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New Evidence on Home Prices from Freddie Mac Repeat Sales

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  • Jesse M. Abraham
  • William S. Schauman

Abstract

The weighted repeat sales price index methodology recently reported in Case and Shiller [5][6] is applied to a dataset of over eight million loans bought by the Federal Home Loan Mortgage Corporation over the last twenty years. Regional price indices are reported and compared to indices from other sources. Statistical issues in the creation of the index, both technical and due to sample selectivity of the Freddie Mac dataset, are extensively discussed. It is found that the new index grows at a rate similar to other indices up until 1985, after which time it grows at a significantly higher rate. Copyright American Real Estate and Urban Economics Association.

Suggested Citation

  • Jesse M. Abraham & William S. Schauman, 1991. "New Evidence on Home Prices from Freddie Mac Repeat Sales," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 19(3), pages 333-352.
  • Handle: RePEc:bla:reesec:v:19:y:1991:i:3:p:333-352
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    1. John Cotter, 2005. "Uncovering long memory in high frequency UK futures," The European Journal of Finance, Taylor & Francis Journals, pages 325-337.
    2. Lamoureux, Christopher G & Lastrapes, William D, 1990. " Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-229, March.
    3. Lobato, Ignacio N & Savin, N E, 1998. "Real and Spurious Long-Memory Properties of Stock-Market Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 261-268, July.
    4. Scholes, Myron & Williams, Joseph, 1977. "Estimating betas from nonsynchronous data," Journal of Financial Economics, Elsevier, vol. 5(3), pages 309-327, December.
    5. Don Bredin & Gerard O’Reilly & Simon Stevenson, 2007. "Monetary Shocks and REIT Returns," The Journal of Real Estate Finance and Economics, Springer, vol. 35(3), pages 315-331, October.
    6. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    7. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, pages 3-30.
    8. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, pages 83-106.
    9. Diebold, Francis X. & Rudebusch, Glenn D., 1989. "Long memory and persistence in aggregate output," Journal of Monetary Economics, Elsevier, pages 189-209.
    10. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, pages 151-184.
    11. Breidt, F. Jay & Crato, Nuno & de Lima, Pedro, 1998. "The detection and estimation of long memory in stochastic volatility," Journal of Econometrics, Elsevier, pages 325-348.
    12. John Cotter & Simon Stevenson, 2006. "Multivariate Modeling of Daily REIT Volatility," The Journal of Real Estate Finance and Economics, Springer, pages 305-325.
    13. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July.
    14. Andersen, Torben G & Bollerslev, Tim, 1997. " Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long-Run in High Frequency Returns," Journal of Finance, American Finance Association, vol. 52(3), pages 975-1005, July.
    15. Ding, Zhuanxin & Granger, Clive W. J., 1996. "Modeling volatility persistence of speculative returns: A new approach," Journal of Econometrics, Elsevier, pages 185-215.
    16. Robert T. Kleiman & James E. Payne & Anandi P. Sahu, 2002. "Random Walks and Market Efficiency: Evidence from International Real Estate Markets," Journal of Real Estate Research, American Real Estate Society, vol. 24(3), pages 279-298.
    17. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, pages 5-59.
    18. Baillie, Richard T. & DeGennaro, Ramon P., 1990. "Stock Returns and Volatility," Journal of Financial and Quantitative Analysis, Cambridge University Press, pages 203-214.
    19. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    20. Engle, Robert F & Ng, Victor K, 1993. " Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    21. Andersen, Torben G. & Bollerslev, Tim, 1997. "Intraday periodicity and volatility persistence in financial markets," Journal of Empirical Finance, Elsevier, pages 115-158.
    22. Simon Stevenson, 2002. "Momentum Effects and Mean Reversion in Real Estate Securities," Journal of Real Estate Research, American Real Estate Society, vol. 23(1/2), pages 47-64.
    23. Deo, Rohit S. & Hurvich, Clifford M., 2001. "On The Log Periodogram Regression Estimator Of The Memory Parameter In Long Memory Stochastic Volatility Models," Econometric Theory, Cambridge University Press, vol. 17(04), pages 686-710, August.
    24. Devaney, Michael, 2001. "Time varying risk premia for real estate investment trusts: A GARCH-M model," The Quarterly Review of Economics and Finance, Elsevier, vol. 41(3), pages 335-346.
    25. Dacorogna, Michael M. & Muller, Ulrich A. & Nagler, Robert J. & Olsen, Richard B. & Pictet, Olivier V., 1993. "A geographical model for the daily and weekly seasonal volatility in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 12(4), pages 413-438, August.
    26. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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