States displays a much more modest and stable level of segmentation compared to India at the establishment level. Ideally, researchers in other countries with administrative data of workforce gender can also provide comparison points.

# **_Correlates of Female Activity in India_**

Table 6a presents our first district level regression results that estimate the correlates of female participation in economic activity and gender segmentation, measured as the average over the period 2001-2010. The estimations in Tables 6a and 6b use information on 421 districts in India, are weighted by log district population and report robust standard errors. Table 6a suggests that a higher female-to-male ratio in population is highly correlated with heightened activity among females, including higher segmentation in female-led plants and lower segmentation in male-led plants. A larger demographic dividend, measured as the ratio of working age population relative to non-working age population, is also associated with increased activity and lower segmentation, especially in male-led plants. In the case of services sector, however, a higher working age population is significantly correlated with higher segmentation in female-led plants. Another difference between unorganized manufacturing and services is in the role of technology. Interestingly, the proportion of plants using the Internet in the services sector is associated with larger female employment share and lower segmentation in both the male-led and the female-led establishments. Comparably, we find null effects of Internet usage among plants on female based activity or segmentation in unorganized manufacturing. Besides these, most other district level traits are not found to be correlated with either the participation of women in manufacturing and services or gender segmentation. The result continues to hold across a wide range of specifications and sample restrictions (e.g., young plants, high-wage plants and so on).

Table 6b repeats the set-up in Table 6a using the change in female activity over the period covering 2001 to 2010 as the dependent variable. In addition to the listed covariates, these regressions also control for the initial value of the dependent variable. The most interesting feature of this table is that the state of electronic infrastructure and technology, as measured by the share of plants using the Internet, is strongly correlated with the decline in female participation in manufacturing activity and the concurrent rise in services. Further, the use of Internet among plants is also associated with a decline in segmentation in both manufacturing and services. Physical infrastructure, measured as the local district level composite comprising of measures on the quality of roads, telecom, electricity and safe drinking water, is also associated with heightened shares of women-led enterprises, particularly in informal manufacturing. In both the sectors, physical infrastructure is also significantly and positively correlated with the female employment shares and a decline in segmentation among male-led establishments. It is, however, associated with increased segmentation among female-led plants. These results are broadly robust to including only young plants or only plants paying higher wages, or to excluding some of the explanatory variables such as the spatial fixed effects measured via the distance from the biggest cities.

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