Contract Price Confirmation Bias: Evidence from Repeat Appraisals

  • Michael D. EriksenEmail author
  • Hamilton B. Fout
  • Mark Palim
  • Eric Rosenblatt


Prior research has argued that upwardly biased appraised values of residential properties were a contributing factor of the 2008 financial crisis. Subsequent reforms have been enacted to reduce appraiser’s financial incentives to submit biased appraisals, but appraisers continue to receive the contract price of pending home sales. This knowledge may lead them to subconsciously interpret and select information to confirm the contract price exposing the economy to future crises. A novel data series of properties that were appraised twice within six months where one appraiser was uninformed of the contract price is used to test how appraisal practices differ when prices are known. Significant differences were found in the property descriptions and the selection, price adjustment, and weighting of comparable transactions for appraisers aware of the contract price. Appraisers aware of contract price were more than twice as likely to reach an appraised value at least equal to contract price; on average their valuations were 4.2%-to-8.3% higher than appraisers unaware of contract prices.


Mortgage loans Collateral Appraisal bias Financial crisis 

JEL Classifications

G21 G28 K11 L85 R31 



The authors would like to thank Bob Barclay, Luke Wong, Jesse Staal, Ruwei Wang, and Weifeng Wu for excellent research assistance. They would also like to thank Lynn Fisher, Lan Shi, Lauren Lambie-Hanson, Doug Duncan and Pete Bakel for helpful discussions throughout the research project. Views expressed in the paper do not represent official position of Fannie Mae or any other employer. All remaining errors are our own.


  1. Agarwal, S., Ben-David, I., & Yao, V. (2015). Collateral valuation and borrower financial constraints: Evidence from the residential real estate market. Management Science, 61(9), 2220–2240.CrossRefGoogle Scholar
  2. Ben-David, I. (2011). Financial constraints and inflated home prices during the real estate boom. American Economic Journal: Applied Economics, 3, 55–67.Google Scholar
  3. Calem, P., Lambie-Hanson, L., & Nakamura, L. (2015). Information losses in home purchase appraisals. Working Paper, Federal Reserve Bank of Philadelphia, 2015, Q1.Google Scholar
  4. Ding, L., & Nakamura, L. (2016). The impact of the home valuation code of conduct on appraisal and mortgage outcomes. Real Estate Economics, 44(3), 658–690.CrossRefGoogle Scholar
  5. Elul, R., Souleles, N., Chmosisenghpert, S., Glennon, D., & Hunt, R. (2010). What Triggers Mortgage Default? American Economic Review Papers and Proceedings, 100(2), 490–494.CrossRefGoogle Scholar
  6. Eriksen, Michael D., Hamilton Fout, Mark Palim, and Eric Rosenblatt, 2018. The effect of contract prices and relationships on appraisal Bias, Journal of Urban Economics, forthcoming.Google Scholar
  7. Foote, C., Gerardi, K., & Willen, P. (2008). Negative equity and foreclosure: Theory and evidence. Journal of Urban Economics, 64(2), 234–245.CrossRefGoogle Scholar
  8. Fout, H., & Yao, V. (2016). Housing market effects of appraising below contract. Fannie Mae Housing Whitepaper: Working Paper.Google Scholar
  9. Mayer, C., Pence, K., & Sherlund, S. (2009). The rise in mortgage defaults. Journal of Economic Perspectives, 23(1), 27–50.CrossRefGoogle Scholar
  10. Nakamura, L. (2010). How much is that home really worth? Appraisal Bias and Home-Price Uncertainty, Business Review, Federal Reserve Bank of Philadelphia, 2010, Q1.Google Scholar
  11. Shi, L., & Zhang, Y. (2015). Appraisal inflation: Evidence from the 2009 GSE HVCC intervention. Journal of Housing Economics, 27, 71–90.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Finance and Real Estate; Lindner College of BusinessUniversity of CincinnatiCincinnatiUSA
  2. 2.Fannie MaeWashingtonUSA
  3. 3.Department of EconomicsKansas State UniversityManhattanUSA

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