A two-step estimator for large approximate dynamic factor models based on Kalman filtering

Catherine Doz, Domenico Giannone and Lucrezia Reichlin

Journal of Econometrics, 2011, vol. 164, issue 1, 188-205

Abstract: This paper shows consistency of a two-step estimation of the factors in a dynamic approximate factor model when the panel of time series is large (n large). In the first step, the parameters of the model are estimated from an OLS on principal components. In the second step, the factors are estimated via the Kalman smoother. The analysis develops the theory for the estimator considered in Giannone et al. (2004) and Giannone et al. (2008) and for the many empirical papers using this framework for nowcasting.

Keywords: Factor; models; Kalman; filter; Principal; components; Large; cross-sections (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (329)

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Related works:
Working Paper: A two-step estimator for large approximate dynamic factor models based on Kalman filtering (2011)
Working Paper: A two-step estimator for large approximate dynamic factor models based on Kalman filtering (2011)
Working Paper: A two-step estimator for large approximate dynamic factor models based on Kalman filtering (2011)
Working Paper: A two-step estimator for large approximate dynamic factor models based on Kalman filtering (2011)
Working Paper: A Two-Step Estimator for Large Approximate Dynamic Factor Models Based on Kalman Filtering (2007)
Working Paper: A Two-step estimator for large approximate dynamic factor models based on Kalman filtering (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:164:y:2011:i:1:p:188-205

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