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Financial Inclusion and Women’s Economic Empowerment in India
By Nehal Jain
Abstract
On August 14th, 2014 India’s Prime Minister Narendra Modi implemented the largest ever
financial inclusion scheme to date known as Pradhan Mantri Jan Dhan Yojana (PMJDY). The
program aimed to bank all of India’s unbanked population. Prior to the program, India had one of
the highest rates of unbanked citizens. The program also included measures that prioritized women’s
access to these financial institutions given the gender gap in financial inclusivity. This paper aims
both to understand the effectiveness of PMJDY on granting women equal access as men to financial
institutions and whether financial inclusion results in increased economic empowerment, I find that
PMJDY was successful in increasing access to bank accounts and separately, that access to bank
accounts economically empowers women.
Pengpeng Xiao, Faculty Advisor
Michelle Connolly, Faculty Advisor
JEL classification: J1; G28; I31
Bayesian Non-Parametric Risk Metric
By Kiwan Hyun
Abstract
This thesis constructs completely non-parametric Risk Metric models through Dirichlet process in order to account for both the parametric uncertainty and model uncertainty that a Risk Metric may bring.
Value at Risk (VaR), along with its integrated form Continuous Value at Risk (CVaR) / Expected Shortfall (ES), is one of the most frequently used risk metrics in finance. VaR is a quantile value of forecasted return of a portfolio—linear and non-linear. [Siu, et. al., 2006] According to the Basel 95% and 99% VaR are recommended to be posted by the financial institutions for portfolios and assets; 97.5% CVaR/ES value needs to be set aside when making an investment for “capital buffer”. [Obrenovic & Akhunjonov, 2016] Therefore, an accurate estimation of risk is critical for VaR models and CVaR/ES models.
The traditional approach of a normal approximation to VaR and CVaR/ES has been discredited—especially for daily returns—and even blamed by some for causing the 2008 Financial Crisis [Nocera, 2009] Many advancements have been made to the VaR model including Bayesian inference to the normal model [Siu, et. al., 2006], Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) VaR model [Bollerslev, 1986], and Conditional Autoregressive Value at Risk (CAViaR) model [Engle & Manganelli, 2004]. When tested against 6 years (Jan, 2001 – Jan, 2005) of daily returns data of 10 different market indexes, the Bayesian CAViaR model has shown to be the most accurate in predicting daily 95% and 99% VaR. [Gerlach, et. al., 2011]
However, there were certain years for certain indexes where the 99% Bayesian CAViaR VaR did not perform well, especially for years that had multiple > 5% daily drops. Moreover, the Bayesian CAViaR models—though are almost non-parametric—follow a Skewed-Laplace distribution. To even account for the uncertainty of the likelihood model, this thesis constructed daily 97.5% VaRs for 7 different country indexes for 7 years (Jan, 2012 – Dec, 2019) using the completely non-parametric Dirichlet Process.
The Dirichlet Process 97.5% VaR outperformed all Bayesian Normal, Bayesian GARCH, and Bayesian CAViaR models of years when CAViaR models underperformed. The model may be inefficient for normal years since it is overly conservative. Nevertheless, the non-parametric model still seems to be significantly more accurate during fluctuant years.
Professor Kyle Jurado, Ph.D., Faculty Advisor,
Assistant Professor Simon Mak, Ph.D., Faculty Advisor
Long-term Benefits of Breastfeeding: Impact on Education in Indonesia
By Natalie Gulrajani
Abstract
Healthy breastfeeding behaviors have been shown to produce many long-term health benefits
including improved cognition. This study uses data from the Indonesian Family Life Survey
(IFLS) to assess the longitudinal impact of exclusive breastfeeding duration and early life
breastfeeding practices on education. Though a positive correlation was found between
breastfeeding duration and years of schooling in naïve regressions, the significance and
magnitude of this effect decreased when household fixed effects were added. A stronger
correlation was found between early life breastfeeding and schooling, with income-stratified
results demonstrating that poorer households are potentially subject to greater benefits.
Professor Erica Field, Faculty Advisor
JEL classification: I0; I12; I21
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 Classification: L11; I11; C3
The Russian Maternity Capital Policy: Two Models
By Jackson Cooksey
Abstract
Between 1991 and 2007 the Russian Federation experienced a decrease in population
and a drop in total fertility rate below population replacement levels. In 2007 the
government, citing the importance of forestalling this decline, implemented the Russian
Maternity Capital Policy, a one-time subsidy to those families who have a second or
higher order birth. Study aims to analyze the impact of this policy on the total fertility
rate of the Russian Federation to better understand post-Soviet trends in fertility and
gain insight into how effective similar policies will be in the future if implemented
elsewhere. This study uses two models to assess the policy. First, a novel difference-indifference-
in-difference model is developed to add to existing literature on the policy.
Second, a synthetic control model is developed generate a counterfactual to measure
causal effects of the policy on total fertility rate in Russia. Difference-in-difference-indifference
estimations show the policy having a 0% to 3.5% positive effect on fertility,
and the synthetic control model results show that the policy had a large impact on
fertility in the mid-2010s but this change has declined since 2019.
