Measuring Potential Efficiency Gains from Deregulation of Electricity Generation: A Bayesian Approach
用贝叶斯随机前沿模型分析美国78家天然气发电厂的数据，发现平均可削减13%成本，且多数电厂存在规模报酬递增。
This paper examines the efficiency of electric power generation plants in the United States. A 1996 data set from the Utility Data Institute and county-level wage data from the Bureau of Labor statistics provide the information needed to construct measures of cost, output, and input prices for 78 steam plants using natural gas as the primary fuel. This paper uses a Bayesian stochastic frontier model that imposes concavity and monotonicity restrictions implied by microeconomic theory to measure efficiency, price elasticities, and returns to scale of these plants. Results indicate that plants on average could reduce costs by up to 13% by eliminating production inefficiency. Results also indicate that most plants operate at increasing returns to scale, suggesting further cost savings could be achieved through increasing output. © 2001 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology