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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. Fernandez C. & Koop G. & Steel M.F.J., 2002. "Multiple-Output Production With Undesirable Outputs: An Application to Nitrogen Surplus in Agriculture," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 432-442, June.
    2. Christine Amsler & Peter Schmidt & Wen-Jen Tsay, 2015. "A post-truncation parameterization of truncated normal technical inefficiency," Journal of Productivity Analysis, Springer, vol. 44(2), pages 209-220, October.
    3. Hoang, Viet-Ngu & Coelli, Tim, 2011. "Measurement of agricultural total factor productivity growth incorporating environmental factors: A nutrients balance approach," Journal of Environmental Economics and Management, Elsevier, vol. 62(3), pages 462-474.
    4. Murty, Sushama & Russell, R. Robert, 2010. "On modeling pollution-generating technologies," Economic Research Papers 271176, University of Warwick - Department of Economics.
    5. Jorge Galán & Helena Veiga & Michael Wiper, 2014. "Bayesian estimation of inefficiency heterogeneity in stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 42(1), pages 85-101, August.
    6. Benjamin Hampf, 2014. "Separating environmental efficiency into production and abatement efficiency: a nonparametric model with application to US power plants," Journal of Productivity Analysis, Springer, vol. 41(3), pages 457-473, June.
    7. Murray D. Smith, 2008. "Stochastic frontier models with dependent error components," Econometrics Journal, Royal Economic Society, vol. 11(1), pages 172-192, March.
    8. Horrace, William C., 2005. "On ranking and selection from independent truncated normal distributions," Journal of Econometrics, Elsevier, vol. 126(2), pages 335-354, June.
    9. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    10. Hoang, Viet-Ngu & Nguyen, Trung Thanh, 2013. "Analysis of environmental efficiency variations: A nutrient balance approach," Ecological Economics, Elsevier, vol. 86(C), pages 37-46.
    11. Hung-jen Wang & Peter Schmidt, 2002. "One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels," Journal of Productivity Analysis, Springer, vol. 18(2), pages 129-144, September.
    12. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    13. Hoang, Viet-Ngu & Rao, D.S. Prasada, 2010. "Measuring and decomposing sustainable efficiency in agricultural production: A cumulative exergy balance approach," Ecological Economics, Elsevier, vol. 69(9), pages 1765-1776, July.
    14. Hampf, Benjamin, 2014. "Separating Environmental Efficiency into Production and Abatement Efficiency - A Nonparametric Model with Application to U.S. Power Plants," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 69997, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    15. Murty, Sushama & Robert Russell, R. & Levkoff, Steven B., 2012. "On modeling pollution-generating technologies," Journal of Environmental Economics and Management, Elsevier, vol. 64(1), pages 117-135.
    16. Färe, Rolf & Grosskopf, Shawna & Pasurka, Carl A., 2007. "Environmental production functions and environmental directional distance functions," Energy, Elsevier, vol. 32(7), pages 1055-1066.
    17. Fernandez, Carmen & Osiewalski, Jacek & Steel, Mark F. J., 1997. "On the use of panel data in stochastic frontier models with improper priors," Journal of Econometrics, Elsevier, vol. 79(1), pages 169-193, July.
    18. Subal Kumbhakar & Efthymios Tsionas, 2008. "Scale and efficiency measurement using a semiparametric stochastic frontier model: evidence from the U.S. commercial banks," Empirical Economics, Springer, vol. 34(3), pages 585-602, June.
    19. Efthymios G. Tsionas, 2001. "An introduction to efficiency measurement using Bayesian stochastic frontier models," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 3(2), pages 287-311.
    20. Lauwers, Ludwig, 2009. "Justifying the incorporation of the materials balance principle into frontier-based eco-efficiency models," Ecological Economics, Elsevier, vol. 68(6), pages 1605-1614, April.
    21. Kumbhakar, Subal C & Ghosh, Soumendra & McGuckin, J Thomas, 1991. "A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 279-286, July.
    22. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    23. Hung-Jen Wang, 2002. "Heteroscedasticity and Non-Monotonic Efficiency Effects of a Stochastic Frontier Model," Journal of Productivity Analysis, Springer, vol. 18(3), pages 241-253, November.
    24. Kumbhakar, Subal C. & Park, Byeong U. & Simar, Leopold & Tsionas, Efthymios G., 2007. "Nonparametric stochastic frontiers: A local maximum likelihood approach," Journal of Econometrics, Elsevier, vol. 137(1), pages 1-27, March.
    25. Fare, Rolf, et al, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    26. Akao, Ken-Ichi & Managi, Shunsuke, 2007. "Feasibility and optimality of sustainable growth under materials balance," Journal of Economic Dynamics and Control, Elsevier, vol. 31(12), pages 3778-3790, December.
    27. Ho-chuan Huang, 2004. "Estimation of Technical Inefficiencies with Heterogeneous Technologies," Journal of Productivity Analysis, Springer, vol. 21(3), pages 277-296, May.
    28. Viet-Ngu Hoang & Mohammad Alauddin, 2012. "Input-Orientated Data Envelopment Analysis Framework for Measuring and Decomposing Economic, Environmental and Ecological Efficiency: An Application to OECD Agriculture," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 51(3), pages 431-452, March.
    29. van den Bergh, Jeroen C. J. M. & Nijkamp, Peter, 1994. "Dynamic macro modelling and materials balance : Economic-environmental integration for sustainable development," Economic Modelling, Elsevier, vol. 11(3), pages 283-307, July.
    30. Robin C. Sickles & William C. Horrace (ed.), 2014. "Festschrift in Honor of Peter Schmidt," Springer Books, Springer, edition 127, number 978-1-4899-8008-3, November.
    31. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    32. Mekaroonreung, Maethee & Johnson, Andrew L., 2012. "Estimating the shadow prices of SO2 and NOx for U.S. coal power plants: A convex nonparametric least squares approach," Energy Economics, Elsevier, vol. 34(3), pages 723-732.
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    Cited by:

    1. Benjamin Hampf, 2018. "Measuring inefficiency in the presence of bad outputs: Does the disposability assumption matter?," Empirical Economics, Springer, vol. 54(1), pages 101-127, February.

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    More about this item

    Keywords

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

    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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