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A Comparative Study of Alternative Approaches to Estimate Productivity

  • Saleem ShaikEmail author
  • Joseph Atwood
Original Article
  • 7 Downloads

Abstract

Theoretically, for single output-single input, annual productivity are expected to be identical across index, non-parametric programming and parametric statistical approaches. The following models within each approach is considered—index (Tornqvist-Theil and Ideal Fisher), the non-parametric programming (Malmquist input, output and graph; Malmquist total factor productivity) and parametric (Input and Output; total factor productivity) regression. Empirically, for single output-single input, this research show differences in annual productivity and productivity growth rate between and within each of the three approaches using Nebraska agriculture data from 1936 to 2004. The annual productivity growth rate from 1936 to 2004 was identical across non-parametric Malmquist output, input, graph and Malmquist total factor productivity, and parametric Malmquist total factor productivity. However annual productivity estimated by parametric Malmquist total factor productivity is identical to Ideal Fisher productivity.

Keywords

Annual productivity and productivity growth rate Tornqvist-Theil and Ideal fisher index Non-parametric programming Malmquist input, output and graph measures Parametric solow residuals Nebraska agriculture sector data, 1936–2004 

JEL Classification

O3 C6 Q1 

Notes

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Copyright information

© The Indian Econometric Society 2019

Authors and Affiliations

  1. 1.Center for Agricultural Policy and Trade Studies (CAPTS)NDSUFargoUSA
  2. 2.MSUBozemanUSA

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