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Estimating the materials balance condition: A stochastic frontier approach

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  • Hampf, Benjamin

Abstract

In this paper we propose a stochastic formulation of the materials balance condition which imposes physical constraints on production technologies. The estimation of the model involves a composed error term structure that is commonly applied in the literature on stochastic frontier analysis of productive efficiency. Moreover, we discuss how OLS, maximum likelihood and Bayesian methods can be used to estimate the proposed model. In contrast to previous approaches our model allows to estimate the physical limitations to production possibilities in the presence of statistical noise and depends on substantially weaker data requirements. We demonstrate the applicability of our new approach by estimating the materials balance condition for SO2 and CO2 using a sample of fossil-fueled power plants in the United States.

Suggested Citation

  • Hampf, Benjamin, 2015. "Estimating the materials balance condition: A stochastic frontier approach," Darmstadt Discussion Papers in Economics 226, Darmstadt University of Technology, Department of Law and Economics.
  • Handle: RePEc:zbw:darddp:226
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    1. repec:spr:empeco:v:54:y:2018:i:1:d:10.1007_s00181-016-1204-3 is not listed on IDEAS

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    Keywords

    Materials balance condition; Abatement efficiency; Stochastic frontier analysis; Laws of thermodynamics; Applied econometrics; Environmental economics;

    JEL classification:

    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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