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This paper uses data from 2010 to 2016 across 32 states and union territories to investigate the determinants of crime in India. Results indicate the significance of macroeconomic, demographic, socioeconomic and deterrence factors in accounting for various categories of crime.

Due to the evidence of heteroskedasticity and cross-sectional dependence, linear regression with panel-corrected standard errors is implemented.

It has been found that among the macroeconomic factors, only GSDP per capita was found relevant in explaining total crime rates. However, the unemployment rate and price level are crucial in explaining some categories of crime. The demographic factor, that is, population density, socioeconomic factors, that is, income inequality, poverty rate, literacy rate exhibit important and significant relationship with crime rates in India. Further, out of the four deterrence factors, charge-sheeting rate, conviction rate, pendency in police cases are important in explaining various categories of crime rates in India.

While implications of some socioeconomic variables are consistent with those found in previous studies, literacy rates and deterrence variables were found to have a positive association with crime. In particular, in a developing country such as India, white-collar crimes tend to increase as literacy rates increase. This calls for implementing policies that lead to greater employment opportunities for the educated masses. This paper also sheds light on the relationship between deterrence factors and crime rates in India. Deficiencies in the legal and judicial system have been detrimental to the nation's ability to curb crime rates.

The primary purpose of this paper is to empirically investigate the impact of educational attainment on crime rates across 33 Indian states over the period 2001 to 2013. This paper also examines the role of various macroeconomic, socio-economic and demographic factors in determining the variation of crimes in India.

First, this paper provides a representative theoretical model and discusses the possible relationship between crime and education. Second, the paper applies a dynamic panel data (DPD) model to extract more precise, unbiased and reliable estimates of the effect of education in abating different crime rates. The main advantage of using the dynamic panel model is to address the problem of endogeneity in some regressors and capture the time persistent effect of education on crime.

Empirical findings reveal that a 1% increase in gross enrolment ratio leads to the reduction of total crime by 8%. However, a unique finding identifies a positive association between tertiary education and economic crime. This finding further goes against the general belief that criminals tend to be less educated than non-criminals.

This paper recommends that instead of punishment and mandatory law enforcement for offenders, increase in government expenditure and different educational attainment ratios can go a long way to combat crime in India, which has posed a serious threat to the stability of society. Furthermore, utilizing the information on offenders' educational attainment in examining the crime rates can be a future research agenda for policymakers.

This study contributes to the empirical debate of ‘crime-education nexus’ by examining the role of education on crime in India. This study is the first of its kind that focuses on the aspects of crime and education more recently and investigates the relationship between crime and education due to the recent changes in educational attainment ratios and crime rate.

The specific objective of the study is to investigate the presence of natural rate of crime rates in selected emerging economies by using panel unit roots. The majority of the literature examines the issue using conventional unit root tests in a country-specific context. Meanwhile, there is no panel unit root investigation has been undertaken considering both cross-sectional dependence (CD) and structural changes.

As a result, this study is to fill the aforementioned gap and validate the natural rate of crime rates for 10 countries by using a Fourier panel unit root test. The advantage of the test is that structural shifts are modelled as gradual or smooth changes with a Fourier approximation, and it also accounts cross-sectional dependency. Thus, the Fourier panel unit root test may have better performance in capturing potential changes in the nature of data.

The result of the conventional unit roots test shows evidence of the hysteresis effect in crime, as it stands does not adequately account for smooth transitions or breaks. On contrary, the Fourier panel unit root test confirms the natural rate hypothesis in crime rates. The present results highlight the detrimental effects of crime cannot be abated by short-run deterrence policies.

Contrary to previous studies, the theoretical implications of the study imply that the empirical models consider the dynamic nature of crime rates should account for natural rate properties instead of the hysteresis assumption.

The purpose of this paper is to examine the influence of reference data, input address quality, and crime type on completeness and positional accuracy of street geocoded crime events.

Existing data were analyzed using ArcGIS, including crime incident information, street network reference data, and address point and/or parcel reference data. Geocoding completeness was determined by the overall match rate. Positional accuracy was determined by comparing the Euclidian distance between street geocoded locations of crime events to the corresponding address point/parcel geocoded location.

Results indicate that match rates vary by reference data, input address quality, and crime type. Local street centerline files consistently produced match rates that were as good as – and in many cases superior to – other types of reference data, including commercial data. Greater variability in positional accuracy was observed across reference data when crime type and input address quality was considered, but results were consistent with positional accuracy analysis conducted using data from other disciplines.

Results provide researchers and practitioners with valuable guidance and insight into one of the most basic – albeit fundamental – procedures related to the spatio‐temporal analysis of crime, suggesting that reference data required to produce geocoded crime incidents successfully and of high quality does not necessarily mean a large financial investment on the part of law enforcement agencies or researchers interested in the geospatial analysis of crime.

Prior to this investigation, a comprehensive examination of the impact of data quality on geocoded crime events was absent from the literature.

The purpose of this paper is to relate the quality of governance with crime in Malaysia. The study also identifies the best good governance tool to fight against crime in Malaysia.

The study uses time-series data on crime rates and six measures of governance: voice and accountability, political stability, government effectiveness, regulatory quality, rule of law and control of corruption. In this study the authors employed the popular autoregressive distributed lagged modeling approach to estimate the long-run model of crime and governance.

