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Pollution control: when, and how, to be precautious

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  • Stergios Athanassoglou
  • Anastasios Xepapadeas

Abstract

The precautionary principle (PP) applied to environmental policy stipulates that, in the pres- ence of physical uncertainty, society must take take robust preventive action to guard against worst-case outcomes. It follows that the higher the degree of uncertainty, the more aggressive this preventive action should be. This normative maxim is explored in the case of a stylized dy- namic model of pollution control under Knightian uncertainty. At time 0 a decisionmaker makes a one-time investment in damage-control technology and subsequently decides on a desirable dynamic emissions policy. Adopting the robust control framework of Hansen and Sargent [10], we investigate optimal damage-control and mitigation policies. We show that optimal invest- ment in damage control is always increasing in the degree of uncertainty, thus con rming the conventional PP wisdom. Optimal mitigation decisions, however, need not always comport with the PP and we provide analytical conditions that sway the relationship one way or the other. This result is interesting when contrasted to a model with xed damage-control technology, in which it can be easily shown that a PP vis-a-vis mitigation unambiguously holds. We conduct a set of numerical experiments to determine the sensitivity of our results to speci c functional forms of damage-control cost. We nd that when the cost of damage-control technology is low enough, damage-control investment and mitigation may act as substitutes and a PP with respect to the latter can be unambiguously irrational.

Suggested Citation

  • Stergios Athanassoglou & Anastasios Xepapadeas, 2011. "Pollution control: when, and how, to be precautious," DEOS Working Papers 1112, Athens University of Economics and Business.
  • Handle: RePEc:aue:wpaper:1112
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    References listed on IDEAS

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    Cited by:

    1. W. Brock & A. Xepapadeas & A. Yannacopoulos, 2014. "Robust Control and Hot Spots in Spatiotemporal Economic Systems," Dynamic Games and Applications, Springer, vol. 4(3), pages 257-289, September.
    2. William Brock & Anastasios Xepapadeas & Athanasios Yannacopoulos, 2014. "Spatiotemporal robust control in infinite dimensional spaces," DEOS Working Papers 1405, Athens University of Economics and Business.
    3. Heuson, Clemens & Gawel, Erik & Gebhardt, Oliver & Hansjürgens, Bernd & Lehmann, Paul & Meyer, Volker & Schwarze, Reimund, 2012. "Fundamental questions on the economics of climate adaptation: Outlines of a new research programme," UFZ Reports 05/2012, Helmholtz Centre for Environmental Research (UFZ).
    4. Tobon Orozco, David & Molina Guerra, Carlos & Vargas Cano, John Harvey, 2016. "Extent of Expected Pigouvian Taxes and Permits for Environmental Services in a General Equilibrium Model with a natural capital constraint," Borradores Departamento de Economía 15258, Universidad de Antioquia, CIE.

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    More about this item

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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