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Pensions and Growth: A Cointegration Analysis

Received: 7 May 2015     Accepted: 1 June 2015     Published: 3 July 2015
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Abstract

This article investigates the long-term relationship between economic growth and old-age provision using time series analysis, particularly the techniques of cointegration. The neoclassical growth model by Solow (1956) provides atheoretical basis for the empirical analysis. The results are based onquarterly data from 1970 to 2013 for the US-economy. In this work, the existence of a cointegrating relation between economic growth and pensions is verified by use of scientifically accepted statistical methods and proven for historical US-data. The empirical analysis confirms that improved technological capabilities constitute a very important determinant of growth in the context of neoclassical theory. The effects within the cointegrated relationship cannot be determined at this point and there is no information if the effect is reciprocal or not. For this purpose, further investigations are necessary and can build on the results presented here.

Published in Applied and Computational Mathematics (Volume 5, Issue 1-1)

This article belongs to the Special Issue Computational Methods in Monetary and Financial Economics

DOI 10.11648/j.acm.s.2016050101.13
Page(s) 21-35
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Growth, Old-Age Provision, Pensions, Time Series, Cointegration, Solow Model, Neoclassical Economics

References
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[3] Bretschger, L. (2004): Wachstumstheorie, R. Oldenbourg Verlag München Wien.
[4] Breyer, F. (1990): Ökonomische Theorie der Alterssicherung, Verlag Franz Vahlen München.
[5] Cass, David (1965): Optimum Growth in an Aggregative Model of Capital Accumulation, Review of Economic Studies 32 (3), 233-240.
[6] Christiaans, T. (2004): Neoklassische Wachstumstheorie Darstellung, Kritik und Erweiterung, Books on Demand GmbH Noderstedt.
[7] Engle, R.F. and Granger, C.W.J. (1987): Co-integration and error correction: representation, estimation, and testing, Econometrica 55, 251-276.
[8] Federal Reserve Bank of St. Louis (2015): FRED® Economic Data, https://research.stlouisfed.org/fred2/.
[9] Fisher, I. (1930): The Theory of Interest, New York: The Macmillan Co.
[10] Fujitsu Research Institute (1998): The Influence of Technological Progress on Labor Productivity, FRI Research Report No. 28.
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[12] Granger, C.W.J. (1986): Developments in the study of cointegrated economic variables, Oxford Bulletin of Economics and Statistics 48, 213-228.
[13] Granger, C.W.J. (2003): Time Series Analysis, Cointegration, and Applications, Nobel Prize Committee, 2003-7.
[14] Guest, R. and Swift, R. (2008): Fertility, income inequality, and labour productivity, Oxford Economic Papers, 60 (4), 597-618.
[15] Hauenschild, N. (1999): Alterssicherungssysteme im Rahmen stochastischer Modelle überlappender Generationen, Peter Lang Frankfurt Berlin Bern.
[16] Homburg, S. (1988): Theorie der Alterssicherung, Springer-Verlag Berlin Heidelberg New York.
[17] Hondroyiannis, G. and Papapetrou, E. (2001): Demographic changes, labor effort and economic growth: empirical evidence from Greece, Journal of Policy Modeling, 23 (2), 169-188.
[18] Johansen, S. (1988): Statistical analysis of cointegration vectors, Journal of Economic Dynamics and Control 12, 231-254.
[19] Johansen, S. (1991): Estimation and hypothesis testing of cointegration vectors in gaussian vector autoregressive models, Econometrica 59, 1551-1580.
[20] Jones, C. (2002): Introduction to Economic Growth, W. W. Norton & Company New York.
[21] Kaldor, N. (1961): Capital Accumulation and Economic Growth, in: Lutz, F.A. and Hague, D.C. (eds.), The Theory of Capital, St. Martins Press, pp. 177-222.
[22] Koopmans, T.C. (1965): On the Concept of Optimal Economic Growth, The Economic Approach to Development Planning Chicago.
[23] Liddle, B. and Lung, S. (2010): Age-structure, urbanization, and climate change in developed countries: revisiting STIRPAT for disaggregated population and consumption-related environmental impacts, Population and Environment, 31 (5), 317-343.
[24] Phillips, P.C.B. and Perron, P. (1988): Testing for a unit root in time series regression, Biometrika 75, 335–346.
[25] Ramsey, F.P. (1928): A Mathematical Theory of Saving, Economic Journal 38 (152), 543-559.
[26] Romer, P.M. (1989): What Determines the Rate of Growth and Technological Change?, World Bank Working Paper 279.
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[28] Shimotsu, K. (2012): Exact local Whittle estimation of fractionally cointegrated systems, Journal of Econometrics 169 (2), 266-278.
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Cite This Article
  • APA Style

