Journal of Real Estate Finance and Economics, 7:205-212 (1993) 9 1993 Kluwer Academic Publishers

Race of the Homeowner and Appreciation of Single-family Homes in the United States DOUGLAS COATE A N D JAMES VANDERHOFF Department of Economics, Rutgers University, Newark, New Jersey 07102 Abstract

In this article we use data from the annual housing surveysto compare the real appreciation of black- and whiteowned single-familyhomes in the U.S. in the 1974 to 1983 period. The empirical results show that single-family home appreciation depends primarily on income and population growth in the local real estate market and that race of the homeowner is not important to the appreciation process. Key words: Black, white housing appreciation

In this article we use data from the annual housing surveys to compare the real appreciation of white- and black-owned single-family homes in the United States in the 1974 to 1983 period. There have been several references to lower appreciation rates experienced by black home owners in the literature (Blau and Graham, 1990; Oliver and Shapiro, 1989; Parcel, 1982; Orfield, 1978), but to our reading at least, these claims are based on no empirical evidence. Most recently, Long and Caudill (1992) have reported from census data very similar appreciation rates among black- and white-owned homes, husband and wife present, between 1970 and 1980. The issue has important implications for black-white differences in the demand for housing and in the distribution of wealth. Home ownership rates differ substantially between blacks and whites although they have narrowed some in recent years. In 1960, 65 percent of white household units and 38 percent of black household units were owner-occupied. The corresponding figures for 1985 were 67 percent for whites and 43 percent for blacks. ~With income and wealth proxies constant, the ownership differential has been reported in the range of .09 to. 17 in favor of whites (Kain and Quigley, 1972; Roistacher and Goodman, 1976; Jackman and Jackman, 1986). 2 Whites also own homes of greater value than do blacks. In 1983 the average values of white-owned homes and black-owned homes were $70,343 and $45,122, respectively? One explanation for the higher rate of white ownership and housing expenditure could be a higher expected rate of appreciation. A higher appreciation rate for white homeowners would also have contributed to an increase in black-white wealth inequality in recent years. Black-white household wealth ratios indicate substantial inequality, with estimates in the range of .08 t o . 19. 4 It is not obvious why some researchers have assumed a lower rate of appreciation for black homeowners. If blacks own homes in neighborhoods with less amenities than do whites their price per unit of housing service would be lower, but not necessarily the rate

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DOUGLASCOATEAND JAMES VANDERHOFF

of change in price. In this article we show that race of the homeowner is not an important factor in housing price appreciation. We do find that income and population changes in local real estate markets are important housing appreciation determinants.

1. Theory Hedonic models have been used in the analysis of housing price levels when micro data are available. In this approach the prices of individual housing units are related to structural, neighborhood and locational characteristics, and regression coefficients are assumed to represent implicit prices of these characteristics.5 If we use the hedonic approach as a starting point, appreciation or the change in the price level of the housing unit is the first difference of the hedonic equation. Structural, neighborhood, and locational characteristics of the model fall out. With physical characteristics and neighborhood amenities constant, a "naive" model of housing unit appreciation should depend on income and population changes in the local housing market during the period of appreciation and on local market supply-side changes. By naive we mean that expectations of changes in market fundamentals are not assumed to be appreciation determinants. This view of the housing appreciation process is consistent with the empirical results discussed in the next section and with two recent and influential articles. Case and ShiUer (1989) tested the efficiency of the housing market in an econometric analysis of housing price changes in San Francisco, Chicago, Dallas, and Atlanta, 1972-86. They found the market was not forward looking. "Predictable movements" in real interest rates were not incorporated into house prices and there were statistically significant relationships between changes in current and lagged prices. Mankiw and Weft (1989) also concluded the housing market was not forward looking. Their simulations of an intertemporal model of the housing market, using a range of estimates of demand and supply elasticities, indicated a forward-looking market would have assimilated nearly all of the consequent housing price increase into market price before the baby boom generation hit the housing market. Furthermore, the price increases would be smaller and more gradual in the forwardlooking market in comparison to a naive market. Mankiw and Weil found that the implications of the forward-looking model were not borne out when the baby boomers arrived as home buyers in the 1970s. Home prices rose sharply and continued to rise even after the period of peak demand. In this article we use data from the annual housing surveys to build a naive model of housing appreciation in which we place special emphasis on isolating the effects of race of the homeowner. The longitudinal nature of the annual housing surveys enables us to assume structural, neighborhood ? and locational characteristics constant for the housing units in our sample, subject to the provisions detailed in the following section.

