论网络犯罪及其防治对策

网络犯罪是现代社会的一种新型犯罪,它包括以网络为对象的犯罪和以网络为犯罪现场的犯罪。它具有技术含量高、危害程度重、涉及面广、隐蔽性强等特征。因此,打击该种犯罪,要完善法律法规,加强网络犯罪立法的国际协调与合作。     

Short-term forecasting of crime

The major question investigated is whether it is possible to accurately forecast selected crimes 1 month ahead in small areas, such as police precincts. In a case study of Pittsburgh, PA, we contrast the forecast accuracy of univariate time series models with naïve methods commonly used by police. A major result, expected for the small-scale data of this problem, is that average crime count by precinct is the major determinant of forecast accuracy. A fixed-effects regression model of absolute percent forecast error shows that such counts need to be on the order of 30 or more to achieve accuracy of 20% absolute forecast error or less. A second major result is that practically any model-based forecasting approach is vastly more accurate than current police practices. Holt exponential smoothing with monthly seasonality estimated using city-wide data is the most accurate forecast model for precinct-level crime series.     

Poverty and crime in 19th century Germany

We estimate the impact of poverty on crime in 19th century Bavaria, Germany. Rainfall is used as an instrumental variable for grain (rye) prices to address econometric identification problems in the existing literature. The rye price was a major determinant of living standards during this period. The rye price has a positive effect on property crime: a one standard deviation increased property crime by 8%. OLS estimates are twice as large as instrumental variable estimates, highlighting the value of our empirical approach. Higher rye prices lead to significantly less violent crime, though, and we argue that higher beer prices, caused by the higher rye prices, are a likely explanation.     

MODEL AVERAGING IN ECONOMICS: AN OVERVIEW

Standard practice in empirical research is based on two steps: first, researchers select a model from the space of all possible models; second, they proceed as if the selected model had generated the data. Therefore, uncertainty in the model selection step is typically ignored. Alternatively, model averaging accounts for this model uncertainty. In this paper, I review the literature on model averaging with special emphasis on its applications to economics. Finally, as an empirical illustration, I consider model averaging to examine the deterrent effect of capital punishment across states in the USA.     

论我国经济犯罪的刑事政策

当前经济犯罪持续高发,在目前的经济犯罪刑事政策收效甚微的情况下,有必要对其进行反思。文中从刑事司法、刑事立法及犯罪预防三个角度对当前的经济犯罪的刑事政策进行了评析,并提出从这三个方面进行的调整及完善。     

会计职务犯罪的心理学分析

近年来有的财会人员经不住种种诱惑,采取非法手段,侵害国家、集体和人民的利益,其突出表现为做假帐。本文从心理学的角度分析了会计职务犯罪产生的因素,会计职务犯罪对社会的危害。最后,对如何预防会计职务犯罪,运用制度经济学原理从宏观和微观两方面提出了建议。     

Marked point process hotspot maps for homicide and gun crime prediction in Chicago

Crime hotspot maps are a widely used and successful method of displaying spatial crime patterns and allocating police resources. However, hotspot maps are often created over a single timescale using only one crime type. In the case of short-term hotspot maps that utilize several weeks of crime data, risk estimates suffer from a high variance, especially for low frequency crimes such as homicide. Long-term hotspot maps that utilize several years of data fail to take into account near-repeat effects and emerging hotspot trends. In this paper we show how point process models of crime can be extended to include leading indicator crime types, while capturing both short-term and long-term patterns of risk, through a marked point process approach. Several years of data and many different crime types are systematically combined to yield accurate hotspot maps that can be used for the purpose of predictive policing of gun-related crime. We apply the methodology to a large, open source data set which has been made available to the general public online by the Chicago Police Department.     

Fear of crime and housing prices: Household reactions to sex offender registries

Megan's Law requires public dissemination of information from sex offender registries. Opponents to this controversial law have questioned whether households misinterpret or even use this information. One concern was that the information might simply induce a “fear of crime.” This study finds evidence for both use and misinterpretation of the publicly available information on sex offenders. Using a unique dataset that tracks sex offenders in Hillsborough County, Florida, the results indicate that after a sex offender moves into a neighborhood, nearby housing prices fall by 2.3% ($3500 on average). However, once a sex offender moves out of a neighborhood, housing prices appear to immediately rebound. Surprisingly, these price impacts do not appear to differ in areas near high risk offenders labeled as “predators.”     

Predicting the geo-temporal variations of crime and disorder

Traditional police boundaries—precincts, patrol districts, etc.—often fail to reflect the true distribution of criminal activity and thus do little to assist in the optimal allocation of police resources. This paper introduces methods for crime incident forecasting by focusing upon geographical areas of concern that transcend traditional policing boundaries. The computerised procedure utilises a geographical crime incidence-scanning algorithm to identify clusters with relatively high levels of crime (hot spots). These clusters provide sufficient data for training artificial neural networks (ANNs) capable of modelling trends within them. The approach to ANN specification and estimation is enhanced by application of a novel and noteworthy approach, the Gamma test (GT).     

Modelling and predicting recorded property crime trends in England and Wales—a retrospective

In 1999 the Home Office published, for the first time ever, 3-year ahead projections of property crime in England and Wales. The projections covered the period 1999–2001 and indicated strong upward pressure after five full years of falling crime. This pressure was generated by three factors: the number of young men in the general population, the state of the economy and the fact that property crime appeared to be well below its underlying trend level. The projections received a mixed response, with some agreeing that crime was set to rise while questioning the scale of any increase, to others who doubted the value of this type of econometric modelling. In fact, property crime did increase in 1999, although not at the rate suggested by the models—and indeed levels of burglary continued to fall. This paper addresses some of the reasons for this disparity as well as considering various criticisms of the Home Office approach.     

Tradable and non-tradable expenditure and aggregate demand for imports in an emerging market economy

Using an assumption of non-separability of non-tradable expenditure from imports, this paper examines the impact of the structural transformation undertaken after 2001 on imports and, in turn, the current account stance of Turkey. In this regard, an import demand function is derived under the assumption of non-separability, and is estimated using quarterly time series data from Turkey. The empirical results show that the assumption of non-separability cannot be rejected in the case of Turkey and the relative prices of non-tradable and tradable goods must be among the determinants of import demand in addition to the relative price of imports and real GDP. This result accordingly implies that recent increases in import expenditure are, to some extent, due to changes in the relative price structure in favour of non-tradable goods.