. "Supervision in Factor Models Using a Large Number of Predictors," CREATES Research Papers 2015-38, Department of Economics and Business Economics, Aarhus University.
    25. Koopman, S.J.M. & Lai, H.N., 1998. "Modelling bid-ask spreads in competitive dealership markets," Discussion Paper 1998-032, Tilburg University, Center for Economic Research.
    26. Helmut Herwartz & Christian Ochsner & Hannes Rohloff, 2021. "The Credit Composition of Global Liquidity," MAGKS Papers on Economics 202115, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    27. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    28. Adjemian, Stéphane & Juillard, Michel & Karamé, Fréderic & Mutschler, Willi & Pfeifer, Johannes & Ratto, Marco & Rion, Normann & Villemot, Sébastien, 2024. "Dynare: Reference Manual, Version 6," Dynare Working Papers 80, CEPREMAP.
    29. Christian Bayer & Benjamin Born & Ralph Luetticke, 2021. "The Liquidity Channel of Fiscal Policy," ifo Working Paper Series 351, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    30. Johannes Huber, 2022. "An Augmented Steady-State Kalman Filter to Evaluate the Likelihood of Linear and Time-Invariant State-Space Models," Discussion Paper Series 343, Universitaet Augsburg, Institute for Economics.
    31. 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.
    32. Steff De Visscher & Markus Eberhardt & Gerdie Everaert, 2017. "Measuring productivity and absorptive capacity evolution," Discussion Papers 2017-11, University of Nottingham, GEP.
    33. Luke Mosley & Tak-Shing Chan & Alex Gibberd, 2023. "sparseDFM: An R Package to Estimate Dynamic Factor Models with Sparse Loadings," Papers 2303.14125, arXiv.org.
    34. Proietti, Tommaso & Giovannelli, Alessandro & Ricchi, Ottavio & Citton, Ambra & Tegami, Christían & Tinti, Cristina, 2021. "Nowcasting GDP and its components in a data-rich environment: The merits of the indirect approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1376-1398.
    35. 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.
    36. 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.
    37. Siem Jan Koopman & Michel van der Wel, 2011. "Forecasting the U.S. Term Structure of Interest Rates using a Macroeconomic Smooth Dynamic Factor Model," Tinbergen Institute Discussion Papers 11-063/4, Tinbergen Institute.
    38. Eberhardt, Markus & Everaert, Gerdie & De Visscher, Stef, 2017. "Measuring Productivity and Absorptive Capacity Evolution in OECD Economies," CEPR Discussion Papers 12261, C.E.P.R. Discussion Papers.
    39. Strid, Ingvar & Walentin, Karl, 2008. "Block Kalman filtering for large-scale DSGE models," Working Paper Series 224, Sveriges Riksbank (Central Bank of Sweden).
    40. Algaba, Andres & Borms, Samuel & Boudt, Kris & Verbeken, Brecht, 2023. "Daily news sentiment and monthly surveys: A mixed-frequency dynamic factor model for nowcasting consumer confidence," International Journal of Forecasting, Elsevier, vol. 39(1), pages 266-278.
    41. 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.
    42. Dossche, Maarten & Everaert, Gerdie, 2005. "Measuring inflation persistence: a structural time series approach," Working Paper Series 495, European Central Bank.
    43. Cecilia Frale & David Veredas, 2008. "A Monthly Volatility Index for the US Economy," Working Papers ECARES 2008-008, ULB -- Universite Libre de Bruxelles.
    44. Prashant Srivastava & Dawei Han & Miguel Rico-Ramirez & Deleen Al-Shrafany & Tanvir Islam, 2013. "Data Fusion Techniques for Improving Soil Moisture Deficit Using SMOS Satellite and WRF-NOAH Land Surface Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(15), pages 5069-5087, December.
    45. Blasques, F. & Koopman, S.J. & Mallee, M. & Zhang, Z., 2016. "Weighted maximum likelihood for dynamic factor analysis and forecasting with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 405-417.
    46. 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.
    47. 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.
    48. Lorenzo Boldrini & Eric Hillebrand, 2015. "The Forecasting Power of the Yield Curve, a Supervised Factor Model Approach," CREATES Research Papers 2015-39, Department of Economics and Business Economics, Aarhus University.
    49. Lorenzo Boldrini, 2015. "Forecasting the Global Mean Sea Level, a Continuous-Time State-Space Approach," CREATES Research Papers 2015-40, Department of Economics and Business Economics, Aarhus University.
    50. António Alberto Santos, 2010. "MCMC, likelihood estimation and identifiability problems in DLM models," GEMF Working Papers 2010-12, GEMF, Faculty of Economics, University of Coimbra.
    51. 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.
    52. Edward P. Herbst, 2012. "Using the \"Chandrasekhar Recursions\" for likelihood evaluation of DSGE models," Finance and Economics Discussion Series 2012-35, Board of Governors of the Federal Reserve System (U.S.).
    53. Fondeur, Y. & Karamé, F., 2013. "Can Google data help predict French youth unemployment?," Economic Modelling, Elsevier, vol. 30(C), pages 117-125.
    54. Paul Labonne & Martin Weale, 2018. "Temporal disaggregation of overlapping noisy quarterly data using state space models: Estimation of monthly business sector output from Value Added Tax data in the UK," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-18, Economic Statistics Centre of Excellence (ESCoE).
    55. Edward P. Herbst & Fabian Winkler, 2021. "The Factor Structure of Disagreement," Finance and Economics Discussion Series 2021-046, Board of Governors of the Federal Reserve System (U.S.).
    56. Misha van Beek, 2020. "Consistent Calibration of Economic Scenario Generators: The Case for Conditional Simulation," Papers 2004.09042, arXiv.org.
    57. Lorenzo Pozzi & Guido Wolswijk, 2008. "Have Euro Area Government Bond Risk Premia Converged To Their Common State?," Tinbergen Institute Discussion Papers 08-042/2, Tinbergen Institute, revised 07 Sep 2009.
    58. Berger, Tino & Grabert, Sibylle & Kempa, Bernd, 2017. "Global macroeconomic uncertainty," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 42-56.
    59. Kathryn Holston & Thomas Laubach & John C. Williams, 2023. "Measuring the Natural Rate of Interest after COVID-19," Staff Reports 1063, Federal Reserve Bank of New York.
    60. Borus Jungbacker & Siem Jan Koopman & Michel van der Wel, 0000. "Dynamic Factor Models with Smooth Loadings for Analyzing the Term Structure of Interest Rates," Tinbergen Institute Discussion Papers 09-041/4, Tinbergen Institute, revised 17 Sep 2010.
    61. Changyu Liu & Michael Sherris, 2017. "Immunization and Hedging of Post Retirement Income Annuity Products," Risks, MDPI, vol. 5(1), pages 1-29, March.
    62. T. Berger & G. Everaert, 2006. "Re-examining the Structural and the Persistence Approach to Unemployment," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 06/383, Ghent University, Faculty of Economics and Business Administration.
    63. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    64. Joao Valle e Azevedo & Siem Jan Koopman & Antonio Rua, 2003. "Tracking Growth and the Business Cycle: a Stochastic Common Cycle Model for the Euro Area," Tinbergen Institute Discussion Papers 03-069/4, Tinbergen Institute.
    65. Berger, Tino & Pozzi, Lorenzo, 2013. "Measuring time-varying financial market integration: An unobserved components approach," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 463-473.
    66. Francisco Blasques & Siem Jan Koopman & Max Mallee, 2014. "Low Frequency and Weighted Likelihood Solutions for Mixed Frequency Dynamic Factor Models," Tinbergen Institute Discussion Papers 14-105/III, Tinbergen Institute.
    67. Andree,Bo Pieter Johannes, 2021. "Estimating Food Price Inflation from Partial Surveys," Policy Research Working Paper Series 9886, The World Bank.
    68. 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.
    69. G. Everaert & L. Pozzi, 2014. "The dynamics of European financial market integration," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 14/877, Ghent University, Faculty of Economics and Business Administration.
    70. Schrager, David F., 2006. "Affine stochastic mortality," Insurance: Mathematics and Economics, Elsevier, vol. 38(1), pages 81-97, February.
    71. Borus Jungbacker & Siem Jan Koopman, 2015. "Likelihood‐based dynamic factor analysis for measurement and forecasting," Econometrics Journal, Royal Economic Society, vol. 18(2), pages 1-21, June.
    72. Borus Jungbacker & Siem Jan Koopman, 2008. "Likelihood-based Analysis for Dynamic Factor Models," Tinbergen Institute Discussion Papers 08-007/4, Tinbergen Institute, revised 20 Mar 2014.

Articles

  1. S. J. Koopman & J. Durbin, 2003. "Filtering and smoothing of state vector for diffuse state‐space models," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(1), pages 85-98, January.

    Cited by:

    1. Helske, Jouni, 2017. "KFAS: Exponential Family State Space Models in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 78(i10).
    2. Siem Jan Koopman & Kai Ming Lee, 0000. "Seasonality with Trend and Cycle Interactions in Unobserved Components Models," Tinbergen Institute Discussion Papers 08-028/4, Tinbergen Institute.
    3. Michal Franta & Branislav Saxa & Katerina Smidkova, 2007. "Inflation Persistence in New EU Member States: Is It Different Than in the Euro Area Members?," Working Papers 2007/10, Czech National Bank.
    4. Adrian Pizzinga & Marcelo Fernandes, 2021. "Extensions to the invariance property of maximum likelihood estimation for affine‐transformed state‐space models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(3), pages 355-371, May.
    5. Ziyue Liu & Anne R. Cappola & Leslie J. Crofford & Wensheng Guo, 2014. "Modeling Bivariate Longitudinal Hormone Profiles by Hierarchical State Space Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 108-118, March.
    6. Antonello D’Agostino & Jacopo Cimadomo, 2015. "Combining time-variation and mixed-frequencies: an analysis of government spending multipliers in Italy," Working Papers 7, European Stability Mechanism.
    7. Catherine Doz & Laurent Ferrara & Pierre-Alain Pionnier, 2020. "Business cycle dynamics after the Great Recession: An Extended Markov-Switching Dynamic Factor Model," Working Papers halshs-02443364, HAL.
    8. 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.
    9. Stéphane Adjemian & Houtan Bastani & Michel Juillard & Frédéric Karamé & Ferhat Mihoubi & Willi Mutschler & Johannes Pfeifer & Marco Ratto & Sébastien Villemot & Normann Rion, 2023. "Dynare: Reference Manual Version 5," PSE Working Papers hal-04219920, HAL.
      • Stéphane Adjemian & Houtan Bastani & Michel Juillard & Frédéric Karamé & Ferhat Mihoubi & Willi Mutschler & Johannes Pfeifer & Marco Ratto & Sébastien Villemot & Normann Rion, 2023. "Dynare: Reference Manual Version 5," Working Papers hal-04219920, HAL.
      • Adjemian, Stéphane & Bastani, Houtan & Juillard, Michel & Karamé, Fréderic & Mihoubi, Ferhat & Mutschler, Willi & Pfeifer, Johannes & Ratto, Marco & Rion, Normann & Villemot, Sébastien, 2022. "Dynare: Reference Manual Version 5," Dynare Working Papers 72, CEPREMAP, revised Mar 2023.
    10. Daniel Rees & David Lancaster & Richard Finlay, 2014. "A State-space Approach to Australian GDP Measurement," RBA Research Discussion Papers rdp2014-12, Reserve Bank of Australia.
    11. Adjemian, Stéphane & Juillard, Michel & Karamé, Fréderic & Mutschler, Willi & Pfeifer, Johannes & Ratto, Marco & Rion, Normann & Villemot, Sébastien, 2024. "Dynare: Reference Manual, Version 6," Dynare Working Papers 80, CEPREMAP.
    12. Carlos David Ardila-Dueñas & Hernán Rincón-Castro, 2019. "¿Cómo y qué tanto impacta la deuda pública a las tasas de interés de mercado?," Borradores de Economia 1077, Banco de la Republica de Colombia.
    13. Nicolaas Johannes Odendaal & Monique Reid, 2018. "Media based sentiment indices as an alternative measure of consumer confidence," Working Papers 17/2018, Stellenbosch University, Department of Economics.
    14. 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.
    15. Algaba, Andres & Borms, Samuel & Boudt, Kris & Verbeken, Brecht, 2023. "Daily news sentiment and monthly surveys: A mixed-frequency dynamic factor model for nowcasting consumer confidence," International Journal of Forecasting, Elsevier, vol. 39(1), pages 266-278.
    16. Dossche, Maarten & Everaert, Gerdie, 2005. "Measuring inflation persistence: a structural time series approach," Working Paper Series 495, European Central Bank.
    17. Prashant Srivastava & Dawei Han & Miguel Rico-Ramirez & Deleen Al-Shrafany & Tanvir Islam, 2013. "Data Fusion Techniques for Improving Soil Moisture Deficit Using SMOS Satellite and WRF-NOAH Land Surface Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(15), pages 5069-5087, December.
    18. Chen, Xiaoshan & MacDonald, Ronald, 2014. "Measuring the Euro-Dollar Permanent Equilibrium Exchange Rate using the Unobserved Components Model," Stirling Economics Discussion Papers 2014-12, University of Stirling, Division of Economics.
    19. Machado, Vicente da Gama & Portugal, Marcelo Savino, 2014. "Measuring inflation persistence in Brazil using a multivariate model," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 68(2), June.
    20. Geert Mesters & Siem Jan Koopman, 2012. "Generalized Dynamic Panel Data Models with Random Effects for Cross-Section and Time," Tinbergen Institute Discussion Papers 12-009/4, Tinbergen Institute, revised 18 Mar 2014.
    21. Damioli, Giacomo & Gregori, Wildmer Daniel, 2021. "Diplomatic relations and cross-border investments in the European Union," Working Papers 2021-02, Joint Research Centre, European Commission.
    22. B. Jungbacker & S.J. Koopman & M. van Der Wel, 2011. "Maximum likelihood estimation for dynamic factor models with missing data," Post-Print hal-00828980, HAL.
    23. Komi Nagbe & Jairo Cugliari & Julien Jacques, 2018. "Short-Term Electricity Demand Forecasting Using a Functional State Space Model," Energies, MDPI, vol. 11(5), pages 1-24, May.
    24. Fondeur, Y. & Karamé, F., 2013. "Can Google data help predict French youth unemployment?," Economic Modelling, Elsevier, vol. 30(C), pages 117-125.
    25. Adrian Pizzinga, 2010. "Constrained Kalman Filtering: Additional Results," International Statistical Review, International Statistical Institute, vol. 78(2), pages 189-208, August.
    26. 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).
    27. T. Berger & G. Everaert, 2006. "Re-examining the Structural and the Persistence Approach to Unemployment," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 06/383, Ghent University, Faculty of Economics and Business Administration.
    28. Mariam Camarero & Juan Sapena & Cecilio Tamarit, 2024. "Introducing sspaneltvp: a code to estimating state-space time varying parameter models in panels. An application to Okun’s law," Working Papers 2405, Department of Applied Economics II, Universidad de Valencia.
    29. Giovannini, Massimo & Pfeiffer, Philipp & Ratto, Marco, 2021. "Efficient and robust inference of models with occasionally binding constraints," Working Papers 2021-03, Joint Research Centre, European Commission.
    30. Calo, Silvia & Gregori, Wildmer Daniel & Petracco Giudici, Marco & Rancan, Michela, 2021. "Has the Comprehensive Assessment made the European financial system more resilient?," Working Papers 2021-08, Joint Research Centre, European Commission.
    31. B. Jungbacker & S.J. Koopman & M. van der Wel, 2009. "Dynamic Factor Analysis in The Presence of Missing Data," Tinbergen Institute Discussion Papers 09-010/4, Tinbergen Institute, revised 11 Mar 2011.
    32. 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. J. Durbin, 2002. "A simple and efficient simulation smoother for state space time series analysis," Biometrika, Biometrika Trust, vol. 89(3), pages 603-616, August.

