Watch Rebecca Thornquist '14 discuss her research project.

Students can find opportunities to do fascinating research in the Pomona College Economics Department. Below is a list of recent summer undergraduate research projects by economics students.

2015

Modeling Public Transportation Demand with Agent Based Models

Boyu Liu ’16; Mentor: Bowman Cutter

Funding Provided By: Richter

NCAA: Cartel or Club?

Sophia Fang ’18; Mentor: Jill Harris

For the past few decades, a majority of economists have considered the National Collegiate Association (NCAA) to be a cartel, yet a small group of scholars and legal precedents have recognized the organization as a club, or joint venture. However, recent legal cases, such as O'Bannon v. NCAA, have ruled in the favor of former student-athletes. These decisions bring the legality of the NCAA's practices to the forefront of public dialogue and raise awareness of issues such as the true definition of amateurism and the individual right of publicity. Our research aimed to gain a fully comprehensive view of the standpoints of leading economic and legal scholars on the NCAA. After perusing academic journals and other published works, we categorized nearly a hundred papers by the subcategories of cartel or club and summarized their theses and conclusions. We also explored the extent of the "cohort effect" on influencing the perspectives of co-authors and contemporaries in the economic and legal academia with regression analysis and GIS software. The ultimate product of this research is an online database that will make our findings accessible to a wide audience. There is a demonstrated demand for such a resource; two experts for the O’Bannon v. NCAA plaintiffs report spending over 400 hours researching the NCAA to prepare for the trial. Given the imminent court decisions related to the NCAA, this resource will help facilitate future economic and legal research on the NCAA's policies.
Funding Provided By: Seed

Overreaction in Football Wagers and the Value of WAR in Predicting Future Performance in Baseball

Andrew Capron ’16; Mentor: Gary Smith

Professor Smith and I spent this summer exploring several economic theories pertaining to professional sports – particularly to American Football and Baseball. We began with the NFL, collecting game data to test for bettors’ ability to account for regression to the mean in future performances of football teams with the purpose of determining a profitable betting strategy. Football scores are an imperfect measure of team abilities, thereby overstating differences in abilities between teams, meaning that future performances should regress to the mean. To test whether or not bettors account for this regression, we accumulated all regular season game scores and betting lines from 1993-2014. After running multiple regressions, we found that bettors do not fully account for this principle, allowing for a profitable strategy: betting against teams that have been much more successful than their opponents in covering their spreads, as well as betting under when the two teams have been going far over their lines, and betting over when the reverse is true. Following the NFL research, we examined the value of WAR (Wins Above Replacement) as a metric for predicting future performances in the MLB. To conduct this evaluation, we collected data from 1965-2015 on all games played in the regular season, the top 1000 players drafted annually, and every player’s individual WAR data annually. We have not yet finished the analysis of the data but will continue our research until its completion.
Funding Provided By: Seed

Reconsidering the Role of Response Time in Ethical Choice Models

Maya Kaul ’17; Mentor: John Clithero

Ethics frame human behavior each and every day. This project explores the relationship between moral decision making and response time (RT), examining if acting according to a certain ethical system is more instinctive than solving that same moral dilemma through an alternative ethical system. We conducted online experiments that posed various ethical dilemmas—some hypothetical, and others corresponding to current policy. Each dilemma required respondents to chose to act according either to the ethical theory of deontology, in which the rights of an individual cannot be violated, or according to utilitarianism, in which the rights of the individual can be compromised to maximize the well-being of the greater good. The majority of respondents varied in which ethical system they used to solve the dilemmas, suggesting that ethical choice is context-dependent, varying with attributes of the scenarios. We found the average RT for utilitarian decisions was faster, whereas deontological decisions required more time. This intriguing result contradicts existing research that suggests that deontological behavior is more emotional and based upon instinct. Ethical choice did not vary by age group, educational level, political ideology, or gender, also contrary to what much existing research suggests. Our results show the value in exploring morality in a diverse range of scenarios and that many facets of moral decision making require further exploration.
Funding Provided By: Seed

