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Dynamic Factor Models with Jagged Edge Panel Data: Taking on Board the Dynamics of the Idiosyncratic Components
Author(s) -
Pinheiro Maximiano,
Rua António,
Dias Francisco
Publication year - 2013
Publication title -
oxford bulletin of economics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.131
H-Index - 73
eISSN - 1468-0084
pISSN - 0305-9049
DOI - 10.1111/obes.12006
Subject(s) - autoregressive model , dynamic factor , econometrics , panel data , monte carlo method , sample (material) , missing data , factor analysis , enhanced data rates for gsm evolution , estimation , dynamics (music) , statistics , computer science , mathematics , economics , artificial intelligence , chemistry , physics , management , chromatography , acoustics
As macroeconomic data are released with different delays, one has to handle unbalanced panel data sets with missing values at the end of the sample period when estimating dynamic factor models. We propose an EM algorithm which copes with such data sets while accounting for autoregressive common factors and allowing for serial correlation in the idiosyncratic components. Based on Monte Carlo simulations, we find that taking on board the dynamics of the idiosyncratic components improves significantly the accuracy of the estimation of both the missing values and the common factors at the end of the sample period.