[QUOTE=CaveMike]
I followed your post up to this point. Pricing insurance too high will drive away low-risk customers; customers that would otherwise subsidize high-risk customers. This in turn will raise prices. Presumably in a stable market, insurance companies would find the sweet spot that maximized profit by balancing cost vs. number of customers. This is the complicated science every company has to do in order to set their price. However, it makes sense in the current market where healthcare costs are increasing rapidly. As costs soar, low-risk customers are more likely to leave.
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You’re assuming that insurance companies can set prices just like other markets do. But they can’t, because of informational asymmetry. When one party knows something critical that the other doesn’t, it’s difficult or impossible to find a price that results in gained value for both sides.
For example, let’s take used cars (and this was a great example from a highly recommended book called “The Undercover Economist”). The used car market is somewhat broken because of informational asymmetry. It works like this:
Let’s say you’re looking for a used Ford Taurus. A Taurus in average condition of the age you are looking for might be worth $5000. A crappy one might be worth $2500. An excellent one might be worth $7500. So, you see a Taurus advertised in the paper for $7500. Are you going to buy it? Nope. You don’t know if it’s excellent or a piece of crap. So you assume it’s of average quality, and you offer $5000 for it.
Now let’s say you’re the buyer, and you know your car is excellent. So you put it up for sale for $7500. That’s what the car is worth to you. But no one will pay that, because they are going to price in the cost of risk that it’s a lemon. So no one will offer you more than $5,000. Since the car is worth more than that to you, you take it off the market.
So eventually, the excellent cars leave the market. Now all thats left are average cars and lemons. But now if you’ve got a 50/50 chance of getting a lemon or an average car, the most you are willing to pay is $3750. But the average cars are worth $5,000 to their owners, and soon THEY leave the market. Eventually, you wind up with a used car market filled with overpriced lemons. Excellent cars cannot find buyers. The market is broken.
Of course, there are ways to minimize this problem. Mechanical inspections, paperwork retention, used-car warranties, etc. A big one is reputation. Excellent cars often wind up being traded in for new vehicles. Of course, so do lemons. But now there’s an expert in the mix who can evaluate the vehicles. A trade-in that turns out to be mechanically excellent will be sold on the dealer’s lot, perhaps with a used-car warranty. If the dealer has been around for a long time, and has a lot of money invested in buildings and high-quality fixtures, he has a reputation to maintain, so you can count on the cars he sells not being lemons.
When a reputable dealer takes in a lemon, he’ll sell it for auction, and it will be picked up by curbers or “Ca$h for Car$” fly-by-night dealers, who don’t care about reputation and compete only on price. That’s why these kinds of lots almost never have decent cars - they’re pre-selected to have nothing but lemons.
Anyway, this was a long digression, but it gets the point across that you can’t always find a ‘fair’ price when there is a fundamental asymmetry of information. And this is a big problem in insurance markets. Let’s take your example of finding a 'price that lets you keep the optimal number of customers, just like conventional pricing theory would suggest you do. Will that work?
Well, let’s say that I’m trying to find a fair price for four randomly selected people. I know that health expenditures average, say, $5,000 per person per year for the age group I’m looking at, but I don’t know anything else about them.
Here’s the hidden information I can’t see:
Of the five people, one is in excellent health, with an excellent genetic backgound. Such people typically only cost $2,000 per year at this age group.
Another is in reasonable health, and doesn’t smoke. Cost: $4,000/yr.
A third is a reasonably healthy smoker. This person would cost $6,000/yr.
The fourth is a person with a hidden family history of diabetes, hypertension, and heart attacks. This person has regular shortness of breath, and chronic health issues. Cost: $8,000/yr.
Okay, so where do I set my price for health insurance? If I set it at $5,000, I lose the first two customers, and the people who are willing to accept the price will cost me on average $7,000/yr. So I raise the price to $7,000, and now the $6,000 person drops out, and I’m still short.
Assuming one side has perfect information and the other side has none, there is no price I can find that will result in my being able to make a profit.
Contrast that to a regular transaction where information is known by both sides, but values differ. If I can evaluate something and rationally determine that it is worth $5,000 to me, and you can evaluate the same thing and determine that it’s only worth $4,000 to you, we can settle on a price, say $4500, that gains us both $500 in value. That’s the way most market transactions work.
Without randomness, there IS no insurance industry. If all risks are perfectly knowable, there would be no need to buy insurance. In fact, the market breaks down again. The whole point to insurance is that neither side knows what the individual risks are. The insurance company buys your risk because it has a pool of customers to average the risk out and ensure a profit. You’re willing to pay a premium over what your risk really is because you can’t take the chance of being wiped out by chance.
If the risk and randomness is eliminated, no insurer is going to insure you if you are a candidate for extreme costs. If they’re willing to insure you, that tells you that you probably don’t need their insurance for the price they are offering.
The most efficient insurance market would be one where neither side knows anything specific about the other, but where overall risks can be determined statistically from the population.