Corporate Governance in State-Owned and Privately-Owned Enterprises
by Despoina Chouliara
Abstract
In this paper I examine the principal/agency relationship in corporate governance and introduce it in a steady state growth model. More specifically, I will model a profit-maximizing privately-owned enterprise and a series of state-owned enterprises with varying economic goals. I will use the insights of agency theory to revisit the debate about public versus private ownership with the objective of exploring how ownership a↵ects a firm’s performance and whether the sole objective of profit-maximization is optimal for the firm and the aggregate economy. Hence, the scope of this paper is to enhance our understanding of the channels through which corporate governance influences the aggregate economy.
Professor Pietro Peretto, Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
JEL Codes: D2, D21, O40
Labor Market Effects of the Minimum Wage in South Korea
by Alec Ashforth
Abstract
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.
Professor Arnaud Maurel, Faculty Advisor
Professor Kent Kimbrough, Faculty Advisor
JEL Codes: J31, J38, O15
The Impact of Conflict on Economic Activity: Night Lights and the Bosnian Civil War
by Stephanie Dodd
Abstract
The tendency of violent conflict to suppress economic activity is well documented in the civil war economic literature. However, differential consequences resulting from distinct characteristics of conflicts have not been rigorously studied. Utilizing new conflict data on the 1992-1995 Bosnian civil war from Becker, Devine, Dogo, and Margolin (2018) and DSMP-OLS night light data as a proxy for economic activity, this paper investigates the disparate economic impacts that different types of conflict have on Bosnia’s municipalities.
This investigation first uses data from other Yugoslavian countries to impute pre-war night light values for conflict-affected Bosnian municipalities. Next, a spatial autocorrelation model with fixed effects is used to determine if and how the occurrence of different types of violence vary in their implications for economic activity. This analysis finds that the five types of warfare identified in the context of the Bosnian Civil war have different impacts on night lights and economic activity.
Professor Charles Becker,Faculty Advisor
Professor Grace Kim, Faculty Advisor
JEL Codes: F52, H56, O52
Predicting the Work Task Replacement Effects of the Adoption of Machine Learning Technology
by Shreya Hurli
Abstract
This paper develops a methodology to attempt to predict which tasks in the workforce will be resistant to the replacement of labor by machine learning technology in the near future given current technology and technology adoption trends. Tasks are individual activities completed as parts of a job. Prior research in the field suggests that characteristics of tasks (non-roteness, creativity, analysis/cognitive work) that make them harder for machine learning technology to complete are good predictors of whether those tasks will be resistant to replacement in the workforce. This study utilizes O*NET (Occupational Information Network) task description and education data from October 2015 to August 2020 and Bureau of Labor Statistics salary data to use task characteristics to predict tasks’ resistance to replacement. Normalized scores, average salaries, and average worker education levels are calculated to quantify the relative presence or absence of non-roteness, creativity, and cognitive work in a task. This paper then uses the calculated scores, salary, and education data, as well as a number of interaction terms as inputs to a support vector machine (SVM) model to predict which tasks will be resistant to decline in their shares of workplace tasks weighted by the jobs under which the tasks fall. Using task characteristics, the SVM predicts that just approximately 39% of tasks are likely to be resistant to replacement. These tasks tend to be highly non-deterministic (very non-rote, analytical/cognitive, and/or creative) in nature.
Professor David Berger, Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
JEL Codes: J23, J24, O33
The Effects of Health IT Innovation on Throughput Efficiency in the Emergency Department
by Michael Levin
Abstract
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: Michelle Connolly, Ryan McDevitt | JEL Codes: I1, I18, O33
Patrolling the Future: Unintended Consequences of Predictive Policing in Chicago
By Jenny Jiao
In the past decade, police departments have increasingly adopted predictive policing programs in an effort to identify where crimes will occur and who will commit them. Yet, there have been few empirical analyses to date examining the efficacy of such initiatives in preventing crime. Using police and court data from the second-largest police department in the country, this paper seeks to evaluate the pilot version of Chicago’s Strategic Subject List, a person-based predictive policing program. Using a boundary discontinuity design, I find that individuals eligible for the Strategic Subject List were 2.07 times more likely to be found not guilty of all charges in court than similarly situated individuals in the control group. Taking into account crime category heterogeneity, I find evidence that individuals previously arrested for drug crimes drive this result. This research sheds light on the potential unintended consequences of person-based predictive policing.
