The Oxford Handbook of Health Economics
I don’t know in how much detail I’ll cover this book in the week to come but there’s some interesting stuff in there and I figure I might as well start ‘work-blogging’ a bit again. It is my goal to read at least 100 pages/day in this book over the next week’s time, meaning I should be finished at the end of next week (the book has 937 pages, excluding the index at the end – I’ve read 165 pages so far). 100 pages per day isn’t actually all that much and I may decide to work more than that, but the book is occasionally a little technical and I set that goal also because I knew it would be achievable (plus it’s not the only work I’ll be doing). I’ll probably cover plenty of stuff here which will end up not being directly relevant to my work, but I don’t think any of you will object strongly to this – almost none of the stuff I cover here on the blog has anything to do with my university activities anyway. I’m in the very rare situation that stuff which I might have read anyway because I find it interesting actually turns out to be relevant to my work/studies.
I don’t know how difficult the material covered in this book will be to understand for people without a background in economics; it’s much easier to make correct assumptions about such things if you’re covering stuff which is technically not within ‘your field’ either (e.g. psychology textbooks). Fortunately unlike Mas-Colell this is not a (not very well…) disguised math textbook, so I think it actually makes sense to cover some of the stuff from the book here on the blog – it made pretty much no sense to cover the stuff in Mas-Colell which was a big part of why I didn’t do it. I don’t know to which extent it’ll be necessary to add links and comments etc. along the way to aid understanding and I will probably underestimate the need – if you don’t get what they’re talking about even though I seem to be assuming that you ought to get it, just ask questions in the comments and I’ll try to clarify. I have done work on some of the topics covered in the book before, so it’s not like I don’t know anything about these things. Only one chapter so far has been what I’d term ‘model-heavy’, and although I probably won’t talk much about that one there should still be plenty of stuff in the book which it makes sense to cover here. I should note that I’m very aware of the fact that time spent covering the book is time not spent reading, and although I may derive a small benefit from covering the material here I won’t let blogging interfere with the reading goal. So I don’t know how much I’ll blog in the week to come – we’ll see.
Below some observations from the first 7 chapters/160 pages:
“Health care spending has been capturing a growing share of the GDP in all OECD countries between 1970 and 2008. In the median OECD country, health care spending was 5.1 percent of GDP in 1970 and increased to 9.1 percent by 2008 […] A persistent outlier in health care spending has been the US, where health care spending increased from 7.0 percent of the GDP in 1970 to 16.0 percent in 2008. […] Denmark was also an early outlier, actually spending a greater percentage of its GDP on health than the US (7.9%) in 1970. By 2008, Denmark had similar health care spending levels as the median OECD country, a result of a very slow rate of growth in health care spending between 1970 and 2008.” [Actually one might argue that this last part shouldn’t be news to ‘regular readers’ as I’ve covered the Danish numbers before here on the blog in a post in Danish. Note that the data in that post seem to indicate that there may have been a structural shift around the year 2000 or so – the cost share has risen relatively fast since that time, compared to earlier. Denmark is above 11% of GDP now.]
“Growth rates in health care spending are […] compared using the average annual growth rates of health care spending adjusted for inflation and population growth. Using this measure, the average annual rate of health care spending growth was 3.9 percent in the median OECD country from 1970 to 2008 […] The rate of health care spending growth was higher than inflation in every OECD country during the overall time period. […] In 2008, approximately three-quarters of the health spending was from public funds in the median OECD country, while the remaining quarter was from private funds. […] Of the private health care dollars in the median OECD country, 72 percent were out-of-pocket expenses in 2008. Private health insurance is responsible for a small proportion of health spending in most OECD countries. […] Across the OECD, about 15 percent of all tax revenue is devoted to health care – a proportion that is steadily increasing.”
“Three sectors of health care represents over half of the total health care spending in most OECD countries: inpatient hospital care, outpatient medical services, and pharmaceuticals. […] Inpatient hospital spending declined rapidly during the period from a median of 48.5 percent in 1970 to 32.3 percent in 2008. […] During the same time period, the length of stay for inpatient care has fallen by approximately 58 percent. […] The median OECD country has seen a slight increase in the share of pharmaceutical expenditures from 17.5 percent […] to 13.8 percent [sic; I’m sure those numbers were mixed up during editing.] […] Real GDP per capita increased by 120 percent from 1970 to 2008 in the median country of the OECD. […] health spending per capita increased by 314 percent […] after controlling for inflation and population growth […] Health spending grew an average of 1.8 percent per year faster than GDP in the median OECD country […] The percent of the population over the age 65 [increased] 40 percent in the median OECD country. […] Life expectancy increased by 8.8 years […] while fertility rates declined by 31 percent. […] Every OECD country had an increase in the number of physicians per 1000 capita between 1970 and 2008 […] The median OECD country had a 223 percent increase.” […but note also that: “on the whole, healthcare wages does not drive health spending growth”]
“Chronic diseases is creating a growing burden on health care spending. […] within the US, 85 percent of health spending was attributed to people with chronic diseases in 2006 (Anderson 2007).”
