Figure 4 documents the results. Panels A and B present our general female and male segmentation indices—how similar is the gender composition of a firm’s workforce to a focal employee—by firm size and also their simulated counterparts. The dark red bars are the actual segmentation levels, while the light blue bars represent predicted segmentation based upon India’s workforce composition and firm size. For women, segmentation levels are highest among the smallest firms and largest firms. By contrast, Monte Carlo simulations predict a uniform decline in firm size; for the largest firms, the expected segmentation levels are basically the same as those contemplated above for the economy as a whole. This pattern is quite interesting as it suggests root causes of abnormal segmentation are most prevalent among small enterprises and very large establishments, which have different economic properties and competitive environments. Panel B, by contrast, shows that gender segmentation for men is consistently higher than anticipated by the Monte Carlo simulations but also uniformly declining in firm size.

Panels C and D turn to our estimations of segmentation that focus on the match of employees to the gender of the owner. We can only calculate these metrics for establishments with ten employees or fewer. It is, of course, possible to simulate expected levels of owner-based segmentation for larger establishments, and we do this extension so that we have baselines than are comparable to Panels A and B. Owner-based segmentation for women-owned enterprises shows its greatest deviation from expectation for the smallest firms of 1-3 employees, with deviations shrinking substantially for larger establishments. By contrast, male-owned establishments have a more modest deviation from baseline for the smallest firms, but this appears to widen somewhat for larger establishments. Said differently, it appears women business owners are increasingly likely compared to random hiring to pull workers of both genders while scaling small enterprises, while men have a greater capacity to continue scaling with a focus on male employees.

We have also investigated a comparison point to the United States using the Longitudinal Employer-Household Dynamics (LEHD) database. The LEHD is a confidential database maintained by the U.S. Census Bureau. Sourced from required state unemployment insurance reporting, the LEHD provides linked employer-employee records for all private sector firms in 29 covered states. Among the information included for each employee is the worker's quarterly salary, age, gender, citizenship status, and place of birth. This wealth of information allows us to observe directly the establishment level workforce composition by gender in a manner similar to the Indian data. (By comparison, the LEHD does not record the gender of the business owner.) Kerr et al. (2015) provide additional details.

Our LEHD estimates are not disclosed, and we only provide an approximate benchmark in this first report for our India data. In the United States, both men and women tend to match with a workforce that is approximately 60% their own gender during the 2001-2010 period. This shows quite limited variation over states, and the time trend is overall very weak. The United States has roughly equal employment of both genders, so the expected shares are about 50%. Thus, the United 27