Estimation and inference under economic restrictions

Abstract

Estimation of economic relationships often requires imposition of constraints such as positivity or monotonicity on each observation. Methods to impose such constraints, however, vary depending upon the estimation technique employed. We describe a general methodology to impose (observation-specific) constraints for the class of linear regression estimators using a method known as constraint weighted bootstrapping. While this method has received attention in the nonparametric regression literature, we show how it can be applied for both parametric and nonparametric estimators. A benefit of this method is that imposing numerous constraints simultaneously can be performed seamlessly. We apply this method to Norwegian dairy farm data to estimate both unconstrained and constrained parametric and nonparametric models.

Publication DOI: https://doi.org/10.1007/s11123-013-0339-x
Divisions: College of Business and Social Sciences > Aston Business School > Economics, Finance & Entrepreneurship
College of Business and Social Sciences > Aston Business School
Additional Information: The final publication is available at link.springer.com
Uncontrolled Keywords: constraint weighted bootstrapping,restrictions,equality,inequality,linear regression estimators
Publication ISSN: 1573-0441
Last Modified: 04 Jan 2024 08:18
Date Deposited: 12 Feb 2014 11:30
Full Text Link: http://link.spr ... 1123-013-0339-x
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2014-02
Authors: Parmeter, Christopher F.
Sun, Kai
Henderson, Daniel J.
Kumbhakar, Subal C.

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