If the Chinese central planner Xi had decided against a zero-covid policy in China, this thing would have been far better.
But that's beside the point.
Had everyone followed the New Zealand model in the first year until vaccines were widespread and available, the virus would have gotten extinct just as Influenza Yamagata strain.
China has about 1.4 billion people - and all-time 5.226 COVID deaths. The US has 331 million people - about a quarter of China - and an all-time of 1.1 million people, about 200x of China.
As much as it pains me to write this, but China did the morally better thing here and actually cared about the lives of its citizens.
Their leaders have never ever cared about the lives of individual citizens. Xu’s hero, Mao, boasted that he would sacrifice as many innocent lives as he saw fit to reach his goals. The 5,000 number is laughable and meant only to keep Xi from executing party members, which he would certainly do if they told him anything approximating fact.
Eventually you will learn that way more than 5,000 people, mostly senior citizens, died from starvation alone during the recent months-long lockdown in Shanghai.
But that eats into profit margins today so it doesn't happen...
One thing I noticed is that smoothing functions that reduce overshooting the response also add some delay to the time taken to first reach the command threshold. This is interesting, if not quite surprising.
It's one of the fundamental techniques to get PIDs to work properly IRL. I can't find it right now, but I remember having a cheat sheet with a lot of tricks to make PIDs work properly. As a control engineer you learn a lot of fancy techniques, of which you usually only use a few, but practical PID control is sadly not taught in most courses because it's basically a collection of hacks.
If you know a little bit more about the system's behavior you can usually precalculate the optimal inputs and use the PID only for course correction, that often yields much better responses than what you can achieve with a controller alone.
If your system is nonlinear, it might be useful to use gain scheduling to adapt the PID parameters to the setpoint region you're operating in.
Switching behaviors in the system can also mess up your responses.
Sometimes your system has a vibrating frequency that can lead to resonance in your control. You may need to filter that, too, maybe even with a sliding frequency window. E.g. when controlling a gearbox attached to a motor, you don't want to actuate at the motor's vibrating frequency.
>smoothing functions that reduce overshooting the response also add some delay to the time taken
It's not so surprising if you think about what a low pass filter does. By filtering out the high frequencies the response becomes more sluggish, meaning that your input to the PID is already delayed. This means your PID reacts more slowly.
See Gosplan ([1]). They kind of tried. It will work better with an implementation that has more silicon than humans, but it will still be miserable on the edges.
"He is regarded as the founder of linear programming. He was the winner of the Stalin Prize in 1949 and the Nobel Memorial Prize in Economic Sciences in 1975."
In that respect, any book about linear programming is a good start. The problem with the approach used back in the time was a slow feedback loop (5-10 years) and inability to adjust to externalities, including technology changes. That should be possible to improve with our modern tech, but I am not aware of any good contemporary books about it - if someone knows one, I would appreciate a reference myself.
Edit: from the CIA file on Kantorovich ([2]):
"In addition to his mathematical research, Kantorovich has been directly involved in developing improved designs for high-speed digital computers, an activity apparently motivated by the Soviet Union's need for improved computers in solving large economic planning problems" "
1. https://en.wikipedia.org/wiki/Leonid_Kantorovich
2. https://en.wikipedia.org/wiki/Leonid_Kantorovich#/media/File...
https://www.google.com/search?q=red+plenty
It's a fictionalised history of some Soviet economics. There's a chapter on Kantorovich (cf the sibling comment). It goes reasonably deep (not mathematically deep) and provides a lot of context. Great book from a great author. Don't be put off by the "Soviet" part -- it's very entertaining.
I’ve seen a lot of Gosplan computer center. We were borrowing “untouched” versions of software for Soviet bloc-produced IBM-compatible mainframes there. At the exit there was a KGB post, they were checking for a permission for every single bit of paper that was being carried out. But we were not carrying paper, we were carrying magnetic tapes, and our contact at GVC (“the main computing center of”) Gosplan was too lazy to go get a permission for them. So I tucked a magnetic tape behind my belt and buttoned up my coat. Not a single time I was stopped. GVC Gosplan had a full detailed data on the Soviet economy and I could have potentially carried any secret data away.
