Real Estate Brokers: Do they inflate housing prices? - CEREG
Real Estate Brokers: Do they inflate housing prices? - CEREG Real Estate Brokers: Do they inflate housing prices? - CEREG
and the probit results indicate that, in these cities, there may be some underlyingcharacteristics that strongly impact the presence or absence of brokers in the transactions.Least Squares RegressionsSeveral ordinary least squares estimations of the selling price were performed. The R-squaresare in majority around 0.40 and the adjusted R-squares are about 0.33. We first estimate anOLS regression on the full sample by controlling for difference in housing characteristics, andincluded the dummy variable RE which indicates the presence or the absence of a real estatebroker in the transaction. We then model the selling price of subsamples constructed usinghedonic and individual characteristics. The variable of interest is of course RE as we wish toexamine the impact of real estate brokers on the selling price of houses. The values and thesignificance levels of the coefficient RE for the full and subsambles can be found in Table 5.Note that even though not all coefficients are significant, the large majority is positive.The coefficient RE for the full sample is positive and statistically significant. More precisely,buyers who purchase their homes through real estate brokers pay on average 1.3% more fortheir homes. To account for heterogeneity across the full sample, we then estimate OLSregressions on subsamples. We estimated the selling-price equation for each city. The REcoefficient was positively significant for the cities Lille-Roubaix-Tourcoing (4.2%), Marseille(3.2%), Toulouse (2.5%), and Lyon (2.4%), whereas for Nantes (-3%) it was negative. Thecoefficient was also negative for Rennes and Strasbourg although not significant. Even thoughreal estate agents have the most impact on prices in Lille-Roubaix-Tourcoing it does not meanthat the average price is higher. Indeed, the average price per square meter is 141 eurosgreater in Nantes than in Lille-Roubaix-Tourcoing. Lyon and Marseille have the highestaverage price per square meter, whereas Nancy and Strasbourg have the lowest. These resultsare interesting because they indicate that real estate agents do not behave the same waynationwide. The probit estimates revealed that in Lille-Roubaix-Tourcoing buyers and sellerswere less likely to seek the assistance of a broker. This could be due to the fact that buyers inthis area are aware of the fact that real estate brokers inflate prices and therefore are reluctantto seek their assistance. Moreover, the coefficients for Toulouse and half of the districts ofLyon even though not significant where negative. This is not true though for Marseille as weshowed that apartments in some districts had more probability of being sold by real estateagents. The coefficient for Nantes is positive but not at all significant.20
We estimate separate regressions for houses from one to six rooms. It appears that real estateagent increase the prices of one and two rooms apartment by respectively 3.4% and 1.9%. Theimpact of brokers on the other subsambles was not significant. This result is not surprising asthe demand for small accommodations is large and constantly increasing due to demographicreasons. Indeed, these categories of houses are very demanded by retired and young couples,singles (single persons represent 60% of home buyers) and real estate investors’ in particularbecause of the Robien law. As the demand for these types of properties often exceeds offer,they usually sell really fast. Therefore, real estate professionals have no trouble finding buyerswho are willing to pay more for these kinds of houses.Results for the construction period indicate that real estate agents increase the prices of housesbuilt during the first four periods, especially the first one which corresponds to very oldconstructions. Interestingly, the RE coefficient is negative and significant for the subsample Gof houses built between 1992 and 1999 and even though not significant, the coefficient for thesubsample of new houses is also negative. The Probit estimates revealed that those twocategories of buildings had a lower probability of being sold by real estate agents. But whenthey are sold by brokers they sell for less. This could be a result of distressed situation.Indeed, owners who sale their homes less than 13 years after buying it may face financialproblems. In such a situation, sellers may be more inclined to sell cheaply and to seek theassistance of brokers in order to accelerate the selling process. Moreover, the Robien