Abstract
We propose a general emulation method for constructing low-dimensional approximations of complex dynamic climate models. Our method uses artificially designed uncorrelated CO2 emissions scenarios, which are much better suited for the construction of an emulator than are conventional emissions scenarios. We apply our method to the climate model MAGICC to approximate the impact of emissions on global temperature. Comparing the temperature forecasts of MAGICC and our emulator, we show that the average relative out-of-sample forecast errors in the low-dimensional emulation models are below 2%. Our emulator offers an avenue to merge modern macroeconomic models with complex dynamic climate models.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 67-80 |
| Number of pages | 14 |
| Journal | Journal of Econometrics |
| Volume | 214 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2020 |
Funding
We are grateful to three anonymous referees for helpful reviews of earlier versions and to the guest editor Eric Hillebrand for his guidance. We thank the participants at the 2014 Initiative on Computational Economics at the Hoover Institution, at the conference “Econometric Models of Climate Change 2016” at the University of Aarhus, and at the 23rd Annual Conference of the European Association of Environmental and Resource Economists (2017) for helpful comments. We are indebted to Marc Paolella for his helpful advice and to Dave Brooks for excellent editorial support. Alena Miftakhova gratefully acknowledges financial support from the Swiss National Science Foundation. We are grateful to three anonymous referees for helpful reviews of earlier versions and to the guest editor Eric Hillebrand for his guidance. We thank the participants at the 2014 Initiative on Computational Economics at the Hoover Institution, at the conference “Econometric Models of Climate Change 2016” at the University of Aarhus, and at the 23rd Annual Conference of the European Association of Environmental and Resource Economists (2017) for helpful comments. We are indebted to Marc Paolella for his helpful advice and to Dave Brooks for excellent editorial support. Alena Miftakhova gratefully acknowledges financial support from the Swiss National Science Foundation .
Keywords
- Climate change
- Greenhouse gas
- Orthogonal polynomials
- Single equation models
ASJC Scopus subject areas
- Economics and Econometrics
