http://engineering.curiouscatblog.net/2008/07/13/500-year-floods/
The reason is that most human settlements occur in flood plains because we cannot live without water. We drink it. We bath in it. We irrigate crops with it. Flood plains have fertile soil. We use rivers and oceans for essential cargo transit.
Insurance is about risk management. It is a form of betting. And there is no bet here because there is no question of if it will flood. The question is only when will it flood?
That's a fool's bet to say "I will pay you X amount of money if it floods" when it is guaranteed to flood sooner or later. That amounts to charity, not insurance.
Insurance companies don't mind insuring risks that they know will happen at some point, e.g. most property policies will have some claims, and life term contracts (as have been stated below) of course will have a claim at some point (unless the policy is lapsed). However, they have an idea of how often and how costly these claims will be, and through risk pooling diversification, this is lower (per policy) than the cost to the individual. Thus there is an incentive to buy the policy, and an incentive to sell it - as the difference can be made as profit to the insurer.
In addition there's a timing element to insurance: insurers take in premiums "now" for claims that will be paid out "later", so they can invest the money in the meantime. Large insurance companies may have $200bn investment portfolios.
EDIT: So the point is that flood insurance can of course be sold by private companies, however they know the risk is too high and won't offer competitive premiums. If we only had private flood insurance in the US, in the long term this would lead to people having to move to places with cheaper flood insurance. In this way it actively promotes people moving away from risky places (which I think is a good thing) - but it makes it difficult for people in the short term.
It gets handled this way for the same reason our government provides welfare et al: it makes no sense as a business, but the cost to the nation to do nothing is a bigger problem.
I think the bigger issue is that there is an inherent incompatibility between free markets (or strict laissez faire, non-intervention of any kind) and democracy. Of course people, in the millions, are going to say "help us" and direct it at their various layers of government, and punish those who don't at the election booth.
Therefore it stands to reason in major floods like this, that everyone is going to get some kind of relief even if they didn't have flood insurance. What I'm not sure of is whether the insured get 100% payouts and those not insured get partial payouts? What's the incentive to have flood insurance, except in smaller, localized, 50 or 100 year floods?
This is asset destruction and the only way to properly handle it is through savings. So it's either made compulsory or you do end up with something of a free loader problem. Whether that free loader problem is a real problem, I don't know.
The industry also feels B makes selling flood insurance a bad idea. That said, there are Private policies you can buy in some areas.
PS: Insurance companies like frequent small scale random events like car accidents, because they are easy to plan for.
i don't quite see that.
if the flood insurer covered a broad variety of geographically dispersed areas across North America, or even just the US, would that be true?
https://en.m.wikipedia.org/wiki/Great_Flood_of_1993
Edit: fix an extraneous wording mistake.
https://www.cnbc.com/2017/05/02/apples-cash-hoard-swells-to-...
A statement with profound implications in other areas of insurance, notably health insurance. You're insuring against expensive losses that will almost certainly happen at some point... which suggests that traditional insurance isn't the right framework for solving the problem at hand.
Just like the government provides fire protection in the form of fire departments, the government needs to provide health care. What we are doing currently is broken.
you've just outlined a money-losing system run by the government.
the reason private health insurance systems fail is not merely because everyone needs it at some point. it's because everyone uses much more of it than they've paid for with their premiums. (which is why, pre-Obamacare, insurance companies used to reject applicants with pre-existing conditions and why they put lifetime caps on benefits paid.)
but a government run single-payer system is not magic. the extra cash must come from somewhere.
one way a single-payer system could obtain the additional funds needed is by taking cash from some other government source (which is exactly what Obamacare does when it provides refundable tax credits to help low income people pay their otherwise unaffordable health insurance premiums.) but there's no end to the amount of money that could require.
another thing the government can do is limit services to patients, i.e. take a certain amount of decision making authority, by law, away from individuals, especially old individuals who are very sick. ("i'm sorry, but we're not paying for that new chemotherapy. it's hospice care for you.")
in addition, a single-payer system can also uniformly limit the prices health care providers, pharma companies, hospitals, etc can charge. (i.e take some decision making authority away from that sector of the economy, again, by law.)
First, how it is paid. It's text book socialism. People pay into it based on ability and receive benefits based on need. It doesn't run at a loss.
Second, the level of care. Basically the government puts a lower bound on health care and uses taxation to do it. You're guaranteed a basic level of care regardless of your situation. You can opt for private insurance that stacks on top of that. A basic level of treatment is covered by the government, but anything experimental or exorbitant you will likely have to pay yourself, unless you have the aforementioned gold-plated insurance. Insurance is much cheaper because it only needs to cover unusual care, but of course I do pay a lot of taxes.
