Estimating market power under a nonparametric analysis: evidence from the Chinese real estate sector

TY - JOUR

T1 - Estimating market power under a nonparametric analysis

T2 - evidence from the Chinese real estate sector

AU - Fukuyama, Hirofumi

AU - Tan, Yong

N1 - Publisher Copyright: © 2022, The Author(s).

PY - 2023/6

Y1 - 2023/6

N2 - The traditional Lerner index is limited in its capacity to estimate the level of competition in the economic sector from the perspective that it mainly focuses on the overall level of market power for each individual decision-making unit. Recently, Fukuyama and Tan (J Oper Res Soc, 73:445–453, 2022) estimated the Lerner index by applying the nonparametric data envelopment analysis (DEA) to calculate the marginal cost, which is an important component in the estimation of the Lerner index. Our study further extends the study of Fukuyama and Tan (J Oper Res Soc, 73:445–453, 2022) by estimating the marginal cost under the DEA in a multi-product setting. Our proposed methodology benefits from the ability to find positive marginal costs for all the products and specifies all decision-making units are profit maximizers. In order to achieve this, the marginal cost is estimated by referring to the nearest point on the best practice cost-efficient frontier for the profit-maximizing firms. We then apply our innovative method to the Chinese real estate industry. The result shows that the Chinese real estate industry has higher market power in the residential commodity housing market than that in the commodity housing market. This is also the case for different geographical areas in China. Overall, for both of these two different markets, the level of market power experiences a level of volatility.

AB - The traditional Lerner index is limited in its capacity to estimate the level of competition in the economic sector from the perspective that it mainly focuses on the overall level of market power for each individual decision-making unit. Recently, Fukuyama and Tan (J Oper Res Soc, 73:445–453, 2022) estimated the Lerner index by applying the nonparametric data envelopment analysis (DEA) to calculate the marginal cost, which is an important component in the estimation of the Lerner index. Our study further extends the study of Fukuyama and Tan (J Oper Res Soc, 73:445–453, 2022) by estimating the marginal cost under the DEA in a multi-product setting. Our proposed methodology benefits from the ability to find positive marginal costs for all the products and specifies all decision-making units are profit maximizers. In order to achieve this, the marginal cost is estimated by referring to the nearest point on the best practice cost-efficient frontier for the profit-maximizing firms. We then apply our innovative method to the Chinese real estate industry. The result shows that the Chinese real estate industry has higher market power in the residential commodity housing market than that in the commodity housing market. This is also the case for different geographical areas in China. Overall, for both of these two different markets, the level of market power experiences a level of volatility.

KW - Aggregate Lerner index

KW - Data envelopment analysis

KW - Nearest targets

KW - Real estate

UR - https://www.scopus.com/pages/publications/85140847498

U2 - 10.1007/s00291-022-00691-y

DO - 10.1007/s00291-022-00691-y

M3 - Article

AN - SCOPUS:85140847498

SN - 0171-6468

VL - 45

SP - 599

EP - 622

JO - OR Spectrum

JF - OR Spectrum

IS - 2

ER -