# **APPENDIX 2: THE MAMS DATABASE**

The database with this disaggregation consists of a Social Accounting Matrix (SAM), data on stocks (of factors of production and debts), elasticities (in production, consumption, trade, and MDG functions), and miscellaneous other data.<sup>18</sup> Table A2.1 shows the disaggregation of the database. The SAM, which was specifically built for this analysis is mainly based on the 2008 Supply and Use Tables (SUTs; which also include employment data), IMF fiscal and balance of payments data, as well as disaggregated fiscal and foreign aid data from the Ministry of Finance on the allocation of foreign aid across different areas (LISGIS 2011; Ministry of Finance, 2009, pp. 27-30; Ministry of Finance, 2010, p. 8). World Bank (2012) provided additional indicators, both on Liberia and across countries. Relative to earlier national accounts data (which mostly relied on extrapolations of pre-war surveys), the SUTs offer improved coverage of non-tradable domestic economic activities (including subsistence farming and informal service sectors). At the same time, the SUTs are by construction incomplete when it comes to fiscal and foreign transactions, requiring reliance on data from other sources; we here turned to IMF data. Inconsistencies between IMF and SUT data were resolved using statistical procedures. According to the resulting SAM, FY2009 GDP was US$1,421 million, in contrast with an earlier IMF figure of US$832 million for CY (calendar year) 2008 and an SUT figure of US$2,025 million for calendar year 2008; after a recent round of revisions, the IMF GDP figure for CY2008 and CY2009 are now US$1101 million and US$1155 million, respectively (IMF 2011, p. 21; LISGIS 2011, p. I; IMF 2012, p. 51).<sup>19</sup> With regard to the findings of the fiscal space analysis of this paper, the exact level of GDP makes little difference; the structure of the economy (the relative sizes of different payment flows is more important.

The analysis addresses the effects of alternative government spending patterns. In MAMS, these effects are covered via two mechanisms: (1) total factor productivity in selected production sectors is a function of the level of government service-specific capital stocks (cf. the disaggregation of government service sectors in Table 1), which are driven by government investments and depreciation rates; and (2) spending on health and water-sanitation has a direct impact on the MDGs for under-five mortality, water access, and sanitation.<sup>20</sup> The 18 A SAM is a square matrix that that provides a comprehensive, consistent economy-wide summary of the payments in an economy during one year. It links institutions, factors, and production sectors. The latter are split into activities (which carry out production) and commodities (representing activity outputs or imports without domestic production). Given the consistency requirement, each account must be balanced – its receipts must equal its outlays. The accounts of the Liberia SAM closely match the disaggregation of MAMS (cf. Table 1). The elasticities used in MAMS draws on the international literature; given the consistency features of an economywide model like MAMS, as long as they stay within ranges that are widely accepted, most elasticities play a very minor role. In the analysis of the simulation results, we will highlight the features of the model and the database (including elasticities) that have a significant bearing on our qualitative conclusions.

19 The higher the GDP (and GNI), the lower the average growth rate required to reach middle-income status by 2030. However, it is also worth noticing that economic activities that register the largest increases compared to earlier statistics (the informal sector and subsistence farming in particular) are less likely to grow rapidly. 20 In other MAMS applications, the impact of education has typically been captured by linking a detailed treatment of this sector to a labor market that is disaggregated by educational attainment, with higher wages (and marginal value products) for workers with more education. By permitting education spending to bring about an expansion in 27