We exploit the local variations crime across time to measure the effect of local crime on house prices. We have access to a very granular micro-dataset consisting of real estate listings for sale in Buenos Aires City, Mexico City and São Paulo. We follow an IV procedure and instrument local crime with the homicide rate. We find that our IV estimates for local crime are greater than their corresponding pseudo-panel linear model coefficient estimates. Second, we show that the direct crime elasticity to house prices is robust to varying sizes of the regular polygons. However, the spillover effects of crime on house prices fade away when the size of the polygons is sufficiently large.

我们利用随时间变化的地方犯罪来衡量地方犯罪对房价的影响。我们可以访问一个非常精细的微数据集，其中包含布宜诺斯艾利斯市、墨西哥城和圣保罗待售的房地产清单。我们遵循 IV 程序并用凶杀率衡量当地犯罪。我们发现我们对当地犯罪的 IV 估计值大于其相应的伪面板线性模型系数估计值。其次，我们表明，房价的直接犯罪弹性对于正多边形的不同大小是稳健的。然而，当多边形足够大时，犯罪对房价的溢出效应就会消失。