This paper extends the cross sectionally augmented panel unit root test proposed byPesaran (2007) to the case of a multifactor error structure. The basic idea is to exploitinformation regarding the unobserved factors that are shared by other time series in additionto the variable under...

This paper proposes a theoretical framework to analyze the impacts of credit and technologyshocks on business cycle dynamics, where firms rely on banks and households for capitalfinancing. Firms are identical ex ante but differ ex post due to different realizations of firmspecific technology...

We investigate the effect of forecast uncertainty in a cointegrating vector error correctionmodel for Switzerland. Forecast uncertainty is evaluated in three different dimensions. First,we investigate the effect on forecasting performance of averaging over forecasts fromdifferent models...

This paper considers a multivariate t version of the Gaussian dynamic conditional correlation(DCC) model proposed by Engle (2002), and suggests the use of devolatized returnscomputed as returns standardized by realized volatilities rather than by GARCH type volatilityestimates. The t-DCC...

This paper considers the implications of the permanent/transitory decomposition of shocksfor identification of structural models in the general case where the model might contain morethan one permanent structural shock. It provides a simple and intuitive generalization of theinfluential work of...

This paper introduces a novel approach for dealing with the curse of dimensionality in thecase of large linear dynamic systems. Restrictions on the coefficients of an unrestricted VARare proposed that are binding only in a limit as the number of endogenous variables tends toinfinity...

This paper considers the statistical analysis of large panel data sets where even afterconditioning on common observed effects the cross section units might remain dependentlydistributed. This could arise when the cross section units are subject to unobserved commoneffects and/or if there are...