    Cited by:

    1. Florian Heiss, 2008. "Sequential numerical integration in nonlinear state space models for microeconometric panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 373-389.
    2. Helske, Jouni, 2017. "KFAS: Exponential Family State Space Models in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 78(i10).
    3. 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.
    4. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    5. Siem Jan Koopman & André Lucas & André Monteiro, 2005. "The Multi-State Latent Factor Intensity Model for Credit Rating Transitions," Tinbergen Institute Discussion Papers 05-071/4, Tinbergen Institute, revised 04 Jul 2005.
    6. Gary Koop & Roberto Leon-Gonzalez & Rodney Strachan, 2011. "Bayesian Inference in the Time Varying Cointegration Model," Working Papers 1121, University of Strathclyde Business School, Department of Economics.
    7. Jaeho Kim & Sora Chon, 2020. "Why are Bayesian trend-cycle decompositions of US real GDP so different?," Empirical Economics, Springer, vol. 58(3), pages 1339-1354, March.
    8. Max Bruche, 2006. "Estimating Structural Models of Corporate Bond Prices," Working Papers wp2006_0610, CEMFI.
    9. Antonello D'Agostino & Domenico Giannone & Michele Lenza & Michele Modugno, 2015. "Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models," Finance and Economics Discussion Series 2015-66, Board of Governors of the Federal Reserve System (U.S.).
    10. Dimitris Korobilis, 2009. "Assessing the Transmission of Monetary Policy Shocks Using Dynamic Factor Models," Working Paper series 35_09, Rimini Centre for Economic Analysis.
    11. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    12. Makoto Takahashi & Toshiaki Watanabe & Yasuhiro Omori, 2014. "Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution," CIRJE F-Series CIRJE-F-949, CIRJE, Faculty of Economics, University of Tokyo.
    13. Yu-Fan Huang & Sui Luo, 2018. "Potential output and inflation dynamics after the Great Recession," Empirical Economics, Springer, vol. 55(2), pages 495-517, September.
    14. Bańbura, Marta & Giannone, Domenico & Lenza, Michele, 2015. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," International Journal of Forecasting, Elsevier, vol. 31(3), pages 739-756.
    15. 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.
    16. Eyal Argov & Alon Binyamini & Eliezer Borenstein & Irit Rozenshtrom, 2015. "Model-Based Ex Post Evaluation of Monetary Policy," International Journal of Central Banking, International Journal of Central Banking, vol. 11(4), pages 219-254, December.
    17. Shang, Yuhuang & Liu, Lulu, 2017. "An extension of stochastic volatility model with mixed frequency information," Economics Letters, Elsevier, vol. 155(C), pages 144-148.
    18. Tommaso Proietti & Marco Riani, 2009. "Transformations and seasonal adjustment," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 47-69, January.
    19. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Real-time nowcasting with a Bayesian mixed frequency model with stochastic volatility," Working Papers (Old Series) 1227, Federal Reserve Bank of Cleveland.
    20. Drew D. Creal & Jing Cynthia Wu, 2020. "Bond risk premia in consumption‐based models," Quantitative Economics, Econometric Society, vol. 11(4), pages 1461-1484, November.
    21. Michael D. Bauer & Carolin Pflueger & Adi Sunderam, 2022. "Perceptions about Monetary Policy," NBER Working Papers 30480, National Bureau of Economic Research, Inc.
    22. Charles S. Bos & Neil Shephard, 2004. "Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form," Economics Papers 2004-W02, Economics Group, Nuffield College, University of Oxford.
    23. Michael D. Bauer & Glenn D. Rudebusch, 2017. "Interest Rates Under Falling Stars," CESifo Working Paper Series 6571, CESifo.
    24. Makoto Takahashi & Yasuhiro Omori & Toshiaki Watanabe, 2007. "Estimating Stochastic Volatility Models Using Daily Returns and Realized Volatility Simultaneously," CIRJE F-Series CIRJE-F-515, CIRJE, Faculty of Economics, University of Tokyo.
    25. Richard K. Crump & Stefano Eusepi & Domenico Giannone & Eric Qian & Argia M. Sbordone, 2021. "A Large Bayesian VAR of the United States Economy," Staff Reports 976, Federal Reserve Bank of New York.
    26. Giorgio Primiceri & Alejandro Justiniano, 2006. "The Time Varying Volatility of Macroeconomic Fluctuations," 2006 Meeting Papers 353, Society for Economic Dynamics.
    27. Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022. "Monitoring the Economy in Real Time: Trends and Gaps in Real Activity and Prices," SciencePo Working papers Main hal-03573080, HAL.
    28. Tommaso Proietti & Alessandra Luati, 2013. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 15, pages 334-362, Edward Elgar Publishing.
    29. Xianguo HUANG & Roberto LEON-GONZALEZ & Somrasri YUPHO, 2013. "Financial Integration from a Time-Varying Cointegration Perspective," Asian Journal of Empirical Research, Asian Economic and Social Society, vol. 3(12), pages 1473-1487.
    30. Borus Jungbacker & Siem Jan Koopman, 2005. "On Importance Sampling for State Space Models," Tinbergen Institute Discussion Papers 05-117/4, Tinbergen Institute.
    31. Davide Pettenuzzo & Antonio Gargano & Allan Timmermann, 2014. "Bond Return Predictability: Economic Value and Links to the Macroeconomy," Working Papers 75, Brandeis University, Department of Economics and International Business School.
    32. Omori, Yasuhiro & Watanabe, Toshiaki, 2008. "Block sampler and posterior mode estimation for asymmetric stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2892-2910, February.
    33. Joshua C.C. Chan & Garry Koop & Roberto Leon Gonzales & Rodney W. Strachan, 2010. "Time Varying Dimension Models," ANU Working Papers in Economics and Econometrics 2010-523, Australian National University, College of Business and Economics, School of Economics.
    34. Guido Ascari & Luca Fosso, 2021. "The Inflation Rate Disconnect Puzzle: On the International Component of Trend Inflation and the Flattening of the Phillips Curve," Working Paper 2021/17, Norges Bank.
    35. Koop, Gary & Leon-Gonzalez, Roberto & Strachan, Rodney W., 2009. "On the evolution of the monetary policy transmission mechanism," Journal of Economic Dynamics and Control, Elsevier, vol. 33(4), pages 997-1017, April.
    36. 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.
    37. 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.
    38. Nakajima, Jouchi & Omori, Yasuhiro, 2009. "Leverage, heavy-tails and correlated jumps in stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2335-2353, April.
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    92. Koopman, Siem Jan & Kräussl, Roman & Lucas, André, 2006. "Credit cycles and macro fundamentals," CFS Working Paper Series 2006/33, Center for Financial Studies (CFS).
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    118. Rodríguez, Aldo, 2020. "Estimación Bayesiana de un Modelo de Economía Abierta con Sector Bancario," Dynare Working Papers 52, CEPREMAP.
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    145. Luis Uzeda, 2018. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Staff Working Papers 18-14, Bank of Canada.
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    147. Terence D. Agbeyegbe, 2023. "The Link Between Output Growth and Output Growth Volatility: Barbados," Annals of Data Science, Springer, vol. 10(3), pages 787-804, June.
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    151. 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.
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    155. Koopman, Siem Jan & Lucas, André & Schwaab, Bernd, 2011. "Modeling frailty-correlated defaults using many macroeconomic covariates," Journal of Econometrics, Elsevier, vol. 162(2), pages 312-325, June.
    156. André A. Monteiro, 2008. "Parameter Driven Multi-state Duration Models: Simulated vs. Approximate Maximum Likelihood Estimation," Tinbergen Institute Discussion Papers 08-021/2, Tinbergen Institute.
    157. Ankargren, Sebastian & Jonéus, Paulina, 2021. "Simulation smoothing for nowcasting with large mixed-frequency VARs," Econometrics and Statistics, Elsevier, vol. 19(C), pages 97-113.
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    161. G. Mesters & S. J. Koopman & M. Ooms, 2016. "Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models," Econometric Reviews, Taylor & Francis Journals, vol. 35(4), pages 659-687, April.
    162. M. Berument & Yeliz Yalcin & Julide Yildirim, 2011. "The inflation and inflation uncertainty relationship for Turkey: a dynamic framework," Empirical Economics, Springer, vol. 41(2), pages 293-309, October.
    163. Todd E. Clark & Francesco Ravazzolo, 2012. "The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility," Working Paper 2012/09, Norges Bank.
    164. Istvan Barra & Siem Jan Koopman & Agnieszka Borowska, 2016. "Bayesian Dynamic Modeling of High-Frequency Integer Price Changes," Tinbergen Institute Discussion Papers 16-028/III, Tinbergen Institute, revised 16 Feb 2018.
    165. Nakajima, Jouchi & Kunihama, Tsuyoshi & Omori, Yasuhiro & Frühwirth-Schnatter, Sylvia, 2012. "Generalized extreme value distribution with time-dependence using the AR and MA models in state space form," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3241-3259.
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    Cited by:

    1. Einmahl, J.H.J. & Magnus, J.R. & Kumar, K., 2011. "On the Choice of Prior in Bayesian Model Averaging," Other publications TiSEM 3ca603c9-5336-4ecb-9521-6, Tilburg University, School of Economics and Management.
    2. Clarke, Judith A., 2008. "On weighted estimation in linear regression in the presence of parameter uncertainty," Economics Letters, Elsevier, vol. 100(1), pages 1-3, July.
    3. Jan R. Magnus & Wendun Wang & Xinyu Zhang, 2016. "Weighted-Average Least Squares Prediction," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1040-1074, June.
    4. Galbraith, John W. & Zinde-Walsh, Victoria, 2020. "Simple and reliable estimators of coefficients of interest in a model with high-dimensional confounding effects," Journal of Econometrics, Elsevier, vol. 218(2), pages 609-632.
    5. Poghosyan, K. & Magnus, J.R., 2011. "WALS estimation and forecasting in factor-based dynamic models with an application to Armenia," Other publications TiSEM 419d588e-7827-4cdd-b989-4, Tilburg University, School of Economics and Management.
    6. Magnus, Jan & Peresetsky, Anatoly, 2010. "The price of Moscow apartments," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 17(1), pages 89-105.
    7. Le-Yu Chen & Sokbae Lee, 2016. "Best Subset Binary Prediction," Papers 1610.02738, arXiv.org, revised May 2018.
    8. Srdelić, Leonarda & Dávila-Fernández, Marwil J., 2024. "International trade and economic growth in Croatia," Structural Change and Economic Dynamics, Elsevier, vol. 68(C), pages 240-258.
    9. Giuseppe de Luca & Jan Magnus & Franco Peracchi, 2017. "Weighted-Average Least Squares Estimation of Generalized Linear Models," Tinbergen Institute Discussion Papers 17-029/III, Tinbergen Institute.
    10. Dardanoni, Valentino & Modica, Salvatore & Peracchi, Franco, 2011. "Regression with imputed covariates: A generalized missing-indicator approach," Journal of Econometrics, Elsevier, vol. 162(2), pages 362-368, June.
    11. Badi H. Baltagi & Georges Bresson & Anoop Chaturvedi & Guy Lacroix, 2017. "Robust Linear Static Panel Data Models Using ε-Contamination," Center for Policy Research Working Papers 208, Center for Policy Research, Maxwell School, Syracuse University.
    12. Berger, Michael & Pock, Markus & Reiss, Miriam & Röhrling, Gerald & Czypionka, Thomas, 2023. "Exploring the effectiveness of demand-side retail pharmaceutical expenditure reforms: cross-country evidence from weighted-average least squares estimation," LSE Research Online Documents on Economics 116928, London School of Economics and Political Science, LSE Library.
    13. Giuseppe De Luca & Jan R. Magnus, 2011. "Bayesian model averaging and weighted-average least squares: Equivariance, stability, and numerical issues," Stata Journal, StataCorp LP, vol. 11(4), pages 518-544, December.
    14. Magnus, J.R. & Powell, O.R. & Prüfer, P., 2008. "A Comparison of Two Averaging Techniques with an Application to Growth Empirics," Other publications TiSEM 0392dffa-51e0-4bc9-9644-f, Tilburg University, School of Economics and Management.
    15. Giuseppe De Luca & Jan R. Magnus & Franco Peracchi, 2020. "Sampling properties of the Bayesian posterior mean with anapplication to WALS estimation," EIEF Working Papers Series 2003, Einaudi Institute for Economics and Finance (EIEF), revised Mar 2020.
    16. Poghosyan, K., 2012. "Structural and reduced-form modeling and forecasting with application to Armenia," Other publications TiSEM ad1a24c3-15e6-4f04-b338-3, Tilburg University, School of Economics and Management.
    17. End, Nicolas, 2023. "Big Brother is also being watched: Measuring fiscal credibility," Journal of Macroeconomics, Elsevier, vol. 77(C).
    18. Giuseppe De Luca & Jan Magnus & Franco Peracchi, 2022. "Asymptotic properties of the weighted average least squares (WALS) estimator," Tinbergen Institute Discussion Papers 22-022/III, Tinbergen Institute.
    19. Giuseppe Luca & Jan R. Magnus & Franco Peracchi, 2023. "Weighted-Average Least Squares (WALS): Confidence and Prediction Intervals," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1637-1664, April.
    20. Nicolas End, 2020. "Rousseau's social contract or Machiavelli's virtue? A measure of fiscal credibility," Working Papers halshs-03078704, HAL.
    21. Michael Berger & Markus Pock & Miriam Reiss & Gerald Röhrling & Thomas Czypionka, 2023. "Exploring the effectiveness of demand-side retail pharmaceutical expenditure reforms," International Journal of Health Economics and Management, Springer, vol. 23(1), pages 149-172, March.
    22. Magnus, Jan R. & Wan, Alan T.K. & Zhang, Xinyu, 2011. "Weighted average least squares estimation with nonspherical disturbances and an application to the Hong Kong housing market," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1331-1341, March.
    23. Becker William & Paruolo Paolo & Saltelli Andrea, 2021. "Variable Selection in Regression Models Using Global Sensitivity Analysis," Journal of Time Series Econometrics, De Gruyter, vol. 13(2), pages 187-233, July.
    24. Giuseppe De Luca & Jan R. Magnus & Franco Peracchi, 2015. "On the ambiguous consequences of omitting variables," EIEF Working Papers Series 1505, Einaudi Institute for Economics and Finance (EIEF), revised May 2015.
    25. Bo Jiang & Yongge Tian, 2022. "Equivalence Analysis of Statistical Inference Results under True and Misspecified Multivariate Linear Models," Mathematics, MDPI, vol. 11(1), pages 1-16, December.
    26. Jan R. Magnus & Dmitry Danilov, 2004. "Forecast accuracy after pretesting with an application to the stock market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(4), pages 251-274.
    27. Zou, Guohua & Wan, Alan T.K. & Wu, Xiaoyong & Chen, Ti, 2007. "Estimation of regression coefficients of interest when other regression coefficients are of no interest: The case of non-normal errors," Statistics & Probability Letters, Elsevier, vol. 77(8), pages 803-810, April.
    28. Zhang, Xinyu, 2015. "Consistency of model averaging estimators," Economics Letters, Elsevier, vol. 130(C), pages 120-123.
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    31. Magnus, Jan R. & Powell, Owen & Prüfer, Patricia, 2010. "A comparison of two model averaging techniques with an application to growth empirics," Journal of Econometrics, Elsevier, vol. 154(2), pages 139-153, February.
    32. Giuseppe De Luca & Jan R. Magnus & Franco Peracchi, 2018. "Balanced Variable Addition In Linear Models," Journal of Economic Surveys, Wiley Blackwell, vol. 32(4), pages 1183-1200, September.
    33. Hai Wang & Xinjie Chen & Nancy Flournoy, 2016. "The focused information criterion for varying-coefficient partially linear measurement error models," Statistical Papers, Springer, vol. 57(1), pages 99-113, March.
    34. Danilov, D.L. & Magnus, J.R., 2002. "Estimation of the Mean of a Univariate Normal Distribution When the Variance is not Known," Other publications TiSEM 002a672b-73b6-4a8b-8901-7, Tilburg University, School of Economics and Management.
    35. Ali Mehrabani & Aman Ullah, 2022. "Weighted Average Estimation in Panel Data," Working Papers 202209, University of California at Riverside, Department of Economics, revised Apr 2022.
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    37. Tumala, Mohammed M & Olubusoye, Olusanya E & Yaaba, Baba N & Yaya, OlaOluwa S & Akanbi, Olawale B, 2017. "Investigating Predictors of Inflation in Nigeria: BMA and WALS Techniques," MPRA Paper 88773, University Library of Munich, Germany, revised Feb 2018.
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    40. Dardanoni, Valentino & De Luca, Giuseppe & Modica, Salvatore & Peracchi, Franco, 2015. "Model averaging estimation of generalized linear models with imputed covariates," Journal of Econometrics, Elsevier, vol. 184(2), pages 452-463.
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  6. J. Durbin & B. Quenneville, 1997. "Benchmarking by State Space Models," International Statistical Review, International Statistical Institute, vol. 65(1), pages 23-48, April.

