Club Good Influence on Residential Transaction Prices

We examine residential real estate transactions in a market where an additional property right to a club good may have an influence on prices. We find that for single-family property, the market capitalizes approximately 50% of the full value of the extra property right. For condominiums, the amount reduces to approximately 25%. While these amounts are positive, they clearly are significantly lower than full value

Conservation Status and Residential Transaction Prices: Initial Evidence from Dallas, Texas

The traditional mechanisms of private covenants and public restrictions may not meet the needs of residential property owners who want to preserve a certain neighborhood style. Privately initiated and publicly enforced conservation district regulations can preserve desirable neighborhood characteristics and signal to buyers that neighborhood conformity will likely persist. We analyze residential transaction prices in Dallas, Texas and find premiums associated with residential properties within and buffering conservation district locations. These results are robust to the spatial autocorrelation common in residential transaction prices.

Market competition for high‐density residential land

We investigate the potential competition between multifamily and condominium developers for raw land throughout the U.S. When considering the entire sample period, we find evidence that condominium developers paid, on average, more for land than their multifamily counterparts. Alternatively, when we separate the sample into low versus high‐growth locations and two time subperiods, we observe that the premium is not entirely consistent. The average premiums appear to be largely a result of the high‐growth locations from 2004 to mid‐2008. Indeed, the results demonstrate that condominium developers paid over 60 percent more for land in high‐growth states during the later subperiod. This extraordinary premium calls into question the price formation process in these locations. Santruka Savo darbe nagrinejame potencialia konkurencija tarp daugiabučiu namu ir kooperatiniu namu vystytoju del žemes sklypu visoje JAV teritorijoje. Nagrinedami visa imties laikotarpi, aptinkame irodymu, kad kooperatiniu namu vystytojai už sklypus vidutiniškai mokejo daugiau nei ju kolegos, statantys daugiabučius namus. Kita vertus, suskirsčius imti i letai ir sparčiai besivystančias vietoves bei du laikotarpius, pastebima, kad priemoka ne visiškai pastovi. Regis, priemoku vidurki iš esmes lemia sparčiai besivystančios vietoves ir laikotarpis nuo 2004 m. iki 2008 m. vidurio. Iš tiesu rezultatai rodo, kad per ši laikotarpi kooperatiniu namu vystytojai sparčiai besivystančiose valstijose už sklypus mokejo per 60 proc. daugiau. Tokia neitiketina priemoka verčia abejoti tose vietovese taikomu kainodaros procesu. First Published Online: 18 Oct 201

Geostatistical space–time mapping of house prices using Bayesian maximum entropy

<p>Mapping spatial processes at a small scale is a challenge when observed data are not abundant. The article examines the residential housing market in Fort Worth, Texas, and builds price indices at the inter- and intra-neighborhood levels. To accomplish our objectives, we initially model price variability in the joint space<b>–</b>time continuum. We then use geostatistics to predict and map monthly housing prices across the area of interest over a period of 4 years. For this analysis, we introduce the Bayesian maximum entropy (BME) method into real estate research. We use BME because it rigorously integrates uncertain or secondary soft data, which are needed to build the price indices. The soft data in our analysis are property tax values, which are plentiful, publicly available, and highly correlated with transaction prices. The results demonstrate how the use of the soft data provides the ability to map house prices within a small areal unit such as a subdivision or neighborhood.</p

Spatial Statistics Applied to Commercial Real Estate

Spatial statistics, Commercial real estate, Portfolio diversification,