This paper considers the problem of testing cross-sectional correlation in large panel data models with serially-correlated errors. It finds that existing tests for cross-sectional correlation encounter size distortions with serial correlation in the errors. To control the size, this paper...

In the first half of the paper we study spurious regressions in panel data when the cross-section and time-series dimensions are comparable. Asymptotic properties of the least-squares dummy variable (LSDV) estimator and other conventional statistics are examined. We show that the LSDV...

This paper surveys recent developments and provides Monte Carlo comparison on various tests proposed for cointegration in panel data. In particular, tests for two panel models, varying intercepts and varying slopes and varying intercepts and common slopes, are presented from the literature with...

This paper proposes a residual-based Lagrange Multiplier (LM) test for the null of cointegration in panel data. The test is analogous to the locally best unbiased invariant (LBUI) for a moving average (MA) unit root. The asymptotic distribution of the test is derived under the null. Monte Carlo...

In this paper, we study the limiting distributions for the ordinary least squares (OLS), the fixed effects (FE), first difference (FD), and the generalized least squares (GLS) estimators in a linear time trend regression with a one-way error component model in the presence of serially correlated...

In this paper, we study the asymptotic distributions for least-squares (OLS), fully modified (FM), and dynamic OLS\ (DOLS) estimators in cointegrated regression models in panel data. We show that the OLS, FM, and DOLS estimators are all asymptotically normally distributed. However, the...