IDEAS home Printed from https://ideas.repec.org/p/ulp/sbbeta/2015-18.html
   My bibliography  Save this paper

A ’Jump’ in the Stochasticity of the Solow-Swan Growth Model

Author

Listed:
  • Claude Diebolt
  • Tapas Mishra
  • Mamata Parhi

Abstract

We characterize ’Solow-Swan’ economic growth model in a stochastic environment. Our interest basically lies in modelling arrival of uncommon or stochastic shocks in both physical capital and labour, introducing discontinuities in the growth of these variables. These characterizations are completed by employing a Jump process to the Solow-Swan model. Interesting dynamics of capital and labor growth emerge from our investigation.

Suggested Citation

  • Claude Diebolt & Tapas Mishra & Mamata Parhi, 2015. "A ’Jump’ in the Stochasticity of the Solow-Swan Growth Model," Working Papers of BETA 2015-18, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    • Handle: RePEc:ulp:sbbeta:2015-18
    as

    Download full text from publisher

    File URL: http://beta.u-strasbg.fr/WP/2015/2015-18.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Schenk-Hoppe, Klaus Reiner & Schmalfu[ss], Bjorn, 2001. "Random fixed points in a stochastic Solow growth model," Journal of Mathematical Economics, Elsevier, vol. 36(1), pages 19-30, September.
    2. Pennings, Enrico & Sereno, Luigi, 2011. "Evaluating pharmaceutical R&D under technical and economic uncertainty," European Journal of Operational Research, Elsevier, vol. 212(2), pages 374-385, July.
    3. Milton Barossi-Filho & Ricardo Gonçalves Silva & Eliezer Martins Diniz, 2005. "The empirics of the Solow growth model: Long-term evidence," Journal of Applied Economics, Universidad del CEMA, vol. 8, pages 31-51, May.
    4. Moreno, Manuel & Serrano, Pedro & Stute, Winfried, 2011. "Statistical properties and economic implications of jump-diffusion processes with shot-noise effects," European Journal of Operational Research, Elsevier, vol. 214(3), pages 656-664, November.
    5. Stachurski, John, 2002. "Stochastic Optimal Growth with Unbounded Shock," Journal of Economic Theory, Elsevier, vol. 106(1), pages 40-65, September.
    6. Milton Barossi-Filho & Ricardo Gonçalves Silva & Eliezer Martins Diniz, 2005. "The Empirics of the Solow Growth Model: Long-Term Evidence," Journal of Applied Economics, Taylor & Francis Journals, vol. 8(1), pages 31-51, May.
    7. Barossi-Filho, Milton & Goncalves Silva, Ricardo & Diniz, Eliezer Martins, 2005. "The empirics of the Solow Growth Model: Long-term evidence," Journal of Applied Economics, Universidad del CEMA, vol. 8(1), pages 1-21, May.
    8. Torben G. Andersen & Luca Benzoni & Jesper Lund, 2002. "An Empirical Investigation of Continuous‐Time Equity Return Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1239-1284, June.
    9. Robert C. Merton, 1975. "An Asymptotic Theory of Growth Under Uncertainty," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 42(3), pages 375-393.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Murach, Michael & Wagner, Helmut & Kim, Jungsuk & Park, Donghyun, 2022. "Trajectories to high income: Comparing the growth dynamics in China, South Korea, and Japan with cointegrated VAR models," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 492-511.
    2. Edwards, Jeffrey A. & Kasibhatla, Krishna, 2009. "Dynamic heterogeneity in cross-country growth relationships," Economic Modelling, Elsevier, vol. 26(2), pages 445-455, March.
    3. Berthold, Norbert & Gründler, Klaus, 2012. "Entrepreneurship and economic growth in a panel of countries," Discussion Paper Series 118, Julius Maximilian University of Würzburg, Chair of Economic Order and Social Policy.
    4. Bas Van Leeuwen & Peter Foldvari, 2008. "Human Capital and Economic Growth in Asia 1890–2000: A Time‐series Analysis," Asian Economic Journal, East Asian Economic Association, vol. 22(3), pages 225-240, September.
