There are two distinct and crucial components of disaster preparedness. The one that understandably gets the most attention is the capacity to mount a rapid and effective response.
In a chaotic collapse speed is more important, it is a short time high energy situation where preventing more collapses and tipping points is more important.
The second component comprises investments that minimize the expected damage to the economy.
This is a V-Bi aspect, by making infrastructure more resilient and elastic they are less likely to crack and reach tipping points chaotically. Insurance often does this.
The cost of this power failure, though difficult to calculate, is surely huge. Unlike the economic boost that may occur from recovery spending to restore damaged physical assets, this is a deadweight loss. Local power outages may be unavoidable, but one can create grids that are less vulnerable – and less prone to bringing large parts of the economy to a halt – by building in redundancy.
Like a dead weight on something fragile, this can cause cracks and collapses. Every kind of economic structure has deadweight on it as well as an uplifting force or deadlift. A V-Bi approach is to randomize the system rather than having lines of Iv branches and B roots where if one part breaks the rest losing connectivity and starts to die off from a lack of resources. In the GFC there were deadweight losses in the sense of downward pressures on the Iv-B economy that caused it to collapse like the uplifting forces or deadlift of carry trade loans causes the bubble to inflate. Both are chaotic and prone to causing cracks in an economy.
For example a deadweight on a house in a hurricane might be a tree that causes it to collapse, a deadlift is where the wind gets under the roof and rips it off. In a boom a deadlift can be where Iv-B investors rushing in tear the roof or market price of houses away from their foundations causing them to raise, then collapse when the upward force is spent and there are no longer any foundations under it.
One argument is that redundancy looks like waste in normal times, with cost-benefit calculations ruling out higher investment. That seems clearly wrong: Numerous expert estimates indicate that built-in redundancy pays off unless one assigns unrealistically low probabilities to disruptive events.
That leads to a second and more plausible explanation, which is psychological and behavioral in character. We have a tendency to underestimate both the probabilities and consequences of what in the investment world are called “left-tailed events.”
Iv-B systems waste fewer resources by using leverage, for example the Iv branches and B roots of a tree use little wood for their size and what they do. However they are also easier to crack and collapse the thinner they get, a system constantly growing more and thinner branches will eventually collapse under the energy of a chaotic event like a storm. There is a fundamental uncertainty in predictions, chaos does not fit on a normal curve at all and is just the tails. On a normal curve then towards the center events are random and towards the tails more chaotic and so a normal curve cannot predict these chaotic tails as the mathematics changes.
