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The Effect of Listing Price Strategy on Transaction Selling Prices

Abstract

While true underlying home values are expected to be randomly distributed, actual residential listing prices tend to be highly clustered. Particularly, more than 75 % of the homes in our sample are associated with a round or “just below” round asking price. This study provides a theoretical and empirical examination of how the thousands digit in a home’s asking price is related to the final transaction price relative to its true underlying value. Our findings suggest that, on average, homes listed using a “just below” pricing strategy are associated with the greatest discount negotiated relative to the asking price. However, the higher initial degree of list overpricing reflected in “just below” pricing compared with other strategies more than offsets the greater discount. Therefore, “just below” is the most effective pricing strategy for the seller in terms of a greater dollar yield relative to value. These empirical findings have economic significance and are robust across both “buyer” and “seller” housing markets, new versus existing homes, and across multiple home price ranges.

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Notes

  1. 1.

    As a robustness test, we also examine the effect of the ten-thousands and hundreds digits on discount and the degree of overpricing. We find no evidence that these digits are related to the negotiated price discount or settlement price relative to the underlying value of the house. For brevity, these results are omitted from this version of the paper.

  2. 2.

    In Australia, coins smaller than 5 cents have not been used since 1992, yet still today, prices continue to be listed in fractions (such as $3.98) for which proper change cannot be given.

  3. 3.

    Only 3 % of prices end in a “1, 2, 3, 4, 6, 7, or 8.”

  4. 4.

    Datasets in both studies ended before both the dramatic run up and precipitous decline in the most recent real estate markets.

  5. 5.

    If the seller employs a real estate agent to market and sell their home, the real estate agent will often provide their own opinion to the seller about the home’s fair market value.

  6. 6.

    Constrained sellers, such as underwater sellers, may be forced to price at a certain level and only accept an offer that is above this threshold, regardless of the value of their home.

  7. 7.

    The reservation price for a home is often a mental threshold (Seiler et al. 2008) and therefore sellers are more likely to set a round reservation price. As a result, a reservation price such as $190,000 is more likely than $188,000, which is more likely than a reservation price of $188,392, for example.

  8. 8.

    For robustness, we repeat this analysis for the ten-thousands and hundreds digit. We find no evidence on the relation between these two order digits and discount that can be supported with statistical significance. For brevity we exclude these results from this version of the paper.

  9. 9.

    For example, if a particular house was on the market for 78 days before it was sold, TOM will be assigned a value of 2.56 (78/365*12).

  10. 10.

    We also used other specifications instead of Eq. (5), and the overall results were largely unaffected. For brevity, we exclude all other specification from this version of the paper.

  11. 11.

    As a robustness check, alternative hedonic model specifications were tested and generally yielded similar results.

  12. 12.

    Once again, for robustness, we repeat this analysis for the ten-thousands and hundreds digits. We find no evidence on the relation between these two order digits and the degree of overpricing that can be supported with statistical significance. For brevity, we exclude these results from this version of the paper.

  13. 13.

    The standard deviation of the thousands digit number frequency for new construction is 4.95 % compared with 11.24 % for existing homes.

References

  1. Allen, M., & Dare, W. (2004). The effects of charm listing prices on house transaction prices. Real Estate Economics, 32(4), 695–713.

    Article  Google Scholar 

  2. Allen, M., & Dare, W. (2006). Charm pricing as a signal of listing price precision. Journal of Housing Research, 15(2), 113–127.

    Google Scholar 

  3. Anglin, P., Rutherford, R., & Springer, T. (2003). The trade-off between the selling price of residential properties and time-on-the-market: the impact of price setting. Journal of Real Estate Finance and Economics, 26(1), 95–111.

    Article  Google Scholar 

  4. Arnold, M. (1999). Search, bargaining and optimal asking prices. Real Estate Economics, 27(3), 453–481.

    Article  Google Scholar 

  5. Bhattacharya, U., Holden, C., & Jacobsen, S. (2012). Penny wise, dollar foolish: Buy-sell imbalances on and around round numbers. Management Science, 58(2), 413–431.

    Article  Google Scholar 

  6. Black, R., & Diaz, J. (1996). The use of information versus asking price in the real property negotiation process. Journal of Property Research, 13(4), 287–297.

    Article  Google Scholar 

  7. Deng, Y., Gabriel, S., Nishimura, K., & Zheng, D. (2013). Optimal pricing strategy in the case of price dispersion: new evidence from Tokyo housing market. Real Estate Economics, 40(5), forthcoming.

  8. Friedman, L. (1967). In A. Phillips & O. E. Williamson (Eds.), Psychological pricing in the food industry, in prices: Issues in theory, practice, and public policy (pp. 187–201). Philadelphia: University of Pennsylvania Press.

    Google Scholar 

  9. Gendall, P., Holdershaw, J., & Garland, R. (1997). The effect of odd pricing on demand. European Journal of Marketing, 31(11/12), 799–813.