Smart Villages: How Energy Access Transforms Rural Poverty

Theresa Wong ’16; Mentor: Eleanor Brown, Shailaja Fennell (University of Cambridge), and Sir Brian Heap (University of Cambridge)

Smart Villages is a $5M joint project between Cambridge and Oxford funded by the Templeton World Charity Foundation and Cambridge Education & Development Trust. The concept of the ‘smart village’ is that energy access acts as a catalyst for development – enabling the provision of good education and healthcare, access to clean water, sanitation and nutrition, the growth of productive enterprises to boost incomes, and enhanced security, gender equality and democratic engagement. As such, energy access can provide a much needed driver for sustainable economic development and growth for a major (circa 2 billion people), but neglected, sector of the world’s economy. Smart Villages is undertaking a study of sustainable energy for villages ‘off-grid’ first in Africa, and then in Asia and Latin America. Smart Villages aims to provide policy makers, donors and development agencies concerned with rural energy access with new insights on the real barriers to energy access in villages in developing countries – technological, financial and political – and how they can be overcome. Smart Villages has chosen to focus on remote off-grid villages, where local solutions (home or institution-based systems, and mini-grids) are both more realistic and cheaper than national grid extension. The concern is ensuring energy access results in the development and creation of ‘smart villages’ in which many of the benefits of life in modern societies are available to rural communities.
Funding Provided By: Faucett

Spatially variable costs of minimum parking requirements (MPRs) in Los Angeles County: an analysis using mixed geographically weighted regression

William Skyler Lewis ’16; Mentor: Bowman Cutter

Minimum parking requirements (MPRs) are standard practice in urban planning. Research has shown that MPRs force (sub)urban developers to devote more space to parking than they otherwise would, creating an implicit tax incentivizing low-density development and urban sprawl. Through a regression of price on property attributes, one can identify where the marginal value of land exceeds that of parking, in which case MPRs bind to create excess parking area. We hypothesize that MPR impacts vary by geographic region. Real estate markets are often local, so land and parking value is likely to vary across regions or neighborhoods. To examine this spatial variation, we extend Cutter & Franco’s (2011) study of LA County by applying mixed geographically weighted regression (MGWR), a technique that allows parameters (in this case land, parking, etc.) to vary spatially. We run MGWR using data on non-residential property prices, aggregating results regionally and by property attributes. We analyze 4 distinct property types (industrial, service retail, general retail, offices) separately because of their different uses and regulatory characteristics. We find that MPRs bind the strongest in high-value areas (LA CBD, West LA, San Fernando Valley) and for smaller properties due to high marginal value of land area. Results are strongly statistically significant for offices, while all property types show similar geographic and size trends. Trends are robust to controls for zoning and amenities.
Funding Provided By: Schulz

Understanding the Decline of IPO

Lily Liu ’17; Mentors: Michelle Zemel and Manisha Goel;

IPO (Initial Public Offering) volume has been declining for nearly two decades, especially among small businesses, which are important sources of innovation, employment, and economic growth. To better understand this trend and what it would mean for the economy, I read literature regarding IPO timing , firms’ choice between conducting IPO, mergers and acquisition (M&A), or remaining private, and macro and firm level consequences of IPO and M&A. I gathered firm level IPO and M&A data, combined with macroeconomic data, and used STATA to analyze the trend in IPO volume. I found that there has been a structural break in the late 1990s and early 2000s that, except for the financial industry, there has been a decline in IPO volume across all other industries. Also, IPO volume declined significantly among small businesses. My research this summer lays the foundation for future work regarding the decline of IPO volume. The next steps of the research are building models and studying the impact of low IPO volume to employment, productivity, and economic growth, and analyzing potential causes of the issue and proposing how we can change the policies for the better.
Funding Provided By: Seed

Using the Drift-Diffusion Model to Understand Attribute Weighting of Risk and Reward

