Effective Market Power and Welfare Loss

ABSTRACT This paper introduces a straightforward and effective estimation methodology for quantifying firm‐level welfare losses attributable to market power in monopolistic competition markets. Our analysis underscores that welfare losses are primarily contingent on effective market power, expressed as the product of the Lerner index and market share. Furthermore, our study demonstrates that welfare loss computed using the Hicksian measurement is smaller than that obtained through the Marshallian measurement. Finally, we apply this methodology to estimate firm‐level market power and welfare losses in the Chinese carbonated beverage industry.

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Publication Details

Journal
Australian Economic Papers
Published
2024-11-19
DOI
https://doi.org/10.1111/1467-8454.12386
Primary Topic
Merger and Competition Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Effective Market Power and Welfare Loss

Yue Luo, Xuecheng Fan, Zhongqi Deng, Cailin Yang
Australian Economic Papers
Merger and Competition Analysis
article

Effective Market Power and Welfare Loss

Yue Luo, Xuecheng Fan, Zhongqi Deng, Cailin Yang
article en

Abstract

ABSTRACT This paper introduces a straightforward and effective estimation methodology for quantifying firm‐level welfare losses attributable to market power in monopolistic competition markets. Our analysis underscores that welfare losses are primarily contingent on effective market power, expressed as the product of the Lerner index and market share. Furthermore, our study demonstrates that welfare loss computed using the Hicksian measurement is smaller than that obtained through the Marshallian measurement. Finally, we apply this methodology to estimate firm‐level market power and welfare losses in the Chinese carbonated beverage industry.

Australian Economic PapersVol. 64(2)
Sichuan University (CN)
National Office for Philosophy and Social Sciences, National Social Science Fund of China
Openalex Percentile: Top 75%
Merger and Competition Analysis
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