Advisors: Professor Patrick Bayer, Professor Bocar Ba | JEL Codes: K4, K42, O33
Investigating the Impact of Chinese Financing on Productivity in the African Continent
By Kedest Mathewos
Given that productivity is a key component of long-term economic growth and that China has become an important source of external financing in Africa, this study aims to investigate the impact of Chinese foreign direct investment and government-to-government loans on productivity. Using a panel of the top fourteen African recipients of Chinese financing during the period 2003-2017, this study employs a two-stage regression process. The first relies on the use of a revised version of the Solow Model that accounts for human capital, natural resource accumulation and country-specific heterogeneity, to generate values of total factor productivity. The second examines the impact of Chinese financing on this generated measure of productivity. After taking into account significant confounding variables such as institutional quality, trade openness and manufacturing value-added, this study finds that Chinese foreign direct investment (FDI) has a significant negative impact on productivity while Chinese government loans are positively associated with productivity. However, consistent with the literature, the impact of Chinese FDI depends on the country’s absorptive capacity – proxied here by the level of human capital accumulation. Therefore, as African countries seek to boost productivity levels, they should continue to attract Chinese government loans while enhancing their FDI absorptive capacity.
Advisors: Professor Lori Leachman, Professor Grace Kim, Professor Kent Kimbrough| JEL Codes: O4, O47, F21
Where Did the Money Go? Impact of the ECB’s Corporate Sector Purchase Program on Eurozone Corporate Spending
By Tina Tian
Slow corporate growth and a lack of corporate investment has plagued European markets for the past decade. As a response, the ECB began the Corporate Sector Purchase Program (CSPP) in 2016 to provide liquidity to corporate debt markets through bond purchases. Four years after the start of the program, this paper assesses its impact by looking at how companies spent this money on a micro level. In particular, it looks at the impact of long-term debt on five expenditures (fixed assets and R&D, cash balances, short-term debt, cash to shareholders, and share buybacks). We test these hypothesized expenditures based on financial statement panel data from a selection of European firms whose bonds were purchased by the ECB. The results show an increase in financial expenditures including cash balances and short-term debt and a decrease in productive investment expenditures such as fixed assets and R&D. This indicates a lack of efficacy of the corporate bond purchase program as excess liquidity provided by the ECB went towards eurozone companies refinancing existing debt rather than investing in growth ventures.
Advisors: Professor Connel Fullenkamp, Professor Kent Kimbrough | JEL Codes: G3, O16, E58
Social Capital and Financial Development after Economic Shocks: Evidence from Italy after the Financial Crisis of 2007-2009
By Sujay Rao & Ethan Lampert
Like traditional forms of capital, social capital – an intangible measure of an individual’s social networks, trust in institutions, and participation in civic life – has implications for personal and financial behavior. Individuals from educated, well established backgrounds with fruitful family ties may be more amenable to opening new lines of credit or investing in stock markets due to their trust in and connectedness with society. But what happens after a major economic shock, such as the financial crisis of 2008? Using Italy as a case study and panel data from the Survey of Household Income and Wealth, we find that social capital has significant effects on an individual’s credit card usage, informal borrowing, and choice to invest in securities.
Advisors: Professor Grace Kim, Professor Michelle Connolly, Professor Giovanni Zanalda | JEL Codes: G01, G2, O1, D1, D14
The Impact of Microfinance on Women’s Empowerment: Evidence from Rural Areas of Uganda
By Sonia Maria Hernandez
Microfinance is the practice of extending small collateral-free loans to underserved populations in developing areas with no access to credit. The Village Savings and Loan Association (VSLA) randomized access to microfinance treatment for women in rural areas of Uganda and tracked outcomes through surveys. This research determines the impact of microfinance by analyzing outcomes over five dimensions of women’s empowerment, including decision making power, community participation, business outcomes, emotional wellness, and beliefs about women. The strongest results showed that access to the VSLA program empowered women in terms of business outcomes and decision-making power. This leads to the conclusion that microfinance can more easily impact how a woman behaves within the household than change how a woman behaves within the community.
Advisors: Professor Kent Kimbrough, Professor Lori Leachman | JEL Codes: O1, O12, O35
