Back to the plough: Women managers and farm productivity in India. (December 2019) - Mahajan, Kanika
Highlights: The paper looks at productivity differentials across women and men managed farms in India. We find that productivity on women managed farms is on an average 11% lower than male managed farms. This gap reduces to 7% once crop choice, input usage, location and farmer characteristics are controlled for. Semi-parametric decomposition shows that productivity differential remains largest in lower part of the value distribution. Heterogeneity analyses shows inadequate experience among women managers as a contributor to the residual productivity gap. Abstract: In India, role of women as farm managers has been veiled behind image of men as primary decision makers on farms. Data shows that approximately 8% farm households had women farm managers in India in 2004, and this number increased to 11% in 2011. This rising phenomenon of farm management by women begets an in depth understanding about these farms, including, differentials in productivity levels across men and women managers. This paper uses three measures to capture productivity – production value, profit value and crop specific yields. Results show that total farm production and profits are lower by approximately 11% in households where women manage farms. This falls to 7% when controls for crop choice, input usage, location and farmer characteristics are included. The main mediating factors in explaining the productivity gap are crop choice and input usage, explaining almost 45% of the productivity gap. Further, the paper provides suggestive evidence on mechanisms contributing to the remaining productivity difference that cannot be explained by differences in observed characteristics. It shows that inadequate experience of women farm managers in agricultural production processes can be an important factor behind the remaining gap. The study makes two contributions to the literature – one, it is the first quantitative study in the Indian context on gender differentials in farm productivity and second, it applies semi-parametric decomposition techniques to look at the productivity differentials along the entire distribution.