Job Market Paper:
Screening and Compliance Documentation as Complements? Effects on Fraud and Administrative Burden
[Abstract] [Paper]
Screening and Compliance Documentation as Complements? Effects on Fraud and Administrative Burden
[Abstract] [Paper]
Abstract:
This paper investigates whether compliance documentation offer incremental fraud deterrence beyond initial ex-ante screening in public programs by leveraging a policy feature of the Paycheck Protection Program - a loan-size threshold that waived compliance documentation requirements for loan forgiveness. On one hand, the waiver may encourage firms with true loan eligibility below the threshold to opportunistically inflate their loan requests up to the threshold. On the other hand, firms with true loan amounts above the threshold may strategically reduce their loans to avoid the administrative burden of compliance. Quantitatively, opportunistic overclaiming was limited, and the loan-reducing effect outweighed the loan-increasing effect, resulting in a net welfare gain of $0.03 per dollar borrowed from the documentation waiver. More broadly, when screening is in place, a higher probability of random audit can substitute for universal compliance documentation to limit fraud. Documentation requirements may impose substantial compliance burdens while providing limited marginal fraud deterrence beyond the initial screening process.
Spend Now, Forgiven Later? Student Loan Forgiveness Uncertainty and Personal Finance
[Abstract]
Abstract:
This paper examines the effects of student loan forgiveness uncertainty on low income borrowers’ financial outcomes. Focusing on the period between August 2022 and June 2023 - when the Biden Administration’s loan forgiveness program was announced, contested in courts, and ultimately ruled unconstitutional by the Supreme Court - I study whether conflicting policy signals altered expectations on receiving forgiveness and financial decisions. I find that low-income borrowers exhibit larger fluctuations in forgiveness expectations in response to forgiveness-related events, with program expectation peaking after the announcement and dropping after the ruling. To estimate causal effects on financial behavior, I exploit plausibly exogenous variation in program eligibility and application intensity across districts. I show that a triple-difference framework isolates the impact of forgiveness uncertainty from the concurrent student loan payment pause. I find that low income borrowers increased credit card spending and actual payment; however, the increase in credit card spending was driven by the forgiveness uncertainty while the increase in actual payment was driven by student loan payment pause. These findings highlight that policy uncertainty - independent of actual implementation - can influence household financial behavior, underscoring the importance of clear and credible policy communication.
Abstract:
This paper investigates the short-run effects of childbirth on the work performance and productivity of fathers. Using a two-way fixed effects model with a novel dataset combining NBA players’ performance data and the birth dates of the players’ children, this study identifies the causal effects of childbirth by arguing that the timing of birth is an exogenous random shock to performance on the games played shortly before and after childbirth. The results indicate a decrease in total productivity postpartum, measured as total points scored per minute played, which is mainly driven by a decrease in performance on harder tasks (3-point shots) but not on easier tasks (2-point shots). Specifically, there is a negative and statistically significant decrease in the number of successful and attempted 3-point shots postpartum. The results complement findings from previous studies, highlighting the importance of not only offering but also incentivizing paternity leave.
Publication:
International student-migrant flows and growth in low- and middle-income countries: brain gain or brain drain?. Rasamoelison, J. D., Averett, S., & Stifel, D. (2021). Applied Economics, 53(34).
[Abstract] [Paper]
Abstract:
The number of students flowing from low-income countries to high-income countries has grown over the past several decades, but is likely to fall substantially in the coming years due to the coronavirus pandemic. To gauge the potential impact of the coronavirus-induced reduction in the international flow of student migrants, we estimate the pre-pandemic effects of student migration from 122 low- and middle-income countries to French- and English-speaking high-income countries on the economic growth of the sending countries. Using region fixed-effects and instrumental-variables estimators to address the potential endogeneity of student-migrant flows, we find positive and statistically significant effects of student migration on per capita GDP in sending countries. These findings are robust to different time lags and are increasing over time. Our results indicate that student migrants have a modest but meaningful impact on the short-run economic growth of their home countries. In terms of the mechanisms through which student-migrant flows can affect growth of the home countries, we find evidence of ‘incentive effects’ for students going to English-speaking countries, and evidence of student-migrant flows affecting interest in politics and democratic political systems in the sending countries.
Undergraduate thesis: "Can low-income households benefit from better access to formal credit without borrowing?: Access to formal credit as insurance in developing countries."
[Abstract] [Link to paper]
Abstract:
Does better access to formal credit allow households in developing countries to improve welfare and manage risks more efficiently? Using principal component analysis on various indicators of access to formal credit, we develop a household-level index of access to formal credit. Then we investigate whether better access to formal credit improves household welfare outcomes, probability of borrowing, and ability to recover from agricultural shocks. To conduct the analysis, we use the “Enquête Périodique Auprès des Ménages” (EPM), a nationally representative survey of 11,753 households conducted in Madagascar in 2005. The difficulty of application procedures and the distance from formal credit institutions are negatively related to households’ access to formal credit. Conversely, the availability of formal credit institutions in the household’s commune and the household’s knowledge of a formal credit institution, and the borrowing procedures are positively related to the household’s access to formal credit. Although credit access does translate into borrowing, the effects appear to be small. A 1-point increase in the household’s access to formal credit index increases the probability of borrowing by 1 percent on average. Using both a commune fixed effect (FE) and an instrumental variable (IV) model, we also find that a 1-point increase in the access to formal credit index increases household expenditure by 10 percent on average. That effect is mostly attributable to the indirect effects of access to formal credit, by using access to formal credit as a quasi-insurance. Moreover, the effect of better access to formal credit on expenditure is more pronounced for households that experienced agricultural shocks compared to the total sample. This result indicates that the effect of better access to formal credit on expenditure for households that experienced agricultural shocks is consistent with consumption smoothing.
A Machine Learning Approach to Predicting Inflation.
[Abstract]
Abstract:
Computing the inflation rate is a long and arduous task, especially in developing countries. From sending surveys to businesses and consumers to processing and analyzing the data, the entire process can take several months in many countries. However, current and future inflation projections are often necessary for several economic decision-making entities. This project, by applying machine learning models, attempts to predict inflation trends using Google search data of keywords related to inflation. To develop the model, I use 3 different sets of data: newspaper data, Google Trend data, and OECD country-level inflation data. First, I use the newspaper data to identify the relevant keywords related to inflation. Then, I collect the search data related to the inflation keywords from Google Trends. Finally, I merge the search data with inflation data from the OECD to predict the inflation trend using machine learning. The methods applied in this model can be useful to provide inflation estimates from countries where collecting inflation data is very difficult.
Undergraduate consulting capstone project: "Cost-benefit analysis study of replacing residence halls’ window air conditioners with a central air conditioning system at Lafayette College."
[Abstract]
Abstract:
This paper conducts a Cost-Benefit Analysis (CBA) of switching from a window unit to a central unit air conditioning system at Gates Hall, Lafayette College. We found that despite its high upfront cost, the central unit air conditioning system is more efficient and more cost-effective than the window unit system. At low levels (less than 15 units) of window units demanded by the students at Lafayette College, the cost of spending on electricity is high for the college. However, the net incremental benefit is positive because the student’s benefit from installing the central unit system outweighs the cost the college spends on electricity. At high levels of window units demanded (more than 15 units), both the students and the college can benefit from installing the central unit system. As the current number of window units used at Gates Hall is higher than 15, and is expected to rise with rising temperatures, we recommend that the college switch to the central unit system. Although our analysis found that it is beneficial to install a central unit system at Gates Hall, it does not imply that installing a central unit system in every residence hall can be beneficial from the college and student perspective.