overall agricultural yield in the sector (e.g. Horrell and Krishnan 2007). Another approach to test for allocative inefficiency is to estimate each input’s marginal value product separately for male and female farmers and to observe whether this is above or below the input’s factor price (Tiruneh _et al._ 2001).

Inter-household analyses of the gender gap tend to find a statistically significant and practically substantial gap in mean yield (or value of yield) of around 20-30% in favor of male farmers. The overwhelming conclusion from these studies has been that the gap is driven by differences in resource endowment between male and female headed households, rather than technical efficiency (Horrell and Krishnan 2007; KinkingninhounMedagbe _et al._ 2010; Oladeebo and Fajuyigbe 2007), with a few exceptions (Holden, Shiferaw, and Pender 2001; Quisumbing 2001).

Characteristics accounted for in the tests for technical efficiency include physical inputs (organic and chemical fertilizer, crop protection chemicals, improved seed varieties, mechanization), human capital (labor, education, extension services, childbearing), quality of land and water access, land investment (duration left fallow, erosion control and water harvesting structures, planting of tree crops), access to credit and input and output markets, and informal institutional constraints (norms regarding division of crop production and assignment of household responsibilities).

One limitation of these tests for technical inefficiency is that they do not quantify the individual contribution of endowment differences relative to the simple difference in agricultural productivity. A detailed decomposition of the endowment gap would be useful for designing policy programs to close the gap and highlighting areas for future in-depth study.

Another limitation of inter-household studies is that, while the gap between male- and female-headed households is policy relevant in its own right, it is important to distinguish the inter-household gender gap from the overall gender gap. The majority of female-managed plots in Sub-Saharan Africa are located within maleheaded households, the typical structure of which is fundamentally different from the typical structure of female-headed households. In particular, female-headed households are overwhelmingly characterized by cases where the husband has passed away, is a migrant laborer, or is polygamously married and member of a different household. Analysis of the inter-household gap therefore draws inference from a subset of femalemanaged plots quite distinct from the typical female-managed plot, and categorizes female-managed plots as “male” and vice-versa.

Finally, given fundamental differences between female-headed and male-headed households, these tests for technical inefficiency are likely to be invalid due to omission of important unobservable characteristics from the analysis.

To address the latter two concerns, intra-household analyses of the gender gap use plot-manager level agricultural data from panel surveys and restrict the study sample to households in which both male and femalemanaged plots are present. This allows these studies to use a fixed effects estimator to account for all unobserved household characteristics, as well as observed farmer and plot-level characteristics, substantially reducing the likelihood of omitted variables confounding the analysis.

The most rigorous of these studies first show that unobserved household characteristics and a set of plot-level characteristics are insufficient to completely explain the gap between female and male productivity. The 3