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@danielashby @AdamWJT @Greens4HS2 @TheGreenParty @GarethDennis @XRebellionUK @Hs2RebelRebel @HS2ltd I'll bite. Let's try to keep it factual. There's a reasonable basis to some aspects of this question, that it might be possible to agree on. Then there are other, more variable, elements which depend on external factors such as transport and energy policy. /1

@AdamWJT @Greens4HS2 @TheGreenParty @GarethDennis @XRebellionUK @Hs2RebelRebel @HS2ltd First up, we know reasonably well how much energy it takes to propel a high-speed train along the HS2 route. We can translate that into effective CO2 generated by making some assumptions about how green the electricity grid is. /2

@AdamWJT @Greens4HS2 @TheGreenParty @GarethDennis @XRebellionUK @Hs2RebelRebel @HS2ltd Secondly, we have a reasonable grasp of how much CO2 is going to be generated by building HS2 - there are standard methods of working this out, based on the amount of steel, concrete, earthmoving, machine-fuelling etc required. /3

@AdamWJT @Greens4HS2 @TheGreenParty @GarethDennis @XRebellionUK @Hs2RebelRebel @HS2ltd Thirdly, we can estimate how much CO2 is generated by cutting down trees, and how much is captured by planting new trees. We can also estimate how much CO2 is needed to keep the railway running and generated by maintaining the track /4

@AdamWJT @Greens4HS2 @TheGreenParty @GarethDennis @XRebellionUK @Hs2RebelRebel @HS2ltd We know how much CO2 is saved by moving goods by freight train on the lines freed up by moving the express trains on to HS2, rather than by truck. /5
Which metric is a better predictor of the severity of the fall surge in US states?

1) Margin of Democrat victory in Nov 2020 election
or
2) % infected through Sep 1, 2020

Can you guess which plot is which?


The left plot is based on the % infected through Sep 1, 2020. You can see that there is very little correlation with the % infected since Sep 1.

However, there is a *strong* correlation when using the margin of Biden's victory (right).

Infections % from
https://t.co/WcXlfxv3Ah.


This is the strongest single variable I've seen in being able to explain the severity of this most recent wave in each state.

Not past infections / existing immunity, population density, racial makeup, latitude / weather / humidity, etc.

But political lean.

One can argue that states that lean Democrat are more likely to implement restrictions/mandates.

This is valid, so we test this by using the Government Stringency Index made by @UniofOxford.

We also see a correlation, but it's weaker (R^2=0.36 vs 0.50).

https://t.co/BxBBKwW6ta


To avoid look-ahead bias/confounding variables, here is the same analysis but using 2016 margin of victory as the predictor. Similar results.

This basically says that 2016 election results is a better predictor of the severity of the fall wave than intervention levels in 2020!
There's blood on these streets. BUY THE DIP!

[A quick thread]


So yesterday I sold two of my holdings that I didn't like very much for the following


I know what you thinking: "smart move! 😎"
Will I be going on a buying frenzy today? Not quite. I think I'll sit today out. I've had some great lessons about the dip that I'd like to share with you.

I came across this fortune teller on YouTube who could predict pullbacks.


Of course I thought to myself, I'm going to be smart about this and decided to split my money over the full week because no one can predict the bottom. However, this