Arbeitspapier

Robust Dynamic Optimal Taxation and Environmental Externalities

We study a dynamic stochastic general equilibrium model where agents are concerned about model uncertainty regarding climate change. An externality from greenhouse gas emissions adversely affects the economy’s capital stock. We assume that the mapping from climate change to damages is subject to uncertainty, and we adapt and use techniques from robust control theory in order to study efficiency and optimal policy. We obtain a sharp analytical solution for the implied environmental externality, and we characterize dynamic optimal taxation. A small increase in the concern about model uncertainty can cause a significant drop in optimal energy extraction. The optimal tax which restores the social optimal allocation is Pigouvian. Under more general assumptions, we develop a recursive method and solve the model computationally. We find that the introduction of uncertainty matters qualitatively and quantitatively. We study optimal output growth in the presence and in the absence of concerns about uncertainty and find that these can lead to substantially different conclusions.

Sprache
Englisch

Erschienen in
Series: CESifo Working Paper ; No. 4562

Klassifikation
Wirtschaft
Economic History: Macroeconomics and Monetary Economics; Industrial Structure; Growth; Fluctuations: General, International, or Comparative

Ereignis
Geistige Schöpfung
(wer)
Li, Xin
Narajabad, Borghan
Temzelides, Ted
Ereignis
Veröffentlichung
(wer)
Center for Economic Studies and ifo Institute (CESifo)
(wo)
Munich
(wann)
2014

Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Li, Xin
  • Narajabad, Borghan
  • Temzelides, Ted
  • Center for Economic Studies and ifo Institute (CESifo)

Entstanden

  • 2014

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