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Restricted Least Squares Subject to Monotonicity and Concavity Constraints

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  • Paul Ruud

Abstract

Economists have devoted a large research effort to the estimation of cost functions and profit functions. Since the popularization of the dual approach to such functions, econometricians have focussed particularly on methods for fitting functions that satisfy the restrictions implied by optimizing behavior, minimizing costs or maximizing profits. For the most part, researchers have sought simple parametric functional forms that are sufficiently flexible to approximate well all possible functions in the families of cost and profit functions. Given such parametric functions, much of the estimation has followed the method of least squares.
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  • Paul Ruud, "undated". "Restricted Least Squares Subject to Monotonicity and Concavity Constraints," Working Papers _007, University of California at Berkeley, Econometrics Laboratory Software Archive.
    • Handle: RePEc:wop:calbem:_007
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    File URL: http://emlab.berkeley.edu/users/ruud/tokyo2.ps.Z
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    References listed on IDEAS

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    1. John Geweke, "undated". "Posterior Simulators in Econometrics," Computing in Economics and Finance 1996 _019, Society for Computational Economics.
    2. S. M. Goldman & P. A. Ruud, 1993. "Nonparametric Multivariate Regression Subject to Constraint," Econometrics 9311001, University Library of Munich, Germany.
    3. Ying, John S, 1990. "The Inefficiency of Regulating a Competitive Industry: Productivity Gains in Trucking Following Reform," The Review of Economics and Statistics, MIT Press, vol. 72(2), pages 191-201, May.
    4. Diewert, Walter E & Wales, Terence J, 1987. "Flexible Functional Forms and Global Curvature Conditions," Econometrica, Econometric Society, vol. 55(1), pages 43-68, January.
    5. Diewert, W. E., 1973. "Functional forms for profit and transformation functions," Journal of Economic Theory, Elsevier, vol. 6(3), pages 284-316, June.
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    Cited by:

    1. Daniel J. Henderson & Christopher F. Parmeter, 2009. "Imposing economic constraints in nonparametric regression: survey, implementation, and extension," Advances in Econometrics, in: Nonparametric Econometric Methods, pages 433-469, Emerald Group Publishing Limited.
    2. Lee, Chia-Yen & Johnson, Andrew L. & Moreno-Centeno, Erick & Kuosmanen, Timo, 2013. "A more efficient algorithm for Convex Nonparametric Least Squares," European Journal of Operational Research, Elsevier, vol. 227(2), pages 391-400.

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