Ethnic and gender disparities in U.S. agriculture: An analysis of technology and technical efficiency differentials

Abstract

We explore ethnic and gender disparities in U.S. agriculture by comparing productivity gaps between male- and female-headed family farms, and between non-Hispanic White and minority-headed family farms. Using Agricultural Resource Management Survey data from 2017 to 2020, propensity score matching techniques are applied to obtain comparable samples based on observable covariates. Statistical tests reveal structural differences in production technologies between male- and female-headed farms, and between non-Hispanic White and minority-headed farms, thus requiring the estimation of separate production technologies for each group. Accordingly, a stochastic metafrontier framework is used to envelop the group frontiers and assess technology gaps. The results indicate that female and minority-principal operators not only use different production technologies but are also less proficient at combining inputs to maximize farm output. The results also reveal within-group gender and ethnic differences—ceteris paribus, among non-Hispanic White and minority-led farms, female producers generated substantially less output compared to their male counterparts. Similarly, among male principal operators, Hispanic producers generated more output compared to their non-Hispanic White and non-Hispanic non-White counterparts.