摘要
集中度上升可以同时反映效率和市场势力。基于新产业组织研究方法,引入推测变量导出微观层面的企业行为优化方程,再将其过渡到行业层面,创造性地将Lerner指数推广至寡占势力测度,最后导出集中度上升的寡占势力效应和规模经济效应分解方程。笔者应用极大似然法对结构方程进行参数估计,计算样本行业的推测变量、寡占势力和成本弹性。研究发现,集中度上升的规模经济效应推动60%的行业价格下降,但寡占势力效应仍超过规模经济效应或强化低效率,导致大多数行业价格上升。
Changes in industrial concentration reflect efficiency and market power. The paper uses NEIO method to construct theoretical framework by introducing conjectural variation derived enterprises optimization equation. After transition enterprises optimization equation to industry lever we separate oligopoly-power and scale economy effects of changes in industrial concentration. Using ML method to estimate structure model,the paper computers conjectural variation oligopoly-power and cost elasticity of sample industries. Empirical results indicates that concentration lows 60% industries price because of scale economy effects,but oligopoly-power effects either dominates cost efficiency or reinforce inefficiency resulting higher prices in most industries.
出处
《经济经纬》
CSSCI
北大核心
2016年第5期72-77,共6页
Economic Survey
基金
安徽省哲学社会科学规划项目(AHSKY2014D58)
关键词
集中度
寡占势力效应
规模经济效应
新产业组织
推测变量
Concentration ratio
Oligopoly-Power Effect
Scale Economy Effect
New Empirical Industrial Organization
Conjectural Variation