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The shape of aggregate production functions: evidence from estimates of the World Technology Frontier

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The article provides multifaceted evidence on the shape of the aggregate country-level production function, derived from the World Technology Frontier, estimated on the basis of annual data on inputs and output in 19 highly developed OECD countries in the period 1970–2004. A comparison of its estimates based on Data Envelopment Analysis and Bayesian Stochastic Frontier Analysis uncovers a number of significant discrepancies between the nonparametric estimates of the frontier and the Cobb–Douglas and translog production functions in terms of implied efficiency levels, partial elasticities, and returns-to-scale properties. Furthermore, the two latter characteristics as well as elasticities of substitution are found to differ markedly across countries and time, providing strong evidence against the constant-returns-to-scale (CRS) Cobb–Douglas specification, frequently used in related literature. We also find notable departures from perfect substitutability between unskilled and skilled labor, consistent with the hypotheses of skill-biased technical change and capital–skill complementarity. In the Appendix, as a corollary from our results, we have also conducted a series of development accounting and growth accounting exercises.

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  • Jakub Growiec & Anna Pajor & Dorota Pelle & Artur Prędki, 2011. "The shape of aggregate production functions: evidence from estimates of the World Technology Frontier," NBP Working Papers 102, Narodowy Bank Polski.
  • Handle: RePEc:nbp:nbpmis:102
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    2. Jakub Growiec, 2013. "On the measurement of technological progress across countries," Bank i Kredyt, Narodowy Bank Polski, vol. 44(5), pages 467-504.
    3. Sinem Kilic Celik & M. Ayhan Kose & Franziska Ohnsorge & F. Ulrich Ruch, 2023. "Potential Growth: A Global Database," CAMA Working Papers 2023-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Viktor Zavhorodniy & Janusz Kudła, 2017. "Zmiany efektywności banków w Rosji po wprowadzeniu międzynarodowych sankcji w 2014 r," Bank i Kredyt, Narodowy Bank Polski, vol. 48(1), pages 97-118.
    5. Kamil Makieła, 2014. "Bayesian Stochastic Frontier Analysis of Economic Growth and Productivity Change in the EU, USA, Japan and Switzerland," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(3), pages 193-216, September.
    6. Jerzy Marzec & Andrzej Pisulewski, 2017. "The Effect of CAP Subsidies on the Technical Efficiency of Polish Dairy Farms," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(3), pages 243-273, September.

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    More about this item

    Keywords

    world technology frontier; aggregate production function; Data Envelopment Analysis; Stochastic Frontier Analysis; partial elasticity; returns to scale; substitutability;
    All these keywords.

    JEL classification:

    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • 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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