I found considerable variability in the parameters and forecasting performance across models, cities, crimes, and horizons. While there is evidence of heterogeneity across cities, heterogeneous models do not perform notably better than the homogeneous alternatives. A naïve random walk forecasting model performs quite well for shorter run forecast horizons, but the regression models are superior for longer horizon forecasts.

Finally, I use the basic homogeneous panel data models to provide point forecasts for city-level crime rates in 2005, 2006, and 2009. This out-of-sample forecasting exercise reveals predictions that are sensitive to the covariate specification. All models generally indicate modest changes in city-level crime rates over the next several years. However, forecasts found using one model imply that city-level crime rates will tend to increase over the remainder of the decade, whereas forecasts from another model imply that crime rates will fall.

In closing, I draw conclusions about the limitations of forecasting in general and the specific problems associated with forecasting crime. Forecasting city-level crime rates appears to be a volatile exercise, with few generalizable lessons for how best to proceed.


While my primary interest is to forecast city-level crime rates, I begin by considering the national time series in homicide rates. Some of the basic issues involved in forecasting crime can be illustrated effectively by considering this single national time series. Attempts to forecast this series in the 1980s and 1990s have been notoriously inaccurate.

Using data on annual homicide rates per 100,000 persons from the National Center for Health Statistics, I display the annual time series in the log rate for 1935-2002 in Figure 6-1.3 The series appears to be quite persistent over time, with some periods of fluctuation and notable turns. From 1935 until around 1960, the homicide rate tended downward and then began sharply rising, reaching a peak of just over 10 homicides per 100,000 (log rate of 2.31) in 1974. Over the next 15 years, homicide rates fluctuated between 8 and 10 per 100,000 (log rates between 2.13 and 2.33) and then unexpectedly began to sharply and steadily fall in the 1990s. By the end of the century, the homicide rate hit a 34-year low of 6.1 per 100,000 (log rate of 1.81).


Data come from the National Center for Health Statistics and were downloaded in January 2007 from the Bureau of Justice Statistics Historical Crime Data Series at http://www.ojp.usdoj.gov/bjs/glance/tables/hmrttab.htm. The victims of the terrorist attacks of September 11, 2001, are not included in this analysis. Some concerns have been raised about the reliability of the annual time-series data on crime prior to 1960, but the effect on homicide trends is thought to be minimal. For further discussion of these issues, see Zahn and McCall (1999).

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