Predictors of Student Loan Repayments: A Comparison Between Public, Private For-Profit and Private Nonprofit Schools
by Mannat Bakshi and Arjun Ahluwalia
Using a sample of over 3,500 colleges from the College Scorecard Dataset , we investigate the association of average federal student loan repayment rates with institutional, regional, and student demographic characteristics of colleges. We consider educational cohorts from 2010 to 2016 at public, private for-profit, and private non-profit institutions. Our data do not allow us to see individual student characteristics, hence we control for traits of the average student in each college and focus on institutional traits that impact repayment rates. Our controls for demographics are consistent with prior research on student loan repayment rates (Lochner and Monge-Naranjo, 2014; Kelchen and Li, 2017).
We ran a Random Effects panel regression to determine how institutional, regional, and student demographic characteristics impact repayment rates. We see an important influence of the institution attended. Institution selectivity (lower admission and withdrawal rates) is associated with higher average repayment. Furthermore, the highest degree awarded is a more significant variable when it comes to describing the variation in repayment rates for public schools; private for-profit schools exhibit lower repayment rates and private nonprofit schools exhibit higher repayment rates regardless of the highest degree awarded. This could be due to a combination of signaling and screening effects. Local income and unemployment impact repayment for the average student in public and for-profit schools, but not in private non-profit schools.
A noticeable institutional finding is that, even after controlling for average school demographics, for-profit schools exhibit lower repayment rates across all types of degree-granting programs. Attending a for-profit school may be a negative signal of ability or value to potential employers. Median family income positively affects repayment twice as much for for-profit schools compared to other school types. These finding on for-profit institutions help explain Obama’s “crack down on for-profit career training colleges” (Simon & Emma, 2014).
Advisor: Professor Genna Miller | JEL Codes: I2, I22, I26
By Michael Levin
Overcrowding in United States hospitals’ emergency departments (EDs) has been identified as a significant barrier to receiving high-quality emergency care, resulting from many EDs struggling to properly triage, diagnose, and treat emergency patients in a timely and effective manner. Priority is now being placed on research that explores the effectiveness of possible solutions, such as heightened adoption of IT to advance operational workflow and care services related to diagnostics and information accessibility, with the goal of improving what is called throughput efficiency. However, high costs of technological process innovation as well as usability challenges still impede wide-spanning and rapid implementation of these disruptive solutions. This paper will contribute to the pursuit of better understanding the value of adopting health IT (HIT) to improve ED throughput efficiency.
Using hospital visit data, I investigate two ways in which ED throughput activity changes due to increased HIT sophistication. First, I use a probit model to estimate any statistically and economically significant decreases in the probability of ED mortality resulting from greater HIT sophistication. Second, my analysis turns to workflow efficiency, using a negative binomial regression model to estimate the impact of HIT sophistication on reducing ED waiting room times. The results show a negative and statistically significant (p < 0.01) association between the presence of HIT and the probability of mortality in the ED. However, the marginal impact of an increase in sophistication from basic HIT functionality to advanced HIT functionality was not meaningful. Finally, I do not find a statistically significant impact of HIT sophistication on expected waiting room time. Together, these findings suggest that although technological progress is trending in the right direction to ultimately have a wide-sweeping impact on ED throughput, more progress must be made in order for HIT to directly move the needle on confronting healthcare’s greatest challenges.
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Advisors: Professor Ryan McDevitt, Professor Michelle Connolly | JEL Codes: I1, I18, O33
Navigating the Maize of Poverty: Intra-Household Allocation and Investment in Children’s Human Capital in Tanzania
By Saheel Chodavadia
Intra-household resource allocation influences investment in children’s human capital and hence influences long-term poverty levels. I study how climate shocks in Tanzania shift intra-household bargaining power and investment in children’s human capital. Past empirical work finds that bargaining power is associated with income, assets, education, and other often unobservable factors. Anthropological evidence from Tanzania suggests that male decision-makers in poor households control most income and own most assets. Conditioning on changes in total household resources due to climate shocks, I find evidence consistent with climate shocks increasing female bargaining power through a reduction in male decision-maker’s income. Specifically, climate shocks in households with more educated women increase investment in children’s education and improve anthropometric measures of health. Lastly, I comment on the usefulness of relative education as a proxy for bargaining power in contexts of data and cultural limitations on distinct assets and income streams for decision-makers.
