Smooth coefficient estimation of stochastic frontier models

C-Tier
Journal: Economics Letters
Year: 2020
Volume: 193
Issue: C

Authors (2)

Lopez Gomez, Daniel (not in RePEc) Parmeter, Christopher F. (University of Miami)

Score contribution per author:

0.503 = (α=2.01 / 2 authors) × 0.5x C-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

This paper proposes two alternative estimators for the semiparametric smooth coefficient stochastic frontier model which do not require parametric specification of the parameters of the distribution of inefficiency to identify all of the model primitives. These new estimators offer avenues for testing for correct specification. A small Monte Carlo simulation study reveals that the new methods perform similarly when correct specification is present and that the existing smooth coefficient estimator can perform poorly when it is incorrectly specified.

Technical Details

RePEc Handle
repec:eee:ecolet:v:193:y:2020:i:c:s0165176520302202
Journal Field
General
Author Count
2
Added to Database
2026-01-26