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.

A two-step estimator for large approximate dynamic factor models based on Kalman filtering / Catherine, Doz; Giannone, Domenico; Lucrezia, Reichlin. - In: JOURNAL OF ECONOMETRICS. - ISSN 0304-4076. - 164:1(2011), pp. 188-205. [10.1016/j.jeconom.2011.02.012]

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

GIANNONE, DOMENICO;
2011

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.
A two-step estimator for large approximate dynamic factor models based on Kalman filtering / Catherine, Doz; Giannone, Domenico; Lucrezia, Reichlin. - In: JOURNAL OF ECONOMETRICS. - ISSN 0304-4076. - 164:1(2011), pp. 188-205. [10.1016/j.jeconom.2011.02.012]
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11385/93991
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