We consider estimation of a panel data model where disturbances are spatially correlated in the cross-sectional dimension, based on geographic or economic proximity. When the time dimension of the data is large, spatial correlation parameters may be consistently estimated. When the time...

This paper is an empirical study of the uncertainty associated with estimates from stochastic frontier models. We show how to construct confidence intervals for estimates of technical efficiency levels under different sets of assumptions ranging from the very strong to the relatively weak. We...

This paper uses multiple comparison methods to perform inference on labor market wage gap estimates from a regression model of wage determination. The regression decomposes a sample of workers' wages into a human capital component and a gender specific component; the gender component is called...

In a presentation to the American Economics Association, McCloskey (1998) argued that "statistical significance is bankrupt" and that economists' time would be "better spent on finding out How Big Is Big". This brief survey is devoted to methods of determining "How Big Is Big". It is concerned...

This paper develops probability statements and ranking and selection rules for independent truncated normal populations. An application to a broad class of parametric stochastic frontier models is considered, where interest centers on making probability statements concerning unobserved...

This paper gives tabulations of the upper percentage points of the maximum absolute value of the k variate normal distribution with common correlation for values of k as high as 500. The tables are useful for performing multiple comparisons procedures in experiments with large numbers of treatments.

The conditions under which ordinary least squares (OLS) is an unbiased and consistent estimator of the linear probability model (LPM) are unlikely to hold in many instances. Yet the LPM still may be the correct model or, perhaps, justified for practical reasons. A sequential least squares (SLS)...