    Cited by:

    1. Luiz Cerqueira & Adrian Pizzinga & Cristiano Fernandes, 2009. "Methodological Procedure for Estimating Brazilian Quarterly GDP Series," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 15(1), pages 102-114, February.
    2. Baoline Chen, 2007. "An Empirical Comparison of Methods for Temporal Distribution and Interpolation at the National Accounts," BEA Papers 0077, Bureau of Economic Analysis.
    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. Christian Caamaño-Carrillo & Sergio Contreras-Espinoza & Orietta Nicolis, 2023. "Reconstructing the Quarterly Series of the Chilean Gross Domestic Product Using a State Space Approach," Mathematics, MDPI, vol. 11(8), pages 1-14, April.
    5. Danny Pfeffermann & Anna Sikov & Richard Tiller, 2014. "Single- and two-stage cross-sectional and time series benchmarking procedures for small area estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(4), pages 631-666, December.
    6. José Casals & Miguel Jerez & Sonia Sotoca, 2009. "Modelling and forecasting time series sampled at different frequencies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(4), pages 316-342.
    7. Findley, David F. & Potscher, Benedikt M. & Wei, Ching-Zong, 2004. "Modeling of time series arrays by multistep prediction or likelihood methods," Journal of Econometrics, Elsevier, vol. 118(1-2), pages 151-187.
    8. Adrian Pizzinga, 2010. "Constrained Kalman Filtering: Additional Results," International Statistical Review, International Statistical Institute, vol. 78(2), pages 189-208, August.
    9. Pizzinga, Adrian, 2009. "Further investigation into restricted Kalman filtering," Statistics & Probability Letters, Elsevier, vol. 79(2), pages 264-269, January.
    10. M. D. Ugarte & A. F. Militino & T. Goicoa, 2008. "Adjusting economic estimates in business surveys," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(11), pages 1253-1265.
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    14. Homesh Sayal & John A. D. Aston & Duncan Elliott & Hernando Ombao, 2017. "An introduction to applications of wavelet benchmarking with seasonal adjustment," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(3), pages 863-889, June.
    15. Weigand Roland & Wanger Susanne & Zapf Ines, 2018. "Factor Structural Time Series Models for Official Statistics with an Application to Hours Worked in Germany," Journal of Official Statistics, Sciendo, vol. 34(1), pages 265-301, March.
    16. 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.
    17. M. Ugarte & A. Militino & T. Goicoa, 2009. "Benchmarked estimates in small areas using linear mixed models with restrictions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(2), pages 342-364, August.

  7. John Kingman & J. Durbin & David Cox & M. J. R. Healy, 1988. "Appendix: Statistical Requirements of the AIDS Epidemic," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 151(1), pages 127-130, January.

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    1. Sylvia Richardson, 2022. "Statistics in times of increasing uncertainty," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1471-1496, October.

  8. Durbin, James, 1988. "Maximum Likelihood Estimation of the Parameters of a System of Simultaneous Regression Equations," Econometric Theory, Cambridge University Press, vol. 4(1), pages 159-170, April.

    Cited by:

    1. Maria Kyriacou & Peter C.B. Phillips & Francesca Rossi, 2019. "Continuously Updated Indirect Inference in Heteroskedastic Spatial Models," Working Papers 15/2019, University of Verona, Department of Economics.
    2. Calzolari, Giorgio, 2012. "Econometric notes," MPRA Paper 36765, University Library of Munich, Germany.
    3. Oya, Kosuke & Morimune, Kimio, 1992. "The distribution of the full information maximum likelihood estimator," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 33(5), pages 569-574.
    4. Charles G. Renfro, 2009. "The Practice of Econometric Theory," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75571-5, July-Dece.
    5. Richard Sweeney, 2014. "Equivalent valuations in cash flow and accounting models," Review of Quantitative Finance and Accounting, Springer, vol. 42(1), pages 29-49, January.
    6. Mala Raghavan & George Athanasopoulos & Param Silvapulle, 2009. "VARMA models for Malaysian Monetary Policy Analysis," Monash Econometrics and Business Statistics Working Papers 6/09, Monash University, Department of Econometrics and Business Statistics.
    7. David F. Hendry & Peter C.B. Phillips, 2017. "John Denis Sargan at the London School of Economics," Cowles Foundation Discussion Papers 2082, Cowles Foundation for Research in Economics, Yale University.

  9. Durbin, J, 1970. "An Alternative to the Bounds Test for Testing for Serial Correlation in Least-Squares Regression," Econometrica, Econometric Society, vol. 38(3), pages 422-429, May.

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    1. Martellosio, Federico, 2008. "Power Properties of Invariant Tests for Spatial Autocorrelation in Linear Regression," MPRA Paper 7255, University Library of Munich, Germany.
    2. Dubbelman, C., 1971. "A Priori Fixed Covariance Matrices Of Disturbance Estimators," Econometric Institute Archives 272044, Erasmus University Rotterdam.
    3. Aihara, Yasuaki, 1988. "International comparison of causal relationships among selected social indicators and economic welfare," ISU General Staff Papers 1988010108000017609, Iowa State University, Department of Economics.
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  10. Durbin, J, 1970. "Testing for Serial Correlation in Least-Squares Regression When Some of the Regressors are Lagged Dependent Variables," Econometrica, Econometric Society, vol. 38(3), pages 410-421, May.

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    Cited by:

    1. A. Chaudhuri, 1975. "A simple method of sampling without replacement with inclusion-probabilities exactly proportional to size," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 22(1), pages 147-152, December.

Chapters

    Sorry, no citations of chapters recorded.

Books

  1. Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543, Decembrie.

    Cited by:

