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A Demand System for Input Factors when there are Technological Changes in Production

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In a system with n input factors there are n − 1 independent cost shares. An often-used approach in estimating factor demand systems is to (implicitly or explicitly) assume that there is a (independent) cointegrating relationship for each of the n − 1 independent cost shares. However, due to technological changes there might not be as many cointegrating relationships as there are (independent) cost shares. The paper presents a flexible demand system that allows for both factor neutral technological changes as well as technological changes that affect the relative use of the different factors. The empirical tests indicate that there are fewer cointegrating relationships than usually implied by using conventional estimation approaches. This result is consistent with technological changes. I argue that since such unexplained technological changes are likely to affect input factor decisions, a demand system that allows for such changes should be preferred.

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  • Håvard Hungnes, 2008. "A Demand System for Input Factors when there are Technological Changes in Production," Discussion Papers 556, Statistics Norway, Research Department.
    • Handle: RePEc:ssb:dispap:556
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    7. Abadir,Karim M. & Magnus,Jan R., 2005. "Matrix Algebra," Cambridge Books, Cambridge University Press, number 9780521537469.
    8. Allen, Chris & Urga, Giovanni, 1999. "Interrelated Factor Demands from Dynamic Cost Functions: An Application to the Non-energy Business Sector of the UK Economy," Economica, London School of Economics and Political Science, vol. 66(263), pages 403-413, August.
    9. Harbo, Ingrid, et al, 1998. "Asymptotic Inference on Cointegrating Rank in Partial Systems," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 388-399, October.
    10. repec:cup:cbooks:9780521822893 is not listed on IDEAS
    11. Slade, Margaret E., 1989. "Modelling stochastic and cyclical components of technical change : An application of the Kalman filter," Journal of Econometrics, Elsevier, vol. 41(3), pages 363-383, July.
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    1. Boug, Pål & Brasch, Thomas von & Cappelen, Ådne & Hammersland, Roger & Hungnes, Håvard & Kolsrud, Dag & Skretting, Julia & Strøm, Birger & Vigtel, Trond C., 2023. "Fiscal policy, macroeconomic performance and industry structure in a small open economy," Journal of Macroeconomics, Elsevier, vol. 76(C).
    2. Ådne Cappelen & Torbjørn Eika, 2020. "Immigration and the Dutch disease A counterfactual analysis of the Norwegian resource boom 2004-2013," Open Economies Review, Springer, vol. 31(3), pages 669-690, July.
    3. Pål Boug & Ådne Cappelen & Torbjørn Eika, 2013. "The importance of the distribution sector for exchange rate pass-through in a small open economy. A large scale macroeconometric modelling approach," Discussion Papers 731, Statistics Norway, Research Department.
    4. Thomas von Brasch & Marit Linnea Gjelsvik & Victoria Sparrman, 2018. "Deunionization and job polarization – a macroeconomic model analysis for a small open economy," Economic Systems Research, Taylor & Francis Journals, vol. 30(3), pages 380-399, July.
    5. Thomas von Brasch & Ådne Cappelen & Håvard Hungnes & Terje Skjerpen, 2020. "Modeling R&D spillovers to productivity. The effects of tax policy," Discussion Papers 927, Statistics Norway, Research Department.
    6. Pål Boug & Ådne Cappelen & Torbjørn Eika, 2013. "Exchange Rate Pass-through in a Small Open Economy: the Importance of the Distribution Sector," Open Economies Review, Springer, vol. 24(5), pages 853-879, November.
    7. von Brasch, T. & Cappelen, Å. & Hungnes, H. & Skjerpen, T., 2021. "Modeling R&D spillovers to productivity: The effects of tax credits," Economic Modelling, Elsevier, vol. 101(C).

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    More about this item

    Keywords

    Factor demand; technological changes; growth rates;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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