Outdoor Lighting and Crime - Amper

5.3 DISCUSSION OF THE CRIME AND LIGHT ENERGY LOSS
CORRELATIONS
Overall, the examination of city crime as a function of satellite measures of city light energy
loss gave results ranging from statistically non-significant negative relationships to significant
positive relationships. Although data quality and compatibility remains an issue, the strong
positive correlations found with both English and USA data are consistent with the lighting,
commerce and crime hypothesis. If the ‘lighting for crime prevention’ theory had any
currency at all, significant negative relationships would have been found instead. It is not too
early to say that this theory, almost an article of faith for many people, now needs vigorous
debunking to diminish its potential for further mischief.
Some discordance is apparent between the English and USA results. The highest correlation
for the English data was for total crime rate against light energy loss per unit area. The USA
version of this returned a nil effect. Using the Morgan Quitno score instead produced an
equivocal result. There is apparently no UK version of this score, so a UK test of a similar
relationship does not appear feasible at present. A significant positive effect was found for
USA total crime rate against light energy loss per person, and an even stronger result for the
Morgan Quitno score against light energy loss per person. In contrast, the UK result for total
crime rate against light energy loss per person was a nil effect.
It would be possible at this stage simply to ascribe these differences to the often large and
seemingly inexplicable differences in crime patterns between England plus Wales and the
USA (Langan and Farrington 1998). For example, the rate of burglary offences in the USA
fell substantially over the report period (1981 to 1996) while the rate in England and Wales
rose by a similar amount. Nevertheless, the apparent diametrical differences between the light
energy variables giving the highest and lowest correlations detract from confidence in the
present results. A closer look at the situation changes this view to some extent, however.
The higher USA correlations were for annual rate of day plus night crime, R, or a derivation
from it, against total annual light energy loss per person, L. The regression equation can be
written
R = m L + R0,
where R0 is a constant and m is the gradient or slope. If L is zero, R0 would be the total crime
rate expected to occur if every night of the year were completely dark outdoors. In the real
world, a crime rate such as R0 has to be zero or a positive value. If m is positive, as found for
the USA, then the excess of crime rate over this limiting value, R – R0, is directly proportional
to L, regardless of the population size or density of any city for which this relationship holds.
In the real world, this relationship would only give the most likely values. The actual values
would not be constrained to linearity and would be subject to variation from other factors.
For the high English correlation (crime rate against light energy loss per unit area), the
regression equation is
R' = m' Q + R0',
78