44
1 MIGUEL A. KIGUEL – JAVIER OKSENIUK September 2009 2010 Latin America and the Caribbean Regional Flagship Commodity Prices and Exchange Rate Policies During the Recent Boom and Bust in Latin America and the Caribbean

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Page 1: Commodity Prices and Exchange Rate Policies During the ...siteresources.worldbank.org/EXTLACOFFICEOFCE/Resources/870892... · Commodity Prices and Exchange Rate Policies During the

1

MIGUEL A. KIGUEL – JAVIER OKSENIUK

September 2009

2010 Latin America and the Caribbean Regional Flagship

Commodity Prices and Exchange Rate Policies During the Recent Boom and Bust

in Latin America and the Caribbean

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2

Motivation and Purpose of the Paper

Analytical Framework

Methodology

Stylized facts of the last cycle

Commodity prices and agflation

Macroeconomic effects of the last cycle and policy responses

Final remarks and conclusions

Outline

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3

Commodity swings as a challenge for monetary and exchange rate policies in developing countries

Motivation and Purpose of the Paper

Terms of Trade Shocks in Previous Episodesas % of GDP

1974 1979-81 2004-07Argentina -0.9 -1 5.8%Brasil -2.6 -3 5.0%Chile -12.4 -5 49.9%Colombia 0.9 -3.1 7.8%Costa Rica -5.1 -4.3 -11.9%Indonesia 17 11.9 naNigeria 23.1 14.3 na

Source: Cooper (1993) and own calculations

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Commodity swings as a challenge for monetary and exchange rate policies in developing countries

Motivation and Purpose of the Paper

Terms of Trade Shocks and Real Exchange Rate Movements

1974-78 2004-07 1974 2004-07Indonesia -33% n.a. 17% n.a.Nigeria -29% n.a. 23% n.a.Venezuela n.a. -47.8% 52%Chile n.a. -37.7% 50%Bolivia n.a. -18.3% 22%Panama n.a. -9% -14%Honduras n.a. -19% -24%Nicaragua n.a. -15% -27%

Source: Cooper (1993), Alan H. Gelb 1988, and own calculations

Real Exchange Rate Variation Terms of Trade Shock

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Motivation and Purpose of the Paper

Try to asses the effectiveness of different exchange rate regimes and of alternative policy measures (such as fiscal policy and capital controls) to deal with terms of trade shocks:

Degree of appreciation of the currency for those countries that benefited from a positive terms of trade shock

The impact of the increase in food prices (agflation) and of overall inflation during commodity booms on the economy

Effectiveness of different exchange rate systems to buffer the negative impact of the commodity booms as well as to cope with a possible reversal of a commodity boom

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Motivation and Purpose of the Paper

Analytical Framework

Methodology

Stylized facts of the last cycle

Commodity prices and agflation

Macroeconomic effects of the last cycle and policy responses

Final remarks and conclusions

Outline

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Analytical Framework

We consider a simple analytical framework based in the Salter-Swan model with 3 goods Non-traded good (N)

Tradeable good (T)

Commodity (C)

Nominal income is defined as:

ccttnnn XPXPXPY ++=

And prices as:

*. tt PEP = *. cc PEP =

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Analytical Framework The consumption of the non-tradeable (Cn) and of the tradeable (Ct ) good depend on relative prices and on the level of aggregate demand:

= α.AD , C

t

nnn P

PC

= AD

PPC

t

ntt . α)-(1 , C

We assume that AD, aggregate demand, is a function of nominal disposable income (Yn) and the fiscal surplus, where Yn is defined as:

ccnnttn YPYPYPY ... ++=

The Current Account (in foreign currency) is:

ccttt XPCYP .)(CA ** += −

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Analytical FrameworkEquilibrium in the non-tradeable good and in the current

account of the balance of payments

Real Exchange

Rate

Aggregate Demand

AD0 AD1

NN

XX

R0

R1

An increase in Commodity Prices (Pc) generates a real appreciation

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Motivation and Purpose of the Paper

Analytical Framework

Methodology

Stylized facts of the last cycle

Commodity prices and agflation

Macroeconomic effects of the last cycle and policy responses

Final remarks and conclusions

Outline

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Methodology

Our methodology to define the exchange rate regime is based on Levy-Yeyati and Sturzenegger (2005).

