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Optimal Control of Linear Econometric Models with Intermittent Controls

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  • Deissenberg, Christophe

Abstract

Dynamic Programming is used to derive the optimal feedback solution to the minimization of a quadratic welfare loss-functional subject to a linear econometric model, when the value of some instrument variables can not be optimized in every model period, but only in single ones. In this way, the relative inertia of fiscal policy-making, as compared to monetary policymaking, can e.g. be taken into account. Analytical expressions are derived for the optimal feedback rules and for the minimum expected losses, and literative schemes are proposed for their numerical computation. It is suggested that a numerical analysis of the economic gain to be realized by making more frequent adjustment of fiscal policy variables than is actually the case could yield valuable information for policy-makers.
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Suggested Citation

  • Deissenberg, Christophe, 1980. "Optimal Control of Linear Econometric Models with Intermittent Controls," Economic Change and Restructuring, Springer, vol. 16(1), pages 49-56.
  • Handle: RePEc:kap:ecopln:v:16:y:1980:i:1:p:49-56
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    Cited by:

    1. Yu, Juan & Hu, Cheng & Jiang, Haijun & Teng, Zhidong, 2012. "Exponential lag synchronization for delayed fuzzy cellular neural networks via periodically intermittent control," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(5), pages 895-908.
    2. Chu, Xiaoyan & Xu, Liguang & Hu, Hongxiao, 2020. "Exponential quasi-synchronization of conformable fractional-order complex dynamical networks," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    3. David Kendrick & George Shoukry, 2014. "Quarterly Fiscal Policy Experiments with a Multiplier-Accelerator Model," Computational Economics, Springer;Society for Computational Economics, vol. 44(3), pages 269-293, October.
    4. Hu, Cheng & Yu, Juan, 2016. "Generalized intermittent control and its adaptive strategy on stabilization and synchronization of chaotic systems," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 262-269.

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