a b s t r a c tIn this paper we study the determinants of banks' decisions to adopt a transactional website for their customers. Using a panel of commercial banks in the United States for the period 2003-2006, we show that although bank-specific characteristics are important determinants of banks' adoption decisions, competition also plays a prominent role. The extent of competition is related to the geographic overlap of banks in different markets and their relative market share in terms of deposits. In particular, banks adopt online banking services earlier in markets where their competitors have already adopted this technology. This paper is one of the first to construct local banking markets using the geographic market definitions delimited by the CASSIDI Ò Database compiled at the Federal Reserve Bank of St. Louis.

a b s t r a c t JEL classification: G21 J15 R23 C11We investigate whether race and ethnicity influenced subprime loan pricing during 2005, the peak of the subprime mortgage expansion. We combine loan-level data on the performance of non-prime securitized mortgages with individual-and neighborhood-level data on racial and ethnic characteristics for metropolitan areas in California and Florida. Using a model of rate determination that accounts for predicted loan performance, we evaluate the differences in subprime mortgage rates in terms of racial and ethnic groups and neighborhood characteristics. We find evidence of adverse pricing for Blacks and Hispanics. The evidence of adverse pricing is strongest for purchase mortgages and mortgages originated by non-depository institutions.

n individual's attitude about risk underlies economic decisions about the optimal amount of retirement or precautionary savings to set aside, investment in human capital, public or private sector employment, and entrepreneurship, among other things. In the aggregate, these micro-level decisions can influence a country's growth and development.Although there is a vast literature on measuring risk aversion, estimates of the coefficient of relative risk aversion vary widely-from as low as 0.2 to 10 and higher. Probably the most widely accepted measures lie between 1 and 3. 1 The most common approach to measuring risk aversion is based on a consumption-based capital asset pricing model (CAPM). Hansen and Singleton (1982), using the generalized method of moments (GMM) to estimate a CAPM, report that relative risk aversion is small. Hall (1988) shows that minor changes in the specification and instruments cause the results to vary substantially. Neely, Roy, and Whiteman (2001), in turn, explain this difference, arguing that CAPM-based estimations fail to provide robust results because difficulties in predicting consumption growth and asset returns from available instruments lead to a near identification failure of the model. In this article, we follow a different approach.We build on the methodology first outlined in Layard, Mayraz, and Nickell (2008). Using happiness data to estimate how fast the marginal utility of income declines as income increases, This article estimates the coefficient of relative risk aversion for 75 countries using data on self-reports of personal well-being from the 2006 Gallup World Poll. The analysis suggests that the coefficient of relative risk aversion varies closely around 1, which corresponds to a logarithmic utility function. The authors conclude that their results support the use of the log utility function in numerical simulations of economic models. (JEL D80, D31, I31, O57)

In this paper we provide estimates of the coefficient of relative risk aversion using information on self-reports of subjective personal well-being from multiple datasets, including three cross-sectional surveys and two panel surveys, namely the Gallup World Poll, the European Social Survey, the World Values Survey, the British Household Panel Survey for the United Kingdom, and the General Social Survey for the United States. We additionally consider the implications of allowing for health-state dependence in the utility function on the estimates of risk aversion and examine how the marginal utility of income changes in poor health states. Our estimates of relative risk aversion with cross-section data vary closely around 1, which corresponds to logarithmic utility, while the estimates with panel data are slightly larger. We find that controlling for health dependence generally reduces these estimates. In contrast with other studies in the literature, our results also suggest that the marginal utility of income increases when satisfaction with health deteriorates, and this effect is robust across the various datasets analyzed.

Okun's law is an empirical relationship that measures the correlation between the deviation of the unemployment rate from its natural rate and the deviation of output growth from its potential. This relationship is often referred to by policy makers and used by forecasters. In this paper, we estimate Okun's coefficients separately for each U.S. state using an unobserved components framework and find variation of the coefficients across states. We exploit this heterogeneity of Okun's coefficients to directly examine the potential factors that shape Okun's law, and find that indicators of more flexible labor markets (higher levels of education achievement in the population, lower rate of unionization, and a higher share of non-manufacturing employment) are important determinants of the differences in Okun's coefficient across states.

State-wide reports on police traffic stops and searches summarize very large populations, making them potentially powerful tools for identifying racial bias, particularly when statistics on search outcomes are included. But when the reported statistics conflate searches involving different levels of police discretion, standard tests for racial bias are not applicable. This article develops a model of police search decisions that allows for nondiscretionary searches and derives tests for racial bias in data that mix different search types. Our tests reject unbiased policing as an explanation of the disparate impact of motor-vehicle searches on minorities in Missouri. * Manuscript

Statewide reports on police traffic stops and searches summarize very large populations, making them potentially powerful tools for identifying racial bias, particularly when statistics on search outcomes are included. But when the reported statistics conflate searches involving different levels of police discretion, standard tests for racial bias are not applicable. This paper develops a model of police search decisions that allows for non-discretionary searches and derives tests for racial bias in data that mixes different search types. Our tests reject unbiased policing as an explanation of the disparate impact of motor-vehicle searches on minorities in Missouri.

We reexamine the relationship between quality of public schools and house prices and find it to be nonlinear. Unlike most studies in the literature, we find that the price premium parents must pay to buy a house in an area associated with a better school increases as school quality increases. This is true even after controlling for neighborhood characteristics, such as the racial composition of neighborhoods, which is also capitalized into house prices. In contrast to previous studies that use the boundary discontinuity approach, we find that the price premium from school quality remains substantially large, particularly for neighborhoods associated with high-quality schools. (JEL C21, I20, R21)