They divide the countries in 3 groups, based on 3 variables:

Exhange Rate Volatility

Volatility of Exchange Rate Changes

Volatility of International Reserves

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MethodologyWe classify the countries in 3 groups:

Previous Exchange Rate Regime Classification and Nominal Excahge Rate (Jan04=100)

Dic-04 Dic-05 Dic-06 Dic-07 Dic-08 Jul-09Hard PegEcuador 100.0 100.0 100.0 100.0 99.6 99.6

El Salvador 100.0 100.0 100.0 100.0 100.0 100.0Panama 100.0 100.0 100.0 100.0 100.0 100.0

IntermediateArgentina 101.5 103.6 104.5 107.7 118.0 130.8

Bolivia 102.1 101.2 101.1 95.9 88.9 88.7Costa Rica 108.7 117.7 122.9 117.7 132.4 138.8Honduras 104.6 106.1 106.1 106.1 106.1 106.1Nicaragua 104.4 106.1 115.4 121.1 127.3 127.9Venezuela 120.0 134.4 134.4 134.4 134.4 134.4Floaters

Brasil 90.5 79.6 72.8 60.6 78.8 63.5Chile 95.1 88.0 91.1 85.2 108.8 92.5

Colombia 85.8 83.5 81.7 73.7 82.0 74.3Dominican Rep 57.5 68.0 66.2 66.6 70.9 72.6

Guatemala 95.3 93.4 93.9 94.0 95.4 100.3Jamaica 101.4 106.4 110.7 117.4 131.5 146.3Mexico 100.6 96.1 97.6 98.5 123.4 119.1

Paraguay 98.5 97.9 83.0 76.4 78.3 80.1Peru 93.6 97.7 91.3 85.7 89.5 85.3

Uruguay 91.1 83.3 83.9 74.1 83.8 80.3

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MethodologyNER volatility was naturally higher in flexible regimes and the

intermediates had a higher level of intervention than the floaters through most of the period

0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

3.00%

3.50%

4.00%

Ene-

05

May

-05

Sep-

05

Ene-

06

May

-06

Sep-

06

Ene-

07

May

-07

Sep-

07

Ene-

08

May

-08

Sep-

08

Ene-

09

May

-09

Hard PegIntermFloaters

NER Volatility

0.0%

0.1%

0.2%

0.3%

0.4%

0.5%

0.6%

0.7%

0.8%

0.9%

Ene-

05

May

-05

Sep-

05

Ene-

06

May

-06

Sep-

06

Ene-

07

May

-07

Sep-

07

Ene-

08

May

-08

Sep-

08

Ene-

09

May

-09

Hard PegIntermFloaters

IR Variation in absolute value

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Methodology

We summarize the evolution of the three variables to classify exchange rate regimes. We use a slightly different methodology to LY-S (2005). We compute a simple and ad hoc formula that assigns a value for each of the three variables in order to consolidate these trends into a single one.

Our formula indicates that in periods when countries were facing a stress scenario like an adverse shock in the terms of trade, floaters were maintained their the de facto regime that was in place prior to that date. It thus seems that floaters were really floaters, while intermediates turned, on average, into a more fixed scheme.

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MethodologyNo group of countries has crossed over, on average, the others,

indicating some kind of regularity of the regimes.

-2.00%

-1.50%

-1.00%

-0.50%

0.00%

0.50%

1.00%

Ene-

05

May

-05

Sep-

05

Ene-

06

May

-06

Sep-

06

Ene-

07

May

-07

Sep-

07

Ene-

08

May

-08

Sep-

08

Ene-

09

Hard PegIntermFloaters

Regime Formula A - with absolute values

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Motivation and Purpose of the Paper

Analytical Framework

Methodology

Stylized facts of the last cycle

Commodity prices and agflation

Macroeconomic effects of the last cycle and policy responses

Final remarks and conclusions

Outline

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Stylized facts of the last cycle Winners and Loser in the last Commodity boom

Terms of Trade Shockas % of GDP, cumulative shock between 2003 and 2007

Venezuela 52.3%Chile 49.9%Bolivia 22.2%Peru 17.1%Ecuador 14.5%Colombia 7.8%Argentina 5.8%Brasil 5.0%Mexico 3.7%Paraguay -6.5%Uruguay -9.6%Dominican Republic -9.9%El Salvador -10.5%Costa Rica -11.9%Guatemala -13.6%Panama -14.4%Honduras -24.1%Nicaragua -26.6%

