Maximum likelihood estimation for dynamic factor models with missing data
AbstractThis paper concerns estimating parameters in a high-dimensional dynamic factor model by the method of maximum likelihood. To accommodate missing data in the analysis, we propose a new model representation for the dynamic factor model. It allows the Kalman filter and related smoothing methods to evaluate the likelihood function and to produce optimal factor estimates in a computationally efficient way when missing data is present. The implementation details of our methods for signal extraction and maximum likelihood estimation are discussed. The computational gains of the new devices are presented based on simulated data sets with varying numbers of missing entries.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Economic Dynamics and Control.
Volume (Year): 35 (2011)
Issue (Month): 8 (August)
Contact details of provider:
Web page: http://www.elsevier.com/locate/jedc
High-dimensional vector series Kalman filtering and smoothing Unbalanced panels of time series;
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- 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, 01.
- Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000.
"The generalised dynamic factor model: identification and estimation,"
ULB Institutional Repository
2013/10143, ULB -- Universite Libre de Bruxelles.
- Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
- Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 1999. "The Generalized Dynamic Factor Model: Identification and Estimation," CEPR Discussion Papers 2338, C.E.P.R. Discussion Papers.
- Kapetanios, George & Marcellino, Massimiliano, 2006.
"A Parametric Estimation Method for Dynamic Factor Models of Large Dimensions,"
CEPR Discussion Papers
5620, C.E.P.R. Discussion Papers.
- George Kapetanios & Massimiliano Marcellino, 2009. "A parametric estimation method for dynamic factor models of large dimensions," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(2), pages 208-238, 03.
- Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
- Ruud, Paul A., 1991.
"Extensions of estimation methods using the EM algorithm,"
Journal of Econometrics,
Elsevier, vol. 49(3), pages 305-341, September.
- Paul A. Ruud., 1988. "Extensions of Estimation Methods Using the EM Algorithm.," Economics Working Papers 8899, University of California at Berkeley.
- Otrok, C. & Whiteman, C.H., 1996.
"Bayesian Leading Indicators: Measuring and Predicting Economic Conditions in Iowa,"
96-14, University of Iowa, Department of Economics.
- Otrok, Christopher & Whiteman, Charles H, 1998. "Bayesian Leading Indicators: Measuring and Predicting Economic Conditions in Iowa," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 997-1014, November.
- Thomas J. Sargent & Christopher A. Sims, 1977.
"Business cycle modeling without pretending to have too much a priori economic theory,"
55, Federal Reserve Bank of Minneapolis.
- Tom Doan, . "RATS program to estimate observable index model from Sargent-Sims(1977)," Statistical Software Components RTZ00126, Boston College Department of Economics.
- Watson, Mark W. & Engle, Robert F., 1983. "Alternative algorithms for the estimation of dynamic factor, mimic and varying coefficient regression models," Journal of Econometrics, Elsevier, vol. 23(3), pages 385-400, December.
- Durbin, James & Koopman, Siem Jan, 2001.
"Time Series Analysis by State Space Methods,"
Oxford University Press, number 9780198523543.
- Tom Doan, . "SEASONALDLM: RATS procedure to create the matrices for the seasonal component of a DLM," Statistical Software Components RTS00251, Boston College Department of Economics.
- Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
- Christopher Otrok & Panayiotis M. Pourpourides, 2011.
"On the Cyclicality of Real Wages and Wage Differentials,"
2011-4, Central Bank of Cyprus.
- Otrok, Christopher & Pourpourides, Panayiotis M., 2008. "On The Cyclicality of Real Wages and Wage Differentials," Cardiff Economics Working Papers E2008/19, Cardiff University, Cardiff Business School, Economics Section, revised Mar 2009.
- Borus Jungbacker & Siem Jan Koopman, 2008. "Likelihood-based Analysis for Dynamic Factor Models," Tinbergen Institute Discussion Papers 08-007/4, Tinbergen Institute.
- Liebermann, Joelle, 2012.
"Real-time forecasting in a data-rich environment,"
39452, University Library of Munich, Germany.
- Luati, Alessandra & Proietti, Tommaso, 2012.
"Maximum likelihood estimation of time series models: the Kalman filter and beyond,"
02 BAWP, University of Sydney Business School, Discipline of Business Analytics.
- Tommaso, Proietti & Alessandra, Luati, 2012. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," MPRA Paper 39600, University Library of Munich, Germany.
- Nikolaos Zirogiannis & Yorghos Tripodis, 2013. "A Generalized Dynamic Factor Model for Panel Data: Estimation with a Two-Cycle Conditional Expectation-Maximization Algorithm," Working Papers 2013-1, University of Massachusetts Amherst, Department of Resource Economics.
- Qian, Hang, 2012. "A Flexible State Space Model and its Applications," MPRA Paper 38455, University Library of Munich, Germany.
- Otrok, Christopher & Pourpourides, Panayiotis M., 2008.
"On The Cyclicality of Real Wages and Wage Differentials,"
Cardiff Economics Working Papers
E2008/19, Cardiff University, Cardiff Business School, Economics Section, revised Mar 2009.
- Christopher Otrok & Panayiotis M. Pourpourides, 2011. "On the Cyclicality of Real Wages and Wage Differentials," Working Papers 2011-4, Central Bank of Cyprus.
- 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.
- Christopher Otrok & Panayiotis M. Pourpourides, 2011. "On The Cyclicality of Real Wages and Wage DiÂ¤erentials," Working Papers 1116, Department of Economics, University of Missouri.
- 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.
- Kihwan Kim & Norman Swanson, 2013. "Diffusion Index Model Specification and Estimation Using Mixed Frequency Datasets," Departmental Working Papers 201315, Rutgers University, Department of Economics.
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