Do Restrictive Land Use Regulations Make Housing More Expensive Everywhere?

This study makes three contributions to the debate over the effect of local land use regulations on housing prices and affordability. First, it is more geographically extensive than previous studies, encompassing 336 of the nation's 384 metropolitan areas. Second, it looks at multiple measures of regulatory stringency, not just one. Most prior studies have focused either on a single regulatory measure or index across multiple metropolitan areas, or multiple regulatory measures in a single region. Third, this paper considers the connection between regulatory stringency and housing values as a function of employment growth and per-worker payroll levels. We find that restrictive land use regulations do indeed have a pervasive effect on local home values and rents, and that these effects are magnified in faster-growing and more prosperous economies. We also find more restrictive land use regulations are not associated with faster rates of recent home value or rent growth, and that their effects on housing construction levels—that is, the degree to which they constrain supply—is uneven among different housing markets.

Gentrification effects on housing prices in neighbouring areas

Purpose This study aims to measure the occurrence of gentrification and to relate gentrification with housing values. Design/methodology/approach The authors have used Getis-Ord statistics to identify and quantify gentrification in different residential areas in a case study of Stockholm, Sweden. Gentrification will be measured in two dimensions, namely, income and population. In step two, this measure is included in a traditional hedonic pricing model where the intention is to explain future housing prices. Findings The results indicate that the parameter estimate is statistically significant, suggesting that gentrification contributes to higher housing values in gentrified areas and near gentrified neighbourhoods. This latter possible spillover effect of house prices due to gentrification by income and population was similar in both the hedonic price and treatment effect models. According to the hedonic price model, proximity to the gentrified area increases housing value by around 6%–8%. The spillover effect on price distribution seems to be consistent and stable in gentrified areas. Originality/value A few studies estimate the effect of gentrification on property values. Those studies focussed on analysing the impacts of gentrification in higher rents and increasing house prices within the gentrifying areas, not gentrification on property prices in neighbouring areas. Hence, one of the paper’s contributions is to bridge the gap in previous studies by measuring gentrification’s impact on neighbouring housing prices.

What effect does gun-related violence have on the attractiveness of a residential area? The case of Stockholm, Sweden

PurposeThis study aims to analyse the effect of gun-related violence on housing values, controlling for the area's crime levels and locational factors. Previous studies that aimed to find a causal connection between crime and housing values used instrument variables to solve the endogeneity problem. Here, the authors have instead been able to take advantage of the fact that shootings have occurred in random time and space. This has made it possible to estimate models to create windows around the shooting (event) and to estimate the causal effects of the shootings. Thus, the authors aim to contribute to the regression discontinuity design method in this context to estimate the short-term effects.Design/methodology/approachUsing the regression discontinuity design method, the authors can estimate the short-term effects of shootings.FindingsFindings from the analysis indicate that shootings directly affect those who are impacted by shootings and indirectly affect the environments where shootings occur. The indirect effect of shootings is momentary as it is capitalised directly in housing values in the immediate area. The effect also appears to be relatively long-term and persistent as housing values have not returned to the price level before the shooting 100–200 days after the shooting. The capitalisation effect is higher the closer one gets to the central parts of the city. On the other hand, the capitalisation effect is not higher or lower in areas with a higher crime rate per capita.Originality/valueThe article contributes to the previous literature in several ways. First and foremost, it provides an explicit analysis of shootings in built-up areas and their hypothesised effect on property prices through the impact on attractiveness and perceived safety. As far as the authors know, no study has analysed this issue on the international level or in Sweden. In this way, the authors aim to develop a study that can provide critical knowledge about one of the adverse effects of shootings. The authors also contribute to the literature by utilising unique data material, which allows the authors to merge information from the police about the exact location of shootings in the Stockholm area with data on sales of apartments in the same residential areas. In addition to the exact location of the shootings (coordinates), the authors also have access to data about whether the shootings led to injuries or deaths. Thus, the authors have separated the effect of shootings and fatal shootings, which has not been done before. Finally, the authors set out to highlight the results as a contribution to the debate on shootings.

Inter-city transport infrastructure and intra-city housing markets: Estimating the redistribution effect of high-speed rail in Shenzhen, China

This study analyses the changes in intra-city housing values in response to improved inter-city connection brought by high-speed rail (HSR), using the opening of the Hangzhou–Fuzhou–Shenzhen Passenger Dedicated Line (HFSL) in Shenzhen, China, as an example. The opening of the HFSL and its integration into the local metro network at Shenzhen North Station provide exogenous intra-city variations in access to the surrounding economic mass. With a difference-in-differences approach, we find that the HFSL showed a negative local effect as housing values declined by 11.5%–13.3% in the proximity of Shenzhen North Station relative to areas further from the station after the opening, possibly due to the negative externalities of the HFSL. The HFSL effect can spread along the metro network and lead to, on average, a 7% appreciation of housing values around metro stations (network effect). The direction and strength of the network effect vary by metro travel time between Shenzhen North Station and metro stations. Housing values decreased by 7.7% around metro stations within 5–15 minutes of metro travel time but increased by 63.6%, 16.6% and 29.2% around metro stations within 15–25, 25–35 and 35–45 minutes of metro travel time to Shenzhen North Station, respectively. The HFSL effect on housing values diminishes when the rail travel time is above 45 minutes. We interpret these findings as evidence of the redistribution effect in the city related to HSR connection.