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Smart Health Care Cost sharing

Ezra Klein writes about smart cost sharing.

He wants a committee to decide reimbursement rates.

This made me think about an idea I got from Mark Thoma

Mark Thoma linked to the even more verbose version of this at my other blog. He has an interesting comment thread.

…preventative care … ought to be encouraged, and one way to help with this is … to forge an unbreakable lifetime relationship between the insurance company and the consumer so that expected lifetime costs are important to the insurance carrier.

I strongly suspect (with no evidence) that Thoma’s thoughts were influenced by
an empirical result that very small financial incentives to doctors based on their patients’ blood glucose caused big changes in those outcomes (pdf warning).
which will save huge amounts of money for medicare but small amounts of money for the HMO’s that introduced the incentives.

I think the best we can do is to charge medical costs not just to the current insurance plan but also, in part, to the one that covered the patients in the past (to give the an incentive to keep their clients healthy).

If insurance companies saw obese people with horrible eating habits who watch TV all day as a profit opportunity, the USA would be a healthier place.

Just think, sleazy insurance agent hangs around bars and then calls his boss to say “Right in front of my eyes, I have a guy who must way 300. He’s on his 4th whiskey, has emptied 2 bowls of bear nuts in the past five minutes and he’s chain smoking camels, we got to move fast before our competitors sign him”.

[line above updated for punctuation and to add details plus a homonym to celebrate the fact that Matthew Yglesias linked to this post (the homonym was honestly accidental. In fact, there were not one but to honest homonyms — I typed “too add details” two before correcting it, witch just goes to show how thrilled eye am.]

To try to explain better

My plan is the Edwards plan plus insurance companies pay for care of former clients based on alpha(cost of the treatment)*(years with that company)/(age at time of care) where alpha is well below one and for the care of current clients minus the part paid by former insurers. They get paid a constant which depends only on the region where they are located times the same alpha factors.

Thus they have an incentive to keep their clients healthy (which they can pass on to doctors).

Plus they get paid based on progress on preventive measures (patients who quit smoking, got blood pressure from x down to y, lost weight from obese to not obese etch)funded with a tax on insurance companies per patient so on average they get zero.

This means they would be more willing to sign fat lazy smokers as there is lots of room for improvement compared to things as they are.

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Auto Prices and the CPI

Earlier today in discussing auto prices I’m afraid I did not explain myself very well.
Let me use actual data and see if I can do better.

Because the CPI is quality adjusted what it is showing is the price of buying an earlier model car, if you could. In the chart above I set the base at 1975 so the CPI is saying that from 1974 to 2007 the price of buying a 1974 car rose from 100 in 1974 to 216.2 in 2007, or 116%.

Over this time the average transaction price for a new car rose from $4,859 in 1975 to $23,336.
This is a 371% increase — the index rose from 100 to 471. I could not quickly find the data to update the suggested retail price data.


The difference between a 116% price increase and the 371% increase is what you actually have to spend to buy a new car. By using the CPI data Carpe Diem was implying that the average consumer was getting a real raise because the CPI data shows that auto and light truck quality adjusted prices fell in the 1990s. To a certain extent this is true. But in other ways it is not true
because the consumer is unable to buy an earlier model car. What the consumer has to buy is the car that is offered in the market place today and the actual price the consumer faces is the average transaction price. Part of the differences is what the consumer has to buy in the market place that is not counted in the CPI as a quality improvement. For example the standard radio in an auto use to be a simple AM radio. Now it is a AM-FM radio. Another example is that today’s autos are much more durable. A quarter century ago about the only car on the market that was still in very good shape after 100,000 miles was a Volvo. But it was an expensive car.
Now, essentially every car can reasonably be expected to still be a good car after 100,000 miles.
But this change is quality is not incorporated into the CPI quality adjustment.

The Carpe Diem argument that because the CPI for new cars had fallen over the past decade the consumer has gotten a real raise is only partially true because the consumer can not go into the market place and buy the earlier model car. What consumers have to actually spend is the average transaction price whether they want to or not. So going back to the data on the chart above, the average sum the average consumer spent on a new car rose 371%, but out of this increase some 116% represented quality improvements, so the real price increase was 155%.

