Models for the analysis of multivariate spatial data are receiving increased attention these days. In many applications it will be preferable to work with multivariate spatial processes to specify such models. A critical specification in providing these models is the cross covariance function. Constructive approaches for developing valid cross-covariance functions offer the most practical strategy for doing this. These approaches include separability, kernel convolution or moving average methods, and convolution of covariance functions. We review these approaches but take as our main focus the computationally manageable class referred to as the linear model of coregionalization (LMC). We introduce a fully Bayesian development of the LMC. We offer clarification of the connection between joint and conditional approaches to fitting such models including prior specifications. However, to substantially enhance the usefulness of such modelling we propose the notion of a spatially varying LMC (SVLMC) providing a very rich class of multivariate nonstationary processes with simple interpretation. We illustrate the use of our proposed SVLMC with application to more than 600 commercial property transactions in three quite different real estate markets, Chicago, Dallas and San Diego. Bivariate nonstationary process models are developed for income from and selling price of the property.

Nonstationary Multivariate Process Modeling through Spatially Varying Coregionalization

Summary. Designation of historic districts is increasingly used as a tool to revive or halt the deterioration of central-city neighbourhoods. While historic designation is generally thought to have a positive impact on property values, evidence on this issue is mixed. One limitation of previous research is that it typically focuses on historic neighbourhoods in one city and thus bases its conclusions on a very limited sample. This study expands upon previous work by examining the effects of designation on property values across a larger set of cities. The study employs hedonic regression models to estimate housing prices in historic districts and comparable neighbourhoods in nine Texas cities. Results suggest that, in most cases, historic designation is associated with higher property values.

/pdf/historic-preservation-and-residential-property-values-an-nux75yrj1f.pdf

Historic Preservation and Residential Property Values: An Analysis of Texas Cities:

Valuation is often said to be “an art not a science” but this relates to the techniques employed to calculate value not to the underlying concept itself. Valuation is the process of estimating price in the market place. Yet, such an estimation will be affected by uncertainties. These input uncertainties will translate into an uncertainty with the output figure, the valuation. The degree of the uncertainties will vary according to the level of market activity; the more active a market, the more credence will be given to the input information. In the UK at the moment the Royal Institution of Chartered Surveyors (RICS) is considering ways in which the uncertainty of the valuation can be conveyed to the use of the valuation, but as yet no definitive view has been taken apart from a single Guidance Note (GN5). One of the major problems is that valuation models (in the UK) are based on comparable information and rely on single inputs. They are not probability‐based, yet uncertainty is probability driven. This paper discusses the issues underlying uncertainty in valuations and suggests a probability‐based model (using Crystal Ball) to address the shortcomings of the current model.

/pdf/the-uncertainty-of-valuation-2w0htnnek4.pdf

The uncertainty of valuation

A two-stage least squares model of housing prices is estimated with data collected from 3358 single-family home transactions. The results provide evidence for an optimal marketing period and indicate that a liquidity premium is priced in single-family home sales. Consistent with the hypothesis derived from economic search models, the model shows higher selling prices for houses having longer expected marketing periods. The model also shows a price premium for houses that sell faster than expectations. This effect supports the concept that liquidity is a value-enhancing characteristic.

Search and Liquidity in Single-Family Housing

Weak form tests of the efficiency of real estate investment markets

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Income Property Appraisal

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