differential quantity of inputs/outputs used/produced by female and male farmers (such as land) and gender differences in input prices may impact productivity gaps. Also, it seems likely that the choice of unit of analysis (gender of household head or gender of plot farmer/owner) has significant impact on study results, with plot level analysis appearing to capture more of the gender productivity gap.

In this paper, we examine gender-based productivity differences in Africa’s most populous country, Nigeria. We bring to bear a nationally representative data set to examine first, if such a cross-gender productivity differential across plots exists in Nigeria, and second, to examine which factors in the production process seem to be driving it. Nigeria represents a particularly interesting case due to differences in the North and South regions of the country. The analysis is conducted separately for these regions based on the hypotheses that agro-ecological and socioeconomic conditions differ so substantially that gender differences are also likely to vary. To carry out this analysis, we utilize the Oaxaca-Blinder decomposition method which allows us to decompose the gender gap into (i) the portion due to observable differences in the factors of production (endowment effect) and (ii) the unexplained portion due to differences in returns to the same observed factors of production (structural effect). This method further allows us to identify the contribution of each of the factors of production to (i) and (ii).

The few studies on Nigerian gender differentials have focused on particular states or regions of the country and most have used household level data (Peterman et al., 2011; Timothy and Adeoti, 2006; Oladeebo and Fajuyigbe, 2007). Peterman et al. (2011) use data collected as part of an evaluation of the second phase of the World Bank sponsored National Fadama Development Project covering 12 Fadama states in northern Nigeria. Using household level data, the authors find persistent lower productivity among female headed households, even when accounting for a range of socio-economic variables, agricultural inputs and crop choices (Peterman et al., 2011). They also found that the results vary across crops as well as by agro-ecological zone in Nigeria and inclusion of biophysical characteristics, suggesting either cultural or regional gender differences or crop-specific comparative advantages that interact with productivity and gender. Timothy and Adeoti (2006) use a Cobb-Douglas production function to analyze data on cassava farmers in Ondo and Ogun states in Nigeria and their results suggest that while female farmers are more economically efficient than male farmers, male farmers have higher average technical and allocative efficiency than female farmers. While the study by Oladeebo and Fajuyigbe (2007) conducts its gender analysis at the plot level, the study was carried out exclusively on data for the tropics in Osun State, South-western Nigeria. The authors found that women farmers are more efficient technically than men farmers with mean technical efficient indices of 0.904 and 0.897 respectively, but the difference is not significant.

In this study, we find that women in the North produce 28 percent less than men after controlling for observed manager characteristics and factors of production—a result that is very similar to the Peterman et al (2011) who find a 32 percent difference. In our decomposition results, we find that the unexplained portion of the gender gap in the North is bigger than the explained portion at the mean. Although women in the North have access to less productive resources than men, the results indicate that even if provided with the same level of inputs, significant differences may 3