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Diagnosing the cost disease

Last year William Baumol published a book entitled The Cost Disease in which he discussed his theory for why healthcare costs continue to rise as a proportion of GDP, while at the same time manufactured goods get cheaper. This idea wasn’t new; he’d first published it in 1967. However, even with 45 years for people to digest his idea, it has generally been overlooked. I shan’t go into much detail about the theory here as it is the subject of a previous post; nevertheless a short outline is probably warranted given its centrality to the rest of this post.

Baumol divides the economy into productive and stagnant sectors; the former includes industries with a high degree of capital input that see increases to labour productivity greater than average as a result of innovation (i.e. computers), while the latter has a less than average labour productivity growth rate since labour is the main input and there is a low degree of substitution between capital and labour (e.g. in healthcare). Wages increase in the productive sector in line with productivity growth. In the stagnant sector wages increase at the same rate to ‘keep up’ and not lose skilled workers, despite the smaller increases to productivity. As a result of productivity growth, overall the economy grows. The costs in the stagnant sector grow relative to the output, whereas costs in the productive sector don’t increase relative to output. Hence, the economy is bigger but the stagnant sector takes up a larger part of it.

The question arises, then, as to how we might test for the presence of the cost disease. The idea is simple and is based on the principle that wages in the economy as a whole rise in line with the productive sector, and that, in the productive sector, wages are tied to productivity. In the productive sector we should not expect to see any deviation in the difference between wages and productivity. Therefore, when we look at differences in wages and productivity in the economy as a whole, any variation in the difference between wages and productivity should be due to the stagnant sector. Shortfalls in productivity in the stagnant sector are not associated with changes to the wage rate. The test for the cost disease is then whether changes to the difference between wages and productivity in the economy as a whole are related to the costs in the stagnant sector, since the theory proposes that the driver of increased stagnant sector costs is the increase in wages relative to productivity.

In a very recent paper, using a panel of 50 US states between 1980 and 2009, Bates and Santerre estimated the effect of the difference between wages and productivity, in the economy as a whole, on unit costs in healthcare. This difference has been called the ‘Baumol variable’. It doesn’t seem to have much direct economic interpretation, but a positive coefficient is interpreted as evidence for the cost disease. They also included controls for the other possible determinants of rising healthcare costs: an aging population, unemployment and income per capita. In a previous paper, Hartwig estimated a similar model.

Both papers find a positive and statistically significant coefficient on the Baumol variable. Bates and Santerre argue that their method and results are an improvement over those of Hartwig, and since they support his findings they further strengthen the evidence for the presence of the cost disease in the US.

As Baumol himself identifies, if we accept the cost disease hypothesis, rising healthcare costs are not that great a problem. While healthcare costs take up a greater share of the pie, the pie is expanding at least as fast. However, Bates and Santerre also find evidence that population aging and unemployment cause increases to healthcare costs. This may mean that the pie does not grow proportionally to the healthcare slice but it does provide some reassurance that the problem is not as severe as depicted by many politicians.

From a policy perspective it may appear as if the solution is a Logan’s Run style scenario where, once people reach a certain age, they are vaporised and ‘renewed’. This would at once solve the aging problem and probably reduce unemployment too. Increases in healthcare costs would then only be a cost disease effect, but I doubt this idea would pass ethics approval. What is certainly true is that a greater understanding of the determinants of healthcare costs are required to better control them and understand the limits of our ability to control them.


  • Sam Watson

    Health economics, statistics, and health services research at the University of Warwick. Also like rock climbing and making noise on the guitar.

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6 years ago

[…] few years ago we discussed Baumol’s theory of the ‘cost disease’ and an empirical study trying to identify it. In brief, the theory supposes that spending on health care (and other […]

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Wally Knox
Wally Knox
11 years ago

Sam, thanks for your excellent intro to Baumol’s theory. Here is another thorough paper assessing the theory: William Nordhaus’ 2006 paper “Baumol’s Diseases: A Macroeconomic Perspective”, NBER’s working paper 12218 found at

Nordhaus looks at half a century of data from 67 industries and concludes: (1) industries with lower productivity show a percentage-point for percentage-point higher growth in relative prices (Baumol confirmed); (2) stagnant industries tend to have lower real output growth; (3) the effect on job growth is “murky”; (4) factor rewards of higher productivity (higher wages or profits) are slight with the vast bulk of the benefit flowing to consumers through lower prices; and (5) Baumol’s disease lowered overall productivity growth by half a percentage point.

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