Estimation and inference under economic restrictions

Christopher F. Parmeter, Kai Sun, Daniel J. Henderson, Subal C. Kumbhakar

Research output: Contribution to journalArticle

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.
Original languageEnglish
Pages (from-to)111-129
Number of pages9
JournalJournal of Productivity Analysis
Volume41
Issue number1
DOIs
Publication statusPublished - Feb 2014

Bibliographical note

The final publication is available at link.springer.com

Keywords

  • constraint weighted bootstrapping
  • restrictions
  • equality
  • inequality
  • linear regression estimators

Fingerprint Dive into the research topics of 'Estimation and inference under economic restrictions'. Together they form a unique fingerprint.

  • Cite this

    Parmeter, C. F., Sun, K., Henderson, D. J., & Kumbhakar, S. C. (2014). Estimation and inference under economic restrictions. Journal of Productivity Analysis, 41(1), 111-129. https://doi.org/10.1007/s11123-013-0339-x