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α: calibrated so average coauthorship-adjusted count equals average raw count
This paper proposes an improved way of treating experience in estimating wage equations for women when measures of actual experience are lacking. It shows that using a predicted value for experience from occupation-specific equations estimated on another data set containing actual experience is preferable to using either potential experience (time since school leaving) or predicted experience without taking account of the woman's occupation. Results also show that the use of potential experience may bias the estimated impact of factors such as race and schooling on women's wages.