Determining what factors have an impact on the burglary rate in the United States Team 7 : Adam Fletcher, Branko Djapic, Ivan Montiel, Chayaporn Lertarattanapaiboon, Jared Smith, Carson Marries

Introduction What? Our study is to determine which factors have an impact on the burglary rate in the US. Why? Burglary is one of major crimes in the society. It leads to many social problems such as murder and rape. It leads to inefficient and ineffective economy. This test would help us to determine what factors could explain the burglary variable.

Introduction How? Figure out what could be possible factors. Income distribution, Unemployment rate, Number of Illegal immigrants. Immigration rates (Removals) : INS Immigration and Naturalization Service -Department of Justice Labor rates (Unemployment) : Bureau of Labor Statistics Income per capita : Burglary rates : FBI database

Executive Summary OBJECTIVE : test which factors have an impact on the annual number of burglaries in the United States (based on the data from ) Data Type : Interval Dependent Variable : Number of burglaries per 100,000 people per year. Independent variables : - unemployment rate - lowest income people (% of aggregate income earned by the lowest fifth of the population), - removals (number of immigrants' deportations, exclusions and removals).

Number of Burglaries/100,000 People ( )

Number of Immigrants’ Removal ( )

Unemployment Rate and Percentage of Income Earned by the Poorest Population

Descriptive statistics (Eviews) BURGLERIES REMOVALS LOWINCOME(%) UNEMPLOYMENT(%) Mean Median Maximum Minimum Std. Dev Skewness Kurtosis Jarque-Bera Probability Observations

Correlation matrix BURGLARIES REMOVALS LOWINCOME UNEMPLOYMENT BURGLARIES REMOVALS LOWINCOME UNEMPLOYMENT

Hypothesis Testing Ho: The burglary rate is not dependent on the unemployment rate, deportations, and lowest income people ( b 1,b 2, b 3 =0) H1: The burglary rate is dependent on unemployment rate, deportations, and lowest income people (neither b 1,b 2,nor b 3 =0) The model was developed with multiple regression consisting of the three independent variables with respect to their relationship with burglary. Burglaries = c + Unemployment * b 1 +Lowincome*b 2 + Removals* b 3 + e

LS // Dependent Variable is BURGLERIES Date: 11/25/02 Time: 10:17 Sample(adjusted): Included observations: 25 after adjusting endpoints Variable Coefficient Std. Error t-Statistic Prob. UNEMPLOYMENT LOWINCOME *** REMOVALS *** C R-squared Mean dependent var Adjusted R-square S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic)

Results of Least Squares regression Burgleries = Unemployment Lowincome Removals The overall model is significant with F-Stat of The proportion of robberies that can be explained by the independent variables was calculated to be approximately 87 percent. (R 2 = 87%) The t-stat indicate that Lowincome and removals are significant, but not the unemployment rate. Low income variable is positive significant (the lower income the poorest people gets, the less burglaries). Removals variable negative significant (the more deportations the less robberies). Unemployment rate is not significant: people who commit crimes might not be registered as unemployed.

LS // Dependent Variable is BURGLERIES Date: 12/04/02 Time: 16:33 Sample(adjusted): Included observations: 25 after adjusting endpoints VariableCoefficient Std. Error t-StatisticProb. LOWINCOME *** UNEMPLOYMENT LOGREMOVALS *** C R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic)

Conclusions Unemployment rate does not explain burglaries rate. A better measure could be labor participation rate because most criminals might not applying for jobs but simply leave the labor force. Although the people who earn less income are getting poorer overtime, the burglary rate doesn’t increase as we expected it would. (We had the opposite result!) Deportations have a negative impact on burglaries. The more people deported the less burglaries.