The inflation appreciation trade-off revisited

The monetary management of the Zambian copper boom

by

Elva BovaPhD candidateSOAS, University of London,NCCR Trade Regulation, WTI, Berne

Email: eb29@soas.ac.uk

Introduction

Presentation outlineTheoretical framework:

exchange rate management and the RER

The nominal appreciation of the Kwacha:

impact on non traditional exports

Inflation, food and non food: Cointegrated VAR for exchange and money channel

Results and policy implications

Theoretical framework: the trade off

Further to a commodity boom the economy is exposed to the risk of a RER appreciation:

Dutch disease (Pt/Pnt) Money inflation linkresource switching effect (e Pt/Pnt)spending effect

flexible fixednominal appreciation inflation

(money-exchange channels)

Theor.framework: the trade-off revisited

Neutrality argument: the real exchange rate (Pt/Pnt) appreciates under the two regimes

Hypothesis: RER not neutral to the exchange rate regime.

-food component in CPI

-economy operates not at full employment, yet absorptive capacity is limited

How to maintain export competitiveness in an inflation stabilising monetary framework?

The copper boom in ZambiaThe copper boomThe increase in export receipts, Debt relief at the end of 2005 and

a surge in foreign capital put pressure on the Zambian Kwacha.

Monetary framework: Monetary targeting (M3, reserve money) with price stability as the main objective for monetary policy. Flexible exchange rate (IMF managed float) with interventions mainly aimed at smoothing volatility.

The Kwacha appreciation

The nominal appreciation

Non Traditional Exports (NTEs)

Zambian exports 2000-2007

010002000300040005000

2000 2001 2002 2003 2004 2005 2006 2007

US$

Mill

ions

Metals Total Non Metals CIF

Source: Export board of Zambia

The nominal appreciation

Sectors

2005-06 2006-07% change 05-07

US$'000%

NTEs US$'000%

NTEs

Engineering products 96,419 17.07% 288,592. 38.11% 199.31%

Agriculture 196,975 34.85% 176,913 23.36% -10.19%

Processed Refined Food 66,933 11.83% 103,573 13.68% 54.74%

Horticulture 32,094 5.67% 17,839 2.36% -44.42%

Floriculture 20,507 3.63% 23,024 3.04% 12.27%

Textiles 26,937 4.76% 19,583 2.59% -27.30%

Other manufactures 22,216 3.39% 24,512 3.24% 10.34%

Gemstones 31,607 5.59% 18,694 2.47% -40.86%

Source: Export board of Zambia

Inflation

Source: Bank of Zambia

Two main channels from exchange rate management to inflation:Money supply channelExchange rate channel

Inflation (2000-2008)

0.05.0

10.015.020.025.030.035.040.0

Jan-

00

Jul-

00

Jan-

01

Jul-

01

Jan-

02

Jul-

02

Jan-

03

Jul-

03

Jan-

04

Jul-

04

Jan-

05

Jul-

05

Jan-

06

Jul-

06

Jan-

07

Jul-

07

Jan-

08

Food inflation Non food inflation Headline inflation

The modelThe unrestricted VAR:

Xt = ΠXt-1 + Φ1 Dtt + μ1 t + μ0 + εt εt ~ Np (0, Σ), t=1,….., T

Variables: M3 = log M3sea – log CPIz, Ex = log CPIz – log CPIus –NEus-z CPI f, CPI nf

Exog.: real copper price, real oil price*

Residual Analysis Identification of the cointegrated VARLong run: Short run

Results and interpretationsFood inflation:

not significantly related to money supply (or copper price); long run relationship with the exchange rate;

in the short run adjusts more to its previous values (0.52) than with respect to deviations from its equilibrium with exchange rate (0.17).

Non food inflation: significant long run relationship with money supply, not with the exchange rate;it adjusts rapidly to deviations from its equilibrium with money supply;

The exchange rate:related in the long run with money supply and the price of copper (commodity currency hypothesis);

Conclusions

Under the flexible exchange rate regime with a monetary target and price stability as overriding objective, the Zambian Kwacha has appreciated in nominal terms (2005, 2007).

The nominal appreciation (2005) has fed into a real appreciation with deterioration of some non traditional exports: tobacco, cotton, coffee and horticulture, with increase in unemployment and possible rural-urban bias.

Had Bank of Zambia managed more the exchange rate, inflation would have increased but not that much more likely through the exchange rate channel, since the money channel is only valid for non food prices, which comprise 30% of total headline CPI.