2. The data

To investigate the appreciation rates of black- and white-owned single-family homes we use data from the Annual Housing Surveys (AHS). We use the "national core samples,"

RACE OF THE HOMEOWNERAND APPRECIATIONOF SINGLE-FAMILYHOMES

207

which are drawn from the housing units enumerated in the 1970 census and which are updated to include new construction since 1970. Census Bureau interviewers visit each property in the sample and obtain information from landlords, rental agents, or neighbors for vacant units. Note that the housing unit is the unit of observation and that the same housing units will often appear in consecutive surveys. It is possible to track housing units beginning with the 1974 sample through the 1983 sample.7 Data collected in the surveys include physical characteristics of the unit, housing costs, self-reported market value, and socioeconomic characteristics of the household members. National core samples were collected in every year between 1974 and 1983. We have chosen the 1974, 1976, 1979, 1981, and 1983 samples to do our analysis. Our working sample consists of owner-occupied singlefamily homes owned by whites or blacks in metropolitan statistical areas that appear in at least two consecutive surveys, that were not condominmiums, townhouses, or mobile homes, which had no change in the number of rooms between survey years, which were not valued in the highest or lowest (open-ended) categories, and which showed annual appreciation rates of no more than 50 percent and no less than minus 50 percent. We eliminated houses with a change in number of rooms to catch renovations that would influence market value but obviously change the characteristics of the unit. We eliminated houses where homeowners valued their homes in the highest or lowest questionnaire categories because they were open-ended and appreciation rates could not be calculated. We considered dramatic changes in value to be response error or data collection/data entry error.8 We supplemented the AHS data with per capita income and population growth data for the metropolitan statistical area (MSA) from the area resource file. As an example of the calculation of real annual house value appreciation, consider a house appearing in the 1974 and 1976 surveys. First, the midpoint of the value category indicated by the respondent in each survey is used to calculate nominal appreciation during the period. The nominal appreciation rate is then annualized and real annual appreciation determined by subtracting the Consumer Price Index based inflation rate. This house could appear up to three more times as an observation in the data set, that is, in the 19761979, 1979-81, or the 1981-1983 interval.

3. Regression results Consider a fixed effects model of annual real house appreciation (Ap), where demand-side influences are represented by annual real income growth 0nc) and annual population growth (Pop) in the metropolitan area, where supply-side influences (and other fixed effects specific to a metropolitan area) are captured by 122 MSA dummy variable identifiers, and where a dummy variable is specified to measure differences in black-white appreciation rates (Blk = 1 for black home owner). Generalized least square estimates of this model (observations weighted by the estimated residual for each MSA) with period identifiers (P7476, P7679, P7981) yield: 9

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DOUGLAS COATE AND JAMES VANDERHOFF

Ap =

-.027 -.001 Blk +1.155 Pop +.411 Inc +.018 P7476 ( - 11.6) (-.7) (10.3) (11.3) (11.2) +.045 P7679 -.016 (26.3)

P 7 9 8 1 + 1 2 1 M S A D u m m i e s R 2 = .11

(-9.7)

F = 40.7 n = 37,324

T h e b l a c k d u m m y c o e f f i c i e n t is s m a l l r e l a t i v e to t h e s a m p l e m e a n real a n n u a l a p p r e c i a t i o n o f .006 a n d is statistically i n s i g n i f i c a n t . I n t a b l e 1 o r d i n a r y least s q u a r e s results for t h e b l a c k d u m m y c o e f f i c i e n t a r e s u m m a r i z e d w h e n t h e m o d e l is e s t i m a t e d for e a c h i n d i v i d u a l M S A . In o n l y five o f 106 M S A s (in 16 M S A s t h e r e w e r e n o o b s e r v a t i o n s o n b l a c k - o w n e d h o u s e s ) are t statistics l a r g e r t h a n 2 a n d in o n l y 2 7 cases are t statistics l a r g e r t h a n one. T h e b l a c k d u m m y c o e f f i c i e n t is n e g a t i v e for 55 o f t h e M S A s a n d p o s i t i v e for 51. We c o n c l u d e f r o m t h e s e results t h a t single-family h o m e a p p r e c i a t i o n d e p e n d s p r i m a r i l y o n i n c o m e a n d p o p u l a t i o n c h a n g e in t h e local real estate m a r k e t a n d t h a t r a c e o f t h e h o m e o w n e r is n o t i m p o r t a n t in t h e a p p r e c i a t i o n p r o c e s s . l ~

