# Using Revisions as a Measure of Price Index Quality in Repeat-Sales Models

- 18 Downloads

## Abstract

Repeat-sales indexes are the most widely used type of transaction based property price indexes. However, such indexes are particularly prone to revision. When a new period of transaction data becomes available and is used to update the repeat-sales model, all past index values can potentially be revised. These revisions are especially problematical for commercial real estate (as compared to housing), due to the relative scarcity of transaction data and the heterogeneity of the underlying properties. From a methodological perspective, the magnitude of the revisions is a particularly useful measure of the index quality, as it directly reflects both the precision of the index and its practical usefulness in economic and business applications. This paper focuses on index revisions in thin, commercial property markets, the type of market that is most challenging. We present multiple specifications of the repeat-sales model (both existing and new), seeking to reduce revisions. We are able to reduce overall index revisions by more than 50%, compared to more traditional repeat-sales models.

## Keywords

Commercial real estate Markov chained Monte Carlo Property price indexes State space models## Notes

### Acknowledgements

We would like to thank the attendees at the Property Indices session of the 2017 international AREUEA conference in Amsterdam and at the 2016 Hoyt meeting in West Palm Beach. Specifically, we would like to thank Daniel Melser and Martijn Dröes whom both discussed the paper. We also want to thank Real Capital Analytics for providing the data and insights that made this study possible. The comments and observations by Jim Sempere, Elizabeth Szep and Willem Vlaming at Real Capital Analytics were especially appreciated. Finally, we would like to thank the anonymous referee for his comments on this paper.

