The aim of this investigation was to determine

The aim of this investigation was to determine if there
is a correlation between total recorded crime rates and unemployment rates from
1981 until 2016 in England and Wales.  It was found out that there is a moderate
negative correlation by observing the data plots on a graph, which was further
proved by the Pearson’s Correlation Coefficient. Through the simple linear
regression, the production of an equation for the line of best fit was possible
and identified as predicting future
values if a change in the unemployment rate occurs.

 

This
conclusion is contrary to the expected results, believing that a rise in
unemployment will cause an increase in the crime rate. This may be surprising
as a lot of people connect those two together and think that one might
influence the other. There is the common idea that people that are unemployed
have a higher chance of committing crimes, as they have more free time, certain
needs and possibly a higher motivation.

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Looking
at Britt’s hypothesis again this would mean that the motivational perspective
and the resulting positive correlation cannot be proven by this investigation.
This might conclude that his other hypothesis of “less suitable victims can be
applicable. As this reduction in possibilities only occurs during a period of
economic downturn we have to take a closer look at the years following the 2008
financial crisis. As the data shows the recession is followed by an expected
increase in unemployment (5.7 to 7.6), and a decrease in total reported crime
rates (4.703 to 4.338). This negative correlation would support the theory of
less potential victims due to a decrease in property during this significant
time period.

 

However,
one could argue that there is no direct causal relationship and the values are
driven by a third factor. Although unemployment may have a direct effect on
economic related crimes, other crimes may have multiple different causations
such as mental health, upbringing and social circumstances. Therefore, the
crime rate has to be separated into different types of crime. As the main
motivation for unemployment related crimes is to maintain certain living
standards, this investigation should only focus on property crime including
offences such as burglary and auto theft, having a direct economic effect and
not violent crimes such as murder or rape.

 

Whilst
concluding the correlation of two variables, one also has to take a closer look
at them and the sources they come from. One big aspect which is important for
the evaluation of this issue is the variety of definitions for crimes. Everyone
can have a different one. Some would already report an insult, where others
draw the line at a robbery or burglary. As a result, this could also influence
the numbers of reports. Maybe in a year with a higher crime rate, this is only
due to a heightened willingness to report, rather than the factors included,
such as unemployment. This could also be closely linked to an expansion in the
activity of prosecution, where more cases are officially recorded and
registered. In this investigation one has to remember and clearly distinguish,
that these numbers only include the reported ones and not all committed
felonies.

 

Also
the unemployment rate is subjective as there are multiple types of
unemployment. Additionally, it is difficult to measure it, as some part-time
workers would like to be permanent, some are on zero hours’ contracts or have
higher skills than required in their current job. These are defined as
underemployed and would not be counted as unemployed. Using the Claimant Count
as a measurement can also be hard as not all people classified as unemployed
can claim benefits and are therefore not included. An example for this could be
someone who is looking for work alongside full-time study.

 

Therefore,
it could be stated that an observable correlation or association between two
variables is not the same as an alliance with regards to the content.
Therefore, before drawing conclusion, you have to qualify and relativize your
results with certain important factors such as the definition or source.

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