    Miguel Rodriguez Gonzalez, Christoph Schwarzbach. (2015). Pensions and Growth: A Cointegration Analysis. Applied and Computational Mathematics, 5(1-1), 21-35. https://doi.org/10.11648/j.acm.s.2016050101.13

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    ACS Style

    Miguel Rodriguez Gonzalez; Christoph Schwarzbach. Pensions and Growth: A Cointegration Analysis. Appl. Comput. Math. 2015, 5(1-1), 21-35. doi: 10.11648/j.acm.s.2016050101.13

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    AMA Style

    Miguel Rodriguez Gonzalez, Christoph Schwarzbach. Pensions and Growth: A Cointegration Analysis. Appl Comput Math. 2015;5(1-1):21-35. doi: 10.11648/j.acm.s.2016050101.13

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  • @article{10.11648/j.acm.s.2016050101.13,
      author = {Miguel Rodriguez Gonzalez and Christoph Schwarzbach},
      title = {Pensions and Growth: A Cointegration Analysis},
      journal = {Applied and Computational Mathematics},
      volume = {5},
      number = {1-1},
      pages = {21-35},
      doi = {10.11648/j.acm.s.2016050101.13},
      url = {https://doi.org/10.11648/j.acm.s.2016050101.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acm.s.2016050101.13},
      abstract = {This article investigates the long-term relationship between economic growth and old-age provision using time series analysis, particularly the techniques of cointegration. The neoclassical growth model by Solow (1956) provides atheoretical basis for the empirical analysis. The results are based onquarterly data from 1970 to 2013 for the US-economy. In this work, the existence of a cointegrating relation between economic growth and pensions is verified by use of scientifically accepted statistical methods and proven for historical US-data. The empirical analysis confirms that improved technological capabilities constitute a very important determinant of growth in the context of neoclassical theory. The effects within the cointegrated relationship cannot be determined at this point and there is no information if the effect is reciprocal or not. For this purpose, further investigations are necessary and can build on the results presented here.},
     year = {2015}
    }
    

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  • TY  - JOUR
    T1  - Pensions and Growth: A Cointegration Analysis
    AU  - Miguel Rodriguez Gonzalez
    AU  - Christoph Schwarzbach
    Y1  - 2015/07/03
    PY  - 2015
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    T2  - Applied and Computational Mathematics
    JF  - Applied and Computational Mathematics
    JO  - Applied and Computational Mathematics
    SP  - 21
    EP  - 35
    PB  - Science Publishing Group
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    UR  - https://doi.org/10.11648/j.acm.s.2016050101.13
    AB  - This article investigates the long-term relationship between economic growth and old-age provision using time series analysis, particularly the techniques of cointegration. The neoclassical growth model by Solow (1956) provides atheoretical basis for the empirical analysis. The results are based onquarterly data from 1970 to 2013 for the US-economy. In this work, the existence of a cointegrating relation between economic growth and pensions is verified by use of scientifically accepted statistical methods and proven for historical US-data. The empirical analysis confirms that improved technological capabilities constitute a very important determinant of growth in the context of neoclassical theory. The effects within the cointegrated relationship cannot be determined at this point and there is no information if the effect is reciprocal or not. For this purpose, further investigations are necessary and can build on the results presented here.
    VL  - 5
    IS  - 1-1
    ER  - 

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Author Information
  • Institute for Risk and Insurance, Leibniz University Hanover, Hanover, Germany

  • Center for Risk and Insurance, Hanover, Germany

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