Analyzing gender gap in agricultural productivity: Evidence from Ethiopia

Abstract

Women make up more than 50% of the agricultural labor force but contribute less than 30% to agricultural productivity. Agriculture is the main source of livelihood in Ethiopia but by contributes more than 35% to GDP, 90% to forex earnings, and 70% to employment sources. So Improving economic well-being ensuring sustainable development, and reducing poverty is impossible by ignoring the role of women. Consequently, the main objective of the study is to investigate the gender gap in agricultural productivity using national Panel data of 3474 households which were collected in 2017 and 2019 by the Policy Studies Institute for AGP II baseline study and midline evaluation. Among these, 69% (2404) were male-headed and 31% (1070) were female-headed households. The panel data were combined with DID, Oaxaca Decomposition, and the Random effect Tobit model to investigate the gender gap. The result from the DID Method of Impact Evaluation shows that female-headed households were less productive by 3.7% and 2.05 quintals per hectare when measured in terms of value in birr and quintals per hectare compared to male-headed households. In contrast, male-headed households were more productive by 4% and 2.05 quintals compared to female-headed households. Additionally, the results from the pooled and random effect Tobit model showed that soil fertility, sex of the household head, slope of the land, total livestock holding in TLU, extension contact, use of inorganic fertilizer, credit use, machinery use, and plantation method are among the determinants of the gender gap in agricultural productivity. Furthermore, results from the Oaxaca decomposition show that a gender productivity difference between male and female-headed households was roughly 11.2% when measured by value and 5% when measured by an area-weighted formula. The main finding of the study is that endowment effects were less likely to have a significant impact on the productivity gap than structural effects did. Differences in the unexplained characteristics of men and women may also contribute to the considerable productivity gap between male-headed and female-headed households. Therefore, working on women's empowerment to improve their structural disadvantages through various training programs that favor women or gender-mainstreamed extension training programs for lowering gender productivity differentials is a possible policy option.