It's not different from a private system, because you can't receive unlimited care, but unlike a private system you're always guaranteed a minimum care.
In the case of these massive flooding, it's hard to make the pool big enough. That's why reinsurance companies exist, which can mix the risk pool of different types and locals.
Origin story for Lloyd's of London:
The patrons bet, for example, on whether Admiral John Byng would be shot for his incompetence in a naval battle with the French. He was.
The gentlemen of Lloyd's would have had no qualms about taking my bet on my own life.
Edward Lloyd realised his customers were as thirsty for information to fuel their bets as they were for coffee, and began to assemble a network of informants and a newsletter full of information about foreign ports, tides, and the comings and goings of ships.
His newsletter became known as Lloyd's List.
Lloyd's coffee house hosted ship auctions, and gatherings of sea captains who would share stories.
If someone wished to insure a ship, that could be done too: a contract would be drawn up, and the insurer would sign his name underneath - hence the term "underwriter". It became hard to say quite where coffee-house gambling ended and formal insurance began.
Usually, both. Plus, if you had high expenses they'd actively search for an (even unrelated) pre-existing condition as a pretext to cancel your coverage (recission).
That is called single payer, government provided coverage. I would support that.
That is not remotely what Obamacare does. Obamacare requires private insurance to cover people with pre-existing conditions and it requires everyone to buy private insurance. It is busted as all fuck and I would like to see it go die in a fire.
I am aware what we were doing before Obamacare sucks and we need a real solution and to not simply go back to that. But this is not a real solution.
> Obamacare requires private insurance to cover people with pre-existing conditions and it requires everyone to buy private insurance.
So does single payer, we just call "buying" taxes and we replace insurers with government. You're still forced to pay and the insurer is still forced to provide for everyone regardless of pre-existing conditions. So it would seem you're simply against the name Obamacare.
> But this is not a real solution.
It's not supposed to be, everyone isn't blind, they see that single payer is the solution, but you can't simply declare the private insurance industry we already have dead in one fell swoop. Obamacare or something just like Obamacare is a necessary step to get to single payer. We need to get everyone into a public option, and then have that option slowly kill off private insurance by simply operating cheaper than they can until the public option is pretty much what is insuring everyone, at that point, it's effectively single payer.
Just charge more money for your insurance. Boom! Profitable business.
The bet is more like, "I will pay you X amount of money if your damages from flooding exceed your deductible within the next year." It's not at all given that it will flood at all this year, or that your losses will exceed the deductible.
It's true that it would require substantial diversification or re-insurance, since flooding is a clustering event.
So it’s about determining the expected value of losses for a given risk. You’re right that given a long enough time, there is a near-certain chance of a flood, but the question is more about how much that’s likely to cost.
That is entirely insurance.
If the answer to that is that only people in areas vulnerable to flooding would buy insurance, and the companies would have to pay out too much - well, that means the insurance buyers are pricing the risks better, and the insurance company should hire some of them.
https://i.imgur.com/HLxUBim.png
edit: not sure why I'm being downvoted. I can only assume the downvotes are political in nature, which is a shame.
It's a positive feedback process.
What is interesting is that one of the motivations (funding wise) for understanding fat tailed distribution, extreme value distributions were indeed flooding and dyke failure events.
https://en.wikipedia.org/wiki/Extreme_value_theory#Univariat...
It seems it could go either way to me, and the way to get a good indication of which is most likely is to look at look at much smaller timeframe models and assess if they are changing over time, and how much. It's entirely possible it's both, but it seems we have a good way of gauging the relative importance of changing climate norms so we should at look at that before discounting it as noise in the bigger problem of poor models in general.
Sounds like a use for Baye's Theorem.
That is, if the probability for each city flooding is 0.002 but the different cities are positively correlated, then the probability of at least one city flooding is lower than it would be if they were uncorrelated. (Because the probability of no cities flooding is higher, because of positive correlation.)
It's a scam involving the ratings much like the mooody's ratings scam of the last decade IMNSHO
For instance, chances of 500-year floods in two Texas cities is not 1 out of 500*500 in a year. If they're geographically similar and physically close, it should be closer to 1 out of 500.
That means dozens of cities and towns with 7% of the US population.
I suspect that's it. Of course I may be falling into the same birthday paradox here, but a similar thing happened when it flooded where I lived now. The x in "x-year Flood" kept increasing (I'm inclinced to blame that on sensationalizing news for ratings), but people kept comparing it to the 3 or 4 similar floods that happened in the last hundred years. It would seem the probably has gone up due to climate change, or that we're noticing the floods more now because there's more damage to be caused to more things that have been built up, and we have better records and better news transmission, but it certainly seems that can objectively say they're no longer 1-in-500 year flood regardless of the reason.
