Introduction 4 CHAPTER I: LITERATURE REVIEW 5 1. Overview of The Crime Index 5 2. Factors affecting The Crime Index 5 3. Research overview 7 3.1. Theories related to factors affecting crime rate 7 3.2. Relevant published research 8 CHAPTER II: METHODOLOGY, MODEL SPECIFICATION AND DATA 10 1. Methodology 10 2. Model specification 10 3. Variables, measure, and data source 11 CHAPTER III: ESTIMATION, MODEL TESTING AND STATISTICAL INFERENCE 12 1. Statistical description of variables 12 1.1. Summary of variables 12 1.2. Correlation matrix of variables 13 2. Quantitative analysis 14 2.1. Selecting the proper model 14 2.2. Testing violations 15 2.3. Fixing and finalizing the model 17 CHAPTER IV: RECOMMENDATIONS AND SOLUTIONS 19 CHAPTER V: CONCLUSION 19 References 21 Appendix 22 Introduction The Crime Index is one of the most effective indexes used in determining the stability of a nation. It is used to describe the overall level of crime in a given country in a period of time. The index indicates that a low Crime Index would result in a low overall level of crime, a stable economy, a solid political foundation and a high development level while a high Crime Index would result in a high overall level of crime, an unstable economy, a weakened political regime and a low development level.
https://tailieuluatkinhte.com/ FOREIGN TRADE UNIVERSITY FACULTY OF INTERNATIONAL ECONOMICS -*** ECONOMETRICS REPORT factors affecting crime index in 13 european countries from 2012 to 2021 Group: Class: KTEE318 Instructor: MS DINH THANH BINH Hanoi, June 2023 INDIVIDUAL ASSESSMENT TABLE OF CONTENTS Introduction .4 CHAPTER I: LITERATURE REVIEW Overview of The Crime Index Factors affecting The Crime Index Research overview 3.1 Theories related to factors affecting crime rate 3.2 Relevant published research CHAPTER II: METHODOLOGY, MODEL SPECIFICATION AND DATA 10 Methodology 10 Model specification 10 Variables, measure, and data source 11 CHAPTER III: ESTIMATION, MODEL TESTING AND STATISTICAL INFERENCE 12 Statistical description of variables .12 1.1 Summary of variables 12 1.2 Correlation matrix of variables .13 Quantitative analysis .14 2.1 Selecting the proper model 14 2.2 Testing violations 15 2.3 Fixing and finalizing the model 17 CHAPTER IV: RECOMMENDATIONS AND SOLUTIONS 19 CHAPTER V: CONCLUSION 19 References 21 Appendix 22 Introduction The Crime Index is one of the most effective indexes used in determining the stability of a nation It is used to describe the overall level of crime in a given country in a period of time The index indicates that a low Crime Index would result in a low overall level of crime, a stable economy, a solid political foundation and a high development level while a high Crime Index would result in a high overall level of crime, an unstable economy, a weakened political regime and a low development level. In order to have more insight about the crime index, our group chose the topic: ‘‘Factors affecting crime index in 13 European countries from 2012 to 2020’’ This paper uses theoretical basis and related studies to conduct linear regression models in order to analyze four factors affecting crime index in 13 European countries These factors include population density, Net National Income, GINI Index and years of education The purpose of this paper is to determine the relationship between dependent variables (crime index) and the independent variables (population density,Net National Income, GINI Index and years of education) and to propose recommendations to decrease the crime rate in 13 European countries The structure of this paper is organized as followed: Chapter 1: Literature review Chapter 2: Methodology, model specification and data Chapter 3: Estimation, model testing and statistical inference Chapter 4: Recommendations and solutions Chapter 5: Conclusion CHAPTER I: LITERATURE REVIEW Overview of The Crime Index The Crime Index is an estimation of the overall level of crime in a given city or country Crime levels lower than 20 are considered very low, between 20 and 40 as being low, between 40 and 60 as being moderate, between 60 and 80 as being high, and finally, crime levels higher than 80 as being very high Every year, the Federal Bureau of Investigation (FBI) compiles crime statistics from across the country and publishes the results The results of this data are known as the Crime Index or the National Uniform Crime Report The index provides a specific list of crimes that are measured each year and reported Factors affecting The Crime Index Population density Population density is a measurement of the number of people in an area It is calculated by dividing the number of people by the area, and is usually shown as the number of people per square kilometer Population density is an average number In simple