Estimates of the effect of employment on women's risk of partner violence in cross-sectional studies are subject to potential "self-selection bias." Women's personal choice of whether to pursue employment or not may create fundamental differences between the group of women who are employed and those who are not employed that standard regression methods cannot account for even after adjusting for confounding. The aim of this study is to demonstrate the utility of propensity score matching (PSM), a technique used widely in econometrics, to address this bias in cross-sectional studies. We use PSM to estimate an unbiased effect-size of women's employment on their risk of experiencing partner violence in urban and rural Tanzania using data from the 2010 Tanzania Demographic and Health Survey (DHS). Three different measures of women's employment were analyzed: whether they had engaged in any productive work outside of the home in the past year, whether they received payment in cash for this productive work, and whether their employment was stable. Women who worked outside of the home were significantly different from those who did not. In both urban and rural Tanzania, women's risk of violence appears higher among women who worked in the past year than among those who did not, even after using PSM to account for underlying differences in these two groups of women. Being paid in cash reversed this effect in rural areas whereas stability of employment reduced this risk in urban centers. The estimated size of effect varied by type of matching estimator, but the direction of the association remained largely consistent. This study's findings suggest substantial self-selection into employment. PSM methods, by compensating for this bias, appear to be a useful tool for estimating the relationship between women's employment and partner violence in cross-sectional studies.