nurses/midwives, the combined region‐ and income group‐specific aggregate median density rate was applied to the most recent data year. In a number of countries where no empirical data for nurses/midwives was available but information on physicians was available, a global ratio of 2.517 nurse/midwives to physicians was applied to obtain the estimate for nurse/midwife density. The ratio multiplier for all other health workers was then similarly applied to obtain an estimate for all other health workers, and the estimates for all three types of health workers summed to obtain the total supply of health workers per country (see Annex A for more details).

We explored alternatively specifying Equations 2 and 3 as log‐linear models, which assumes an exponential functional form. The resulting projections from the exponential specification yielded estimates that were magnified compared to those from the linear specification, exaggerating both positive and negative trends. Coupled with the sparse number of data points for many lower income countries, resulting predicted values appeared to be less stable. Within‐ sample specification tests were also not possible given the data constraints. We therefore adopted the more conservative linear specification.

# _Data_

Country‐level data were collated from multiple sources. Historical data on physician and nurse/midwife densities (1990‐2013) were obtained from the WHO Global Observatory Health database (WHO no date). Historical and projected total population and population aged 65 and over were obtained from the United Nations Population Division.

We used the World Bank Development Indicator database to retrieve historical (1995 – 2013) GDP per capita (in constant 2011 dollars, purchasing power parity (PPP) values), total health expenditures per capita (in constant 2011 international dollars, PPP values), and the share of health spending OOP (World Bank 2015). Projected real GDP per capita through 2030 were obtained from the analysis carried out by Patrick Huang‐Vu Eozenou (see Annex B for details). Historical data on OOP expenditures per capita (1995‐2013) were calculated from health expenditure and OOP percentage data. Estimates for future OOP per capita were obtained by projecting the OOP percentage of total health spending from 2014 to 2030 by selecting the models giving the smallest predicted error for each country (see Annex A for details). Projections of future workforce demand were made for 165 countries for which both demand and supply input data were available.

To obtain the estimates for nurses and midwives and all other workers, we use the approach taken by WHO to fill missing data by multiplying the projected physician density for each country by a constant 2.517 ratio of nurses and midwives to physicians based on the WHO Global Observatory data (WHO 2016). This estimation assumes that the production function for health care workers will stay constant and is the same for all countries. To obtain estimates of all other workers, we similarly applied constant multipliers, but did so stratified according to World Bank income groups (high income = 0.373; upper middle income = 0.406; lower middle 8