Mar 25, 2020 in Economics

Socio-Economic Factors and Crime Rates in the USA

Abstract

The impact of crime in society is enormous. In essence, crime not only increases financial expenditure of the society in apprehending and punishing criminals or in repairing the damage done during the criminal activities but also in guaranteeing happiness and personal safety for the community. As one of the tasks of the government is to protect its citizens, the key objective of any governing body is to craft vital social policies to mitigate effects of crime as much as possible. To achieve this end, it is pivotal to identify the determinants of crime in the society. Despite the original thought that criminal intent is mainly a personal problem sparked by insanity or weak morals, many theories have focused on ecological causes. The theories indicate that people commit crime through environmental stimuli and not internal urges. Therefore, the most effective way of reducing such illegal actions is to establish control over external influences. This article analyzes how socio-economic variables are related to crime. They include; poverty, population density, income inequality, religious participation, and gun ownership. The study relies on the data from 1000 respondents in US regardless of their state to investigate the connection between crime and variables. The target population fills a structured questionnaire to gather primary data on their experience with crime in the US. The literature review is based on books and journals on crimes across America. After statistical data analysis, the study found that property crimes occur more often than violent crimes in the US. It is also clear that age, residential stability, and police expenditures register a big impact on property crimes and inequality cannot be used as a predictor for crime. Even though poverty and inequality are seen as the ills of the society for many reasons, this study proves that their impact on crime is lesser than the influence of social factors. The findings present vital information that establishes a platform for future research. The study concludes that the government should create structures that would anticipate crime in the future.

 

Socio-Economic Factors and Crime Rates in the USA

Findings

The findings were based on the reports provided by 1000 law enforcement agencies that filled the questionnaires. Certainly, each of the respondents has experienced a criminal activity. In fact, crime rate is a dependent variable while various social economic factors such as inequality, unemployment, population density, total population, age bracket, female to male ratio, gun ownership, religious participation, poverty, and race are independent variables. All the factors captured in the independent variable feature in the questionnaire were presented to respondents.

 

 

Mean

Median

Minimum

Maximum

Std. Dev.

Violent Crime Rate

2.89

2.28

0

11.10

1.760

Property Crime Rate

22.40

19.80

0

64.01

12.44

Income Gini

0.336

0.39

0.2651

0.45510

0.0217

Total Pop.

79836

1635

59

3300500

282840

Pop. Density

83.15

20.55

0.10

2521.50

254.51

Unemployment

3.89

4.22

1.75

15.70

1.41

Race

28.86

29.87

3.80

88.00

19.827

Poverty

16.75

15.38

0

40.78

5.54

Family Instability

3.33

3.145

0

12.27

1.037

Residential Stability

46.37

47.00

21.10

61.70

6.134

Police Ex. Per Capita

86.10

70.81

0

1227.30

137.9

Aged 15 - 24

12.74

12.623

4.86

33.65

2.02

Female-Male Ratio

34.11

42.53

24.15

44.16

3.686

High School Grad.

68.21

70.30

28.60

88.70

7.8077

Gun Owners

1.40

2.23

0.38

6.42

1.1422

Religious Participation

56.21

59.27

7.88

100

15.34

Table 1. Results

The percentage of population and of non-white residents above 25 years old who graduated from high school showed a negative correlation. It was discovered that the correlation between family instability and poverty is high while there is also a strong correlation between high school graduates and poverty. Notably, there is a correlation between race and poverty and family instability while at the same time there is a negative correlation between family instability, high school graduates, and unemployment. Additionally, inequality is less correlated to property and violent crime.

Distributions of Selected Variables

In the Figure 1 below, one can observe the relation between dependent variables, property and violent crimes, and independent variables, inequality and poverty. Poverty appears as a significant predictor of crime since its highest levels represent a large percentage of target population for whom criminal activities present a weak opportunity to get costs by engaging themselves in illegal activity. Inequality, in its turn, becomes a vital predictor of crimes, because it represents a possible payoff of criminal activities prohibited by law.

 

Figure 1. Crimes.

The above histogram shows that majority of counties in the US experience violent crime at the rate of 3 for a population of 1000. Responses from those who filled questionnaire indicate that only in 28 counties of the same state people experience violent crimes at the rate of 5 per 1000 population. 

 

Figure 2. 

The Figure 2 indicates that in the United Sates of American property crimes happen more often than violent crimes. In the state where the study was conducted, about half of the population has experienced property crimes at the rate of 1 per population of 30 people or less. 

About half of all Texas counties have property crime rates of 20 per 1000 population or less.

 

Figure 3.

The Figure 3 depicts the frequency of poverty levels within the target population. Most areas register poverty rates less than 20% of their population. Only one area indicated on the questionnaire by a respondent has showed a poverty rate exceeding 50%.