I’m still afraid I made the correct point here, but maybe the discussion can clear it up.

P.S. In rethinking this the difference between the 116% in the CPI for autos and 371% increase in the average transaction price is how much of a quality improvement in cars the BLS estimates happened. The BLS says the average 2007 car is 255% better in quality than the 1975 car.

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All Economic Analysis is Counterfactual

In partial response to Cactus’s post, Megan McArdle offers the “look at those low air fares” defense of airline deregulation, going so far as to suggest:

I think it’s telling that complaints about deregulation of the airlines come almost entirely from three groups of people:

1) People who have no idea what they are talking about
2) Affluent people
3) People who fly a lot for work

The story being that (2) and (3) aren’t price-sensitive and other critics of deregulation are just know-nothings or whiners (or both).

Not so fast.

The conceptually correct comparison is not with 1978 airfares, but rather with whatever current airfares would be under a reasonable forecast of airfares absent deregulation but with whatever other changes would have happened anyway. Recall, Robert William Fogel was given his share of the Bank of Sweden prize in significant part for cementing this “counterfactual” (or ceteris paribus) analysis as the standard methodology of economic history.

This is a non-trivial matter for airfares as deregulation was implemented during an oil price spike, and its subsequent golden age to roughly 9/11/01 was a period marked by a very long decline in the real price of oil — not to mention cost-reducing technological change from sources such as cockpit automation and the deployment of high-bypass-ratio turbofans to the single-aisle airliners that are the workhorses of the U.S. domestic fleet. So not all of the secular airfare decline (or what’s left of it) is properly attributed to deregulation.

One source [PDF] suggests that deregulation accounted for around 60% of the observed fare-level decline to 1993 using the old CAB pricing formula as the benchmark, and that 30% of flyers paid higher fares under deregulation. Don’t get me wrong, this isn’t bad, and the liberal in me can’t help but say that taking money from airline investors and corporate travel budgets and turning it into air transportation for the middle- to upper-middle classes beats many other deregulatory outcomes (at until the system blows up). Still, it isn’t Pareto-improving, and by the standards of, say, repeal of the upper-income Bush tax cuts, the disaffected class is pretty big, though. We aren’t just talking about the “affluent” and ultra-frequent flyers.

Moreover, would-be Fogels looking for an icon-smashing result that may also be true could try to figure out whether modern systems of rate regulation would perform better than the late CAB. So once we consider what Barry Ritholtz amusingly calls “dedonics” (*) issues like service levels and qualities, the need to keep the industry somewhat stable until alternative modes of fast intercity travel are (re)developed, and so on, I submit that the true benefits of deregulation are at least a matter for careful study.

(*) It’s amusing even though it isn’t true that all quality adjustments in CPI are for quality improvements.

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All in the phrasing

The phrasing of these projections read just like Social Security crisis projections. I hope some of our friends see the irony of such claims about Social Security if they dislike these statements.

The CBO has released a report detailing the effects of indexing the the AMT to inflation (i.e. “patching” it so that fewer households would pay it than otherwise anticipated) and extending the 2001-2003 Bush tax cuts without offsetting the revenue loss.

If the Bush tax cuts are allowed to expire and if the AMT continues its ever-deepening reach into the middle class, the federal debt held by the public will increase from today’s 37 percent of GDP to 115 percent in 2050. If AMT is indexed for inflation to limit its impact on the middle class, that debt figure becomes 115 percent in 2050. If the AMT is indexed for inflation and the Bush tax cuts are extended, federal debt held by the public jumps to 190 percent in 2050.
(Source: Congressional Budget Office)

Deficit financing of these tax cuts has a pernicious effect, reducing per capita income by 13 percent in 2050. But, “[b]eyond 2073, projected deficits under those tax policies would become so large and unsustainable that CBO’s model cannot calculate their effects.”

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What economics would you teach kids?

by jsalvati

What economics would you teach kids?