Notes

1. From the Census of Housing, 1960 and the American Housing Survey, 1985. Cited in the U.S. Dept. of Commerce, Statistical Abstract of the US., 1989, p. 706. 2. However, Long and Caudill (1992) report no difference in home ownership rates in black and white households where husband and wife are present, based on data from the 1986 Current Population Survey and after controlling for age, income, wealth, and region. 3. Authors' calculations from the 1983 Annual Housing Survey. 4. These estimates are reviewed in Blau and Graham (1990). 5. Follain and Malpezzi (1980) review the theoretical basis for the hedonic approach in housing market analysis. 6. Because we examine single-family home appreciation over relativeley short periods of two to three years, important changes in neighborhood quality are unlikely. 7. The 1983 AHS was the last to use the housing units enumerated in the 1970 census. The 1985 AHS uses housing units enumerated in the 1980 census. 8. The Census Bureau did not perform data edits to assure longitudinal matches of observations. The data edits we have just described in addition to an MSA code consistency requirement would delete from our samples cases when the same identifier is inadvertently assigned to different properties. 9. The 1981-83 period is the reference period. Mean values (standard deviations) for the variables for the full sample are: Ap..006 (.113); Inc .018 (.028); Pop .009 (.013); Blk .09 (.28). For black-owned houses the means are: Ap .003 (.131); Inc .019 (.029); Pop .009 (.013). A test of the difference between mean black appreciation and mean white appreciation gives a t value of .4. 10. The MSAs in table 1 have been sorted so that real annual appreciation rates are in descending order. In the top 40 cities average real annual house appreciation was 3 percent, annual real income growth was 3 percent, and annual population growth was 2 percent. In the lowest 40 cities real annual house appreciation averaged - 1%, annual real income growth was 1%, and annual population growth was 0%. These summary statistics are consistent with an important role for real income and population growth in determining housing price appreciation in metropolitan areas. An even proportion of observations (.08) in both groups of MSAs consisted of black-owned houses.

209

RACE OF THE HOMEOWNER AND APPRECIATION OF SINGLE-FAMILY HOMES

Table 1. Summary statistics by MSA and regression results for the black dummy coefficient from MSA specific appreciation models. MSA Oxnard-Simi Valley, CA Anaheim-Santa Ana, CA Los Angeles-Long Beach, CA San Jose, CA San Francisco-Oakland, CA Santa Barbara, CA Bakersfield, CA Sacramento, CA Tacoma, WA Tucson, AZ Houston, TX Stockton, CA Austin, TX Nashville, TN Seattle-Everett, WA Baton Rouge, LA Wichita, KS Tulsa, OK Salinas-Seaside, CA San Diego, CA Minneapolis-St. Paul, MN Fresno, CA New York, NY-NJ Oklahoma City, OK Denver-Boulder, CO Dallas-Fort Worth, TX Shreveport, LA Alburquerque, NM Charleston, SC Appleton-Oshkosh, WI South Bend, IN Beaumont, TX Salt Lake City, UT New Orleans, LA Duluth-Superior, M N - W I Huntington-Ashland, W V - O H Portland, O R - W A Boston, MA Charlotte-Gastonia, NC Mobile, AL Jersey City, NJ San Antonio, TX E1 Paso, TX Phoenix, AZ Pittsburgh, PA St. Louis, M O - I L Little Rock, AR Baltimore, MD

