We construct a growth model with an explicit government role, where more government resources reduce the optimal level of private consumption and of output per worker. In the empirical analysis, for a panel of 108 countries from 1970-2008, we use different proxies for government size and...

In a panel data framework applied to Portfolio Distance-to-Default series of corporate sectors in the euro area, this paper evaluates systemic and idiosyncratic determinants of default risk and examines how distress is transferred in and between the financial and corporate sectors since the...

This paper proposes a quantile regression estimator for a heterogeneous panel model with lagged dependent variables and interactive effects. The paper adopts the Common Correlated Effects (CCE) approach proposed by Pesaran (2006) and Chudik and Pesaran (2015) and demonstrates that the extension...

This paper presents a new approach to estimation and inference in panel data models with a multifactor error structure where the unobserved common factors are (possibly) correlated with exogenously given individual-specific regressors, and the factor loadings differ over the cross section units....

The presence of cross-sectionally correlated error terms invalidates much inferential theory of panel data models. Recently work by Pesaran (2006) has suggested a method which makes use of cross-sectional averages to provide valid inference for stationary panel regressions with multifactor error...

I consider linear panel data models with unobserved factor structures when the number of time periods is small relative to the number of cross-sectional units. I examine two popular methods of estimation: the first eliminates the factors with a parameterized quasi-long-differencing (QLD)...

Bestehende Frühwarnsysteme für wirtschaftliche Krisen haben die Auswirkungen des Teufelskreises zwischen Banken und Staaten auf die Finanzstabilität nicht erkannt. Der vor-liegende Beitrag stellt ein neues Prognosemodell für Kredit-risiken im Banken- und Staatssektor vor, das die...