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 a good approximation to the probability generating process. A sequential...

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 a good approximation to the probability generating process. A sequential...

An intuitively appealing method for estimating gender wage gaps by industry is shown to yield estimates that vary according to the arbitrary choice of left-out reference groups for non-industry categorical variables, such as race and marital status. This study uses data from the Current...

An intuitively appealing method for estimating gender wage gaps by industry is shown to yield estimates that vary according to the arbitrary choice of left-out reference groups for non-industry categorical variables, such as race and marital status. This study uses data from the Current...

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 a good approximation to the probability generating process. A sequential...