A Comparative Study of Alternative Approaches to Estimate Productivity
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A Comparative Study of Alternative Approaches to Estimate Productivity Saleem Shaik1
· Joseph Atwood2
© The Indian Econometric Society 2019
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
S. Shaik.: I dedicate this to my mother, S. Suseela Jabbar who passed away on December 28, 2018. This work is/was supported by the USDA National Institute of Food and Agriculture, Hatch Multistate project number ND01325.
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Saleem Shaik [email protected] Joseph Atwood [email protected]
1
Center for Agricultural Policy and Trade Studies (CAPTS) , NDSU, Fargo, ND, USA
2
MSU, Bozeman, MT, USA
123
Journal of Quantitative Economics
Introduction The total factor productivity (TFP) or productivity has been identified as the major source of economic growth leading to welfare improvement of the economy. The three main approaches to productivity measurement are: the index numbers approach, non-parametric programming approach,1 and parametric statistical2 approach. The productivity measures computed by U.S. Department of Agriculture and Bureau of Labor Statistics use the Theil-Tornqvist or Ideal Fisher index approach (for detail discussion see Caves et al. 1982; and Diewert 1992). Based on the theory of production economics, the non-parametric programming approach to estimate productivity has gained popularity due to its ability to (a) impose little a prior functional form, (b) handle multiple output-input technology without the need of price data and (c) accommodate weak and strong disposability (see Lovell 1978 and Fare et al. 1994). Parametric estimation (Beveren 2012; and Capalbo and Antle 1988) of technology (time trend) using the primal or one of the dual representations of the production function to capture long-term changes in productivity is an alternative approach. Alternativ
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