    1. Taylor, Alan M. & Grimm, Maximilian & Jordà , Òscar & Schularick, Moritz, 2023. "Loose monetary policy and financial instability," CEPR Discussion Papers 17896, C.E.P.R. Discussion Papers.
    2. Victor Bystrov, 2018. "Measuring the Natural Rates of Interest in Germany and Italy," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 10(4), pages 333-353, December.
    3. Florian Heiss, 2008. "Sequential numerical integration in nonlinear state space models for microeconometric panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 373-389.
    4. Yukai Yang & Luc Bauwens, 2018. "State-Space Models on the Stiefel Manifold with a New Approach to Nonlinear Filtering," Econometrics, MDPI, vol. 6(4), pages 1-22, December.
    5. Sbrana, Giacomo & Silvestrini, Andrea, 2020. "Forecasting with the damped trend model using the structural approach," International Journal of Production Economics, Elsevier, vol. 226(C).
    6. Maria A. Arias & Charles S. Gascon & David E. Rapach, 2014. "Metro Business Cycles," Working Papers 2014-46, Federal Reserve Bank of St. Louis.
    7. Fernando Tusell, 2008. "An Introduction to State Space Time Series Analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(3), pages 756-757, June.
    8. Helske, Jouni, 2017. "KFAS: Exponential Family State Space Models in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 78(i10).
    9. Dainauskas, Justas, 2023. "Time-varying exchange rate pass-through into terms of trade," LSE Research Online Documents on Economics 120000, London School of Economics and Political Science, LSE Library.
    10. Fernández-Macho, Javier, 2008. "Spectral estimation of a structural thin-plate smoothing model," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 189-195, September.
    11. Alastair Cunningham & Jana Eklund & Christopher Jeffery & George Kapetanios & Vincent Labhard, 2007. "A state space approach to extracting the signal from uncertain data," Bank of England working papers 336, Bank of England.
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    161. Tucker McElroy & Brian Monsell, 2015. "Model Estimation, Prediction, and Signal Extraction for Nonstationary Stock and Flow Time Series Observed at Mixed Frequencies," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 1284-1303, September.
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    166. Siem Jan Koopman & Andre Lucas & Bernd Schwaab, 2010. "Macro, Industry and Frailty Effects in Defaults: The 2008 Credit Crisis in Perspective," Tinbergen Institute Discussion Papers 10-004/2, Tinbergen Institute, revised 24 Aug 2010.
    167. Carmen Broto & Esther Ruiz, 2008. "Testing for conditional heteroscedasticity in the components of inflation," Working Papers 0812, Banco de España.
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    181. Siem Jan Koopman & Philip Hans Franses, 2002. "Constructing Seasonally Adjusted Data with Time‐varying Confidence Intervals," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(5), pages 509-526, December.
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    203. Konrad Banachewicz & André Lucas, 2007. "Quantile Forecasting for Credit Risk Management using possibly Mis-specified Hidden Markov Models," Tinbergen Institute Discussion Papers 07-046/2, Tinbergen Institute.
    204. Blasques, Francisco & Koopman, Siem Jan & Nientker, Marc, 2022. "A time-varying parameter model for local explosions," Journal of Econometrics, Elsevier, vol. 227(1), pages 65-84.
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    209. Michael Hirsch & Richard Wareham & Ji W Yoon & Daniel J Rolfe & Laura C Zanetti-Domingues & Michael P Hobson & Peter J Parker & Marisa L Martin-Fernandez & Sumeetpal S Singh, 2019. "A global sampler of single particle tracking solutions for single molecule microscopy," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-21, October.
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    215. Siem Jan Koopman & Joao Valle e Azevedo, 2003. "Measuring Synchronisation and Convergence of Business Cycles," Tinbergen Institute Discussion Papers 03-052/4, Tinbergen Institute.
    216. Lenza, Michele & Cimadomo, Jacopo & Giannone, Domenico & Monti, Francesca & Sokol, Andrej, 2021. "Nowcasting with Large Bayesian Vector Autoregressions," CEPR Discussion Papers 15854, C.E.P.R. Discussion Papers.
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    230. 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.
    231. Siem Jan Koopman & Rutger Lit & Thuy Minh Nguyen, 2012. "Fast Efficient Importance Sampling by State Space Methods," Tinbergen Institute Discussion Papers 12-008/4, Tinbergen Institute, revised 16 Oct 2014.
    232. 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].
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    245. Jarocinski, Marek, 2014. "A note on implementing the Durbin and Koopman simulation smoother," MPRA Paper 59466, University Library of Munich, Germany.
    246. Samuel Standaert & Glenn Rayp, 2015. "Trade Integration And Trade Agreements:Resolving The Endogeneity Problem Through A Qualitative Var," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 15/912, Ghent University, Faculty of Economics and Business Administration.
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    255. Lorenzo Pozzi, 2007. "Idiosyncratic Labour Income Risk and Aggregate Consumption: an Unobserved Component Approach," Tinbergen Institute Discussion Papers 07-069/2, Tinbergen Institute.
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    407. George B. Tawadros, 2009. "Testing the impact of inflation targeting on inflation," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 36(4), pages 326-342, September.
    408. Frühwirth-Schnatter, Sylvia & Wagner, Helga, 2008. "Marginal likelihoods for non-Gaussian models using auxiliary mixture sampling," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4608-4624, June.
    409. Bianchi, Francesco & Bianchi, Giada & Song, Dongho, 2023. "The long-term impact of the COVID-19 unemployment shock on life expectancy and mortality rates," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    410. Gianluca Moretti & Giulio Nicoletti, 2010. "Estimating DSGE models with unknown data persistence," Temi di discussione (Economic working papers) 750, Bank of Italy, Economic Research and International Relations Area.
    411. Gabriele Fiorentini & Enrique Sentana, 2013. "Dynamic Specification Tests for Dynamic Factor Models," Working Papers wp2013_1306, CEMFI.
    412. Siem Jan Koopman & Eugenie Hol Uspensky, 2002. "The stochastic volatility in mean model: empirical evidence from international stock markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(6), pages 667-689, December.
    413. Søren Johansen & Morten Nyboe Tabor, 2017. "Cointegration between trends and their estimators in state space models and CVAR models," Discussion Papers 17-02, University of Copenhagen. Department of Economics.
    414. Cem Cakmakli & Hamza Demircan & Sumru Altug, 2019. "Modeling of Economic and Financial Conditions for Nowcasting and Forecasting Recessions: A Unified Approach," Koç University-TUSIAD Economic Research Forum Working Papers 1907, Koc University-TUSIAD Economic Research Forum.
    415. Corradin, Stefano & Grimm, Niklas & Schwaab, Bernd, 2021. "Euro area sovereign bond risk premia during the Covid-19 pandemic," Working Paper Series 2561, European Central Bank.
    416. Krist'of N'emeth & D'aniel Hadh'azi, 2023. "GDP nowcasting with artificial neural networks: How much does long-term memory matter?," Papers 2304.05805, arXiv.org, revised Feb 2024.
    417. Refai, Hisham Al & Zeitun, Rami & Eissa, Mohamed Abdel-Aziz, 2022. "Impact of global health crisis and oil price shocks on stock markets in the GCC," Finance Research Letters, Elsevier, vol. 45(C).
    418. Li, Mengheng & Koopman, Siem Jan & Lit, Rutger & Petrova, Desislava, 2020. "Long-term forecasting of El Niño events via dynamic factor simulations," Journal of Econometrics, Elsevier, vol. 214(1), pages 46-66.
    419. Klaus Wohlrabe, 2009. "Macroeconomic forecasting with mixed frequencies," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(21), pages 22-33, November.
    420. In Choi, 2023. "Does climate change affect economic data?," Empirical Economics, Springer, vol. 64(6), pages 2939-2956, June.
    421. Johan Dahlin & Mattias Villani & Thomas B. Schon, 2015. "Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods," Papers 1506.06975, arXiv.org, revised Jun 2017.
    422. Gijsbert Suren & Guilherme Moura, 2012. "Heteroskedastic Dynamic Factor Models: A Monte Carlo Study," Economics Bulletin, AccessEcon, vol. 32(4), pages 2884-2898.
    423. Andrew Lee-Poy, 2018. "Characterizing the Canadian Financial Cycle with Frequency Filtering Approaches," Staff Analytical Notes 2018-34, Bank of Canada.
    424. Arslanturk, Yalcin & Balcilar, Mehmet & Ozdemir, Zeynel Abidin, 2011. "Time-varying linkages between tourism receipts and economic growth in a small open economy," Economic Modelling, Elsevier, vol. 28(1), pages 664-671.
    425. Iseringhausen, Martin, 2024. "A time-varying skewness model for Growth-at-Risk," International Journal of Forecasting, Elsevier, vol. 40(1), pages 229-246.
    426. Heather M. Anderson & Chin Nam Low, 2006. "Random Walk Smooth Transition Autoregressive Models," Contributions to Economic Analysis, in: Nonlinear Time Series Analysis of Business Cycles, pages 247-281, Emerald Group Publishing Limited.
    427. Siem Jan Koopman & Marcel Scharth, 2011. "The Analysis of Stochastic Volatility in the Presence of Daily Realised Measures," Tinbergen Institute Discussion Papers 11-132/4, Tinbergen Institute.
    428. Schalk Burger & Searle Silverman & Gary van Vuuren, 2018. "Deriving Correlation Matrices for Missing Financial Time-Series Data," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(10), pages 105-105, October.
    429. Georges Prat & David Le Bris, 2019. "Equity Risk Premium and Time Horizon: what do the French secular data say ?," EconomiX Working Papers 2019-8, University of Paris Nanterre, EconomiX.
    430. Cartea, Álvaro & Karyampas, Dimitrios, 2009. "Volatility and covariation of financial assets: a high-frequency analysis," DEE - Working Papers. Business Economics. WB wb097609, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    431. Shahidul Islam & Subhadip Ghosh & Mohua Podder, 2022. "Fifty years of agricultural development in Bangladesh: a comparison with India and Pakistan," SN Business & Economics, Springer, vol. 2(7), pages 1-41, July.
    432. Corradini, Riccardo, 2018. "A set of state space models at an high disaggregation level to forecast Italian Industrial Production," MPRA Paper 84558, University Library of Munich, Germany, revised 12 Feb 2018.
    433. Bashar, Omar H. M. N. & Bashar, Omar K. M. R., 2020. "Resource abundance, financial crisis and economic growth: did resource-rich countries fare better during the global financial crisis?," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(2), April.
    434. Stefano Grassi & Paolo Santucci de Magistris, 2013. "It’s all about volatility (of volatility): evidence from a two-factor stochastic volatility model," CREATES Research Papers 2013-03, Department of Economics and Business Economics, Aarhus University.
    435. 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.
    436. Siem Jan Koopman & André Lucas & Bernd Schwaab, 2008. "Forecasting Cross-Sections of Frailty-Correlated Default," Tinbergen Institute Discussion Papers 08-029/4, Tinbergen Institute.
    437. 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.
    438. Darolles, Serge & Francq, Christian & Laurent, Sébastien, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Journal of Econometrics, Elsevier, vol. 204(2), pages 223-247.
    439. Geert Mesters & Victor van der Geest & Catrien Bijleveld, 2014. "Crime, Employment and Social Welfare: an Individual-level Study on Disadvantaged Males," Tinbergen Institute Discussion Papers 14-091/III, Tinbergen Institute.
    440. Clegg, Matthew & Krauss, Christopher, 2016. "Pairs trading with partial cointegration," FAU Discussion Papers in Economics 05/2016, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    441. Sy-Miin Chow & Zhaohua Lu & Andrew Sherwood & Hongtu Zhu, 2016. "Fitting Nonlinear Ordinary Differential Equation Models with Random Effects and Unknown Initial Conditions Using the Stochastic Approximation Expectation–Maximization (SAEM) Algorithm," Psychometrika, Springer;The Psychometric Society, vol. 81(1), pages 102-134, March.
    442. Rob J. Hyndman & Yeasmin Khandakar, 2007. "Automatic time series forecasting: the forecast package for R," Monash Econometrics and Business Statistics Working Papers 6/07, Monash University, Department of Econometrics and Business Statistics.
    443. Siem Jan Koopman & André Lucas & Pieter Klaassen, 2002. "Pro-Cyclicality, Empirical Credit Cycles, and Capital Buffer Formation," Tinbergen Institute Discussion Papers 02-107/2, Tinbergen Institute.
    444. Nonejad, Nima, 2021. "Predicting equity premium using dynamic model averaging. Does the state–space representation matter?," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    445. 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.
    446. Heimberger, Philipp & Kapeller, Jakob & Schütz, Bernhard, 2017. "The NAIRU determinants: What’s structural about unemployment in Europe?," Journal of Policy Modeling, Elsevier, vol. 39(5), pages 883-908.
    447. S. Boragan Aruoba, 2014. "Term Structures of Inflation Expectations and Real Interest Rates: The Effects of Unconventional Monetary Policy," Staff Report 502, Federal Reserve Bank of Minneapolis.
    448. Pettenuzzo, Davide & Sabbatucci, Riccardo & Timmermann, Allan, 2023. "Dividend suspensions and cash flows during the Covid-19 pandemic: A dynamic econometric model," Journal of Econometrics, Elsevier, vol. 235(2), pages 1522-1541.
    449. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2011. "Systemic risk diagnostics: coincident indicators and early warning signals," Working Paper Series 1327, European Central Bank.
    450. Yasuhiro Omori & Siddhartha Chib & Neil Shephard & Jouchi Nakajima, 2004. "Stochastic Volatility with Leverage: Fast Likelihood Inference," CIRJE F-Series CIRJE-F-297, CIRJE, Faculty of Economics, University of Tokyo.
    451. 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.
    452. Fernando Antonio Lucena Aiube & Ariel Levy, 2019. "Recent movement of oil prices and future scenarios [Movimentos recentes dos preços do petróleo e os cenários futuros]," Nova Economia, Economics Department, Universidade Federal de Minas Gerais (Brazil), vol. 29(1), pages 223-248, January-A.
    453. Jaime Casassus & Peng Liu & Ke Tang, 2011. "Relative Scarcity of Commodities with a Long-Term Economic Relationship and the Correlation of Futures Returns," Documentos de Trabajo 404, Instituto de Economia. Pontificia Universidad Católica de Chile..
    454. Oleg Rytchkov, 2012. "Filtering Out Expected Dividends and Expected Returns," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 2(03), pages 1-56.
    455. Christian Bayer & Benjamin Born & Ralph Luetticke, 2021. "The Liquidity Channel of Fiscal Policy," ifo Working Paper Series 351, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    456. Johannes Huber, 2022. "An Augmented Steady-State Kalman Filter to Evaluate the Likelihood of Linear and Time-Invariant State-Space Models," Discussion Paper Series 343, Universitaet Augsburg, Institute for Economics.
    457. Andersson, Fredrik N. G. & Li, Yushu, 2014. "Are Central Bankers Inflation Nutters? - A Bayesian MCMC Estimator of the Long Memory Parameter in a State Space Model," Discussion Papers 2014/38, Norwegian School of Economics, Department of Business and Management Science.
    458. Matthieu Lemoine & Florian Pelgrin, 2003. "Introduction aux modèles espace-état et au filtre de Kalman," Revue de l'OFCE, Presses de Sciences-Po, vol. 86(3), pages 203-229.
    459. George Kapetanios & Elias Tzavalis, 2006. "Stochastic Volatility Driven by Large Shocks," Working Papers 568, Queen Mary University of London, School of Economics and Finance.
