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Evaluating the semi-nonparametric fourier, aim, and neural networks cost functions

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  • Fleissig, Adrian R.
  • Kastens, Terry
  • Terrell, Dek

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  • Fleissig, Adrian R. & Kastens, Terry & Terrell, Dek, 2000. "Evaluating the semi-nonparametric fourier, aim, and neural networks cost functions," Economics Letters, Elsevier, vol. 68(3), pages 235-244, September.
    • Handle: RePEc:eee:ecolet:v:68:y:2000:i:3:p:235-244
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    1. William A. Barnett & Michael Wolfe, 2004. "Semi-nonparametric Bayesian Estimation of the Asymptotically Ideal Production Model1," Contributions to Economic Analysis, in: Functional Structure and Approximation in Econometrics, pages 303-349, Emerald Group Publishing Limited.
    2. Gallant, A. Ronald, 1981. "On the bias in flexible functional forms and an essentially unbiased form : The fourier flexible form," Journal of Econometrics, Elsevier, vol. 15(2), pages 211-245, February.
    3. Fleissig, Adrian R & Swofford, James L, 1997. "Dynamic Asymptotically Ideal Models and Finite Approximation," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(4), pages 482-492, October.
    4. Chalfant, James A. & Gallant, A. Ronald, 1985. "Estimating substitution elasticities with the Fourier cost function : Some Monte Carlo results," Journal of Econometrics, Elsevier, vol. 28(2), pages 205-222, May.
    5. Blackorby, Charles & Russell, R Robert, 1989. "Will the Real Elasticity of Substitution Please Stand Up? (A Comparison of the Allen/Uzawa and Morishima Elasticities)," American Economic Review, American Economic Association, vol. 79(4), pages 882-888, September.
    6. Barnett, William A. & Jonas, Andrew B., 1983. "The Muntz-Szatz demand system : An application of a globally well behaved series expansion," Economics Letters, Elsevier, vol. 11(4), pages 337-342.
    7. Berndt, Ernst R & Wood, David O, 1975. "Technology, Prices, and the Derived Demand for Energy," The Review of Economics and Statistics, MIT Press, vol. 57(3), pages 259-268, August.
    8. Gallant, A. Ronald, 1982. "Unbiased determination of production technologies," Journal of Econometrics, Elsevier, vol. 20(2), pages 285-323, November.
    9. Guilkey, David K & Lovell, C A Knox & Sickles, Robin C, 1983. "A Comparison of the Performance of Three Flexible Functional Forms," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 24(3), pages 591-616, October.
    10. Fleissig, Adrian R. & Kastens, Terry & Terrell, Dek, 1997. "Semi-nonparametric estimates of substitution elasticities," Economics Letters, Elsevier, vol. 54(3), pages 209-215, July.
    11. Mark Jensen, 1997. "Revisiting the flexibility and regularity properties of the asymptotically ideal production model," Econometric Reviews, Taylor & Francis Journals, vol. 16(2), pages 179-203.
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    Cited by:

    1. William A. Barnett & Ikuyasu Usui, 2007. "The Theoretical Regularity Properties of the Normalized Quadratic Consumer Demand Model," International Symposia in Economic Theory and Econometrics, in: Functional Structure Inference, pages 107-127, Emerald Group Publishing Limited.
    2. Michaelides, Panayotis G. & Vouldis, Angelos T. & Tsionas, Efthymios G., 2010. "Globally flexible functional forms: The neural distance function," European Journal of Operational Research, Elsevier, vol. 206(2), pages 456-469, October.
    3. Wolff, Hendrik & Heckelei, Thomas & Mittelhammer, Ronald C., 2004. "Imposing Monotonicity And Curvature On Flexible Functional Forms," 2004 Annual meeting, August 1-4, Denver, CO 20256, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. Adrian R. Fleissig, 2016. "Changing Trends in U.S. Alcohol Demand," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 44(3), pages 263-276, September.
    5. Vouldis, Angelos T. & Michaelides, Panayotis G. & Tsionas, Efthymios G., 2010. "Estimating semi-parametric output distance functions with neural-based reduced form equations using LIML," Economic Modelling, Elsevier, vol. 27(3), pages 697-704, May.
    6. Hendrik Wolff & Thomas Heckelei & Ron Mittelhammer, 2010. "Imposing Curvature and Monotonicity on Flexible Functional Forms: An Efficient Regional Approach," Computational Economics, Springer;Society for Computational Economics, vol. 36(4), pages 309-339, December.
    7. Francisco J. Delgado, 2005. "Measuring efficiency with neural networks. An application to the public sector," Economics Bulletin, AccessEcon, vol. 3(15), pages 1-10.
    8. Amiri, Arshia & Ventelou, Bruno, 2011. "Forecasting the role of public expenditure in economic growth Using DEA-neural network approach," MPRA Paper 33955, University Library of Munich, Germany.
    9. repec:ebl:ecbull:v:3:y:2005:i:15:p:1-10 is not listed on IDEAS
    10. Matteo Manera & Bruno Sitzia, 2005. "Empirical factor demands and flexible functional forms: a bayesian approach," Economic Systems Research, Taylor & Francis Journals, vol. 17(1), pages 57-75.

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