Charles Fries ’17; Mentor: John Clithero

Understanding how people make value based decisions is a common goal across the behavioral sciences. There is a growing interest within economics regarding the process behind how decisions are made. Here, we examine the effects that varying degrees of monetary risk and reward have on the decision-making process. We use the drift-diffusion model (DDM) as our primary model of choice. The DDM incorporates both response time (RT) in a model that has been used in both psychology and neuroscience. The DDM is especially well suited to evaluate data from binary choice tasks. Using various specifications of the DDM, we demonstrate that aspects of choice and RT can be consistently explained by the interaction of risk and reward in the model. In the DDM, the drift rate is the rate at which information is accumulated in favor of one decision or another, while the threshold is interpreted as the caution applied to a given task. In this study, we find (i) that the drift rate is dependent on the attributes of the gambles that go into expected value, in this case probability and magnitude; (ii) subjects’ level of caution decreases throughout the task, and also scales with the cumulative weight of stimuli attributes; and (iii) these results are stable across two separate paradigms. Our study suggests that the DDM is applicable to choice environments of interest to economists, especially towards understanding the behavioral implications of risk and reward.
Funding Provided By: Faucett

2014

Bank Lending to Young Firms During Financial Crises

Susan Nussbaum (2015); Mentor(s): Michelle Zemel, Manisha Goel

Abstract: Motivated by the importance of young firms for job creation in the US economy, this paper takes a first step in understanding the fate of these firms, specifically examining the conditions under which young firms receive bank financing. Small banks have been found to have a comparative advantage in relationship lending, though this has traditionally been examined in the context of small firms. I believe that this relationship holds for young firms, which have a short public history, and therefore are somewhat restricted to borrowing from small banks. If this is true, any situation in which small banks are adversely affected could lead to adverse outcomes for young firms. Specifically, I expect that in times of financial crisis, small banks will be negatively impacted for the following reasons: large banks are protected as they are more diversified and the government views them as too big to fail. As a result, I believe that times of financial crisis will be similarly disadvantageous for young firms. To study the fate of young firms in this context, I will evaluate the following hypotheses empirically: Are young firms disproportionately less likely to receive loans from a large bank during a crisis? If a young firm were to get a loan, would the terms be worse? To run these empirical tests, I will use loan, bank and firm level data, regressing likelihood of receiving a loan and loan terms on firm age, bank size and state of the economy, controlling for external factors. 
Funding Provided by: Faucett Catalyst Fund

Culture and Economics: Priming Evidence

Alex Kellogg (2015); Mentor(s): Tahir Andrabi

Abstract: Cultural inertia in rural Pakistan tends to drive women out of the labor force, although recent media has shown this tendency to be less extreme than before. Women in the past were relegated to the status of homemaker by tradition, and many of then were not allowed to receive education. Now, younger girls attend medical schools in rural Punjab in disproportionately high rates. The experiment conducted to investigate these cultural changes incorporates a psychological device known as a prime; survey respondents are shown one of 4 statements (one of which is a control group) and they are subsequently asked whether women are capable of working, and whether they should be allowed to work. Moreover, questions of this nature were also asked about particular daughters of the respondent. Ultimately, we find that an economic prime effects women's perception of whether they should be allowed to work, and men are generally unaffected. This could imply a perceived information gap that has caused the gender divide to persist. 
Funding Provided by: Faucett Catalyst Fund

Analyzing Education Trends in Pakistan

Joshua Rosenberg (2013); Mentor(s): Tahir Andrabi

Abstract: My project used the newest rounds of household and school-level data from the “Learning and Educational Achievement in Pakistan Schools” (LEAPS) project to analyze various aspects of education in Pakistan. One part of my project involved using STATA and regression analysis to analyze the trends and determinants of pre-school enrollment over time. Some have theorized that pre-school enrollment in Pakistan is increasing because private schools have been able to provide pre-school education cheaply while remaining profitable. However, I found that pre-school enrollment, as a percentage of total enrollment, has not increased in the last 5 years and that private schools have not offered proportionally more pre-school services than public schools. I also found that younger children were more likely to enroll in private schools. To determine causes of enrollment, I constructed variables for parents' education level, parents' time use, household wealth, and household demographics, but my regression analysis was inconclusive.
Funding Provided by: Pomona College SURP

Recession Blues: Do Economic Conditions Affect Music Preferences?

