A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models 论文

详细信息

发表期刊/会议

The Review of Economics and Statistics

发表日期

2011-07-19

发表年份

2011

摘要

Is maximum likelihood suitable for factor models in large cross-sections of time series? We answer this question from both an asymptotic and an empirical perspective. We show that estimates of the common factors based on maximum likelihood are consistent for the size of the cross-section (n) and the sample size (T), going to infinity along any path, and that maximum likelihood is viable for n large. The estimator is robust to misspecification of cross-sectional and time series correlation of the idiosyncratic components. In practice, the estimator can be easily implemented using the Kalman smoother and the EM algorithm as in traditional factor analysis.