CONCLUSIONS

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The literature on right-to-carry laws summarized in this chapter has

obtained conflicting estimates of their effects on crime. Estimation results

have proven to be very sensitive to the precise specification used and time

period examined. The initial model specification, when extended to new

data, does not show evidence that passage of right-to-carry laws reduces

crime. The estimated effects are highly sensitive to seemingly minor changes

in the model specification and control variables. No link between right-tocarry

laws and changes in crime is apparent in the raw data, even in the

initial sample; it is only once numerous covariates are included that the

negative results in the early data emerge. While the trend models show a

reduction in the crime growth rate following the adoption of right-to-carry

laws, these trend reductions occur long after law adoption, casting serious

doubt on the proposition that the trend models estimated in the literature

reflect effects of the law change. Finally, some of the point estimates are

imprecise. Thus, the committee concludes that with the current evidence it

is not possible to determine that there is a causal link between the passage

of right-to-carry laws and crime rates.

TABLE 6-7 Trend Model with Varying Postlaw Change Durations

Violent

Years Controlsa Crime Murder Rape

1. Baseline 2000 Yes –0.95 –2.03 –2.81

comm estimateb

from row 1 of

Table 6-6

SE (0.18)** (0.26)** (0.20)**

2. 6 years 2000 Yes –0.97 –1.11 –2.90

SE (0.29)** (0.42)** (0.33)**

3. 5 years 2000 Yes –0.65 0.05 –2.45

SE (0.35) (0.50) (0.40)**

4. 4 years 2000 Yes –0.27 0.48 –0.74

SE (0.44) (0.63) (0.50)

aThe regressions use the covariates and specification from the original Lott and Mustard

(1997) models that do not control for state poverty, unemployment, death penalty execution

rates, or regional time trends. The controls include the arrest rate for the crime category in

question (AOVIOICP), population density in the county, real per capita income variables

(RPCPI RPCUI RPCIM RPCRPO), county population (POPC), and variables for the percentage

of the population that is in each of many race age gender categories (e.g., PBM1019 is

the percentage of the population that is black, male, and between ages 10 and 19).

It is also the committee’s view that additional analysis along the lines of

the current literature is unlikely to yield results that will persuasively demonstrate

a causal link between right-to-carry laws and crime rates (unless

substantial numbers of states were to adopt or repeal right-to-carry laws),

because of the sensitivity of the results to model specification. Furthermore,

the usefulness of future crime data for studying the effects of right-tocarry

laws will decrease as the time elapsed since enactment of the laws

increases.

If further headway is to be made on this question, new analytical

approaches and data sets will need to be used. For example, studies that

more carefully analyze changes in actual gun-carrying behavior at the county

or even the local level in response to these laws may have greater power in

identifying the impact of such laws. Surveys of criminals or quantitative

measures of criminal behavior might also shed light on the extent to which

crime is affected by such laws.

bUsing the revised new data set, for the full available time period (1977-2000).

NOTES: All samples start in 1977. All estimates use the trend model. Rows 2 through 4 of

this table restrict the sample to include only years falling fixed numbers of years past the law

change. For example, row 2 includes all the prelaw-change years, the year of the law change

(year 0), plus 5 additional years, for a total of 6 years after the prelaw-change period. SE =

standard error. Standard errors are in parentheses, where * = significant at 5% and ** =

significant at 1%.