Crime Rates per population of 600

 

Coefficient

Constant

-39.8443

Unemployment

0.9309

Pop. Density

0.0115

Poverty

-0.7640

Police Ex. Per Capita

0.0195

Female-Male Ratio

0.9848

Family Instability

2.9587

Residential Stability

-0.6424

Race

0.1282

Aged 15 - 24

0.7770

Income Gini

34.4412

Religious Participation

-0.0506

Gun Owners

0.2223

High School Grad

0.2382

R2 =.5327

Violent Crime Rates per population of 600

Coefficient

Constant

-2.6526

Unemployment

0.0789

Pop. Density

0.0021

High School Grad

-0.0077

Aged 15 - 24

0.1044

Gun Owners

0.0855

Family Instability

0.4406

Residential Stability

-0.0553

Police Ex. Per Capita

-0.0003

Race

0.0091

Female-Male Ratio

0.1082

Income Gini

2.9073

Poverty

-0.1094

Religious Participation

-0.0009

R2 =.3993

From the above finding it is clear that violent crimes and property crimes are influenced by similar factors namely; poverty, population density, male to female ratio and family instability, although the coefficients may vary. All these factors that affect crime have one sign for both violent and property crimes with different sizes of coefficients in some cases such as family instability, foe example. It is also evident that police expenditures, age, residential stability have a big impact on property crimes despite there are no significant factors influencing violent crimes. In fact, the findings provide different indicators for police expenditures: they appeared to have a positive impact on property crimes, but their impact on violent crimes is insignificant. Most of the coefficients seem to shift in the opposite directions. For example, female percentage has a positive coefficient while poverty is represented by a negative one. However, inequality shows zero significance for property and violent crimes. Nevertheless, not all dependent variables are exogenous. Gun ownership and police expenditures, however, are endogenous and entirely depend on crime rates.

Discussion

Inequality is not a factor for predicting a total crime. It is not significant in property crimes either, even though some studies consider it as an important factor in violent crimes. It appears to align with a strain theory and not an economic theory despite the fact that some violent crimes may be committed with pecuniary intents such as armed robbery. Further, poverty has lacked the consistency in its sufficiency to predict crime, because in almost every case it had a negative coefficient. It is an unexpected outcome considering a common assumption that crime rate is high in poverty stricken areas. The possible explanation is that there is a gap between individuals who are capable of generating enough income to support themselves and those whose poverty level qualifies them for different welfare programs. As more Americans fall below the set income limit to qualify for state programs, they can sustain their lives through such avenues making crime not to look like an attractive option. Three factors that meet the expectations of the researchers are family instability, population density, and female to male ratio. The outcome shows that family instability significantly impacts both types of crime that clearly validate a social disorganization theory. The role of this variable is well known and is an important independent variable. Thus, the recurring significance of the percentage of people living in the same residence for at least five years tells volumes at the role of community as a crime deterrent.

The importance of the ration of female to male is not surprising, but for the reason that it is not always positive, the contrast of the likely outcome. It contradicts the findings of Li, Yi, Edlund, and Zhang that an increase in the number of males can contribute to 70% increase in crime rate in China under the government policy of one child. From the data collected, it seems that a change in economic circumstance would have a weak impact on crimes unlike what the policymakers might expect. While inequality and poverty are regarded as the ills of the society for different reasons, the data shows that their impact on crime is lesser than from other social factors. Rather, it appears that focus on social issues is the most effective way of reducing crime. Poverty, which seemed to be consequential in certain specifications, has a high correlation to family stability, though this study hardly shows any causal links. For the purpose of authenticating these results, longitudinal tests are the most appropriate. Also, getting the individual-level data might generate more precise measures of inequality and poverty. Considering the number of individuals whose earnings exceed the income limit for various social welfare programs as a probable factor that causes crime might reveal the determinants of it.

SWOT Analysis

Strengths

Time of research: this research is timely in a period in the United States when the dynamics behind criminal activities continues to change. For instance, according to FBI, the number of violent crimes happening in the US increased by 3.9% in 2015. There was also a drop of 2.6% in property crimes which marks the 13th year of decline in collective estimates of such offenses. In 2016, the number of murders continues to rise and currently stands at 10.5% in big cities. In 2015, the number was 14.5%. Therefore, this research addressing current issues and the data received can be used by the law enforcement in efforts to deter the crimes in communities across the country. Additionally, the researchers enjoyed a sufficient time allowance to complete the study. Since they were not pressurized to meet any deadline, they were able to focus on accuracy and in-depth data analysis

Reliable Data: The respondents were people from law enforcement agencies who have experienced crimes. Thus, they are the most suitable group to provide this kind of data for the research. Also, the instruments for collecting data allowed the anonymity of the respondents. Thus, they could confidently provide all the information with boldness. Thus, this measure validates the data collected and ensures accuracy.

Experienced Researchers: The study was done by individuals with vast experience and statistical knowledge. This knowledge helped them in in-depth data analysis and overcoming various challenges while dealing with the target population and following important right procedure in acquiring permits and making ethical considerations.