lawwhich was passed in 2003 to boost the constructions of new accommodations gave rise toinvestment packages including credit facilities and financial insurances hooked up with thepurchase of apartments not yet constructed. Buyers who buy off-plan and thus through a realestate developer usually obtain a discount. The estimates reveal that it is a bargain for buyerswho seek recent homes to buy through a broker. Sellers of old apartments obtain a higherprice for their homes by engaging a broker. This could be due to the fact that brokers havemore architecture knowledge than owners and therefore they can better market oldapartments. Nevertheless, the construction period may capture other hedonic characteristicswhich are not controlled for.We then divide the data according to the age trenches of individuals and estimate the OLSregressions for each subsample. Real estate agents have a positive impact on prices paid bybuyers who are between thirty and forty nine years old. Buyers in their forties pay, onaverage, 3.65% more for their homes when purchasing with the help of brokers whereas21
- Page 1 and 2: Real Estate Brokers: Do they inflat
- Page 4: esults have risen from empirical st
- Page 7 and 8: Zietz and Newsome (2001), examined
- Page 9 and 10: - In terms of education he must hol
- Page 11 and 12: ias, when not corrected for in the
- Page 13 and 14: The number of rooms is included to
- Page 15 and 16: Other characteristics such as matri
- Page 17 and 18: Table 4 │Probit estimates of brok
- Page 19: This is surprising as the assisted
- Page 23 and 24: Table 5 │House price estimates: O
- Page 25 and 26: experience of buyers and sellers me
- Page 27 and 28: ReferencesBajtelsmit, V. L. and E.
- Page 29: Annex 2 │Chart of MarseilleThe ma
and the probit results indicate that, in these cities, there may be some underlyingcharacteristics that strongly impact the presence or absence of brokers in the transactions.Least Squares RegressionsSeveral ordinary least squares estimations of the selling price were performed. The R-squaresare in majority around 0.40 and the adjusted R-squares are about 0.33. We first estimate anOLS regression on the full sample by controlling for difference in <strong>housing</strong> characteristics, andincluded the dummy variable RE which indicates the presence or the absence of a real estatebroker in the transaction. We then model the selling price of subsamples constructed usinghedonic and individual characteristics. The variable of interest is of course RE as we wish toexamine the impact of real estate brokers on the selling price of houses. The values and thesignificance levels of the coefficient RE for the full and subsambles can be found in Table 5.Note that even though not all coefficients are significant, the large majority is positive.The coefficient RE for the full sample is positive and statistically significant. More precisely,buyers who purchase their homes through real estate brokers pay on average 1.3% more fortheir homes. To account for heterogeneity across the full sample, we then estimate OLSregressions on subsamples. We estimated the selling-price equation for each city. The REcoefficient was positively significant for the cities Lille-Roubaix-Tourcoing (4.2%), Marseille(3.2%), Toulouse (2.5%), and Lyon (2.4%), whereas for Nantes (-3%) it was negative. Thecoefficient was also negative for Rennes and Strasbourg although not significant. Even thoughreal estate agents have the most impact on <strong>prices</strong> in Lille-Roubaix-Tourcoing it does not meanthat the average price is higher. Indeed, the average price per square meter is 141 eurosgreater in Nantes than in Lille-Roubaix-Tourcoing. Lyon and Marseille have the highestaverage price per square meter, whereas Nancy and Strasbourg have the lowest. These resultsare interesting because <strong>they</strong> indicate that real estate agents do not behave the same waynationwide. The probit estimates revealed that in Lille-Roubaix-Tourcoing buyers and sellerswere less likely to seek the assistance of a broker. This could be due to the fact that buyers inthis area are aware of the fact that real estate brokers <strong>inflate</strong> <strong>prices</strong> and therefore are reluctantto seek their assistance. Moreover, the coefficients for Toulouse and half of the districts ofLyon even though not significant where negative. This is not true though for Marseille as weshowed that apartments in some districts had more probability of being sold by real estateagents. The coefficient for Nantes is positive but not at all significant.20
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