Measuring potential efficiency gains from deregulation of electricity generation: A Bayesian approach

Andrew N. Kleit, Dek Terrell

Research output: Contribution to journalArticlepeer-review

81 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)523-530
Number of pages8
JournalReview of Economics and Statistics
Volume83
Issue number3
DOIs
StatePublished - Aug 1 2001

All Science Journal Classification (ASJC) codes

  • Social Sciences (miscellaneous)
  • Economics and Econometrics

Fingerprint

Dive into the research topics of 'Measuring potential efficiency gains from deregulation of electricity generation: A Bayesian approach'. Together they form a unique fingerprint.

Cite this