Sam Copeland July 31st, 2007 GISC 6387 Census vs. Appraisal Sam Copeland July 31st, 2007 GISC 6387

Objective and Hypothesis Objectives To determine what differences if any exist between the US Census records of housing value and the Dallas County Appraisal District’s records of housing value. To analyze and explain any differences that occur. Hypothesis There may be large discrepancies between individual records, but the overall datasets should be relatively comparable.

Existing Literature Two key articles Kish, L; Lansing, J. Response Errors in Estimating the Value of Homes. Journal of the American Statistical Association. Vol. 49, No. 267. (Sep., 1954), pp. 520-538. Kain, J; Quigley, J. Notes on Owner’s Estimates of Housing Values (in Applications). Journal of the American Statistical Association. Vol. 67, No. 340. (Dec., 1972), pp. 803-806.

Existing Literature, cont. Research focused on sample groups with less than 600 observations. Very large response errors are noted, but they were observed to be “offsetting.”(Kish, Lansing) Net errors were small (less than 4%). There are systematic differences based on socioeconomic characteristics.(Kain, Quigley)

Data Sources Block group shapefiles from the 1990 and 2000 US Census Dallas County Appraisal District parcel data for 2000 NCTCOG city limit and roads shapefiles for Dallas County House Price Indexes from the Office of Federal Housing Enterprise Oversight GDP percentage growth records from the Bureau of Economic Analysis

Census Housing Values Census Housing Values

Census Housing Values Collected on the long form questionnaire Grouped by range value Aggregated to the block group level Freely and easily available Based on likely subjective evaluations

Appraisal Housing Values Produced by the Dallas County Appraisal District Produced for the purposes of taxes Uses “generally accepted appraisal techniques.” Dallas County Appraisal District (http://www.dcad.org/FaqEstVal.aspx) 2007 Theoretically objective Not widely available Very large dataset

Analysis and Methodology Appraisal parcel centroids were joined spatially to the Census block group files. Census range observations were assigned the median value of their range. The two datasets were compared. The differences are discussed in terms of the economic circumstances, city variation, and growth variation.

Comparison

Results HUGE discrepancies are noticeable What could cause these discrepancies in the data? If we assume that the DCAD values are generally accurate, then census-takers are reflecting certain distortions or perceptions that seem to be mostly consistent across the entire county. These discrepancies are discussed in the context of economic circumstances, city variation, and growth variations.

Optimism Effect? A result of economic optimism? Either as a result of general economic increase (GDP growth) or improvements in the housing market? 2000 was a period of distinctly pleasant economic circumstances in both of the above contexts.

GDP Growth

US Housing Market US House Price Index 1990q1 1990q3 1991q1 1991q3 1 2 3 4 5 6 7 8 1990q1 1990q3 1991q1 1991q3 1992q1 1992q3 1993q1 1993q3 1994q1 1994q3 1995q1 1995q3 1996q1 1996q3 1997q1 1997q3 1998q1 1998q3 1999q1 1999q3 2000q1 2000q3 Year/Quarter Percent Growth

Dallas Housing Market

City Variations? Cities apply different laws, taxes, and regulations to each of its citizens. Cities may also reflect different socioeconomic populations. Is it possible for these variables to affect census reporting trends?

City Variations?

Growth Variation? Logically, block groups seeing population growth are currently more desirable places to live. They should also see increasing house value if their desirability is increasing. Is this reflected in census reports? Does growth imbue citizens with greater optimism than DCAD appraisals reflect?

Variation by Growth?

Population Change Regression SUMMARY OF OUTPUT: ORDINARY LEAST SQUARES ESTIMATION Data set : PopRegress Dependent Variable : CENSUSAPPR Number of Observations: 1682 Mean dependent var : 13862.1 Number of Variables : 2 S.D. dependent var : 46615.8 Degrees of Freedom : 1680 R-squared : 0.003340 F-statistic : 5.62965 Adjusted R-squared : 0.002747 Prob(F-statistic) : 0.0177715 Sum squared residual:3.64284e+012 Log likelihood : -20464.8 Sigma-square :2.16836e+009 Akaike info criterion : 40933.7 S.E. of regression : 46565.6 Schwarz criterion : 40944.5 Sigma-square ML :2.16578e+009 S.E of regression ML: 46537.9 ----------------------------------------------------------------------- Variable Coefficient Std.Error t-Statistic Probability CONSTANT 12883.85 1207.949 10.66589 0.0000000 POP_CHAN_1 4.432737 1.868235 2.372688 0.0177715

Population Percentage Change Regression SUMMARY OF OUTPUT: ORDINARY LEAST SQUARES ESTIMATION Data set : PopRegress Dependent Variable : CENSUSAPPR Number of Observations: 1682 Mean dependent var : 13862.1 Number of Variables : 2 S.D. dependent var : 46615.8 Degrees of Freedom : 1680 R-squared : 0.000068 F-statistic : 0.114309 Adjusted R-squared : -0.000527 Prob(F-statistic) : 0.735385 Sum squared residual: 3.6548e+012 Log likelihood : -20467.6 Sigma-square :2.17548e+009 Akaike info criterion : 40939.2 S.E. of regression : 46642 Schwarz criterion : 40950 Sigma-square ML :2.17289e+009 S.E of regression ML: 46614.3 ----------------------------------------------------------------------- Variable Coefficient Std.Error t-Statistic Probability CONSTANT 13886.36 1139.533 12.186 0.0000000 POP_PERC_1 -7.367857 21.79221 -0.3380959 0.7353846

Conclusions I must reject my hypothesis that the two datasets are similar. The discrepancy between the two datasets is very large. Realistically they cannot be used for the same purposes. Discrepancies seem highly correlated to more highly-valued properties. Further studies using time series data to correlate economic status with reported values and to dig into the socio-economic variations that are observed in cities may be useful.

References Agarwal, Sumit. The Impact of Homeowners' Housing Wealth Misestimation on Consumption and Saving Decisions. Real Estate Economics. Vol. 35, No. 2. (2007). pp. 135–154. Bailar, Barbara. Some Sources of Error and their Effect on Census Statistics. Demography, Vol. 13, No. 2. (May, 1976), pp. 273-286. Bancroft, G; Welch, E. Recent Experience with Problems of Labor Force Measurement. Journal of the American Statistical Association. Vol. 41, No. 235. (Sep., 1946), pp. 303-312. Deming, W. On Errors in Surveys. American Sociological Review. Vol. 9, No. 4. (Aug., 1944), pp. 359-369. Jaeger, Carol; Pennock, J. An Analysis of Consistency of Response in Household Surveys. Journal of the American Statistical Association. Vol. 56, No. 294. (Jun., 1961), pp. 320-327. Kain, J; Quigley, J. Note on Owner’s Estimates of Housing Values (in Applications). Journal of the American Statistical Association. Vol. 67, No. 340. (Dec., 1972), pp. 803-806. Kiel, K; Zabel, J. The Accuracy of Owner-Provided House Values: The 1978-1991 American Housing Survey. Real Estate Economics. Vol. 27, No. 2, (1999). 263–298.

References Kish, L; Lansing, J. Response Errors in Estimating the Value of Homes. Journal of the American Statistical Association, Vol. 49, No. 267. (Sep., 1954), pp. 520-538. Lansing, J; Eapen, A. Dealing with Missing Information in Surveys. Journal of Marketing. Vol. 24, No. 2. (Oct., 1959), pp. 21-27. Marks, E; Mauldin, W. Response Errors in Census Research. Journal of the American Statistical Association. Vol. 45, No. 251. (Sep., 1950), pp. 424-438. Neter, J; Wakesberg, J. A Study of Response Errors in Expenditures Data from Household Interviews. Journal of the American Statistical Association. Vol. 59, No. 305. (Mar., 1964), pp. 18-55. O'Dell, Alan. An Assessment of the Errors in a Housing Survey. Urban Studies, Vol. 17, No. 2, (1980). pp. 217 – 222. Robbins, P; West, R. Measurement Errors in the Estimation of Home Value (in Applications). Journal of the American Statistical Association. Vol. 72, No. 358. (Jun., 1977), pp. 290-294. Wakesberg, J; Perkins, W. The Role of Evaluation in U.S. Censuses of Population and Housing. The Statistician. Vol. 20, No. 2, Population Censuses. (Jun., 1971), pp. 33-46.