Graduate Thesis Or Dissertation

 

Smooth nonparametric conditional quantile profit function estimation 公开 Deposited

可下载的内容

下载PDF文件
https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/3b591d09p

Descriptions

Attribute NameValues
Creator
Abstract
  • Recently, in an attempt to produce robust production frontier estimators, Aragon et al. [2005, Nonparametric frontier estimation: a conditional quantile-based approach. Econometric Theory 21, 358-389] and Martins-Filho and Yao [2008, A smooth nonparametric conditional quantile frontier estimator. Journal of Econometrics 143, 317-333] considered the estimation of nonparametric α- frontier models based on conditional quantiles with α ∈ (0,1). There exist, however, a large and growing literature in economics devoted to the estimation of profit functions. In this paper, we first define an α-profit function based on the quantile of the suitably defined conditional distribution for profits. Second we propose a smooth nonparametric conditional quantile estimator for the α-profit function model. Our estimator is computationally simple, resistant to outliers and extreme values, and smooth. In addition, the estimator is shown to be consistent and asymptotically normal under mild regularity conditions. A small simulation study provides evidence of the finite sample properties for the estimator.
License
Resource Type
Date Available
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Committee Member
Academic Affiliation
Non-Academic Affiliation
Subject
权利声明
Publisher
Peer Reviewed
Language
Replaces

关联

Parents:

This work has no parents.

属于 Collection:

单件