challenging the idyll: does crime affect property prices in small towns ?
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Challenging the idyll: Does crime affect property prices in small towns ?. Vania Ceccato and Mats Wilhelmsson. Introduction. There is no novelty in saying that crime concentrates in urban environments. - PowerPoint PPT PresentationTRANSCRIPT
Challenging the idyll: Does crime affect property prices in small towns?
Vania Ceccato and Mats Wilhelmsson
Introduction
• There is no novelty in saying that crime concentrates in urban environments.
• Rural municipalities are often regarded as idyllic safe places; a retreat from the problems of big cities, including crime.
• The problem is that far too often low crime rates in rural areas are taken as a sign of there being ‘no problem’, or that, just because fewer offences occur, crime does not affect people living there.
Literature reviewSource Case study Effect of crime on prices or rent
Kain and Quigley (1970) St. Louis, USA No effectThaler (1978) Rochester, New York, USA NegativeHellman and Naroff (1979) Boston, UK NegativeRizzo (1979) Chicago and Boston, USA NegativeDubin and Goodman (1982) Baltimore metropolitan area, USA Negative
Tita et al. (2006) Columbus, USA InconclusiveMunroe (2007) Charlotte, NC, USA NegativeLynch and Rasmussen (2001) Jacksonville, Florida, USA No effect/
Positive effect
Bowes and Ihlanfeldt (2001) Atlanta, USA NegativeGibbons (2004) London, UK NegativeCeccato and Wilhelmsson (2011) Stockholm, Sweden Negative
Ceccato and Wilhelmsson (2012) Stockholm, Sweden Negative
Aim
• The aim of this study is to assess whether crime, particularly burglary, affects property prices in a rural municipality.
Case study: Jönköping• The municipality has a housing market that is sufficiently large
to allow a hedonic analysis of the impact of safety on property prices.
• Although Jönköping can be classified as a middle large municipality in terms of total population in Sweden, with an important university, it is located geographically isolated from the three main urban Swedish centers: Stockholm, Gothenburg and Malmö.
• The municipality has excellent transport communications but it is relatively distant from the main national urban centers.
• In terms of safety, the number of reported crimes per 1000 inhabitants in Jönköping is lower than the national average, a typical characteristic of rural municipalities in Sweden.
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 20120
2000
4000
6000
8000
10000
12000
14000
16000
SwedenJönköping municipalityTheft - JönköpingViolence - Jönköping
Offe
nce
by 1
00 0
00 in
habi
tant
s
Figure 2 – Offences per 100,000 inhabitants, Sweden total, Jönköping total, theft and violence rates. Data source, BRÅ (2013).
Hedonic modelling
• Hedonic price modelling is traditionally used to assess property values and one’s willingness to pay for the property.
• The price of a property reflects attributes associated with it, which can be of two types:– those related to the property itself and – those related to the environment in which the property is
located. • Controlling: spatial dependency, endogeneity, outliers
Hypotheses
1. Residential burglary negatively impacts apartment prices after controlling for attributes of the property and neighborhood characteristics.
2. Residential burglary affects different market segments differently. Residential burglary will have a stronger negative effect on high-priced apartments regardless of year.
3. The effect of residential burglary on property prices varies over time. Property prices will be more negatively affected in areas that show higher increases in crime rates (changes).
Data• The estimation of the hedonic equation in this article is
based on two cross-sectional data sets that include arm’s-length transactions of apartment sales in co-operative housing societies.
• Using Geographical Information Systems (GIS), the apartment sales data have been merged together with land use, demographic and socio-economic data from Jönköping’s City planning office.
• Crime data for 2005 and 2011 were provided by the Jönköping Police and contained the coordinates of each address.
Results (2011)
Coefficient t-value
Area .8525 11.38Fee -.235 -5.03Room .161 .022Top floor .027 1.24Road50m .008 0.34Water50m .406 10.50DistJönköping -.251 -18.20DistHuskvar -.051 .030Age40_64 -.203 -6.00Age65_84 -.340 -8.33AgeOlder_85 -.247 -.5.23RBurgrate11 -.230 -3.44Constant 14.675 29.73R2 .697 Moran’s I 20.000
Robust results (2011)
OLS IV Spatial lag Spatial Error
-2-1.8-1.6-1.4-1.2
-1-0.8-0.6-0.4-0.2
0
Burglary
Conclusion
1. Residential burglary negatively impacts apartment prices after controlling for attributes of the property and neighborhood characteristics.
• Findings show that residential burglary has a significant negative effect on property prices in Jönköping in 2011
Conclusion
2. Residential burglary affects different market segments differently. Residential burglary will have a stronger negative effect on high-priced apartments regardless of year.
• The variable ‘burglary rates’ is slightly more significant in for upper quantile prices than for lower or mid quantiles.
Conclusion
3. The effect of residential burglary on property prices varies over time. Property prices will be more negatively affected in areas that show higher increases in crime rates.
• The models based on change in crime rate as an explanatory variable produce a poor goodness of fit, the hypothesis of effect of residential burglary on property prices over time was only partially tested.