The question of establishing a relationship between unemployment and crime rate has attracted a significant interest over the years. Researchers have implemented a study to investigate whether any relationship exists. The solution to the question has made many scientists think that it is deterioration of morals in this century that causes substantial increase in crime. Perhaps, moral degradation has led to a massive growth in crime rate; this is just one of the factors. However, according to the late research study, it is undeniably true that unemployment is involved in increasing the crime rate today. Using the United States data from the World Bank source, from the year 1980-2014 (“United States Crime Rates 1960 – 2014”, 2016) the inferential conclusions, findings, and recommendationswill be presented in the paper (McDowall, 2005).
Most people think that perhaps crime is a state of moral degradation in the current century. However, if they stop being single-minded, they will lose their jobs and experience the desperation of paying their bills and providing even the very basic needs (food, shelter, and medical care). Moreover, they will realize that unemployment can also be the cause of crime.
Purpose of the Study
The purpose of the study will be to examine if there is a relation between crime rate and unemployment. In addition, the research will help to answer the questions whether there is a strong or weak relationship if it actually exists.
To examine the problem statement and determine whether unemployment affects crime rate directly, the following research questions of the case studywill be used:
- RQ 1: What are the major crimes that are happening today?
- RQ 2: Is crime increasing or reducing over the years?
- RQ 3: Is unemployment rising or lowering the over years?
- RQ4: What is the relationship between unemployment and crime?
- RQ5: Does wage pay affect crime?
Weinberg (1979) conducted a research that studied the relationship between the rate of crime and unemployment. He confirmed that reduced wage pay indeed results in the increase of crime rate. Evidently, the long-term trend in earnings was the dominant factor in crime during this period (“The link between crime and unemployment rate fluctuations: An analysis at the county, state, and national levels”, 2016).
In turn, Becker (1968), Stigler (1970) and Ehrlich (1973) discovered a model called Ehrlich's model, which states that people could divide themselves into risky illegal and legal activists. In their model, they found a structure suggesting that when legal income opportunities become less available, then crime increases. Therefore, it becomes clear that enhanced unemployment could lead to a considerable increase in crime. In the research implemented in the year 1987, they introduced the findings that actually supported the theory stating that there is a positive relationship between crime and increased unemployment.
Gottfredson (1978), Hirschi (1990) Wilson, and Herrenstein (1985) were criminologists who investigated the issue and presented different theories. Generally, they all concluded that unemployment is a deniable cause of crime. Moreover, they confirmed that even though there is an undeniable relationship between unemployment and rate of crime,many arrested peopleare more likely to be unemployed.
Furthermore, Cantor and Land (1985) again affirmed that unemployment has a positive effect on crime. They choose to contribute to the fact that unemployment crime findings in the United States are handily influenced by poor wage rates, which leads to many ventures into illegal activities. In spite of the limited evidence, they suggested that the long-term issue was hypothetical. However, through research findings now one can confirm the study results. It is paradoxical that in some countries, for example, in South Africa, poverty reduces criminal levels among teenagers. Therefore, all the researchers believe that there is an empirical link between poverty and crime.
The representative data acquired from the World Bank to produce the inferential statistics serves as a valuable tool today to aid in making correct statistical inference.
The data of USA Unemployment Rate and Crime Rate
The statistical Method of Analysis and Analysis of Data
These are the statistical methods in place for the discussion of the data. ANOVA will first help determine whether the study in place is significant, whereas the correlation will contribute to ascertaining the relationship of the data and multiple regression.
The method establishes the relationship between two variables. The possible outcomes include strong, perfect or weak correlation of data. Using R-statistical software of data analysis it is presented here (“The correlation method for computer-aided statistical analysis”,1972).
In the result, the correlation coefficient between unemployment and rate of theft is 0.1548428, therefore, unemployment and theft are low positively correlated. Since we are examining the relationship between unemployment and crime, theft is the result of one of these crimes. Hence, we make an inference that a relation between unemployment and theft indeed exists. The data has a non-linear relationship as read from the graph; however, a linear regression model can be applied.
When the rate of unemployment increases by one unit, the rate of theft grows by 0.007302 units. Evidently, there is a relationship between unemployment and the rate of theft.
When we are investigating the connection between unemployment and rate of theft, we have the researchers’ hypothesis and the null hypothesis. When p-value is greater than 0.05, then we reject the null hypothesis and accept the researchers’ hypothesis. In our case, we accept the hypothesis that unemployment affects the rate of theft("ANOVA: Repeated Measures," 1993).
The analysis of the data has clearly shown that there is a relationship between the rate of unemployment and rate of theft. Clearly, when the rate of unemployment increases, we have the rate of theft (crime) growing, which was proved by the regression test. The researchers’ hypothesis regardeddiscovering whether unemployment affects the rate of offence. Consequently, our analysis has made us accept the hypothesis. The statistical tests performed included:
We had the correlation coefficient of 0.1548. Statistically, we say that the unemployment impactsthe crime rate since it is low positively correlated.
- Linear regression
From the linear regression test, it is clear that when unemployment increases then the rate of the offence also enhances. The data we have used preciselyshows that if we increase unemployment by one unit, the rate of theft (crime) growsby 0.007302 units.
- Anova test
Anova test helps the researcher to confirm the existence of a relationship between unemployment and crime rate. We accepted the researchers’ hypothesis and rejected the null hypothesis. In the result, there is a relationship between unemployment and rate of the offence.
From the research findings, it is obvious that our research problem is accepted, which means that there is a relationship between unemployment and crime rate. Therefore, it is recommended to encourage our youths to be creative and even when oneis not employed, motivate one todo self-employment. Here are some of the recommendations as by the findings:
- Involve youths to participate in extracurricular activities to make sure that they are busy and avoid bad company.
- Increase awareness to confirm people understand the implications of being unemployed.
- Encourage private investors to invest locally in such a way increasing job opportunities.
- Build an environment that favors the start of new business.
In conlusion, indeed, there is a clear relation between the unemployment and rate of crime by the statistical research findings.In fact, if there is higher rate of unemployment, the rate of crime in the country rises.