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Creal, Drew
Schwaab, Bernd
Koopman, Siem Jan
Lucas, Andre
Year of Publication: 
Series/Report no.: 
Tinbergen Institute Discussion Paper No. 11-042/2/DSF16
This paper has been accepted for publication in the 'Review of Economics and Statistics'.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.
panel data
loss given default
default risk
dynamic beta density
dynamic ordered probit
dynamic factor model
Document Type: 
Working Paper

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