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Stylized facts of the last cycle Regardless of the difference in the evolution of the terms of

trade, there were some common features regarding macroeconomic variables among countries, that to a large

extent can be attributed to a favorable external environment Real GDP Growth

Annual variation

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

5.0%

5.5%

6.0%

6.5%

Hard Peg Intermediate Floaters

2004 2005 2006 2007

Current Accountas % of GDP

-5%

-4%

-3%

-2%

-1%

0%

1%

2%

Hard Peg Intermediate Floaters

2004 2005 2006 2007

Sovereign Interest RatesEMBI Index, in basis points

0

100

200

300

400

500

600

700

800

900

1000

Hard Peg Intermediate Floaters

2004 20052006 2007

International Reservesas % of GDP

5%

7%

9%

11%

13%

15%

17%

19%

21%

23%

Hard Peg Intermediate Floaters

2004 2005 2006 2007

Foreign Direct Investmentas % of GDP

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

5.0%

5.5%

6.0%

Hard Peg Intermediate Floaters

2004 2005 2006 2007

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Stylized facts of the last cycle The three groups of countries experienced a real appreciation of the currency, suggesting that there were common features

pushing towards stronger currencies

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Stylized facts of the last cycle Real appreciation mainly took place through nominal

appreciations in the floaters and trough inflation in hard peg and intermediates

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Stylized facts of the last cycle Floaters used monetary policy (high interest rates) to target low rates of inflation while intermediates and hard pegs use

NER as the nominal anchor

Real Interest RateIn percentage points

-6%

-4%

-2%

0%

2%

4%

6%Q

1 20

04

Q3

2004

Q1

2005

Q3

2005

Q1

2006

Q3

2006

Q1

2007

Q3

2007

Q1

2008

Q3

2008

Floaters

Intermediate

Hard Peg

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22

Stylized facts of the last cycle

Factors that could have contributed to the real appreciation in this period:

Terms of trade gains

Capital flows

Expansions in domestic bank credit

Fiscal policy

Higher real interest rates

Improvements in macro-fundamentals

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23

Stylized facts of the last cycle There is evidence that the extent of the real appreciation was

related to the size of the terms of trade gains

Terms of Trade Gains vs. Real Exchange Rate

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

-15%

-10% -5% 0% 5% 10%

15%

20%

Terms of Trade Gains as % of GDP

Rea

l Exc

hang

e R

ate

2003

=1

Hard Peg

Intermediate

Floaters

Terms of Trade Gains vs. Real Exchange Rate(cumulative gains and REER variation, 2004-07 )

Uru

Per

Par

Mex

Gtm Dr

Col

Chi

Bra

Ven

Nic

Hon

Cri

Bol

Arg

Pan

Slv

Ecu

-65%

-55%

-45%

-35%

-25%

-15%

-5%

-40%

-30%

-20%

-10% 0% 10%

20%

30%

40%

50%

60%

Terms of Trade Gains as % of GDP

Rea

l Exc

hang

e R

ate

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24

Stylized facts of the last cycle The role of capital inflows

Capital Account Variation As % of GDP

-4%

-3%

-2%

-1%

0%

1%

2%

3%

4%

5%

6%

Hard Peg Intermediate Floaters

2004-07 vs. 20032S.08-1Q.09 vs. 2007

Capital flows increased besides the exchange rate regime and whether the countries were winners or losers in terms of the commodity boom

The reversal was also “commodity blind”

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Stylized facts of the last cycle Were capital flows pro-cyclical (correlated with the commodity

cycle) during the boom?

Terms of Trade Shock vs. Cap. Account Variation2007 vs. 2003, as % of GDP

-40%-30%-20%

-10%0%

10%20%30%

40%50%60%

Arg

enti

na

Bol

ivia

Cost

aR

ica

Hon

dura

s

Nic

arag

ua

Vene

zuel

a

ToT Shock Capital Account Variation

Terms of Trade Shock vs. Cap. Account Variationas % of GDP

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

Bra

sil

Chile

Colo

mbi

a

Dom

inic

anR

ep

Gua

tem

ala

Mex

ico

Para

guay

Peru

Uru

guay

ToT Shock Capital Account Variation

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Stylized facts of the last cycle And during the bust?

Terms of Trade Shock vs. Cap. Account Variation2S.08/1Q09 vs. 2007, as % of GDP

-15%

-10%

-5%

0%

5%

10%

15%

Arg

enti

na

Bol

ivia

Nic

arag

ua

Vene

zuel

a

Bra

sil

Chile

Gua

tem

ala

Mex

ico

Peru

ToT Shock Capital Account Variation

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27

Stylized facts of the last cycle The evidence is mixed: multiple factors were playing in

different senses

Capital Flows vs. REER(cumulative 2004-07 gains and REER variation)

-60%

-50%

-40%

-30%

-20%

-10%

0%

-20%

-10% 0% 10%

20%

30%

40%

Capital Account variation vs. 2003 as % of GDP

Rea

l Exc

hang

e R

ate

2003

=1

Capital Account vs. Real Exchange Rate

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

-10% -5% 0% 5% 10%

15%

20%

Capital Account Variation vs. 2003

Rea

l Exc

hang

e R

ate

2003

=1

Hard Peg

Intermediate

Floaters

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Stylized facts of the last cycle What about the “total effect”?

