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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.
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The Macroeconomic Challenge of Aid Volatility
African DepartmentInternational Monetary Fund
Andrew BergCalvin McDonald
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 betterBut move to budget support can make problem more acute.
Recipients should be able to smoothIMF programs have come a ways on thisEven if IMF programs allow through adjusters, headline domestic borrowing and deficit targets can go awry.
Medium-run predictability: problems
Again, lots of volatilityFirst 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 sectorMakes 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?
RecipientsCreate good MTEFs, scaling up scenariosSmooth aid
How many reserves do you need, and how costly? Many countries have enough
Surprisingly hard to do.Complications of exchange rate managementSeparate central bank/fiscal decision making and even objectives
Behavior of Aid Over Medium Term.
Aid Flows -Three Year Non-Overlapping Average
0
5
10
15
20
25
30
1990-92 1993-95 1996-98 1999-01 2002-04
Period
Aid
Flo
ws
as P
erce
ntag
e of
GD
P
Ethiopia Ghana
Malawi Mozambique
Tanzania Uganda
Behavior of Aid Over Medium Term
- Longer Series.Aid Flows - Thre Year Non-Overlapping Averages.
0
5
10
15
20
25
1975-77 1978-80 1981-83 1984-86 1987-89 1990-92 1993-95 1996-98 1999-01 2002-04Period
Thr
ee Y
ear
Ave
rage
Ethiopia Ghana
Malawi Mozambique
Tanzania Uganda
How Many Reserves Do We Need To Smooth Aid Shocks?
Reserve Adequacy
11.3
17.7
4.4
17.4 1816.8
0
4
8
12
16
20
24
Ethiopia Ghana Malawi Mozambique Tanzania Uganda
Country
Ave
rage
Res
erve
to G
DP
Rat
io.
Actual Reserves to GDP Ratio (2003-06)Broken line shows the reserves needed to cover the bottom 10 percentile of negative Aid shocks.
Country Specific Reserves.Largest Negative Aid Shock Since 1990.
0
5
10
15
20
25
Ethiopia Ghana Malawi Mozambique Tanzania Uganda
Country
Neg
ativ
e A
id S
hock
as P
erce
ntag
e of
GD
P.
Size of the Largest Negative Aid ShockActual Reserves to GDP Ratio (2003-06)
Long-run predictability
Irreducible and large uncertainty
Donors?
Recipient reactionsSmoothing infeasible and expensiveAid-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/non-aid-led strategies too
We don’t pay enough attention to private capital flows: aid shocks seem to result in comparable private outflows on impact.
Donors?
Recipient reactionsSmoothing infeasible and expensiveAid-led strategy is fundamentally risky
Malawi fertilizer subsidy