Measuring the impact of crime on house prices
By Allen K. Lynch, D. W. Rasmussen. 2001
220 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/b9b1db107bb27e2fa29d8705200463c3af280b9c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- S. Gibbons
- Stephen Machin
- Tricia L. Petras
- Paul Dolan
- George E. Tita
- Robert T. Greenbaum
- T. Peasgood
- Olmo Silva
In Finance
In Sociology and Political Science
- S. Gibbons
- Tricia L. Petras
- Paul Dolan
- George E. Tita
- Robert T. Greenbaum
- Stephen Machin
- T. Peasgood
- Kevin Albertson
Citations in the corpus
- Estimates of the Impact of Crime Risk on Property Values from Megan's Laws (2008, unknown): “We choose to use the estimates listed in Table 5 of Miller et al. (1996) as a rough approximation of the relative costs of victimization among different types of crime; e.g., the relative cost of assault is about 30 percent the cost of rape. It is important to note that, for our calculation, we requ”
- Crime and Residential Choice: A Neighborhood Level Analysis of the Impact of Crime on Housing Prices (2006, background): “Such findings, however, are not unique to our data (e.g., Case and Mayer 1996; Gibbons 2004; Lynch and Rasmussen 2001 ).”
- ESTIMATING THE ECONOMIC AND SOCIAL COSTS OF THE FEAR OF CRIME (2007, background): “For example, ‘hedonic pricing’ studies of house prices in different areas try to estimate how much of the variation in house prices is due to crime by controlling for as many of the other factors that affect house prices as possible (e.g. Lynch and Rasmussen 2001).”
- Valuing School Quality, Better Transport, and Lower Crime: Evidence from House Prices (2008, background): “No significant impact from burglary Lynch and Rasmussen (2001) Jacksonville Florida, impact of violent and property crime Cross-sectional regression with control variables 4% decrease in price for 1. standard deviation increase in violent crime (elasticity of -0.048).”