CA Variation and ToT Shock vs. RER2003-2007

0.5

0.6

0.7

0.8

0.9

1.0

1.1

-15%

-10% -5% 0% 5% 10%

15%

20%

Terms of Trade Gains and CA Variation as % of GDP vis-a-vis 2003

Rea

l Exc

hang

e R

ate

2003

=1

CA Variation and ToT Shock vs. RER(cumulative 2004-07 gains and REER variation)

Uru

Per

Par

Mex Jam

Gua Dr

Col

Chi

Bra

Ven

Nic

Hon

Cri

Bol

Arg

Pan

SlvEcu

-60%

-50%

-40%

-30%

-20%

-10%

0%

-40%

-30%

-20%

-10% 0% 10%

20%

30%

40%

50%

Terms of Trade Gains and CA Variation as % of GDP vis-a-vis 2003

Rea

l Exc

hang

e R

ate

2003

=1

There is evidence of a negative correlation between the total foreign exchange flows and the real exchange rate

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Stylized facts of the last cycle Where aggregate demand policies also expansionary?

Credit to the Private Sectoras % of GDP

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

Hard Peg Intermediate Floaters

2004 2005 2006 2007

Credit to Private Sector vs. Real Exchange Rate

Uru

Per

Par

Mex Jam

Gtm Dr

Col

Chi

Bra

Ven

Nic Hon

Cri

Bol

Arg

Pan

SlvEcu

-60%

-50%

-40%

-30%

-20%

-10%

0%

-50% 0% 50%

100%

150%

200%

Credit to the Private Sector as % of GDP variation between 2003 and 2007

Rea

l Exc

hang

e R

ate

varia

tion

betw

een

2003

and

200

7

There is a negative relationship between the growth in domestic credit during this period and the real exchange rate

This could have been one additional factor underlying the real appreciation of the currency.

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30

Stylized facts of the last cycle Where aggregate demand policies also expansionary?

The degree of prudence in fiscal management was not related with the exchange rate regime

Fiscal Accounts Primary Expenditures - Primary Balance as % of GDP,

cumulative between 2007/8 and 2003

-5%-3%-1%1%3%5%7%9%

11%13%15%

Chile

Bol

ivia

El S

alva

dor

Peru

Para

guay

Gua

tem

ala

Uru

guay

Pana

ma

Hon

dura

sCo

lom

bia

Cost

a R

ica

Vene

zuel

aA

rgen

tina

Dom

inic

anN

icar

agua

Mex

ico

Bra

sil

Ecua

dor

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31

Stylized facts of the last cycle Did the exchange rate made a difference?

Real Exchange Rate and Exchange Rate Regime

Dependant variable: Real Exchange Rate (Index number, 2003=100)Method: Random Effects GLS Panel Regression

Float Regime Dummy Variable -0.158***(0.034)

Terms of Trade Gains as % of GDP -0.356*and Capital Account variation vs. 2003 (0.240)

Credit as % of GDP -0.002***(0.000)

Note: Standard Error in parenthesis. *Significant at 15%, **Significant at 5%, ***Significant at 1%.

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Motivation and Purpose of the Paper

Analytical Framework

Methodology

Stylized facts of the last cycle

Commodity prices and agflation

Macroeconomic effects of the last cycle and policy responses

Final remarks and conclusions

Outline

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33

Commodity prices and agflationThere is a strong and possitive correlation between overall CPI

inflation and food inflation

Correlation between CPI and Food Inflation 4 quarters as of IIQ2008

UruPer

Par

Mex

GuaDom

Col

Chi

Bra

Ven

Nic

Hon CRi

Bol

Arg

Pan

SalEcu

0%

5%

10%

15%

20%

25%

30%

35%

0% 10% 20% 30% 40% 50% 60%

Food inflation

CPI

infla

tion

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34

Commodity prices and agflationThere is now correlation between ToT shock and CPI, meaning that the income effect of the shock was not important in terms

