Amrutha Manjunath
Welcome! I am a sixth-year PhD candidate at the Department of Economics at Pennsylvania State University. My research interests are in international economics, labor economics, and development economics. I am on the job market in the 2024-25 academic year.
I received my BA in Economics (major) and Mathematics (minor) from Ashoka University in 2019.
My CV is here.
Email: amrutha.manjunath@psu.edu
Research
Working Papers
Language Barriers, Internal Migration, and Labor Markets in General Equilibrium (Job Market Paper)
[Draft coming soon.]
Abstract: This paper studies how language barriers impact internal migration, inequality between skilled and unskilled workers, and welfare using rich microdata from India applied to a static spatial general equilibrium framework. I document that (1) consistent with lower incentives, workers migrate less often to locations where they face high language barriers, (2) consistent with comparative advantage, migrants with language barriers are employed in speaking-intensive occupations less often, (3) consistent with selection, migrants with language barriers get a wage premium, and (4) these patterns are strongest for unskilled workers. To explain these facts, I develop and estimate a quantitative model. Through the lens of the model, I show that removing language barriers increases internal migration by 6.2 percentage points, enhances welfare by 1.2 percent, and reduces inequality between skilled and unskilled workers by 1.9 percentage points. As economies shift towards services, language barriers increasingly impede aggregate gains due to the rising prevalence of speaking-intensive occupations. The importance of language barriers resulting from structural change lowered internal migration by 7.2 percentage points, lowered welfare by 1.9 percent, and increased inequality between skilled and unskilled workers by 3.4 percentage points. Finally, I argue that welfare benefits of implementing language programs outweigh costs.
Presentations
2024: Urban Economics Association European Meeting (Copenhagen, Denmark), Federal Reserve Bank of Atlanta Brownbag, Federal Reserve Bank of Philadelphia Brownbag, Trade and Development Brownbag* (PSU)
2023: Midwest Economics Association (Cleveland), Canadian Economics Association (Winnipeg, Canada), European Trade Study Group (Surrey, UK), Federal Reserve Bank of Philadelphia PFMAP Brownbag, Trade and Development Brownbag (PSU), Applied Microeconomics Brownbag (PSU)
(*scheduled)
Criminal Politicians, Political Parties, and Selection
[Draft available upon request.]
Abstract: I study how criminally accused candidates win three times more often than non-criminals upon nomination using data from four recent parliamentary elections in India. I write a simple model of party nomination choice, which predicts that criminals are nominated only when they are needed to win and not otherwise. Using local linear regressions, I confirm this prediction in the data. In particular, I find that the predicted probability from the ex post decision to nominate a criminal has an inverse-U relationship with a party's ex ante margin of victory. This may explain why criminal candidates are more successful than non-criminal candidates upon nomination: they are selected by political parties to do so.
Presentations
2023: International Economic Association World Congress (Medellin, Colombia)
2022: Midwest Political Science Association (Chicago), Annual Conference on Economic Growth and Development (ISI Delhi, India), Applied Microeconomics Brownbag (PSU)
Work in Progress
Climate Uncertainty and Temporary Migration
w. Tim Dobermann and Yinong Tan
Using district-to-district migration data from the Indian Census, we demonstrate that locations with higher mean and variance of adverse climate conditions experience increased out-migration. Among out-migrating households, temporary migration and household splits are common, with female members typically remaining behind. To explain these patterns, we develop a dynamic spatial general equilibrium model of migration incorporating agricultural productivity uncertainty, migration costs, and concave household utility functions. The model predicts that, controlling for mean income, greater agricultural income uncertainty increases rural out-migration. It also suggests that moderate uncertainty leads to more household splits, as location diversification aids risk sharing, while high uncertainty promotes whole-household migration. Using the estimated model, we quantify the impact of climate variability on migration patterns, determining thresholds of uncertainty that trigger different household responses. Our analysis of household splitting behavior provides crucial insights for guiding mitigation policies in developing countries. We argue that migration may serve as an effective strategy to combat climate-induced agricultural productivity losses, and inform targeted climate adaptation measures.
Teaching
Instructor, Pennsylvania State University
Introductory Microeconomic Analysis and Policy (Summer 2022)
Teaching Assistant, Pennsylvania State University
Migration and Development (Fall 2022, Spring 2023, Spring 2024)
Political Economy (Spring 2022)
Intermediate Microeconomic Analysis (Spring 2021, Fall 2021)
Introductory Microeconomic Analysis and Policy (Fall 2019, Fall 2020)
Statistical Foundations for Econometrics (Spring 2020)
Other
Non-Academic Writing
Splitting Hairs, The Booming Wig Trade between India and Africa, The Caravan Magazine, December 2017
Bone of Contention, An Andhra Pradesh Family's Generations-Old Method of Treating Fractures, The Caravan Magazine, August 2017