Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/86923 
Year of Publication: 
2011
Series/Report no.: 
Tinbergen Institute Discussion Paper No. 11-042/2/DSF16
Publisher: 
Tinbergen Institute, Amsterdam and Rotterdam
Abstract: 
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.
Subjects: 
panel data
loss given default
default risk
dynamic beta density
dynamic ordered probit
dynamic factor model
JEL: 
C32
G32
Document Type: 
Working Paper

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