Commercial property values in a border metropolitan economy (original) (raw)

Infrastructure Impacts on Commercial Property Values Across El Paso in 2013

2018

Real estate property value analysis is used for municipal taxation and budgeting. Commercial properties make up a large percentage of the property tax base in many, if not most, taxing jurisdictions. Data constraints limit the number of analyses conducted on commercial property value patterns. This study employs a fairly extensive data set to address that problem in the context of El Paso in 2013. The sample contains data for 105,611 commercial real estate parcels. Empirical analysis is conducted using geographically weighted regression analysis. Results confirm that parameter estimation for the commercial property data in this sample should be conducted using methodologies that allow for spatial autocorrelation and heteroscedasticity. ACKNOWLEDGEMENTS The authors thank David Stone and Howard Johnson from the El Paso County Central Appraisal District for invaluable support in facilitating access to the data required to conduct this research. The efforts of Beatriz Mesta, who assiste...

Trends in Real Estate Valuation: Spatial Econometrics, Land Values and Sustainability

In the aftermath of the recent boom and bust of U.S. real estate, both a re nement and a deeper understanding of real estate valuation methods have become critical concerns across a number of broad urban-related academic elds. Out of this we see three major trends in the eld of real estate valuation research: 1) the expansion of spatial econometrics; 2) the recognition of the di erences between land values and improvement values; and 3) acknowledgement of value premiums stemming from more sustainable forms of development. This paper o ers a brief summary of the latest work in these emerging areas of academic valuation research.

An Analysis of Spatial Dependence in Real Estate Prices

An Analysis of Spatial Dependence in Real Estate Prices, 2022

Real estate properties are naturally location-fixed. When space related factors are not fully incorporated in a standard pricing equation, spatial autocorrelation is likely to exist. This results in inefficiencies in estimations and raises the need for more complex spatial models. This paper analyzes the determinants of spatial dependence and evaluates the performance of the hedonic regression equation when the determinants of spatial dependence are controlled for. Using a novel dataset for a metropolitan housing market, we document the spatial clustering of housing characteristics such as area, total number of floors and the building age. We find support for the hypotheses that the construction process, shared social services and high-rise residential complexes cause spatial correlation. Our findings show that spatial correlation is significantly reduced when the factors of spatial dependence and district level data is controlled for in the standard hedonic regression.

Discovering and Applying Location Influence Patterns in the Mass Valuation of Domestic Real Property

This thesis addresses the important question of how to incorporate location into a model for the mass valuation of residential (domestic) real property. Two new methods for doing so are described. The first is a process for detecting distinct market segments within a defined study area. It makes use of Geographically Weighted Regression to construct a three dimensional point pattern surface throughout the area for a home of identical characteristics. When the surface displays a discernable spatial structure, evidence is provided for the existence of market segments. The segments detected by this technique are used in a system of models that account for large-scale effects of location on value and thereby improve the predictive accuracy of this model system as compared to a single global model of the same form. The second is a modification to the comparable sales method of valuation such that it provides a prediction accuracy superior to both ordinary least squares (OLS) estimates and the comparables sales method itself. It is formed by taking an optimal linear combination of the OLS model and the comparables sales model based on an examination of the spatial structure of the localized residual errors of the OLS. In combination, these two methods provide improved predictive accuracy and a reduction in the spatial autocorrelation of the residual errors of the resultant predictions when compared to alternative model structures

