Economic Indicators Selection for Property Crime Rates using Grey Relational Analysis and Support Vector Regression

Features selection is very important in the multivariate models because the accuracy of forecasting results produced by the model are highly dependent on these selected features. The purpose of this study is to propose grey relational analysis and support vector regression for features selection. The features are economic indicators that are used to forecast property crime rate. Grey relational analysis selects the best data series to represent each economic indicator and rank the economic indicators according to its importance to the property crime rate. Next, the support vector regression is used to select the significant economic indicators where particle swarm optimization estimates the parameters of support vector regression. In this study, we use unemployment rate, consumer price index, gross domestic product and consumer sentiment index as the economic indicators, as well as property crime rate for the United States. From our experiments, we found that the gross domestic product, unemployment rate and consumer price index are the most influential economic indicators. The proposed method is also found to produce better forecasting accuracy as compared to multiple linear regressions.

Community vibrancy and its relationship with safety in Philadelphia

To what extent can the strength of a local urban community impact neighborhood safety? We construct measures of community vibrancy based on a unique dataset of block party permit approvals from the City of Philadelphia. Our first measure captures the overall volume of block party events in a neighborhood whereas our second measure captures differences in the type (regular versus spontaneous) of block party activities. We use both regression modeling and propensity score matching to control for the economic, demographic and land use characteristics of the surrounding neighborhood when examining the relationship between crime and our two measures of community vibrancy. We conduct our analysis on aggregate levels of crime and community vibrancy from 2006 to 2015 as well as the trends in community vibrancy and crime over this time period. We find that neighborhoods with a higher number of block parties have a significantly higher crime rate, while those holding a greater proportion of spontaneous block party events have a significantly lower crime rate. We also find that neighborhoods which have an increase in the proportion of spontaneous block parties over time are significantly more likely to have a decreasing trend in total crime incidence over that same time period.

Prosecutor Quality, Witness Participation, Crime, and Reform

We develop a model wherein concerns about prosecutor quality reduce the willingness of witnesses to cooperate with prosecutors. This causes an increase in the crime rate and in wrongly convicted innocent defendants. Because citizens are taxpayers and may be victims, perpetrators, witnesses, or falsely accused defendants, they care about the prosecutor’s quality. They update beliefs about this quality based on the disposition of cases. If the prosecutor’s believed quality falls below a threshold, then a majority of voters chooses to replace the prosecutor with a challenger, in expectation of reform. We compare the majority’s choice with that of a social planner. (JEL D83, K41, K42)

Count Regression Models for Analyzing Crime Rates in The East Java Province

Crime rate is the number of reported crimes divided by total population. Several factors could contribute the variability of crime rates among areas. This study aims to model the relationship between crime rates among regencies and cities in the East Java Province (Indonesia) and some potentially explanatory variables based on Statistics Indonesia publication in 2020. The crime rate in the East Java Province was consistently at the top three after DKI Jakarta and North Sumatra during 2017 to 2019. Therefore, it is interesting for us to study further about the crime rate in the East Java. Our preliminary analysis indicates that there is an overdispersion in our sample data. To overcome the overdispersion, we fit Generalized Poisson and Negative Binomial regression. The ratio of deviance and degree of freedom based on Negative Binomial is slightly smaller (1.38) than Generalized Poisson (1.99). The results indicate that Negative Binomial and Generalized Poisson regression, compared to standard Poisson regression, are relatively fit to model our crime rate data. Some factors which contribute significantly (α=0.05) for the crime rate in the East Java Province under Negative Binomial as well as Generalized Poisson regression are percentage of poor people, number of households, unemployment rate, and percentage of expenditure.

Criminality and economic growth province in Indonesian

The decline in economic growth, which is offset by the increasing number of people and the lack of availability of jobs, has caused more people to be affected and involved in non-crime activities based on the crime rate (CR). This study aims to analyze the effect of crime rates on provincial economic growth in Indonesia in 2011-2020. The variables used are economic growth, crime rates, investment, labor, and initial growth. The method used is the Fixed Effect Model. The results show that the higher the crime rate impacts the decline in economic growth, further increase in investment and labor will encourage economic growth. In contrast, the initial growth shows that the economy of poor provinces grows slower than rich provinces.

Radical decrease in the number of homicides in Hungary

In Hungary, the number of crimes recorded by crime statistics is surprisingly decreasing. Since its peak in 1998, the overall crime rate has fallen to less than a third. Within this, the decline in the number of homicides, which fell to one-fifth, is even more pronounced. Many people critically look at statistical indicators, and the authority’s accounting methods know the superior numbers. In my research, I examined this.

Law Enforcement, Security, and Transnational Crime

The border area between Indonesia and Malaysia is one of the border areas with a high transnational crime rate. Both the Indonesian and Malaysian governments have tightened the procedures to enter and leave the two countries' territory. However, the illegal movements of goods and people still occur frequently, caused by many rat runs connecting both countries. This paper uses a qualitative research method. The literature study was used as a method of collecting data in this study. This paper was made to determine the Indonesian government's progress in creating order and security for the people in the border areas from trans-border crimes. It is apparent that in terms of law enforcement, the Indonesian government strives to enforce rules based on the applicable customs laws without prejudice to the regulations of values and customary laws adhered to by communities of Indonesia and Malaysia. Through the Resort Police (Polres), the Indonesian government must pay attention to the provision of protection and services to their people in the process of enforcing the law. The Polres as investigators, coordinating with the Attorney to carry out the pre-prosecution stage of the perpetrators of crimes. The Polres is also coordinating with several related institutions, such as Customs and Excise and the Indonesian National Narcotics Agency (BNN), to better control the flow of illegal goods that enters and leaves Indonesia. Keywords: Law Enforcement; Security; Transnational Crime

Crime rate, real earnings management and managerial ability

Purpose This paper aims to examine the effect of managerial ability (MA) on real earnings management and the effect of real earnings management by higher ability managers on future profitability, at a different level of the crime rate. Design/methodology/approach The research sample includes 864 manufacturing firms-years listed on the Indonesian Stock Exchange. MA uses an efficiency score by data envelopment analysis. Real earnings management is measured by abnormal activities. The crime rate is measured by logarithm natural of the number of crimes per 100.000 citizens in the region where the firm is headquartered. Data analysis uses fixed-effect regression. Findings MA increases real earnings management in the region where the firm is headquartered with a higher crime rate while MA will reduce real earnings management in the region where the firm is headquartered with a lower crime rate. Also, real earnings management by higher-ability managers gives a signal of better future profitability in the region where the firm is headquartered with a lower crime rate. Originality/value This research contributes to filling the previous gap of managerial characteristics ability-related on real earnings management by providing regional crime rate as a determinant factor of managers’ ethical behavior. This research is the first one to considers the regional crime rate treatment to the relationship between MA and real earnings management especially in Indonesia. This research also provides new evidence of efficient real earnings management for a lower crime rate group of samples to give a signal of better future profitability.