Risk Assessment Steeplechase: Hurdles to Becoming a Target Market
Framed in a quadrant model, the data sources that analysts use to predict the performance of core property types for the major metropolitan areas in the United States are reviewed. The hypothesis is that forecasters rely on information from the economic base, the property inventory and financial performance quadrants to generate forecasts. For each core property type, analysts are rather homogeneous in grouping metropolitan areas from best to worst. However, the property type determines what sets of economic, social, inventory and market information are used. The only consistent forecast factor used across all property types appears to be economic growth.
Volume (Year): 17 (1999)
Issue (Month): 2 ()
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References listed on IDEAS
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- Joseph Gyourko & Donald B. Keim, . "What Does the Stock Market Tell Us About Real Estate Returns? (Revision of 18-91) (Reprint 030)," Rodney L. White Center for Financial Research Working Papers 11-92, Wharton School Rodney L. White Center for Financial Research.
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NBER Working Papers
3120, National Bureau of Economic Research, Inc.
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"Clustering Methods for Real Estate Portfolios,"
Real Estate Economics,
American Real Estate and Urban Economics Association, vol. 23(3), pages 271-310.
- In Jae Myung & Sridhar Ramamoorti & Andrew D. Bailey, Jr., 1996. "Maximum Entropy Aggregation of Expert Predictions," Management Science, INFORMS, vol. 42(10), pages 1420-1436, October.
- Joseph Gyourko & Donald B. Keim, 1992. "What Does the Stock Market Tell Us About Real Estate Returns?," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 20(3), pages 457-485.
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