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A Comparative Study of Alternative Approaches to Estimate Productivity

Author

Listed:
  • Saleem Shaik

    (NDSU)

  • Joseph Atwood

    (MSU)

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.

Suggested Citation

  • Saleem Shaik & Joseph Atwood, 2020. "A Comparative Study of Alternative Approaches to Estimate Productivity," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(4), pages 747-766, December.
  • Handle: RePEc:spr:jqecon:v:18:y:2020:i:4:d:10.1007_s40953-019-00191-x
    DOI: 10.1007/s40953-019-00191-x
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    References listed on IDEAS

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    1. C. Lovell & Shawna Grosskopf & Eduardo Ley & Jesús Pastor & Diego Prior & Philippe Eeckaut, 1994. "Linear programming approaches to the measurement and analysis of productive efficiency," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 2(2), pages 175-248, December.
    2. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    3. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    4. Richard H. Moorsteen, 1961. "On Measuring Productive Potential and Relative Efficiency," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 75(3), pages 451-467.
    5. Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
    6. Zvi Griliches, 1996. "The Discovery of the Residual: A Historical Note," Journal of Economic Literature, American Economic Association, vol. 34(3), pages 1324-1330, September.
    7. Saleem Shaik & Ashok K. Mishra & Joseph Atwood, 2012. "Aggregation Issues in the Estimation of Linear Programming Productivity Measures," Journal of Applied Economics, Taylor & Francis Journals, vol. 15(1), pages 169-187, May.
    8. Samoilenko, Sergey & Osei-Bryson, Kweku-Muata, 2013. "Using Data Envelopment Analysis (DEA) for monitoring efficiency-based performance of productivity-driven organizations: Design and implementation of a decision support system," Omega, Elsevier, vol. 41(1), pages 131-142.
    9. repec:bla:scandj:v:98:y:1996:i:2:p:303-13 is not listed on IDEAS
    10. Diewert, W Erwin, 1978. "Superlative Index Numbers and Consistency in Aggregation," Econometrica, Econometric Society, vol. 46(4), pages 883-900, July.
    11. Shaik, Saleem & Perrin, Richard K., 1998. "Non-Parametric Environmental Adjusted Productivity (Eap) Measures: Nebraska Agriculture Sector," 1998 Annual meeting, August 2-5, Salt Lake City, UT 20816, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    12. Diewert, W. E., 1976. "Exact and superlative index numbers," Journal of Econometrics, Elsevier, vol. 4(2), pages 115-145, May.
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    More about this item

    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;
    All these keywords.

    JEL classification:

    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • Q1 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture

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