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Real Estate Valuation Theory is organized around five categories of intellectual contribution to the whole-appraiser decision making and valuation accuracy, application of nontraditional appraisal techniques such as regression and the minimum-variance grid method, appraising contaminated property, ad valorem tax assessment, and new perspectives on traditional appraisal methods. One common thread is that all of the papers are exceptionally well written and thought provoking.



Appraiser Decision Making and Valuation Accuracy


Chapter 1. Behavioral Research into the Real Estate Valuation Process: Progress Toward a Descriptive Model

The Appraisal Institute (2001) prescribes an eight-step real estate valuation process in The Appraisal of Real Estate, 12th Edition (see Appendix A for a summary of this process).1 This process model, pioneered by George Schmutz (1941), has appeared in the Institute’s valuation text in various forms since the first edition was published in 1951. The Appraisal Institute’s valuation process is a normative model because it suggests how appraisers should proceed, step-by-step, when addressing a valuation problem. This model is a cookbook or recipe approach to valuation. However, expert appraisers, like master chefs, do not appear to follow a normative, systematic process or recipe.
Julian Diaz, J. Andrew Hansz

Chapter 2. Are Appraisers Statisticians?

Traditional hedonic pricing models, based upon an impressive corpus of statistical and economic theory, often exhibit prediction errors with a standard deviation in the range of 28–50%.1 In contrast, statistically challenged appraisers following ad hoc procedures often exhibit prediction errors with a standard deviation around 10%.2 The juxtaposition of these purported facts suggests the fruitfulness of examining elements of appraisal practice from a statistical perspective. In this vein Pace and Gilley (1998) showed the grid adjustment estimator employed by appraisers is a restricted version of the simultaneous autoregressive (SAR) estimator from spatial statistics. They suggest spatial statistics provides a unifying intellectual framework for reconciling appraisal practices with statistical theory.3
R. Kelley Pace, C. F. Sirmans, V. Carlos Slawson

Chapter 3. The Components of Appraisal Accuracy

In the past decade or so, there has been growing attention paid to the question of appraisal, or valuation, accuracy. Studies that encompass this question have principally been driven by concerns over how appraisal in accuracy may adversely affect the validity of appraisal-based real estate indices and of the portfolio management policies that draw inferences from them. Such studies have been pursued in the US (e.g. Webb, 1994; Fisher, Miles and Webb, 1999; Clayton, Geltner and Hamilton, 2000), the UK (e.g. Matysiak and Wang, 1995; Blundell and Ward, 1997; Drivers Jonas/IPD, 1997) and Australia (Parker, 1998; Newell and Kishore, 1998). Given the nature of the concerns, these studies have generally focused on commercial appraisals, especially of institutional grade real estate, although accuracy is a wider issue that surrounds all forms of appraisals.
Paul Gallimore

Regression, Minimum-Variance Grid Method, and Other Valuation Modeling Techniques


Chapter 4. An Investigation of Property Price Studies

Several delicate issues are connected to the question of how to compose scientific papers. A number of rules and guidelines apply — some interdisciplinary, others common for all sciences. The scientific policies of the academic journals, but also their space constraints, play an important role in forming the rules. Still, in several situations the question regarding what should be explained and interpreted explicitly and what may be left for the been discussed above, that can explain why it is reasonable not to find only “yes” answers to the questionnaire. In light of these objections, we find the overall result to be reasonably good. However, in two respects we found the results surprisingly poor, taking into account the emphasis that has been put on the topics in standard textbooks and earlier reviews.
Kicki Björklund, Bo Söderberg, Mats Wilhelmsson

Chapter 5. Comparison of the Accuracy of the Minimum-Variance Grid Method and the Least Squares Method — a Non-linear Extension

The Minimum-Variance Grid method developed by Vandell (1991) has laid down the theoretical foundation for the selection of a set of optimal weights for property valuation based on transaction prices of comparables. This method has also been shown by Lai and Way (1996) to be more accurate compared with valuation based on linear multiple regression. However, Lai and Wang’s results do not hold universally. The paper identifies the necessary and sufficient conditions for Lai and Wang’s results to hold.
Kwong Wing Chau, Wei Huang, Fung Fai Ng, Hin Man Louise Ng-Mak

