Wednesday, May 12, 2021

Fifth Francqui Lecture: Econometric Modeling of Climate Change

The video of my fifth and final Francqui lecture on the econometric modeling of climate change is now on Youtube:  


The lecture begins by introducing the issue of global climate change. The first image of the Earth's energy balance is from an IPCC assessment report. Probably, the 4th Assessment Report. The graph of global temperature is the Berkeley Earth combined land and sea series. The graph of CO2 concentration is based on the data we used in our Journal of Econometrics paper updated with recent observations from Hawaii. The original source of the global CO2 emissions series is the now defunct CDIAC website updated from the BP Statistical Review of World Energy. Following that are three charts from the IPCC 5th Assessment Report. World sulfur dioxide emissions are from the CEDS datasite.

The next section – "Why Econometrics" – opens with a graph of the relationship between economic growth and CO2 emissions, which I put together from World Bank, International Energy Agency, and BP data sources.

The following section – "Do GHG Emissions Cause Climate Change?" starts with original research using the temperature and CO2 time series in the previous graphs. The CO2 concentration acts as a proxy variable for all radiative forcing in this analysis. It then goes on to present results from my 2014 paper with Robert Kaufmann published in Climatic Change. Details of the data are given in that paper.

Finally, I presented my paper coauthored with Stephan Bruns and Zsuzsanna Csereklyei, which was published in the Journal of Econometrics.

Public Policy Schools in the Asia-Pacific Ranked

I have a new paper with my Crawford School colleague Bjoern Dressel published in Asia & the Pacific Policy Studies (open access). The data and figures for the article are on Figshare. Bjoern has been interested for a while in ranking public policy schools in the Asia-Pacific region.  But a comprehensive ranking seemed hard to achieve. Recently, I came across an article by Ash and Urquiola (2020) that ranks US public policy schools according to their research output and impact. Well, we thought, if they can rank schools just by their research output and not by their education and public policy impact then so can we 😀. Research is the easiest component to evaluate.

We compare the publication output of 45 schools with at least one publication listed in Scopus between 2014 and 2018, based on affiliations listed on the publications rather than current faculty. We compute the 5-Year impact factor for each school. This is identical to the impact factor reported for academic journals, but we compute it for a school rather than a journal. It is the mean number of citations received in 2019 by a publication published between 2014 and 2018. This can be seen as an estimate of research quality. We also report the standard error of the impact factor as in my 2013 article in the Journal of Economic Literature. If we treat the impact factor as an estimate of the research quality of a school then we can construct a confidence interval to express how certain or uncertain we are about that estimate. This graph shows the schools ranked by impact factor with a 90% confidence interval:

Peking and Melbourne are the two top-ranked schools but the point estimates have a very wide confidence interval. This is because their research output is relatively small and the variance of citations is quite large. The third ranked school – SGPP in Indonesia – only had two publications in our target period. After that there are several schools with much narrower confidence intervals. These mostly have more publications.


Here we can see the impact factors on the y-axis and the number of publications of each school on the x-axis. Three schools clearly stand out at the right: Crawford, Lee Kwan Yew, and Tsinghua. These schools are also top-ranked by total citations, which combines the quality and quantity variables. The three top schools account for 54% of publications and 63% of citations from the region.

In general, the elite schools are in China and Australia. Australia has three out of the top ten schools ranked by impact factor and total citations, despite its small population size. China, on the other hand has at least five schools ranked in the top ten across both rankings, which is remarkable given that many of these schools have been established only in the last 15 years (though linked to well-established research universities).

We found more schools that had no publications in Scopus in the target period. Perhaps in some cases they are too new, or faculty use their other affiliations, but clearly there is a lot of variation in research-intensiveness. Somewhat surprising is the low ranking of public policy schools in Japan and India – both countries with a considerable number of public policy schools, but none in the top ten schools when ranked by 5-year citation impact factor or total number of citations. 

One reason for the strong performance of the Chinese schools is that they focus to some degree on environmental issues, and particularly climate change, where citation numbers tend to be higher. We did not adjust for differences in citations across fields in this research, but this is something that future research should address.