On the Use of Expert Opinion in Housing Quality Analysis: An Application of the "Five City Housing Survey"

Abstract

Quantifying the level of poor housing within the United States has traditionally been based on the use of combinatorial analysis of census-derived indicators of housing conditions. Units falling below a threshold value on each indicator are defined as being of poor quality. Housing experts from the U.S. Bureau of the Census have produced data showing that census variables, when used as housing quality indicators, must be viewed as random variables, not definitions. The paper that follows explains the use of combinatorial analysis where the indicators are recognized to be random variables. Based upon the results of the Five City Housing Survey of the U.S. Census, the level of error associated with a set of combinatorial rules is estimated and the principles needed to locate the optimal rule established.

Get full access to this article

View all access options for this article.

References

Baer, W.C. 1976. The Evolution of Housing Indicators and Housing Standards . Public Policy. 24(3):361-393.

Beaton, W.P. and Sossamon, L.B. 1982. Housing Integration and Rent Supplements to Existing Housing . Professional Geographer. 34:147,155.

Burchell, R.W. et al. 1983. Mount Laurell II: Challenge and Delivery of Low-Cost Housing. New Brunswick, NJ: Center for Urban Policy Research.

Clemmer, R.B. and Simonson, J.C. 1983. Trends in Substandard Housing 1940-1980. American Real Estate and Urban Economics Association. 10(4): 442-464.

DeNeufville, J.I. 1975. Social Indicators and Public Policy. New York: Elsevier.

Goedert, J.E. and Goodman, J.L., Jr. 1977. Indicators of the Quality of U. S. Housing. Washington, D.C.: The Urban Institute.

Goodman, J.L., Jr. 1978. Causes and Indicators of Housing Quality. Social Indicators Research 5. 195-210.

Kain, J.F. and Quigley, J.M. 1970. Evaluating the Quality of the Residential Environment . Environment and Planning. 2:23-32.

Kemeny, J.G. et al. 1962. Finite Mathematics. Englewood Cliffs, NJ Prentice-Hall.

10.

Krueckeberg, D.A. and Silvers, A.L. 1974. Urban Plannmg Analysis: Methods and Models. New York: Wiley.

11.

Naylor, C. 1982. How to Build an Inferencing Engine. In Expert Systems: Principles and Case Studies, ed. R. Forsyth. London: Chapman & Hall.

12.

Panhandle Regional Planning Commission. 1973 . Texas Panhandle Housing Survey. HUD Report No. HUD-TX-73-33.

13.

Phipps, A.A. and Feins, J.D. 1981. Measurement and Prediction of Housing Conditions and Rehabilitation Need. H U D Report No. HUD-0002186. Washington, D.C.. U.S. Government Printing Office.

14.

President's Housing Commission. 1908. See Subcommittee on Banking Currency and Housing, House of Representatives . In Evolution of Role of the Federal Government in Housmg and Community Development. 94th Congress, First Session. Washington, D.C.: U.S. Government Printing Office, 1975.

15.

Southern Burlington County NAACP v. Township of Mount Laurel. 1983. 92, N.J. 158, 456 A. nd 390 (usually referred to as Mount Laurel II decision).

16.

Sternlieb, G. 1973. The Sociology of Statistics: Measuring Substandard Housing . Public Data Use. 1 (31:1-6.

17.

Sumka, H.J. 1977. Measuring the Quality of Housing: An Econometric Analysis of Tax Appraisal Records. Land Economics. 53(3):298-309.

18.

U.S. Bureau of the Census. 1967. Measuring the Quality of Housing: An Appraisal of Census Statistics and Methods . Washington, D.C.: U.S. Government Printing Office.

19.

U.S. Department of Commerce. Bureau of Census . 1975. Five City Housing Survey.

20.

Weicher, J.C. ; Yap, L. ; and Jones, M.S. 1980. National Housing Needs and Quality Changes During the 1980s. Washington, D.C.: The Urban Institute.

21.

Wieand, K.F. 1978. Analysis of Multiple-Defect Indicators of Housing Quality with Data from the 1976 Annual Housing S u rvey. Annual Housing Survey Working Papers Report #1. Washington, D.C.: U.S. Department of Housing and Urban Development.