That probably has a small reason to do with the increase, but your next line highlights the issue.
> or that we're noticing the floods more now because there's more damage to be caused to more things that have been built up
No, not exactly. The more stuff you build, the faster water runs off. Unincorporated land has a pretty high water slowing capability. It takes more time for water to run through tall grass, and puddles, and log jams, and loose dirt. All things that occur naturally. Humans build houses that have all the water run into gutters, that run into a well cut lawn and down a sidewalk. Once it hits the road it's like a water expressway. It can travel quickly to a local stream. A stream that likely has a concrete lining so the water moves swiftly to a lake or reservoir in hours rather than days.
As a place develops new flood plans must be studied every 5 to 10 years. A new development of 100 hours up the watershed from you can mean your risk of flooding increases dramatically. Places like Houston have had 10,000's of houses build in the surrounding areas meaning what was a 1 in 100 year flood could be as low as a 1 in 10 year flood. All this stuff being built is not taking into account its effect on downstream rainfall runoff.
But faster run-off sounds like a good thing to prevent the flood - are you saying that more development upstream means more flooding downstream because all the run-off arrives with much lower latency and higher bandwidth, to use IT terms?
Also people tend to drain marshes and any other shallow stagnant waterways to avoid mosquitoes having breeding places. It can save us from terrible diseases, but it can make flooding worse.
When Rainfall * Area >= SoilAbsorption(See note) + WetlandAbsorption + ArtificialDrainage the end result is flooding.
Essentially the left hand side of the inequality has been slightly increasing because of climate change, but we're chipping away constantly at the right side of the equation in three ways.
(1) More and more soils in American metro areas have been covered by impervious surfaces for development. (2) More wetlands are being destroyed for development. (3) Artificial drainage is being under-built. Drainage is generally built for 1 in 100 year events but the rate of urbanization is increasing the magnitude of flooding. (Drainage is only a problem for the developer that hasn't sold what they're building.)
Note: Soil has a finite capacity for water infiltration.
The tables on the wiki pages shows "curve numbers" for different types of soils. These numbers are based on experimental data which is then used to model runoff. (Or used to be. Its been 20 years since I've done runoff modeling, so maybe things have changed)
Mother nature does not respect grandfather clauses.
see also https://qz.com/1063985/hurricane-harvey-why-85-of-homeowners...
There's gonna be lots of screaming when homeowners in Houston realize how much flood insurance is going to cost them in the future. We all got a preview of this in coastal Florida.
As you appear to be in or near Houston, I hope things are OK with you and your family.
all well here, many people I know or are aware of are affected, thanks.
It's kind of analogous to hitting a golf ball into an open field and then exclaiming "Of all the blades of grass, the ball landed on this one!" It's only interesting if it goes in the hole with the flag, otherwise you have a sort of selection bias going.
But for this case, it would still be very unlikely. For any arbitrary 3-year span, the probability of consecutively getting a "1 in 500 year" flood for 3 years is (1/500)^3. If we have N cities, then the probability of none of these cities having 3 consecutive floods is (1-(1/500)^3)^N. For even a vast overestimate such as N=20000, it is still a significantly improbable event. Of course, this doesn't account for "3 consecutive years or more within some year range" and it is a gross simplification, but I think there are probably better explanations than selection bias, such as the inaccuracy of the model or the fact that these events might be temporally dependent on each other.
p = 1/500 years = 0.002
For 100 cities, the probability of at least one city having a 500-year flood is 18.14%.
For a 3-year run:
p = (1/500)^3 = 8e-9
For 100 cities, the probability is 8e-7 of at least one success. For 1000 cities, the probability is still only 8e-6.
Wolfram alpha helps in calculating PDFs and CDFs: http://www.wolframalpha.com/input/?i=binomial+distribution+n...
1) Suppose I flip a coin 3 times and repeat that experiment on 10 different occasions. What's the probability that I get all heads at least once?
2) Suppose I flip a coin 30 times (same total number of flips). What's the probability that I get at least 1 string of at least 3 heads?
(1) is more like the binomial calculation you've set up, but I think (2) is closer to the question we want to be asking.
This is important because, as it turns out, (2) is much more likely than (1). You can tell intuitively that there are more sequences of coin flips that would satisfy (2). For example "THH HTT ..." would satisfy (2) but not (1).
