Research

Abstract: I develop an algorithm to construct the "Unobserved Intermediate Goods Set (UIGS);" that is, the intermediate goods establishments produce in-house rather than source externally. Because plants only report directly purchased inputs and final output(s) produced, the in-house production of intermediate goods is unreported. Uncovering this provides a clearer picture of the production networks and reveals a fuller extent of input-output linkages for establishments in the manufacturing sector, even those that occur within the boundaries of an establishment. I apply the algorithm to confidential Indian plant-level data from 2001 to 2010, which allows me to estimate the reaction of establishments to tariff reductions on both externally sourced and internally produced intermediates. Notably, a decline in tariffs on internally produced intermediates leads to an increase in vertical specialization as establishments shift to purchasing those inputs externally. This, in turn, leads to gains in productivity, sales, profits, and employment in addition to those coming solely from the reduction in tariffs on existing externally sourced inputs. The estimates suggest that the impacts of tariffs on trade may be biased if UIGS is ignored.

Presentations: 

Federal Reserve Bank of Dallas (2024);  

Hobby School of Public Affairs (2024) 

Abstract: What is the potential impact of industrial robots on trade and labor markets of open developing economies? This paper studies the impact of: (i) increased adoption of industrial robots in advanced economies on imports from emerging economies, and (ii) how this change in imports by advanced economies affects the domestic manufacturing labor of developing economies. For the empirical analysis, using industry-year level data on labor from India, and country-industry-year level international trade data, a long-difference panel regression approach is used to examine these questions. I find that industrial robots adopted by developed economies reduce exports and domestic employment in the manufacturing sector in India. To further carefully investigate and answer the research question, using the input-output tables, I allow for supply chains in order to fully comprehend the industry-to-industry linkages and cross-industry impact of robot adoption by advanced economies on imports from India. The preliminary evidence suggests that as the industries in the advanced economies expand, they import more from upstream industries in India (demand effect), and as advanced economies adopt more robots in upstream industries, imports from India decreases (substitution effect), which possibly means that if advanced economies adopt more robots in upstream industries, it is cheaper to produce domestically than to import from India. In other words, industrial robots can facilitate the process of reshoring in advanced economies by replacing the need to import inputs from the upstream industries.

Presentations:  

Macroeconomics Student Workshop, University of Houston (2021, 2022);

Graduate Student Workshop, University of Houston (2021, 2022)

Abstract: Affective polarization can impact policy evaluations, as individuals who experience intense negative emotions towards parties they oppose often view issues through a partisan lens and emotional biases, leading to diverging policy positions. We examine how partisan biases affect inflation expectations, a critical economic indicator in monetary policymaking. Using data from a choice experiment (CE) embedded in a survey of a representative sample of US residents conducted between August 11 and 29, 2022, we find that political polarization plays a significant role in shaping public inflation expectations even after controlling for policies affecting macroeconomic performance. Republicans are going to have higher inflation expectations when Democrats are in office regardless of their policies, and vice versa. This study allows a better understanding of the interactions between partisan perceptions and economic expectations.

Presentations: 

American Political Science Association (APSA) Annual Meeting, Philadelphia* (2024); 

Midwest Political Science Association (MPSA)  Annual Conference, Chicago* (2024);

8th Latin American PolMeth Meeting, Montevideo, Uruguay* (2024)

* Presented by co-author

Abstract: This paper conducts an empirical investigation of capital expenditures by independent school districts in the United States. Capital spending warrants particular attention due to its significantly more flexible financing compared to current expenditures, which are constrained by numerous institutional factors. This flexibility suggests that school districts may align their capital investments more closely with their preferences. Accordingly, we examine whether capital spending is motivated by enrollment levels or influenced by other factors. Our primary objective is to assess whether capital allocation is optimized relative to enrollment. If capital is optimized with respect to enrollment, estimating the rate of return on capital would be appropriate; if not, such estimation may not be feasible. Our empirical findings indicate that both per capita income and population influence capital spending. Furthermore, we find that school districts do not adjust capital investments over time, resulting in substantial disparities in capital per student across different cohorts. Finally, we observe that capital spending is also related to aspects of the administrative structure, such as the frequency of borrowing. The importance of these findings is that school districts appear unlikely to be on their production possibilities frontier in terms of learning, which suggests estimation of the rate of return to capital spending may not yield meaningful results.

Presentations: 

92nd Southern Economic Association (SEA) Conference, Fort Lauderdale, Florida (2022);

17th WEAI International Conference , Melbourne, Australia* (2023)

* Presented by co-author