that potential murderers respond to sanction risk probabilities and that execution events cause them to update their perceptions of those probabilities.

Studies of Deviations from Fitted Trends

This issue of why and how potential murderers react to executions is equally important to the interpretation of studies that combine data on executions and homicides over multiple time periods, deploying subtle time-series methods to analyze these data. Consider Figures 5-1 and 5-2, which plot executions and homicides, respectively, in Texas from 1990 to 2008. The most obvious way to examine the association of executions and homicides in Texas is to correlate these two time series. Over the period, this correlation is –0.68. However, there are innumerable obvious objections to interpreting this negative association as deterrence because many factors that influence the homicide rate were also changing over this time period. One manifestation of this observation can be seen in Figure 3-3 (in Chapter 3), which shows the close correspondence over time in the homi-

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FIGURE 5-1 Executions in Texas from 1990 to 2008.
SOURCE: Data from Texas Department of Criminal Justice (2011).



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