Environmental and Resource Economics

, Volume 64, Issue 3, pp 349–372 | Cite as

A Dynamic Game of Emissions Pollution with Uncertainty and Learning

  • Nahid Masoudi
  • Marc Santugini
  • Georges Zaccour


We introduce learning in a dynamic game of international pollution, with ecological uncertainty. We characterize and compare the feedback non-cooperative emissions strategies of players when the players do not know the distribution of ecological uncertainty but they gain information (learn) about it. We then compare our learning model with the benchmark model of full information, where players know the distribution of ecological uncertainty. We find that uncertainty due to anticipative learning induces a decrease in total emissions, but not necessarily in individual emissions. Further, the effect of structural uncertainty on total and individual emissions depends on the beliefs distribution and bias. Moreover, we obtain that if a player’s beliefs change toward more optimistic views or if she feels that the situation is less risky, then she increases her emissions while others react to this change and decrease their emissions.


Pollution emissions Dynamic games Uncertainty  Learning 

JEL Classification

Q50 D83 D81 C73 


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Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Nahid Masoudi
    • 1
  • Marc Santugini
    • 2
  • Georges Zaccour
    • 3
  1. 1.Department of EconomicsConcordia University, GERADMontrealCanada
  2. 2.IEA and CIRPEEHEC MontréalMontrealCanada
  3. 3.GERAD, HEC MontréalMontrealCanada

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