terms, population density refers to the number of people living in an area per square kilometer or other unit of land area The formula of calculating population density is: Population Density = Number of People / Land Area Population density is believed to have a positive relationship with crime rate This mainly due to the chance that higher population density may increase the number of potential contacts between motivated offenders and attracted targets Net national income Net National Income (NNI) is defined as gross national income minus the depreciation of fixed capital assets (dwellings, buildings, machinery, transport equipment and physical infrastructure) through wear and tear and obsolescence The formula of calculating Net National Income is: NNI = Gross National Income - Depreciation of Fixed Capital Assets The net national income is expected to have a negative relationship with crime rate because the more wealth a nation has, the higher the living standard becomes The increased living standard will discourage potential crime activity thus decreasing the crime rate in that nation GINI index The Gini Index, also known as the Gini Coefficient, is a measure of statistical dispersion intended to represent the income inequality or the wealth inequality or the consumption inequality within a nation or a social group The Gini Index measures income distribution across a population and often serves as a gauge of economic inequality, measuring income distribution or, less commonly, wealth distribution among a population The coefficient ranges from (or 0%) to (or 100%), with representing perfect equality and representing perfect inequality The Gini Index is calculated using the Lorenz Curve, which plots the cumulative proportion of the population on the x-axis and the cumulative proportion of income on the y-axis The Gini Index is equal to the area between the Lorenz Curve and the line of perfect equality, divided by the total area under the line of perfect equality The formula for calculating the Gini Index is: G = (A / (A + B)) Where A is the area between the Lorenz Curve and the line of perfect equality, and B is the area under the Lorenz Curve The gap of inequality is proved to have positive effects on the crime rate A study conducted by The AAF found that income inequality is actually a better predictor of crime rates than poverty, with numerous studies showing that the greater the inequality, the more crime there will likely be in an area Years of education Number of years of education refers to the number of academic years a person completed in a formal program provided by elementary and secondary schools, universities, colleges or other formal post-secondary institutions Years of education are often negatively related to crime rate in general Education can influence the decision to commit crime significantly The higher the years of education, the lower the rate of crime This can be explained by two reasons First, the education years can influence the living standard and therefore higher education years discourages criminal activity Second, education affects the personality and the mindset of potential law-breakers and disincentivizes them from committing crime. Research overview 3.1 Theories related to factors affecting crime rate There are many theories that examine the factors that may affect crime rate in different countries, including Psychological theories, Social class theories, Criminology theories, and Socioeconomic factors theories Among them, Socioeconomic factors theories are the most relevant to our research paper Formalized by Nobel Laureate Gary Becker in 1968, the Economic theory of crime is a micro-theory that postulates that a welfare-maximizing individual optimally allocates resources according to relative returns, and links socioeconomic conditions to an individual’s relative returns to legal and illegal activity This theory suggests that criminals are rational decision-makers that commit crimes based on expected utility that is affected by their own economic conditions, Risktolerant, impatient and selfish people with a low level of education are more likely to commit crime than people who are highly educated, risk-averse, patient and selfless While Strain theory, following the work of Émile Durkheim, advanced by Robert King Merton (1938), Albert K Cohen (1955), Richard Cloward, Lloyd Ohlin (1960), Neil Smelser (1963), Robert Agnew (1992), Steven Messner, Richard Rosenfeld (1994) and Jie Zhang (2012), the theory states that society puts pressure on individuals to achieve socially accepted goals, including goals like attaining higher economic or class status, these goals often put more strain on individuals living in areas with high inequality 3.2 Relevant published research Research by Lance Lochner and