Environmental tipping points significantly affect the cost benefit assessment of climate policies. Cai, Y., Judd, K. L., Lenton, T. M., Lontzek, T. S., & Narita, D. Proceedings of the National Academy of Sciences, 112(15):4606–4611, April, 2015.
Environmental tipping points significantly affect the cost benefit assessment of climate policies [link]Paper  doi  abstract   bibtex   
Most current cost−benefit analyses of climate change policies suggest an optimal global climate policy that is significantly less stringent than the level required to meet the internationally agreed 2 °C target. This is partly because the sum of estimated economic damage of climate change across various sectors, such as energy use and changes in agricultural production, results in only a small economic loss or even a small economic gain in the gross world product under predicted levels of climate change. However, those cost−benefit analyses rarely take account of environmental tipping points leading to abrupt and irreversible impacts on market and nonmarket goods and services, including those provided by the climate and by ecosystems. Here we show that including environmental tipping point impacts in a stochastic dynamic integrated assessment model profoundly alters cost−benefit assessment of global climate policy. The risk of a tipping point, even if it only has nonmarket impacts, could substantially increase the present optimal carbon tax. For example, a risk of only 5% loss in nonmarket goods that occurs with a 5% annual probability at 4 °C increase of the global surface temperature causes an immediate two-thirds increase in optimal carbon tax. If the tipping point also has a 5% impact on market goods, the optimal carbon tax increases by more than a factor of 3. Hence existing cost−benefit assessments of global climate policy may be significantly underestimating the needs for controlling climate change.
@article{cai_environmental_2015,
	title = {Environmental tipping points significantly affect the cost benefit assessment of climate policies},
	volume = {112},
	issn = {0027-8424, 1091-6490},
	shorttitle = {Environmental tipping points significantly affect the cost?},
	url = {http://www.pnas.org/lookup/doi/10.1073/pnas.1503890112},
	doi = {10.1073/pnas.1503890112},
	abstract = {Most current cost−benefit analyses of climate change policies suggest an optimal global climate policy that is significantly less stringent than the level required to meet the internationally agreed 2 °C target. This is partly because the sum of estimated economic damage of climate change across various sectors, such as energy use and changes in agricultural production, results in only a small economic loss or even a small economic gain in the gross world product under predicted levels of climate change. However, those cost−benefit analyses rarely take account of environmental tipping points leading to abrupt and irreversible impacts on market and nonmarket goods and services, including those provided by the climate and by ecosystems. Here we show that including environmental tipping point impacts in a stochastic dynamic integrated assessment model profoundly alters cost−benefit assessment of global climate policy. The risk of a tipping point, even if it only has nonmarket impacts, could substantially increase the present optimal carbon tax. For example, a risk of only 5\% loss in nonmarket goods that occurs with a 5\% annual probability at 4 °C increase of the global surface temperature causes an immediate two-thirds increase in optimal carbon tax. If the tipping point also has a 5\% impact on market goods, the optimal carbon tax increases by more than a factor of 3. Hence existing cost−benefit assessments of global climate policy may be significantly underestimating the needs for controlling climate change.},
	language = {en},
	number = {15},
	urldate = {2017-06-29},
	journal = {Proceedings of the National Academy of Sciences},
	author = {Cai, Yongyang and Judd, Kenneth L. and Lenton, Timothy M. and Lontzek, Thomas S. and Narita, Daiju},
	month = apr,
	year = {2015},
	keywords = {DR, Damages, Geography: Global, IAM: Yes, Sector: Tipping Elements, Tags Edited, Valuation: Yes},
	pages = {4606--4611},
}

Downloads: 0