On the performance of the United States nuclear power sector: A Bayesian approach

A-Tier
Journal: Energy Economics
Year: 2023
Volume: 125
Issue: C

Authors (3)

Bernstein, David H. (University of Miami) Parmeter, Christopher F. (not in RePEc) Tsionas, Mike G. (not in RePEc)

Score contribution per author:

1.341 = (α=2.01 / 3 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

Concerns over climate change and global emissions has again placed attention on clean energy sources. Nuclear power plants are one of many sources of clean energy and yet few studies have examined the structure of technology exclusively in this area. We utilize Bayesian empirical likelihood methods to estimate a stochastic frontier model to examine scale economies, technical efficiency and technological change in the United States nuclear energy generation sector. We find decreasing scale economies, a fact consistent with the recent decline of the industry. Our results suggest that small nuclear reactors may benefit the sector as a whole.

Technical Details

RePEc Handle
repec:eee:eneeco:v:125:y:2023:i:c:s0140988323003821
Journal Field
Energy
Author Count
3
Added to Database
2026-01-24