Ap 0.059 0.055 0.053 0.052 0.048 0.048 0.042 0.037 0.031 0.030 0.029 0.029 0.028 0.027 0.026 0.026 0.025 0.025 0.024 0.024 0.023 0.023 0.021 0.020 0.019 0.019 0.018 0.016 0.016 0.016 0.015 0.015 0.015 0.012 0.012 0.012 0.011 0.009 0.009 0.008 0.007 0.007 0.007 0.007 0.006 0.006 0.006 0.005

Inc

Pop

Blk

n

Coef

tstat

0.059 0.047 0.017 0.043 0.023 0.034 0.043 0.025 0.028 0.040 0.059 0.015 0.072 0.032 0.028 0.055 0.019 0.039 0.018 0.041 0.022 0.023 0.005 0.040 0.046 0.054 0.032 0.042 0.036 0.019 0.007 0.036 0.034 0.028 0.002 0.012 0.018 0.016 0.027 0.024 -0.013 0.037 0.031 0.049 -0.001 0.013 0.021 0.013

0.029 0.023 0.013 0.015 0.009 0.015 0.030 0.025 0.020 0.029 0.044 0.029 0.039 0.014 0.017 0.029 0.012 0.028 0.019 0.025 0.009 0.023 -0.002 0.023 0.025 0.030 0.014 0.023 0.024 0.004 -0.001 0.014 0.031 0.014 0.001 0.008 0.016 -0.002 0.013 0.018 -0.006 0.021 0.026 0.033 -0.005 0.000 0.012 0.002

0.05 0.02 0.12 0.02 0.10 0.06 0.08 0.07 0.04 0.00 0.14 0.02 0.19 0.12 0.03 0.21 0.02 0.03 0.00 0.07 0.02 0.01 0.08 0.08 0.02 0.18 0.11 0.00 0.25 0.00 0.10 0.11 0.00 0.21 0.00 0.00 0.04 0.00 0.10 0.29 0.13 0.09 0.03 0.00 0.04 0.10 0.12 0.16

136 534 1652 319 783 50 140 338 159 154 642 122 140 174 529 63 144 182 42 509 755 118 1141 252 604 572 117 134 81 95 108 106 228 298 79 76 413 712 147 119 55 254 110 409 804 845 130 677

0.01 0.02 -0.01 0.04 -0.01 0.09 0.01 -0.03 -0.06

0.24 0.56 -1.60 1.03 -0.39 1.25 0.35 - 1.02 - 1.28

0.00 0.01 -0.01 0.02 -0.06 -0.02 0.02 0.02

0.30 0.06 -0.38 0.76 -2.64 -0.69 0.20 0.42

0.02 0.01 0.06 0.00 -0.01 -0.01 -0.02 0.01

1.28 0.46 0.62 -0.32 -0.21 -0.56 -1.51 0.44

-0.01

-0.27

-0.03 -0.02

-0.96 -0.67

0.00

0.22

-0.02 0.13 -0.01 -0.01 0.07 -0.03 -0.06 0.00 -0.03 -0.02 -0.00 0.01

-0.60 2.12 -0.40 -0.37 1.46 - 1.24 - 1.22 0.05 - 1.20 - 1.40 -0.15 0.53

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DOUGLAS COATE AND JAMES VANDERHOFF

Table 1. Continued.

MSA

Ap

Inc

Pop

Blk

n

Coef

tstat

Corpus Christi, TX Jacksonville, FL Lancaster, PA Newport News-Hampton, VA Tampa-St. Petersburg, FL Allentown-Bethlehem, PA Augusta, GA-SC Davenport-Rock Island, IA-IL New Haven-West Haven, CT Indianapolis, IN Spokane, W A Des Moines, IA Orlando, FL Grand Rapids, MI Reading, PA Louisville, KY-IN Hartford, CT Madison, WI Gary-Hammond-East Chicago, IN Rochester, NY Paterson-Clifton, NJ Washington, D C - M D - V A Las Vegas, NV Knoxville, TN Kansas City, MO-KS Memphis, T N - A R - M S Greenville-Spartanburg, SC West Palm Beach-Boca Raton, FL Norfolk-Virginia Beach, VA Springfield-Chicopee, MA Miami, FL Birmingham, AL Wilmington, D E - N J - M D Richmond, VA Newark, NJ Lansing-East Lansing, MI Bridgeport, CT Peoria, IL Fort Lauderdale-Hollywood, FL Milwaukee, WI York, PA Philadelphia, PA-NJ Honolulu, HI Rockford, IL Omaha, NE-IA Harrisburg, PA Greensboro, NC Cleveland, OH

