Persistent Private Information

This paper studies the design of optimal contracts in dynamic environments where agents have private information that is persistent. In particular, I focus on a continuous‐time version of a benchmark insurance problem where a risk‐averse agent would like to borrow from a risk‐neutral lender to stabilize his utility. The agent privately observes a persistent state variable, typically either income or a taste shock, and he makes reports to the principal. I give verifiable sufficient conditions showing that incentive‐compatible contracts can be written recursively, conditioning on the report and two additional state variables: the agent's promised utility and promised marginal utility of the private state. I then study two examples where the optimal contracts can be solved in closed form, showing how persistence alters the nature of the contract. Unlike the previous discrete‐time models with independent and identically distributed (i.i.d.) private information, the agent's consumption under the contract may grow over time. Furthermore, in my setting the efficiency losses due to private information increase with the persistence of the private information, and the distortions vanish as I approximate an i.i.d. environment.     

Hispanic Immigration and Black Violence at the Macro‐Level: Examining the Conditioning Effect of Victim Race/Ethnicity

Much attention has been devoted to the relationship between Hispanic immigration and violent offending at the macro‐level, including how it varies across racial and ethnic groups. Unfortunately, little attention has been paid to the conditioning effect of the race/ethnicity of the victim, or how Hispanic immigration is associated with crime by one racial/ethnic group against members of the same or different groups. Using National Incident‐Based Reporting System offending estimates and American Community Survey data, we examine the association between Hispanic immigration and black intra‐ and intergroup (black‐on‐white and black‐on‐Hispanic) homicide, robbery, and serious index violence in over 350 U.S. communities. We employ advanced imputation methods to address missing data that have constrained much prior research, as well as utilize crime measures adjusted for the likelihood of random contact between groups. Findings suggest that (1) Hispanic immigration has a positive association with black violence on the whole, but that (2) this association is conditioned by the race/ethnicity of the victim. Our results reinforce the importance of distinguishing across offender–victim dyads in research on the immigration–crime nexus, particularly in light of competing theoretical expectations. Directions for future research and policy are discussed.     

Are Blacks and Hispanics Disproportionately Incarcerated Relative to Their Arrests? Racial and Ethnic Disproportionality Between Arrest and Incarceration

Do large racial and ethnic disparities in prison populations reflect systematic racial and policy discrimination in the criminal justice system, or do they reflect disproportionate involvement of blacks and Hispanics in “serious” or street crime? Our investigation of this question keys off the approach initiated by Alfred Blumstein is his pioneering studies on the topic. While yielding important findings, there are, however, substantial gaps in the empirical literature on the racial disproportionality issue. We attempt to fill those gaps by (1) using both data on prison admission as well as in-stock prison populations, (2) presenting more recent racially and ethnically disaggregated arrest and incarceration data from Pennsylvania for 2003–2007, and (3) including Hispanic offenders in our racial and ethnic disproportionality comparisons. Our results indicate, first, that the representation of blacks, whites, and Hispanics among offenders admitted to state prison and in the prison population corresponds closely to their representation in arrest statistics. Second, using arrests as a marker of violent offending, the overrepresentation of blacks among offenders admitted to state prisons occurs because they commit a disproportionate number of frequently imprisoned (i.e., violent) crimes. Third, for those offenses where there is a within-race difference between arrest and incarceration representation, Hispanics experience the greatest disadvantage. Fourth, failing to account for Hispanics in white and black estimates tends to inflate white proportions and deflate black proportions of arrests, admissions, and prison population estimates, masking the “true” black and white racial disproportionality. We conclude that while there is a need for continued concern with possible racial discrimination in justice system processing, this concern should not distract attention from what arguably is the more important matter—ameliorating the social environmental conditions that foster disproportionate minority (especially black) involvement in violent crime.     

Does Activism in Social Science Explain Conservatives’ Distrust of Scientists?

Data from the General Social Survey suggest that conservatives have become less trustful of scientists since the 1970s. Gauchat argues that this is because conservatives increasingly see scientific findings as threatening to their worldview. However, the General Social Survey data concern trust in scientists, not in science. We suggest that conservatives’ diminishing trust in scientists reflects the fact that scientists in certain fields, particularly social science, have increasingly adopted a liberal-activist stance, seeking to influence public policy in a liberal direction.     

Measuring the impacts of community development initiatives: a new application of the adjusted interrupted time-series method

The authors contribute to the development of empirical methods for measuring the impacts of place-based local development strategies by introducing the adjusted interrupted time-series (AITS) approach. It estimates a more precise counterfactual scenario, thus offering a stronger basis for drawing causal inferences about impacts. The authors applied the AITS approach to three community development initiatives using single-family home prices as the outcome indicator and found that it could measure impacts on both the base level of prices and the rate of price appreciation. The authors also found a situation in which the method appears unreliable, however. The AITS approach benefits from more recurrent data on outcomes during the pre-and post-intervention periods, with an intertemporal pattern that avoids great volatility. The AITS approach to measuring effects of community development initiatives holds strong promise, with caveats.