Agriculture Questionnaire, which solicited information on land areas, labor and non-labor input use, crop cultivation and production at the plot<sup>5</sup> -level, separately for the reference rainy and dry seasons.

While the data do not include direct measures of either intra-household cooperation or wives’ empowerment, the IHPS included over 40 questions asked at varying levels of observation across all income domains that could be used to identify up to 2 household members that decide on the use of each unique source of income. Using this information, we calculate total gross income<sup>6</sup> that is controlled solely by females; solely by males; and jointly by females and males; and use the share of joint controlled income in total gross income as a proxy for intra-household cooperation, and the share of female controlled income in total disjoint gross income as a proxy for wives’ empowerment. Using the share of female controlled income in total disjoint gross income avoids difficulties in interpreting the coefficient that would arise if we used female share in total income. Conceptually, it also allows for a cleaner distinction between cooperation leading to joint control of income versus wives’ bargaining power leading to greater control over disjoint income. Appendix II provides the details on the computation of intra-household income shares.

Additionally, we would like to allow for non-linear impacts of income shares on our outcomes of interest. However, including a squared term may magnify attenuation bias if there are measurement errors in our income shares variables (Griliches, 1986). Income shares are, of course, based on measures of income, which suffer from measurement error. As noted by Bound et al. (1994), fixed effects can compound measurement error, particularly when the variable of interest is highly correlated over time, as it is here. Therefore, instead of using intra-household income shares as calculated above, we divided both income shares of interest into five categories. Three categories map to income share terciles calculated in each round among households where income shares are positive but less than 1. The fourth category contains households where the income share is equal to zero, and the fifth contains households where the income share is equal to one.<sup>7</sup> Table 2 presents the relevant variable means in each round, and the results from the tests of mean and distributional differences. On our outcome variables, the inter-annual differences in means are

> 5 A plot was defined as a continuous piece of land on which a unique crop or a mixture of crops is grown, under a uniform, consistent crop management system, not split by a path of more than one meter in width. Plot boundaries were defined in accordance with the crops grown and the operator.

> 6 Total disjoint gross income is defined as the sum of (i) gross income controlled solely by females and (ii) gross income controlled solely by males.

> 7 While misclassification errors may remain, Goldstein et al. (2008) argue that small misclassification probabilities result in small changes in parameter estimates. To test for possible misclassification bias, we estimated our regressions using only three categories for each share of interest, namely zero, some, and all; as well as using four categories where “some” is broken down to above and below the median share.  It is reasonable to posit that, if misclassification is a problem, it would become more pronounced as categories are defined finer. The results using three and four categories are substantially similar to the results shown here, with goodness of fit measures being slightly higher for the preferred specification discussed in the subsequent section. The results from these sensitivity analyses are available upon request.

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