For the case of Liberia, MAMS is applied to a database for 2009, developed from Supply and Use Tables for 2008, complemented by data from other sources (including the Government of Liberia, IMF, and the World Bank), and balanced to ensure consistency. The database is disaggregated into multiple sectors, factors, institutions, including auxiliary accounts for different tax types; see Table A2.1 for details). One important feature is that government budget and (off-budget) donor-financed activities are integrated under the government heading. This reflects the fact that on- and off-budget spending in different areas serve similar purposes and often are complementary (for example with the government covering a larger share of O&M [Operations and Maintenance] and donors a larger share of investments). The integration underlines the need to align and harmonize their activities.<sup>5</sup> In terms of model adjustments, the main changes in Liberia MAMS compared to more standard versions of MAMS are related to the mining sector, where investment and production projections are exogenous. The simulations , which are focused on the period 2012-2030, incorporate information about the development of the economy starting from 2009 (to ensure that the 2012 starting point is realistic), including developments related to growth, foreign grants, foreign borrowing, and the mining sector.

The simulations include a base scenario, a set of policy scenarios, and an export price shock scenario. The base scenario is designed to generate a plausible projection into the future to which the other scenarios can be compared. The policy scenarios are designed to address the consequences of additions to fiscal space from alternative sources (taxes, foreign grants, or government efficiency) and alternative uses of this fiscal space (infrastructure, human development or a combination of the two). The export price shock scenario explores the impact of a decline in the price of mining exports. In addition, we briefly discuss additional scenarios that were designed to test the sensitivity of our findings to alternative combinations of assumptions related to financing, priority spending, and iron export prices.

# _BASE SCENARIO_

Our presentation of the base scenario starts with an overview of key assumptions, followed by an analysis of the simulation results. The presentation emphasizes developments during the full period 2013-2010; Tables with detailed simulation results singles out two sub-periods, 2013-

> 5 The distinction between on- and off-budget aid is important for some purposes. However, keeping the two separate in the MAMS database would impose an additional data requirement and complicate the analysis given that these two activity types are complementary; for example, the government carries out the bulk O&M for infrastructure while donors are responsible for most new investments. At the same time, it would not yield any significant insights, in particular given limited knowledge about how input structures and output quality differ between donor- and government-operated activities. Given the questions posed, it would be a mistake to limit the analysis to on-budget government; to exemplify, in 2012, donor on-budget transfers only represented 7.3 percent of total donor transfers (excluding UNMIL). Out of total government revenues (including on- and off-budget grants and domestic revenues but excluding UNMIL), in 2012 around 53 percent (433 out of 822 million US$) was onbudget; the on-budget share of total non-UNMIL grants share was only around 7 percent (IMF 2012, pp. 41-42).

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