Samuel Antill (2013); Mentor(s): Eleanor Brown

Abstract: In this work, I examine the relationship between economic conditions and the market for popular music. While some forms of entertainment, such as movies, immerse the consumer in a prolonged, multisensory experience that offers an escape from daily life, popular music is an expressive art form that is more likely to be chosen based on the listener's mood . I hypothesize that the relative popularity of sad songs increases during economic downturns. To test this, I use the One Million Song dataset to obtain characteristics of a large sample of songs published between 1922 and 2010. Using mode as a proxy for the mood of the song, a song is classified as sad if it is minor and happy if major. I test whether changes in the mood of popular music can be explained by recessions or general economic conditions. Preliminary results suggest that economic downturns have a significant positive correlation with the proportion of contemporary songs that are sad. In addition to a cyclical pattern in the demand for sad songs, my results confirm a recent study's finding that popular music is getting sadder over time.
Funding Provided by: Paul K. Richter and Evalyn E. Cook Richter Memorial Funds

2013

Analyzing Test Scores and Teacher Performance in Pakistani Schools

Rebecca Howland (2014); Mentor(s): Tahir Andrabi

Abstract: My work consisted of two distinct elements. The first was organizing raw data on student and teacher test scores from Pakistani schools. The second was done in collaboration with Developments in Literacy (DIL), a Pakistani education non-profit. The goal of this component was to analyze a set of baseline data for a new teaching intervention that DIL is in the process of implementing. The study contains two groups: a control group and a group that will receive the intervention. DIL will continue to test the teachers and compare the results of these tests in the two groups. This involved performing an item analysis (determining the quality of question on a multiple-choice test as well as how teachers performed on each question). In order to understand the areas in which teachers need to improve, I identified low correct response rates and matched the percentage with the specific type of question. An example of a question classification going from most general to most specific was English: Reading: Grammar: function of pronouns. I performed these analyses using Excel for data management and STATA for data analysis.
Funding provided by Aubrey H. and Eileen J. Seed Student Research Fund

Evaluating the effect of uncertainty reductions in the selection of wind projects

Kristen McCormack (2015); Additional Collaborator(s): Katie Dickinson (National Center for Atmospheric Research); Matthew Hendrickson (3TIER); Mentor(s): Bowman Cutter

Abstract: This project focuses on understanding the role of uncertainty in project selection decisions that are made during the development of a wind farm. In past decades, wind projects have underperformed pre-construction energy estimates by an average of about 10%. This has put a strain on various players in the wind industry, and has damaged the reputation of wind energy. Research to address this gap in performance has primarily considered ways to reduce the bias in pre-construction estimates. However, even with unbiased energy modeling, uncertainty may lead to significant overprediction as well as a tendency to pick suboptimal projects. By simulating selection decisions made by utilities during power purchase negotiations, the effect of pool size and uncertainty on suboptimal selection and overprediction were analyzed. The results of the model indicate that, with no change to model bias, reducing model uncertainty may result in a reduction in the overprediction of wind energy and may enable more optimal selection of projects. This model may be used by utilities and developers to adjust their own selection processes and to determine the value of investing in more precise modeling techniques.
Funding provided by Faucett Catalyst Fund

The Green Premium in New York City: Energy Efficiency and Certification in the New York Commercial Real Estate Market

