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

Hirofumi Fukuyama () and Yong Tan ()
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Yong Tan: University of Bradford

OR Spectrum: Quantitative Approaches in Management, 2023, vol. 45, issue 2, No 8, 599-622

Abstract: Abstract 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.

Keywords: Data envelopment analysis; Aggregate Lerner index; Nearest targets; Real estate (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s00291-022-00691-y

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