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