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.

The papers included in this special issue are primarily concerned with the problem of cross section dependence and heterogeneity in the analysis of panel data models and their relevance in applied econometric research. Cross section dependence can arise due to spatial or spill over effects, or...

This paper examines the permanence of excess capacity in the US airline industry. To avoid the problems with the standard engineering measure of capacity utilization, load factor, we define and measure capacity as an economic concept. Two measures of economic capacity utilization are then...

This paper sets up a nested random effects spatial autoregressive panel data model to explain annual house price variation for 2000–2007 across 353 local authority districts in England. The estimation problem posed is how to allow for the endogeneity of the spatial lag variable producing the...

Predicting the demand for motor gasoline over the last ten years has proven a most frustrating experience. Up until 1973, industry analysts felt considerable assurance in applying historical growth rates that averaged approximately 5 percent per year. Who in 1973 would have predicted that...