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that changed their laws during the 1977—1992 period

A. Comparing the before-and-after mean mass shooting deaths and injuries for states that changed their concealed-handgun laws during the 1977—1992 period 1

1.63

0.039

1.19

0.012

Number of mass shooting deaths and injuries Mass shooting deaths and injuries per 100,000 population

B. Comparing the mean mass shooting deaths and injuries for all states with nondiscretionary concealed-handgun laws and those without such laws 2

2.09 0.041

0.89 0.037

'Column 1 for section A has 128 observations; column 2 has 32 observations. HZolumn 1 for section B has 656 observations; column 2 has 160 observations.

Years before and after the adoption of concealed-handgun laws

Figure 5.1. Probability that the ten states that adopted concealed-handgun laws during the 1977—1992 period experienced deaths or injuries from a shooting spree in a public place

plained is now the total number of deaths or injuries due to mass public shootings in a state. 5

Figure 5.1 shows that although the total number of deaths and injuries from mass public shootings actually rises slightly immediately after a nondiscretionary concealed-handgun law is implemented, it quickly falls after that, with the rate reaching zero five years after the law is enacted. 6 Why there is an initial increase is not immediately obvious, though during this early period relatively few people have concealed-handgun permits. Perhaps those planning such shootings do them sooner than they otherwise would have, before too many citizens acquire concealed-handgun permits. One additional qualification should also be made. While nondiscretionary concealed-handgun laws reduced deaths and injuries from mass public shootings to zero after five years in the ten states that changed their laws during the 1977 to 1992 period, a look at the mean death and injury rates from mass public shootings in the eight states that passed such laws before 1977 shows that these rates were quite low but definitely not zero. This tempers the conclusion here and implies that

VICTIMSANDTHE BENEFITSFROM P ROT E CT I O N / 103

while deaths and injuries from mass public shootings fall dramatically after nondiscretionary concealed-handgun laws are passed, it is unlikely that the true rate will drop to zero for the average state that adopts these laws.

County Data for Arizona, Pennsylvania, and Oregon, and State Data for Florida

One problem with the preceding results was the use of county population as a proxy for how restrictive counties were in allowing concealed-handgun permits before the passage of nondiscretionary laws. Since I am still going to control county-specific levels of crime with county dummies, a better measure would have been to use the actual change in the number of gun permits before and after the adoption of a concealed-handgun law. The per-capita number of permits provides a more direct measure of the expected costs that criminals face in attacking people. Knowing the number of permits also allows us to calculate the benefit from issuing an additional permit.

Fortunately, the information on the number of permits issued by county is available for three states: Arizona, Oregon, and Pennsylvania. Florida also provides yearly permit data at the state level. Arizona and Oregon also provided additional information on the conviction rate and the mean prison-sentence length. However, for Oregon, because the sentence-length variable is not directly comparable over time, it is interacted with all the individual year variables, so that we can still retain any cross-sectional information in the data. One difficulty with the Arizona sentence-length and conviction data is that they are available only from 1990 to 1995, and since the nondiscretionary concealed-handgun law did not take effect until July 1994, we cannot control for all the other variables that we control for in the other regressions.

Unlike Oregon and Pennsylvania, Arizona did not allow private citizens to carry concealed handguns prior to July 1994 (and permits were not actually issued until the end of the year), so the value of concealed-handgun permits equals zero for this earlier period. Unfortunately, however, because Arizona changed its law so recently, I cannot control for all the variables that I controlled for in the other regressions. Florida's data are even more limited, but they allow the study of the simple relationship between crime and permits at the state level for a relatively long period of time.

The results in table 5.4 for Pennsylvania and table 5.5 for Oregon provide a couple of consistent patterns. 7 The most economically and statistically important relationship involves the arrest rate: higher arrest rates consistently imply lower crime rates, and in twelve of the sixteen regres-

Table 5.4 Crime and county data on concealed-handgun permits: Pennsylvania counties with populations greater than 200,000

Crimes per 100,000 population

Percent change in the crime rate

Violent crime

Murder Rape

Aggravated PropertyAuto

assault Robberycrime theft

BurglaryLarceny

Due to a 1 percent change -5.3%** -26.1%* -5.1%** -4.8%**

in the number of right-to-carry pistol permits/ population over 21 between 1988 and each year since the law was implemented

Due to a 1 percent change -0.79%* -0.37%* -0.08% -0.76%*

in the arrest rate for the crime category

1.2%

-0.12%

1.5%

-1.4%

0.7%

-0.84%* -0.41%** -0.065% -1.1%*

0.13%

Note: While not all the coefficient estimates are reported, all the control variables are the same as those used in table 4.1, including year and county dummies. All regressions use weighted least squares, where the weighting is each county's population. The nondiscretionary-law-times-county-population variable that was used in the earlier regressions instead of the variable for change in right-to-carry permits was tried here and produced very similar results. I also tried controlling for either the robbery or burglary rates, but I obtained very similar results.

*The result is statistically significant at the 1 percent level for a two-tailed t-test. **The result is statistically significant at the 10 percent level for

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