Dynamic Efficiency Estimation

Rungsuriyawiboon, Supawat; Stefanou, Spiro E.

doi:10.1198/073500106000000288

Cited by 62 publications

(15 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Table 6 indicates that the short-run marginal cost is 0.386 cents per kwh at the sample mean, and increases to 0.493 cents per kwh in the long-run. These results are much lower than those of the steam power industry in Rungsuriyawiboon and Stefanou (2007). Their results show the short-run marginal cost is 1.938 cents per kwh, and decreases to 1.782 cents per kwh in the long run.…”

Section: Resultsmentioning

confidence: 77%

“…Table 6 also shows that long-run average cost is 2.199 cents per kwh which is approximately half of actual total average cost. Compared to the 2.774 cents per kwh estimate of Rungsuriyawiboon and Stefanou (2007), nuclear power generation offers possible cost savings by 26 percent. Short-and long-run technological changes are negative.…”

Section: Resultsmentioning

confidence: 97%

“…Nerlove (1963), Christensen and Greene (1976), Greene (1985), Kamerschen and Thompson (1993), Considine (2000)]. Recent empirical applications of the U.S. electric power generation use data on steam electric power generation for major investor owned utilities (IOUs) to estimate the cost structures and the inefficiency level of the electric utilities [e.g., Atkinson and Primont (2002), Rungsuriyawiboon and Stefanou (2007)]. These studies used data on the generation source, which represents the dominant part of the U.S. electricity supply industry.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Estimating Cost Structures in the U.S. Nuclear Power Industry

Rungsuriyawiboon

2008

Energy Exploration & Exploitation

Self Cite

View full text Add to dashboard Cite

With growing concerns about global warming and surging oil prices, nuclear power is now back on the U.S. energy policy agenda. This paper provides firm level analysis of the production technology and cost structures in the U.S. nuclear power generation industry. The paper applies an econometric approach into a dual restricted variable cost function within a "temporal equilibrium" framework. A panel data set of 32 nuclear power generations for major U.S. investor owned utilities over the period 1986-2002 is used. The major finding indicates that most electric utilities in the nuclear electricity generation industry over utilized capital in production. The estimated results show evidence of scale economies in the production of the electricity industry. The paper presents supporting evidence that nuclear technology is cheaper than other alternative technologies and fuels, and it can offer possible cost savings to other alternative technologies.

show abstract

Section: Resultsmentioning

confidence: 77%

Section: Resultsmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Estimating Cost Structures in the U.S. Nuclear Power Industry

Rungsuriyawiboon

2008

Energy Exploration & Exploitation

Self Cite

View full text Add to dashboard Cite

show abstract

“…Formulating technical efficiency and its relation to TFP growth, they find seek to address how the productivity gap relates to the efficiency adjustment cost shares. Recently, Rungsuriyawiboon and Stefanou (2007) establish a dynamic efficiency model of the cost minimizing firm by integrating the static shadow cost approach and the dynamic duality model of intertemporal decision making. The dynamic efficiency model measures the firms' inefficiency and accounts for allocative and technical inefficiencies of net investment and variable inputs.…”

Section: Introductionmentioning

confidence: 99%

The dynamics of efficiency and productivity growth in U.S. electric utilities

Rungsuriyawiboon

Stefanou

2008

J Prod Anal

Self Cite

View full text Add to dashboard Cite

show abstract

“…Our work complements Rungsuriyawiboon and Stefanou (2007), who formulate and estimate a shadow-cost system that incorporates adjustment costs. However, they take a different approach to estimation and are not concerned with productivity change and its decomposition.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Allocative Inefficiency and Productivity Growth with Dynamic Adjustment Costs

Atkinson

Cornwell

2011

Econometric Reviews

View full text Add to dashboard Cite

A substantial literature has been generated on the estimation of allocative and technical inefficiency using static production, cost, profit, and distance functions. We develop a dynamic shadow distance system that integrates dynamic adjustment costs into a long-run shadow cost-minimization problem, which allows us to distinguish static allocative distortions from short-run inefficiencies that arise due to period-to-period adjustment costs. The set of estimating equations is comprised of the first-order conditions from the short-run shadow cost-minimization problem for the variable shadow input quantities, a set of Euler equations derived from subsequent shadow cost minimization with respect to the quasifixed inputs, and the input distance function, expressed in terms of shadow quantities. This system nests within it the static model with zero adjustment costs. Using panel data on U.S. electric utilities, we contrast the results of static and dynamic shadow distance systems. First, the zero-adjustment-cost restriction is strongly rejected. Second, we find that adjustment costs represent about .42 percent of total cost and about 1.26 percent of capital costs. Third, while both models reveal that labor is not utilized efficiently, the dynamic model indicates a longer period of over-use and less variance over time in the degree of inefficiency. With the dynamic model, productivity growth is larger but more stable.JEL Categories: C13, C33

show abstract

Dynamic Efficiency Estimation

Cited by 62 publications

References 24 publications

Estimating Cost Structures in the U.S. Nuclear Power Industry

Estimating Cost Structures in the U.S. Nuclear Power Industry

The dynamics of efficiency and productivity growth in U.S. electric utilities

Estimation of Allocative Inefficiency and Productivity Growth with Dynamic Adjustment Costs

Contact Info

Product

Resources

About