Skip to main content

Please enter a keyword and click the arrow to search the site

A quasi-maximum likelihood approach for large approximate dynamic factor models

Journal

Review of Economics and Statistics

Subject

Economics

Authors / Editors

Doz C;Giannone D;Reichlin L

Publication Year

2012

Abstract

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.

Available on ECCH

No


Select up to 4 programmes to compare

Select one more to compare
×
subscribe_image_desktop 5949B9BFE33243D782D1C7A17E3345D0

Sign up to receive our latest news and business thinking direct to your inbox

×

Sign up to receive our latest course information and business thinking

Leave your details above if you would like to receive emails containing the latest thought leadership, invitations to events and news about courses that could enhance your career. If you would prefer not to receive our emails, you can still access the case study by clicking the button below. You can opt-out of receiving our emails at any time by visiting: https://london.edu/my-profile-preferences or by unsubscribing through the link provided in our emails. View our Privacy Policy for more information on your rights.