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The inflation appreciation trade-off revisited The monetary management of the Zambian copper boom by Elva Bova PhD candidate SOAS, University of London,

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Presentation on theme: "The inflation appreciation trade-off revisited The monetary management of the Zambian copper boom by Elva Bova PhD candidate SOAS, University of London,"— Presentation transcript:

1 The inflation appreciation trade-off revisited The monetary management of the Zambian copper boom by Elva Bova PhD candidate SOAS, University of London, NCCR Trade Regulation, WTI, Berne

2 Introduction

3 Presentation outline Theoretical 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

4 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 link resource switching effect( e Pt/Pnt) spending effect flexible fixed nominal appreciation inflation (money-exchange channels)

5 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?

6 The copper boom in Zambia The copper boom The 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

7 The nominal appreciation Non Traditional Exports (NTEs) Source: Export board of Zambia

8 The nominal appreciation Sectors % change US$'000 % NTEs US$'000 % NTEs Engineering products96, %288, %199.31% Agriculture196, %176, %-10.19% Processed Refined Food66, %103, %54.74% Horticulture32, %17, %-44.42% Floriculture20, %23, %12.27% Textiles26, %19, %-27.30% Other manufactures22, %24, %10.34% Gemstones31, %18, %-40.86% Source: Export board of Zambia

9 Inflation Source: Bank of Zambia Two main channels from exchange rate management to inflation: Money supply channel Exchange rate channel

10 The model The 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 VAR Long run: Short run

11 Results and interpretations Food 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);

12 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.

13 Conclusions Thank you very much

14 The copper boom Source: IMF-IFS, Bank of Zambia

15 The Kwacha Source: IMF-IFS, Bank of Zambia

16 Headline CPI composition Composite Index Weights Food and Beverage Index57% Transport and Communication9.60% Rent, Fuel and Lighting8.50% Furniture and Household Goods8.20% Medical care8% Clothing and Footwear6.80% Recreation and Education4.90% All other goods and services4.10%

17 Residual analysis Multivariate tests Tests for Autocorrelation Ljung-Box(37): ChiSqr(560) = [0.000] LM(1): ChiSqr(16) = [0.001] LM(2): ChiSqr(16) = [0.295] Test for Normality: ChiSqr(8) = [0.061] Univariate Tests Std.Dev Skew. Kurtosis ARCH(2) Normality R-Squared M [0.256] [0.697] CPI f [0.692] [0.431] CPInf [0.155] [0.043] Ex [0.077] [0.088] 0.612

18 Trace test for number of cointegrating relations p-r r Eig.Value Trace Trace* Frac95 P-Value P-Value* Source: RATS estimation

19 Long run identification M3 CPI-f Ex CPI-nf COP T(2005:12) TREND Beta(1) (2.107) (.NA) (.NA) (.NA) ( ) (.NA) (-8.803) Beta(2) (.NA) (.NA) (6.010) (.NA) (.NA) (9.418) ( ) Beta(3) (4.632) (.NA) (.NA) (.NA) (.NA) (.NA) (.NA) TEST OF RESTRICTED MODEL: CHISQR(7) = 3.748[0.879] Source: RATS estimation

20 Short run identification M3 Ex CPIf CPInf Ex (0.0218) (0.0004) (0.0069) CPIf (0.0003)(0.0000) (0.0082) M (0.0001) ECM (0.0543) (0.0000) ECM (0.0000) ECM (0.0000) Dcop (0.0000) LR test of over-ident. restrictions:Chi^2(43)= [0.0613] Source: RATS estimation


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