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European Central Bank

By Drew Creal A, Bernd Schwaab, Siem Jan Koopman and André Lucas D

Abstract

We propose a dynamic factor model for mixed-measurement and mixed-frequency panel data. In this framework time series observations may come from a range of families of parametric distributions, may be observed at different time frequencies, may have missing observations, and may exhibit common dynamics and cross-sectional dependence due to shared exposure to dynamic latent factors. The distinguishing feature of our model is that the likelihood function is known in closed form and need not be obtained by means of simulation, thus enabling straightforward parameter estimation by standard maximum likelihood. We use the new mixed-measurement framework for the signal extraction and forecasting of macro, credit, and loss given default risk conditions for U.S. Moody’s-rated firms from January 1982 until March 2010

Topics: panel data, loss given default, default risk, dynamic beta density, dynamic ordered probit, dynamic factor model
Year: 2011
OAI identifier: oai:CiteSeerX.psu:10.1.1.188.6601
Provided by: CiteSeerX
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