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Oil revenues for public investment in Africa: targeting urban or rural areas?


This paper investigates the effects of oil-financed public investment on economic growth and poverty reduction using a dynamic multi-sectoral general equilibrium model featuring inter-temporal productivity spillovers. The paper shows that the relationship between resource-rent flows and real exchange rates, output growth, and poverty is less straightforward than simple models of the “resource curse” suggest. Taking Ghana as a stylized agriculture-based economy with poverty most pronounced in a region with home based agricultural production, a policy mix of smoothing the real exchange rate shock and an allocation of infrastructure spending in rural areas seems to be the most promising public investment strategy to enhance growth and reduce poverty.

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  1. Windfall income or the expectations of such income generated by a discovery of natural resources might induce the country to neglect the need for sound economic management and institutional quality (Gylfason 2001). A false sense of security might lead governments to undervalue the importance of human capital, institutional quality and long-run growth (Rodriguez and Sachs 1999; Sachs and Warner 2001). In addition, adverse results may be the effect of an interplay of rent-seeking groups and weak institutions (Auty 2000).

  2. Recent publications present evidence that natural resources diminish the need for investment and savings because of the expected future income (Gylfason and Zoega 2006). Hence, at least part of the windfalls will be consumed and expectations about additional economic growth driven by the full extent of the windfall spend for investment may be exaggerated (see, e.g., Sachs and Warner 1997; Edwards 1989; Brunstad and Dyrstad 1997; Bjørnland 1998; Hutchinson 1994; Usui 1997 and Jahan-Parvar and Mohammadi 2009).

  3. A comprehensive survey of this literature is provided by Gramlich (1994) and Straub (2008).

  4. Tables 4 and 5 in the “Appendix” provide some indicators on the export orientation of individual sectors and the import dependence of domestic demand, together with information on sectoral and regional production, employment and cost structure. Besides mining, cocoa, forestry and livestock are the most export oriented sectors, exporting between 25 and 85% of their production, with the bulk of export production stemming from agro-ecological zones 1–3 while the poor zone 4 (Northern savanna) is producing almost exclusively for the domestic market.

  5. Recently Rutherford et al. (2004), have constructed a model for Russia that endogenously includes over 55,000 households.

  6. For each simulation, the impact effect (years 2008–2010) and the evolution of the economy until years 2015, 2020, and 2027 are reported. To simplify the presentation, the focus is on changes in only a small number of key aggregates: the trade weighted real exchange rate, the volume of exports, real GDP, private investment, the fiscal balance, the aggregated sectoral real value added, rural and urban household welfare measured by the equivalent variation (Table 1) and the incidence of poverty (poverty headcount; Table 2). Tables 6, 7, 8 in the "Appendix" report on the disaggregated factor income distribution, poverty depth, and poverty severety.

  7. For a similar result in the case of home driven productivity increases, see, e.g. Adam and Bevan (2006).

  8. For details, see Breisinger et al. (2009). The simulations neglect the phasing in and out of the actually expected stream of Government revenue, which consists of two successive temporary increases in foreign exchange revenues to the government, yielding 4 years of peak revenue, to be followed by a continues decline of revenue afterwards (World Bank 2009b).

  9. Government revenue grows as real incomes and expenditures grow while, after the initial step changes in year 2010, real government spending does not. Savings available for private investment grow partly with GDP but also because of crowding-in from the improvement in the fiscal balance. It is a consequence of the closure rule mentioned earlier that these resources are duly invested.

  10. Scenarios OIL4 and OIL5 assume the same infrastructure spending pattern as scenario OIL3.


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Correspondence to Manfred Wiebelt.



See Tables 4, 5, 6, 7, and 8.

Table 4 Production and trade structure, Ghana 2007 (percent)
Table 5 Output, input, and trade structure of agriculture, Ghana, 2007 (%)
Table 6 Change in disaggregated factor income distribution
Table 7 Simulation results of the poverty effects of a temporary increase in government oil revenues (poverty depth)
Table 8 Simulation results of the poverty effects of a temporary increase in government oil revenues (Poverty severety)

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Wiebelt, M., Schweickert, R., Breisinger, C. et al. Oil revenues for public investment in Africa: targeting urban or rural areas?. Rev World Econ 147, 745 (2011).

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  • Oil revenue
  • Public investment
  • Productivity
  • Africa
  • Agricultural development
  • Poverty

JEL Classification

  • H4
  • O5
  • Q3