Overall, we see that male-headed households have higher agricultural productivity (measured as the value of harvested crops over the last 12 months per hectare), this advantage being significant for food crops only. In terms of explanatory variables, we see a large difference between female- and male-headed households for total land area cultivated, with male-headed households cultivating nearly twice as much. Though the total land area cultivated is substantially lower for women, the number of fields managed are only slightly lower. This indicates that the average size of plots managed by female-headed households is lower than that for male-headed households.

Female household heads also tend to be older than their male counterparts, be less educated, and have a higher incidence of disability. The dependency ratio is 32 percent higher in female-headed households. Female-headed households also have a lower number of household laborers – mostly deriving from lower household male labor. All labor variables are defined as the number of workers employed on household land during the last 12 months. Moreover, the prevalence of chemical fertilizer use and pesticide use is less than half that of male-headed households. Male-headed households are also 36 percentage points likelier to cultivate an export crop (cashew, cacao, coffee, cotton, rubber or palm oil).

Next, we investigate these same differences between male- and female-headed households in 2016, using data from the Enquête Nationale sur la Situation de l'Emploi et le Secteur Informel (ENSESI). Identically to the 2008 ENV, the sample is representative at the national, regional and urban/rural levels. The sample contains 10,392 households overall, of which 5,910 were agricultural households, and 4,529 households report some production and have information available for covariates included in the analysis. We implement the same procedure of excluding observations with productivity above the 99th percentile or below the 1st percentile, leading to a 3,936 households data set of which 517 are headed by women (13.1 percent), while 3,419 (86.9 percent) are headed by men. The share of female-headed households is thus held constant between 2008 and 2016 in our data.

As in 2008, some differences in education, household male labor, input use and export crop adoption are observed between households excluded and those remaining in the sample. All descriptive statistics and regressions are weighted by the sample weight which is the inverse probability of a household to be included in the sample. The sample design exploited two-stage clustered sampling methods. At the first stage, a certain number of EAs were randomly selected with equal probability, and with implicit stratification by urban/rural and region while in the second stage 12 households were randomly selected within each EA.

In Table 2, we present the 2016 results for the overall sample average and for female-headed and maleheaded households separately. Similarly, to 2008, we report in the table the significance levels of all differences, using a t-test. The simple difference shows no significant difference in overall agricultural productivity between female-headed households and male-headed households. Note that the summary statistics presented in Table 2 are fairly sensitive to winsorization, while our gender gap results are not, remaining substantially unchanged regardless of how the data is trimmed. Female-headed households cultivated far less land than male-headed households. As in 2008, female household heads in 2016 tend to be older, less educated and have a higher incidence of disability. Households headed by women use less hired labor and substantially less male household labor, though they use more female and child household laborers. The dependency ratio in female-headed households is approximately 39 percent higher; they also use less fertilizer and pesticide and are 38 percentage points less likely to be engaged in export crop cultivation.

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