of aggregate demand

Correlation between ToT shock and CPI Inflation 4 quarters as of IIQ2008

-2%

0%

2%

4%

6%

8%

10%

12%

14%

-20% -10% 0% 10% 20%

ToT shock IIIQ07-IIQ08

Chan

ge in

CPI

infla

tion

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35

Commodity prices and agflationThere is evidence that the de facto exchange rate regime was

important on the inflation rate

Correlation between Regime and CPI inflation4 quarters as of IIQ2008

Uru

PerPar

Mex

Jam

GuaDom

Col

Chi

Bra

VenNic

Hon

CRi

BolArg

Pan

Sal

Ecu

-2%

0%

2%

4%

6%

8%

10%

12%

14%

16%

-2.5% -2.0% -1.5% -1.0% -0.5% 0.0% 0.5% 1.0%

Regime Formula A

Chan

ge in

infla

tion

IIQ

07-

IIQ

08

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36

Commodity prices and agflationThe econometric analysis confirms that the exchange rate

regime did have an effect on inflation

Agflation and Exhange Rate RegimeDependant variable: Inflation (annual variation of CPI)Method: Fixed Effects Panel Data

Regime Formula 1.295**(0.656)

Terms of Trade Gains as % of GDP -0.027(0.152)

Agriculture Commodity Prices 0.560***(0.718)

Note: Std error in parenthesis. **Significant at 5%, ***Significant at 1%.

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Motivation and Purpose of the Paper

Analytical Framework

Methodology

Stylized facts of the last cycle

Commodity prices and agflation

Macroeconomic effects of the last cycle and policy responses

Final remarks and conclusions

Outline

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Effects of the last cycle and policy responses

The global financial crisis, which led to a reversal in the terms of trade and large capital outflows, represented a new policy challenge

In the first phase of the crisis (before Lehman), commodity prices were still high, and LAC countries were doing well and were still fighting inflation with high interest rates

After Lehman, the entire global financial system collapse and the crisis hit commodity prices and LAC economic activity. Some LAC countries had room to run countercyclical fiscal and monetary policy

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Effects of the last cycle and policy responses

Regarding monetary policy, the exchange rate regime made a difference: Floaters allowed the exchange rate to depreciate because the capital outflows and sharp decrease in commodity prices. This depreciations did not have an impact on inflation.

Formal inflation targeters with almost pure free-floating regimes (Brazil, Chile, Colombia, Mexico and Peru) put the tightening cycle on hold during the last months of 2008 and they started cutting the policy rates in January 2009 to fight the economic downturn and help financial stability

The hard pegs could not and did not use monetary policy during the crisis, as the economies were fully dollarized

Intermediate regimes adopted a policy of “controlled” depreciation of their currencies during the crisis, but were forced to allow increases in domestic nominal interest rates to sustain the demand for domestic currency

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Effects of the last cycle and policy responsesCommodity bust and monetary policy

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Motivation and Purpose of the Paper

Analytical Framework

Methodology

Stylized facts of the last cycle

Commodity prices and agflation

Macroeconomic effects of the last cycle and policy responses

Final remarks and conclusions

Outline

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There is evidence that countries in the region experienced the so called “Dutch disease”

The exchange rate system made a difference for the adjustment process:

Final remarks and conclusions

Countries with floating exchange rate systems experienced more real appreciation during the boom years than those that had hard pegs or intermediate regimes

Countries with managed floats suffered more inflation

During the reversal, the floaters were able to adjust RER much faster (there was also some overshooting of the NER) and to sharply reduce nominal interest rates

Countries with less flexible regimes were not able to reduce interest rates and some of them were forced to increase rates to limit capital outflows

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The evidence suggests that the regime also made a difference regarding agflation:

Final remarks and conclusions

Countries with floating regimes were more successful in limiting the impact of the rise in commodity prices, as they compensated the increase in international prices through nominal appreciaton of their currencies

In sum: In this period more exchange rate flexibility implied less inflation during the boom years, more capacity to run countercyclical monetary policy but also much more volatility in the real exchange and a much faster transmission from commodity prices to Dutch disease

The intermediate regimes responded more slowly to the pressures on relative prices and hence the could smooth the real appreciations that took place primarily through inflation, and hence required a smaller “swing” when the cycle changed from boom to bust.

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Can Fiscal Policy be used to avoid the “Dutch Disease”?

Final remarks and conclusions

In emerging market countries a countercyclical fiscal stance could in the end become a pro-cyclical policy

Larger fiscal surplus that is intended to reduce aggregate demand could induced capital inflows which offset the fiscal adjustment

Are there any options?

Commodity stabilization funds Could be hard to implement (complex policy issues)

Foreign exchange or capital controls