Who Misvotes? The Effect of Differential Cognition Costs on Election Outcomes

If voters are fully rational and have negligible cognition costs, ballot layout should not affect election outcomes. In this paper, we explore deviations from rational voting using quasi-random variation in candidate name placement on ballots from the 2003 California Recall Election. We find that the voteshares of minor candidates almost double when their names are adjacent to the names of major candidates on a ballot. Voteshare gains are largest in precincts with high percentages of Democratic, Hispanic, low-income, non-English speaking, poorly educated, or young voters. A major candidate that attracts a disproportionate share of voters from these types of precincts faces a systematic electoral disadvantage. If the Republican frontrunner Arnold Schwarzenegger and Democratic frontrunner Cruz Bustamante had been in a tie, adjacency misvoting would have given Schwarzenegger an edge of 0.06% of the voteshare. This gain in voteshare exceeds the margins of victory in the 2000 U.S. Presidential Election and the 2004 Washington Gubernatorial Election. We explore which voting technology platforms and brands mitigate misvoting.

Screening in New Credit Markets: Can Individual Lenders Infer Borrower Creditworthiness in Peer-to-Peer Lending?

The current banking crisis highlights the challenges faced in the traditional lending model, particularly in terms of screening smaller borrowers. The recent growth in online peer-to-peer lending marketplaces offers opportunities to examine different lending models that rely on screening by multiple peers. This paper evaluates the screening ability of lenders in such peer-to-peer markets. Our methodology takes advantage of the fact that lenders do not observe a borrower's true credit score but only see an aggregate credit category. We find that lenders are able to use available information to infer a third of the variation in creditworthiness that is captured by a borrower's credit score. This inference is economically significant and allows lenders to lend at a 140-basis-points lower rate for borrowers with (unobserved to lenders) better credit scores within a credit category. While lenders infer the most from standard banking "hard" information, they also use non-standard (subjective) information. Our methodology shows, without needing to code subjective information that lenders learn even from such "softer" information, particularly when it is likely to provide credible signals regarding borrower creditworthiness. Our findings highlight the screening ability of peer-to-peer markets and suggest that these emerging markets may provide a viable complement to traditional lending markets, especially for smaller borrowers.

Screening in New Credit Markets: Can Individual Lenders Infer Borrower Creditworthiness in Peer-to-Peer Lending?

The current banking crisis highlights the challenges faced in the traditional lending model, particularly in terms of screening smaller borrowers. The recent growth in online peer-to-peer lending marketplaces offers opportunities to examine different lending models that rely on screening by multiple peers. This paper evaluates the screening ability of lenders in such peer-to-peer markets. Our methodology takes advantage of the fact that lenders do not observe a borrower’s true credit score but only see an aggregate credit category. We find that lenders are able to use available information to infer a third of the variation in creditworthiness that is captured by a borrower’s credit score. This inference is economically significant and allows lenders to lend at a 140-basis-points lower rate for borrowers with (unobserved to lenders) better credit scores within a credit category. While lenders infer the most from standard banking “hard” information, they also use non-standard (subjective) information. Our methodology shows, without needing to code subjective information that lenders learn even from such “softer” information, particularly when it is likely to provide credible signals regarding borrower creditworthiness. Our findings highlight the screening ability of peer-to-peer markets and suggest that these emerging markets may provide a viable complement to traditional lending markets, especially for smaller borrowers

Screening Peers Softly: Inferring the Quality of Small Borrowers

The recent banking crisis highlights the challenges faced in credit intermediation. New online peer-to-peer lending markets offer opportunities to examine lending models that primarily cater to small borrowers and that generate more types of information on which to screen. This paper evaluates screening in a peer-to-peer market where lenders observe both standard financial information and soft, or nonstandard, information about borrower quality. Our methodology takes advantage of the fact that while lenders do not observe a borrower’s exact credit score, we do. We find that lenders are able to predict default with 45% greater accuracy than what is achievable based on just the borrower’s credit score, the traditional measure of creditworthiness used by banks. We further find that lenders effectively use nonstandard or soft information and that such information is relatively more important when screening borrowers of lower credit quality. In addition to estimating the overall inference of creditworthiness, we also find that lenders infer a third of the variation in the dimension of creditworthiness that is captured by the credit score. This credit-score inference relies primarily upon standard hard information, but still draws relatively more from softer or less standard information when screening lower-quality borrowers. Our results highlight the importance of screening mechanisms that rely on soft information, especially in settings targeted at smaller borrowers.

Margin trading and leverage management

We use granular data covering regulated (brokerage-financed) and unregulated (shadow-financed) margin trading during the 2015 market turmoil in China to provide the first systematic analysis of margin investors' characteristics, leverage management policies, and liquidation choices. We show that leverage constraints induced substantial forced and preemptive sales, and leverage and cash management differed substantially across investor and account types. We explore the relation between margin trading and shock propagation, and show that China's price limit rule led to unintended contagion across stocks. Compared to brokerage investors, shadow investors were closer to their leverage constraints, and played a more significant role in transmitting shocks across stocks

Objective, Subjective, and Self-Assessment of Preadolescent Orthodontic Treatment Need – A Function of Age, Gender, and Ethnic/Racial Background?

Children from socioeconomically disadvantaged and/or underrepresented minority backgrounds in the United States have limited or no access to orthodontic treatment. Objectives: To determine whether preadolescents' (a) objectively assessed orthodontic treatment need; (b) subjectively assessed orthodontic treatment need; and (c) self-perceptions of the psychologic aspects of their oral health-related quality of life and desire to have braces vary as a function of age, gender, ethnicity/race, and socioeconomic status (SES). Methods: Data were collected from 1,566 preadolescents (age range: 8 to 11 years; 47.3 percent male/52.7 percent female; 55.7 percent African-American/39.7 percent White/2.9 percent Hispanic) in oral exams and in face to face interviews. Malocclusion was determined with the Index of Orthodontic Treatment Need. Results: Children (17.2 percent) had definite treatment need, 33.7 percent were borderline, and 49.1 percent had little or no need. Objectively and subjectively assessed treatment need was not affected by the children's age or gender. However, girls were more critical of their smiles and wanted braces more than boys. The older the children were, the more critical they were and the more they wanted braces. African-American children and children in schools with higher percentages of children on free school lunches had less treatment need than White children and children in schools with lower percentages of students with free school lunches. While the provider-assessed treatment need was higher for White children than for Black children, Black children were less happy with their smiles than White children, and wanted braces more than White children. SES did not affect the children's self-perceptions. Conclusions: Findings showed that substantial percentages of the preadolescents have an orthodontic treatment need. Orthodontic need and child self-perceptions varied as a function of the children's age, gender, ethnicity/race, and SES.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65150/1/j.1752-7325.2008.00089.x.pd

Transient reconnection in the cusp during strongly negative IMF B y

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94721/1/jgra16996.pd