The paper investigates the role of insurance and technological progress on the rising health inequality across income groups. Using large scale federal survey datasets, I document new findings which suggest the role of timing of health investments as a key channel behind increased health disparities. I then develop a dynamic stochastic life-cycle model of an economy where individuals choose insurance, timing of investment into their health capital, consumption, and savings. My estimates show that while rich and poor have comparable health investments, there are substantial differences in their timing. The estimated model is able to explain about half of the gap in life-expectancy across income/ wealth groups. I show that technological innovation and insurance interacts with the timing of investments and have a first order effect on disparities. While a non-uniform increase in the productivity of the medical sector -- one where there are improvements in treating early stages of cancer for example, but none for stage 4 -- can lead to increase in inequality in life-expectancy, a uniform increase in the productivity leads to a reduction. Focusing on the role of insurance, I find that while Medicaid alleviates health inequality, private insurance exacerbates it by almost twice as much. Finally, I find that a policy of ``Medicare-for-all" not only reduces health inequality, it could also lower existing income inequality.

Presentations: USC Marshall Macro Day; Dissertation Workshop, Federal Reserve Bank of St. Louis; Essen Health Conference; YES2020; Econ Brown Bag, Olin Business School; WEAI; 2020 Kansas Health Economics Conference; Fall 2019 Midwest Macroeconomics Meetings; Fall 2019 Midwest Economics Theory; Econ Brown Bag, Olin Business School; EEA-ESEM 2019; 2019 SED Annual Meeting; 2019 ASHEcon; 2019 Midwest Economics Association/SOLE; Fall 2018 Midwest Macroeconomics Meetings; 2018 EGSC; 2018 EEA-ESEM; CHEPAR Meeting, Institute for Public Health, WashU

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We study a dynamic macro model to determine the optimal choice of stay-at-home and vaccination policies. We find that optimal lockdown policies initially significantly restrict employment but allow for partial loosening before the peak of the epidemic. Under a variety of scenarios the optimal vaccination policy (when a vaccine arrives) has an almost bang-bang property: vaccinate at the highest possible rate and then rapidly converge to the steady state. The model illustrates interesting trade-offs as it implies that lower hospital capacity requires flattening the infection curve and hence a more stringent lockdown, but lower vaccination possibilities (both the likelihood of a vaccine and the vaccination rate) push the optimal lockdown policy in the opposite direction, even before the arrival of vaccine. We find that the ``dollar" value of a vaccine decreases rapidly as time passes with the re-infection rate being a large determinant of the monetary value. The value that society assigns to averting deaths is a major determinant of the optimal policy. Our sensitivity analysis shows that even when we restrict the analysis to reasonable bounds of the economic and epidemiological parameters, we find widely varying implications.

In less developed countries, firms tend to be small and many are family firms. We build a model of joint production in which managers collaborate subject to limited contract enforceability. Such contractual frictions keep firms small and give rise to family firms because collaboration among family members is better sustained than among professional managers. However, family members have different productivities, which is a source of disadvantage due to complementarity in joint production. The degree of contract enforceability and families’ size and productivity endowment determine the prevalence of single manager firms, family firms (with or without outside managers), and professional firms in the economy, as well as the firm size distribution and aggregate productivity. Our quantitative model based on Indian micro data shows that India’s income per capital would be 7 to 16 percent higher if contracts in India were enforced as well as in the US. If family firms are not allowed in the model, this income gap increases by 14 to 20 percent, since family firms are a way of mitigating the contractual frictions. Dissolving all family firms results in an income loss of 1 to 3 percent to large wealthy families and small poor families. In addition, the mid-range of the firm size distribution hollows out and income inequality worsens. Finally, a policy reducing family sizes undermines the role of family firms in mitigating the impact of contractual frictions and hence reduces income per capita, which contrasts with the conventional wisdom on fertility and economic development.

Presentations: Bank of Italy/ CEPR/ EIEF

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4. Entrepreneurship in Black and White (with Bart Hamilton, Andrés Hincapié and Prasanthi Ramakrishnan).
Slides] Draft Available Upon Request!

White males are two-and-a-half times more likely to be entrepreneurs as compared to black males, and this gap begins at the start of their career and widens over their life-cycle.

This paper aims to understand the causes and consequences of this gap. We explore six mechanisms focusing on differences in: (a) access to capital; (b) initial human capital and assets; (c) returns from on-the-job experience; (d) idea profitability and demand factors; (e) non-pecuniary benefits; (f) attitudes towards risk. We build and estimate a model of life cycle occupational choice in which individuals can opt for paid-employment, self-employment or not working. Starting from their initial levels of human capital and wealth, individuals make occupational choices to generate income, accumulating wealth and human capital along the way until retirement. Individuals are risk-averse, have non-pecuniary preferences for self-employment, and face a borrowing constraint. We estimate the model separately for black and white males using data from the PSID. The estimates from a static benchmark of the model show that the lower returns to capital for black businesses, which govern the scale of a business, can explain up to 70 percent of the differences in the profitability of black-white businesses and more than 90 percent of the gap in self-employment rates between blacks and whites. While both whites and blacks face tight collateral constraints, lower assets explain more than 60 percent of the differences in business profitability but a modest 11 percent of self-employment differences between blacks and whites, in the presence of large differences in returns to capital.