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An Algorithmic Measurement of Technical Progress

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  • Stefano Zambelli
  • Thomas Fredholm

Abstract

In this paper we propose a measure of technological progress which is based on the information embedded in standard input-output tables. Well known duality properties enables one to establish a connection between the quantities necessary as inputs and the associated output and some auxiliary prices (like the wage-profit curves). We claim that properly tailored wage-profit frontiers may provide a basis for the measurement of technological progress. But the computation of these wage-profit frontiers is not trivial. A brute force algorithm for the computation of the wage-profit frontiers has high combinatorial complexity that would make its precise computation intractable. But thanks to an efficient algorithm that we have been able to devise we can now compute it. We consider this to be an important and original contribution. Here we present and apply this algorithm. Due to this improvement we can now use these wage-profit frontiers as benchmarks against which to measure technological progress: two new indices have been defined. These new tools have have been applied to the OECD input-output data 1970-2005 and the reslts are presented here.

Suggested Citation

  • Stefano Zambelli & Thomas Fredholm, 2010. "An Algorithmic Measurement of Technical Progress," ASSRU Discussion Papers 1006, ASSRU - Algorithmic Social Science Research Unit.
    • Handle: RePEc:trn:utwpas:1006
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    Citations

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    Cited by:

    1. Zambelli, Stefano & Fredholm, Thomas & Venkatachalam, Ragupathy, 2017. "Robust measurement of national technological progress," Structural Change and Economic Dynamics, Elsevier, vol. 42(C), pages 38-55.
    2. K. Vela Velupillai, "undated". "Remembering Krishna Bharadwaj," ASSRU Discussion Papers 1209, ASSRU - Algorithmic Social Science Research Unit.

    More about this item

    Keywords

    Technological Change; Convergence; Input-output analysis; Technological Frontier; Computational Techniques;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • 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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