Projections of the gross world product GWP for the 21st century are computed on a simple climatendash;macroeconomic model using different global mean surface air temperature projections provided by General Circulation Models GCMs as input data. Two alternative specifications of climate damage functions proposed by Nordhaus and Weitzman are considered. High uncertainty of long-term global macroeconomic dynamics with respect to the choice of climate scenarios and climate damage functions is revealed. Strong nonlinearity of the Weitzman function combined with the "worst-case" temperature scenario yields a very dramatic scenario of long-term global economic development. A high degree of uncertainty accompanying existing assessments of climate#x2013;socioeconomic projections urgently calls for more detailed and better justified estimations of anticipated climate damages at high temperature increases above pre-industrial level.
climate change, economic growth, climate damage function, uncertaint
1. Anderson, Beyond `dangerous' climate change: emission scenarios for a new world, Philosophical Transactions of the Royal Society A, v. 369, 2011., doi:https://doi.org/10.1098/rsta.2010.0290
2. Atkinson, Global temperatures continue to rise, Universe Today,, 2013.
3. Barro, Economic Growth, 2003.
4. Bobylev, Arctic Environment Variability in the Context of Global Change, 2003.
5. Capellan-Perez, New climate scenario framework implementation in the GCAM integrated assessment model. BC3 Working Paper Series 2014-04. Basque Centre for Climate Change BC3. Bilbao, Spain, 2014.
6. Hasselmann, Detecting and responding to climate change, Tellus B, v. 65, 2013., doi:https://doi.org/10.3402/tellusb.v65i0.20088
7. IPCC, Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, 2007.
8. IPCC, Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, 2013.
9. Jaeger, Three views of two degrees, Regional Environmental Change, v. 11, 2011., doi:https://doi.org/10.1007/s10113-010-0190-9
10. Mann, Defining dangerous anthropogenic interference, Proceedings of the National Academy of Sciences of the USA, v. 106, 2009., doi:https://doi.org/10.1073/pnas.0901303106
11. Matveenko, Stimulating mechanisms in ecologically motivated regulation: will ecological policies in transition and developing countries become efficient?, Journal of the New Economic Association, v. 8, 2010.
12. Nordhaus, A Question of Balance, 2008.
13. Ortiz, Integrated Impact Assessment models with an emphasis on damage functions: a literature review. BC3 Working Paper Series 2009-06. Basque Centre for Climate Change BC3. Bilbao, Spain, 2009.
14. Peters, The challenge to keep global warming below 2$^\circ $C, Nature Climate Change, v. 3, 2013., doi:https://doi.org/10.1038/nclimate1783
15. Pindyck, Climate change policy: What do the models tell us?, Journal of Economic Literature, v. 513, 2013., doi:https://doi.org/10.1257/jel.51.3.860
16. Porfiryev, The Economics of Climate Change, 2008.
17. Rodkin, Damage from natural disasters: Fast growth of losses or stable ratio?, Russian Journal of Earth Sciences, v. 10, 2008., doi:https://doi.org/10.2205/2007ES000267
18. Rovenskaya, Optimal economic growth under stochastic environmental impact: sensitivity analysis., Dynamic Systems, Economic Growth, and the Environment, v. 12, 2010., doi:https://doi.org/10.1007/978-3-642-02132-9_5
19. Shkol'nik, Changes in climate extremes on the territory of Siberia by the middle of the 21st century: An ensemble forecast based on the MGO regional climate model, Russian Meteorology and Hydrology, v. 372, 2012., doi:https://doi.org/10.3103/S106837391202001X
20. Smith, Assessing dangerous climate change through an update of the Intergovernmental Panel on Climate Change IPCC ``reasons for concern'', Proceedings of the National Academy of Sciences of the USA, v. 106, 2009., doi:https://doi.org/10.1073/pnas.0812355106
21. Stern, The Economics of Climate Change: The Stern Review, 2007.
22. Stroeve, Trends in Arctic sea ice extent from CMIP5, CMIP3 and observations, Geophysical Research Letters, v. 39, 2012., doi:https://doi.org/10.1029/2012GL052676
23. Taylor, An overview of CMIP5 and the experiment design, Bulletin of the American Meteorological Society, v. 934, 2012., doi:https://doi.org/10.1175/BAMS-D-11-00094.1
24. UNFCCC. Conference of the Parties COP, Report of the Conference of the Parties on its Fifteenth Session, held in Copenhagen from 7 to 19 December 2009. Addendum, Part two: Action taken by the Conference of the Parties at its Fifteenth Session,, 2010.
25. Voinov, Pricing strategies in inelastic energy markets: can we use less if we can't extract more?, Frontiers of Earth Science, v. 8, 2014., doi:https://doi.org/10.1007/s11707-013-0410-y
26. Volodin, Mathematical modeling of potential catastrophic climate changes, Russian Journal of Earth Sciences, v. 10, 2008., doi:https://doi.org/10.2205/2007ES000231
27. Weber, A multi-actor dynamic integrated assessment model MADIAM of induced technological change and sustainable economic growth, Ecological Economics, v. 54, 2005., doi:https://doi.org/10.1016/j.ecolecon.2004.12.035
28. Weitzman, GHG targets as insurance against catastrophic climate damages, Journal of Public Economic Theory, v. 142, 2012., doi:https://doi.org/10.1111/j.1467-9779.2011.01539.x
29. Wouter Botzen, How sensitive is Nordhaus to Weitzman? Climate policy in DICE with an alternative damage function, Economics Letters, v. 1171, 2012., doi:https://doi.org/10.1016/j.econlet.2012.05.032