    460. Scott A. Brave & R. Andrew Butters & David Kelley, 2019. "A New “Big Data” Index of U.S. Economic Activity," Economic Perspectives, Federal Reserve Bank of Chicago, issue 1, pages 1-30.
    461. Chansu Lim, 2019. "Estimating Residential and Industrial City Gas Demand Function in the Republic of Korea—A Kalman Filter Application," Sustainability, MDPI, vol. 11(5), pages 1-12, March.
    462. Tommaso Proietti, 2006. "Measuring Core Inflation by Multivariate Structural Time Series Models," CEIS Research Paper 83, Tor Vergata University, CEIS.
    463. Sampi Bravo,James Robert Ezequiel & Jooste,Charl, 2020. "Nowcasting Economic Activity in Times of COVID-19 : An Approximation from the Google Community Mobility Report," Policy Research Working Paper Series 9247, The World Bank.
    464. Rojas, Helder & Dias, David, 2021. "Transfer of macroeconomic shocks in stress tests modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    465. Neha Saini & Anil Kumar Mittal, 2019. "On the predictive ability of GARCH and SV models of volatility: An empirical test on the SENSEX index," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 8(4), pages 1-5.
    466. Martha Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Nowcasting," Working Papers ECARES ECARES 2010-021, ULB -- Universite Libre de Bruxelles.
    467. John C. Frain, 2004. "Inflation and Money Growth - Evidence from a Multi-Country Data-Set," The Economic and Social Review, Economic and Social Studies, vol. 35(3), pages 251-266.
    468. Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2012. "Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models," Tinbergen Institute Discussion Papers 12-020/4, Tinbergen Institute.
    469. Jacek Kwiatkowski, 2008. "Bayesian Analysis of Polish Inflation Rates Using RCA and GLL Models," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 8, pages 129-138.
    470. 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.
    471. 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.
    472. Luke Mosley & Tak-Shing Chan & Alex Gibberd, 2023. "sparseDFM: An R Package to Estimate Dynamic Factor Models with Sparse Loadings," Papers 2303.14125, arXiv.org.
    473. 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.
    474. S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2007. "Real-Time Measurement of Business Conditions, Second Version," PIER Working Paper Archive 08-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 04 Apr 2008.
    475. Stephanie R. Clark & Dan Pagendam & Louise Ryan, 2022. "Forecasting Multiple Groundwater Time Series with Local and Global Deep Learning Networks," IJERPH, MDPI, vol. 19(9), pages 1-31, April.
    476. 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.
    477. Arnaud Doucet & Neil Shephard, 2012. "Robust inference on parameters via particle filters and sandwich covariance matrices," Economics Papers 2012-W05, Economics Group, Nuffield College, University of Oxford.
    478. Chan, Ying Tung & Qiao, Hui, 2023. "Volatility spillover between oil and stock prices: Structural connectedness based on a multi-sector DSGE model approach with Bayesian estimation," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 265-286.
    479. 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.
    480. Dat T. Pham & Adam D. Switzer & Gabriel Huerta & Aron J. Meltzner & Huan M. Nguyen & Emma M. Hill, 2019. "Spatiotemporal variations of extreme sea levels around the South China Sea: assessing the influence of tropical cyclones, monsoons and major climate modes," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 98(3), pages 969-1001, September.
    481. Paolo Agnolucci & Vincenzo De Lipsis, 2020. "Long-run trend in agricultural yield and climatic factors in Europe," Climatic Change, Springer, vol. 159(3), pages 385-405, April.
    482. Alexander Kreuzer & Luciana Dalla Valle & Claudia Czado, 2022. "A Bayesian non‐linear state space copula model for air pollution in Beijing," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 613-638, June.
    483. Stephen G. Hall & P. A. V. B. Swamy & George S. Tavlas, 2014. "Time Varying Coefficient Models; A Proposal for selecting the Coefficient Driver Sets," Discussion Papers in Economics 14/18, Division of Economics, School of Business, University of Leicester.
    484. Guillochon, Justine & Le Roux, Julien, 2023. "Unobserved components model(s): output gaps and financial cycles," Working Paper Series 2832, European Central Bank.
    485. Paul Knottnerus, 2016. "On new variance approximations for linear models with inequality constraints," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(1), pages 26-46, February.
    486. Diebold, F.X. & Kilian, L. & Nerlove, Marc, 2006. "Time Series Analysis," Working Papers 28556, University of Maryland, Department of Agricultural and Resource Economics.
    487. Jmaes McNeil, 2020. "Monetary policy and the term structure of Inflation expectations with information frictions," Working Papers daleconwp2020-07, Dalhousie University, Department of Economics.
    488. Inkyu Kang, 2023. "How does technology‐based monitoring affect street‐level bureaucrats' behavior? An analysis of body‐worn cameras and police actions," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 42(4), pages 971-991, September.
    489. 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.
    490. Castillo-Manzano, José I. & Castro-Nuño, Mercedes & González-Laxe, Fernando & Pedregal, Diego J., 2018. "Legal reform and the devolution of the Spanish Port System: An econometric assessment," Utilities Policy, Elsevier, vol. 50(C), pages 73-82.
    491. Gary Koop & Roberto Leon-Gonzalez & Rodney W. Strachan, 2008. "Dynamic probabilities of restrictions in state space models: An application to the Phillips curve," Working Paper series 26_08, Rimini Centre for Economic Analysis.
    492. Alicia Rambaldi & Ryan McAllister & Kerry Collins & Cameron Fletcher, 2011. "An Unobserved Components Approach to Separating Land from Structure in Property Prices: A Case Study for the City of Brisbane," Discussion Papers Series 428, School of Economics, University of Queensland, Australia.
    493. Ilka van de Werve & Siem Jan Koopman, 2022. "Finding the European crime drop using a panel data model with stochastic trends," Tinbergen Institute Discussion Papers 22-089/III, Tinbergen Institute.
    494. 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.
    495. Siem Jan Koopman & André Lucas, 2005. "Business and default cycles for credit risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 311-323.
    496. Dimitrios Thomakos & Hossein Hassani & Kerry Patterson, 2013. "Optimal Linear Filtering, Smoothing and Trend Extraction for the m-th Differences of a Unit Root Process: A Singular Spectrum Analysis Approach," Economics Discussion Papers em-dp2013-04, Department of Economics, University of Reading.
    497. Pizzinga, Adrian & Fernandes, Cristiano & Contreras, Sergio, 2008. "Restricted Kalman filtering revisited," Journal of Econometrics, Elsevier, vol. 144(2), pages 428-429, June.
    498. Strid, Ingvar, 2010. "Efficient parallelisation of Metropolis-Hastings algorithms using a prefetching approach," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2814-2835, November.
    499. Ulm, M. & Hambuckers, J., 2022. "Do interest rate differentials drive the volatility of exchange rates? Evidence from an extended stochastic volatility model," Journal of Empirical Finance, Elsevier, vol. 65(C), pages 125-148.
    500. 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.
    501. Josef Arlt & Petr Pokorný, 2006. "Model nepozorovaných komponent a jeho využití při identifikaci společných trendů časových řad [The model of unobservable components and its use for identification of time series common trends]," Politická ekonomie, Prague University of Economics and Business, vol. 2006(1), pages 48-55.
    502. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2006. "Dynamic Factor GARCH: Multivariate Volatility Forecast for a Large Number of Series," LEM Papers Series 2006/25, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    503. Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2011. "Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State Space Models," Tinbergen Institute Discussion Papers 11-057/4, Tinbergen Institute, revised 27 Jan 2012.
    504. Alexander Tsyplakov, 2011. "An introduction to state space modeling (in Russian)," Quantile, Quantile, issue 9, pages 1-24, July.
    505. Martin Wagner, 2010. "Cointegration analysis with state space models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 94(3), pages 273-305, September.
    506. Fulop, Andras & Li, Junye, 2013. "Efficient learning via simulation: A marginalized resample-move approach," Journal of Econometrics, Elsevier, vol. 176(2), pages 146-161.
    507. Hall, Viv & Thomson, Peter & McKelvie, Stuart, 2015. "On trend robustness and end-point issues for New Zealand’s stylised business cycle facts," Working Paper Series 18867, Victoria University of Wellington, School of Economics and Finance.
    508. Bruche, Max, 2005. "Estimating structural bond pricing models via simulated maximum likelihood," LSE Research Online Documents on Economics 24647, London School of Economics and Political Science, LSE Library.
    509. Dr. Alain Galli, 2017. "Which indicators matter? Analyzing the Swiss business cycle using a large-scale mixed-frequency dynamic factor model," Working Papers 2017-08, Swiss National Bank.
    510. Boril Šopov & Jakub Seidler, 2010. "Yield Curve Dynamics: Regional Common Factor Model," Working Papers IES 2010/17, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Aug 2010.
    511. Francesco Calvori & Drew Creal & Siem Jan Koopman & Andre Lucas, 2014. "Testing for Parameter Instability in Competing Modeling Frameworks," Tinbergen Institute Discussion Papers 14-010/IV/DSF71, Tinbergen Institute.
    512. Trapero, Juan R. & Pedregal, Diego J., 2016. "A novel time-varying bullwhip effect metric: An application to promotional sales," International Journal of Production Economics, Elsevier, vol. 182(C), pages 465-471.
    513. Tsuruoka, Yuriko & Tamura, Yoshiyasu & Shibasaki, Ryosuke, 2007. "Reciprocal contribution analysis of the left and right hips while walking," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 535-541.
    514. Benjamin Avanzi & Gregory Clive Taylor & Phuong Anh Vu & Bernard Wong, 2020. "A multivariate evolutionary generalised linear model framework with adaptive estimation for claims reserving," Papers 2004.06880, arXiv.org.
    515. Olivier Filatriau & Frédéric Reynés, 2012. "A new estimate of discouraged and additional worker effects on labor participation by sex and age in OECD countries," Working Papers hal-03476015, HAL.
    516. 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.
    517. Francesco Furlanetto & Paolo Gelain & Marzie Sanjani, 2020. "Output Gap, Monetary Policy Trade-offs, and Financial Frictions," Working Papers 20-05, Federal Reserve Bank of Cleveland.
    518. Sy-Miin Chow & Jungmin Lee & Abe D. Hofman & Han L. J. Maas & Dennis K. Pearl & Peter C. M. Molenaar, 2022. "Control Theory Forecasts of Optimal Training Dosage to Facilitate Children’s Arithmetic Learning in a Digital Educational Application," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 559-592, June.
    519. Arlene Naranjo & A. Alexandre Trindade & George Casella, 2013. "Extending the State-Space Model to Accommodate Missing Values in Responses and Covariates," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(501), pages 202-216, March.
    520. Steffen Hitzemann & Marliese Uhrig-Homburg, 2019. "Empirical performance of reduced-form models for emission permit prices," Review of Derivatives Research, Springer, vol. 22(3), pages 389-418, October.
    521. James H. Stock & Mark W. Watson, 2017. "Twenty Years of Time Series Econometrics in Ten Pictures," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 59-86, Spring.
    522. Juan C. Méndez-Vizcaíno & Alexander Guarin & César Anzola-Bravo & Anderson Grajales-Olarte, 2021. "Characterizing and Communicating the Balance of Risks of Macroeconomic Forecasts: A Predictive Density Approach for Colombia," Borradores de Economia 1178, Banco de la Republica de Colombia.
    523. 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.
    524. 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.
    525. Manabu Asai & Chia-Lin Chang & Michael McAleer, 2016. "Realized Matrix-Exponential Stochastic Volatility with Asymmetry, Long Memory and Spillovers," Documentos de Trabajo del ICAE 2016-15, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    526. MORI Tomoya & MURAKAMI Daisuke, 2024. "The Rise and Fall of Cities under Declining Population and Diminishing Distance Frictions: The case of Japan," Discussion papers 24028, Research Institute of Economy, Trade and Industry (RIETI).
    527. Charles F. Nicholson & Mark W. Stephenson, 2015. "Milk Price Cycles in the U.S. Dairy Supply Chain and Their Management Implications," Agribusiness, John Wiley & Sons, Ltd., vol. 31(4), pages 507-520, October.
    528. Timo Baas & Marjan Aikimbaeva, 2016. "Macroeconomic Stability and the Single European Labor Market," EcoMod2016 9555, EcoMod.
    529. Luis Uzeda, 2018. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Staff Working Papers 18-14, Bank of Canada.
    530. Neil Shephard & Thomas Flury, 2009. "Learning and filtering via simulation: smoothly jittered particle filters," Economics Series Working Papers 469, University of Oxford, Department of Economics.
    531. J. Huston McCulloch, 2005. "The Kalman Foundations of Adaptive Least Squares: Applications to Unemployment and Inflation," Computing in Economics and Finance 2005 239, Society for Computational Economics.
    532. Tommaso Proietti, 2019. "Predictability, Real Time Estimation, and the Formulation of Unobserved Components Models," CEIS Research Paper 455, Tor Vergata University, CEIS, revised 22 Mar 2019.
    533. 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.
    534. Harvey, Andrew, 2021. "Time Series Modelling Of Epidemics: Leading Indicators, Control Groups And Policy Assessment," National Institute Economic Review, National Institute of Economic and Social Research, vol. 257, pages 83-100, August.
    535. Tobias Adrian & Francesco Franzoni, 2008. "Learning about beta: time-varying factor loadings, expected returns, and the conditional CAPM," Staff Reports 193, Federal Reserve Bank of New York.
    536. Standaert, Samuel, 2015. "Divining the level of corruption: A Bayesian state-space approach," Journal of Comparative Economics, Elsevier, vol. 43(3), pages 782-803.
    537. Alexandre Ounnas, 2020. "Worker Flows and Occupations in the CPS 1976-2010: A Framework for Adjusting the Data," LIDAM Discussion Papers IRES 2020008, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    538. Shephard, Neil & Xiu, Dacheng, 2017. "Econometric analysis of multivariate realised QML: Estimation of the covariation of equity prices under asynchronous trading," Journal of Econometrics, Elsevier, vol. 201(1), pages 19-42.
    539. Haque, M. Ohidul & Haque, Tariq H., 2018. "Evaluating the effects of the road safety system approach in Brunei," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 594-607.
    540. Díaz, Guzmán & Gómez-Aleixandre, Javier & Coto, José, 2016. "Wind power scenario generation through state-space specifications for uncertainty analysis of wind power plants," Applied Energy, Elsevier, vol. 162(C), pages 21-30.
    541. Hahn, William F. & Jones, Keithly G. & Davis, Christopher G., 2003. "Levels or Differences in Meat Demand Specification," 2003 Annual meeting, July 27-30, Montreal, Canada 21896, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    542. Kuzin, Vladimir, 2006. "The inflation aversion of the Bundesbank: A state space approach," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1671-1686.
    543. Håvard Hungnes, 2012. "Testing for co-non-linearity," Discussion Papers 699, Statistics Norway, Research Department.
    544. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    545. Fernando Antonio Lucena Aiube & Carlos Patricio Samanez & Tara Keshar Nanda Baidya & Larissa de Oliveira Resende, 2017. "Evaluating the risk premium in the U.S.A. natural gas market: evidence from low-price regime," Applied Economics, Taylor & Francis Journals, vol. 49(9), pages 860-871, February.