“Low and middle-income countries (LMICs) […] account for 84 percent of the world’s population, 90 percent of the world’s disease burden […], 24 percent of the world’s GDP, and only 13 percent of global health expenditure. […] The lower the country income level, the higher tends to be the share of out-of-pocket payments […] and the lower the share of revenues (e.g. tax, insurance premiums) which flows through financing agents. […] Even in a country like India, 83 percent of total expenditures on health is from private sources, and of this 94 percent is from out-of-pocket payments. […] [there is] only 0.3 physicians and one nurse per 1000 people in low-income countries. SSA has the lowest density of physicians (one doctor for every 5.000 people), and South Asia of nurses (one nurse for every 1430 people).” [I was very surprised when looking at the data in this chapter; everybody knows that South-Saharan Africa sucks, but South Asia do almost as badly on a lot of health metrics – and on some of them they do even worse than SSA.] […] “Within overall low coverage levels, there are considerable within-country inequalities by socioeconomic group […] In low-income countries, children from the highest wealth quintile have double the measles immunization coverage of the lowest wealth quintile, and there is a seven-fold difference between highest and lowest wealth quintiles in presence of a skilled birth attendant at birth” [note that this latter difference likely translates into a lot of dead babies; infant mortality rates are high these places.]
“There is some evidence from developing countries to suggest that while the public share of revenue may increase as countries grow richer, the public share of [health care] provision shrinks.”
“In low-income countries […] resource limitations make it difficult to provide universally even a limited package of high priority interventions […] The commonly recommended solution is to target resources to the poorest, but there is little evidence so far that such targeting can be done effectively, or that it is cost-effective relative to broader approaches”
“In sum, education is strongly related to health, with both reserve causality and direct effects. However, the extent to which the correlation between education and health reflects direct causality, reverse causality, or omitted factors is not known. Although mechanisms by which health affect educational attainment are well-understood, how education affects health is not. […] it seems unlikely that any one mechanism alone can explain the effect of education on health.” [I wrote a review paper on this topic a while back, coming to some roughly similar conclusions. I won’t cover this stuff in detail here because it’d just be review, but if you want to know more you’re welcome to ask. I incidentally think I may have written about this topic on the blog previously, but I’m not certain how detailed my coverage was.]
“Both income and wealth have strong independent correlations with health, net of education and other measures of SES. Assessing causality is difficult, however. Income and wealth improve access to health inputs (such as medical care and food), but health improves one’s ability to participate in the labour market and earn a decent wage. Illness also raises health care spending, thus reducing wealth […do note here that: “onset of a new illness reduces household wealth by far more than the household’s out-of-pocket health expenditures […] A large share of this reduction in wealth is attributable to a decline in labor earnings.]. Additionally, “third factors” – such as education – may determine both financial ressources and health status. Despite these caveats, many public health researchers have attributed the health-income gradient to a causal effect running from income to health. Some have even gone as far as labeling income “one of the most profound influences on mortality” (Wilkinson 1990: 412). Initial research seemed to support this view – in one such study, McDonough et al. (1997) estimated that a move from a household income of $20.000-$30.000 to a household income greater than $70.000 (in 1993 dollars) was associated with a halving of the odds of adult mortality. It was difficult to fathom that an association so large could be entirely due to omitted variables or reverse causality. However, more recent studies suggest that the direction of causality is far from clear and, furthermore, that it varies considerably by age. Among adults, the negative impact of poor health on income and wealth appears to account for a sizeable part of the correlation between financial ressources and health. […] Careful studies that look for the effect of income on health find little evidence to support this causal link in samples of older individuals in developed countries. […] a preponderance of evidence suggests that in developed countries today, income does not have a large causal effect on adult health, whereas adult health has a large effect on adult income. […] In the last two decades, economists’ most substantial contributions to this literature have involved untangling causal mechanisms.” [This is not news to me as I’ve done some work on this subject during my studies. But it seems like this often surprises people who don’t know what (at least some) economists/econometricians do.]
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