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case western reserve university

Justin Sydnor

 

Assistant Professor of Economics

Weatherhead School of Management
11119 Bellflower Road
Cleveland, Ohio 44106

 

Office Phone: 216-368-8845
Email: justin.sydnor@case.edu

 

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.