are identified by sectoral studies underpinned by econometric analysis. They include other MDGs – better access to water and sanitation may improve health outcomes (MDGs 4 and 5) – as well as infrastructure or consumption per capita. For example, a higher level of consumption per capita may certainly influence health achievements positively. Pregnant women who are better fed run less health risks for themselves and for their babies. Among the “other determinants,” per-capita household consumption and other MDGs represent demand-side factors whereas public infrastructure can be seen as facilitating both demand and supply.

**Table 2.1: Determinants of MDG achievements**

|||**Other Determinants**<br>||
|---|---|---|---|
|**MDG**|**Per-capita real**<br>**service delivery**|**Per-capita household**<br>**consumption**<br>**Public infrastructure**|**Other MDGs**|
|4|X|X<br>X|7a,7b|
|5|X|X<br>X|7a,7b|
|7a|X|X<br>X||
|7b|X|X<br>X||

_Note_ : The MDGs referred to in this table are defined as follows: MDG-4: Reduce by two thirds the mortality rate among children under five; MDG-5: Reduce by three quarters the maternal mortality ratio; MDG-7a: Halve the proportion of people without sustainable access to safe drinking water; and MDG-7b: Halve the proportion of people without sustainable access to sanitation services. The target year is 2015 and the reference year is 1990. The services related to these MDGs are health (disaggregated by technology), and water-sanitation services. Other determinants should be added if they are important in the context of a particular country study; if any of the determinants listed in the table are unimportant then they can be omitted (or given an elasticity of zero). MDG 2 is covered in the following discussion of education.

In order to implement the first block of MDG equations, data is required on government spending by function (one or more health sectors, water and sanitation, other public infrastructure, and other government) and type of outlay (current vs. capital). Current outlays must be disaggregated into payments to different types of labor (wages) and intermediate inputs.<sup>5</sup> This information, complemented by elasticities of factor substitution, is similar to what is required for other (non-government) sectors in a standard CGE model and can easily be built into the model's Social Accounting Matrix (SAM). In parallel with data on payments to labor, information is also needed on the number of people employed. The information needed for this block can typically be found in sectoral studies and databases of governments, international organizations and other research institutions.

> 5 The national accounts rarely ascribe value-added to government capital – by accounting conventions, only labor creates value-added in the government sector – making it impossible to derive coefficients of the MDG production functions from value-added shares as is standard practice in the calibration of private-sector production functions. The assumption of Leontief production functions made earlier is justified by that difficulty as well as the lack of information about the substitutability between capital and labor in these service sectors.

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