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Long horizon versus short horizon planning in dynamic optimization problems with incomplete information

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  • Herbert Dawid

Abstract

This paper compares the implications of short and long horizon planning in dynamic optimization problems with the structure of a standard one-sector growth model if agents have incomplete knowledge about the production function. Agents know the output and rate of return at the current capital stock and use an estimation of the production function based on this knowledge to determine current consumption. For standard utility functions without wealth-effects both long and short planning horizons yield convergence to the steady state - however at a faster rate than optimal -, or fluctuations around the steady state, and in both cases, long horizon planning yields a policy which locally at the steady state is closer to the optimal one than short horizon planning. On the other hand, for preferences with wealth effects where the intertemporal optimal path exhibits fluctuations, long horizon planning destabilizes the path and short horizon planning can generate paths which are qualitatively closer to the optimal one and yield higher discounted utility. Copyright Springer-Verlag Berlin/Heidelberg 2005

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  • Herbert Dawid, 2005. "Long horizon versus short horizon planning in dynamic optimization problems with incomplete information," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 25(3), pages 575-597, April.
    • Handle: RePEc:spr:joecth:v:25:y:2005:i:3:p:575-597
    DOI: 10.1007/s00199-003-0437-5
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    Citations

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    Cited by:

    1. Teglio, Andrea & Catalano, Michele & Petrovic, Marko, 2014. "Myopic households on a stable path: the neoclassical growth model with rule-based expectations," MPRA Paper 120253, University Library of Munich, Germany.
    2. Arifovic, Jasmina & Dawid, Herbert & Deissenberg, Christophe & Kostyshyna, Olena, 2010. "Learning benevolent leadership in a heterogenous agents economy," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1768-1790, September.
    3. Liam Graham, 2011. "Individual rationality, model-consistent expectations and learning," CDMA Working Paper Series 201112, Centre for Dynamic Macroeconomic Analysis.
    4. Cellarier, Laurent L., 2021. "Is landownership a ladder out of poverty?," World Development, Elsevier, vol. 146(C).
    5. Cellarier, Laurent L., 2008. "Least squares learning and business cycles," Journal of Economic Behavior & Organization, Elsevier, vol. 68(3-4), pages 553-564, December.
    6. Cellarier, Laurent L., 2013. "A family production overlapping generations economy," Journal of Economic Dynamics and Control, Elsevier, vol. 37(11), pages 2168-2179.
    7. Dawid, Herbert & Day, Richard H., 2007. "On sustainable growth and collapse: Optimal and adaptive paths," Journal of Economic Dynamics and Control, Elsevier, vol. 31(7), pages 2374-2397, July.
    8. Mosnier, C. & Agabriel, J. & Lherm, M. & Reynaud, A., 2009. "A dynamic bio-economic model to simulate optimal adjustments of suckler cow farm management to production and market shocks in France," Agricultural Systems, Elsevier, vol. 102(1-3), pages 77-88, October.

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