0.004 0.004 0.003 0.003 0.003 0.003 0.002 0.002 0.002 0.002 0.001 0.001 0.001 0.001 0.001 0.000 -0.001 -0.001 -0.002 -0.002 -0.002 -0.003 -0.003 -0.003 -0.003 -0.003 -0.004 -0.004 -0.004 -0.005 -0.005 -0.005 -0.005 -0.006 -0.006 -0.007 -0.007 -0.007 -0.007 -0.008 -0.008 -0.008 -0.008 -0.008 -0.008 -0.008 -0.008 -0.009

0.046 0.022 0.020 0.029 0.039 0.010 0.041 -0.006 0.011 0.007 0.022 0.006 0.054 0.018 0.018 0.010 0.013 0.023 -0.007 0.004 0.006 0.021 0.049 0.026 0.014 0.010 0.029 0.071 0.029 0.003 0.013 0.010 0.012 0.028 0.011 0.019 0.027 -0.020 0.051 0.004 0.017 0.008 0.012 0.004 0.01 l 0.013 0.021 -0.004

0.019 0.017 0.011 0.012 0.024 0.004 0.023 0.002 0.001 0.004 0.014 0.004 0.034 0.011 0.004 0.002 0.000 0.013 -0.002 0.001 -0.001 0.006 0.049 0.014 0.006 0.008 0.009 0.043 0.014 -0.002 0.017 0.007 0.002 0.014 -0.003 0.005 0.003 0.002 0.026 0.000 0.010 0.000 0.013 0.001 0.005 0.007 0.011 -0.006

0.03 0.21 0.04 0.18 0.09 0.02 0.29 0.01 0.09 0.07 0.00 0.00 0.03 0.02 0.01 0.08 0.04 0.00 0.15 0.02 0.02 0.20 0.08 0.08 0.08 0.29 0.09 0.09 0.10 0.00 0.17 0.14 0.08 0.19 0.08 0.04 0.02 0.06 0.14 0.03 0.01 0.11 0.00 0.04 0.08 0.01 0.11 0.11

70 226 93 100 451 226 78 150 70 396 120 93 226 217 133 340 254 121 168 326 368 737 129 149 558 243 74 145 213 157 329 302 193 223 476 111 124 136 258 478 121 1731 18 101 199 164 250 664

0.02 0.01 -0.05 -0.03 -0.01 0.03 0.05 -0.04 0.10 0.04

0.16 0.69 -0.92 - 1.36 -0.54 0.45 1.64 -0.44 2.24 1.82

0.04 -0.03 -0.05 0.00 0.00

0.84 -0.63 -0.46 0.05 0.12

0.03 0.00 -0.02 -0.01 -0.01 -0.06 0.00 0.0t3 -0.03 0.02 0.00

1.21 -0.12 -0.75 -0.67 -0.24 - 1.94 -0.03 0.29 -0.73 0.71 0.13

-0.01 0.01 0.04 0.03 -0.01 0.02 0.01 -0.01 -0.01 -0.03 -0.02 -0.00

-0.50 0.59 1.49 1.81 -0.50 0.34 0.20 -0.19 -0.40 - 1.23 - 1.88 -0.18

0.05 0.06 -0.05 0.01 -0.00

0.81 2.29 -0.56 0.45 -0.16

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RACE OF THE HOMEOWNER AND APPRECIATION OF SINGLE-FAMILY HOMES

Table 1. Continued. MSA Binghamton, NY-PA Cincinnati, OH-KY-IN Atlanta, GA Chicago, IL Youngstown-Warren, OH Loraln-Elyria, OH Dayton, OH Chattanooga, TN-GA Syracuse, NY Akron, OH Flint, MI Johnstown, PA Canton, OH Columbia, SC Columbus, OH Worcester, MA Providence-Warwick, RI Buffalo, NY Utica-Rome, NY Fort Wayne, IN Albany-Schenectady-Troy, NY Erie, PA Toledo, OH-MI Jackson, MS Detroit, MI Trenton, NJ

