The residential burglary rate in Kennesaw, Georgia dropped sharply
after a city ordinance requiring heads of household to keep at least one
firearm in their homes was passed. The law passed early in 1982.
In 1986 the rate was still down 85% compared to 1981. (1)
This statistic is essentially meaningless. If the crime rate
fluctuates, then by picking the right two years to compare, you can
get any result you want. To make a credible case, you need to provide
data for at least the ten years 77-86. I haven’t seen Kleck’s book,
but in his “Social Problems” paper, he uses figures for residential
burglary that are contradicted by the official UCR data.
What about that study that shows no drop in burglary in Kennesaw?
Well strangely, the authors used the total burglary rate not the
more relevant residential burglary rate.
Does the UCR data break burglaries down into residential and
non-residential ones? If not, then in the absence of reliable data on
residential burglaries, it is best to use total burglaries. Since
this includes residential burglaries, it would be surprising if a
reduction in the residential rate did not appear as a reduction in the
In another strange error(*), the authors did not account for
Kennesaw’s seventy percent population increase over the period. (2)
The population would have to increased by over 500% between 81 and 85
for there to be an 85% drop in the population adjusted rate, and no
reduction in the actual number of burglaries.
The population increase would occur gradually over the period and
could not mask an abrupt change in the burglary rate, so dividing the
number of burglaries by the population will not change the result of
the interrupted time series analysis: Here are the burglary rates
76-86, assuming a population growth of 70%, normalized to the 76
population value. Each x represents 5 burglaries.
xx xx xx xx xx x xx x x xx xx xx xx xx xx xx xx xx xx xx xx xx xx xx xx xx xx xx xx xx xx xx 76 77 78 79 80 81 82 83 84 85 86 ^ Law
The rate does not appear to be lower after the law.
Average 76-81 is 29
Average 82-86 is 26
The average after is a little lower. To test the significance of
this, I use Student’s t-test. I compute t=-0.13 with 9 df, p=0.51,
that is, 51% of the time chance will produce a change this large.
This obviously not significant.
In any case, a population increase of 70% weakens any evidence for a
deterrent effect. Such rapid growth means Kennesaw changed
significantly during the period in question, so even if there was a
significant reduction in burglaries, we don’t know whether one of the
other changes in Kennesaw caused it.