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The identification of directed technical change revisited

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  • Saam, Marianne

Abstract

Technical change that augments capital and labor input in a non-neutral way plays an important role in explaining the relation between growth and other macroeconomic outcomes. Previous research has shown that restricting technical change to be neutral leads to overestimating the elasticity of substitution between capital and labor. I extend this line of analysis to misspecification of the functional form. Evidence from Monte Carlo simulations shows that the problem of biased estimates of the direction of technical change is relevant in the estimation of aggregate CES and translog production functions. In particular, I find examples where true technical change is neutral and estimated technical change is strongly directed towards one factor.

Suggested Citation

  • Saam, Marianne, 2014. "The identification of directed technical change revisited," ZEW Discussion Papers 14-127, ZEW - Leibniz Centre for European Economic Research.
    • Handle: RePEc:zbw:zewdip:14127
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    Cited by:

    1. Zha, Donglan & Kavuri, Anil Savio & Si, Songjian, 2018. "Energy-biased technical change in the Chinese industrial sector with CES production functions," Energy, Elsevier, vol. 148(C), pages 896-903.
    2. de la Fonteijne, Marcel R., 2018. "Why the concept of Hicks, Harrod, Solow neutral and even non-neutral augmented technical progress is flawed in principle in any economic model," MPRA Paper 107730, University Library of Munich, Germany.
    3. Zha, Donglan & Kavuri, Anil Savio & Si, Songjian, 2017. "Energy biased technology change: Focused on Chinese energy-intensive industries," Applied Energy, Elsevier, vol. 190(C), pages 1081-1089.
    4. Saam, Marianne & Niebel, Thomas & Schulte, Patrick, 2017. "The sectoral impact of the digitisation of the economy: Final report," ZEW Expertises, ZEW - Leibniz Centre for European Economic Research, number 181911.

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    More about this item

    Keywords

    directed technical change; estimation of production functions; CES functions; translog functions;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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