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Mass Appraisal: An Introduction to Multiple Regression Analysis for Real Estate Valuation

Journal of Real Estate Practice and Education,  2004  by Benjamin, John D,  Guttery, Randall S,  Sirmans, C F

Focus

This case study presents an introduction to the basics of real estate appraisal and multiple regression analysis; in particular, as used in real estate valuation for mass property tax assessment. While real estate researchers, appraisers and some tax assessors have used multiple regression analysis for many years, its use by a large number of assessors is relatively new. The purpose of this case is to expose students to standard appraisal approaches including the market comparison technique as well as the advantages and disadvantages of using multiple regression analysis. In their answers to the case, students are encouraged to explore and develop solutions, so as to understand how to use the market comparison approach and multiple regression analysis for real estate valuation.

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Setting

The real estate tax assessment process is used to provide an introduction to multiple regression analysis. The tax assessor's office in a small west Texas county has always assessed properties through manual market comparison analysis. This manual process uses recently sold properties that are in close proximity to the subject property to make corresponding weighted adjustments. After going to a seminar on multiple regression analysis for mass appraisals, the county tax assessor employs a university professor to explain how multiple regression analysis works for real estate valuation and mass assessment, as well as what its relative benefits are over the existing manual system. He invites his staff, the county commissioners, and others to a one-night seminar that explains multiple regression analysis. This seminar presented by a university professor to Texas participants is used educate case readers about real estate appraisal and multiple regression analysis.

Exhibits

Multiple regression handout presented in Appendix.

Availability

This case is available through the ARES clearing house.

Teaching Notes

Teaching Notes are available and emphasize the objectives that the students are expected to master. Generalized solutions for the case are included.

Introduction

This case study presents an overview of the basics of multiple regression analysis and illustrates its use in real estate valuation for mass property tax assessment. While real estate researchers, appraisers and some tax assessors have used this methodology for many years, its use by a large number of assessors is relatively new. Lusht (2001) suggests that multiple regression analysis ". . . can be used to value a large number of properties quickly and economically, which helps explain its (growing) popularity with tax assessors." The Appraisal of Real Estate (2001), published by The Appraisal Institute, offers an in-depth analysis of this methodology. Smith, Root, and Belloit (1995), Downing and Clark (1997), Allison (1998), Baldwin (1999), Betts and Ely (2001) and Ratterman (2001) investigate the worthiness of multiple regression analysis and its application to real estate valuation.

Background: Back to Texas with New Information

Mr. Austin Modano has recently returned from a business trip to the annual tax assessors' conference in Washington, D.C. Being the assessor of a small west Texas county, he is a bit in awe of the advances in software technology and statistical techniques being used by his counterparts around the country. In particular, he is intrigued by the use of multiple regression analysis to estimate real estate value for taxation purposes. His county has always assessed properties the old-fashioned way-through manual market comparison analysis of recently sold properties that are in close proximity to the subject property, a costly and time-consuming process. Furthermore, it requires hiring additional appraisers during the reassessment process and it is prone to human bias and error.

Changing from his county's assessment methodology to one using a multiple regression analysis for estimating value now seems preferable for several reasons. First, he realizes that in multiple regression analysis, data from all sales are utilized, rather than data from only three or four comparable properties that have sold recently. Appraiser bias with respect to choosing comparables or "comps," therefore, would be eliminated. Second, rather than "guesstimating" adjustments in magnitude and direction, the multiple regression software output statistically estimates the adjustments through the values and signs of the regression coefficients. In other words, having to calculate the magnitude (i.e., the dollar value) of each characteristic, such as a fireplace or a swimming pool's contributory value, would not be necessary. Unnecessary as well would be determining whether or not a characteristic is a positive or a negative attribute. In multiple regression analysis, the direction of the adjustment is determined simply by the sign of the coefficient from the regression equation's output. Last, matched pairs analysis-an appraisal technique used in the traditional market comparison approach-becomes unnecessary. Although switching to a statistical analysis methodology would be costly and may require staff training, the ease of mass appraisals for property tax assessments would largely overcome these costs in the long run. Local elected officials, however, would also have to be persuaded of the benefits for these changes.

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