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Information Producers and Valuation: Evidence from Real Estate Markets

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Abstract

This paper examines valuation and its relation to information production by licensed appraisers across real estate markets. The testable implications are discussed for either a peer monitoring or a crowding out effect in the data. The empirical model is estimated with data for all 50 US states and DC covering the sample period from 1999 to 2008. While analysis is primarily cross-sectional and not causal, the evidence is consistent with theory stating that the minimum quality associated with residential licensure standards may be too low. In contrast, the evidence suggests certified residential standards afford information producers the opportunity to signal or information consumers the ability to screen based on quality.

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Notes

  1. This work benefited from a number of excellent points raised by anonymous referees. We are particularly grateful to an anonymous referee’s suggestion that we augment our initial analysis of price-to-income with a, arguably, more theoretically appropriate price-to-rent ratio.

  2. See Jaffe (1988) for an evolutionary theory of trade associations with emphasis on real estate appraisers as information specialists.

  3. For example, Cole et al. (1986), Dietrich et al. (2000), Gwin and Maxam (2002), Gwin et al. (2006), Hendershott and Kane (1995), LaCour-Little and Malpezzi (2003), Lentz and Wang (1998), Muller and Reidl (2002), Rudolph (1998), Smolen and Hambleton (1997), Worzala et al. (1998).

  4. The count data that we assembled in this project differ somewhat from the summary data presented by the ASC. This difference is attributed to the fact that we control for duplicate records within a state.

  5. The summary statistics for certified general appraisers are not reported here to conserve space. They are available from the authors upon request. Since the number of all appraisers is the sum of licensed, certified residential and certified general appraisers, numbers reported in Panels B and C of Table 1 do not add up to the numbers reported in Panel A. The summary statistics for all appraisers by state for the sample period are reported in the Appendix.

  6. It is straightforward to show a house price to gross annual income ratio of 4 based on (a) 30% of income to housing cost underwriting, (b) nominal insurance and property taxes, (c) a fixed rate mortgage of 6% or higher, and (d) an 80% LTV.

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Acknowledgements

The authors gratefully acknowledge the research assistance of Kriroek Hemkamon and Ernest O’Boyle. We thank Austin Jaffe (our discussant), Manu Gupta, participants at The 2010 FSU Critical Issues in Real Estate Symposium, and two anonymous referees for helpful comments and suggestions. Güner acknowledges partial support of the Turkish Academy of Sciences, in the framework of the Young Scientist Award Program (EA-TÜBA-GEBİP/2001-1-1). Downs thanks The Kornblau Institute for support.

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Authors and Affiliations

  1. The Kornblau Institute, Virginia Commonwealth University, Snead Hall, 301 West Main Street, Richmond, VA, 23284-4000, USA

    David H. Downs

  2. Department of Business Administration, Middle East Technical University, Ankara, Turkey

    Z. Nuray Güner

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  1. David H. Downs
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  2. Z. Nuray Güner
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Correspondence to David H. Downs.

Appendix

Appendix

Table 6 Number of appraisers by states
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Downs, D.H., Güner, Z.N. Information Producers and Valuation: Evidence from Real Estate Markets. J Real Estate Finan Econ 44, 167–183 (2012). https://doi.org/10.1007/s11146-010-9294-8

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