    5. Luis A. Quezada-Téllez & Guillermo Fernández-Anaya & Dominique Brun-Battistini & Benjamín Nuñez-Zavala & Jorge E. Macías-Díaz, 2021. "An Economic Model for OECD Economies with Truncated M -Derivatives: Exact Solutions and Simulations," Mathematics, MDPI, vol. 9(15), pages 1-14, July.
    6. Juchem Neto, J.P. & Claeyssen, J.C.R. & Pôrto Júnior, S.S., 2018. "Economic agglomerations and spatio-temporal cycles in a spatial growth model with capital transport cost," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 76-86.
    7. Max Kohler & Stefan Sperlich, 2019. "The Africa-Dummy: Gone with the Millennium?," Papers 1903.02357, arXiv.org.
    8. Darong Dai, 2014. "A Golden Formula in Neoclassical-Growth Models with Brownian-Motion Shocks," Scottish Journal of Political Economy, Scottish Economic Society, vol. 61(2), pages 211-228, May.
    9. Albeverio, Sergio & Mastrogiacomo, Elisa, 2022. "Large deviation principle for spatial economic growth model on networks," Journal of Mathematical Economics, Elsevier, vol. 103(C).
    10. Moreno, Manuel & Serrano, Pedro & Stute, Winfried, 2011. "Statistical properties and economic implications of jump-diffusion processes with shot-noise effects," European Journal of Operational Research, Elsevier, vol. 214(3), pages 656-664, November.
    11. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez & Manuel S. Santos, 2006. "Convergence Properties of the Likelihood of Computed Dynamic Models," Econometrica, Econometric Society, vol. 74(1), pages 93-119, January.
    12. Murach, Michael & Wagner, Helmut & Kim, Jungsuk & Park, Donghyun, 2020. "Trajectories to high income: comparing the growth dynamics in China, Korea, and Japan with cointegrated VAR models," CEAMeS Discussion Paper Series 16/2020, University of Hagen, Center for East Asia Macro-economic Studies (CEAMeS).
    13. Lars J. Olson & Santanu Roy, 2006. "Theory of Stochastic Optimal Economic Growth," Springer Books, in: Rose-Anne Dana & Cuong Le Van & Tapan Mitra & Kazuo Nishimura (ed.), Handbook on Optimal Growth 1, chapter 11, pages 297-335, Springer.
    14. Ali Khan, M. & Zhang, Zhixiang, 2023. "The random two-sector RSS model: On discounted optimal growth without Ramsey-Euler conditions," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    15. Auffret, Philippe, 2001. "An alternative unifying measure of welfare gains from risk-sharing," Policy Research Working Paper Series 2676, The World Bank.
    16. Takashi Kamihigashi & John Stachurski, 2011. "Existence, Stability and Computation of Stationary Distributions: An Extension of the Hopenhayn-Prescott Theorem," Discussion Paper Series DP2011-32, Research Institute for Economics & Business Administration, Kobe University.
    17. Biancardi, Marta & Di Bari, Antonio & Villani, Giovanni, 2021. "R&D investment decision on smart cities: Energy sustainability and opportunity," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).
    18. Mancini, Cecilia, 2008. "Large deviation principle for an estimator of the diffusion coefficient in a jump-diffusion process," Statistics & Probability Letters, Elsevier, vol. 78(7), pages 869-879, May.
    19. Klaus Reiner Schenk-Hopp�, "undated". "Economic Growth and Business Cycles: A Critical Comment on Detrending Time Series (Revised Version)," IEW - Working Papers 054, Institute for Empirical Research in Economics - University of Zurich.
    20. Nour Meddahi, 2002. "A theoretical comparison between integrated and realized volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 479-508.

    More about this item

    Keywords

    Stochastic Solow-Swan growth; Brownian motion; Jump process.;
    All these keywords.

    JEL classification:

    • E13 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Neoclassical
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • D2 - Microeconomics - - Production and Organizations

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ulp:sbbeta:2015-18. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/bestrfr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.