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Oklahoma has seen rapid growth in the development of wind energy over the past decade. Residents are concerned about the negative impacts of turbines such as noise or their appearance. This has raised concerns about property values. Thus, this paper aims to examine and quantify the overall impact of wind turbines upon real estate prices in Western Oklahoma.

Sales prices and the history of approximately 23,000 residential real estate records for both platted and unplatted properties in five counties were examined prior to the announcement of construction, after announcement and after construction. A hedonic analysis was undertaken to examine the real estate prices of the properties near wind farms.

While there may be isolated instances of lower property values for homes near wind turbines, results show no significant decreases in property values over homes near wind farms in the study area. Similar results are found for the unplatted properties.

This paper highlights that in spite of mixed attitudes toward wind farms and misconceptions regarding the link between turbines and property values, Oklahoma’s growing wind industry can continue to thrive without negatively impacting nearby home and land values and prices.

Although there have been numerous studies examining the relationship between wind turbine locations and real estate prices, no study has combined the large quantity of records (over 23,000) as well as both platted and unplatted locations.

In this paper, we examine dynamic relationships among three housing market variables and a stock market index in a multivariate vector autoregressive error correction (VAREC) model. It is first found that, in the USA, sales and the median sales price of the existing single‐family homes and the 30‐year mortgage rate have unit roots, while the New York Stock Exchange (NYSE) value‐weighted portfolio returns appear random. Moreover, it is found that not only are three real estate variables cointegrated with one another but that they are also cointegrated with the stock index returns. After controlling for the unit root problem and cointegration, a multivariate VAREC model is further developed to examine dynamic relationships among the four variables using Johansen’s approach. It is found that the price, mortgage rate, and stock returns affect sales. It is found that the mortgage rate and stock returns affect the price. The 30‐year mortgage rate is affected by sales and the stock returns. Except for the mortgage rate which is negatively correlated with the stock returns, significant evidence is not found that sales and the median sales price affect the stock returns directly.

The size and number of employment subcenters have increased in large metropolitan areas as the spatial distribution of jobs has become increasingly decentralized. Although employment decentralization is not a new phenomenon, only recently have concentrations of employment outside the central city begun to rival the traditional central business district (CBD) in size and scope. Because of this change, neither theoretical nor empirical models in urban economics now rely solely on the traditional monocentric city model of Muth (1969) and Mills (1972). Instead, recent research incorporates some version of a polycentric model, a trend that Anas et al. (1998) document in their excellent review article.

Speed bumps invite varied responses from homeowners, drivers and policymakers. Parents of small children like speed bumps, if they slow the passing traffic, but prospective home buyers may reject a home with a speed bump nearby, contemplating the traversal of it thousand times during an ownership period. The purpose of this study is to empirically identify the effect of speed bumps on home values.

Analysis presented here is based on an examination of home sales prices and exploits variation in the number of speed bumps traversed and the installation of speed bumps to identify the effect of speed bumps on home values. An anonymous online survey is also used to shed light on drivers of the empirical results.

Initial results exploiting variation in the number of bumps traversed suggest speed bumps are associated with reduced residential property values. An estimated treatment effect of speed bump installation underscores the original findings. Finally, survey results imply that older homeowners and homeowners with children may favor speed bumps but less than the disfavor of those who do not.

The research presented here applies to speed bumps in residential areas and on streets not considered through streets.

The findings suggest that planners should investigate options such as medians and roundabouts instead of speed bumps.

These results suggest that communities can be visually improved and home values lifted through the removal of speed bumps and installation of other traffic control devices.

This research is valuable to residential developers, planners and neighborhood associations across the country.

To determine if the ancient Chinese tradition of Feng Shui affects residential property prices in a Western setting (“Western” and “the West” refers to the cultures and peoples of the mainlands Europe, the Americas, Australia, and New Zealand.)

Two approaches were adopted to measure the impact of Feng Shui design principles on property prices. First, a case study approach using a paired sales analysis was adopted to compare sales transaction prices of Feng Shui designed condominiums with sales prices of condominiums that were built without this design feature. Second, sales transaction data were analysed using multiple regression analysis in a hedonic pricing framework.

The results were mixed but provide preliminary evidence that Feng Shui impacts positively on property prices in the West.

Firstly, the units were sold as “designer ready”. Prices for these units exclude floor coverings, painting, kitchen and bathroom fittings, appliances, counter tops and plumbing fixtures. A more precise adjustment was not able to be made as the actual build‐out cost for each unit was not available. However, it was felt that the average rate was a reasonable proxy for the cost of a build‐out. Secondly, the case study includes sales of Feng Shui designed units in only one building. A more reliable result would have been achieved had the data set included several buildings constructed using the principles of Feng Shui.