Conclusions

Thank you very much

The copper boomCopper prices

0

2000

4000

6000

8000

10000

1957

m01

1960

m04

1963

m07

1966

m10

1970

m01

1973

m04

1976

m07

1979

m10

1983

m01

1986

m04

1989

m07

1992

m10

1996

m01

1999

m04

2002

m07

2005

m10

US

$ pe

r m

etri

c to

n

0

20

40

60

80

100

120

Nominal price lft-scale Real price rgt-scale

Copper price and exports in Zambia

0

10,000

20,000

30,000

40,000

50,000

60,000

Jan-

95

Jan-

96

Jan-

97

Jan-

98

Jan-

99

Jan-

00

Jan-

01

Jan-

02

Jan-

03

Jan-

04

Jan-

05

Jan-

06

Jan-

07

Met

ric to

nnes

0

100

200

300

400

500

copper exports (volume) lft-scale copper price (index) rgt-scale

Source: IMF-IFS, Bank of Zambia

The KwachaThe appreciation of the Kwacha

0100020003000400050006000

1990

m01

1991

m03

1992

m05

1993

m07

1994

m09

1995

m11

1997

m01

1998

m03

1999

m05

2000

m07

2001

m09

2002

m11

2004

m01

2005

m03

2006

m05

2007

m07

Kwac

ha p

er U

S$

0

20

40

60

80

Nominal exchange rate Real copper price

Foreign exchange intervention (net purchases)

-30.000-20.000-10.000

0.00010.00020.00030.00040.000

07/0

1/00

07/1

1/00

07/0

9/01

07/0

7/02

07/0

5/03

07/0

3/04

07/0

1/05

07/1

1/05

07/0

9/06

07/0

7/07

US $

Mill

ion

0100020003000400050006000

2000

m01

2000

m11

2001

m09

2002

m07

2003

m05

2004

m03

2005

m01

2005

m11

2006

m09

2007

m07

ZMK-

US$

Forex lft-scale NE rgt-scale

Source: IMF-IFS, Bank of Zambia

Headline CPI composition

Composite Index WeightsFood and Beverage Index 57%

Transport and Communication 9.60%

Rent, Fuel and Lighting 8.50%

Furniture and Household Goods 8.20%

Medical care 8%

Clothing and Footwear 6.80%

Recreation and Education 4.90%

All other goods and services 4.10%

Residual analysisMultivariate tests

Tests for Autocorrelation Ljung-Box(37): ChiSqr(560) = 674.636 [0.000] LM(1): ChiSqr(16) = 39.811 [0.001] LM(2): ChiSqr(16) = 18.501 [0.295]

Test for Normality: ChiSqr(8) = 14.927 [0.061]

Univariate Tests

Std.Dev Skew. Kurtosis ARCH(2) Normality R-SquaredM3 0.021 -0.097 3.111 2.727 [0.256] 0.721 [0.697] 0.510CPI f 0.009 0.241 2.823 0.735 [0.692] 1.684 [0.431] 0.755CPInf 0.006 0.434 2.853 3.735 [0.155] 6.306 [0.043] 0.735Ex 0.024 -0.101 3.720 5.131 [0.077] 4.872 [0.088] 0.612

Trace test for number of cointegrating relations

p-r r Eig.Value Trace Trace* Frac95 P-Value P-Value*4 0 0.506 191.011 181.954 63.659 0.000 0.0003 1 0.279 90.130 86.714 42.770 0.000 0.0002 2 0.204 43.341 41.043 25.731 0.000 0.0001 3 0.072 10.671 10.052 12.448 0.101 0.127

Trace Test Statistics

The test statistics are scaled by the 5% critical values of the `Basic Model'

2000 2001 2002 2003 2004 2005 2006 2007 20080.0

0.4

0.8

1.2

1.6

2.0

2.4

2.8X(t)

H(0)|H(4) H(1)|H(4) H(2)|H(4) H(3)|H(4)

2000 2001 2002 2003 2004 2005 2006 2007 20080.0

0.5

1.0

1.5

2.0

2.5R1(t)

Source: RATS estimation

Long run identification

M3 CPI-f Ex CPI-nf COP T(2005:12) TREND

Beta(1) 0.225 0.000 1.000 0.000 -0.377 0.000 -0.007

(2.107) (.NA) (.NA) (.NA) (-12.009) (.NA) (-8.803)

Beta(2) 0.000 1.000 0.195 0.000 0.000 0.009 -0.016

(.NA) (.NA) (6.010) (.NA) (.NA) (9.418) (-119.363)

Beta(3) 0.020 0.000 0.000 1.000 0.000 0.000 0.000

(4.632) (.NA) (.NA) (.NA) (.NA) (.NA) (.NA)

TEST OF RESTRICTED MODEL: CHISQR(7) = 3.748[0.879]

Source: RATS estimation

Short run identification M3 Ex CPIf CPInf

Ex-1 0.1550 0.2492 -0.0514 (0.0218) (0.0004) (0.0069)

CPIf-1 -0.5693 0.5172 0.1163 (0.0003) (0.0000) (0.0082)M3-1 -0.2938

(0.0001)ECM1-1 -0.0670 -0.1688

(0.0543) (0.0000)ECM2-1 -0.1696

(0.0000)ECM3-1 -0.7982

(0.0000)Dcop 0.1469

(0.0000)

LR test of over-ident. restrictions:Chi^2(43)=61.645 [0.0613]

Source: RATS estimation