Weakness

Sample Size: Considering the goal of the research is to understand the factors affecting crime rate in the United States of America, 1000 may be a small sample size to represent the US population of more than 200 million people. Widening the sample increases the impact of legislative and demographic differences across the US.

Possible Bias and possible inaccuracy of data: Use of random sampling could lead to inclusion of individuals with less knowledge of crime in the US. Probability methods of sampling increase the confidence in data provided by experienced and knowledgeable people who deal with crime. Also, use of questionnaire increases a possibility of bias, because some respondents may provide false information, especially, details on economic situation, for instance, level of income.

Reliance on external sources of information: This research compares its findings to existing data on this topic such as FBI criminal records. Any contradiction creates data on the authenticity of information provided.

Opportunities

Further Studies: Some findings did not meet the expectations of the researchers as they contradicted the ongoing trends. There are several research institutions that can sponsor a further research to account for various findings with an absolute certainty. These organizations provide the funding, resources and personnel which are vital in conducting a more detail research.

Detailed data analysis: The findings can be exposed to sophisticated statistical software for further analysis. This would reveal some details that might have not featured in the previous analysis. Use of various software and equipment in the research would make the data more comprehensive comparing to the first research.

Threats: Existence of Superior Research: Socio-economic factors and crime rate in the US is a contemporary issue. Thus, it has triggered many research studies from corporations and institutions with superior resources to collect quality and quantity data. This lowers the confidence levels in information provided in this research. In other words, this research may not be classified as an important source of data on this topic due to existence of research from credible authors and institutions. It is likely that this research would not be seriously considered for use by the government because it has been done by a college student.

Conclusion

While there are socio-economic factors that impact crime rates differently, it is easy to predict that there would be a dramatic increase in crime rate during the next decade. This prediction is leveraged by an increase in sophistication in the way of running society, globalization, and organization of crime. Thus, the impact is likely to be severe despite the possible reduction in factors such as family instability, poverty and inequality. Even if the authorities intervene to minimize the effect of these factors, the growing use of technology in aiding criminal activities will be the key factor in increasing the impact. In particular, telecommunication technology offers the offenders a greater access to important services and information at both commercial and household levels. Police expenditure is the economic factor that can impact crime rate caused by use of technology. One of the biggest lessons from this study is that the law enforcement agencies need to emphasize on anticipating and response to crime cycles in the future. To achieve this goal, it is imperative to develop and implement more integrated and rigorous research methods capable of accurately predicting the scope and more significantly the nature and cycles of future crimes. Statistical modeling and crime trend analysis must be merged with a qualitative research for a quick identification of potential new targets for a criminal activity and the ways criminality would evolve and have an impact on the society. While impact assessment and accuracy of predicting crimes will be continually scrutinized, a further research on this subject can be useful for programs and policies. Future trends in crime and possible impact on America should be anticipated for the purpose of developing the programs and policies that would minimize a possible negative impact on society. In other words, the utility of this program is predicting alternative scenarios and factors that catalyze crime and address them in present and not in the future.

Recommendations

  • Improvement of child nurturance: This paradigm asserts that there is a possibility of mitigating the concentration of criminality by improving experiences at early stages of life in a population and channeling a proper development of children and adolescents. Thus, the government needs to invest in nurturing strategies such as child care, education, and health care programs that would address the criminality roots at early stages in life.
  • The government and corporations should establish a dedicated funding stream meant to provide for a holistic research program that searches and maps the trends in crime, forecasts the future crime patterns and rates and estimates the cost of crime presently and in the future.
  • The US federal government should ratify the mechanisms for a continual assessment of a wider impact of emerging technologies on crime as well as criminal justice system. These mechanisms should combine the programs that can tackle crime at different stages of products’ life cycle and work together with retailers, manufacturers and customers in to develop secure products. This kind of research should provide concrete measures to reduce the use of technology to promote criminal activities. It also important to promote such initiatives internationally.
  • The US federal government should assemble a multi-sectoral group charged with coordinating and conducting research on crime. The function of this group should be coordinating a systemic research that accurately anticipate the scope and nature of crime in the next two or three decades and create policies and program to be executed in different states presently and in the future to mitigate the impact of future trends in crimes. The group should also strive to support current research programs to boost horizon scanning and prepare for future threats. This group should include representatives from academia, government and private organizations. Non-governmental organizations and Criminal justice agencies should be allowed to steer this working group. Statisticians should be drawn from relevant disciplines such as demographics and economics. The consulting community and academic should also be multidisciplinary to combine efforts from criminologists with expertise in violence, youth, organized crime, property crime and economic crimes, econometricians and economists. Those participating from private organizations should include individuals from different industries such as internet industry, telecommunication industry, insurance, forensic accountants and private security.
  • Allow religious leaders to participate in crime deterrence efforts. As the findings revealed, religious participation lowers chances of committing criminal offence. Religious leaders can help in counseling families and nurturing the character of children in families.
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