Professor Charles Becker, Faculty Advisor
JEL Classification: J, J1, J11, J12, J13
Economic Situations and Social Distance: Taxation and Donation
By Alexander Brandt
Abstract:
This experimental study evaluated the effects of two common economic situations –
taxation and donation – on the social distance between participants in the situations, an original
effect of interest that is the opposite of prior research. This study employed a novel survey
framework, in which subjects gave money to others in the economic situations and socially
judged recipients of their money. Findings mostly did not support predictions that the economic
situations would differently affect social distance, but the novel framework enabled an effective
test of the effect of economic situations on social distance and is a major contribution to the field.
Professor Rachel E. Kranton, Faculty Advisor
Professor Scott A. Huettel, Faculty Advisor
Professor Grace Kim, Seminar Advisor
JEL classification: C91; D64; D89; D90
Is Affordable Housing Moving Mobile? Analyzing the Impact of COVID-19 on Demand for Manufactured Housing
By Jair Coleridge Soman Alleyne
As demand for affordable housing continues to increase in America, manufactured homes provide a private solution to this problem. Research has shown that manufactured home prices are largely dependent on the price of local housing substitutes as well as other geographic hedonic factors. This paper looks at the impact of Covid-19 on the manufactured housing market to determine the effects that economic shocks have on the demand for manufactured housing. Conditional on wanting to buy a house, we use a logistic model to examine the probability that an individual purchases a manufactured home and whether this probability increases at times of high unemployment and economic uncertainty. Due to the nature of our data, although the impact of Covid as a disease is difficult to measure, we do find decreased income and increased unemployment to be a factor increasing the likelihood of purchasing a manufactured home. We also find that in 2020, demand for manufactured housing increased significantly compared to the years prior.
Advisors: Professor Charles Becker, Professor Michelle Connolly | JEL Codes: R2, R21, I32
Labor Market Effects of the Minimum Wage in South Korea
by Alec Ashforth
This paper analyzes survey data from businesses regarding individual worker earnings, hours, and characteristics from 1971 to 1998 in order to estimate the labor market effects of the minimum wage in South Korea. Since the minimum wage was only implemented in manufacturing, construction, and mining industries, we are able to compare earnings and hours of workers in these industries with workers in other industries using both a difference-in-differences and a synthetic control approach. Additionally, we test to see if the minimum wage had heterogeneous effects based on an individual worker’s gender, level of education, experience, and payment period.
Advisors: Professor Arnaud Maurel, Professor Kent Kimbrough | JEL Codes: J31, J38, O15
The Effects of Leveraged Buyouts on Health Outcomes
by Robert Williams
Private equity firms first began acquiring hospitals in the United States during the early 1990s, yet the effects of private equity ownership on patient outcomes and treatment costs are still not clear. Some argue that although private equity firms are adept at improving operating efficiencies and introducing managerial expertise, these cost-cutting measures may come at the expense of patient outcomes.
Because acute myocardial infarctions (AMIs) serve as proxies for patient outcomes and treatment costs, I collect information on 30-day mortality rates and Medicare reimbursements for treatments of AMIs at US Medicare-certified short-term acute care general hospitals from 2014 to 2019. This paper uses fixed effects models to analyze the impact of leveraged buyouts, relative to strategic acquisitions, on patient outcomes. After integrating both hospital and time fixed effects, I find that private equity ownership does not lead to significant changes in Medicare reimbursements or mortality rates for AMI treatments.
Advisors: Professor Ryan McDevitt, Professor Grace Kim, Professor Michelle Connolly | JEL Codes: I0, I110, G340
Municipal and Cooperative Internet on Broadband Entry and Competition
by Tianjiu Zuo
The broadband market is unique for municipal (government-owned) and cooperative (member-owned) competitors. Their participation, however, raises conflict of interest concerns. Both municipalities and cooperatives are often owners of utility poles that are an essential input for broadband deployment. Internet service providers (ISPs) must lease pole attachment space. While most pole attachment rates are regulated, municipal and cooperative pole owners are exempt by Section 224 of the Telecommunications Act. This paper, therefore, studies the competitive effects of municipal and cooperative ISPs, and the effect of potential entry by municipal and cooperative electric utilities (non-ISPs), on broadband entry and quality. I add to the existing literature by building a dataset of municipal and cooperative non-ISP service areas, designing a method to clean the Federal Communications Commission’s (FCC) broadband data, developing a novel geographic entry threat model, and analyzing municipalities and cooperatives in conjunction. I categorize markets into three types: rural, urban clusters (2,500 to 50,000 people), and urbanized areas (≥ 50,000 people). Looking at Illinois from June 2015 to June 2018, I find that the presence of a municipal ISP lowers the probability of market entry and service quality in urbanized areas. The presence of a cooperative ISP lowers the probability of market entry and service quality in rural areas and urban clusters. The presence of a municipal non-ISP has little to no effect on the probability of market entry or service quality. The presence of a cooperative non-ISP appears to increase the probability of market entry in rural and urbanized areas, but depress service quality in urbanized areas, though these effects could be attributed to bad data.
Advisor: Professor Michelle Connolly | JEL Codes: L32, L41, L96