Chapter 6. Error Trade-offs in Regression Appraisal Methods

This chapter presents a conceptualization of the problem of how many sales to use in a sales comparison method appraisal. We propose that the answer to this question depends on a tradeoff between different kinds of errors and is data dependent, varying across data sets. In hedonic regression appraisals, the law of large numbers does not necessarily hold. Increasing variance, omitted variables, and measurement errors in the sample may overwhelm the efficiency benefits of larger sample size. Heterogeneity within samples makes for the common problem of large standard errors in regression appraisal price predictions (Lenz & Wang, 1998) and suggests disaggregating data to improve the precision of price estimates. A “law of medium numbers” applies, meaning that heterogeneous data may yield smallest standard errors when subsets of data are used for estimates rather than the whole population of sales.
Max Kummerow, Hanga Galfalvy

Chapter 7. Automated Valuation Models

Traditional fee appraisers have welcomed the computer technology of databases, spreadsheets, and word processing. Even further, they have welcomed appraisal software which has reduced the clerical element of writing appraisal reports. However, the basic methods they follow in estimating value have not changed much in some time. In contrast, over the same period, assessors have quietly yet radically changed their valuation technology through application of computer aided mass assessment (CAMA) techniques. These techniques have improved the accuracy of mass appraisals while reducing their cost. As the price of computer power and automated data collection spirals downwards, could the application of CAMA techniques supplant traditional appraisal in other settings?1
R. Kelley Pace, C. F. Sirmans, V. Carlos Slawson

Chapter 8. A Note on the Hedonic Model Specification for Income Properties

The hedonic technique is well established as a tool for analysing the determinants of property prices on the market for single-family housing. The theoretical foundation is solid, including particularly the work by Rosen (1974), and there is a large body of empirical applications. There are fewer papers applying the technique to the investigation of market prices for income property; Miles, Cole, and Guilkey (1990), Fehribach, Rutherford, and Eakin (1993), Saderion, Smith, and Smith (1994), Colwell, Munneke, and Trefzger (1998).
Bo Söderberg

Chapter 9. Neural Network vs. Hedonic Price Model: Appraisal of High-Density Condominiums

In Hong Kong, high-density condominiums are routinely appraised by practitioners using the traditional comparative method. They collect a vast volume of transaction records, selecting suitable comparables from their data bank and then apply their professional judgment to adjust for any differences on factors such as view, orientation, area, floor height and market situation etc.
K. C. Wong, Albert T. P. So, Y. C. Hung

Appraising Contaminated Property


Chapter 10. Comparative Studies of United States, United Kingdom and New Zealand Appraisal Practice: Valuing Contaminated Commercial Real Estate

The late 1980s and early 1990s saw the development of official governmental concern about merging risks of ownership and threats to the investment value of sites affected by contamination. These concerns were prompted by the earlier discovery of negative impacts on property values associated with a number of high-profile sites around the world: Love Canal, New York and Times Beach, Missouri in the United States; Lekkerkerk in the Netherlands; and Seveso in Italy, for example. Owners of both residential and commercial/industrial properties in or near these sites suffered substantial financial losses as a result of on-site and nearby contamination that was identified.
William N. Kinnard, Elaine M. Worzala, Sandy G. Bond, Paul J. Kennedy

Chapter 11. Hedonic Modeling in Real Estate Appraisal: The Case of Environmental Damages Assessment

The literature regarding the use of hedonic pricing models in the real estate appraisal field is quite extensive (Freeman, 1979; Epple, 1987; Palmquist, 1992). While empirical studies using hedonic regression date back to the 1960’s, in 1974 Rosen published the seminal article regarding the theory which underlies hedonic pricing models.1 Over the years hedonic modeling has been applied to estimating the value of a wide range of economic and social amenities such as the value of nearby golf courses, properties with ocean views, and the impact of resort communities (Do and Grudnitski, 1995; Spahr and Sunderman, 1999; Rush and Bruggink, 2000) and dis-amenities such as proximity to landfills and environmental pollution (Harrison and Rubinfield, 1978; Li and Brown, 1980; Reichert, 1991).
Alan K. Reichert

