Maximum Likelihood Estimation of Factor Models on Data Sets with Arbitrary Pattern of Missing Data

47 Pages Posted: 25 May 2010

See all articles by Marta Banbura

Marta Banbura

European Central Bank

Michele Modugno

Board of Governors of the Federal Reserve System

Date Written: April 30, 2010

Abstract

In this paper we propose a methodology to estimate a dynamic factor model on data sets with an arbitrary pattern of missing data. We modify the Expectation Maximisation (EM) algorithm as proposed for a dynamic factor model by Watson and Engle (1983) to the case with general pattern of missing data. We also extend the model to the case with serially correlated diosyncratic component. The framework allows to handle efficiently and in an automatic manner sets of indicators characterized by different publication delays, frequencies and sample lengths. This can be relevant e.g. for young economies for which many indicators are compiled only since recently. We also show how to extract a model based news from a statistical data release within our framework and we derive the relationship between the news and the resulting forecast revision. This can be used for interpretation in e.g. nowcasting applications as it allows to determine the sign and size of a news as well as its contribution to the revision, in particular in case of simultaneous data releases. We evaluate the methodology in a Monte Carlo experiment and we apply it to nowcasting and backdating of euro area GDP.

Keywords: Factor Models, Forecasting, Large Cross-Sections, Missing data, EM algorithm

JEL Classification: C53, E37

Suggested Citation

Banbura, Marta and Modugno, Michele, Maximum Likelihood Estimation of Factor Models on Data Sets with Arbitrary Pattern of Missing Data (April 30, 2010). ECB Working Paper No. 1189, Available at SSRN: https://ssrn.com/abstract=1598302 or http://dx.doi.org/10.2139/ssrn.1598302

Marta Banbura (Contact Author)

European Central Bank ( email )

Sonnemannstrasse 22
Frankfurt am Main, 60314
Germany

Michele Modugno

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States

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