A relationship between income inequality and crime, time series

A great deal of criminological and economic
research investigate the relationship between income inequality and economic
growth following Becker’ study (1968). As a variety of social phenomena, lack
of resources or the unequal distribution of the resources can be driven to
society the crime or vice versa (i.e. Brush, 2007). The relationship between income
inequality and economic growth and some key social variables, political
conflict, gender, education, health, and crime are explored (Jiang et al., 2012). Most of
studies in the literature stated the hypothesis that economic incentives to
commit crimes are higher in areas with greater inequality (Ehrlich, 1973). Some
studies show that various factors are responsible for promoting crime in the
world. such as Lee (2002). Kelly (2000) found that the robbery, assault and
overall violent crime are strongly aggravated by income inequality.

 

Some of the income and crime studies
investigates the income inequality and crime relationship in a macro
perspective such as Gillani et al. (2009). The author used a time series data
set to examine the crime and other factor relationship such as unemployment and
poverty. For this purpose they applied a Granger causality test on the 1975 to
2007 data set. Results of their study indicated that there is a clear
relationship between  unemployment,
poverty and crime. Similarly Gilliani et al (2009) paper, Altindag (2009)
examine how the unemployment affects on crime using country level data set. To
examination the relationship, the author applied  Ordinary Least Square (OLS) and 2 stage Least
Square (2SLS) techniques on country level data for European countries. The
results showed that unemployment has a positive influence on property of
crimes. Also, the author point out that the 2SLS estimates are larger than OLS.
Brush (2007) is another study used the country level data of the United States to
estimate income inequality and crime relationship applying a cross sectional
and also a time series analysis. While cross sectional analysis find a positive
relationship between income inequality and crime, time series analysis results
show a negative coefficient for crime variable.

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 On the other hands of these macro studies
there are some research in the literature focused in the micro perspective
while searching the income and crime relationship. For example, Omotor (2012)
uses micro level data set to examine the relationship for Nigeria. The author
used OLS and the results indicate a significant effect of income on crime.
Another finding of this study represent that crimes are triggered due to the
inefficient performance of law enforcement in Nigeria.

 

This study examines whether or not an
increase crime level can cause a decrease income level (or opposite) for this
purpose in the Unites States. It specifically focuses before and after Great
Recession period because fundamentally, recessions impact on economical
variables in a negative way, such as, economic growth, unemployment rate and
income inequality level. According to National Bureau of Economic Research,
unemployment rate has risen 5% in the first quarter after the Great Recession
period. The An increase of the unemployment rate may trigger to crime level,
for instance Heinemann, and Verner
(2006) stated that unemployment is a factor motivating crime and homicidal
especially in urban areas. Therefore, it is important to understand how
the recession period impacted on the income and crime relationship. This paper
is organized as follows: the detailed information about the data set and method
is given in the Experimental part in section 2. Section 3 presents the
analytical results. Section 4 provides the concluding comments.