Enrico Moretti (2004): The Effect of Education on Crime: Evidence from Prison Inmates, Arrests, and Self-Reports The paper uses individual-level data on incarceration from the Census and cohortlevel data on arrests by state from the FBI Uniform Crime Reports (UCR) to analyze the effects of schooling on crime and self-report data on criminal activity from the National Longitudinal Survey of Youth (NLSY) to verify that the estimated impacts measure changes in crime and not educational differences in the probability of arrest or incarceration conditional on crime By using the Ordinary Least Square and Instrumental Variable Estimates method, they were able to produce the conclusion that schooling significantly reduces criminal activity Specifically, a one-year increase in average education levels is estimated to reduce arrest rates by 11 percent and A 1-percent increase in the high school completion rate of all men ages 20–60 would save the United States as much as $1.4 billion per year in reduced costs from crime incurred by victims and society at large Research by Morgan Kelly (2000): Inequality and crime This research uses data on crime taken from the FBI Uniform Crime Reports for 1991, comprising violent crimes and property crimes, while inequality is measured by the estimated Gini coefficient The findings suggest that violent crime is strongly affected by inequality, measured either by income or education, with estimated elasticities above unity By contrast, inequality has little impact on property crime While most crimes are committed by the most disadvantaged members of society, these individuals face greater pressure and incentives to commit crimes in areas of high inequality Research by Mohamad Kassem, Amjad Ali, and Marc Audi (2019): Unemployment Rate, Population Density and Crime Rate in Punjab (Pakistan): An Empirical Analysis This study is based on data from 1981 to 2017, it examined the determinants of crimes in all thirty-five districts of Punjab, Pakistan; including unemployment, amount of remittances, industrialization, social infrastructure, and population density Using Augmented Dickey-Fuller (ADF) Test, the research findings suggest that when there is a percent increase in population density, there will be a 0.249320 percent increase in crime rate in the case of Punjab The impact of this determinant, alongside unemployment rate (0.142692 percent in crime rate per percent increase) is the most significant compared to the others, suggesting the strong correlation between population density and crime rate Research by Dullah Muloka, Mori Kogidb, Jaratin Lilyc, and Rozilee Asidd (2016): The Relationship between Crime and Economic Growth in Malaysia: Re-Examine Using Bound Test Approach The study examines the relationship between crime and economic growth in Malaysia for the period of 1980 to 2013 The ARDL bound test method was used to establish the long-run relationship as well as the direction of causation between variables Contrasting with the common belief that in good economic conditions, criminal activity should decrease, they found strong evidence that the impact of economic growth towards crime, in the long run, was positive and statistically significant In the short run, bidirectional causation between crime and economic growth was also found to be significant CHAPTER II: METHODOLOGY, SPECIFICATION AND DATA MODEL Methodology Based on our theoretical basis and related studies, we have devised the linear regression model to analyze data for the report The relationship between our dependent variable, Crime Index (crime), and four independent variables: population density (PD), average year of education (educ), adjusted net national income (NI), and Gini index (gini), was explored using data from 117 observations from 13 European countries from 20122020 from trustworthy statistical databases (Worldbank, Statista, Numbeo, Global Data Lab) The data collected was then organized by Microsoft Excel and analyzed by STATA 16 Method we used to derive the model: Theoretical basis, Statistical model, Mathematical model Model specification In order to analyze the influence of different factors on crime index, our group has chosen the following linear regression model: Population Regression model: Crime = 𝜷𝟎 + 𝜷1PD + 𝜷𝟐 educ + 𝜷𝟑 NI + 𝜷𝟒 gini + 𝒖i In which: 𝜷0: Constant parameter 𝜷j (j = 1,2,3,4): the regression coefficient of corresponding independent variables Ui: The population random error, representing other factors affecting crime index but are not mentioned in the model Variables, measure, and data source Unit Expected Data source sign Variable Meaning Crime Estimation of the overall level of o crime in a country Number PD Midyear population divided by People/km2 (+) land area Worldbank educ Mean years of schooling