This paper introduces a novel approach to study the effects of common shocks on panel data models with endogenous explanatory variables when the cross section dimension (N) is large and the time series dimension (T) is fixed: this relies on conditional strong laws of large numbers and...

It is well known that confidence intervals for weakly identified parameters are unbounded with positive probability (e.g. Dufour, Econometrica 65, pp. 1365-1387 and Staiger and Stock, Econometrica 65, pp. 557-586), and that the asymptotic risk of their estimators is unbounded (Pötscher,...

We derive general formulae for the asymptotic distribution of the LIML estimator for the coefficients of both endogenous and exogenous variables in a partially identified linear structural equation. We extend previous results of Phillips (1989) and Choi and Phillips (1992) where the focus was on...

Nelson and Startz (Econometrica, 58, 1990), Maddala and Jong (Econometrica, 60, 1992) and Wolgrom (Econometrica, 69, 2001) have shown that the density of the two-stage least squares estimator may be bimodal in a just identified structural equation. This paper further investigates the conditions...

Cragg and Donald (1996) have pointed out that the asymptotic size of tests for overidentifying restrictions can be much smaller than the asymptotic nominal size when the structural equation is partially identified. This may lead to misleading inference if the critical values are obtained from a...

The average exponential tests for structural change of Andrews and Ploberger (Econometrica, 62, 1994) and Andrews, Lee and Ploberger (Journal of Econometrics 70, 1996) and modifications thereof maximize a weighted average power which incorporates specific weighting functions in order to make the...

In this paper, we consider a partially linear panel data model with cross-sectional dependence and non-stationarity. Meanwhile, we allow fixed effects to be correlated with the regressors to capture unobservable heterogeneity. Under a general spatial error dependence structure, we then...

In this paper, we propose a panel data semiparametric varying-coefficient model in which covariates (variables affecting the coefficients) are purely categorical. This model has two features: first, fixed effects are included to allow for correlation between individual unobserved heterogeneity...

In this paper, we consider a semiparametric single index panel data mode with cross-sectional dependence, high-dimensionality and stationarity. Meanwhile, we allow fixed effects to be correlated with the regressors to capture unobservable heterogeneity. Under a general spatial error dependence...