Explanations in the social sciences:
What problems confront social scientists when trying to explain/interpret their data?
In the United States in the 1990s there was a dramatic drop in
the crime rate. Many commentators sought to explain this
sudden and significant decrease in the crime rate. The table
below shows crime-drop explanations cited in articles published
from 1991-2001 in the ten largest circulation papers in the
LexisNexis database, and evidence taken from a study in Levitt
and Dubner’s Freakonomics.
1. From the evidence below, which of the 6 main explanations
for the drop in crime rate on the list seem to have most merit?
NB: Levitt and Dubner argue that only 3 can be shown to have
really contributed to a drop in the crime rate.
CRIME-DROP EXPLANATION
1.Increased reliance on prisons
NUMBER
OF
CITATIONS
47
2.Changes in crack and other drug
markets
33
3.Tougher gun-control laws
32
4.Strong economy
28
5.Increased number of police
26
6.Increased use of capital punishment
34
EVIDENCE SUMMARY
-1980-2000 saw a 15 fold increase in the number of people
sent to prison on drugs charges.
-by 2000 c. 2million people were in prison; 4 times the
number in 1972.
-estimates suggest that over 25% of the homicides in New
York in 1988 were crack-related.
-the price of cocaine began to fall significantly during the
1990s.
-the Brady Act (1993) requires a criminal check before a
person can purchase a handgun.
-there was an increase in prison sentences for those in
possession of an illegal handgun.
-evidence gathered by the economist John R Lott Jr. for his
book More Guns, Less Crime in which he argues that violent
crime has decreased in areas where law-abiding citizens are
allowed to carry concealed weapons*.
-a significant fall in unemployment in 1990s
-unemployment rate fell by 2 % points in 1990s
-non-violent crime fell by 40% in the 1990s: homicide fell at
the greatest rate.
-the number of police officers during the 1990s rose by 14%.
-1991-2001 the NYPD grew by 45% (more than 3 times the
national average) and New York City experienced a big crime
drop: homicide rates fell from 30.7% per 100,000 people to
8.4% per 100,000 in the same period.
-between 1960 and 1985 the number of police officers fell.
-the number of executions in the US quadrupled between
1980s and 1990s.
-in total there were 478 executions in the US in the 1990s.
* = Lott’s work was immediately controversial, drawing large amounts of support and opposition. Numerous academics praised Lott's methodology,
including Florida State University economist Bruce Benson and academics Milton Friedman, and Thomas Sowell. Other reviews claimed that there were
problems with Lott's model. In the New England Journal of Medicine, David Hemenway argued that Lott failed to account for several key variables,
including drug consumption, and that therefore the model was flawed; however, Lott's book did account for other variables such as cocaine prices.
Academic Gary Kleck considered it unlikely that such a large decrease in violent crime could be explained by a relatively modest increase in concealed
carry, and others claimed that removing portions of the data set caused the results to only still show statistically significant drops in aggravated assaults
and robbery when all counties with fewer than 100,000 people and Florida's counties were both simultaneously dropped from the sample. Outside of
academia, Lott is best known for his participation in the gun rights debate, particularly his arguments against restrictions on owning and carrying guns.
He is also known for taking conservative positions on a wide range of political issues.
From http://en.wikipedia.org/wiki/John_Lott
2. What assumption is/maybe being made in the way the explanation is reached from the evidence in some
of the crime-drop explanations?
Explanations in the social sciences:
What problems confront social scientists when trying to explain/interpret their data?
More explanations:
Levitt and Dubner suggest an alternative explanation for the dramatic drop in the crime-rate:
the legalisation of abortion in the USA following the Roe v Wade ruling in 1973.
However, other economists have criticised Levitt and Dubner’s argument:
Sailer argues that the end of the crack wars was more significant than abortion, and that, contrary to what
Levitt's thesis would suggest, "the murder rate for 1993's crop of 14-17 year-olds (who were born in the
high-abortion years of 1975 to 1979) was a horrifying 3.6 times that of the kids who were 14 to 17 years
old in 1984 (who were born in the pre-legalization years of 1966 to 1970)."
Joyce also made a number of arguments against the abortion and crime hypothesis in his 2004 paper "Did
Legalized Abortion Lower Crime?”. He claimed that legal abortions in the early 1970s were just replacing
illegal abortions, that there was no measurable impact of abortion between 1985 and 1990.
The economists Christopher Foote and Christopher Goetz released a paper, "Testing Economic Hypotheses
with State-Level Data: A Comment on Donohue and Levitt (2001)", in which they argued that Donohue and
Levitt's study did not estimate the regressions that Donohue and Levitt had claimed that they examined.
In particular, Foote and Goetz said that, despite their claims that they had done so, the 2001 Donohue and
Levitt study failed to control for influences that varied within a state from year to year (such as the effect
of crack-cocaine). After making these corrections, Foot and Goetz interpreted their results as evidence
that crime is unrelated to abortions.
Mueller, on the other hand, suggests that economic fatherhood is a prime reason against violent crime;
the reasoning being that supporting a child makes a man much less likely to commit a violent crime.
Economic fatherhood, as defined by Mueller, demonstrates a strong correlation with both crime and with
abortion.
http://en.wikipedia.org/wiki/Legalized_abortion_and_crime_effect
SUMMARY QUESTION: What do the various explanations for the decrease in crime rate suggest
about the nature of / difficulties with explanations in the social sciences?
> The following are examples of data which have been found to be closely correlated.
Do you think there is a genuine causal relationship? Why / why not? What might be other possible
explanations?
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



The number of cigarettes smoked is well correlated with poor school grades.
Cancers are increasingly frequent in Switzerland were they drink a lot of milk, but relatively
low in Sri Lanka were very little milk is consumed.
The distance you run is well correlated with the time you spend running.
A reasonable correlation has been found between higher IQs and longevity.
‘Study finds elder siblings are brighter’ INDEPENDENT therefore birth order determines
intelligence.
‘Girls perform better in single sex schools’ INDEPENDENT therefore single sex schools are
better for girls.