Previously I have shown that household gross adjusted disposable income and actual individual consumption (AIC) are superior predictors of national health expenditures (NHE) and that they largely explain why US national health expenditures (NHE) are so high. However, my analyses have been restricted to the handful of mostly highly developed countries affiliated with the OECD for time series and the World Bank’s International Comparison Program (ICP) for cross section for ~all countries in 2011. I know of no simple ways to retrieve AIC or adjusted household disposable income outside of OECD in readily comparable formats, so I decided to spend a little time constructing these estimates for a much broader array of countries using the official system of national accounts tables available from the UN statistics division, which mostly covers between 1990 and 2014.
This analysis is largely a reproduction of prior work, but I felt I would write this up because:
- the data themselves are useful (sharing data & code this time around)
- it provides additional support for my general position vis-a-vis the utility of these measures in this context
- time series nature of the data helps demonstrate the non-linear relationships between these measures and NHE
Unfortunately the coverage is not quite 100%
These particular data notably excludes most of the oil rich gulf states, Singapore, and other high GDP countries where the disconnect between GDP and what is actually going on at a household level vis-a-vis disposable income, AIC, NHE, etc is particularly large (which would have helped illustrate of the limitations of GDP in this context). Still it’s useful for the time series and less OECD-centric nature of the data. I won’t bore you with too many of the particulars of how I constructed the data as it’s in the source code.
A brief review of these concepts
To briefly review for those that have not read my prior posts on these topics: both household gross adjusted disposable income and actual individual consumption include net transfers from government, whether cash or in-kind (e.g., education, health care, etc). Which is to say that they are comprehensive measures of household income or consumption after the net effects of government taxes and transfers have been thoroughly taken into account (also note that a large proportion of welfare state transfers are actually cash, not in-kind). These two figures are very strongly correlated because household gross-adjusted disposable income is little more than AIC plus household gross savings and households generally spend a large and fairly predictable share of their disposable incomes when averaged over a whole country (or at least in the long term… in the short term people may consume out of savings).
My view is that the allocation of resources towards health care is ultimately determined almost entirely by the average households’ real or perceived economic situation, both with regard to direct/out-of-pocket expenditures and indirect expenditures through government and private/employer based programs (at the voting booth, when picking jobs, benefits packages, etc…. even if lagged by a few years). Gross-adjusted household disposable income or AIC are far better indicators of this than GDP as GDP is several steps removed (resources can be allocated towards different sectors of the economy, allocated towards fixed capital consumption, and more).
Real household net disposable income is defined as the sum of household final consumption expenditure and savings, minus the change in net equity of households in pension funds. This indicator also corresponds to the sum of wages and salaries, mixed income, net property income, net current transfers and social benefits other than social transfers in kind, less taxes on income and wealth and social security contributions paid by employees, the self-employed and the unemployed. Household gross adjusted disposable income additionally reallocates “income” from government and non-profit institutions serving households (NPISHs) to households to reflect social transfers in kind. These transfers reflect expenditures made by government or NPISHs on individual goods and services, such as health and education, on behalf of an individual household. The indicator includes the disposable income of non-profit institutions serving households. Disposable income, as a concept, is closer to the idea of income as generally understood in economics, than is either national income or gross domestic product (GDP)
Although GDP is a usually decent proxy for this income concept (and thus usually a decent predictor of NHE) there can be substantial differences between countries’ economic situations that can make straight comparisons of GDP highly misleading, especially as it pertains to the household sector (as opposed to national disposable income). Beyond the potential general disconnect between GDP and material living conditions, I have found that even the allocation of disposable income between economic sectors has very different implications for what we can expect a country to spend on health care. Likewise for the allocation of GDP towards AIC versus other expenditure areas.
Here is a simple animation of health expenditures over real AIC per capita.
Both trend lines are 3rd degree polynomials excluding the USA. The thin blue line is the trend across all years whereas the dotted purple line is the calculated trend for each year. The annual trend line barely changes and largely matches the trend for the entire series, save for the high consumption territory at the start (not enough observations when USA is excluded!). What you’re not seeing here is strong secular trend of increasing intercept in the annual trend line. NHE is not rising inexplicably (e.g., inexplicable increase in “technology” or “health inflation”); it is only systematically increasing to substantial degree in countries with rising income/consumption. It is also quite obviously non-linear.
Including year fixed effects and excluding USA and Luxembourg does not change this.
And the year fixed effect trend is quite modest (~125 USD/person over 19 years):
As a percentage of AIC the non-linearity is also apparent by countries over time and between countries each year, although it is considerably noisier, especially amongst the poorer countries where small absolute changes in NHE can make a huge difference in percentage terms and chances for measure error are higher (unless they’re systematically over or under-estimating these should average out). As real incomes rise countries allocate an increasing share of consumption to NHE and this increases increasingly.
We can show much the same for gross adjusted household disposable income.
This makes the US appear to skew somewhat higher than the equivalent for AIC, but it still paints a vastly different (more realistic) picture that what would be suggested by GDP and it helps establish that this is not just about unusually high US consumption levels due to greater credit access or some such.
The problem, such as it is, is not so much that US has exceptionally high consumption or unusually high disposable incomes relative to its GDP (it’s only slightly above average), but that the relationships between NHE and these determinants of NHE are non-linear and the few other high GDP countries have unusually low consumption and low disposable incomes relative to their GDP.
For instance, using my constructed data set:
Model 2: 2nd degree polynomial
By crudely removing NHE from comprehensive household consumption or disposable income like this we remove a big part of the signal and likely significantly overstate the role of these other GDP components (which nonetheless come out as quite modest), but still we can pretty clearly see that it is the household sector and/or broad measures of consumption that are doing nearly all of the work vis-a-vis GDP and NHE and that it’s not just because of some weird mechanical effect due to ~100% of NHE showing up in these figures. There are clearly strong affinities between overall household consumption or disposable income and national health expenditures that we don’t see elsewhere in GDP.