Flexible Estimation of Heteroskedastic Stochastic Frontier Models via Two-step Iterative Nonlinear Least Squares

31 Pages Posted: 3 Jul 2019

See all articles by Federico Belotti

Federico Belotti

University of Rome Tor Vergata - Department of Economics and Finance; University of Rome, Tor Vergata - Centre for Economics and International Studies (CEIS)

Giancarlo Ferrara

SOSE - Soluzioni per il Sistema Economico SpA; University of Palermo - Department of Economics, Business and Statistics

Date Written: June 21, 2019

Abstract

This article illustrates a straightforward and useful method for incorporating exogenous inefficiency effects in the estimation of semiparametric stochastic frontier models. An iterative estimation algorithm based on two-step nonlinear least squares is developed allowing for any flexible and monotonic specification of the production technology. We investigate the behavior of the proposed procedure through a set of Monte Carlo experiments comparing its finite sample properties with those of available alternatives. The new algorithm provides very good performance, outperforming the competitors in small samples and in presence of small signal-to-noise ratios. Two applications to agricultural data illustrate the usefulness of the proposed algorithm, even when it is used as a tool for sensitivity analysis.

Keywords: Stochastic frontier, Heteroskedasticity, Inefficiency effects, Generalized additive model, Nonlinear least-squares, P-Splines

JEL Classification: C14, C51, D24

Suggested Citation

Belotti, Federico and Ferrara, Giancarlo, Flexible Estimation of Heteroskedastic Stochastic Frontier Models via Two-step Iterative Nonlinear Least Squares (June 21, 2019). CEIS Working Paper No. 462. Available at SSRN: https://ssrn.com/abstract=3414192 or http://dx.doi.org/10.2139/ssrn.3414192

Federico Belotti (Contact Author)

University of Rome Tor Vergata - Department of Economics and Finance

Via Columbia 2
Rome, RM 00133
Italy

University of Rome, Tor Vergata - Centre for Economics and International Studies (CEIS) ( email )

Via Columbia, 2
Rome, RM 00133
Italy

Giancarlo Ferrara

SOSE - Soluzioni per il Sistema Economico SpA ( email )

Via Mentore Maggini
Rome, 00143
Italy

University of Palermo - Department of Economics, Business and Statistics ( email )

Viale delle Scienze
Palermo, 90100
Italy

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
16
Abstract Views
145
PlumX Metrics