Chapter 12. Do Market Perceptions Affect Market Prices? A Case Study of a Remediated Contaminated Site

“Stigma”,1 in relation to remediated contaminated land, is the price (value) reduction required to compensate investors for perceived financial risks2 and uncertainties3 associated with remediated contaminated property. Uncertainties relate to negative intangible factors such as: the inability to effect a total “cure”;4 the possibility of failure of the remediation method: the possibility of changes in legislation or remediation standards; difficulty in obtaining financing, or singly, a fear of the unknown. Post-remediation “stigma” equates to the difference in value between a remediated contaminated site and a comparable “clean” site with no history of contamination.5
Sandy G. Bond

Property Tax Assessment


Chapter 13. Valuation of Land Using Regression Analysis

Estimating the market value of vacant land is one of the more difficult tasks of current real estate appraisal. The problem applies equally to the appraisal of a single site or to the mass appraisal of land. Appraisal texts list several methods to use for this purpose. Regardless of the method chosen, however, when land sales are sparse, valuation may be reduced to an educated guess.
Mark A. Sunderman, John W. Birch

Chapter 14. Grid-Adjustment Approach — Modern Appraisal Technique

Appraisers can learn a great deal of information from government assessment reports, especially when the assessment is ideal. In Taiwan, property tax has been separated into land value tax and house tax. Land value tax revenue is the second largest tax revenue (next to the land value increment tax) for local government. The land value increment tax, which takes the increase in land price as the tax base, is very similar to the capital gain tax in the United States. In Taiwan the assessment of land declared price, which is the tax base of the land value tax, is neither efficient nor equitable. The objective of this study is to improve assessment for the land value tax base, which is a very significant data bank for appraisers.
Shwu-huei Huang

New Perspectives on Traditional Appraisal Methods


Chapter 15. The Unit-comparison Cost Approach in Residential Appraisal

The cost approach has not received much attention in academic journals. However, this lack of attention is undeserved. Cost functions represent one side of the market and may constrain the form of hedonic equations and the type of grid used in the market approach. Of course, cost functions can play a role in appraisals. A theory of cost functions is developed in this chapter. This theory accomplishes several purposes. First, it provides a link between unit-in-place costs and cost comparisons using square footage. Second, it provides the foundation for developing an alternative, non-tabular approach to cost estimation.
Peter F. Colwell, David W. Marshall

Chapter 16. The Long-run Equilibrium Relationship among Equity Capitalization Rates for Retail, Apartment, Office, and Industrial Real Estate

Under the income approach, the value of a property is found by discounting the property’s expected future net cash receipts to their present value. This process of converting a property’s expected future net operating income into an estimate of current market value by discounting is referred to as capitalization.
Michael Devaney

Chapter 17. A Fuzzy Discounted Cash Flow Analysis for Real Estate Investment

In a discounted cash flow (DCF) analysis, reliability and credibility of results are strictly dependent on the prediction of key input variables. There are two approaches at which these inputs can be rigorously determined. The first approach involves the use of standard statistical tools such as the multiple regression analysis and the Box-Jenkin’s time series models. These tools are not foolproof and are fettered by inherent statistical weaknesses. Based on probabilistic assumptions, results of the statistical analysis are bounded by occurrences of ex-post random events or observations. In a complex world, randomness alone is insufficient to capture dynamics and changes in real world events. Ex-ante expert judgement of events in a near future,1 which does not rely on probabilities of ex-post events or information, offers an alternative way to arrive at a prediction of the input variables.
Tien Foo Sing, David Kim Hin Ho, Danny Poh Huat Tay

Chapter 18. Real Options and Real Estate: A Review and Valuation Illustration

The traditional capital budgeting and valuation framework for a land development investment opportunity involves determining the project’s net present value (NPV). The first step in an NPV analysis is to forecast cash flows over time and discount these cash flows at the appropriate required rate-of-return, where the required rate-of-return is based on the systematic risk of these cash flows. The NPV is the difference between the present value of the expected future cash inflows and the present value of the expected cost outflows. When the NPV is zero or positive, the project is accepted. When the NPV is negative, the project is rejected.
Steven H. Ott


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