either insignificant or significant but not sizeable as a percentage of the 2010 mean. However, when mean differences are significant, the inter-annual distributional differences are significant as well. Concerning the key explanatory variables, the average share of joint income in total income and the average share of female controlled income in disjoint income are higher by 12.2 percentage points and 9.0 percentage points, respectively, in 2013 vis-a-vis 2010. Focusing on the distribution of the sample across the categories based on the share of female income in disjoint income, we observe that while only 5.7 percent of the sample had a share of female controlled income in total disjoint income equal to 1 in 2010, the comparable statistic in 2013 was 12.5 percent. In terms of the distribution of the sample across the categories based on the share of joint income in total income, the share of households in all categories with positive share values is higher in 2013 compared to 2010, and the mean differences are statistically significant across the board.

# **4.2. Empirical Model**

To explore the relative impacts of intra-household cooperation vis-à-vis wives’ empowerment on household welfare, we estimate the following regressions: In both equations, **_h_** and **_t_** denote household and survey round, respectively, and **_Y_** represents the outcome variable. Equation 1 is estimated as a linear panel regression with household fixed effects, separately for each of the logarithmic, real, annual and per capita versions of household gross income and household total, food and non-food consumption expenditures.<sup>8</sup> Equation 2 is estimated as a system of seemingly-unrelated regressions (SURs) in which the five dependent variables are the shares for consumption expenditures on (i) food; (ii) public goods, defined as education, health, clothing, and furnishings; (iii) housing and utilities; (iv) adult goods, defined as alcohol, tobacco, transport, and communication; and (v) other goods, inclusive of recreation, hotels and restaurants, and miscellaneous items. We rectify the absence of household fixed effects in Equation 2 by estimating SURs with correlated random effects instead, as explained below.

> 8 We use the real (and disaggregated) consumption aggregates that are disseminated with the IHPS public use data, which include a re-released unit-record data tied specifically to the panel sub-sample of the IHS3 2010/11 (with adjusted sampling weights) and the corresponding 2010 consumption aggregate, which was re-visited in 2013 following the improvements in the ancillary CPI and food conversion factor data and due to the need to adjust the approach to spatial and temporal deflation of nominal consumption in each round in view of the shorter-than-12month-fieldwork underlying the panel data collection. The 2010 consumption aggregate is expressed in 2013 prices to facilitate comparisons in real terms and accounts for 132 percent inflation in between the survey rounds. The household gross income in 2010 is expressed in 2013 terms also using the same inflationary adjustment. For more information on the methodology underlying the computation of the IHS3 and the IHPS consumption aggregates for the panel sub-sample, please visit https://goo.gl/WzuRZF.

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