Beyond Gender: A Logistic Ordinal Regression Model for Earnings Differences.

How important is gender in predicting an individual's personal earnings? The hotly-debated "gender gap" suggests that women do not earn as much as men for equal work. This work develops two multiple logistic ordinal regression models that measure the effect of job and personal characteristics on personal earnings of salaried and hourly-wage workers in the Maine labor force. The models produced not only exhibit substantial predictive accuracy, but also begin to unwind the complex effects that factors such as education, industry, location, and unionization have on what one makes. [ABSTRACT FROM PUBLISHER]