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X-Inefficiencies in the Residential Real Estate Market: A Stochastic Frontier Approach

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This article examines the productive efficiency levels present in the market for residential real estate brokerage services by employing the stochastic frontier approach. The only prior study (Anderson, Zumpano, Elder and Fok, 1998) that examined productive efficiency in this sector employed data envelopment analysis. This current article addresses potential statistical limitations of Data Envelopment Analysis and uses an alternative statistical tool, the stochastic frontier approach, to estimate X-efficiencies. This technique overcomes many of the statistical limitations of DEA and provides additional productive efficiency estimates. The results suggest that residential real estate brokerage firms are relatively efficient, in contrast to the earlier study that found significant inefficiencies present in this market. Firms could only reduce their average total costs by 12% given firm outputs and input prices. Additionally, the firms were divided into three size categories to examine the impact of firm size on efficiency. The results indicate that small firms are the most efficient group. Hence, there seems to be a tradeoff between scale efficiency and productive efficiency.

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  • Randy I. Anderson & Danielle Lewis & Leonard V. Zumpano, 2000. "X-Inefficiencies in the Residential Real Estate Market: A Stochastic Frontier Approach," Journal of Real Estate Research, American Real Estate Society, vol. 20(1), pages 93-103.
    • Handle: RePEc:jre:issued:v:20:n:1:2000:p:93-103
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    1. Randy I. Anderson & Robert Fok & Leonard V. Zumpano & Harold W. Elder, 1998. "Measuring the Efficiency of Residential Real Estate Brokerage Firms," Journal of Real Estate Research, American Real Estate Society, vol. 16(2), pages 139-158.
    2. Berger, Allen N. & Humphrey, David B., 1991. "The dominance of inefficiencies over scale and product mix economies in banking," Journal of Monetary Economics, Elsevier, vol. 28(1), pages 117-148, August.
    3. Ferrier, Gary D. & Lovell, C. A. Knox, 1990. "Measuring cost efficiency in banking : Econometric and linear programming evidence," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 229-245.
    4. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    5. Terrell, Dek, 1996. "Incorporating Monotonicity and Concavity Conditions in Flexible Functional Forms," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(2), pages 179-194, March-Apr.
    6. Olson, Jerome A. & Schmidt, Peter & Waldman, Donald M., 1980. "A Monte Carlo study of estimators of stochastic frontier production functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 67-82, May.
    7. Berger, Allen N. & Hunter, William C. & Timme, Stephen G., 1993. "The efficiency of financial institutions: A review and preview of research past, present and future," Journal of Banking & Finance, Elsevier, vol. 17(2-3), pages 221-249, April.
    8. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    9. Leonard V. Zumpano & Harold W. Elder, 1994. "Economies of Scope and Density in the Market for Real Estate Brokerage Services," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 22(3), pages 497-513, September.
    10. Bauer, Paul W., 1990. "Recent developments in the econometric estimation of frontiers," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 39-56.
    11. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    12. Zumpano, Leonard V & Elder, Harold W & Crellin, Glenn E, 1993. "The Market for Residential Real Estate Brokerage Services: Costs of Production and Economies of Scale," The Journal of Real Estate Finance and Economics, Springer, vol. 6(3), pages 237-250, May.
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    Cited by:

    1. Jonathan Wiley & Justin Benefield & Marcus Allen, 2014. "Cyclical Determinants of Brokerage Commission Rates," The Journal of Real Estate Finance and Economics, Springer, vol. 48(1), pages 196-219, January.
    2. Lewis, Danielle & Anderson, Randy I. & Zumpano, Leonard V., 1999. "An analysis of affinity programs: the case of real estate brokerage participation," Financial Services Review, Elsevier, vol. 8(3), pages 183-197.
    3. Han, Lu & Strange, William C., 2015. "The Microstructure of Housing Markets," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 813-886, Elsevier.
    4. Lewis, Danielle & Webb, James R., 2007. "Potential cost synergies from banks acquiring real estate brokerage services," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2347-2363, August.

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    JEL classification:

    • L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services

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