    546. Majewski, Adam A. & Ciliberti, Stefano & Bouchaud, Jean-Philippe, 2020. "Co-existence of trend and value in financial markets: Estimating an extended Chiarella model," Journal of Economic Dynamics and Control, Elsevier, vol. 112(C).
    547. Zirogiannis, Nikolaos & Tripodis, Yorghos, 2014. "Dynamic Factor Analysis for Short Panels: Estimating Performance Trajectories for Water Utilities," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170592, Agricultural and Applied Economics Association.
    548. V. Dordonnat & S.J. Koopman & M. Ooms & A. Dessertaine & J. Collet, 2008. "An Hourly Periodic State Space Model for Modelling French National Electricity Load," Tinbergen Institute Discussion Papers 08-008/4, Tinbergen Institute.
    549. Huttunen, J.M.J. & Kaipio, J.P. & Haario, H., 2018. "Approximation error approach in spatiotemporally chaotic models with application to Kuramoto–Sivashinsky equation," Computational Statistics & Data Analysis, Elsevier, vol. 123(C), pages 13-31.
    550. Bógalo, Juan & Llada, Martín & Poncela, Pilar & Senra, Eva, 2022. "Seasonality in COVID-19 times," Economics Letters, Elsevier, vol. 211(C).
    551. Francis X. Diebold, 2020. "Real-Time Real Economic Activity: Exiting the Great Recession and Entering the Pandemic Recession," NBER Working Papers 27482, National Bureau of Economic Research, Inc.
    552. Giulio Bottazzi & Francesco Cordoni & Giulia Livieri & Stefano Marmi, 2020. "Stock Recommendations from Stochastic Discounted Cash Flows," LEM Papers Series 2020/17, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    553. Bohl, Martin T. & Kaufmann, Philipp & Stephan, Patrick M., 2013. "From hero to zero: Evidence of performance reversal and speculative bubbles in German renewable energy stocks," Energy Economics, Elsevier, vol. 37(C), pages 40-51.
    554. Nima Nonejad, 2021. "Using the conditional volatility channel to improve the accuracy of aggregate equity return predictions," Empirical Economics, Springer, vol. 61(2), pages 973-1009, August.
    555. Swamy, P.A.V.B. & Mehta, J.S. & Tavlas, G.S. & Hall, S.G., 2015. "Two applications of the random coefficient procedure: Correcting for misspecifications in a small area level model and resolving Simpson's paradox," Economic Modelling, Elsevier, vol. 45(C), pages 93-98.
    556. Hartl, Tobias, 2021. "Monitoring the pandemic: A fractional filter for the COVID-19 contact rate," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242380, Verein für Socialpolitik / German Economic Association.
    557. Andersson, Fredrik N.G. & Li, Yushu, 2013. "How Flexible are the Inflation Targets? A Bayesian MCMC Estimator of the Long Memory Parameter in a State Space Model," Working Papers 2013:38, Lund University, Department of Economics.
    558. Hendershott, Terrence & Menkveld, Albert J., 2014. "Price pressures," Journal of Financial Economics, Elsevier, vol. 114(3), pages 405-423.
    559. Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Impact of jumps on returns and realised variances: econometric analysis of time-deformed Levy processes," Economics Papers 2003-W12, Economics Group, Nuffield College, University of Oxford.
    560. 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.
    561. 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.
    562. Michael Funke & Hao Yu & Aaron Mehrota, 2011. "Tracking Chinese CPI inflation in real time," Quantitative Macroeconomics Working Papers 21112, Hamburg University, Department of Economics.
    563. Milenković, Miloš S. & Bojović, Nebojša J. & Švadlenka, Libor & Melichar, Vlastimil, 2015. "A stochastic model predictive control to heterogeneous rail freight car fleet sizing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 82(C), pages 162-198.
    564. Hideaki Shimazaki & Shun-ichi Amari & Emery N Brown & Sonja Grün, 2012. "State-Space Analysis of Time-Varying Higher-Order Spike Correlation for Multiple Neural Spike Train Data," PLOS Computational Biology, Public Library of Science, vol. 8(3), pages 1-27, March.
    565. Siem Jan Koopman & Michel van der Wel, 2011. "Forecasting the U.S. Term Structure of Interest Rates using a Macroeconomic Smooth Dynamic Factor Model," Tinbergen Institute Discussion Papers 11-063/4, Tinbergen Institute.
    566. 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.
    567. Oksana Bollineni‐Balabay & Jan van den Brakel & Franz Palm & Harm Jan Boonstra, 2017. "Multilevel hierarchical Bayesian versus state space approach in time series small area estimation: the Dutch Travel Survey," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(4), pages 1281-1308, October.
    568. 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.
    569. Obryan Poyser, 2019. "Exploring the dynamics of Bitcoin’s price: a Bayesian structural time series approach," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 9(1), pages 29-60, March.
    570. Zhuo Chen & Bo Yan & Hanwen Kang & Liyu Liu, 2023. "Asymmetric price adjustment and price discovery in spot and futures markets of agricultural commodities," Review of Economic Design, Springer;Society for Economic Design, vol. 27(1), pages 139-162, February.
    571. S. Boragan Aruoba, 2008. "Data Revisions Are Not Well Behaved," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2-3), pages 319-340, March.
    572. Liu, Ping & James Hueng, C., 2017. "Measuring real business condition in China," China Economic Review, Elsevier, vol. 46(C), pages 261-274.
    573. Eric Benhamou, 2019. "Kalman filter demystified: from intuition to probabilistic graphical model to real case in financial markets," Working Papers hal-02012471, HAL.
    574. Eugenie Hol & Siem Jan Koopman & Borus Jungbacker, 2004. "Forecasting daily variability of the S\&P 100 stock index using historical, realised and implied volatility measurements," Computing in Economics and Finance 2004 342, Society for Computational Economics.
    575. Sanjeev Sridharan & Suncica Vujic & Siem Jan Koopman, 2003. "Intervention Time Series Analysis of Crime Rates," Tinbergen Institute Discussion Papers 03-040/4, Tinbergen Institute.
    576. Koopman, Siem Jan & Lucas, André & Schwaab, Bernd, 2011. "Modeling frailty-correlated defaults using many macroeconomic covariates," Journal of Econometrics, Elsevier, vol. 162(2), pages 312-325, June.
    577. André A. Monteiro, 2008. "Parameter Driven Multi-state Duration Models: Simulated vs. Approximate Maximum Likelihood Estimation," Tinbergen Institute Discussion Papers 08-021/2, Tinbergen Institute.
    578. Francis X. Diebold & Glenn D. Rudebusch & S. Boragan Aruoba, 2004. "The Macroeconomy and the Yield Curve: A Dynamic Latent Factor Approach," NBER Working Papers 10616, National Bureau of Economic Research, Inc.
    579. Iacopini, Matteo & Poon, Aubrey & Rossini, Luca & Zhu, Dan, 2023. "Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    580. Joyce, Michael A.S. & Lildholdt, Peter & Sorensen, Steffen, 2010. "Extracting inflation expectations and inflation risk premia from the term structure: A joint model of the UK nominal and real yield curves," Journal of Banking & Finance, Elsevier, vol. 34(2), pages 281-294, February.
    581. Roland Langrock, 2011. "Some applications of nonlinear and non-Gaussian state--space modelling by means of hidden Markov models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(12), pages 2955-2970, March.
    582. Ayman Alzaatreh & Carl Lee & Felix Famoye & Indranil Ghosh, 2016. "The generalized Cauchy family of distributions with applications," Journal of Statistical Distributions and Applications, Springer, vol. 3(1), pages 1-16, December.
    583. Santos, André A.P. & Moura, Guilherme V., 2014. "Dynamic factor multivariate GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 606-617.
    584. Daniel Buncic, 2020. "Econometric issues with Laubach and Williams' estimates of the natural rate of interest," Papers 2002.11583, arXiv.org, revised Aug 2020.
    585. Shepherd, Ben, 2012. "When are adaptive expectations rational? A generalization," Economics Letters, Elsevier, vol. 115(1), pages 4-6.
    586. Andre Lucas & Anne Opschoor & Julia Schaumburg, 2016. "Accounting for Missing Values in Score-Driven Time-Varying Parameter Models," Tinbergen Institute Discussion Papers 16-067/IV, Tinbergen Institute.
    587. 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).
    588. Djennad, Abdelmajid & Rigby, Robert & Stasinopoulos, Dimitrios & Voudouris, Vlasios & Eilers, Paul, 2015. "Beyond location and dispersion models: The Generalized Structural Time Series Model with Applications," MPRA Paper 62807, University Library of Munich, Germany.
    589. Samuel Standaert & Stijn Ronsse & Benjamin Vandermarliere, 2014. "Historical trade integration: Globalization and the distance puzzle in the long 20th century," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 14/897, Ghent University, Faculty of Economics and Business Administration.
    590. Christophe Planas & Alessandro Rossi, 2004. "Can inflation data improve the real-time reliability of output gap estimates?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(1), pages 121-133.
    591. G. Mesters & S. J. Koopman & M. Ooms, 2016. "Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models," Econometric Reviews, Taylor & Francis Journals, vol. 35(4), pages 659-687, April.
    592. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2012. "Common Drifting Volatility in Large Bayesian VARs," CEPR Discussion Papers 8894, C.E.P.R. Discussion Papers.
    593. Istvan Barra & Siem Jan Koopman & Agnieszka Borowska, 2016. "Bayesian Dynamic Modeling of High-Frequency Integer Price Changes," Tinbergen Institute Discussion Papers 16-028/III, Tinbergen Institute, revised 16 Feb 2018.
    594. Bhattacharya, Arnab & Wilson, Simon P., 2018. "Sequential Bayesian inference for static parameters in dynamic state space models," Computational Statistics & Data Analysis, Elsevier, vol. 127(C), pages 187-203.
    595. Breed, Greg A. & Costa, Daniel P. & Jonsen, Ian D. & Robinson, Patrick W. & Mills-Flemming, Joanna, 2012. "State-space methods for more completely capturing behavioral dynamics from animal tracks," Ecological Modelling, Elsevier, vol. 235, pages 49-58.
    596. Akaki Liqokeli, 2020. "Measuring Credit Gaps for Macroprudential Policy Guidance: An Application to Georgia," NBG Working Papers 05/2020, National Bank of Georgia.
    597. Busettti, F. & Harvey, A., 2007. "Tests of time-invariance," Cambridge Working Papers in Economics 0701, Faculty of Economics, University of Cambridge.
    598. Yoonsuk Lee & B. Wade Brorsen, 2017. "Permanent shocks and forecasting with moving averages," Applied Economics, Taylor & Francis Journals, vol. 49(12), pages 1213-1225, March.
    599. Nicholas Sander, 2013. "Fresh perspectives on unobservable variables: Data decomposition of the Kalman smoother," Reserve Bank of New Zealand Analytical Notes series AN2013/09, Reserve Bank of New Zealand.
    600. Nicolas Abad & Teresa Lloyd-Braga & Leonor Modesto, 2019. "The failure of stabilization policy: balanced-budget fiscal rules in the presence of incompressible public expenditures," Working Papers hal-02331811, HAL.
    601. Schwaab, Bernd & Eser, Fabian, 2013. "Assessing asset purchases within the ECB’s securities markets programme," Working Paper Series 1587, European Central Bank.
    602. Stelios D. Bekiros & Alessia Paccagnini, 2015. "Macroprudential policy and forecasting using Hybrid DSGE models with financial frictions and State space Markov-Switching TVP-VARs," Open Access publications 10197/7333, School of Economics, University College Dublin.
    603. Nima Nonejad, 2013. "Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox," CREATES Research Papers 2013-27, Department of Economics and Business Economics, Aarhus University.
    604. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
    605. Kutlu, Levent, 2017. "A constrained state space approach for estimating firm efficiency," Economics Letters, Elsevier, vol. 152(C), pages 54-56.
    606. Sergio Afonso Lago Alves & Angelo Marsiglia Fasolo, 2015. "Not Just Another Mixed Frequency Paper," Working Papers Series 400, Central Bank of Brazil, Research Department.
    607. Bohl, Martin T. & Kaufmann, Philipp & Siklos, Pierre L., 2015. "What drove the mid-2000s explosiveness in alternative energy stock prices? Evidence from U.S., European and global indices," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 194-206.
    608. Debasish Roy & Ramaprasad Bhar, 2020. "Trend of Commodity Prices and Exchange Rate in Australian Economy: Time Varying Parameter Model Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(3), pages 427-437, September.
    609. Christian Aßmann, 2009. "Christensen, B.J. and Kiefer, N.M.: Economic modeling and inference," Journal of Economics, Springer, vol. 98(3), pages 257-259, December.
    610. Georges Prat & Remzi Uctum, 2018. "Term structure of interest rates: modelling the risk premium using a two-horizons framework," Post-Print hal-01828854, HAL.
    611. Georgia Koppe & Hazem Toutounji & Peter Kirsch & Stefanie Lis & Daniel Durstewitz, 2019. "Identifying nonlinear dynamical systems via generative recurrent neural networks with applications to fMRI," PLOS Computational Biology, Public Library of Science, vol. 15(8), pages 1-35, August.
    612. Michel van der Wel & Albert Menkveld & Asani Sarkar, 2009. "Are Market Makers Uninformed and Passive? Signing Trades in The Absence of Quotes," Tinbergen Institute Discussion Papers 09-046/3, Tinbergen Institute.
    613. Alvaro Angeriz & Philip Arestis, 2007. "Assessing the Performance of ‘Inflation Targeting Lite’ Countries," The World Economy, Wiley Blackwell, vol. 30(11), pages 1621-1645, November.
    614. Vladimir Kuzin, 2004. "The Inflation Aversion of the Bundesbank: A State Space Approach," Computing in Economics and Finance 2004 121, Society for Computational Economics.
    615. Algaba, Andres & Borms, Samuel & Boudt, Kris & Verbeken, Brecht, 2023. "Daily news sentiment and monthly surveys: A mixed-frequency dynamic factor model for nowcasting consumer confidence," International Journal of Forecasting, Elsevier, vol. 39(1), pages 266-278.
    616. Serdar Neslihanoglu, 2021. "Linearity extensions of the market model: a case of the top 10 cryptocurrency prices during the pre-COVID-19 and COVID-19 periods," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.
    617. Jiakun Jiang & Wei Yang & Erin M. Schnellinger & Stephen E. Kimmel & Wensheng Guo, 2023. "Dynamic logistic state space prediction model for clinical decision making," Biometrics, The International Biometric Society, vol. 79(1), pages 73-85, March.
    618. Martín Almuzara & Dante Amengual & Enrique Sentana, 2019. "Normality tests for latent variables," Quantitative Economics, Econometric Society, vol. 10(3), pages 981-1017, July.
    619. Kleppe, Tore Selland & Skaug, Hans J., 2008. "Simulated maximum likelihood for general stochastic volatility models: a change of variable approach," MPRA Paper 12022, University Library of Munich, Germany.
    620. Chiranjit Dutta & Nalini Ravishanker & Sumanta Basu, 2022. "Modeling Multivariate Positive-Valued Time Series Using R-INLA," Papers 2206.05374, arXiv.org, revised Jul 2022.
    621. 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.
    622. Dossche, Maarten & Everaert, Gerdie, 2005. "Measuring inflation persistence: a structural time series approach," Working Paper Series 495, European Central Bank.
    623. Ioannis Chatziantoniou & David Gabauer & Alexis Stenfors, 2019. "From CIP-Deviations to a Market for Risk Premia: A Dynamic Investigation of Cross-Currency Basis Swaps," Working Papers in Economics & Finance 2019-05, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    624. Irma Hindrayanto & John A.D. Aston & Siem Jan Koopman & Marius Ooms, 2010. "Modeling Trigonometric Seasonal Components for Monthly Economic Time Series," Tinbergen Institute Discussion Papers 10-018/4, Tinbergen Institute.
    625. Daniel Fehrle & Johannes Huber, 2020. "Business cycle accounting for the German fiscal stimulus program during the Great Recession," Discussion Paper Series 339, Universitaet Augsburg, Institute for Economics.
