exogenously changed. At the same time, the model keeps track of children (less than 15 years of age), working age (15-64 years of age), and aged (over 64 years of age) populations, following the values of the medium fertility scenario of the UN (2015). These data are used to calculate the child and aged dependency ratios in each year of a given simulation, and are in turn used to help determine domestic savings behavior.

Domestic savings as a share of GDP is a linear function of four factors. The first factor is the savings share in the previous year, i.e. if savings were high in the previous year, they will only deviate from that value in the current year. The second factor is the growth rate of real GDP per capita. The third and fourth terms are the child and aged dependency ratios. The function is parameterized following the empirical estimates of Loayza, Schmitt-Hebel, and Servén (2000). These coefficients differ for countries based on their identification as either developing or developed, and are constant over the time horizon of the simulations. The coefficients for the savings and growth term are positive for all countries which imply that as countries grow they save more. The coefficients on the dependency ratio terms are negative for all countries.

As dependency ratios rise, the propensity for households to consume thus rises and savings as a share of GDP falls. The magnitudes of the aged dependency ratio coefficients are greater than that that of the young dependency ratio coefficients, and so an increase in the aged dependency ratio of a given magnitude will drag down savings to a greater extent than a decrease of similar magnitude in the child dependency ratio will increase the savings share. Since investment is modeled as being savings driven, total global investment is driven by total global savings, with the amount of investment in a given country being a function of both domestic savings as well as the current account balance, which is determined exogenously. The additional implication of the savings driven investment assumption is that that as dependency ratios fall in a given country, domestic savings will rise, which in turn will boost investment. The opposite would hold true for a country where dependency ratios are rising.

While LINKAGE provides the economy-wide effects of demographic change over time, the GIDD microsimulation framework (Bussolo et al., 2010; Bourguinon and Bussolo, 2013) will be used to generate income distributions under the various scenarios. GIDD draws on household level survey data benchmarked to 2010 to estimate income distributions by country that account for demographics, household characteristics (e.g. age, gender, and education of different members), sector of employment, skill premia on wages, and income.<sup>10</sup> Using the simulated income and employment under future scenarios from LINKAGE, and accounting for the demographic shifts characterized in the UN (2015), GIDD is able to generate income distributions by country that are consistent with both the more ‘aggregated’ changes under the CGE simulations and also what is known about households from survey data. In addition to incorporating the changes in key variables from the LINKAGE scenario results, the GIDD methodology updates the household survey data for the terminal year of the simulation. This is done by reweighting the population characterized by the base year household surveys using non-

> 10 Table A1 in the annex provides information on the household surveys used in the micro-simulation.

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