Environmental policy under model uncertainty: a robust optimal control approach

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Model uncertainty is inherent in the design of optimal environmental policy. We investigate the consequences in a simple linear model, where the aim of the policymaker is to stabilize the carbon content of the atmosphere. We study how decision-makers' concerns about robustness alter policy using the Hansen and Sargent (2000 approach. The analysis shows that a policymaker, who fears model misspecification should react more aggressively to changes in the stock of atmospheric carbon and implement policies which deliver a greater reduction of emissions. Terms of use: Documents in EconStor mayJEL Code: C61, Q25, Q28, D81.

Uncertainty and International Climate Change Negotiations

“…Because the home and foreign countries are symmetric, only one set of results is reported without being labelled as home or foreign. Overall, our results contridict the model predictions of Ulph and Ulph (1997) and Funke and Paetz (2011) that uncertainty justifies strong mitigation action and facilitates international policy coordination.…”

“…To model such beliefs, we follow the theory of minimax robust optimal control to assume the existence of a fictitious player called nature (see e.g., Zhou et al 1996;Basar and Bernhard 2008;Basar and Olsder 1999;Hansen and Sargent 2008;Funke and Paetz 2011). Given the home and foreign taxes (r h and r f ), nature strategically chooses the least-favorable combination of climatic and economic events (w h , w f , x h and x f ) to minimize home and foreign welfare due to carbon pricing, min w h ,x h {u h } and min w f ,x f u f or equivalently (because u h is independent of w f , x f ; and vice versa),…”

“…Other scholars have argued in favor of the non-probabilistic "maxmin" decision rule for maximizing the economic welfare for a worst case climate scenario (see e.g., Froyn 2005;Funke and Paetz 2011). Climate change is due to the cumulative nature of carbon concentration (Ulph and Ulph 1997;Weitzman 2012).…”

“…Nature strategically chooses the least-favorable combination of climatic and economic events (see e.g., Zhou et al 1996;Basar and Bernhard 2008;Basar and Olsder 1999;Hansen and Sargent 2008;Funke and Paetz 2011). If the policymakers increase efforts to mitigate, nature will decrease the impacts of climate change but increase the costs of mitigation, leading to the policymakers' regret of over-mitigation.…”

Urban Responses to Climate Change: Framework for Decisionmaking and Supporting Indicators

“…Figure B.1 thus situates control theory as a single actor lying between a system and decision-actor view. While some literature has applied the framework to global GHG mitigation (Funke et al, 2011), control theory offers two particularly relevant contributions to urban climate risk governance. First, the advent of urban big data that provide real-time monitoring of such parameters as traffic, energy use, water, transit ridership, and air quality can open opportunities for enhanced management of vital, climate-related city functions.…”