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The Macroeconomic Challenge of Aid Volatility Andrew Berg Calvin McDonald African Department International Monetary Fund Two dimensions Horizon: short (intra-year), medium (1-3 years), and long Agent: donors and recipients. Short-run predictability: problems Lots of volatility, even here. Mix of reasons: sometimes country, sometimes “fickle donors”, usually in between “innocent of what” Program and project very different. Short-run predictability: solutions Donors: can and are doing better But move to budget support can make problem more acute. Recipients should be able to smooth IMF programs have come a ways on this Even if IMF programs allow through adjusters, headline domestic borrowing and deficit targets can go awry. Medium-run predictability: problems Again, lots of volatility First principle component in a panel of aid flows explains 45 percent of the variation (Kang, et al. 2007) Macro risks: can cause inflation, exchange rate and interest rate volatility. Mainly because of problems of fiscal/monetary coordination. May cause increase in size of domestically-financed public sector Makes it hard to plan. Medium-run predictability: solutions Donors multi-year commitments etc. Break link between donation and aid flow: global funds, Rethink budget support? Recipients Create good MTEFs, scaling up scenarios Smooth aid How many reserves do you need, and how costly? Many countries have enough Surprisingly hard to do. Complications of exchange rate management Separate central bank/fiscal decision making and even objectives Behavior of Aid Over Medium Term. Aid Flows -Three Year Non-Overlapping Average 30 Aid Flows as Percentage of GDP 25 Ethiopia Ghana Malawi Mozambique Tanzania Uganda 20 15 10 5 0 1990-92 1993-95 1996-98 Period 1999-01 2002-04 Behavior of Aid Over Medium Term - Longer Series. Aid Flows - Thre Year Non-Overlapping Averages. 25 Three Year Average 20 Ethiopia Ghana Malawi Mozambique Tanzania Uganda 15 10 5 0 1975-77 1978-80 1981-83 1984-86 1987-89 1990-92 Period 1993-95 1996-98 1999-01 2002-04 How Many Reserves Do We Need To Smooth Aid Shocks? Reserve Adequacy 24 Average Reserve to GDP Ratio. 20 Broken line shows the reserves needed to cover the bottom 10 percentile of negative Aid shocks. Actual Reserves to GDP Ratio (2003-06) 17.7 17.4 18 16.8 16 12 11.3 8 4.4 4 0 Ethiopia Ghana Malawi Mozambique Country Tanzania Uganda Country Specific Reserves. Largest Negative Aid Shock Since 1990. Negative Aid Shock as Percentage of GDP. 25 Size of the Largest Negative Aid Shock Actual Reserves to GDP Ratio (2003-06) 20 15 10 5 0 Ethiopia Ghana Malawi Mozambique Country Tanzania Uganda Long-run predictability Irreducible and large uncertainty Donors? Recipient reactions Smoothing infeasible and expensive Aid-led strategy is fundamentally risky Malawi fertilizer subsidy Final provocations/thoughts Countries should figure out how to live with aid volatility Vertical funds have merits Notion of aid/policy interaction may be harmful as well as a bit flimsy “We” should be prepared to support alternative/nonaid-led strategies too We don’t pay enough attention to private capital flows: aid shocks seem to result in comparable private outflows on impact.