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A general model of technical change with an application to the OECD countries

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  • Almas Heshmati
  • Subal C. Kumbhakar

Abstract

In the neoclassical production theory technical change (TC) is specified as a function of time. However, some exogenous external factors other than time can also affect the rate of TC. In this paper, we model TC via a combination of time trend (purely non-economic) and other observable exogenous factors that shift the technology. The exogenous economic factors are used to define several technology indices. These technology indices are embedded into the production function in a flexible manner. By estimating this generalized production function, we get estimates of rate of TC which is decomposed into a pure time component as well as several components attributed to technology indices. The empirical model uses panel data on OECD, accession and enhanced engagement countries observed during 1980--2006.

Suggested Citation

  • Almas Heshmati & Subal C. Kumbhakar, 2014. "A general model of technical change with an application to the OECD countries," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 23(1), pages 25-48, January.
    • Handle: RePEc:taf:ecinnt:v:23:y:2014:i:1:p:25-48
    DOI: 10.1080/10438599.2013.805918
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    Cited by:

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    2. Markus Lampe & Paul Sharp, 2015. "Just add milk: a productivity analysis of the revolutionary changes in nineteenth-century Danish dairying," Economic History Review, Economic History Society, vol. 68(4), pages 1132-1153, November.
    3. Pontus Mattsson & Jonas Månsson & William H. Greene, 2020. "TFP change and its components for Swedish manufacturing firms during the 2008–2009 financial crisis," Journal of Productivity Analysis, Springer, vol. 53(1), pages 79-93, February.
    4. Pontus Mattsson & Jonas Mansson & William H. Greene, 2018. "TFP Change and its Components for Swedish Manufacturing Firms During the 2008-2009 Financial Crisis," Working Papers 18-27, New York University, Leonard N. Stern School of Business, Department of Economics.
    5. Lu, Yuhai & Gong, Mincheng & Lu, Linzhuo & Wang, Yaqin & Wang, Yang, 2024. "Urban polycentrism and total-factor energy efficiency: An analysis based on the night light data," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    6. Haoliang Zhu & Jiao Wang, 2022. "Examining the TFP growth of information technology service sector: a cross-country analysis," Economics Bulletin, AccessEcon, vol. 42(2), pages 740-752.

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    More about this item

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • 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
    • O57 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries

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