Research

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.

WORKING PAPERS

The paper investigates the role of insurance and technological progress on rising health inequality across income/wealth groups in the US. Using large-scale federal survey datasets, I document new findings which suggest that the timing of healthcare spending is a key channel behind increased health disparities. I then develop a dynamic stochastic life-cycle model of an economy where individuals choose the timing of healthcare spending and insurance take-up. Consistent with my data findings, model estimates show that while rich and poor have comparable healthcare spending, there are substantial differences in their timing. This, in turn, is a significant factor in accounting for differences in health outcomes --- the estimated model is able to explain about half of the gap in life expectancy across income/wealth groups. Technological innovation and insurance interacts with the timing of healthcare spending and have a first-order effect on health disparities. While a non-uniform increase in the productivity of the medical sector --- where there are improvements in treating early stages of cancer for example, but none for stage 4 cancer --- can lead to an increase in inequality in life expectancy, a uniform increase in the productivity can lead to a reduction. While Medicaid alleviates health inequality, private insurance exacerbates it by almost twice as much. Finally, a comprehensive public health insurance, financed by a flat income tax, would not only reduce 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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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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White males are two-and-a-half times more likely to be entrepreneurs than black males. Already present at the start of their careers, this gap continues to widen as individuals age. Using a life cycle model of occupational choice we study various mechanisms explaining this gap. In the model individuals can choose whether to work and whether to be paid- or self-employed. Their choices are affected by their endowment of wealth and human capital as well as by the process through which they transform these resources into earnings, a process which includes borrowing constraints. Their decisions are also influenced by their risk preferences and their non-pecuniary preferences for being self-employed. We estimate the model separately by race using data from the PSID. The estimates show that the main sources

explaining the gap in entrepreneurship between black and white males are the returns to capital and the idea profitability distribution.

Federal Reserve Bank of St. Louis Publications

  1. What Can Be Done to Promote Black Entrepreneurship? (with Bart Hamilton, Andrés Hincapié, Maggie Issacson and Prasanthi Ramakrishnan) January, 2022. The Regional Economist. Federal Reserve Bank of St. Louis.

  2. How has life expectancy evolved over time and across race? (with Amy Smaldone) January, 2022. On the Economy Blog. Federal Reserve Bank of St. Louis. [forthcoming]