Home » Year » 2013

Category Archives: 2013

The Impact of Population Mobility on repayment Rates in Microfinance Institutions

By Allison Vernerey

Several studies have attempted to model the determinants of repayment rates for group-based loans administered by micro-finance institutions (MFIs). One of the main variables that have been identifies as playing a role in determining the repayment rate is social capital. Empirical research however has struggled with quantifying this qualitative variable, resulting in vast inconsistencies across studies, aggravating cross-comparison and objective interpretation. Instead, we argue that the use of quantitative, cross-country comparable proxy that is intuitively linked to social capital would yield more consistent and reliable results. We hypothesize that population mobility is such a proxy, and that lower population mobility correlates positively with higher social capital and thus higher repayment rates. Using population mobility as a proxy for social capital would allow MFIs to lower their cost of data collection for performance assessments and simplify the process for policy makers trying to evaluate the programs success. At the village level, we find significant evidence that higher emigration within a community is strongly linked to lower repayment rates in micro-finance. These results provide micro-finance institutions with a new and more cost effective way to monitor their performance as well as improve their capacity to make well-informed lending decisions.

View Thesis

Advisor: Genna Miller | JEL Codes: G, G2, G21 | Tagged: Bangladash, Microfinance Institutions, Population Mobility, Repayment Rates, Social Capital

Geo-Spatial Modeling of Online Ad Distributions

By Mitchel Gorecki

The purpose of this document is to demonstrate how spatial models can be integrated into purchasing decisions for real-time bidding on advertising exchanges to improve ad selection and performance. Historical data makes it very apparent that some neighborhoods are much more interested in some ads than others. Similarly, some neighborhoods are also much more interested in some online domains than others, meaning viewing habits across domains are not equal. Basic data analysis shows that neighborhoods behave in predictable ways that can be exploited using observed performance information. This paper demonstrates how it is possible to use spatially correlated information to better optimize advertising resources.

View Thesis

Advisor: Charles Becker | JEL Codes: C3, C33, C53, M37 | Tagged: Ad Distribution, Advertising, Online, Real Time Bidding, Spatial

Is the Blind Side Tackle Worth It?: An Analysis of the Salary Allocation of the NFL Offensive Line

By Kelly Froelich

The importance of the left tackle position in comparison to the other offensive line positions in the National Football League (NFL) has been widely debated amongst sports commentators, as the left tackle is traditionally the second highest paid player on a football team behind the quarterback; yet, this debate lacks empirical findings. This paper aims to quantify the impact of the individual offensive linemen on the chance of winning a game on a game‐by‐game basis and then compare the impact of the left tackle to the other offensive line positions. Using a conditional logistic regression and the marginal effects from that regression, the results do not dispute the NFL’s current trend in spending more on the left tackle in comparison to the other offensive line positions. The results show that optimal spending for the left tackle could extend to 15.976 percent of the salary cap. Thus, the possibility remains that the optimal spending for the left tackle can range up to fifteen percent of the
salary cap, seven percentage points above the next highest optimal offensive lineman spending.

View Thesis

Advisor: Peter Arcidiacon | JEL Codes: J3, J31, J44 | Tagged: Football, Left Tackle, NFL, Offensive Line, Salary

Fiscal Multicointegration and Sustainability in OECD Economics

By Rajlakshmi De

Policies surrounding government expenditures and revenues are often concerned with the size of the national public debt and whether it is sustainable or unsustainable by employing the multi-cointegration framework and assertion corresponding criteria for sustainability. Denmark, Norway, Finland, Canada, Sweden, Portugal, and Austria are found to exhibit sustainable fiscal policies during the paper’s sample period, whereas the policies of the United States, Italy, France, Netherlands, United Kingdom, Spain, and Japan are determined to be unsustainable.

View Thesis

Advisor: Kent Kimbrough, Lori Leachman | JEL Codes: E6, E61, E62, E66 | Tagged: Fiscal, Multicointegration, Sustainability

Tax Evasion and Tax Morale in Latin America

By Sofia Becerra

Tax evasion throughout the world is widely endured, but not widely understood. The decision making process of the taxpayer may include many concerns outside of the monetary payoffs. The tax compliance decision considers social norms and social sanctions in addition to deterrence levels. The goal of this paper is to illuminate some of the social norms and factors that affect tax morale, since tax morale in turn drives part of compliance. An empirical study comparing tax morale in 18 Latin American countries finds that, social factors like perception of evasion by peers, as well as government trust and approval, are significant determinants of tax morale. Moreover, culture also plays a role. However, its role is not nearly as large as believed, and cannot be explained much of the variance across countries. Compliance is partly explained by tax moral, which is partly explained by culture. Tax morale will drive higher compliance all else equal, but compliance is also a function of deterrence, and both factors work in a feedback loop. Social norms and culture develop through assimilation of deterrence mechanism over time and so, culture need not be deterministic since it mutable.