Angela Gunn (2014); Mentor(s): W. Bowman Cutter

Abstract: LEED and Energy Star certification recognize environmentally friendly buildings, providing a free market incentive to “go green.” Such buildings can be advertised as both socially responsible and less expensive to operate, and existing literature demonstrates that LEED and Energy Star buildings in the United States have higher sale prices and rental rates than similar, non-certified buildings. It is believed that owners of highly efficient, uncertified buildings may not reap the same benefits because energy efficiency is difficult to signal to buyers and renters. This project explores two issues. First, I consider whether the “green premium”– the higher price renters and buyers pay for an efficient building– is primarily determined by third-party certification or actual efficiency. Second, I compare the green premium for commercial buildings in the New York City market to estimates of the national green premium. I use building-level information from the national LEED and Energy Star directories, New York City’s 2011 benchmarking data, and the CoStar real estate database to compare rent and sale prices of New York buildings with certification to those that are highly efficient but not certified, and to similar buildings that are less efficient. I seek to better understand the role of third-party certification groups in motivating commercial building owners to focus on energy efficiency, and to determine whether that efficiency is valued differently in New York City.
Funding provided by Faucett Catalyst Fund

A Bayesian DSGE Model of Financial Business Cycles

Tianyou Gu (2015); Mentor(s): Michael Kuehlwein

Abstract: The paper develops and estimates a dynamic stochastic general equilibrium (DSGE) model where credit market frictions and stock investment exacerbate the business cycles. In this framework, adverse shocks to the housing price or repayment rate force financial intermediaries to deleverage. As a consequence, credit crunch and counter-cyclical external finance premium drive both borrowers away, thus dragging down spending, investment, output and real asset prices. The novelty of the model is that it goes further to capture the fact that financial shocks are further amplified since both consumption and credit supply would drop as shareholders become less wealthy following the plunge of stock prices caused by deteriorating company fundamentals. In this way, any shock in productivity sector, investment sector, or bank intermediation sector is contagious, just as in the real world in which technology shock, investment speculation, or credit frictions shock could lead to boom or depression. The model is estimated with Bayesian techniques using data for the U.S. over the last 30 years. And the empirical analysis delivers the following results. First, decreased bank capital has a substantial impact on the real economy. Second, stock market plays an indispensable accelerator role in driving the bubbles and bursts. Third, the estimated model implies that nominal contract channel and housing collateral channel also contribute a lot to the feedback loop.
Funding provided by Pomona Alumni SURP Fund; Pomona College Department of Economics

Hours Misreporting in the Current Population Survey

Jacob Fiksel (2015); Mentor(s): Fernando Lozano; Michael Steinberger

Abstract: The Current Population Survey (CPS) is the most commonly used survey for investigating wages in the US economy. To estimate hourly wages, researchers must divide weekly earnings by hours worked—but the CPS asks for two different measures of hours per week: the hours the respondent usually works, and the hours worked last week. We document and explore the discordance in how respondents report these two measures of weekly hours over time. If misreporting of usual hours has changed, then this will automatically lead to spurious changes in estimated hourly wage measures. We take advantage of the longitudinal CPS format to suggest what we believe to be more accurate measure of hours worked: the mode response of hours worked last week for each respondent. Using a DiNardo, Fortin, and Lemieux (1996) decomposition technique, we control for changes in the misreporting of hours throughout the distribution of hours worked since 1996. We show that misreporting is an issue for wage measurements in a given year, but does not appear to be a contributing factor for the documented changes in wage inequality during the period.
Funding Provided by: Pomona College SURP

Heterogeneity in Conditional Cash Transfer Effects: Evidence from a Randomized Experiment in Malawi

