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Identifying the critical factors behind the second-hand housing price concession: Empirical evidence from China


Weidong Qu, Professor, School of Public Administration and Policy, RUC


Weidong Qu; Yiqi Huang; Guoying Deng


Habitat International Volume 117, September 2021


• Both-sides commission of dual agent mode will decrease the seller’s price concession.

• Commission incentive has a moderating effect on information transmission during housing transaction.

• Broker’s incentive bias is more obvious when bargaining power is more unequal between the seller and the buyer.

• Exogenous demand shock leads to a change in the relationship between brokers’ actions and sellers’ pricing strategies.

• The disparity between the agent mode and commission incentive scheme should be resolved.


The seller’s price concession reflects the existence of asymmetric information in the second-hand housing market, and it is beneficial to study the influence of the broker’s commission incentive source on the information transmission in the process of second-hand housing transactions. This study examined 310,332 transactions in 17 cities, using the spatio-temporal autoregressive model. Results mainly revealed price concession under the bothsides broker commission arrangement was 1.64% significantly lower than that under the buyer-side commission. The broker commission incentive has a moderating effect on the transmission of market information during transactions, whereas the both-sides commission leads to an increase in the effect of objective market conditions and reduces the difference of effects of individual factors on price concessions. An exogenous demand shock may lead to a change in the relationship between brokers’ actions and sellers’ pricing strategies. The implications will serve to improve the norms of and transparency in the second-hand housing transaction market, and resolve the disparity between the broker agent mode and commission incentive scheme.


Second-hand housing transactions; Price concession; Real estate broker; Spatio-temporal autoregression; China

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