View Thesis

Advisor: Michelle Connolly | JEL Codes: H2, H26, H31 | Tagged: Argentina, Chile, Latin America, Tax Evasion, Tax Morale

The Impact of Macroeconomic Surprises on Mergers & Acquisitions for Real Estate Investment Trusts

By John Reid

This paper examines the impact of various macroeconomics and real estate specific surprises on M&A transactions involving Real Estate Investment Trust. The 2008 financial crisis drastically affected merger & acquisitions activity, especially within the real estate market. The number of M&A transactions involving Real Estate Investment Trusts were very volatile during this period of economic turmoil and it appeared that several economic factors contributed to changing patterns in M&A activity. Our study uses time series data to draw a connection between REIT-related M&A activity and quantifiable factors. From or results we find there to be a relationship between the macroeconomic environment and REIT-related M&A activity.

View Thesis

JEL Codes: G10, G14, G34 | Tagged: Macroeconomic Surprises, Mergers & Acquisitions, Real Estate Investment Trust

Forecasting Beta Using Conditional Heteroskedastic Models

By Andrew Bentley

Conventional measurements of equity return volatility rely on the asset’s previous day closing price to infer the current level of volatility and fail to incorporate information concerning intraday influntuctuations. Realized measures of volatility, such as the realized variance, are able to integrate intraday information by utilizing high-frequency data to form a very accurate measure of the asset’s return volatility. These measures can be used in parallel with the traditional definition of the Capital Asset Pricing Model (CAPM) beta to better predict the time-varying systematic risk of an asset. In this analysis, realized measures were added to the General Autoregressive Conditional Heteroskedastic (GARCH) framework to form a predictive model of beta that can quickly respond to rapid changes in the level of volatility. The ndings suggest that this predictive beta is better able to explain the stylized characteristics of beta and is a more accurate forecast of the realized beta than the GARCH model or the benchmark Autoregressive Moving-Average (ARMA) model used as a comparison.

View Thesis

JEL Codes: C0, C3, C03, C32, C53, C58 | Tagged: Beta, GARCH, GARCHX, High-Frequency Data, Realized Varience

Federal and Industrial Funded Research Expenditures and University Technology Transfer licensing

By Trent Chiang

In this paper I relate the numbers of university licenses and options to both university research characteristics and research expenditures from federal government or industrial sources. I apply the polynomial distributed lag model for unbalanced panel data to understand the effects of research expenditures from different sources on licensing activity. We find evidence suggesting both federal and industrial funded research expenditures take 2-3 years from lab to licenses while federal expenditures have higher long-term dynamic effect. Break down licenses by different types of partners, we found that federal expenditures have highest effect with small companies and licenses generating high income. Further research is necessary to analyze the reason for such difference.

View Thesis

Advisor: David Ridley, Henry Grabowski | JEL Codes: I23, L31, O31, O32, O38 | Tagged: Innovation, Research Expenditures, Science Policy, Technology Transfer

The Role of Income in Environmental Justice: A National Analysis of Race, Housing Markets, and Air Pollution

By Christopher Brown

Historically, evidence has shown that minority populations in the United States suffer a disproportionate burden of pollution compared to whites. This study examines whether this burden could be the result of income disparities between whites and minorities, acting through the housing market. We look at 324 Metropolitan Statistical Areas (MSA’s) in the United States as defined by the Economic and Social Research Institute. Using demographic data from the 2000 Decennial Census and pollution data from the 1999 national Air Toxic Assessments, we compare the race-income correlation in each MSA for four races (white, black, Latino, and Asian) with the race-income.

View Thesis

JEL Codes: Q53, Q56 | Tagged: Environmental Justice, Income, Market Dynamics, Pollution, Race

Evaluating the Motivation and Feasibility Theory in Predicting the Onset and Severity of Civil Conflict

By Ishita Chordia

This paper looks at 187 countries from 1960-2004 and explores the economic indicators of the onset and the severity of civil conflicts, where civil conflicts are described as small clashes that result in 25 or more battle deaths per conflict. For conflict onset, I test a model that uses the Motivation Theory to predict when a conflict will begin while for conflict severity. I test a model that uses the Feasibility Theory to predict how severe a conflict will become. In the final section, I reverse the models and test the ability of the Motivation Theory to predict conflict severity and the ability of the Feasibility Theory to predict conflict onset. I find that the Motivation Theory performs ber at predicting both conflict onset and severity.

View Thesis

JEL Codes: F51, F52, O57 | Tagged: Conflict, Feasibility, International Security, Motivation, Peace


Undergraduate Program Assistant
Matthew Eggleston

Director of the Honors Program
Michelle P. Connolly