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Appendix 1. Poverty Diagnostics and Safety Nets in the MRU Countries
Appendix 2. Fiscal Regimes and Resource Revenue Scenarios
Appendix 3. Model Specification, Solution Method, Calibration, and Simulation Results
The model description follows Melina et al. (2014) closely. The main differences from the original DIGNAR model are in the fiscal specification for managing resource revenues and the time-varying resource tax rates to target the resource revenues as a share of GDP, generated from the FARI model. Sections A to D specify the model, and Section E describes the equilibrium system, the solution method, and calibration.
We are indebted to N. Le, A.A. Wane, A.O. Bah, and L.D. Mireaux for kind assistance with data collection, and to E. Fuli for her support with the FARI model. We also thank IMF seminar participants for insightful comments. This working paper is part of a research project on macroeconomic policy in low-income countries supported by U.K.’s Department for International Development (DFID).
The list of Fragile Countries is available at http://siteresources.worldbank.org/EXTLICUS/Resources/511777-1269623894864/FY15FragileSituationList.pdf. Recent reports by the Africa Progress Panel (2014) and the African Development Bank (AfDB, 2014) address how to harness the continent’s natural resource wealth for all, with the AfDB report focusing on fragile countries.
While these issues and constraints are more salient in the case of fragile countries, all resource-rich low-income countries face similar challenges and, in that sense, the main conclusions of this paper apply more broadly.
The MRU serves as a cooperation forum on security and other cross-border topics. All four countries are also ECOWAS members.
See the poverty reduction strategy paper (PRSP) for Côte d’Ivoire and Guinea, and growth constraints diagnosis documents (building on the methodology developed by Hausman, Rodrick and Velasco, 2005), initiated for qualification to the US Millennium Challenge Corporation’s grants, for Liberia and Sierra Leone.
Both scenarios are thus based on the pre-Ebola outbreak situation for the four MRU countries. Evidently the post-Ebola resource production profiles and macroeconomic frameworks are likely to be quite different. The Ebola crisis is having a significant impact on growth and is disrupting current mining output in Liberia and Sierra Leone and will likely affect medium-term production profiles as key investment is delayed. While there is too much uncertainty at the moment to attempt to establish a new set of macroeconomic projections, the present exercise should be understood as illustrative of the steps that would have to be followed in other resource-rich fragile countries or in the MRU after the current Ebola outbreak is contained.
Botswana’s Sustainable Budget Index requires all current spending to be covered by non-resource revenue, with diamond revenue allocated to public investment and health and education, or saved in the Pula Fund.
Given that the revenue profiles for the three mining countries (Guinea, Liberia, and Sierra Leone) exhibit similar characteristics, in the rest of this section we only present results for Liberia and Côte d’Ivoire.
Under the baseline scenario, for Liberia, the investment path based on the PIH equals the rate of return on the PV of the projected natural resource wealth (about 1.8 percent of GDP), plus the investment financed with the government’s own resources (about 2 percent of GDP). For Côte d’Ivoire, under the PIH, public investment is projected to decrease gradually but to equal on average the sum of the annual return on the PV of resource wealth (equal to 2.3 percent of GDP) and of grant-financed investment (1.3 percent of GDP). In the optimistic scenario, for Liberia the pure PIH estimate is 4.3 percent of GDP, raising the investment path to an average of 10.3 percent of GDP during 2015-19. For Côte d’Ivoire, under PIH the pure estimate of public investment ratio is only slightly higher than under the baseline at 3 percent of GDP.
Spending resource revenues on productive public investment can increase consumption of both types of households. However, it works indirectly by boosting private sector productivity and hence the wage rate due to more productive capital. A higher wage rate increases households’ income and private consumption. Compared to spending resource revenue on public investment, direct revenue transfers increase private consumption of the hand-to-mouth immediately without the delay in building up public capital.
In reality, tax schemes on the resource production can be complicated. The paths of royalty rates used in simulations are backed out to target resource revenues to GDP ratios, obtained from the simulations of the FARI model.
Learning-by-doing externalities can both reduce and enhance private sector productivity, depending on traded output responses to resource spending. Under our assumption that part of the resource revenues is spent on nontraded goods, spending resource revenue leads to real appreciation, which lowers the productivity of the traded good sector. Later as public capital is built up due to increased investment spending, the externalities enhance private productivity of both sectors with more productive public capital.
Van den Bremer and van der Ploeg (2013) distinguish among three types of resource funds often encountered in reality: 1) an intergenerational fund (such as a sovereign wealth fund), which mainly saves current resource revenues to smooth benefits across generations, 2) a liquidity fund, motivated by precautionary saving to self-insure against large future negative shocks to volatile revenues, and 3) an investment fund, which uses resource revenues to undertake domestic public investment projects. The resource fund modeled here is a combination of a liquidity fund and an investment fund.
This implies that the debt trajectory generated by the simulations using the DIGNAR model may not be consistent with the debt path from the debt sustainability analysis, which is generated using a different framework that does not account for the general equilibrium interactions between fiscal and macroeconomic variables.
The initial level of transfers is based on the actual average share of transfers in GDP in the four countries, which, at the moment, are mostly financed by donors (Monchuk, 2014).
The technical committee recently recommended the repealing of the BSGR-VALE concession agreement on the Northern bloc of the Simandou iron-ore deposit, which has been fully endorsed by the Government. But BSGR threatened to take the case to international courts, adding to the uncertainties surrounding the development of this mine.
The authorities’ projections are more ambitious, with oil production expected at 200,000 barrels per day within five years.
Little information is available on the large iron-ore project as well as bauxite and other minerals. The direct revenue impact of gold projects is negligible at about 0.03 percent of GDP per year. Data availability issues and considerable uncertainty on the profile of investment have not allowed to include a surge in mining activities in the scenario.
Note that this starting date may switch to 2018, as discussions on finalizing the legal investment framework have incurred some delays.
Because of the common wedge between tax burden imposed and tax revenues accrued to the government in developing countries, we assume that a fraction ϑK of the tax revenue related to capital income does not enter the government budget constraint
To guarantee that the resource fund is not an explosive process, we assume that in the very long run, a small autoregressive coefficient ρf ϵ (0, 1) is attached to. The model is typically solved at a yearly frequency for a 1000-period horizon. The coefficient ρf is activated after the first 100 years of simulations.
In addition tax rates, government consumption and transfers can also be used as fiscal adjustment instruments.
The DIGNAR model can also use government consumption and transfers as fiscal adjustment instruments.
For simplicity, we assume there is no cost in resource production, and the dividends are received by foreigners.
This assumption may be somewhat conservative. The median return of the World Bank projects is 24 percent in 2008 (International Bank of Reconstruction and Development and the World Bank, 2010).
There is little empirical evidence in quantifying the efficiency costs associated with absorptive capacity constraints. Arestoff and Hurlin (2006) estimate the investment efficiency for Mexico, and find that investment efficiency drops to a lower level when investment expenditures are 60 percent above the sample average.