Based upon estimates of the change in consumption due to a change in out-of-pocket-health expenses (dC/dOOPHE) for 43 countries, this paper aims to argue for a reevaluation of what constitutes OOPHE when determining health insurance especially in the wake of Covid-19.
Reiterative truncated projected least squares (RTPLS), a statistical technique designed to handle the omitted variables problem of regression analysis.
If budgets are binding than dC/dOOPHE should be 0; if OOPHE merely adds to current consumption than dC/dOOPHE should be 1. However, merely plotting consumption versus OOPHE for the 43 countries for which organization for economic cooperation and development has the required data clearly shows a dC/dOOPHE much greater than one. This paper’s estimates of dC/dOOPHE for 2000 to 2017 range from 15.6 for Switzerland (in 2016) to 225.2 for Columbia (in 2003).
RTPLS cannot determine what part of the results are due to an increase in income causing both consumption and OOPHE to increase and what part is because of actual OOPHE far exceeding official OOPHE. However, the latter is involved.
As Covid-19 sickens millions while depriving millions of their normal means of generating income, what constitutes OOPHE should be expanded when determining health insurance. This paper’s results imply that even prior to Covid-19 health insurance covered much less than the optimal amount of actual OOPHE.
This is the first paper to use RTPLS to estimate dC/dOOPHE.
There was no funding for this paper and the author has no conflicts of interest.
The author appreciates Frazer McGilvray’s help with acquiring and setting up the data.
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