Skip to main content

Currently Skimming:

1 Introduction--Richard Rosenfeld and Arthur S. Goldberger
Pages 1-12

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.


From page 1...
... Department of Justice sent teams of "auditors" to a select group of cities in 2007 to examine local records and consult with law enforcement officials concerning local crime trends. Although there may be good reasons for proceeding in this way, the contrast with using available employment indicators to evaluate local labor market conditions is illuminating.
From page 2...
... has no equivalent in criminal justice, even though timely information on changes in serious violent and property crime rates is just as vital to the nation's health and welfare as information on changing levels of industrial production or consumer prices. The FBI's UCR do provide national and local crime indicators, but the UCR data are released several months after the relevant reporting period.
From page 3...
... Two researchers, Eric Baumer and John Pepper, were asked to perform separate analyses, including forecasting crime rates, on a city-level dataset specially created for the committee by Robert Fornango of Arizona State University. Finally, the committee asked Steven Durlauf to discuss statistical and theoretical issues in drawing causal inferences from observational data on crime rates.
From page 4...
... The second lesson is that multiple causes underlie the crime drop and, by extension, longer term variations in crime rates. Some progress has been made in identifying candidate explanatory factors, which include the quadrupling of the nation's prison population since 1980; cyclical variations in unemployment, wages, and other economic conditions; and the changing dynamics of illegal drug markets (Blumstein and Wallman, 2005)
From page 5...
... are, by themselves, unlikely to account for short-run swings in crime rates, such as those occurring in some cities in 2005 and 2006. Better candidate explanations include cyclical economic changes, prison admissions and releases, local enforcement initiatives, and other factors subject to year-to-year fluctuation, some of which may activate local grievances or more widespread and long-standing psychological or cultural conditions.
From page 6...
... In Chapter 3, Karen Heimer and Janet Lauritsen use data from the National Crime Victimization Survey to examine changes between 1980 and 2004 in female and male violent offending and victimization and victim-offender relationships in violent incidents.  This work has not been done previously except for homicide, and so the chapter constitutes a unique contribution to the field.  Among the authors' findings are a widening of the gender gap in intimate partner homicide victimization due to a greater decline in victimization among men, a narrowing of the gender gap in overall violent offending, an increase in the proportion of assaults involving female victims, and an increasing likelihood of female involvement in violent interactions, both as perpetrators and as victims. The authors note that the modal category of violent crime in 2004 is not the same as it was in earlier decades.
From page 7...
... To overcome some of the political challenges to achieving this goal, he calls for the shifting of social and professional norms toward more open and transparent data systems to monitor changes in local crime rates that mirror changes in each city's neighborhoods. The chapters by Eric Baumer and John Pepper analyze crime trends in U.S.
From page 8...
... Changes in the values of the corresponding explanatory variables need to be considered as well. Doing so to estimate the relative contributions of the explanatory variables to observed change in crime rates, Baumer's analysis supports the conclusion that the rise in youth firearm violence, robbery, and some forms of auto theft during the 1980s can be attributed to the emergence and proliferation of crack cocaine markets.
From page 9...
... While Baumer included once-lagged crime rates along with a long list of covariates, Pepper focused on the lagged rates, supplemented in part by a very short list of covariates. He examines the possibility of predicting a crime rate series from its past history, thus treating forecasting as distinct from causal analysis.
From page 10...
... To take one example, Wolfers suggests that "prediction markets" of the kind used to forecast economic changes and election outcomes may have a useful role in forecasting crime rates (Wolfers and Zitzewitz, 2004)
From page 11...
... . Connecting the dots: Crime rates and criminal justice evaluation research.


This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More information on Chapter Skim is available.