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Measurement And Determinants Of Multi‐Factor Productivity: A Survey Of Literature

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  • Tauqir Ahmed
  • Arshad Ali Bhatti

Abstract

This paper surveys and synthesizes fast‐growing literature on the measurement and determinants of multi‐factor productivity (MFP). We identify three strands of the literature to measure MFP: the first is growth accounting, which decomposes observed economic growth into the contribution of factor inputs and technological change, called the Solow Residual; the second is index number methods, accompanied by frontier techniques; the third is growth regressions and econometric methods used to estimate productivity across countries and regions. We keep our focus on assessing the major strengths and weaknesses of commonly used methods for MFP measurement and categorize existing literature on the determinants of MFP growth into macroeconomic and institutional factors. We attempt to provide a reassessment and thematic survey of literature on the drivers of aggregate productivity, enabling policymakers to formulate effective economic policy.

Suggested Citation

  • Tauqir Ahmed & Arshad Ali Bhatti, 2020. "Measurement And Determinants Of Multi‐Factor Productivity: A Survey Of Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 34(2), pages 293-319, April.
  • Handle: RePEc:bla:jecsur:v:34:y:2020:i:2:p:293-319
    DOI: 10.1111/joes.12360
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    Cited by:

    1. Leandro Prados de la Escosura & Tamás Vonyó & Ilya B. Voskoboynikov, 2021. "Accounting For Growth In History," Journal of Economic Surveys, Wiley Blackwell, vol. 35(3), pages 655-669, July.
    2. Ahmad Bathaei & Dalia Štreimikienė, 2023. "A Systematic Review of Agricultural Sustainability Indicators," Agriculture, MDPI, vol. 13(2), pages 1-19, January.
    3. Ziesemer, Thomas, 2020. "Semi-endogenous growth models with domestic and foreign private and public R&D linked to VECMs with evidence for five countries," MERIT Working Papers 2020-013, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    4. Schneider, Henrique, 2021. "Zwei Rätsel der Produktivität: Eine empirische Beobachtung," Edition HWWI: Chapters, in: Straubhaar, Thomas (ed.), Neuvermessung der Datenökonomie, volume 6, pages 83-98, Hamburg Institute of International Economics (HWWI).
    5. Bansal, Pooja & Kumar, Sunil & Mehra, Aparna & Gulati, Rachita, 2022. "Developing two dynamic Malmquist-Luenberger productivity indices: An illustrated application for assessing productivity performance of Indian banks," Omega, Elsevier, vol. 107(C).

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