Are Dual and Primal Estimations Equivalent in the Presence of Stochastic Errors in Input Demand?

Authors

  • Mauricio Vaz Lobo Bittencourt UFPR
  • Armando Vaz Sampaio UFPR

DOI:

https://doi.org/10.12660/bre.v31n22011.4065

Keywords:

stochastic errors, input demands, duality, Monte Carlo simulation

Abstract

This study investigates the primal and dual approaches for production in the presence of stochastic errors in output and input demands, and policy implications when such errors are not taken into account. A synthetic dataset is used to econometrically estimate the primal and dual functions associated with a given technology. Results show that both formulations are unbiased, consistent and efficient, even in the presence of a Cobb-Douglas technology. Not accounting for such errors can lead to wrong policy recommendations in a productive sector. Any kind of policy created to improve the total production of a particular sector should consider these issues before applying them to real data.

Author Biographies

Mauricio Vaz Lobo Bittencourt, UFPR

Professor do Departamento de Economia e do Programa de Pós-Graduação em Desenvolvimento Econômico da UFPR

Armando Vaz Sampaio, UFPR

Professor do Departamento de Economia e do Programa de Pós-Graduação em Desenvolvimento Econômico da UFPR

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Published

2011-12-02

Issue

Section

Articles