The Impact of 2021 Advance Child Tax Credit Payments on Low-Income Households’ Labor Supply
by Zixin “Ellen” Zhang
Abstract
Studies have established that the Advance 2021 Child Tax Credit (CTC) payments substantially reduced poverty and food insecurity, but some claim that the CTC payments may create negative labor supply effects that could offset its hardship-reduction benefits. Researchers have used a variety of methods to measure how the monthly CTC payments affect the labor supply of households, but the results vary from significant decreases to no significant change to even increases in household labor supply. Using a method novel to this literature, I estimate the labor supply impacts of Advance 2021 CTC by analyzing labor supply changes in response to real amounts of CTC received, which varies by household depending on regional cost-of-livings. Through fixed effects linear regressions across many different combinations of household type and income level, I find that, on average, receiving Advance CTC caused a statistically significant decrease in household labor supply. However, for different household subgroups, I find both statistically significant and insignificant labor supply impacts as well as both increases, decreases, and no change in households’ labor supply due to monthly CTC payments. This suggests that the impacts of 2021 Advance CTC on household labor depend heavily on a household’s situation, specifically income level and household composition. These household-specific patterns align with prior research on the Advance 2021 CTC and how welfare payments are used by families.
Professor Thomas Nechyba, Faculty Advisor
JEL Codes: C31, H24, I38, J22
Generic Entry and The Effect on Prices in the Prescription Drug Market
by Sahana Giridharan
Abstract
Drug firms have utilized a variety of strategies that contribute to rising drug prices in the
U.S. for the last few years. Strategic entry timing and number of indications a drug is approved
might be two factors that contribute to this rise in prices. While there have been some studies
uncovering a positive relationship between generic entry and branded prices, there has been little
research done on the effects of generic entry on generic prices thus far. This work can impact
policy aimed at decreasing generic drug prices and increasing competition in the generic drug
market.
Oncology and inflammatory bowel disease (IBD) are two disease areas that have a high
price burden to patients in the U.S. today, hence using Medicare Part B Average Sales Price
(ASP) data, I analyze the effect of entry timing on the price of 24 drugs in these two indication
areas. Using the Drugs@FDA Database, I collect data on the FDA approval date of a drug, and
on the indications a drug is approved for. Utilizing OLS, my results suggest that later entry times
lead to lower drug prices, with a 1 year increase in entry time resulting in a 6.99% increase in
prices. Results also suggest that an increase of 1 in the number of indications a drug is approved
for leads to a 49.79% decrease in drug price. This could suggest that having existing generic
competitors in the pharmaceutical market decreases generic prices, and that number of
indications is a strong indicator of drug price.
If the current work is confirmed by future studies similar to this studying entry time and
price in the generic pharmaceutical market, it is possible that future drug policy should focus on
promoting competition within the pharmaceutical market to lower generic prices.
Professor Frank Sloan, Faculty Advisor
Professor Grace Kim, Faculty Advisor
Professor Kent Kimbrough, Faculty Advisor
JEL Codes: L11; I11; C3
Forecasting the Effects of Battery Recycling on the Global Cobalt Market
by Elena Cavallero
Abstract
This paper addresses existing concerns around a potential cobalt supply shortage driven by lithium-ion battery demand. Using econometric simultaneous equations, historical global cobalt supply and demand are estimated using data from 1981 to 2018. Based on the results of a Three-Stage Least Square estimation model of global supply and demand, this study forecasts global cobalt price and quantity in 2030. Additionally, a parametrization of battery recycling is added to study the effects of cobalt recovery on future market equilibrium. The results indicate that: 1) world GDP is a key determining driver of cobalt demand, 2) conflicts in the Democratic Republic of Congo, the world’s largest cobalt supplier, negatively impact global production, and 3) recycling lithium-ion batteries will increase global cobalt quantity supplied by 23% and decrease price by 60% in 2030 under the EU Green Deal regulations.
Professor Brian Murray, Faculty Advisor
Professor Grace Kim, Faculty Advisor
JEL Codes: C30, Q31, Q55
The Effect of Marriage on the Wages of Americans: Gender and Generational Differences
By William Song and Theresa Tong
A substantial body of literature on the wage effects of marriage finds that married American men earn anywhere from 10% to 40% higher wages than unmarried men on average, while married American women earn up to 7% less than unmarried women, even after controlling for traits such as background, education, and number of children. Because this literature focuses heavily on men born in a single time period, we study both men and women in two different generational cohorts of Americans (Baby Boomers and Millennials) from the National Longitudinal Surveys of Youth to examine how the wage effects of marriage differ between genders and across time. Using a fixed effects approach, we find that Millennial women—but not Baby Boomer women—experience an increase in wages after marriage, and we replicate the finding from the literature that men experience an increase in wages after marriage as well. However, after controlling for wage trajectory-based selection into marriage by using a modified fixed effects approach that allows wage trajectories to vary by individual, we find that the wage effects of marriage are no longer statistically significant for any group in our data, suggesting that the wage differences between married and unmarried individuals found in previous studies are primarily a result of selection.