Ap

Inc

Pop

Blk

n

-0.009 -0.009 -0.009 -0.010 -0.010 -0.010 -0.012 -0.013 -0.013 -0.013 -0.013 -0.014 -0.015 -0.015 -0.017 -0.018 -0.018 -0.020 -0.020 -0.020 -0.021 -0.022 -0.023 -0.023 -0.025 -0.026

0.007 0.010 0.036 0.003 0.000 0.001 0.005 0.015 0.010 0.004 0.022 -0.007 0.004 0.024 0.014 0.007 0.010 -0.006 -0.002 -0.005 0.008 -0.008 0.005 0.024 -0.001 0.015

0.000 0.003 0.021 0.002 0.000 -0.001 -0.003 0.005 0.000 -0.005 -0.004 -0.002 -0.001 0.014 0.004 -0.001 -0.001 -0.010 -0.006 -0.001 -0.001 0.003 -0.003 0.016 -0.007 -0.002

0.00 0.12 0.16 0.11 0.07 0.04 0.04 0.13 0.01 0.05 0.15 0.00 0.10 0.23 0.10 0.08 0.04 0.02 0.00 0.01 0.03 0.00 0.08 0.27 0.11 0.13

78 562 591 1831 158 99 360 101 196 258 205 83 145 90 341 93 310 396 100 121 238 101 289 113 1594 111

Coef

tstat

0.130 -0.01 0.01 0.01 0.01 -0.01 0.04 -0.03 -0.02 -0.02

-0.38 -0.75 0.88 0.27 0.14 -0.54 1.08 -0.42 -0.68 -0.73

0.01 -0.05 -0.01 0.00 0.01 0.03

0.24 - 1.73 -0.62 0.11 0.45 0.81

-0.00 -0.01

-0.02 -0.27

-0.00 0.00 0.00 0.00

-0.23 0.11 0.37 0.15

Note: Ap is average annual real house appreciation; Inc is average annual real income growth; Pop is average annual population growth; Blk is proportion of the sample that is black-owned houses; n is sample size; Coef is the black dummy regression coefficient; t stat is the associated t statistic. Ap is calculated from the national core samples of the 1974, 1976, 1979, 1981, and 1983 Annual Housing Surveys. Inc and Pop are calculated from the area resource file. Right-hand side variables in the MSA specific appreciation models are Inc, Pop, and period identifiers for 1974-76, 1976-79, 1981-83.

References Blau, Francine and Graham, John. "Black/White Differences in Wealth and Asset Composition" Quarterly Journal of Economics CV (May 1990), 321-39. Case, Karl and Shiller, Robert. "The Efficiency of the Market for Single Family Homes?' American Economic Review 79 (March 1989), 125-137. FoUain, James and Malpezzi, Stephen. Dissecting House Value and Rent, Washington, D.C., 1980. Kain, John and Quigley,John. "Housing Market Discrimination, Home Ownership, and SavingsBehavior?'Amer/can Economic Review 62 (June 1972) 263-77. Jackman, M.R. and Jackman, R.W. "Racial Inequalities in Home Ownership." In J.A. Momeni, ed., Race, Ethnicity, and Minority Housing in the United States. New York, 1986. Long, James and Caudill, Steven. "Racial Differences in Homeownership and Housing Wealth, 1970-86." Economic Inquiry, 30 (January 1992), 83-100.

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Mankiw, N. Gregory and Weil, David. "The Baby Boom, the Baby Bust, and the Housing Market" Regional Science and Urban Economics, 26 (May 1989) 235-58. Oliver, Melvin and Shapiro, Thomas. "Race and Wealth." The Review of Black Political Economy 17 (Spring 1989), 5-25. Orfield, Gary. Must We Bus: Segregated Schools and National Policy, Washington D.C., 1978. Parcel, Toby L. "Wealth Accumulation of Black and White Men: The Case of Housing Equity." Social Problems 30 (Dec. 1982), 93-124. Roistacher, Elizabeth and Goodman, John. "Race and Home Ownership: Is Discrimination Disappearing" Economic Inquiry, 14 (March 1976), 59-69.