    Article  Google Scholar 

  10. Gilmour, J. (1985). One cent less doesn’t make sense. Australian Business, March 20, 34.

  11. Haurin, D. (1988). The duration of marketing time of residential housing. Journal of the American Real Estate and Urban Economics Association, 16(4), 397–410.

    Article  Google Scholar 

  12. Haurin, D., Haurin, J., Nadauld, T., & Sanders, A. (2010). List prices, sale prices, and marketing time: an application to U.S. housing markets. Real Estate Economics, 38(4), 659–685.

    Article  Google Scholar 

  13. Hogl, S. (1988). The effects of simulated price changes on consumers in a retail environment-price thresholds and price policy. Lisbon: Esomar Congress Proceedings.

    Google Scholar 

  14. Holdershaw, J., Gendall, P., & Garland, R. (1997). The widespread use of odd pricing in the retail sector. Marketing Bulletin, 8(1), 53–58.

    Google Scholar 

  15. Horowitz, J. (1992). The role of list price in housing markets: theory and an econometric model. Journal of Applied Econometrics, 7(2), 115–129.

    Article  Google Scholar 

  16. Knight, J., Sirmans, C., & Turnbull, G. (1994). List price signaling and buyer behavior in the housing market. Journal of Real Estate Finance and Economics, 9(3), 177–192.

    Article  Google Scholar 

  17. Miller, N., & Sklarz, M. (1987). Pricing strategies and residential property selling prices. Journal of Real Estate Research, 2(1), 31–40.

    Google Scholar 

  18. Northcraft, G., & Neale, M. (1987). Experts, amateurs, and real estate: an anchoring-and-adjustment perspective on property pricing decisions. Organizational Behavior and Human Decision Processes, 39(1), 84–97.

    Article  Google Scholar 

  19. Palmon, O., Smith, B., & Sopranzetti, B. (2004). Clustering in real estate prices: determinants and consequences. Journal of Real Estate Research, 26(2), 115–136.

    Google Scholar 

  20. Rudolph, H. (1954). Pricing for today’s market. Printers Ink, 28, 22–24.

    Google Scholar 

  21. Schindler, R., & Kibarian, T. (1996). Increased consumer sales response through use of 99-ending prices. Journal of Retailing, 72(2), 187–200.

    Article  Google Scholar 

  22. Schindler, R., & Kirby, P. (1997). Patterns of rightmost digits used in advertised prices: implications for nine-ending effects. Journal of Consumer Research, 24(2), 192–201.

    Article  Google Scholar 

  23. Schindler, R., & Wiman, A. (1989). Effects of odd pricing on price recall. Journal of Business Research, 19(4), 165–177.

    Article  Google Scholar 

  24. Seiler, M., Seiler, V., Traub, S., & Harrison, D. (2008). Regret aversion and false reference points in residential real estate. Journal of Real Estate Research, 30(4), 461–474.

    Google Scholar 

  25. Seiler, M., Madhavan, P., & Liechty, M. (2012). Toward an understanding of real estate homebuyer internet search behavior: an application of ocular tracking technology. Journal of Real Estate Research, 34(2), 211–241.

    Google Scholar 

  26. Stiving, M., & Winer, R. (1997). An empirical analysis of price endings with scanner data. Journal of Consumer Research, 24(1), 57–68.

    Article  Google Scholar 

  27. Yavas, A., & Yang, S. (1995). The strategic role of listing price in marketing real estate: theory and evidence. Real Estate Economics, 23(3), 347–368.

    Article  Google Scholar 

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Acknowledgments

We would like to thank Oded Palmon, Ben Sopranzetti, Paul Anglin, and Tom Springer for comments on earlier drafts of this study. We also wish to thank the Virginia Association of Realtors® (VAR) for access to their sample of homeowners for the experimental component of this study. We specifically acknowledge the special assistance of Stacey Ricks at VAR. We would also like to thank Real Estate Information Network (REIN) in Hampton Roads, Virginia for providing transactions data for the empirical aspect of this study. All errors and omissions remain our own.

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Correspondence to Michael J. Seiler.

Appendix: Definition of Variables

Appendix: Definition of Variables

sqft:

Living area of the house measured in square feet

age:

Age of the house measured in years

bedroom:

Number of bedrooms in the house

bath:

Number of bathrooms in the house

halfbath:

Number of half bathrooms in the house

dumyear_i:

Dummy variable indicating the year during which the transaction took place. i can take an integer value between 1994 and 2011.

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Beracha, E., Seiler, M.J. The Effect of Listing Price Strategy on Transaction Selling Prices. J Real Estate Finan Econ 49, 237–255 (2014). https://doi.org/10.1007/s11146-013-9424-1

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Keywords

  • List pricing strategies
  • Time on the market
  • Residential real estate