The deficit of a working age adult can explain the lower agricultural income in female-headed households in our sample. Surprisingly, however, female-headed households report higher incomes from wage work. It could be that female-headed households where men are missing may also be more likely to suffer from a lack of access to land, making wage work or self-employment more important as means of income. It is interesting, however, that while we see limited signs of differences in wealth, we do not see differences in terms of assets or land ownership or value.

# _Pooled estimates_

As we discuss, our choice of outcomes is based on the overlap between variables where the literature suggests possible effects and the data available in VARHS. Thus, we analyze RTP3 impacts on agricultural production patterns, employment outcomes, and household income.<sup>16</sup> In discussing impacts on agriculture, we estimate impacts on crops and livestock in both production and trade. Following <mark>Shamdasani (2016)</mark> , we also distinguish between export and non-export crops. Unfortunately, our data do not allow for construction of reliable indicators of educational or health outcomes. To better understand mechanisms behind the observed results, especially when they vary by gender, we drew on the insights from qualitative work.

# _Agricultural production and trade_

Our analysis suggests that the RTP3 project had statistically significant impacts on both crop production and the amount of crop production traded (Table A.6). Besides being statistically significant, the impact is large in magnitude. The size of the treatment effect on crop production is about 15 percent of the baseline mean for male-headed households, or the equivalent of about US$100 annually. However, for femaleheaded households, the impact is much smaller: less than 0.5 percent of the baseline mean.

A few factors could explain this difference. Since there are fewer working-age adults in female-headed households (Table A.4a), these households have less of one of the critical inputs into agricultural production: household labor. In the absence of market frictions, households should be able to flexibly hire labor from outside the household to compensate. But this is not the case in the presence of market frictions, which appears to be the case for most agricultural households (La Fave and Thomas, 2016). For female-headed households, missing income from a working age adult may result in additional liquidity constraints and borrowing may be impossible due to underdeveloped credit markets. Indeed, we did not find any evidence on the use of credit.<sup>17</sup> Our qualitative data corroborate the access to capital channel. We found that the households that appeared to have benefited the most from improved roads were households that either increased productivity by hiring machinery for ploughing and processing crops and transporting them to market or that were able to switch from cropping paddy to trees like acacia or orange. Both of these changes required up-front payment, with returns on the investment following with a lag of a few months or in the

> 16 We are restricted in the types of effects we can analyze because we rely on data from the VARHS for household outcomes and are restricted both by the choice of variables in this data set and the small number of observations for some variables (such as agricultural inputs).

> 17 Results available upon request.

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