So how should we pose the hurricane question? I propose: What's the probability that in a 100 year period, across 100 cities, there will be at least 1 city that experiences a 500-year flood for at least 3 contiguous years?
Solving this analytically is non-trivial, but it's easy to simulate:
// Scala
val rand = scala.util.Random
def coinFlip(p: Double): Boolean = rand.nextDouble <= p
// Simulates 100 years and returns true if there's a contiguous string
// of three events with p=1/500.
val targetEvent = Seq(true,true,true)
def threeIn100Years = Seq
.fill(100)(coinFlip(1.0/500))
.containsSlice(targetEvent)
// Simulate this 100,000,000 times
val simulations = 100000000
val count = Stream
.fill(simulations)(threeIn100Years)
.foldLeft(0){case (acc, cur) => if(cur){acc + 1} else {acc}}
// Estimated probability for a single city.
val p = count/simulations.toDouble
// The probability it will happen *at least* once in a population of
// 100 cities.
// This calculates the probability if *won't* happen 100 times, and
// then takes the complement, giving us the final probability
1 - Math.pow(1 - p, 100)
I'm not sure how to succinctly phrase this idea. Maybe "non-constant probabilities"?
If you put 400 people in a room, the odds that no two of them share a birthday have gone all the way down to zero percent.
No matter how many independent cities you measure flooding in, you can never achieve a perfect 0 or 1 probability of (whatever), because the cities are independent.
We don't define "interesting" flooding in one city by reference to what happened in another city, so this situation is not described by the birthday paradox.
Not quite the same because Huston is not the only city that has experienced extreme climate these two years, many other cities also have (maybe not 500 years flood, but close).
So that would be like: one pair is born the same day, and 20 other people in the room are born a week around that day. Hardly a coincidence.
It's more likely that there was a party about 9 months and X years before that day. (I'm not sure how far we can go with this silly birthday analogy:)
Interesting note, this is Houstons third 500-year flood in three years [1].
[1] -https://www.washingtonpost.com/news/wonk/wp/2017/08/29/houst...
This is the key point here, and it's called the fallacy of multiple endpoints. If there are 500 observable cities, then somewhere among them should occur a "500-year event" every year. It's just that nobody ever notices the big bulk of the population that hasn't yet had any 500-year event in its recorded history.
If it's 1 - which is what I think is meant when saying "a 1 in XXX years flood" - then your comparison doesn't hold, because the number of floods isn't dependent on the number of cities, but on the distribution of cities on the land, and specifically in flood-prone areas.
In the flood case, a flood in California and one in Miami don't really increase the chance of another flood simply because they have happened.
Or rather, the odds of that kind of flood increase a bit each year.
It's a very complicated question to determine what a 1/500 odds of flooding are.
So, it's very possible that this isn't the gambler's fallacy, but rather the model itself is inaccurate.
This can mean two things: a) a set of events that is evidently possible, but increasingly improbable b) events that are not independent
It's related to the fact that the probability of two people in a room having a birthday is more closely related to the number of pairs of people in the room (which in turn grows as O(n^2)), than to the number of people in the room.
A detailed proof/explanation can be looked up easily with Google, if you have a bit of mathematical maturity.
[0] https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_01_tables.p...
The Birthday Paradox has absolutely nothing to do with procreation, and everything to do with statistical probability.
It's specifically about coincidences in a randomly distributed set.
It just says "birthday" in the common name because that's a relatable, if imperfect, example.
The simple calculation is P=1-(1-1/500^3)^N and the probability is less than 1:10000 assuming independence and even given 6000 cities of a million people (the entire world population is in a similar city).
If it was birthday like (every possible 500 year storm for 3 years is in a room choosing out of 100 random million person cities), the probablility would be reasonable. You can use a Poisson distribution to estimate the 3 person birthday problem. P=1-exp(-3choose100/500^2)=48%
Assuming 1 in 500 year floods are independent, note the ~300 cities in the US [0]. The fact that Huston is a big city doesn't seem relevant to me, because the storm doesn't care. Much like picking a specific number plate, it had to land somewhere.
The chance of there being a city in the US which has a 1 in 500 year flood is therefore 60% (300/500) each year.
The chance of that city having another flood of similar magnitude in Year 2 is 1/500, because the odds are independent and we started monitoring the city in Year 1. The chance of it flooding again the third year brings the odds down to 1/(500 * 500) = 1 in 250,000.
[0] https://en.wikipedia.org/wiki/List_of_United_States_cities_b...
Of course, the "once in 500 years flood" may also be an inaccurate probability as well, but if its not, then I'm not surprised this is happening SOMEWHERE.