The authors test the hypothesis that good governance lowers crime rates (total crime, violent and property crimes). The results suggest a negative relationship between crime rates and good governance in Malaysia. This suggests that good governance reduces crime rates in Malaysia.

The limitations of this study is the short time-series used in the analysis which is from 1996 to 2009.

This study provides evidence that the practice of good governance, for example, lower corruption, good policing and judicial system can mitigate crime in Malaysia.

The implementation of good governance will protect property right of individuals, business sector and the society as a whole, and this will enhance prosperity of a nation.

This study provide the first empirical evidence that linking between crime and good governance in Malaysia.

Detective work is a mainstay of modern law enforcement, but its effectiveness has been much less evaluated than patrol work. To explore what is known about effective investigative practices and to identify evidence gaps, the authors assess the current state of empirical research on investigations.

The authors assess the empirical research about the effectiveness of criminal investigations and detective work in resolving cases and improving clearance rates.

The authors’ analysis of the literature produced 80 studies that focus on seven categories of investigations research, which include the impact that case and situational factors, demographic and neighborhood dynamics, organizational policies and practices, investigative effort, technology, patrol officers and community members have on case resolution. The authors’ assessment shows that evaluation research examining the effectiveness of various investigative activities is rare. However, the broader empirical literature indicates that a combination of organizational policies, investigative effort and certain technologies can be promising in improving investigative outcomes even in cases deemed less solvable.

From an evidence-based perspective, this review emphasizes the need for greater transparency, evaluation and accountability of investigative activities given the resources and importance afforded to criminal investigations.

This review is currently the most up-to-date review of the state of the research on what is known about effective investigative practices.

Since the literature on the effect of the unemployment rate as reflection of economic fluctuations on crime shows an empirically ambiguous effect, the purpose of this paper is to argue that a new way of modeling the dynamics of unemployment and crime by focussing on the transitory and persistent effect of unemployment on crime helps resolve this ambiguity.

Panel data for US states from 1965 to 2006 are examined using the Mundlak (1978) methodology to incorporate the dynamic interactions between crime and unemployment into the estimation.

After decomposing the unemployment effect on crime into a transitory and persistent effect, evidence of a strong positive correlation between unemployment and almost all types of crime rates is unearthed. This evidence is robust to endogeneity and the controlling for cross-panel correlation and indicators for state imprisonment.

The paper is the first to examine the dynamics of the interaction of crime and economic fluctuations using the temporary and persistent effects framework of Mundlak (1978). In one set of estimates, one can evaluation both the short- and long-run effects of changes of unemployment on crime.

The purpose of this paper is to examine whether community-oriented policing (COP) influences rates of police use of force across communities, and whether the impact of COP varies according to the level of violent crime in communities.

A range of data sources including police use of force reports, online surveys of Officers-in-Charge and recorded crime data was used to examine the association between formal and informal community consultation and the frequency of police use of force, across 64 socially challenged communities in Australia.

Poisson multilevel modelling indicated no overall association between informal or formal community engagement and rates of police use of force. However, significant interaction terms for both informal and formal community consultation with violent crime rates indicated that higher levels of informal and formal community consultation were associated with lower rates of police use of force in communities with higher levels of violent crime. This relationship was not evident in low violent crime areas.

Communities were purposively sampled to have a high propensity for police use of force, on the basis that they had high rates of violent crime, or high levels of socio-economic disadvantage, or both. This research should be replicated with a representative sample of communities.

The findings extend the potential benefits of COP to reducing the use of coercive policing tactics in high violent crime communities.

This study finds that COP can reduce the frequency of violent encounters between police and community members in high violent crime communities.

Messner and Rosenfeld have proposed an institutional anomie theory of crime, incorporating the proposition that societal investments in programs to buffer citizens from capricious market forces (decommodification) are inversely related to rates of lethal violence among societies. They support this argument through an analysis of variations in homicide rates among nations. However, the research relevant to their theory is quite limited with numerous claims and arguments yet to be examined. This paper outlines several limitations of the theory and brings data from the World Values Surveys and other sources to bear on their characterization of American culture in comparison to other nations, their arguments about the impact of economic dominance on other institutions, and alternative explanations of the link between decommodification and homicide. Finally, the relevance of the theory to serious property crime is considered and shown to generate serious problems for institutional anomie theory when evaluated as a general theory of crime.

The main purpose of this study is to examine the dynamic relationship between tourist arrivals, inflation, unemployment and crime rates in Malaysia. This study covered the annual data from 1970 to 2008.

The multivariate Johansen‐Juselius cointegration test is employed to examine the potential long‐run equilibrium relationship. While the Granger causality test within the vector error‐correction modelling (VECM) framework is applied to determine the causal relationship between crime rate and its determinants.

The Johansen‐Juselius cointegration test result reveals that the variables are cointegrated and the dynamic ordinary least squares estimator suggest that unemployment, inflation and tourist arrivals are positively related to crime rates in Malaysia. For Granger causality, in the long‐run tourist arrivals, inflation and unemployment rates Granger cause crime rate in Malaysia. However, in the short run we find bilateral causality between unemployment, crime and tourist arrivals. Finally, the variance decompositions and impulse response functions analyses implied that unemployment, inflation and tourist arrivals are important in explaining the variation in crime for Malaysia.

The estimated crime rate function for Malaysia demonstrated that promoting supply‐side economy and also increases the numbers of police and patrolling duties in the potential crime areas will reduce the crime rate in Malaysia and in the same time attract more tourist arrivals to Malaysia.