The statistical analysis of climate data using methods that are commonly employed by econometricians has become increasingly important in recent years. The 5th Assessment Report of the Intergovernmental Panel for Climate Change (IPCC) noted in Ch. 10, p. 874:

“A number of studies have applied methods developed in the econometrics literature (Engle and Granger, 1987) to assess the evidence for a causal link between external drivers of climate and observed climate change, using the observations themselves to estimate the expected properties of internal climate variability (e.g., Kaufmann and Stern, 1997). The advantage of these approaches is that they do not depend on the accuracy of any complex global climate model, but they nevertheless have to assume some kind of model, or restricted class of models, of the properties of the variables under investigation”.

Climate change has, of course, been a research subject in economics for a long time, and environmental economics, energy economics, and macroeconomics have accumulated a well-developed literature, as evidenced, for example, by the 2018 Nobel Memorial Prize awarded to William D. Nordhaus (shared with Paul M. Romer).

In this annals issue we have collected articles that focus on the econometric analysis of climate data referred to in the IPCC quote, which is a relatively younger avenue. Many of the papers were presented at the first conference on Econometric Models of Climate Change in Aarhus in 2016, which so far has seen two successor conferences, at Oxford in 2017 and in Frascati in 2018. In 2019, the conference will be held in Milan.


Hillebrand, E., Pretis, F. & Proietti, T. (Editors) (2020). ‘Special Issue: Econometric Models of Climate Change’, Journal of Econometrics, 214(1), 1-294.
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