Specification errors in estimating cost functions: the case of the nuclear-electric-generating industry

Thesis/Dissertation · Thu Jan 01 00:00:00 EST 1987

OSTI ID:7226757

Jorgensen, E J

This study is an application of production-cost duality theory. Duality theory is reviewed for the competitive and rate-of-return regulated firm. The cost function is developed for the nuclear electric-power-generating industry of the United States using capital, fuel, and labor factor inputs. A comparison is made between the Generalized Box-Cox (GBC) and Fourier Flexible (FF) functional forms. The GBC functional form nests the Generalized Leontief, Generalized Square Root Quadratic and Translog functional forms, and is based upon a second-order Taylor-series expansion. The FF form follows from a Fourier-series expansion in sine and cosine terms using the Sobolev norm as the goodness-of-fit measure. The Sobolev norm takes into account first and second derivatives. The cost function and two factor shares are estimated as a system of equations using maximum-likelihood techniques, with Additive Standard Normal and Logistic Normal error distributions. In summary, none of the special cases of the GBC function form are accepted. Homotheticity of the underlying production technology can be rejected for both GBC and FF forms, leaving only the unrestricted versions supported by the data. Residual analysis indicates a slight improvement in skewness and kurtosis for univariate and multivariate cases when the Logistic Normal distribution is used.

• Research Organization: Arizona Univ., Tucson (USA)
• OSTI ID: 7226757
• Resource Relation: Other Information: Thesis (Ph. D.)
• Country of Publication: United States
• Language: English

Related Subjects

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS
29 ENERGY PLANNING
POLICY AND ECONOMY
NUCLEAR POWER
POWER GENERATION
COST ESTIMATION
CAPITAL
FOURIER ANALYSIS
LABOR
MAXIMUM-LIKELIHOOD FIT
NUCLEAR FUELS
ENERGY SOURCES
FUELS
MATERIALS
NUMERICAL SOLUTION
POWER
REACTOR MATERIALS
210800* - Nuclear Power Plants- Economics
290600 - Energy Planning & Policy- Nuclear Energy