With the rise in popularity of the use of Feng Shui design in Western homes, understanding the effects of this on property values is important to both property valuers and investors of such property.

Research on the impact of cultural beliefs on residential property values in the West is limited. This paper provides a contribution to understanding the value affects of such beliefs, specifically those relating to Feng Shui.

The role of list price is often discussed in a narrative describing sellers’ preferences or sellers’ price expectations. This paper aims to investigate a set of list price strategies that real estate brokers have available to influence the outcome of the sale, which may be many times self-serving.

By analyzing real estate brokers’ arguments on the choice of the list price level, a couple of hypotheses are formulated with regard to different expected outcomes that depend on the list price. This study empirically tests two hypotheses for the underlying incentives in the choice of list price from the real estate broker’s perspective: lower list price compared to market value leads to the higher sales price, lower list price compared to market value leads to a quicker sale. To investigate the two hypotheses, this paper adopts different methodological frameworks: H1 is tested by running a classical hedonic model, while H2 is tested through a duration model. This study further tests the hypotheses by splitting the full sample into two different price segments: above and below the median list price.

The results show that H1 is rejected for the full sample and for the two sub-samples. That is, contrary to the common narrative among brokers that underpricing leads to a higher sales price, underpricing lower sales price. H2, however, receives support for the full sample and for the two sub-samples. The latter result points to that brokers may be tempted to recommend a list price significantly below the expected selling price to minimize their effort while showing a high turnover of apartments.

Although there are a large number of previous studies analyzing list price strategies in the housing market, this paper is one of the few empirical studies that address the effect of list price choice level on auction outcomes of non-distressed housing sales.

The purpose of this research is to analyze a county’s housing market over 23 years to determine what impact, if any, multiple hurricanes have had on the residential real estate market.

This research uses a hedonic price model to determine the impacts that multiple hurricanes had on housing values.

There was a significant and negative countywide impact on housing sales values in the 1996, which can directly be attributed to three hurricanes impacting Brunswick County. Economic factors, rather than hurricanes and related storms, are more likely to impact sales values in all other years.

This research is limited only to single-family home sales in Brunswick County, North Carolina, from 1984 to 2007. The model does not include multi-family residential uses.

Unlike many other areas that have been studied regarding natural disasters, Brunswick County has been hit multiple times by hurricanes and related storms, providing some insight into the long-term implications of the impact of storms on housing values over an extended period of time. The practical implication is that despite the likelihood of hurricanes and proximity to the ocean, people are willing to pay to live in coastal areas, even an area with a history of repeated direct and indirect strikes by hurricanes.

Unlike much of the peer-reviewed research that looks at a single occurrence of a natural disaster, this research looks at the impacts of multiple hurricanes on a single county over 23 years to determine what impact, if any, these storms have on the overall housing market.

The purpose of this study is to examine the net effect of golf courses’ proximity on home sale prices in Kern County, California.

A spatial Durbin error model is used with sales price data for 1,693 homes sold in Kern County in the third quarter of 2018. This paper compares 90 different spatial econometric models using Bayesian techniques to produce posterior model probabilities which guided model selection and the number of neighbors to use.

The results show that significant spatial dependence exists in home values in Kern County. Point estimates indicate that homes abutting golf courses are valued at less than those which are not. This study also finds that the farther away from golf courses the average home is, the higher its value.

This study contributes to the existing literature in three dimensions. First, this paper analyzes whether proximity to golf courses impacts home values in Kern County where a study of this nature has not been conducted. Second, the analysis uses transaction data for 2018 which was a period when the sport’s popularity was fading and golf courses closing. Third, Bayesian model comparison techniques are used to select the appropriate model.

The purpose of this study is to examine the impact of neighborhood design templates on residential home values in King County, WA, USA. Previous research examines a number of individual design factors; this study combines these factors into typologies and tests for the impacts of the composite set of design features.

The study analyzes over 27,000 home sales with a hedonic price model to measure the impacts across three large, regional submarkets. Neighborhood design categories are developed using a cluster analysis on a set of individual neighborhood attributes.

The key finding from this research is that the impact of more traditional (“urban”) design packages on home values is highly contextual. For the older and denser neighborhoods in the study area, a more traditional design results in a significantly positive impact on home values. In the new and more suburban regions of the study area, this effect is not found.

Prior work focused on valuing design attributes individually. The study argues that neighborhood design is better conceived of as a “package”, as the value of a given design element may depend on other co-located attributes. This is the first study, to the authors’ knowledge, to treat physical neighborhood design variables as a composite whole and to attempt to value their impact on home values as such.