Advisors: Professor Marjorie McElroy, Professor Michelle Connolly | JEL Codes: C33; D13; J12; J13; J22; J30
ICT Behavior at the Periphery: Exploring the Social Effect of the Digital Divide through Interest in Video Streaming
By Erik W. Hanson and Justin C. LoTurco
We investigate the factors that influence changes in consumer behavior with regard to video streaming. We focus our analysis on the effect of bandwidth impairment to explore a potential consequence of the digital divide. To measure the change in relative popularity of video streaming services, we use Google Trends data as a proxy. We then investigate whether broadband speed improvements in rural vs. urban regions affect the proxy differently. We find that increasing the broadband speeds in rural regions appears to stimulate greater interest in video streaming than equivalent speed increases in urban regions.
Advisors: Professor Michelle Connolly, Professor Grace Kim | JEL Codes: C33; J11; L96
Evaluating Economic Impacts of Electrification in Zambia
By Aashna Aggarwal
Energy poverty is prevalent in Zambia. It is one of the world’s least electrified nations with 69% of its citizens living in darkness, without access to grid electricity. Zambian government has a goal to achieve universal electricity access in urban areas and increase rural electrification to 51% by 2030. With its main goal to improve the quality of life and wellbeing of Zambians. Electrification is expected to have positive impacts on health, education and employment play an important role to achieve wellbeing, however, previous studies and analysis of renewable energy programs have found different, context-dependent results. To evaluate the impacts of electrification in Zambia I have used the Living Conditions Monitoring Survey (LCMS) of 2015 and applied two different estimation techniques: non-linear regressions and propensity score matching. My study finds that firewood consumption significantly decreases with assess to electricity and education has positive outcomes on grade attainment. I negligible effects on wage earning employment outcomes respiratory health outcomes. Based on these results I conclude that access to grid electrification does have certain positive impacts but empirical evidence is not as strong as the theoretical claims.
Advisors: Professor Robyn Meeks and Professor Grace Kim | JEL Codes: C31; C78; O13; Q40
The Neighborhood Effect on Health Outcomes for Women in Urban India
By Priyanka Venkannagari
The paper uses 2011 Indian Human Development Survey data to assess the impact of 5 categories of variables on health outcomes. It uses OLS models, interaction terms, instrumental variable models, fixed effects and random effects to investigate the existence of a neighborhood effect on health outcomes for women in urban India. This paper finds that various aspects of health practices, empowerment, amenities and financial security are relevant when looking at health outcomes. Interventions looking to address health outcomes should consider these variables and the compounding neighborhood effect.
Advisor: Charles Becker, Michelle Connolly, Kent Kimbrough | JEL Codes: C36, I1, I12, O18
BIDDING FOR PARKING: The Impact of University Affiliation on Predicting Bid Values in Dutch Auctions of On-Campus Parking Permits
By Grant Kelly
Parking is often underpriced and expanding its capacity is expensive; universities need a better way of reducing congestion outside of building costly parking garages. Demand based pricing mechanisms, such as auctions, offer a possible solution to the problem by promising to reduce parking at peak times. However, faculty, students, and staff at universities have systematically different parking needs, leading to different parking valuations. In this study, I determine the impact university affiliation has on predicting bid values cast in three Dutch Auctions of on-campus parking permits sold at Chapman University in Fall 2010. Using clustering techniques crosschecked with university demographic information to detect affiliation groups, I ran a log-linear regression, finding that university affiliation had a larger effect on bid amount than on lot location and fraction of auction duration. Generally, faculty were predicted to have higher bids whereas students were predicted to have lower bids.
Advisor: Alison Hagy, Allan Collard-Wexler, Kent Kimbrough | JEL Codes: C38, C57, D44, R4, R49 | Tagged: Auctions, Parking, University Parking, Bidder Affiliation, Dutch Auction, Clustering
Determining NBA Free Agent Salary from Player Performance
By Joshua Rosen
NBA teams have the opportunity each offseason to sign free agents to alter their rosters. Using only regular season per game statistics, I examine the best method of calculating a player’s appropriate salary value based upon his contribution to a team’s regular season win percentage. I first determine which statistics most accurately predict team regular season win percentage, and then use regression analysis to predict the values of these metrics for individual players. Finally, relying upon predicted statistics, I assign salary values to free agents for their upcoming season on specific teams. My results advise teams to rely heavily on Player Impact Estimate (“PIE”) when predicting their teams’ win percentage, and to seek players whose appropriate salaries would be significantly more than their actual season–long salaries if the free agents were to sign.
Advisor: Kent Kimbrough, Peter Arcidiacono | JEL Codes: C30, Z2, Z22 | Tagged: Free Agents, Salaries, NBA
Conditional Beta Model for Asset Pricing By Sector in the U.S. Equity Markets
By Yuci Zhang
In nance, the beta of an investment is a measure of the risk arising from exposure to general market movements as opposed to idiosyncratic factors. Therefore, reliable estimates of stock portfolio betas are essential for many areas in modern nance, including asset pricing, performance evaluation, and risk management. In this paper, we investigate Static and Dynamic Conditional Correlation (DCC) models for estimating betas by testing them in two asset pricing context, the Capital Asset Pricing Model (CAPM) and Fama-French Three Factor Model. Model precision is evaluated by utilizing the betas to predict out-of-sample portfolio returns within the aforementioned asset-pricing framework. Our findings indicate that DCC-GARCH does consistently have an advantage over the Static model, although with a few exceptions in certain scenarios.
Advisor: Andrew Patton, Michelle Connolly | JEL Codes: C32, C51, G1, G12, G17 | Tagged: Beta, Asset Pricing, Dynamic Correlation, Equity, U.S. Markets
