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Published online by Cambridge University Press:  06 February 2019

Francesco Lamperti*
Institute of Economics and EMbeDS, Scuola Superiore Sant’Anna and RFFCMCC European Institute on Economics and the Environment
Mauro Napoletano
Sciences Po, OFCE, Paris and SKEMA Business School, University Côte D’Azur and Institute of Economics, Scuola Superiore Sant’Anna
Andrea Roventini
Institute of Economics and EMbeDS, Scuola Superiore Sant’Anna and Observatoire Français des Conjonctures Economiques – Sciences Po
Address correspondence to: Francesco Lamperti, Institute of Economics, Scuola Superiore Sant’Anna, Piazza Martiri della Libertá 33, 56127 Pisa, Italy. e-mail:


The paper compares the effects of market-based (M-B) and command-and-control (C&C) climate policies on the direction of technical change and the prevention of environmental disasters. Drawing on a model of endogenous growth and directed technical change, we show that M-B policies (carbon taxes and subsidies toward clean sectors) suffer from path dependence and exhibit bounded window of opportunities: delays in their implementation make them ineffective both in redirecting technical change, (i.e. triggering a transition toward clean energy) and in avoiding environmental catastrophes. On the contrary, we find that C&C interventions are favored by path dependence and guarantee policy effectiveness irrespectively of the timing of their introduction. As the hypothesis of path dependence in technological change has received vast empirical support and it is a key feature of many models of growth, we argue that C&C policies should be seen as a valuable and non-equivalent alternative to M-B interventions.

© Cambridge University Press 2019

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This work was supported by the European Union Seventh FP for research, technological development, and demonstration under grant agreement No. 603416—Project IMPRESSIONS (impacts and risks from high-end scenarios: strategies for innovative solutions), the European Union’s Horizon 2020 research and innovation program under grant agreement No. 640772—DOLFINS and No. 649186—ISIGrowth. Moreover, the authors want to thank Giovanni Dosi, Daniele Giachini, Irene Monasterolo, and Alessandro Sapio for useful suggestions and discussions, as well as all the participants to the 2017 ISEFI Workshop for their comments. The comments of two referees and an associate editor helped improving the quality and readability of the paper. All the errors are responsibility of the authors.


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