Measuring the Efficiency of Residential Real Estate Brokerage Firms
Anderson, Randy I., Fok, Robert, Zumpano, Leonard V., Elder, Harold W., The Journal of Real Estate Research
Randy I. Anderson*
Leonard V Zumpano***
Harold W. Elder****
Abstract. This article measures overall, allocative, technical, pure technical and scale efficiency levels for a sample of residential real estate brokerage firms using data envelopment analysis, a linear-programming technique. The results suggest that real estate brokerage firms operate inefficiently. Inefficiencies are primarily a function of suboptimal input allocations and the failure to operate at constant returns to scale rather than from poor input utilization. Regression analysis is employed to determine which firm and/or market characteristics affect efficiency levels. The results show that increasing firm size increases efficiency while choosing to franchise, adding an additional multiple listing service and increasing operating leverage decreases firm performance.
Over the last decade the market for real estate brokerage services has experienced many significant changes. One of the important changes is that today, the residential real estate brokerage industry consists of fewer, but larger firms. In fact, between 1979 and 1996 the percentage of large firms (with fifty or more employees) making up the industry's total workforce has risen from 29% to 68% (NAR, 1996). Most of this increase has come at the expense of smaller firms through mergers, consolidations and failures. The market efficiency implications of these changes are important. If larger firms are more efficient, the movement towards consolidation should continue, barring regulatory intervention. If firms become less efficient as firm size increases, further consolidation should be viewed with concern in a marketplace with few barriers to entry and exit.
The market has also undergone structural changes. New market arrangements are arising, such as buyer's agency, disclosed dual agency, facilitators and other nonagency brokerage contracts. The market is also relying more heavily on interactive multimedia marketing arrangements such as the Internet and e-mail to complement the traditional use of the multiple listing service (MLS). These changes are likely to alter product mix and competitiveness in the market, which will, in turn, affect firm performance and efficiency levels.
The lack of usable data has hindered empirical research on firm performance in the residential real estate brokerage industry. There are currently only two studies that directly address the efficiency issues described earlier (Zumpano, Elder and Crellin, 1993; and Zumpano and Elder, 1994). These studies indicate that most firms in the industry are too small to take full advantage of economies of scale. In addition, product mix is found to be important. Zumpano and Elder found the presence of significant economies of scope, which suggests that firms are most efficient when they produce a balanced output of both sales and listings.
While these two studies provide a good starting point for addressing firm efficiency questions, additional information is needed. Traditional cost studies assume that all firms are operating on their efficient frontier.1 Tests of this assumption in other sectors have revealed that most firms operate, to differing degrees, off their efficient frontier. Termed X-inefficiencies, these deviations from the efficient frontier have been shown to harm firm performance even more severely than failure to operate in a manner that optimizes economies of scale or scope (Berger, Hunter and Timme, 1993). Hence, the validity of this assumption should be examined for the residential real estate market. It is also important to analyze the sources of these X-inefficiencies should they be found to exist in this market in order to better understand firm performance.
This article addresses these concerns by estimating X-inefficiency levels for a set of residential real estate brokerage firms using a technique called the data envelopment analysis (DEA). …