## References

- Abraham, J.M., & Schauman, W.S. (1991). New evidence on home prices from Freddie Mac repeat sales.
*Real Estate Economics*,*19*(3), 333–352.CrossRefGoogle Scholar - Bailey, M.J., Muth, R.F., Nourse, H.O. (1963). A regression method for real estate price index construction.
*Journal of the American Statistical Association*,*58*, 933–942.CrossRefGoogle Scholar - Barkham, R., & Geltner, D.M. (1995). Price discovery in American and British property markets.
*Real Estate Economics*,*23*(1), 21–44.CrossRefGoogle Scholar - Betancourt, M., & Girolami, M. (2015). Hamiltonian Monte Carlo for hierarchical models.
*Current trends in Bayesian methodology with applications*,*79*, 30.Google Scholar - Bokhari, S., & Geltner, D. (2012). Estimating real estate price movements for high frequency tradable indexes in a scarce data environment.
*The Journal of Real Estate Finance and Economics*,*45*(2), 522–543.CrossRefGoogle Scholar - Bokhari, S., & Geltner, D.M. (2011). Loss aversion and anchoring in commercial real estate pricing: empirical evidence and price index implications.
*Real Estate Economics*,*39*(4), 635–670.CrossRefGoogle Scholar - Bourassa, S.C., Cantoni, E., Hoesli, M. (2013). Robust repeat sales indexes.
*Real Estate Economics*,*41*(3), 517–541.CrossRefGoogle Scholar - Brooks, S.P., & Gelman, A. (1998). General methods for monitoring convergence of iterative simulations.
*Journal of Computational and Graphical Statistics*,*7*(4), 434–455.Google Scholar - Carpenter, B., Gelman, A., Hoffman, M., Lee, D., Goodrich, B., Betancourt, M., Brubaker, M.A., Guo, J., Li, P., Riddell, A. (2017). Stan: a probabilistic programming language.
*Journal of Statistical Software*,*76*(1), 1–32.CrossRefGoogle Scholar - Case, K.E., & Shiller, R.J. (1987). Prices of single family homes since 1970: new indexes for four cities. New England Economic Review, 45–56.Google Scholar
- Case, K.E., & Shiller, R.J. (1989). The efficiency of the market of single-family homes.
*The American Economic Review*,*79*, 125–137.Google Scholar - Case, K.E., & Shiller, R.J. (1990). Forecasting prices and excess returns in the housing market.
*Real Estate Economics*,*18*(3), 253–273.CrossRefGoogle Scholar - Clapham, E., Englund, P., Quigley, J.M., Redfearn, C.L. (2006). Revisiting the past and settling the score: index revision for house price derivatives.
*Real Estate Economics*,*34*, 275–302.CrossRefGoogle Scholar - Clapp, J.M., & Giaccotto, C. (1999). Revisions in repeat-sales price indexes: here today, gone tomorrow.
*Real Estate Economics*,*27*, 79–104.CrossRefGoogle Scholar - Clements, M.P., & Galvão, A. B. (2017). Predicting early data revisions to us gdp and the effects of releases on equity markets.
*Journal of Business & Economic Statistics*,*35*, 1–18.CrossRefGoogle Scholar - De Wit, E.R., Englund, P., Francke, M.K. (2013). Price and transaction volume in the Dutch housing market.
*Regional Science and Urban Economics*,*43*(2), 220–241.CrossRefGoogle Scholar - Deng, Y., & Quigley, J.M. (2008). Index revision, house price risk, and the market for house price derivatives.
*The Journal of Real Estate Finance and Economics*,*37*(3), 191–209.CrossRefGoogle Scholar - Durbin, J., & Koopman, S.J. (2012).
*Time series analysis by state space methods*Vol. 2. Oxford: Oxford Univ Press.CrossRefGoogle Scholar - Fisher, J., Gatzlaff, D., Geltner, D.M., Haurin, D. (2003). Controlling for the impact of variable liquidity in commercial real estate price indices.
*Real Estate Economics*,*31*(2), 269–303.CrossRefGoogle Scholar - Francke, M.K. (2010). Repeat sales index for thin markets: a structural time series approach.
*Journal of Real Estate Finance and Economics*,*41*, 24–52.CrossRefGoogle Scholar - Francke, M.K. (2017). Repeat sales models, holding periods and index revision. The Hoyt Group; May 2017 50th Anniversary Program Presentations.Google Scholar
- Francke, M.K., & De Vos, A.F. (2000). Efficient computation of hierarchical trends.
*Journal of Business and Economic Statistics*,*18*, 51–57.Google Scholar - Francke, M.K., & van de Minne, A. (2017). The hierarchical repeat sales model for granular commercial real estate and residential price indices.
*The Journal of Real Estate Finance and Economics*,*55*(4), 511–532.Google Scholar - Gatzlaff, D.H., & Geltner, D.M. (1998). A transaction-based index of commercial property and its comparison to the NCREIF index.
*Real Estate Finance*,*15*(1), 7–22.Google Scholar - Gelman, A., & Rubin, D.B. (1992). Inference from iterative simulation using multiple sequences.
*Statistical Science*,*7*, 457–72.CrossRefGoogle Scholar - Geltner, D., & Mei, J. (1995). The present value model with time-varying discount rates: implications for commercial property valuation and investment decisions.
*The Journal of Real Estate Finance and Economics*,*11*(2), 119–135.CrossRefGoogle Scholar - Geltner, D.M., & de Neufville, R. (2017). Flexibility and real estate valuation under uncertainty. A practical guide for developers. Wiley Blackwell. Available at SSRN: https://ssrn.com/abstract=2998832.
- Geltner, D.M., Francke, M.K., Shimizu, C., Fenwick, D., Baran, D. (2017). Commercial property price indicators: sources, methods and issues. Eurostat.Google Scholar
- Geltner, D.M., MacGregor, B.D., Schwann, G.M. (2003). Appraisal smoothing and price discovery in real estate markets.
*Urban Studies*,*40*(5-6), 1047–1064.CrossRefGoogle Scholar - Geltner, D.M., Miller, N.G., Clayton, J., Eichholtz, P.M.A. (2014).
*Commercial real estate, analysis & investments*Vol. 4. Boston: Cengage Learning.Google Scholar - Genesove, D., & Mayer, C. (2001). Loss aversion and seller behavior: evidence from the housing market.
*The Quarterly Journal of Economics*,*116*(4), 1233–1260.CrossRefGoogle Scholar - Goetzmann, W.N. (1992). The accuracy of real estate indices: repeat sale estimators.
*Journal of Real Estate Finance and Economics*,*5*, 5–53.CrossRefGoogle Scholar - Guo, X., Zheng, S., Geltner, D.M., Liu, H. (2014). A new approach for constructing home price indices: the pseudo repeat sales model and its application in China.
*Journal of Housing Economics*,*25*, 20–38.CrossRefGoogle Scholar - Harvey, A. (1989).
*Forecasting structural time series models and the kalman filter*. Cambridge: Cambridge University Press.Google Scholar - Hegde, S.P., & McDermott, J.B. (2003). The liquidity effects of revisions to the S&P 500 index: an empirical analysis.
*Journal of Financial Markets*,*6*(3), 413–459.CrossRefGoogle Scholar - Hoffman, M.D., & Gelman, A. (2014). The no-U-turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo.
*Journal of Machine Learning Research*,*15*(1), 1593–1623.Google Scholar - Koehler, E., Brown, E., Haneuse, S.J.P.A. (2009). On the assessment of Monte Carlo error in simulation-based statistical analyses.
*The American Statistician*,*63*(2), 155–162.CrossRefGoogle Scholar - Link, W.A., & Eaton, M.J. (2012). On thinning of chains in MCMC.
*Methods in Ecology and Evolution*,*3*(1), 112–115.CrossRefGoogle Scholar - Lunn, D., Jackson, C., Best, N., Thomas, A., Spiegelhalter, D. (2013).
*The BUGS Book; A practical introduction to bayesian analysis*. Boca Raton: CRC Press.Google Scholar - McMillen, D.P., & Thorsnes, P. (2006). Housing renovations and the quantile repeat-sales price index.
*Real Estate Economics*,*34*(4), 567–584.CrossRefGoogle Scholar - Plummer, M. (2003). JAGS: a Program for analysis of Bayesian graphical models using Gibbs sampling. In: Proceedings of the 3rd internation workshop on distributed statistical computing, pp. 124.Google Scholar
- Quan, D.C., & Quigley, J.M. (1991). Price formation and the appraisal function in real estate markets.
*The Journal of Real Estate Finance and Economics*,*4*(2), 127–146.CrossRefGoogle Scholar - Schwann, G.M. (1998). A real estate price index for thin markets.
*Journal of Real Estate Finance and Economics*,*16*, 269–287.CrossRefGoogle Scholar - Shiller, R.J. (1981). Do stock prices move too much to be justified by subsequent changes in dividends?
*American Economic Review*,*71*, 421–436.Google Scholar - Shiller, R.J. (1993).
*Macro Markets, Creating institutions for managing society’s largest economic risks*. Oxford: Oxford University Press.Google Scholar - Shrestha, M.L., & Marini, M. (2013). Quarterly GDP revisions in G-20 countries: evidence from the 2008 financial crisis. IMF Working Paper (13/60).Google Scholar
- Vehtari, A., Gelman, A., Gabry, J. (2016). Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC.
*Statistics and Computing*,*27*, 1–20.Google Scholar - Watanabe, S. (2010). Asymptotic equivalence of Bayes cross validation and widely applicable information criterion in singular learning theory.
*Journal of Machine Learning Research*,*11*(Dec), 3571–3594.Google Scholar - Yu, K., & Moyeed, R.A. (2001). Bayesian quantile regression.
*Statistics & Probability Letters*,*54*(4), 437–447.CrossRefGoogle Scholar