authors then either introduce an omitted variable to explain the remaining gap, such as duration left fallow (Goldstein and Udry 2008) or physical and labor inputs (Udry 1996), or explore how the gap differs by household-level characteristics, either by introducing interaction terms (Akresh 2008) or re-running the analysis on separate samples (Akresh 2008; Peterman _et al._ 2011).

Intra-household studies performed so far have relied on small samples within geographically limited settings that raise concerns about the external validity of results within or across countries. The seminal paper, Udry _et al._ (1995), examines a sample of 150 households in six villages, while (Goldstein and Udry 2008) examine 60 married couples in four enumeration areas. We are aware of only one study (Akresh 2008) that examines nationally representative data using this method. There is no methodological reason that intra-household analysis cannot be performed on nationally representative panel data.

This intra-household analysis suffers from one of the same limitations of inter-household analysis in that, while it rigorously identifies one subset of characteristics that contribute to the gender gap, it does not quantify the contribution of the complete set of individual endowments to the gap. In cases where the gap is not fully explained (Peterman _et al._ 2011), the apparent difference in returns to endowments is not systematically explored.

A common solution to this problem in the labor economics literature has been to estimate the contribution of characteristics to the gap by examining changes in the coefficient on the gender indicator (the size of the gap) as covariates (characteristics) are sequentially introduced to the analysis.

Gelbach (2009), however, shows that the change in the coefficient on the gender indicator depends on the order in which the covariates are introduced and that estimates from this procedure are, in that sense, path dependent. Sequential addition of covariates also does not quantify differences in returns to inputs and characteristics between male and female farmers.

In some cases, returns to characteristics are estimated over the female and male samples separately and compared to more clearly identify areas where differences in returns exist (Hill and Vigneri 2011). The relevance of these differences in returns is not clear, however, unless they are scaled to the size of the endowment for that characteristic.

An alternative procedure often applied in labor economics is the well-known Oaxaca-Blinder Decomposition (Blinder 1973; Oaxaca 1973), described in detail in section 4. Kilic, Palacios-Lopez, and Goldstein (2013) apply this procedure for the first time to the agricultural productivity gap. O-B decomposition is not pathdependent and, within a partial-equilibrium framework, quantifies the relative contribution of factors to the gap. It decomposes contributions to the simple difference into a component accounted for by endowments (endowment effect) and returns to these endowments (structural effect).

Kilic, Palacios-Lopez, and Goldstein (2013) find that female-managed plots in Malawi are 25% less productive than male-managed plots, and that 82% of this difference is explained by observable characteristics. They find that the primary contributions to the endowment gap are higher levels of adult male labor and selection of export crops, and that the primary contributions to the structural gap are the child dependency ratio (less time to devote to productive activities) and returns to male labor (possibly difficulty supervising male household 4