the second (factor-analysis) decision making index (Table 2, Panel B, Column 3).13 Next, we
separately analyze the impact on women who began the year below (above) the median decision
making power. We find that the average effect is largely driven by increases in decision making
ability for women who were below the baseline median (comparing Panels A and B in Table 2b) -
a fact consistent with initially less-empowered women gaining decision making ability through
increased financial savings and control over committed assets. In contrast, we find no such
treatment effect for married men (Table 2b, Panel A, Columns 5-8).
Table 3 reports the impact for married women for each of the nine household decision
categories that comprise the indices used in Table 2. Panel A shows the results for the full
sample. We find impact on two decisions: expensive purchases and number of children. For
women below the median in terms of household decision making power (Panel B), we find a
significant impact of treatment assignment regarding purchases of expensive items, decisions to
assist family members and purchases of items for personal use. For women above the baseline
median (Panel C), the categories with significant treatment impacts are those beyond financial
decision making: schooling for children and number of children.
Next, we examine whether the increased reported decision making led to a difference in the
types of goods purchased for the household. By increasing the assets available for lumpy
purchases, the mere presence of the SEED account may increase female decision-making power
in the household and hence increase the likelihood that the household acquires female-oriented
durables. Naturally, if the account is held in the women’s name this effect should be even
stronger.
We use three categories for expenditures: house repair, female-oriented durables (washing
machines, sewing machines, electric irons, kitchen appliances, air-conditioning units, fans and
stoves), and other durables (vehicles/motorcycles, entertainment and recreational goods). Table 4
13 The standard deviation shift is calculated by dividing the point estimates of 0.056 and 0.198 from Table 2
by the standard deviations of each index for married women as found in Table 1..