commodities that are traded internationally, which add further rounds of global repercussions. The modeling work carried out for this analysis ensures that impacts on prices, factors of production, and sector outputs are consistently modeled, across sectors and countries, and over time.

Our scenario designs draw on recent studies of AMR that provide well-documented estimates of the individual factors and channels affected by AMR as listed and described next. Moreover, among the studies, we only use those that can be used as inputs and assumptions within our general equilibrium framework.

# **_Declines in labor supplies_**

Of the recent estimates of the impact of AMR on global mortality, the RAND Europe study by Taylor et al. (2014) includes well-defined projections; like our study, theirs also extends to 2050. That study provides increased mortality resulting from resistance to antibiotics for three main pathogens (bacteria): _Escherichia coli_ (popularly known as _E.coli_ ) _, Klebsiella pneumoniae_ (nasty pneumonia with drug-resistant complications), and _Staphylococcus aureus_ (or Staph infection), each of which contributes to the spread and worsening of infectious diseases. The constraints of data and analysis limit the projections of mortality only from three infectious diseases: HIV, Tuberculosis, and Malaria. Even so, the study allows for differences in fatality rate for each disease in low-income regions like Sub-Saharan Africa and high-income regions like OECD.

Following Taylor et al. (2014), the reductions in labor supply under the different scenarios in this study are defined in efficiency units and include the effects of morbidity (reflected in a loss of working days due to illness). The low-case scenario corresponds to the “sc1” case in the RAND study with a 5% AMR resistance rate at the starting period or year 0; the middle-case to “sc4”, which projects a current rate of resistance before year 15 and 40% from year 15; and a the high case to “sc5,” which projects a current rate of resistance before year 15 and 100% from year 15. We avoid the extreme cases of absolute resistance (sc6 and sc7). The “current rate of resistance” refers to the fact that AMR is already underway and that its effects are already registered in the historical estimates of the population for the base year (2007) to 2016, albeit still in small quantities. Hence, the Rand report distinguishes between 0% resistance rate (sc0) and the current rate of resistance (sc00). After testing, however, the estimated labor supplies that are corrected to have the zero rate (the world without AMR) are numerically indistinguishable from the uncorrected UN demographic projections in the significant digits for the unit of population chosen (in millions). Hence, we do not make the delineation, and the baseline simulation in our paper uses the UN population projections, which for all practical purposes is the world without AMR. Finally, the mortality figures are mapped from the geographical regions of the RAND study into World Bank income regions for our study. More specifically, Sub-Saharan Africa is in our low-income region, high-income corresponds directly to our high-income region, while their other regions are split across our lower middle-income and higher middle-income regions.

The RAND study reports the number of deaths only for workers (or labor supply). Applying the fatality rates of the working age population (labor) to the non-working age (the young and the old who are outside the labor force), we derive the number of deaths for the total population. The resulting 9