Estimation and inference under economic restrictions

• Published in: Journal of productivity analysis Vol. 41; no. 1; pp. 111 - 129
• Main Authors: Parmeter, Christopher F., Sun, Kai, Henderson, Daniel J., Kumbhakar, Subal C.
• Format: Journal Article
• Language: English
• Published: Boston Spring Science+Business Media 01.02.2014; Springer US; Springer Nature B.V
• Subjects: Accounting/Auditing; Analysis; Bootstrap method; Consistent estimators; Distance functions; Econometrics; Economic models; Economic theory; Economics; Economics and Finance; Estimates; Estimating techniques; Estimation methods; Estimators; Linear regression; Methods; Microeconomics; Nonparametric models; Operations Research/Decision Theory; Parametric models; Regression analysis; Standard error; Studies; Violations; C13; Constraint weighted bootstrapping; C12; C14; Equality; Restrictions; Inequality; Linear regression estimators
• ISSN: 0895-562X; 1573-0441; 1573-0441
• DOI: 10.1007/s11123-013-0339-x

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.