repeat it, or drop out of their level. A share of labor-force-age students exiting from the school system enters the labor force in the segment that matches their educational background. Similarly, a share of the non-school population (perhaps drop outs at an earlier age) that each year reaches labor force age enters the labor force, typically in its least educated segment.

# _Database_

A typical MAMS application requires an extensive data set for the application base-year – a social accounting matrix (SAM); stocks for production factors (including different types of labor and capital), population, and school enrollment; indicators for selected MDGs and the educational system – as well as a set of elasticities (for production, consumption, trade, and human development relationships), and projections into the future (for growth in GDP at factor cost and the evolution of disaggregated MDG and education indicators and determinants), to which the MAMS baseline simulation is calibrated. (See Appendix 1 for more details.) The database for the current application was designed in light of data availability and the analytical objective of shedding light on the impact of changes in world food prices on MDGs and other major social and economic indicators in LICs. Two database variants were constructed: a LIC net food importer with trade shares that characterize a LIC that is relatively dependent on imports for its food consumption; and a LIC net food exporter that represents a country that has a relatively strong reliance on food exports. In other respects, including initial macro structure and HD, the starting points for the two archetypes are identical, facilitating comparisons between the two.

As shown in Table 2.2, the database is disaggregated into 14 production activities, each of which produces one commodity (good or service), as well as one commodity without domestic production (refined petroleum). Among the sectors, government production is represented by 8 services, covering human development, infrastructure and other areas. The factors of production are split into land (for the agricultural activities) and different types of labor and capital. Tables 2.3-2.5 summarize the macroeconomic and sectoral structure of the archetype LIC net exporter and importer economies in 2009: a macro SAM (common to both archetypes) and tables showing sector structure (in terms of value-added, production, employment, and trade) for each of the two archetypes.<sup>14</sup> In addition, median LIC observations were collected for a set of MAMS-relevant HD indicators.

> 14 A SAM is a square matrix with identical row and column accounts, providing a comprehensive representation of payments flows in the economy of a geographical unit (typically a country) during a period of time (typically one year). Cell entries represent payments from its column account to its row account. In a SAM without errors, row and column totals are equal. SAMs appear with widely varying degrees of disaggregation. The payments flows are expressed in current local currency or some transformation thereof – in Table 2.3, the value of each cell has been transformed into percent of GDP at market prices in the same year. For more on SAMs, see for example Reinert and Roland-Holst (1997) and Round (2003). The detailed LIC MAMS SAMs for this application are available on request.

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