Purpose

This paper focusses on analysing the impact of crime on the housing market in Los Angeles (LA) County. By looking at different types of crime instead of general crime measures and controlling by spatial dimension of prices and crime as well as endogeneity, a model is developed that allows for the understanding of how a specific crime impacts the housing market transaction price. To perform the analysis, the paper merges different data sets (crime, housing transaction and census data) and then computes the distances to crucial transport modes to control the accessibility features affecting housing prices. The latter allows estimating the association of housing prices and crime in the distance and estimating the impact on housing depending on it.

Design/methodology/approach

This paper focusses on the following crimes: aggravated assault, burglary (property crime), narcotics, non-aggravated assault and vandalism. The paper shows firstly how incidents of reported crime are distributed across space and how they are related to each other – thus highlighting crime models with spatial influences. Secondly, the research utilises instrumental variables within the methodology to estimate house prices using spatial analysis techniques while controlling for endogeneity. Thirdly, it estimates the direct impact of crime on house prices and explores the impact of housing and neighbourhood features.

Findings

Results suggest that house transaction prices and crime are closely correlated in two senses. Housing prices are endogenously negatively associated with the levels of narcotics and aggravated assaults. For narcotics, the impact of distance is shorter (1,000 m). However, for burglary, vandalism and non-aggravated assaults, the price reaction suggests a positive association: the further away the crime occurs, the higher the prices. The paper also shows the large spatial association of different crimes suggesting that they occur together and that their accumulation would make negative externalities appear affecting the whole neighbourhood.

Research limitations/implications

The use of a huge database allows interesting findings, but one limitation can be to not have longer time observations to identify the crime evolution and its impact on housing prices.

Practical implications

Large implications as the relationship identified in this paper allow defining precise policies to avoid crime in different areas in LA. In addition, crime has significant but quantitative small effects on LA housing transaction prices suggesting that the effect depends on the spatial scale as well as lack on information about where the crimes are committed. Lack on information suggests low transparency in the market, affecting the transaction decision-taken process, affecting the risk perception and with relevant implications over household welfare.

Originality/value

This paper relates the spatial association among crimes defining the hotspots and their impacts on housing transaction prices.

中文翻译：

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犯罪对洛杉矶县房价的影响

目的

本文重点分析犯罪对洛杉矶 (LA) 县房地产市场的影响。通过查看不同类型的犯罪而不是一般的犯罪措施，并通过价格和犯罪的空间维度以及内生性进行控制，开发了一个模型，可以理解特定犯罪如何影响住房市场交易价格。为了进行分析，本文合并了不同的数据集（犯罪、住房交易和人口普查数据），然后计算到关键交通方式的距离，以控制影响房价的可达性特征。后者允许估计远处的房价和犯罪的关联，并据此估计对住房的影响。

设计/方法/方法

本文重点关注以下罪行：严重袭击、入室盗窃（财产犯罪）、毒品、非严重袭击和故意破坏。该论文首先展示了报告的犯罪事件如何在空间中分布以及它们如何相互关联，从而突出了具有空间影响的犯罪模型。其次，该研究利用方法中的工具变量来使用空间分析技术估计房价，同​​时控制内生性。第三，它估计了犯罪对房价的直接影响，并探讨了住房和社区特征的影响。

发现

结果表明，房屋交易价格和犯罪在两个意义上密切相关。房价与毒品和严重袭击的水平存在内生性负相关。对于麻醉品，距离的影响更短（1,000 米）。然而，对于入室盗窃、故意破坏和非严重攻击，价格反应表明存在正相关关系：犯罪发生的距离越远，价格越高。该论文还显示了不同犯罪的巨大空间关联，表明它们一起发生并且它们的累积会使负面外部性似乎影响整个社区。

研究限制/影响

使用庞大的数据库可以获得有趣的发现，但一个限制可能是没有更长时间的观察来确定犯罪演变及其对房价的影响。

实际影响

本文中确定的关系具有重大意义，允许制定精确的政策以避免洛杉矶不同地区的犯罪。此外，犯罪对洛杉矶住房交易价格有显着但数量上的小影响，这表明该影响取决于空间尺度以及缺乏关于犯罪地点的信息。缺乏信息表明市场透明度低，影响交易决策过程，影响风险认知，并对家庭福利产生相关影响。

原创性/价值

本文将界定热点的犯罪之间的空间关联及其对住房交易价格的影响联系起来。