I am a PhD candidate in Economics at the University of Minnesota. I am on the job market for the 2025/26 academic year.
I am a Macroeconomist with specialization in Growth, Development Economics, Spatial Economics, Education, and Macro Labor. My research combines causal inference techniques with structural macroeconomic models to answer fundamental questions about economic growth and inequality.
Email: verma176@umn.edu
Address: 1925 South 4th Street, 4-101 Hanson Hall, Minneapolis, MN 55455
Higher Education and Economic Development: Evidence from College Expansion in India (JMP)
[Presented: EGSC 2025 (Washignton University in St Louis), Labor Workshop (Duke University), Scheduled: EWMED 2025 (University of Cyprus)]
This paper studies whether higher education causes economic development. The identification strategy combines India's large-scale liberalization of higher education with spatial variation in college expansion generated by affiliation requirements and the pre-determined location of public universities. The empirical estimates show that a one-percentage-point increase in the share of college graduates over a decade reduces agricultural employment by 0.8 percentage points while increasing services employment by 0.9 percentage points, real GDP per worker by 2.3 percent, and nightlight intensity by 6.2 percent. These results are consistent across instrumental variable, event study, and border discontinuity designs. The estimates imply that social returns to human capital are 30 percent larger than private returns. The reduced-form estimates are then used to calibrate a spatial general equilibrium model with endogenous education choices and human capital externalities. The model implies that for the average district, India's higher education reform accounts for 20 percent of output growth between 2001 and 2011. Counterfactual simulations show that removing spatial barriers to college opening would have increased the average district's 2011 output by 3 percent. These findings demonstrate that higher education expansion is a powerful driver of economic development and modernization.
Higher Education Policies and Spatial Inequality Across US States with Sang Min Lee
[Presented: SED Winter 2024, Scheduled: Urban Econ Association, USC, U Monash, LAEF-NYU]
To what extent have the federal and state higher education policies—which have affected the supply and demand of college education—contributed to the growing cross-state wage inequality since 1980? To address this question, we develop and estimate a quantitative spatial model with endogenous college education and migration. The model features skill-biased technical changes and agglomeration effects, which means that a state’s average wage rises as more residents attain college degrees or as college-educated workers migrate into the state. Counterfactual analyses reveal that tuition discounts and public appropriations by the federal and state governments have become more progressive. In the baseline, the standard deviation of log mean wages across states increased from 0.087 in 1980 to 0.117 in 2019. In contrast, had the higher education policies remained at their 1980 levels, the standard deviation would have risen by 73% more to 0.139 by 2019. Agglomeration effects played a significant role in this result: if they had been half as strong as estimated, the standard deviation would have increased by 17% more (instead of 73%) in the counterfactual than in the baseline.
Revisiting Global Income Convergence in 21st Century
Recent research has documented a reversal from divergence to convergence in income levels between rich and poor countries after 2000. This paper employs a growth accounting framework that incorporates heterogeneity in capital income shares–unlike the constant one-third share typically assumed–to investigate global income dynamics over the time period 1980-2019. I find that while output levels began to converge only after 2000, capital (physical and human) had already been converging during 1980-2000. The divergence in total factor productivity (TFP) during this earlier period offset the gains from capital convergence, resulting in little overall income convergence. After 2000, capital maintained its pattern of convergence, and, unlike in the earlier period, TFP also began to converge. Quantitatively, more than half of the convergence between 2000 and 2019—and nearly all the convergence between 1980 and 2019 outside Sub-Saharan Africa—can be attributed to the convergence in capital rather than to improvements in TFP. These findings highlight that factor accumulation has played a much larger role in driving long-run convergence dynamics than previously documented in the literature.
Foundational Skills and Labor Market Outcomes: Evidence from India with Ravinder
(* Older Title: Labor Market Returns to Improvement in Education Quality: Evidence from India)
This paper investigates the causal impact of foundational skills on labor market outcomes in India. Despite substantial expansion in years of schooling, learning levels remain low in India. Addressing this question is challenging because there is no unified dataset that records both foundational skills and labor market outcomes. We impute foundational skills for working-age adults by training a machine learning model on test score data from the IHDS and applying it to the PLFS. The imputed scores show a high correlation with actual test score data from the ASER. To identify causal effects, we exploit quasi-experimental variation from the DPEP within a fuzzy regression discontinuity design. The findings show that higher foundational skills substantially increase earnings, with effects robust to alternative specifications, and bandwidth choices. These results highlight the importance of schooling quality in driving labor market outcomes.
Demography and Structural Transformation with Ruyan Liao
Labor Market Dynamics in Developing Economies with Ravinder
Multi-region Carbon Tax under Time Inconsistency with Honey Batra, Monishankar Bishnu, and Tridip Ray