    626. Nima Nonejad, 2019. "Has the 2008 financial crisis and its aftermath changed the impact of inflation on inflation uncertainty in member states of the european monetary union?," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(2), pages 246-276, May.
    627. Arne Andresen & Fred Espen Benth & Steen Koekebakker & Valeriy Zakamulin, 2014. "The Carma Interest Rate Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 1-27.
    628. Pellegrini, Santiago & Ruiz, Esther & Espasa, Antoni, 2011. "Prediction intervals in conditionally heteroscedastic time series with stochastic components," International Journal of Forecasting, Elsevier, vol. 27(2), pages 308-319.
    629. Chang, Chiao-Yi & Lai, Jing-Yi & Chuang, I-Yuan, 2010. "Futures hedging effectiveness under the segmentation of bear/bull energy markets," Energy Economics, Elsevier, vol. 32(2), pages 442-449, March.
    630. Grigoryeva, Lyudmila & Ortega, Juan-Pablo & Peresetsky, Anatoly, 2015. "Volatility forecasting using global stochastic financial trends extracted from non-synchronous data," MPRA Paper 64503, University Library of Munich, Germany.
    631. Cecilia Frale & David Veredas, 2008. "A Monthly Volatility Index for the US Economy," Working Papers ECARES 2008-008, ULB -- Universite Libre de Bruxelles.
    632. João Frois Caldeira & Marcelo Savino Portugal, 2010. "Long-Short Market Neutral and Index Tracking Strategies Based on Cointegrated Portfolios," Brazilian Review of Finance, Brazilian Society of Finance, vol. 8(4), pages 469-504.
    633. Nonejad, Nima, 2021. "Predicting the return on the spot price of crude oil out-of-sample by conditioning on news-based uncertainty measures: Some new empirical results," Energy Economics, Elsevier, vol. 104(C).
    634. Daniel Kinn, 2018. "Synthetic Control Methods and Big Data," Papers 1803.00096, arXiv.org.
    635. Tommaso Proietti, 2012. "Seasonality, Forecast Extensions And Business Cycle Uncertainty," Journal of Economic Surveys, Wiley Blackwell, vol. 26(4), pages 555-569, September.
    636. Yueqing Jia, 2011. "A New Look at China’s Output Fluctuations: Quarterly GDP Estimation with an Unobserved Components Approach," Working Papers 2011-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    637. Francisco Blasques & Siem Jan Koopman & Katarzyna Lasak & André Lucas, 2015. "In-Sample Confidence Bands and Out-of-Sample Forecast Bands for Time-Varying Parameters in Observation Driven Models," Tinbergen Institute Discussion Papers 15-083/III, Tinbergen Institute.
    638. Prashant Srivastava & Dawei Han & Miguel Rico-Ramirez & Deleen Al-Shrafany & Tanvir Islam, 2013. "Data Fusion Techniques for Improving Soil Moisture Deficit Using SMOS Satellite and WRF-NOAH Land Surface Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(15), pages 5069-5087, December.
    639. Blasques, F. & Koopman, S.J. & Mallee, M. & Zhang, Z., 2016. "Weighted maximum likelihood for dynamic factor analysis and forecasting with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 405-417.
    640. Benjamin Poignard & Manabu Asai, 2022. "High-Dimensional Sparse Multivariate Stochastic Volatility Models," Papers 2201.08584, arXiv.org, revised May 2022.
    641. J. D. M. Yamim & C. C. H. Borges & R. F. Neto, 2023. "Portfolio Optimization Via Online Gradient Descent and Risk Control," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 361-381, June.
    642. Monfort, A. & Renne, J.-P. & Roussellet, G., 2014. "A Quadratic Kalman Filter," Working papers 486, Banque de France.
    643. Arisoy, Ibrahim & Ozturk, Ilhan, 2014. "Estimating industrial and residential electricity demand in Turkey: A time varying parameter approach," Energy, Elsevier, vol. 66(C), pages 959-964.
    644. Franco Peracchi & Claudio Rossetti, 2022. "A nonlinear dynamic factor model of health and medical treatment," Health Economics, John Wiley & Sons, Ltd., vol. 31(6), pages 1046-1066, June.
    645. Funke, Michael & Tsang, Andrew, 2020. "The People's Bank of China's response to the coronavirus pandemic: A quantitative assessment," BOFIT Discussion Papers 12/2020, Bank of Finland Institute for Emerging Economies (BOFIT).
    646. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    647. Izabela Sobiech, 2015. "Remittances, finance and growth: does financial development foster remittances and their impact on economic growth," FIW Working Paper series 158, FIW.
    648. 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.).
    649. Correia, Ricardo & Dubiel-Teleszynski, Tomasz & Población García, Francisco Javier, 2017. "A structural model to study the bail-out process in a bank and its macro-prudential policy implications," Working Paper Series 2110, European Central Bank.
    650. Helena Beltran & Albert J. Menkveld, 2004. "Understanding limit order book depth: conditioning on trade informativeness," Econometric Society 2004 Latin American Meetings 142, Econometric Society.
    651. Triantafyllopoulos, Kostas, 2006. "Multivariate discount weighted regression and local level models," Computational Statistics & Data Analysis, Elsevier, vol. 50(12), pages 3702-3720, August.
    652. Taras Lazariv & Wolfgang Schmid, 2019. "Surveillance of non-stationary processes," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(3), pages 305-331, September.
    653. Emanuele Aliverti & Stefano Mazzuco & Bruno Scarpa, 2022. "Dynamic modelling of mortality via mixtures of skewed distribution functions," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1030-1048, July.
    654. Mamadou Cisse & Mamadou Konte & Mohamed Toure & Smael Afolabi Assani, 2019. "Contribution to the Valuation of BRVM’s Assets: A Conditional CAPM Approach," JRFM, MDPI, vol. 12(1), pages 1-15, February.
    655. 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.
    656. Martin Iseringhausen, 2018. "The Time-Varying Asymmetry Of Exchange Rate Returns: A Stochastic Volatility – Stochastic Skewness Model," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 18/944, Ghent University, Faculty of Economics and Business Administration.
    657. Siem Jan Koopman & João Valle E Azevedo, 2008. "Measuring Synchronization and Convergence of Business Cycles for the Euro area, UK and US," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(1), pages 23-51, February.
    658. 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.
    659. Riccardo Borghi & Eric Hillebrand & Jakob Mikkelsen & Giovanni Urga, 2018. "The dynamics of factor loadings in the cross-section of returns," CREATES Research Papers 2018-38, Department of Economics and Business Economics, Aarhus University.
    660. 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.
    661. Irma Hindrayanto & Siem Jan Koopman & Jasper de Winter, 2014. "Nowcasting and Forecasting Economic Growth in the Euro Area using Principal Components," Tinbergen Institute Discussion Papers 14-113/III, Tinbergen Institute.
    662. 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.
    663. Vendrame, Vasco & Guermat, Cherif & Tucker, Jon, 2018. "A conditional regime switching CAPM," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 1-11.
    664. Kai Liu, 2014. "Public Finances, Business Cycles and Structural Fiscal Balances," Cambridge Working Papers in Economics 1411, Faculty of Economics, University of Cambridge.
    665. Anders Warne & Günter Coenen & Kai Christoffel, 2017. "Marginalized Predictive Likelihood Comparisons of Linear Gaussian State‐Space Models with Applications to DSGE, DSGE‐VAR, and VAR Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 103-119, January.
    666. Robert A. Hill & Paulo M. M. Rodrigues, 2022. "Forgetting approaches to improve forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1356-1371, November.
    667. Gianfreda, Angelica & Maranzano, Paolo & Parisio, Lucia & Pelagatti, Matteo, 2023. "Testing for integration and cointegration when time series are observed with noise," Economic Modelling, Elsevier, vol. 125(C).
    668. Iiboshi, Hirokuni & Nishiyama, Shin-Ichi & Watanabe, Toshiaki, 2006. "An Estimated Dynamic Stochastic General Equilibrium Model of the Japanese Economy: A Bayesian Analysis," MPRA Paper 85702, University Library of Munich, Germany.
    669. Sebastian Rondeau, 2012. "Sources of Fluctuations in Emerging Markets: Structural Estimation with Mixed Frequency Data," 2012 Meeting Papers 1156, Society for Economic Dynamics.
    670. Adolfo Maza, 2006. "Migrations and Regional Convergence: The Case of Spain," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 26(2), pages 191-202, October.
    671. Pedregal, Diego J. & Carmen Carnero, Ma, 2006. "State space models for condition monitoring: a case study," Reliability Engineering and System Safety, Elsevier, vol. 91(2), pages 171-180.
    672. H. Visser & A. Petersen, 2009. "The likelihood of holding outdoor skating marathons in the Netherlands as a policy-relevant indicator of climate change," Climatic Change, Springer, vol. 93(1), pages 39-54, March.
    673. Dimitrije Marković & Jan Gläscher & Peter Bossaerts & John O’Doherty & Stefan J Kiebel, 2015. "Modeling the Evolution of Beliefs Using an Attentional Focus Mechanism," PLOS Computational Biology, Public Library of Science, vol. 11(10), pages 1-34, October.
    674. Chang, Yu Sang, 2014. "Comparative analysis of long-term road fatality targets for individual states in the US—An application of experience curve models," Transport Policy, Elsevier, vol. 36(C), pages 53-69.
    675. Banbura, Marta & Rünstler, Gerhard, 2011. "A look into the factor model black box: Publication lags and the role of hard and soft data in forecasting GDP," International Journal of Forecasting, Elsevier, vol. 27(2), pages 333-346, April.
    676. Siem Jan Koopman & Geert Mesters, 2014. "Empirical Bayes Methods for Dynamic Factor Models," Tinbergen Institute Discussion Papers 14-061/III, Tinbergen Institute.
    677. Rita Justo-Silva & Adelino Ferreira & Gerardo Flintsch, 2021. "Review on Machine Learning Techniques for Developing Pavement Performance Prediction Models," Sustainability, MDPI, vol. 13(9), pages 1-27, May.
    678. Mengheng Li & Ivan Mendieta-Munoz, 2019. "The multivariate simultaneous unobserved components model and identification via heteroskedasticity," Working Paper Series 2019/08, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    679. Tobias Hartl & Rolf Tschernig & Enzo Weber, 2020. "Fractional trends and cycles in macroeconomic time series," Papers 2005.05266, arXiv.org, revised May 2020.
    680. 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.
    681. Christian Matthes & Felipe Schwartzman, 2019. "The Demand Origins of Business Cycles," 2019 Meeting Papers 1122, Society for Economic Dynamics.
    682. Broto, Carmen & Ruiz Ortega, Esther, 2003. "Unobserved component models with asymmetric conditional variances," DES - Working Papers. Statistics and Econometrics. WS ws032003, Universidad Carlos III de Madrid. Departamento de Estadística.
    683. Hendrych, R. & Cipra, T., 2016. "On conditional covariance modelling: An approach using state space models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 304-317.
    684. Frits Bijleveld & Jacques Commandeur & Siem Jan Koopman & Kees van Montfort, 2010. "Multivariate non‐linear time series modelling of exposure and risk in road safety research," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(1), pages 145-161, January.
    685. Sy‐Miin Chow & Guangjian Zhang, 2008. "Continuous‐time modelling of irregularly spaced panel data using a cubic spline model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 62(1), pages 131-154, February.
    686. Zhou, Jian, 2016. "Hedging performance of REIT index futures: A comparison of alternative hedge ratio estimation methods," Economic Modelling, Elsevier, vol. 52(PB), pages 690-698.
    687. Gianni Amisano & Oreste Tristani, 2019. "Uncertainty Shocks, Monetary Policy and Long-Term Interest Rates," Finance and Economics Discussion Series 2019-024, Board of Governors of the Federal Reserve System (U.S.).
    688. Goldstone, Jack A. (Голдстоун, Джек) & Shulgin, Sergey (Шульгин, Сергей) & Arkhangelskiy, Vladimir (Архангельский, Владимир) & Korotaev, Andrey (Коротаев, Андрей) & Zinkina, Yulia (Зинкина, Юлия) & No, 2015. "Political Demography of Russia. Politics and State Government [Политическая Демография России. Политика И Государственное Управление]," Published Papers mn44, Russian Presidential Academy of National Economy and Public Administration.
    689. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    690. Victor Bystrov, 2020. "Identification and Estimation of Initial Conditions in Non-Minimal State-Space Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(4), pages 413-429, December.
    691. Bos, Charles S. & Koopman, Siem Jan & Ooms, Marius, 2014. "Long memory with stochastic variance model: A recursive analysis for US inflation," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 144-157.
    692. Adam Kucera & Michal Dvorak & Zlatuse Komarkova, 2017. "Decomposition of the Czech government bond yield curve," Occasional Publications - Chapters in Edited Volumes, in: CNB Financial Stability Report 2016/2017, chapter 0, pages 125-134, Czech National Bank.
    693. Negro, Marco Del & Schorfheide, Frank, 2013. "DSGE Model-Based Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 57-140, Elsevier.
    694. Pozzi, Lorenzo, 2010. "Idiosyncratic labour income risk and aggregate consumption: An unobserved component approach," Journal of Macroeconomics, Elsevier, vol. 32(1), pages 169-184, March.
    695. P.A.V.B. Swamy & George S. Tavlas & Stephen G. Hall & George Hondroyiannis, 2008. "Estimation of Parameters in the Presence of Model misspecification and Measurement Error," Discussion Papers in Economics 08/27, Division of Economics, School of Business, University of Leicester.
    696. Lemos, Ricardo T., 2016. "An alternative stock-recruitment function for age-structured models," Ecological Modelling, Elsevier, vol. 341(C), pages 14-26.
    697. Sangahn Kim & Mehmet Turkoz, 2022. "Bayesian sequential update for monitoring and control of high-dimensional processes," Annals of Operations Research, Springer, vol. 317(2), pages 693-715, October.
    698. Lorenza Rossi & Emilio Zanetti Chini, 2019. "Temporal Disaggregation of Business Dynamics: New Evidence for U.S. Economy," Working Papers in Public Economics 188, University of Rome La Sapienza, Department of Economics and Law.
    699. Alkhathlan, Khalid & Javid, Muhammad, 2015. "Carbon emissions and oil consumption in Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 105-111.
    700. Francis X. Diebold, & Rudebusch, Glenn D. & Aruoba, S. Boragan, 2003. "The Macroeconomy and the Yield Curve: A Nonstructural Analysis," CFS Working Paper Series 2003/31, Center for Financial Studies (CFS).
    701. Pizzinga, Adrian & Fernandes, Cristiano, 2006. "State Space Models for Dynamic Style Analysis of Portfolios," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 26(1), May.
    702. Lorenzo Boldrini & Eric Hillebrand, 2015. "The Forecasting Power of the Yield Curve, a Supervised Factor Model Approach," CREATES Research Papers 2015-39, Department of Economics and Business Economics, Aarhus University.
    703. 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.
    704. Michael D. Hunter & Haya Fatimah & Marina A. Bornovalova, 2022. "Two Filtering Methods of Forecasting Linear and Nonlinear Dynamics of Intensive Longitudinal Data," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 477-505, June.
    705. Matthew Ferranti, 2022. "Estimating the Currency Composition of Foreign Exchange Reserves," Papers 2206.13751, arXiv.org, revised May 2023.
    706. Christopher Nemeth & Chris Sherlock & Paul Fearnhead, 2016. "Particle Metropolis-adjusted Langevin algorithms," Biometrika, Biometrika Trust, vol. 103(3), pages 701-717.
    707. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Working Papers 22-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    708. Geert Mesters & Siem Jan Koopman, 2012. "Generalized Dynamic Panel Data Models with Random Effects for Cross-Section and Time," Tinbergen Institute Discussion Papers 12-009/4, Tinbergen Institute, revised 18 Mar 2014.