Johnny Huynh (2014); Mentor(s): Michael Steinberger

Abstract: A growing body of literature documents the effectiveness of conditional cash transfers (CCTs) on increasing investments in children’s human capital. While cash transfers can increase children’s average rates of school attendance and test scores, how are these gains are distributed across treated students? How much do parents take into account latent capabilities of their children when deciding how to respond to CCT programs? We explore the distributional effects of a randomized cash transfer experiment for adolescent schoolgirls in Malawi first documented in Baird, McIntosh and Ozler (2011). We present a theoretical model showing that the positive mean effects of the CCT program should be concentrated among a specific subset of potential participants. To test our theory, we use a set of observable test scores to identify latent academic ability and estimate quantile treatment effects for the CCT program. Our evidence shows the impact of the CCT program on test scores is only significant on the third quartile of latent ability. As predicted, unconditional transfers do not show a similar distributional heterogeneity. We also explore the effect of the CCT on school enrollment and attendance, with inconclusive results. Our findings have strong implications for public policy, suggesting the primary beneficiaries of CCTs are higher-ability children, while having little effect on lower ability, often poorer, children.
Funding Provided by: Faucett Catalyst Fund

Does aggregate loan growth predict future performance of the financial sector?

Nathan Shekita (2015); Mentor(s): Michelle Zemel

Abstract: In this project, we examine bank lending and the effect this has on the overall market. We attempt to create a measure that can be used to predict an economic crisis with sufficient accuracy. Data was obtained from the Wharton Research Data Service, as well as the Federal Reserve Economic Data (FRED). Using logistic regression, we find that statistically, our measure does a better job at predicting crises than those defined from other literature. The Hodrick-Prescott filter was used to detrend and deseasonalize the data. We use both backward and forward looking techniques to assure the legitimacy of our findings. We also attempt to explain the reasoning as to why our measure works, as well as its possible applications.
Funding Provided by: Faucett Catalyst Fund

2012

Mapping Global Savings Mechanisms — Bangladesh

Emily Brotman (2013); Mentor(s): Tahir Andrabi

Abstract: Rural poor populations in Bangladesh demonstrate remarkable ingenuity in the management of their meager incomes, particularly in their capacity to save. Working for the research group, Innovations for Poverty Action (IPA) as one of 17 interns placed in 11 different countries, I helped develop a quantitative survey to collect information about the costs, returns, and risks of the various savings arrangements used by the world's poor. I adapted the questionnaire to Bangladesh and surveyed fifty randomly selected households in the sub-district of Tanore. The purpose of this research is to identify the strengths and weaknesses of the financial tools already available to the poor. Should aid foundations invest more money in microfinance or are the existing solutions sufficient? What can a semi-formal financial institution provide that an informal village savings group cannot? These are the kinds of questions this study hopes to inform. Data analysis will be conducted by IPA over the next few months using the information collected this summer. 
Funding Provided by: Pomona College SURP; Pomona College Economics Department; Pacific Basin Institute

Primary and Secondary School Interventions in Pakistan

Gabriela Hybel (2013); Mentor(s): Tahir Andrabi

Abstract: In the past few decades organizations have increasingly taken up the cause of improving primary and secondary education within majority world countries. One such country with a high demand for improved education is Pakistan. Disparities between female and male school enrollment continue, and students who do attend school frequently encounter poorly trained teachers and an environment that is not conducive to learning. In response, Development in Literacy (DIL) was created by a group of Pakistani Americans to focus on educating those most in need, primarily girls in remote regions of the country. Today 17,062 students are attending DIL schools. With this attention on education, there is a need for formal and complete evaluations on effective models for implementing schools in countries such as Pakistan. With this demand in mind, this research uses DIL as a starting point to further the current literature on successful methods of school improvement. It focuses on various DIL school interventions, including teacher training, curriculum development, school management, IT support, and community outreach. This research was conducted through numerous interviews with DIL directors and a review of key DIL documents to understand the models and practices used by the organization. It provides a starting point from which future evaluations and studies can potentially be carried out.
Funding Provided by: Faucett Catalyst Fund

