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Poverty traps and business cycles in a stochastic overlapping generations economy with S-shaped law of motion

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  • Schenk-Hoppe, Klaus Reiner

Abstract

This paper contributes to the understanding of stochastic economic dynamics with S-shaped law of motion. Applying random dynamical systems theory, we obtain a complete analysis of a stochastic OLG growth model. In the long-run the economy converges either to a state with no capital (poverty trap) or a sample path of a random fixed point (business cycle). The threshold capital stock separating both regimes is a random variable that depends on the future realization of the shocks; this critical level cannot be identified using past observations. Supply of outside capital therefore has an uncertain effect. Policy recommendations are given which cannot be obtained employing Markov equilibria. A numerical illustration is provided.
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  • Schenk-Hoppe, Klaus Reiner, 2005. "Poverty traps and business cycles in a stochastic overlapping generations economy with S-shaped law of motion," Journal of Macroeconomics, Elsevier, vol. 27(2), pages 275-288, June.
    • Handle: RePEc:eee:jmacro:v:27:y:2005:i:2:p:275-288
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    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. Taylor, John B & Uhlig, Harald, 1990. "Solving Nonlinear Stochastic Growth Models: A Comparison of Alternative Solution Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 1-17, January.
    3. Schenk–Hoppé, Klaus Reiner, 2002. "Is There A Golden Rule For The Stochastic Solow Growth Model?," Macroeconomic Dynamics, Cambridge University Press, vol. 6(4), pages 457-475, September.
    4. Klaus Reiner Schenk-Hopp�, "undated". "Random Dynamical Systems in Economics," IEW - Working Papers 067, Institute for Empirical Research in Economics - University of Zurich.
    5. Wang, Yong, 1994. "Stationary Markov Equilibria in an OLG Model with Correlated Production Shocks," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 731-744, August.
    6. Wang Yong, 1993. "Stationary Equilibria in an Overlapping Generations Economy with Stochastic Production," Journal of Economic Theory, Elsevier, vol. 61(2), pages 423-435, December.
    7. Costas Azariadis & Allan Drazen, 1990. "Threshold Externalities in Economic Development," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 105(2), pages 501-526.
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    Cited by:

    1. Kazuo Nishimura & Ryszard Rudnicki & John Stachurski, 2012. "Stochastic Optimal Growth with Nonconvexities," Springer Books, in: John Stachurski & Alain Venditti & Makoto Yano (ed.), Nonlinear Dynamics in Equilibrium Models, edition 127, chapter 0, pages 261-288, Springer.
    2. Hatjispyros, S.J. & Nicoleris, Theodoros & Walker, Stephen G., 2007. "Parameter estimation for random dynamical systems using slice sampling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 381(C), pages 71-81.
    3. Elliott, Robert J. & Chen, Zhiping & Duan, Qihong, 2009. "Insurance claims modulated by a hidden Brownian marked point process," Insurance: Mathematics and Economics, Elsevier, vol. 45(2), pages 163-172, October.
    4. Kazuo Nishimura & Ryszard Rudnicki & John Stachurski, 2004. "Stochastic Growth With Nonconvexities:The Optimal Case," Department of Economics - Working Papers Series 897, The University of Melbourne.

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    More about this item

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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