Imposing Economic Constraints in Nonparametric Regression: Survey, Implementation and Extension

Daniel Henderson (daniel.henderson@ua.edu) and Christopher Parmeter

No 4103, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: Economic conditions such as convexity, homogeneity, homotheticity, and monotonicity are all important assumptions or consequences of assumptions of economic functionals to be estimated. Recent research has seen a renewed interest in imposing constraints in nonparametric regression. We survey the available methods in the literature, discuss the challenges that present themselves when empirically implementing these methods and extend an existing method to handle general nonlinear constraints. A heuristic discussion on the empirical implementation for methods that use sequential quadratic programming is provided for the reader and simulated and empirical evidence on the distinction between constrained and unconstrained nonparametric regression surfaces is covered.

Keywords: identification; concavity; Hessian; constraint weighted bootstrapping; earnings function (search for similar items in EconPapers)
JEL-codes: C14 J20 J30 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2009-03
New Economics Papers: this item is included in nep-ecm and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20)

Published - published in: Advances in Econometrics, 2009, 25, 433-469

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Chapter: Imposing economic constraints in nonparametric regression: survey, implementation, and extension (2009)
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