A Comparative Study of Alternative Approaches to Estimate Productivity

Saleem Shaik and Joseph Atwood ()
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Joseph Atwood: MSU

Journal of Quantitative Economics, 2020, vol. 18, issue 4, No 2, 747-766

Abstract: 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 (search for similar items in EconPapers)
JEL-codes: C6 O3 Q1 (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s40953-019-00191-x

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