The Generalized Dynamic Factor Model: Identification and Estimation
Abstract
This paper analyzes identification conditions, and proposes an estimator, for a dynamic factor model where the idiosyncratic components are allowed to be mutually non-orthogonal. This model, which we call the generalized dynamic factor model, is novel to the literature, and generalizes the static approximate factor model of Chamberlain and Rothschild (1983), as well as the exact factor model à la Sargent and Sims (1977). We propose an estimator of the common components and prove convergence as both time and cross-sectional size go to infinity at appropriate rates. Simulations yield encouraging results in small samples. We use our model to construct an index of the state of the economy for the European currency area. Such an index is defined as the common component of real GDP within a model including several macroeconomic variables for each European country.Download Info
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Bibliographic Info
Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 2338.Length:
Date of creation: Dec 1999
Date of revision:
Handle: RePEc:cpr:ceprdp:2338
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Related research
Keywords: Coincident Indicators; Dynamic Factor Models; Dynamic Principal Components Series;Other versions of this item:
- 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.
- 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.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
- C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
References
References listed on IDEASPlease report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Forni, Mario & Reichlin, Lucrezia, 1998.
"Let's Get Real: A Factor Analytical Approach to Disaggregated Business Cycle Dynamics,"
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- Forni, Mario & Reichlin, Lucrezia, 1996.
"Dynamic Common Factors in Large Cross-Sections,"
Empirical Economics,
Springer, vol. 21(1), pages 27-42.
- Mario Forni & Lucrezia Reichlin, 1996. "Dynamic common factors in large cross-sections," ULB Institutional Repository 2013/10149, ULB -- Universite Libre de Bruxelles.
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- Forni, Mario & Lippi, Marco, 2001.
"The Generalized Dynamic Factor Model: Representation Theory,"
Econometric Theory,
Cambridge University Press, vol. 17(06), pages 1113-1141, December.
- Forni, Mario & Lippi, Marco, 2000. "The Generalized Dynamic Factor Model: Representation Theory," CEPR Discussion Papers 2509, C.E.P.R. Discussion Papers.
- Forni, Mario & Lippi, Marco, 1997. "Aggregation and the Microfoundations of Dynamic Macroeconomics," OUP Catalogue, Oxford University Press, number 9780198288008, July.
- Chamberlain, Gary, 1983. "Funds, Factors, and Diversification in Arbitrage Pricing Models," Econometrica, Econometric Society, vol. 51(5), pages 1305-23, September.
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Papers
178d, Harvard - J.F. Kennedy School of Government.
- James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409 National Bureau of Economic Research, Inc.
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