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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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Suggested Citation

  • 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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    2. 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.
    3. 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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