But we were not carrying any secret data, we were carrying OS/360 21.8 and later on - VM/370 (do not remember the exact version for that, sorry).
So, while Gosplan was planning and financing the production and distribution of the “adapted for socialism” version of OS/360 (re)named ОС ЕС - their own computing center (and everyone else who could have got it) were using the original OS/360. I wonder if any mathematical model can handle such a situation properly.
But yes - the mathematical beauty of a planned economy model is often negated by sheer incompetence and corruption of the planner.
Also, to be cruel is not enough. You should have a political power to implement an effective solution. Political power is based on relationships. Suppose mathematics says: person A’s project should be reduced, person B’s project should be funded more. But: person A is your guy, and person B is of your rival’s camp. Will you follow the math? It’s probably a theorem: in a planned economy a recommendation that reduces the political power of a person that has the political power to implement it - will never be implemented…
Aka good, fast, cheap.
The alternative is forcing some slack in the supply chain but that comes at a significant cost to consumers.
Not sure about you, but I’d rather pay less not more for things, even if it means a temporary price increase or even shortage.
I’m amused by this comment.
You think the squeeze and now the glut didn’t come at a significant cost to consumers and the economy as a whole?
It seems pretty clear after the massive failure at the start of the pandemic that just-in-time went too far and there is not enough slack in the supply chain at all level. Even from a purely systemic look, the wild oscillation we see right now should be proof enough that the system is significantly under-dampened.
Paying 10% more for a product in perpetuity costs a lot more than a 12 to 24 month period where prices double. And for non-essential goods, the option is for some customers to simple delay purchase.
And you’re forgetting it works in both directions. Consumers may see temporary high prices but they often see temporary low prices during supply chain recovery.
And again, how do you accurately predict the future? Demand can double pretty quickly. Having 10% slack (and the cost of it) would have dampened higher prices somewhat, but now you’re paying higher prices all the time and slightly less high prices when things go sideways. Doesn’t seem like a good deal at all.
I’d much prefer the free market approach where there are multiple actors each making different bets on future demand than some overarching rule about how future demand should be planned for (thats how we get famines).
The producers who bet on increased demand (or shrinking supply from competitors) get handsomely rewarded for the bet.
JIT manufacturing gains are far under 10%. It’s mostly advantageous from a capital flow point of view. At this point, considering the overall brittleness introduced, it’s not obvious to me there ever was gained at all if you consider both the up and the down.
It’s pretty obvious that at this point the purely free market approach is as successful for manufacturing as it was for banking. How can we even talk about free markets when the government just saves everyone each time a large crisis happens?
People had to pay more for cars? The cost of airline tickets went up? Lumbar prices went up?
I mean, don’t see many consequences for that brittleness. Inconvenience sure.
And I mean, if you think it’s the wrong move then there is an opportunity for you to get very rich - either start a company selling for higher prices to account for slack or heavily invest in ones that do.
Interestingly, food production is heavely planned through regulation, subsidies and incentives in most countries precisely because the free market cannot be trusted with such a sensitive matter. Famines cause riots and that's bad for buisness.
Most companies seem to not know that nuance.
Toyota's tier-two suppliers surely know it pretty well. Their suppliers a little less well. And so on, down through the supply chain.
It isn't the case that Toyota has some magical vision (though they are clear-thinkers). The key difference is that Toyota is at the end of the supply chain for all their suppliers.
Think of pulling an elastic tether on a solid object, which pulls an elastic tether on a solid object, which pulls an elastic tether on a solid object. Friction accumulates and it doesn't disperse evenly.
So the Toyota model is great iff you are Toyota or similar OEM. With diminishing returns as you progress further down the supply chain.
Ah, yes, this tired old "we should incur broad and hard to quantify bad things to avoid some small but easy to quantify bad thing" that is ever popular among people who should be smart enough to know better.
I agree that the system does seem somewhat under dampened but without a serious attempt at forecasting what the actual cost of damping it is I see no reason to change the status quo.