Rdan points to a ‘National Budget Simulation’ program that is apparently part of Massachusetts economics education for grades 4-12. I was surprised when I clicked on the link because the federal budget seems like a really strange place to start economics education.

It seems important to start economics education with the economics concepts that kids can actually use in their lives. If I had control over what economics some kids learned in school, I think this would be my list:

Opportunity cost
Gains from trade
Incentives
Importance of trade offs
Emphasis on the idea that everything has value (time, money, lack of garbage, etc.)
At a more advanced level

Marginal thinking
Efficiency of markets
Interest rates, Net Present Value
Consumption smoothing
I also think it would be useful to teach Utility and Expected Utility, but I don’t think it is possible to get to those topics.

Arnold Kling had post on a similar topic a while back.

As a side note, I think I would like to replace most of pre-calculus with basic probability theory from a Bayesian perspective with some heuristics and biases thrown in. Probability theory is a useful abrstraction for all sorts of problems, and it would also make that optional statistics class a lot less difficult if you could teach it from a bayesian perspective.

I was a little surprised myself to see the link, and pleased. I was planning to write a post on kids and must have left the link on ‘scheduled’ and jsalvati delightfully picked it up. He and a friend are undergraduates who started Good Morning Economics.

As jsalvati noted, Arnold Kling at EconLog wrote that after eliminating things from the high school curriculum:

With all that said, here is what I wish every high school student would learn about economics:

–the concept of opportunity cost
–how economic incentives affect behavior
–the gains from trade
–how prices allocate resources
–how entrepreneurs introduce innovation

If every citizen understood those things, the level of debate over economic policy could be much higher.

The link is to a section of Thinkfinity MA series sponsored by Verizon. I will be a part of of a state based team that provides an opportunity to develop curriculum materials for kids elementary to high school.

I am on a “validation of resources team” scheduled for this Aug. 7 to find out what is expected and to meet both state educators (curriculum and technology sectors) and those doing the validating.

As I gather information I will update and link to other sites that are interesting.

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Did You Get a Huge Increase in Your Real Wage?

Mark Perry presents some interesting data:

Then considering that average hourly earnings have increased by almolst [sic] 40% over the last ten years, the real prices of those products have fallen by an even greater amount, a HUGE amount. In other words, there are many, many products like computers, cameras, new cars, clothing, TVs, appliances, electronics, software, etc. that are significantly cheaper today than ten years ago, especially after adjusting for increases in earnings.

The increase in nominal earnings over the past decade was 38.6% while the reported increase in the CPI was 33.5% so by this data, real earnings have increased by only 3.8% over the past decade. This is not a HUGE increase. Unless you don’t eat consume a lot of electronic products and have figured out how to drive that new car without buying gasoline.

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Brad DeLong asks about the top ten econ blogs by net news wire

Brad DeLong asks:

Here’s what NetNewsWire throws up as tops in attention in the “economics” category:

Mark Thoma’s Economist’s View http://economistsview.typepad.com/economistsview/

Alex Tabarrok and Tyler Cowen’s Marginal Revolution http://www.marginalrevolution.com/marginalrevolution/

Justin Fox’s Curious Capitalist http://time-blog.com/curious_capitalist/

Barry Ritholtz’s The Big Picture http://bigpicture.typepad.com/comments/

James Hamilton’s and Menzie Chinn’s Econbrowser http://www.econbrowser.com/

Angry Bear http://angrybear.blogspot.com/

WSJ Real Time Economics http://blogs.wsj.com/economics/

Paul Krugman http://krugman.blogs.nytimes.com/

Felix Salmon’s Market Movers http://www.portfolio.com/views/blogs/market-movers/

Paul Kedrosky’s Infectious Greed http://paul.kedrosky.com/

How should we use judgment to alter this list as spit out automatically by NetNewsWire? What’s missing? What’s erroneously included? What’s out of place

Update: Seeking Alpha also makes a resource list of blogs with descriptions. Any changes to this description? We need a concise one.

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Unobserved Country Heterogeneity: GDP Levels or Growth Rates

Have you ever noticed that, when considering the economic performance of different countries, people often just report the GDP growth rate without any corrections for e.g. initial GDP ? It’s as if they thought that countries generally have about the same growth rate and any deviation from the world average is interesting.