Analyzing Education Trends in Pakistan

Joshua Rosenberg (2013); Mentor(s): Tahir Andrabi

Abstract: My project used the newest rounds of household and school-level data from the “Learning and Educational Achievement in Pakistan Schools” (LEAPS) project to analyze various aspects of education in Pakistan. One part of my project involved using STATA and regression analysis to analyze the trends and determinants of pre-school enrollment over time. Some have theorized that pre-school enrollment in Pakistan is increasing because private schools have been able to provide pre-school education cheaply while remaining profitable. However, I found that pre-school enrollment, as a percentage of total enrollment, has not increased in the last 5 years and that private schools have not offered proportionally more pre-school services than public schools. I also found that younger children were more likely to enroll in private schools. To determine causes of enrollment, I constructed variables for parents’ education level, parents’ time use, household wealth, and household demographics, but my regression analysis was inconclusive. 
Funding Provided by: Pomona College SURP

Recession Blues: Do Economic Conditions Affect Music Preferences?

Samuel Antill (2013); Mentor(s): Eleanor Brown

Abstract: In this work, I examine the relationship between economic conditions and the market for popular music. While some forms of entertainment, such as movies, immerse the consumer in a prolonged, multisensory experience that offers an escape from daily life, popular music is an expressive art form that is more likely to be chosen based on the listener's mood . I hypothesize that the relative popularity of sad songs increases during economic downturns. To test this, I use the One Million Song dataset to obtain characteristics of a large sample of songs published between 1922 and 2010. Using mode as a proxy for the mood of the song, a song is classified as sad if it is minor and happy if major. I test whether changes in the mood of popular music can be explained by recessions or general economic conditions. Preliminary results suggest that economic downturns have a significant positive correlation with the proportion of contemporary songs that are sad. In addition to a cyclical pattern in the demand for sad songs, my results confirm a recent study’s finding that popular music is getting sadder over time.
Funding Provided by: Paul K. Richter and Evalyn E. Cook Richter Memorial Funds

Parks and Preserved Open Space as Real Estate Amenities

Rebecca Thornquist (2014); Mentor(s): Eleanor Brown

Abstract: Real estate sales data from the Washington, D.C. metropolitan area is used to estimate the effects of proximity to parkland on real estate prices. I use GIS software to measure the exact distance in feet from homes to park boundaries, grouping parks into 4 size categories. I include unrelated demographic and housing characteristic variables to control for other influences. I find that I find that parks with areas of less than 2 acres are not positively correlated to real estate prices. For parks above 2 acres, sale prices increase between $45,038/mi and $81,312/mi with proximity to parks. 
Funding Provided by: Schulz Fund for Environmental Studies

Adaptive Market Synthesis: Theory and Application

Zihao Song (2013); Mentor(s): Gabriel Chandler; Pierangelo De Pace

Abstract: I formalize a theory of adaptive market synthesis that tries to address two problems in economic modelling. First, optimization is hard. Perfect rationality implies optimizing behavior. But in reality we can only solve a very small number of optimization problems, and we hope to “progressively” learn how to solve others. Thus bounded rationality leads to suboptimal behavior. Second, learning does not simply happen in a “progressive” manner. Since knowledge is a set of concepts rather than facts, knowledge doesn't necessarily accumulate as facts accumulate. ``Progressive'' learning needs a common frame of reference for any observer to compare models of reality. I provide a statistical theory such that models from any function space can be compared based on metrics such as bias (subjective error) and variance (random error). I present empirical results that show a low-bias non-linear model with a low-variance numerical solution can consistently generate ex ante positive excess returns on equity indices, given historical prices.
Funding Provided by: Faucett Catalyst Fund

A Comparison of RMB with Other Major Currencies in Forex Market

Shiwei Zhang (2014); Mentor(s): Pierangelo De Pace

Abstract: When compared with other major currencies, RMB displays behavior with least appearance to a random walk. The first part of the research examines RMB/USD exchange rate since 2000 using ARMA and PPP (Purchasing Power Parity) models. We find that among predictions for all the major currencies, RMB/USD rate is the least accurate, by a factor of 2 or 24 even more. The second part of the research examines the reaction of RMB in Forex market when there is a shock in domestic monetary policy. In most free economies, currency depreciates when monetary policy loosens, and appreciates when tightens. In China however, we find no statistically significant change in RMB value when monetary policy changes. The above results reaffirm that RMB is a tightly controlled currency. The second result also raises concern to the claim of “undervalued” RMB—with a loose monetary policy for 10 years, is RMB now undervalued or overvalued?
Funding Provided by: Pomona College SURP