    709. Drew Creal & Siem Jan Koopman & André Lucas, 2008. "A General Framework for Observation Driven Time-Varying Parameter Models," Tinbergen Institute Discussion Papers 08-108/4, Tinbergen Institute.
    710. Hindrayanto, Irma & Koopman, Siem Jan & de Winter, Jasper, 2016. "Forecasting and nowcasting economic growth in the euro area using factor models," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1284-1305.
    711. Christensen, Bent Jesper & van der Wel, Michel, 2019. "An asset pricing approach to testing general term structure models," Journal of Financial Economics, Elsevier, vol. 134(1), pages 165-191.
    712. Díaz, Guzmán & Moreno, Blanca & Coto, José & Gómez-Aleixandre, Javier, 2015. "Valuation of wind power distributed generation by using Longstaff–Schwartz option pricing method," Applied Energy, Elsevier, vol. 145(C), pages 223-233.
    713. Olivier Darné & Amélie Charles, 2008. "The impact of outliers on transitory and permanent components in macroeconomic time series," Economics Bulletin, AccessEcon, vol. 3(60), pages 1-9.
    714. Caterina Schiavoni & Franz Palm & Stephan Smeekes & Jan van den Brakel, 2019. "A dynamic factor model approach to incorporate Big Data in state space models for official statistics," Papers 1901.11355, arXiv.org, revised Feb 2020.
    715. Heejong Lim & Kwanghun Chung & Sangbok Lee, 2022. "Probabilistic Forecasting for Demand of a Bike-Sharing Service Using a Deep-Learning Approach," Sustainability, MDPI, vol. 14(23), pages 1-18, November.
    716. Andreasen, Martin, 2011. "An estimated DSGE model: explaining variation in term premia," Bank of England working papers 441, Bank of England.
    717. 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.
    718. Chu, Chih-Yuan & Durango-Cohen, Pablo L., 2008. "Estimation of dynamic performance models for transportation infrastructure using panel data," Transportation Research Part B: Methodological, Elsevier, vol. 42(1), pages 57-81, January.
    719. 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.
    720. Dominik Bernhofer & Octavio Fernández-Amador & Martin Gächter & Friedrich Sindermann, 2014. "Finance, Potential Output and the Business Cycle: Empirical Evidence from Selected Advanced and CESEE Economies," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 2, pages 52-75.
    721. Javid, Muhammad & Qayyum, Abdul, 2014. "Electricity consumption-GDP nexus in Pakistan: A structural time series analysis," Energy, Elsevier, vol. 64(C), pages 811-817.
    722. Siem Jan Koopman & Marius Ooms, 2004. "Forecasting Daily Time Series using Periodic Unobserved Components Time Series Models," Tinbergen Institute Discussion Papers 04-135/4, Tinbergen Institute.
    723. Lorenzo Boldrini, 2015. "Forecasting the Global Mean Sea Level, a Continuous-Time State-Space Approach," CREATES Research Papers 2015-40, Department of Economics and Business Economics, Aarhus University.
    724. 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.
    725. Müller-Kademann Christian, 2015. "Internal Validation of Temporal Disaggregation: A Cloud Chamber Approach," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 235(3), pages 298-319, June.
    726. Tommaso Proietti & Marco Fioramanti & Cecilia Frale & Libero Monteforte, 2020. "A Systemic Approach to Estimating the Output Gap for the Italian Economy," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 62(3), pages 465-493, September.
    727. Roberto Marfè & Julien Penasse, 2016. "The Time-Varying Risk of Macroeconomic Disasters," Carlo Alberto Notebooks 463, Collegio Carlo Alberto.
    728. Klingenberg, Bernhard, 2008. "Regression models for binary time series with gaps," Computational Statistics & Data Analysis, Elsevier, vol. 52(8), pages 4076-4090, April.
    729. Alonso Fernández, Andrés Modesto & García-Martos, Carolina & Rodríguez, Julio & Sánchez, María Jesús, 2008. "Seasonal dynamic factor analysis and bootstrap inference : application to electricity market forecasting," DES - Working Papers. Statistics and Econometrics. WS ws081406, Universidad Carlos III de Madrid. Departamento de Estadística.
    730. 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.
    731. 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.
    732. Jan van den Brakel & Xichuan (Mark) Zhang & Siu‐Ming Tam, 2020. "Measuring Discontinuities in Time Series Obtained with Repeated Sample Surveys," International Statistical Review, International Statistical Institute, vol. 88(1), pages 155-175, April.
    733. Gianluca Cubadda & Stefano Grassi & Barbara Guardabascio, 2024. "The Time-Varying Multivariate Autoregressive Index Model," CEIS Research Paper 571, Tor Vergata University, CEIS, revised 10 Jan 2024.
    734. Mokinski, Frieder, 2016. "Using time-stamped survey responses to measure expectations at a daily frequency," International Journal of Forecasting, Elsevier, vol. 32(2), pages 271-282.
    735. K. Triantafyllopoulos, 2008. "Multivariate stochastic volatility using state space models," Papers 0802.0223, arXiv.org.
    736. Strickland, Chris M. & Forbes, Catherine S. & Martin, Gael M., 2006. "Bayesian analysis of the stochastic conditional duration model," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2247-2267, May.
    737. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024.
    738. Krzysztof Beck & Piotr Stanek, 2019. "Globalization or Regionalization of Stock Markets? the Case of Central and Eastern European Countries," Eastern European Economics, Taylor & Francis Journals, vol. 57(4), pages 317-330, July.
    739. S. J. Koopman & J. Durbin, 2003. "Filtering and smoothing of state vector for diffuse state‐space models," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(1), pages 85-98, January.
    740. Lai, Jennifer /J.T., 2008. "Capital flow to China and the issue of hot money: an empirical investigation," MPRA Paper 32539, University Library of Munich, Germany, revised Sep 2009.
    741. 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.
    742. Jin, Hailong & Qian, Hang & Wang, Tong & Choi, E Kwan, 2014. "Income Distribution in Urban China: An Overlooked Data Inconsistency Issue," Staff General Research Papers Archive 37381, Iowa State University, Department of Economics.
    743. Philipp Heimberger, 2019. "The Impact of Labour Market Institutions and Capital Accumulation on Unemployment: Evidence for the OECD, 1985-2013," wiiw Working Papers 164, The Vienna Institute for International Economic Studies, wiiw.
    744. Rafael Martins de Souza & Luiz Felipe Pires Maciel & Adrian Pizzinga, 2013. "State space models for the exchange rate pass-through: determinants and null/full pass-through hypotheses," Applied Economics, Taylor & Francis Journals, vol. 45(36), pages 5062-5075, December.
    745. António Alberto Santos, 2010. "MCMC, likelihood estimation and identifiability problems in DLM models," GEMF Working Papers 2010-12, GEMF, Faculty of Economics, University of Coimbra.
    746. 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.
    747. 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.
    748. Scharth, Marcel & Kohn, Robert, 2016. "Particle efficient importance sampling," Journal of Econometrics, Elsevier, vol. 190(1), pages 133-147.
    749. Rob Luginbuhl & Siem Jan Koopman, 2003. "Convergence in European GDP Series," Tinbergen Institute Discussion Papers 03-031/4, Tinbergen Institute.
    750. Glocker, Christian & Kaniovski, Serguei, 2020. "Structural modeling and forecasting using a cluster of dynamic factor models," MPRA Paper 101874, University Library of Munich, Germany.
    751. Díaz, Guzmán & Coto, José & Gómez-Aleixandre, Javier, 2019. "Optimal operation value of combined wind power and energy storage in multi-stage electricity markets," Applied Energy, Elsevier, vol. 235(C), pages 1153-1168.
    752. Creal, D., 2009. "A survey of sequential Monte Carlo methods for economics and finance," Serie Research Memoranda 0018, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    753. Mellár, Tamás & Németh, Kristóf, 2018. "A kibocsátási rés becslése többváltozós állapottérmodellekben. Szuperhiszterézis és további empirikus eredmények [Estimating output gap in multivariate state space models. Super-hysteresis and furt," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(6), pages 557-591.
    754. 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.
    755. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.
    756. Cai, Lingru & Zhang, Zhanchang & Yang, Junjie & Yu, Yidan & Zhou, Teng & Qin, Jing, 2019. "A noise-immune Kalman filter for short-term traffic flow forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    757. Maria Kulikova & Gennady Kulikov, 2023. "Estimation of market efficiency process within time-varying autoregressive models by extended Kalman filtering approach," Papers 2310.04125, arXiv.org.
    758. Siem Jan Koopman & Julia Schaumburg & Quint Wiersma, 2021. "Joint Modelling and Estimation of Global and Local Cross-Sectional Dependence in Large Panels," Tinbergen Institute Discussion Papers 21-008/III, Tinbergen Institute.
    759. Deb, Prokash & Dey, Madan M. & Surathkal, Prasanna, 2021. "Fish Price Volatility Dynamics in Bangladesh," 2021 Annual Meeting, August 1-3, Austin, Texas 314077, Agricultural and Applied Economics Association.
    760. Dimitris Korobilis & Michelle Gilmartin, 2011. "The Dynamic Effects of U.S. Monetary Policy on State Unemployment," Working Paper series 12_11, Rimini Centre for Economic Analysis.
    761. Dany Brouillette & Jonathan Lachaine & Benoit Vincent, 2018. "Wages: Measurement and Key Drivers," Staff Analytical Notes 2018-2, Bank of Canada.
    762. 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.
    763. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2013. "On the Stratonovich – Kalman - Bucy filtering algorithm application for accurate characterization of financial time series with use of state-space model by central banks," MPRA Paper 50235, University Library of Munich, Germany.
    764. Somnath Chatterjee, 2015. "Modelling credit risk," Handbooks, Centre for Central Banking Studies, Bank of England, number 34, April.
    765. Besbeas, P.T. & McCrea, R.S. & Morgan, B.J.T., 2022. "Selecting age structure in integrated population models," Ecological Modelling, Elsevier, vol. 473(C).
    766. B. Jungbacker & S.J. Koopman & M. van Der Wel, 2011. "Maximum likelihood estimation for dynamic factor models with missing data," Post-Print hal-00828980, HAL.
    767. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    768. Dominik Bernhofer & Octavio Fernández-Amador & Martin Gächter & Friedrich Sindermann, 2014. "Finance, potential output and the business cycle," Chapters, in: Ewald Nowotny & Doris Ritzberger-Grünwald & Peter Backé (ed.), Financial Cycles and the Real Economy, chapter 14, pages 235-264, Edward Elgar Publishing.
    769. Koen Pauwels & Imran Currim & Marnik Dekimpe & Dominique Hanssens & Natalie Mizik & Eric Ghysels & Prasad Naik, 2004. "Modeling Marketing Dynamics by Time Series Econometrics," Marketing Letters, Springer, vol. 15(4), pages 167-183, December.
    770. 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.
    771. Bikker Reinier & van den Brakel Jan & Krieg Sabine & Ouwehand Pim & van der Stegen Ronald, 2019. "Consistent Multivariate Seasonal Adjustment for Gross Domestic Product and its Breakdown in Expenditures," Journal of Official Statistics, Sciendo, vol. 35(1), pages 9-30, March.
    772. Holtrop, Niels & Wieringa, Jaap E. & Gijsenberg, Maarten J. & Verhoef, Peter C., 2017. "No future without the past? Predicting churn in the face of customer privacy," International Journal of Research in Marketing, Elsevier, vol. 34(1), pages 154-172.
    773. Alicia N. Rambaldi & D.S. Prasada Rao & K. Renuka Ganegodage, 2009. "Spatial Autocorrelation and Extrapolation of Purchasing Power Parities. Modelling and Sensitivity Analysis," CEPA Working Papers Series WP012009, School of Economics, University of Queensland, Australia.
    774. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707.
    775. Francis Vitek, 2005. "An Unobserved Components Model of the Monetary Transmission Mechanism in a Closed Economy," Macroeconomics 0512018, University Library of Munich, Germany, revised 06 Feb 2006.
    776. IIBOSHI Hirokuni, 2012. "Measuring the Effects of Monetary Policy: A DSGE-DFM Approach," ESRI Discussion paper series 292, Economic and Social Research Institute (ESRI).
    777. Qian, Hang, 2015. "Inequality Constrained State Space Models," MPRA Paper 66447, University Library of Munich, Germany.
    778. Michael Callaghan & Thomas van Florenstein Mulder, 2020. "GDP Plus: An Economic Activity Indicator for New Zealand," Reserve Bank of New Zealand Analytical Notes series AN2020/01, Reserve Bank of New Zealand.
    779. 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.
    780. Bjørn Gunnar Hansen & Yushu Li, 2017. "An Analysis of Past World Market Prices of Feed and Milk and Predictions for the Future," Agribusiness, John Wiley & Sons, Ltd., vol. 33(2), pages 175-193, April.
    781. 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.
    782. 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.
    783. Ivan Lagrosa, 2022. "Income dynamics in dual labor markets," Working Papers wp2022_2209, CEMFI.
    784. Driver, Charles C. & Oud, Johan H. L. & Voelkle, Manuel C., 2017. "Continuous Time Structural Equation Modeling with R Package ctsem," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 77(i05).
    785. Olivier Darné & Amélie Charles, 2011. "Large shocks in U.S. macroeconomic time series: 1860-1988," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(1), pages 79-100, January.
    786. Diego J Pedregal, 2019. "Time series analysis and forecasting with ECOTOOL," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-23, October.
    787. 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.
    788. Galvao, Ana Beatriz, 2016. "Data Revisions and DSGE Models," EMF Research Papers 11, Economic Modelling and Forecasting Group.
    789. Komi Nagbe & Jairo Cugliari & Julien Jacques, 2018. "Short-Term Electricity Demand Forecasting Using a Functional State Space Model," Energies, MDPI, vol. 11(5), pages 1-24, May.
    790. Zhu Wang & Wayne A. Woodward & Henry L. Gray, 2009. "The application of the Kalman filter to nonstationary time series through time deformation," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(5), pages 559-574, September.
    791. 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.
    792. Yasutomo Murasawa & Roberto S. Mariano, 2004. "Constructing a Coincident Index of Business Cycles Without Assuming a One-Factor Model," Econometric Society 2004 Far Eastern Meetings 710, Econometric Society.
    793. Dunsmuir, William T. M. & Scott, David J., 2015. "The glarma Package for Observation-Driven Time Series Regression of Counts," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i07).
    794. Smets, Frank & Warne, Anders & Wouters, Rafael, 2014. "Professional forecasters and real-time forecasting with a DSGE model," International Journal of Forecasting, Elsevier, vol. 30(4), pages 981-995.
    795. Wang, Zhu, 2013. "cts: An R Package for Continuous Time Autoregressive Models via Kalman Filter," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 53(i05).
    796. Eftychios A Pnevmatikakis & Keith Kelleher & Rebecca Chen & Petter Saggau & Krešimir Josić & Liam Paninski, 2012. "Fast Spatiotemporal Smoothing of Calcium Measurements in Dendritic Trees," PLOS Computational Biology, Public Library of Science, vol. 8(6), pages 1-17, June.
    797. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Phillips Curve Models with Non-Filtered Time Series," Tinbergen Institute Discussion Papers 13-011/III, Tinbergen Institute.
    798. Fondeur, Y. & Karamé, F., 2013. "Can Google data help predict French youth unemployment?," Economic Modelling, Elsevier, vol. 30(C), pages 117-125.
    799. Levent Ozbek & Umit Ozlale & Fikri Ozturk, 2003. "Employing Extended Kalman Filter in a Simple Macroeconomic Model," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 3(1), pages 53-65.
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