For polynomial regression models with spatially correlated errors, the covariance matrix of the ordinary least-squares estimator (OLSE) is shown to have the same limiting value as that of the generalized least-squares estimator (GLSE) under the same normalization. This implies that the OLSE is...

The ordinary least-squares-based estimator of the disturbance variance is shown to be asymptotically unbiased and weakly consistent irrespective of restrictions on the nonstochastic regressor matrix, when a regression model uses the data collected by a two-stage sampling.

This note studies the Lee and Yu (2009) spurious regression model for the special case where the weight matrix is normalized and has equal elements, and where the nonstationarity is caused by near unit roots. It shows that spurious spatial regression will not occur in a spatially autoregressive...

Building upon the work of Chen et al. (2010), this paper proposes a test for sphericity of the variance–covariance matrix in a fixed effects panel data regression model without the normality assumption on the disturbances.

This paper modifies the Hausman and Taylor (1981) panel data estimator to allow for serial correlation in the remainder disturbances. It demonstrates the gains in efficiency of this estimator versus the standard panel data estimators that ignore serial correlation using Monte Carlo experiments.

Baltagi and Li [Baltagi, B.H., Li, Q., 1992. A note on the estimation of simultaneous equations with error components. Econometric Theory 8, 113-119] showed that for estimating a single equation in a simultaneous panel data model, EC2SLS has more instruments than G2SLS. Although these extra...

Hausman [1978. Specification tests in econometrics. Econometrica 46, 1251-1271] showed that his specification test in panel data, which is based on the contrast between fixed effects (FE) and the random effects (RE) estimators, can also be obtained as a Wald test from an artificial OLS...

This paper considers three examples from the statistics and econometrics literature where OLS is BLUE and demonstrates the easiness of verifying this result with the necessary and sufficient condition (NSC) derived by Zyskind (1967) and more recently Milliken and Albohali (1984). In particular,...

This paper derives a simple lagrange multiplier (LM) test which jointly tests the presence of random individual effects and serial correlation. This test is an extension of the Breusch and Pagan (1980) LM test. It is computationally simple and requires only the OLS residuals. It should prove...

This paper derives Lagrange multiplier tests based on double-length artificial regressions for testing linear and loglinear error component regressions against Box-Cox alternatives. These tests are easy to implement and should prove useful in panel data regressions.