This speech feels generated by an old short-memory nlp model, Γ la LDA. I am not entirely sure one can back out any signal from such a noisy ramble.
A European strategic autonomy would partially shield us from having to extract meaning from speeches like this.
Interesting work. I did not expect a recalibration of DICE16 to "fix" Dietz et al. (2021), but I guess Von Neumann's elephant is very flexible.
The question seems to be: can we make tests for CEs independent of the optimisation problem we are after?
Climate models since the 1970s nailed itβmost predicted global warming almost exactly as it happened.
If you are at #CCN2025, check this out.
Are you planning to attend #CCN2025? Do you want to reflect on how to direct your skills and aptitudes to tackle today's most pressing social problems? Make sure you come to Amsterdam a day early to attend our satellite event on Science for Social Good. Register here: forms.gle/TFRCZYX2qfwD...
A chart showing bigass roots on a whole bunch of plants.
Thereβs a famous chart from the Conservation Research Institute, which demonstrates this. GAZE UPON THESE ROOTS, YE MIGHTY AND DESPAIR.
Heading to the AOM Meeting in Copenhagen? Interested in Climate Risks, Risk Perception, and Risk Management in the Supply Chain? Stop by my poster presentation on βValue Chain Dependencies and Climate Risks in the Value Chainβ. @ifmbonn.bsky.social #AOM2025 #ClimateRisk #RiskPerception #EconSky
Chart showing the EU vs US: Relative state of technology by sector. The EU leads the US technologically in food products and wearing apparel. Amid geopolitical shocks, the EU is revisiting its industrial strategy. However, traditional metrics often paint a misleading picture of Europeβs underlying strength. This column uses a new approach to measure the EUβs relative state of technology in different sectors. It shows that although EU manufacturing broadly outperforms the rest of the world in productivity terms, the industries in which it specialises are not always those in which it is relatively more productive. It argues that industrial policy must be rooted in productivity diagnostics and support should target sectors with strong relative state of technology but weak trade performance.
#EU manufacturing broadly outperforms the rest of the world in #productivity terms, but the industries in which it specialises are not always those in which it is relatively more productive. Policy should target weak #trade sectors.
F Di Mauro, M Matani, G Ottaviano
cepr.org/voxeu/column...
#EconSky
The Nievas-Piketty unequal exchange paper is certainly better than Hickel's, but their counterfactual assertion of convergence between countries in 1800-2025 is based on these entirely political-economy-free assumptions
I have cleaned a bit my lecture notes on Optimal Transport for Machine Learners arxiv.org/abs/2505.06589
I couldn't agree more!
The excessive focus on linearized solutions to HA models is a bit like the old joke about the drunk who is looking for a key under a lamppost because that's where the light is.
More discussion of why we need non-linear models and ways forward here benjaminmoll.com/challenge/
.@cheussaff.bsky.social and my Policy Brief:
"Upgrading Europe's electricity grid is about more than just money" has just been published.
www.bruegel.org/policy-brief...
As @shengwuli.bsky.social always says, when you notice the network theorists getting really excited, you're probably in for a bad time.
What are you basing this off?
Here (www.sciencedirect.com/science/arti...) they found a reduction in flights from carbon pricing.
Perfect timing: I just finished watching the Michael Penn series on differential forms. It makes me want to dig back into differential geometry.
If I have time and get around to it, I will try and turn this code into a proper package for the #JuliaLang, contributing to the "bottom left quadrant" of dynamic optimization problem, as discussed here by Albert Zevelev (not on Bluesky yet?) here:
You can also find a preliminary implementation of the same idea for differential games (Kushner, 2007) in the repository, which I will be using in a future paper that studies climate agreements in the presence of tipping points. π
In the paper's Appendix, I prove the algorithm's convergence for Epstein-Zin recursive preferences.
I also leverage the excellent implementation of the ZigZag algorithm by ZigZagBoomerang.jl to parallelise everything and run it on the Snellius supercomputer. π
This approach makes your algorithm focus on where it really matters (around the tipping point), rather than wasting time computing policies at boring steady states.
To solve this in a reasonable time, I take an old and relatively straightforward idea from one of my favourite books, Kushner & Dupouis, from 2001.
Just take time steps that get shorter and shorter around the tipping point! Now your time discretisation is state and control dependent.
In the paper, I compute optimal emissions abatement in a climate with tipping points.
As you approach the tipping point, computing optimal emission abatements can be challenging, as you should tread carefully: small mistakes can lead to abrupt and dire consequences! πΏ
The code from my #JMP is now available here: github.com/NoFishLikeIan/carbon-tipping-point
#EconSky: if you are interested in stochastic optimal control problems, #JuliaLang or the climate, read further! Β π§΅
A while ago Alex London and I noticed that many of the objections to utilitarianism depend on a utilitarian being in a world of non-utilitarians.
There would be no forced organ harvesting in a world of utilitarians. People would line up to volunteer.
...
This inequality says that if y=Ο(x) is a continuous, strictly increasing function of x, for xβ₯0, with Ο(0)=0 then (note Ο^{-1}(y) is the function inverse) 2/
Discretisation memes! π
Nice, good timing then! Always happy to talk about it.
Since a few more people decided to follow me in the last week (π and π), let me re-up my #EconJMP, maybe using the right hashtag this time! #EconSky
If you are interested in climate economics and tipping points, check it out:
bsky.app/profile/nofi...
Advertising for a PhD position at Oxford working with me and Tad Komacek. Project is on climate modelling using automatic differentiation with Enzyme in SpeedyWeather.jl applied to Earth and exoplanets. Plenty of space for ML/GPU/HPC/data visualisation projects within that PhD position too!
Got my first paper rejection after a few months of review. But two great reports came with it.
Time to dive back in... π€Ώ
After the job market... π’
#EconSky
Would love to be added too! β