This is very odd as most growth models imply that growth rates should be very different for different countries so such a simple measure is not a reasonable assessment of performance.

It’s as if people think that there is a lot of heterogeneity in GDP levels but not so much in GDP growth rates. Marco Alfò, Giovanni Trovato and I, decided to ask a computer if that’s what it saw in the Heston and Summers data set. The computer (on Gianni’s desk top) said “absolutely”. The paper is here (subscription required for download. If you are using a work IP address or mirror you can hope to get it without paying (please try if you are interested)).

update: Greg in comments has kindly translated the post into English. I pull his comment up here.

[snip]

Perhaps an English summary:
a) Standard Economic Theory, the shibboleth we will be destroying today, says that GDP levels will converge, that is, poor countries will get richer, and rich countries will get richer … slower than the poor countries. (Apocalyptic Econ allows for us all converging at some substantially lower level, of course). This will result in all countries being smarter than average.

b) We’ve run some Fancy Number Analysis that shows this is not true. The Usual Analysis says this because two things confuse the numbers: i) within groups of similarly poor (rich) countries, there is some convergence, and ii) this within-group convergence tends to look like overall convergence.

c) This is Real Important because lots of analysis doesn’t correct for this, and hence draws conclusions that are, um, stupid.

d) Using a short-form analysis (asking your neighbour) may have been more accurate by being less clever (“it’s a fine line between clever and stupid”).

Of course, one might best avoid using Shibboleth in the simplified version.

Grateful comments/clarification if I’ve gotten anything fundamentally wrong.
Greg | 07.24.08 – 5:15 pm |

Thank you Greg.

All of my F-fort to right plane English is now below the jump (jump at your own risk).

The idea is to take a minimal model for GDP levels or Growth (basically the Mankiw Romer and Weil equation for levels applied to growth too by Bernanke (yes that Bernanke) and Gürkaynak and to allow the computer to look for remaining heterogeneity in levels and/or growth rates with minimal parametric restrictions. We used a semi parametric finite mixture random effects model in which the distribution of the unobserved disturbance to the growth and/or level of per capita GDP is drawn from a finite number of points. As the number of such points goes to the number of countries in the sample, all heterogeneity can be explained, so the approach is, in some sense stressed by Heckman, non-parametric. Like everyone we used information criteria (including Akaike they all agreed) to choose the number of points (results are not too sensitive to the number).

The result is that the computer decides that there is huge unobserved heterogeneity in levels and virtually no heterogeneity in growth rates (the unobserved points in level growth rate space have extremely different levels and the similar growth rates). There is no hint of convergence in GDP per capita levels of the different groups of countries which are, therefore, convergence clubs.

So why has every variable and it’s cousin (except for tax rates) proven to be significant in at least one cross country growth regression ? The initial GDP per capita level is always included in these regressions. It has a negative coefficient because of convergence within convergence clubs. Thus the silly computer is convinced that countries in different convergence clubs should converge (that is the one in the poorer club should have higher growth). The other variables help to explain growth by undoing this error. Regressions of just the growth rate on variables *not* including initial per capita GDP are much less likely to be significant.

The bottom line is that a computer with no hints as to the conventional wisdom very firmly told us that there is a huge amount of heterogeniety in per capital GDP levels and very little heterogeneity in growth rates of per capita GDP, just as everyone who doesn’t run regressions tends to assume.

Now the whole experience reminds me of something Zvi Griliches said long long ago (in a presidential address to the AEA I think). To understand economies better we need more information as in data not new and fancy analysis of the same old data. This was a very popular line in the Harvard ec department back when I was there. In particular, he said there was not point in the zillions analysis of the Heston and Summers data set no matter how econometrically rigorous and original. Back at the time I nodded my head and wispered the un-religious analogue of “amen”. Irony of ironies I find my most recent publication to be … the ten zillionth analysis of the Heston and Summers data set and I honestly think it adds something new. I maintain my almost perfect 0% record as a prognosticator.

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