Template-Type: ReDIF-Paper 1.0 Series: Tinbergen Institute Discussion Papers Creation-Date: 2011-02-21 Number: 11-042/2/DSF16 Author-Name: Drew Creal Author-Workplace-Name: University of Chicago, Booth School of Business Author-Name: Bernd Schwaab Author-Workplace-Name: European Central Bank Author-Name: Siem Jan Koopman Author-Workplace-Name: VU University Amsterdam Author-Name: Andre Lucas Author-Workplace-Name: VU University Amsterdam Title: Observation Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk Abstract: This paper led to a publication in the 'Review of Economics and Statistics', 2014, 96(5), 898-915.

We propose an observation-driven dynamic factor model for mixed-measurement and mixed-frequency panel data. Time series observations may come from a range of families of distributions, be observed at different frequencies, have missing observations, and exhibit common dynamics and cross-sectional dependence due to shared dynamic latent factors. A feature of our model is that the likelihood function is known in closed form. This enables parameter estimation using standard maximum likelihood methods. We adopt the new framework for signal extraction and forecasting of macro, credit, and loss given default risk conditions for U.S. Moody's-rated firms from January 1982 to March 2010. Classification-JEL: C32, G32 Keywords: panel data, loss given default, default risk, dynamic beta density, dynamic ordered probit, dynamic factor model File-Url: https://papers.tinbergen.nl/11042.pdf File-Format: application/pdf File-Size: 474970 bytes Handle: RePEc:tin:wpaper:20110042