in each Year country (-) Global Data Lab NI Adjusted net national income Billion (current US$) US$ (-) Worldbank gini Gini index (+) Worldbank, Statista o 10 CHAPTER IV: RECOMMENDATIONS AND SOLUTIONS The increasing crime rate has become an issue to the world Even in developed parts of Europe, crime is still posing a serious threat to the development of the society and lives of people living in it That is why it is urgent for everyone to help reduce the crime rate For the government, the following measures should be taken to better maintain their security, order and to protect their citizens First and foremost is to provide education to all By creating and perfecting the existing education system and provide them to everyone, the government will raise the awareness of the public, make them know of the threat crime can cause to the society, thereby recognize that crime needs to be prevented, turning everyone into better citizens, which can help contribute valuable resources and labour to the country and to the world And in fact, European countries had started investing in education, with the introduction of Socrates programme I and II in 1995 and 2000 respectively, lifelong learning programme in 2007 and Erasmus+ programme in 2014 We can improve these by further investing in facilities, improving teaching skills among teachers, and adding more vocational training into the system, which would bring valuable skills and experience for their citizens. The second priority is to shorten the gap between rich/poor people In some parts of Europe, there is still an unequal income distribution between the rich and the poor, where most of the income and wealth focus on the rich, leaving the poor with little living conditions That can partly explain why even though there are countries with far higher net income, they still hold a high crime rate, which is shown in the model where adjusted net income is positively correlated with crime rate The government can improve this situation by improving and enforcing the tax system, and develop more infrastructure such as accommodations and hospitals for those with lower income Crime can only be lowered and eliminated with the contribution of both the government and the people And along with it, the quality of life can also increase 18 CHAPTER V: CONCLUSION Today, even in the developed part of Europe and the world in general, amidst the improvement in income, the quality of life, or culture, there still lies a serious problem which can hinder the development of society in the increased crime rate This research paper aims to analyse the statistical relationship between the crime rate in 15 countries in Europe with the years of education, population density, the countries’ net income and the income distribution among those countries With the help of STATA, we have conducted the results as followed: the years of education and GINI index have the expected signs of correlation with crime rate Much to our surprise, however, are the adjusted net income variable, which correlated positively with crime index, and population density with negative correlation This means the countries with better economies or less-dense populations might not have the lowest crime rate Our research might have some errors in focusing on only variables in this analysis, but to some extent, the results are reliable and can prove useful for further studies For further development to the research, it may be feasible to use more observations in the database, preferably expand the data to more years, increase the independent variables which can be used, or test out other types of model to define the impacts better 19 References Gary S Becker; Crime and punishment: An economic approach, JSTOR Available at: https://www.jstor.org/stable/1830482 Robert K Merton; Social Structure and Anomie, JSTOR Available at: https://www.jstor.org/stable/2084686?origin=crossref Lance Lochner and Enrico Moretti (2004); The Effect of Education on Crime: Evidence from Prison Inmates, Arrests, and Self-Reports, ResearchGate Available at: https://www.researchgate.net/publication/ 4901649_The_Effect_of_Education_on_Crime_Evidence_from_Prison_Inmates_Arre sts_and_Self-Reports Morgan Kelly (2000); Inequality and crime, ResearchGate Available at: https://www.researchgate.net/publication/24095661_Inequality_And_Crime Mohamad Kassem, Amjad Ali, and Marc Audi (2019); Unemployment Rate, Population Density and Crime Rate in Punjab (Pakistan): An Empirical Analysis, Bulletins of Business and Economics Available at: https://bbejournal.com/index.php/BBE/article/view/148 Dullah Muloka, Mori Kogidb, Jaratin Lilyc, and Rozilee Asidd (2016); The Relationship between Crime and Economic Growth in Malaysia: Re-Examine Using Bound Test Approach, ResearchGate Available at: 20