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Long‐Term Forecasting of Global Carbon Dioxide Emissions: Reducing Uncertainties Using a Per Capita Approach
Author(s) -
Mckitrick Ross,
Strazicich Mark C.,
Lee Junsoo
Publication year - 2013
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.2248
Subject(s) - per capita , econometrics , range (aeronautics) , economics , environmental science , monte carlo method , term (time) , quartile , yield (engineering) , statistics , natural resource economics , mathematics , confidence interval , population , materials science , demography , physics , quantum mechanics , sociology , composite material , metallurgy
Global CO 2 emission forecasts span such a wide range as to yield little guidance for climate policy and analysis. But global per capita emissions appear to be better constrained than total emissions, which we argue has an economic justification. Trend stationarity of per capita emissions may provide a means of characterizing the relative likelihood of global forecasts. On data spanning 1950 to 2009 a unit root hypothesis allowing for endogenous structural breaks is rejected, but adding in the 2010 observation pushes the p ‐value slightly over 0.1. Since structural breaks cannot be detected at the end of sample this may simply indicate a power problem. Using Monte Carlo simulations we conclude that the lower half of a well‐known suite of IPCC emission scenarios is more likely to occur than the upper half, and the top quartile is particularly difficult to justify. Copyright © 2013 John Wiley & Sons, Ltd.