Advisors: Professor Robert Garlick, Professor Michelle Connolly | JEL Codes: D0, D13, I20
By Pranav Ganapathy
We propose and evaluate an auction mechanism for the priority review voucher program. The 2007 voucher program rewards drug developers for regulatory approval of novel treatments for neglected tropical diseases. Previous papers have proposed auctioning vouchers for the priority review voucher program but have offered neither a mathematical model nor a framework. We present a mechanism design problem with one pharmaceutical company producing one drug for a neglected tropical disease. The mechanism that maximizes the regulator’s expected surplus is a take-it-or-leave-it offer, with three different offers based on low, intermediate, and high neglected disease burdens. We demonstrate how mechanism design can be applied to settings in which the buyer pays for public access to a product with regulatory speed. Finally, this paper may be useful to policymakers seeking to improve access to voucher drugs through modifications of the program.
Advisors: Professor David Ridley, Professor Giuseppe Lopomo, Professor Michelle Connolly| JEL Codes: I1, D44, D82
By Audrey Kornkven
In October 2008, a provision of the Deficit Reduction Act of 2005 known as Medicare “Nonpayment” went into effect, eliminating reimbursement for the marginal costs of preventable hospital-acquired conditions in an effort to correct perverse incentives in hospitals and improve patient safety. This paper contributes to the existing debate surrounding Nonpayment’s efficacy by considering varying degrees of fiscal pressure among hospitals; potential impacts on healthcare utilization; and differences between Medicare and non-Medicare patient populations. It combines data on millions of hospital discharges in New York from 2006-2010 with hospital-, hospital referral region-, and county-level data to isolate the policy’s impact. Analysis exploits the quasi-experimental nature of Nonpayment via difference-in-differences with Mahalanobis matching and fuzzy regression discontinuity designs. In line with results from Lee et al. (2012), Schuller et al. (2013), and Vaz et al. (2015), this paper does not find evidence that Nonpayment reduced the likelihood that Medicare patients would develop a hospital-acquired condition, and concludes that the policy is not likely the success claimed by policymakers. Results also suggest that providers may select against unprofitable Medicare patients when possible, and are likely to vary in their responses to financial incentives. Specifically, private non-profit hospitals appear to have been most responsive to the policy. These findings have important implications for pay-for-performance initiatives in American healthcare.
Advisors: Professor Charles Becker, Professor Frank Sloan, Professor Grace Kim| JEL Codes: I1, I13, I18
By Hemal Pragneshbhai Patel
The effect of the economic collapse on health has been extensively documented in Russia since the dissolution of the Soviet Union. The proportion of stunted children in Russia increased substantially in this period, but no study has investigated the mechanisms by which this economic collapse impacted child health outcomes. This paper uses an OLS regression followed by a Binder-Oaxaca decomposition to determine the specific economic factors that significantly contributed to this decrease in child heights.
Advisors: Professor Charles Becker | JEL Codes: I1; I14; J13
By Hemal Pragneshbhai Patel
Increased tourism, especially in developing economies, brings with it more economic opportunities and avenues for development. In Roatán, the largest of Honduras’ Caribbean Bay Islands, tourism has brought economic development that the island had never before experienced. However, the impact of this economic development brought by increasing cruise ship tourism on child health has yet to be investigated. The increase in economic development is expected to improve child health through improved absorbed nutrition, and this paper uses an OLS regression model to examine how differential exposure to tourism development during a child’s crucial early life developmental window impacts later life health outcomes, proxied by height-for-age Z-scores.
Advisors: Professor Dennis Clements, Professor Michelle Connolly | JEL Codes: I1; I15; Z32
By Grace Mok
Evictions are an important aspect of the affordable housing crisis facing low-income American renters. However, there has been little research quantifying the causal impact of evictions, which poses challenges for academics interested in understanding inequality and policy-makers interested in reducing it. Merging two datasets both new to the literature, I address this gap in the causal literature by using an instrumental variables strategy to examine the impact of evictions on household income over time in Durham, North Carolina. Exploiting gentrification-related evictions as an instrument, I find a 2.5% decrease in household income after eviction. This is a small, but significant decrease in income given that median household income for households at time of eviction is about $15,000.
Advisors: Professor Christopher Timmins, Professor Michelle Connolly | JEL Codes: I32, R29