Researchers report estimates of uncertainty in long-run economic growth forecasts. Modeling uncertainty in forecasts of long-run economic growth is an essential part of climate change research that the Intergovernmental Panel on Climate Change (IPCC) has highlighted as a priority. Peter Christensen and colleagues developed comprehensive estimates of uncertainty in long-run projections of global and regional per capita economic growth rates. The authors used two methods to estimate per capita GDP growth rates and their uncertainties through the year 2100: a survey of 16 experts' predictions and a statistical method designed to estimate variability in annual average growth rates on the timescale of a decade or longer. The interquartile range of the average global growth rates to 2100 from expert forecasts was 1.4-2.9% per year, whereas that from the statistical forecasts was 1.7-2.7% per year. Both methods indicated greater uncertainty in long-term growth rates than is assumed in the full range of climate change scenarios, implying a greater likelihood of extreme climate-change outcomes than is currently assumed. The authors modeled the distribution of projected greenhouse gas emissions using these long-run growth rates and found greater than 35% chance of exceeding the highest values assumed in the IPCC's Representative Concentration Pathways. According to the authors, the large uncertainty about future growth has implications for climate policy and other social programs that rely upon long-run growth forecasts.
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Article #17-13628: "Uncertainty in forecasts of long-run economic growth," by Peter Christensen, Kenneth Gillingham, and William Nordhaus.
MEDIA CONTACT: Peter A. Christensen, University of Illinois at Urbana-Champaign, IL; tel: 203-506-6724; e-mail: <pchrist@illinois.edu>
Journal
Proceedings of the National Academy of Sciences