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Assistant Professor of
Economics
Weatherhead School of
Management
11119 Bellflower Road
Cleveland, Ohio 44106
Office Phone: 216-368-8845
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I
am an applied microeconomist specializing in behavioral economics. My
interests are wide-ranging and eclectic and include the study of risk
aversion and insurance choices, discrimination, and issues surrounding
self-control and commitment. I received my Ph.D. in economics from U.C.
Berkeley in 2006.
Working Papers
What's in a Picture? Evidence of Discrimination
from Prosper.com
With Devin Pope
Abstract:
We analyze discrimination in a new type of credit
market known as peer-to-peer lending. Specifically, we examine how
lenders in this online market respond to signals of characteristics such as
race, age, and gender that are conveyed via pictures and text. We
find evidence of significant racial disparities; loan listings with blacks
in the attached picture are 25 to 35 percent less likely to receive funding
than those of whites with similar credit profiles. Conditional on
receiving a loan, the interest rate paid by blacks is 60 to 80 basis points
higher than that paid by comparable whites. Though less significant
than the effects for race, we find that the market also discriminates
somewhat against the elderly and the overweight, but in favor of women and
those that signal military involvement. Despite the higher average
interest rates charged to blacks, lenders making such loans earn a lower
net return compared to loans made to whites with similar credit profiles
because blacks have higher relative default rates. This pattern of
net returns is inconsistent with theories of accurate statistical
discrimination (equal net returns) or costly taste-based preferences
against loaning money to black borrowers (higher net returns for
blacks). It is instead consistent with partial taste-based
preferences by lenders in favor of blacks over whites or with systematic
underestimation by lenders of relative default rates between blacks and
whites.
Sweating
the Small Stuff: Risk Aversion in Homeowners Insurance
Abstract:
The growing interest in economic models that incorporate reference
dependence, such as prospect theory (Kahneman & Tversky, 1979), has
been spurred on by a number of critiques of the standard
expected-utility-of-wealth model, including the so-called "Rabin
critique." Rabin (2000a, 2000b) showed that since concave
utility-of-wealth functions are locally linear, they cannot account for
risk aversion over small to modest stakes without implying implausible risk
aversion over larger stakes. Something other than the diminishing marginal
utility of wealth must be driving risk aversion over moderate financial
risks. Yet how relevant is this issue for the understanding of economic
decision making? Although there is ample evidence that people are risk
averse over small stakes in laboratory settings, there has been little
empirical evidence of substantial risk aversion over moderate stakes in
market settings, such as the demand for insurance. This paper presents
micro-level evidence from a new data set on deductible choice in home
insurance that shows a widespread willingness to pay for costly insurance
against a moderate financial loss. The prototypical homeowner in the sample
paid $100 to reduce the deductible from $1000 to $500; yet with claim rates
under 5% the expected value for this additional $500 of coverage was less
than $25. I demonstrate that these choices are indeed calibrationally
inconsistent with risk aversion arising from the diminishing marginal
utility of wealth, as they require triple-digit measures of relative risk
aversion in a standard model. In contrast, a reference dependent model can
account for these choices. Specifically, I estimate a parameterized version
of Köszegi and Rabin's (2006, 2007) extension of prospect theory using a
combination of the deductible-choice data and existing laboratory evidence.
The estimated model correctly predicts the choices of the majority of
customers, while remaining consistent with sensible risk attitudes in other
domains.
Here
is a link to an earlier version of this paper that circulated under the
title "Abundant Aversion to Moderate
Risk: Evidence from Homeowners Insurance"
A New Perspective on Stereotypical
Gender Differences in Test Scores
With Devin Pope
Abstract:
There is a heated debate surrounding the causes of sex differences in
standardized test scores. Using national test-score data for the
U.S., we document substantial variation in test-score gender disparities
across states and neighborhood characteristics. For example, the
overrepresentation of males in high percentiles of math and science in New
England is 50% less than in the most gender-unequal areas. These
results place bounds on how much genetics can be attributing to the gender
gap by demonstrating the degree to which differences in environmental
factors that exist in the US impact sex differences in academic test
scores.
Implicit
Statistical Discrimination in Predictive Models
With Devin Pope
Abstract:
How should statistical profiling models be implemented when
anti-discrimination policies prohibit basing predictions on characteristics
such as race, gender, or age? Companies, schools, and social-program
administrators typically address such concerns by simply excluding these
sensitive characteristics from the models they estimate. However, other
variables that may be correlated with these omitted characteristics – such
as zip codes, credit scores, and job tenure – are routinely used and may
serve as partial proxies for the excluded groups. We examine the importance
of this issue for the federally mandated Worker Profiling and Reemployment
Services system, in which states profile unemployment-insurance (UI)
claimants and require workshop attendance from those who are predicted to
be likely to exhaust their benefits. Using a large data set on UI
claimants, we utilize a simple procedure to compare and contrast the
approach commonly used by states with one that eliminates the ability for
modeling variables to proxy for sensitive characteristics. In this way we can
establish the degree to which the program outcomes are affected by modeling
variables serving as proxies for the excluded characteristics. We find a
significant effect, especially across racial groups, which we demonstrate
is largely driven by the correlation between race and zip codes. Our
benchmark results suggest that eliminating the influence of the sensitive
characteristics on the predictive process would decrease the fraction of
required workshop attendees that are black by roughly 25%. We address the
question of predictive accuracy and discuss the relevance of these findings
for other situations such as mortgage lending, insurance pricing, and
college admissions.
Digit
Ratios (2D:4D) as Predictors of Risky Decision Making
With Robert Slonim and
Ellen Garbarino
Abstract:
Using an emerging measure of prenatal androgens, the ratio between the
length of the second and fourth digits of the hand, we explore the
biological basis of risk taking. This 2D:4D ratio is a well-known
sexually dimorphic marker, with men having lower ratios than women on
average. In both men and women the 2D:4D ratio is established in
utero and is negatively related to prenatal testosterone and positively
related to prenatal estradiol. We find that a lower 2D:4D ratio
(i.e., signifying higher levels of in utero testosterone) predicts greater
risk taking behavior for both men and women in a financially motivated
risk-taking task, supporting a biological basis for risk taking behavior.
Work in Progress:
"Commitments
and Incentives for Exercise: A Field Experiment" joint with Heather Royer and Mark
Stehr.
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