Abstract
Previous research (Rutherford et al. 2005; Levitt and Syverson 2005) identify and quantify agency problems in the brokerage of single-family houses. Real estate agents are found to receive a premium when selling their own houses in comparison to similar client-owned houses. Given the homogeneity of the condominium market in comparison to the single-family house market, we use a large sample of condominium transactions to examine if agency problems exist in the condominium market. Controlling for sample selection and endogeneity bias of the data, we find evidence for a similar price premium for agent-owned condominiums. In contrast to the results for single-family houses in the same geographic market, we find that agent-owned condominiums must stay on the market longer to receive a higher price.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
In fact, after sharing the commission with his firm and the agent that brings in the buyer, the listing agent receives only about one-fourth of the commission revenue.
They classify houses into 21 different styles, such as ranch, colonial, contemporary, and American four square. Then, they construct the Herfindahl index by summing the squared shares of each housing style in the housing stock on the city block of the sold property.
Each agent may also have to share their portion of the commission revenue with their brokerage firm. Such an extension will not affect the qualitative results of the paper.
The intuition for the first result is due to the fact that the agent retains a much larger portion of a marginal increase in the selling price if he owns the property than if he does not. The reason for the second result is that, although the agent expends a greater effort to search for a buyer for his own property than for a client’s property, this does not necessarily result in a shorter marketing time because the agent sets a higher price for his own property, hence decreasing the probability that a contacted buyer purchases the property.
The initial data set had a total of 23,763 observations. Due to missing values for some variables included in the models and extreme values of variables that were considered to be data entry problems, the final data set has 21,051 observations.
The MLS provides no information on whether properties are relisted, thus the calculation of DOM may understate the actual time a house remained on the market. For instance, a property listed with one agent may not sell within the contract time frame. In this case, the seller may relist the property with another agent.
This compares to 3.2% of the sample of single-family homes being owner-agent listings in Rutherford et al. (2005) study of the same geographic market.
This model adapts from the labor economics literature for wage equations where one has information on the characteristics of the individual but no wage data for those individuals not employed. For our model, we have housing characteristics for all of the sampled condominiums, but no selling price for the 9,500 properties that did not sell during the sample period.
The Heckman selection model corrects for selectivity bias by adjusting the conditional error terms using the Inverse Mills Ratio so that the conditional error terms will have zero means.
Using a semi-log OLS model to estimate the determinants of DOM is equivalent to throwing away nearly 40% of the data if the true model is exponentially distributed and even a higher percent if a Weibull distribution is more appropriate (see Lancaster (1990, ch 8.8)).
We cannot deduce why the agents buy the properties. More information on holding periods and whether the condominium is a homestead would serve this purpose, but the necessary data are not readily available.
References
Anglin, P. M., & Richard, A. (1991). Residential real estate brokerage as a principal-agent problem. Journal of Real Estate Finance and Economics, 4, 99–125.
Fisher, L., & Yavas, A. (2006). A Case for percentage commission contracts: the impact of a race among agents. Working Paper.
Geltner, D., Kluger, B. D., & Miller, N. G. (1991). Optimal price and selling effort from the perspectives of the broker and seller. AREUEA Journal, 19, 1–24.
Heckman, J. J. (1978). Sample selection bias as a specification error. Econometrica, 47, 153–161.
Lancaster, T. (1990). The econometric analysis of transition data. New York: Cambridge University Press.
Levitt, S., & Syverson, C. (2005). Market distortions when agents are better informed: The value of information in real estate transactions. National Bureau of Economic Research, NBER Working Paper 11053.
Miceli, T. J. (1991). The multiple listing service, commission splits, and broker effort. AREUEA Journal, 19, 548–566.
Rutherford, R. C., Springer, T. M., & Yavas A. (2005). Conflicts between principals and agents: Evidence from residential brokerage. Journal of Financial Economics, 76, 627–665.
Williams, J. T. (1998). Agency and brokerage of real assets in competitive equilibrium. Review of Financial Studies, 11, 239–280.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Rutherford, R.C., Springer, T.M. & Yavas, A. Evidence of Information Asymmetries in the Market for Residential Condominiums. J Real Estate Finan Econ 35, 23–38 (2007). https://doi.org/10.1007/s11146-007-9027-9
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11146-007-9027-9