Location-specific analysis of urban land values

The PhD-project aims on retrieving real estate market fundamentals by modelling the residential real property market in some regions of Austria. For this about 250,000 records over a time span of 18 month had been retrieved from the web. These market observations cover asking prices as well as on the rental prices. A subset of this dataset will be compared with the transaction prices registered at the Land Registry. The study areas will include the Vienna region as well as a regional center. The PhD-project focuses on revealing (i) land-to-total value ratio (LTVR) and (ii) price to rent ratio (PRR) for spatial units within the project areas based on market transfer price and rental price data. Information about real property values and the spatiotemporal changes of real estate market values are relevant for making good choices. This applies for households, investors as well as for the state. Estimating and forecasting real estate market fundamentals can reveal market risks including bubbles. Linking datasets from real estate market observations with datasets from public registers allows to deduct parameters for real estate market fundamentals as well as for mass valuation. CLAPP (2003), KAUKO & D'AMATO (2008b:27) discussed issues of mass valuation. SIVITANIDES et al. (2003), BRAUERS (2011) as well as SCHNEIDER (2013:32ff.) identified such fundamental indicators based on variables at supply as well as at demand side of the real estate market and analyzed them over time. There is a strong economic interest for determining the performance of real property prices, the price-to-rent ratio and the total value-to-land value ratio on a national level as we see from increasing activities on real estate indices on European level (EUROSTAT 2013) as well as on national level (BMWFW / BMF 2014). However, most of these indicators have a strong spatial component too - the results depend on the spatial aggregation applied. Thus the national level only averages diverse impacts from regional developments. The deviation of current prices of assets from their fundamental values will be quite different from region to region.

Spatial econometric analysis of Louisiana rural real estate values

Finance. I thank him for assisting me with the spatial econometrics methods and all the suggestions he made in the use of these methods. I would also like to thank Dr. Gail Cramer, Head, Department of Agricultural Economics and Agribusiness for his support and leadership. Extended gratitude to the faculty, staff, research associates, and my fellow graduate students for their help and support throughout my program at LSU. Special appreciation is expressed to Ms. Jane Niu; Instructor and GIS Manager for her assistance in using the GIS resources. Special thanks to Janis Breaux, Raúl Pinel and iii Beth Roule for their help in getting the survey ready. Janis was especially helpful by reviewing the manual reference of the data, editing this manuscript, and making suggestions.

Spatial Regression Analysis of Commercial Land Price Gradients

2001

Commercial land price gradients for an emerging real estate market are estimated using spatial regression techniques. Spatial statistics are used to explore the extent of spatial autocorrelation in the residuals of an OLS land price gradient model. Spatial autocorrelation is present but not to the same degree for all time periods or commercial land uses. Maximum likelihood estimates of land price gradients are as one would expect in mature real estate markets.

Using a Geographic Information System to Track Changes in Spatially Segregated Location Premiums: Alternative Method for Assessing Residential Land Use Impact of Transportation Projects

Transportation Research Record: Journal of the Transportation Research Board, 2001

The corridor-level impact of a recent major urban highway reconstruction project on residential property values is investigated. The housing market encompassing the North Central Expressway corridor in Dallas, Texas, is examined. Hedonic property price models are estimated for each specific phase of the reconstruction project between 1979 and 1997. Five phases are considered. Geographic information system (GIS) tools, like buffering and geocoding, enable spatial segmentation of property sales and improved model specification facilitated by the creation of different types of proximity variables. An econometric refinement is made to traditional hedonic models that, in conjunction with GIS, allows an examination of spatiotemporal fluctuations in location premiums and property-value trends. The results show that some parts are negatively affected and others are positively affected. This finding is in agreement with the findings of earlier studies. However, this study adds to this conclu...

Estimating commercial property prices: an application of cokriging with housing prices as ancillary information

Journal of Geographical Systems, 2009

A vast majority of the recent literature on spatial hedonic analysis has been concerned with residential property values, with only very few examples of studies focused on commercial property prices. The dearth of studies can be attributed to some of the challenges faced in the analysis of commercial properties, in particular the scarcity of information compared to residential transactions. In order to address this issue, in this paper we propose the use of cokriging and housing prices as ancillary information to estimate commercial property prices. Cokriging takes into account the spatial autocorrelation structure of property prices, and the use of more abundant information on housing prices helps to improve the accuracy of property value estimates. A case study of Toledo in Spain, a city for which commercial activity stemming from tourism is one of the key elements of the economy in the city, demonstrates that substantial accuracy and precision gains can be obtained from the use of cokriging.