race crime
Abstract
This study explores the effect of various factors on the crime rate in the US. The model is estimated using the OLS procedure and a cross-sectional data set across the fifty states in 2000. The four variables that are found to have significant coefficients are police expenditures per crime in 1999, unemployment rate, per capita income, and the percentage of people living in poverty. Specifically, for every dollar increase per crime in 1999, the crime rate is found to decline by 260 crimes per 100,000 population. When the unemployment rate increases by 1 percentage point the crime rate increases by 64,939 crimes per 100,000 population. For every 4 dollar increase in per capita income, the crime rate increases by about 1 crime per 100,000 population. For a one percentage point increase in the poverty rate, the crime rate goes up by about 100 crimes per 100,000 population.
I. Introduction
According to the U.S. Department of Justice, the overall crime rate in the United States in the year 2000 was 4,124 crimes per 100,000 persons living in the United States. The crime rate varies across individual states and could be more or less than the overall U.S. crime rate. This study determines the importance of different factors that affect the overall crime rate in the individual states. It is important for policy makers to know which factors affect the crime rate in the individual states to determine what type of policy changes can be made in order to lower the crime rate. Using a regression analysis, this study can answer the question of what factors affect the crime rate the most. By developing an equation based on different studies that have been conducted in the past, a regression analysis is performed on a data set from the year 2000. The data set is based on individual state information that is available to the public through the U.S. Department of Justice and the U.S. Census. Once the regression equation is estimated, the significance of
This study explores the effect of various factors on the crime rate in the US. The model is estimated using the OLS procedure and a cross-sectional data set across the fifty states in 2000. The four variables that are found to have significant coefficients are police expenditures per crime in 1999, unemployment rate, per capita income, and the percentage of people living in poverty. Specifically, for every dollar increase per crime in 1999, the crime rate is found to decline by 260 crimes per 100,000 population. When the unemployment rate increases by 1 percentage point the crime rate increases by 64,939 crimes per 100,000 population. For every 4 dollar increase in per capita income, the crime rate increases by about 1 crime per 100,000 population. For a one percentage point increase in the poverty rate, the crime rate goes up by about 100 crimes per 100,000 population.
I. Introduction
According to the U.S. Department of Justice, the overall crime rate in the United States in the year 2000 was 4,124 crimes per 100,000 persons living in the United States. The crime rate varies across individual states and could be more or less than the overall U.S. crime rate. This study determines the importance of different factors that affect the overall crime rate in the individual states. It is important for policy makers to know which factors affect the crime rate in the individual states to determine what type of policy changes can be made in order to lower the crime rate. Using a regression analysis, this study can answer the question of what factors affect the crime rate the most. By developing an equation based on different studies that have been conducted in the past, a regression analysis is performed on a data set from the year 2000. The data set is based on individual state information that is available to the public through the U.S. Department of Justice and the U.S. Census. Once the regression equation is estimated, the significance of
Cited: Allison, John P. "Economic Factors and the Rate of Crime." Land Economics 48 (1972): 193-96. JSTOR. 9 Feb. 2009 . Becker, Gary S. "Crime and Punishment: An Economic Approach." The Journal of Political Economy 76 (1968): 169-217. Blumstein, Alfred. "Crime Modeling." Operations Research 50 (2002): 16-24. JSTOR. 9 Feb. 2009 . Halcoussis, Dennis. Understanding Econometrics with Economic Applications. New York: South-Western College Pub, 2004. Levitt, Steve D. "The Economics of Crime and the Criminal Justice System." National Bureau of Economic Research. 9 Feb. 2009 . Machin, Stephen, and Costas Meghir. "Crime and Economic Incentives." The Journal of Human Resources 39 (2004): 958-79. JSTOR. 9 Feb. 2009 . Merlo, Antonio. "Income Distribution, Police Expenditures, and Crime: A Political Economy Perspective." Journal of European Economic Association 1 (2003): 450-58. JSTOR. 9 Feb. 2009 .