An Examination of Income Tax Overwithholding

Ashvin Gandhi (2013); Mentor(s): Michael Kuehlwein

Abstract: In 2004, 77% of people left themselves an average of $2,100 less in their pockets over the year by overwithholding on their income. While they do get this money back in the form of a tax refund, they miss out on interest they could have earned throughout the year. Worse yet, low income taxpayers (who are most likely to overwithhold) are sometimes forced to take out high interest consumer loans to pay for day-to-day expenses. We investigate possible causes for this phenomenon. We reexamine the hypothesis that income tax overwithholding can be explained as a taxpayer's response to uncertainty in income and allowances under threat of penalty. We adjust the models used to justify such a conclusion to account for interest accumulated on underwithheld income, enforce boundary conditions, adjust for appropriate income variability, and incorporate relevant tax rules when determining the expected refund rate. We find that each of the aforementioned weakens the conclusion that income tax overwithholding is a response to uncertainty. Further, we use a panel of tax returns to test the alternate hypotheses that overwithholding is driven by other phenomena, such as mental accounting and the default effect.
Funding Provided by: Pomona College SURP

Aspirations and Educational Attainment in Poor Communities

Maria Zhu (2013); Additional Collaborator(s): Shalaija Fennell*; Mentor(s): Fernando Lozano
*Cambridge University

Abstract: This project focuses on developing a better understanding of the role of aspirations in educational outcomes in poor communities, using both quantitative and qualitative data from Pakistan. Aspiration is defined as goals and hopes regarding educational attainment, which encompasses a variety of factors such as school type and quality, purpose of school achievement, and the ways educational achievement shape an individual’s views for their future. Existing economic literature on the topic measures aspirations in terms of income and savings, as a level of material satisfaction of needs and wants. However, these income models are less relevant for developing nations, where poverty is often structurally embedded and income mobility is restricted. Poor households often lack the access to educational resources and social capital of their wealthier counterparts, and thus experience education in different ways. Thus, educational aspirations manifest in a multitude of qualitative contexts beyond years of schooling. This study looks at the quantitative relationship between subjective well-being and level of education (measured in years) for the communities surveyed, identifying differences in age and gender. The relationship of these results are then linked to the qualitative data from interview and focus group transcripts of parents and students to provide a framework for understanding the relationship between aspirations and education, measured by more than years of attendance.
Funding Provided by: Faucett Catalyst Fund

The Economic Crisis of Spain: two stories

Erin Toothaker (2013); Additional Collaborator(s): Rubén Garcia Iglesias*; Mentor(s): Stephen Marks
 

Abstract: The relative impact of the spanish economic crisis on the employment prospects of Spanish citizens and refugees in Spain, specifically Madrid, was evaluated using a combination ethnographicaleconometric approach. Working in the Madrid center for refugee aid during a seven-month period provided a unique opportunity to interview newly arrived refugees, spanish residency-holding refugees, and more established former residents of the refugee center. It also facilitated interviews with long-time employees of the center who have been in a position throughout the last five to ten years to observe these changes across groups of arriving refugees. These interviews are combined with national level econometric analyses of unemployment in citizens and refugees. In this way, the statistical story is informed on a more human level and becomes more individually and personally accessible as well as more complete in its evaluation of the impact of the Spanish economic crisis on the two study groups. Refugees were relatively more negatively impacted by rising unemployment in the earlier stages of the crisis than Spanish citizens, but during more recent increases in unemployment this discrepancy between group impacts has decreased, as have the perceived relative impact discrepancies as reported by members of both groups, refugee center employees, and various employers.
Funding Provided by: Pomona College SURP