While it is widely believed by academics, politicians, and the popular press that incumbent members of Congress are rewarded by the electorate for bringing federal dollars to their district, the empirical evidence supporting that claim is extremely weak. One explanation for the failure to uncover the expected relationship between federal spending and election outcomes is that incumbents who expect to have difficulty being reelected are likely to exert greater effort in obtaining federal outlays. Since it is generally impossible to adequately measure this effort, the estimated impact of spending is biased downward because of an omitted variable bias. We address this estimation problem using instrumental variables. For each House district, we use spending outside the district but inside the state containing the district as an instrument for spending in the district. Federal spending is affected by a large number of actors (e.g., governors, senators, mayors, and other House members in the state delegation), leading to positive correlations in federal spending across the House districts within states. However, federal spending outside of a district is unlikely to be strongly correlated with the strength of that district's electoral challenge. In contrast to previous studies, we find strong evidence that federal spending benefits congressional incumbents: an additional $100 per capita in spending is worth as much as 2 percent of the popular vote. The only category of federal spending that does not appear to yield electoral rewards is direct transfers to individuals.

While it is widely believed by academics, politicians, and the popular press that incumbent members of Congress are rewarded by the electorate for bringing federal dollars to their district, the empirical evidence supporting that claim is extremely weak. One explanation for the failure to uncover the expected relationship between federal spending and election outcomes is that incumbents who expect to have difficulty being reelected are likely to exert greater effort in obtaining federal outlays. Since it is generally impossible to adequately measure this effort, the estimated impact of spending is biased downward because of an omitted variable bias. We address this estimation problem using instrumental variables. For each House district, we use spending outside the district but inside the state containing the district as an instrument for spending in the district. Federal spending is affected by a large number of actors (e.g., governors, senators, mayors, and other House members in the state delegation), leading to positive correlations in federal spending across the House districts within states. However, federal spending outside of a district is unlikely to be strongly correlated with the strength of that district's electoral challenge. In contrast to previous studies, we find strong evidence that federal spending benefits congressional incumbents: an additional $100 per capita in spending is worth as much as 2 percent of the popular vote. The only category of federal spending that does not appear to yield electoral rewards is direct transfers to individuals.

Agents are often better informed than the clients who hire them and may exploit this informational advantage. Real estate agents have an incentive to convince clients to sell their houses too cheaply and too quickly. We test these predictions by comparing home sales in which real estate agents are hired to when an agent sells his own home. Consistent with the theory, we find homes owned by real estate agents sell for 3.7% more than other houses and stay on the market 9.5 days longer, controlling for observables. Greater information asymmetry leads to larger distortions.

Because data are collected for only fatal crashes, it is difficult to accurately measure seat belt and air bag effectiveness. The use of safety devices influences survival rates which in turn determine whether a crash is included in the sample, leading to sample selection bias. We propose a simple solution to the selection problem: limiting the sample to crashes in which someone in a different vehicle dies. Empirically, we find seat belts more effective and air bags to be less effective than previously found. The cost per life saved through seat belts is approximately $30,000, compared to $1.8 million for air bags.

Abstract In this article, we analyze the 1920s Ku Klux Klan, those who joined it, and its social and political impact by combining a wide range of archival data sources with data from the 1920 and 1930 U.S censuses. We find that individuals who joined the Klan in some cities were more educated and more likely to hold professional jobs than the typical American. Surprisingly, we find little evidence that the Klan had an effect on black or foreign-born residential mobility or vote totals. Rather than a terrorist organization, the 1920s Klan is best described as social organization with a very successful multilevel marketing structure fueled by an army of highly incentivized sales agents selling hatred, religious intolerance, and fraternity in a time and place where there was tremendous demand.

In previous research, a substantial gap in test scores between white and black students persists, even after controlling for a wide range of observable characteristics. Using a newly available data set (the Early Childhood Longitudinal Study), we demonstrate that in stark contrast to earlier studies, the black-white test score gap among incoming kindergartners disappears when we control for a small number of covariates. Real gains by black children in recent cohorts appear to play an important role in explaining the differences between our findings and earlier research. The availability of better covariates also contributes. Over the first two years of school, however, blacks lose substantial ground relative to other races. There is suggestive evidence that differences in school quality may be an important part of the explanation. None of the other hypotheses we test to explain why blacks are losing ground receive any empirical backing.

This paper analyzes the link between rising city crime rates and urban flight. Each additional reported crime is associated with a roughly one-person decline in city population. Almost all of the crime-related population decline is attributable to increased out-migration rather than a decrease in new arrivals. Households that leave the city because of crime are much more likely to remain within the Standard Metropolitan Statistical Area (SMSA) than those that leave the city for other reasons. Migration decisions of highly educated households and those with children are particularly responsive to changes in crime. Causality appears to run from rising crime rates to city depopulation.

Although theory on corruption is well developed, it has proven difficult to isolate corrupt behavior empirically. In this paper, we provide overwhelming statistical evidence documenting match rigging in Japanese sumo wrestling. A non-linearity in the incentive structure of promotion leads to gains from trade between wrestlers on the margin for achieving a winning record and their opponents. We show that wrestlers win a disproportionate share of the matches when they are on the margin. Collusion, rather than increased effort, appears to explain the results. Wrestlers who are victorious when needing a victory lose more often than would be expected the next time they meet that same opponent, suggesting that part of the payment for throwing a match is future payment in kind. Cheating disappears in times of high media scrutiny. In addition to collusion by individual wrestlers, there is also evidence of reciprocity agreements across stables of wrestlers, suggesting a centralized element to the match rigging.

We present a methodology for measuring the risks posed by drinking drivers that relies solely on readily available data on fatal crashes. The key to our identification strategy is a hidden richness inherent in two‐car crashes. Drivers with alcohol in their blood are seven times more likely to cause a fatal crash; legally drunk drivers pose a risk 13 times greater than sober drivers. The externality per mile driven by a drunk driver is at least 30 cents. At current enforcement rates the punishment per arrest for drunk driving that internalizes this externality would be equivalent to a fine of $8,000.