Understanding The Empirics Of Financial Volatility

Understanding The Empirics Of Financial Volatility

Outline

• Volatility is big• Volatility is bad• Volatility in a neo-classical setting• What may be missing?• Alternative explanations

What is Volatility ?

• Instability

• Uncertainty

How to measure volatility?• Level vs. rate of change

– GDP vs. GDP growth– RER vs. RER change

• Actual change vs. “unexpected change”– Trend, AR(1), model– E.g. the case of RER

• Alternative measurements– Standard deviation of level– Standard deviation of rate of change– Standard deviation of deviations from trend or fitted values– Standard error of the equation– Other dimensions of “deviation”

• Mean vs. median when doing international comparisons• Mean reversion and the role of frequency

Volatility is bigStandard Deviation of Latin America Industrialized East Asian

Countries Miracles

Macroeconomic Outcomes

Real GDP growth 4.2 2.2 3.1Consumption Growth 5.6 2.1 4.1Change in RER 13.4 4.8 6.2Inflation Rate 463.5 3.9 6.2

Policy

Fiscal Deficit (%GDP) 4.7 2.4 2.4Monetary Growth 211.1 5.6 13.6

External Shocks

Terms of Trade Change 15.1 8.9 8.0Int’l Capital Flows (%GDP) 2.8 1.7 1.5

time

ln(G

DP

W)

Crisis 1Crisis 2

Figure 2: Graphical example of crisis definition

Crises in developing countries are nastier

Table 2: Summary Statistics of Crises by Region

Number of Observations Mean

Standard Deviation Minimum

25th percentile Median

75th percentile Maximum

Duration of CrisisAfrica 151 8.14 10.09 1 1 3 13 43Asia 42 4.79 5.71 1 1 2 7 24Central and Eastern Europe 34 9.74 6.38 1 1 12.5 15 19East Asia and Pacific 46 3.78 4.23 1 1 2 5 20Industrialized 90 2.52 2.88 1 1 2 3 19Latin America and Caribbean 109 6.88 8.92 1 1 3 7 34Middle East and North Africa 63 5.13 7.56 1 1 2 4 27Total 535 6.05 8.02 1 1 2 7 43Peak to ThroughAfrica 151 0.13 0.16 0.00 0.02 0.06 0.19 0.95Asia 42 0.08 0.12 0.00 0.02 0.04 0.08 0.52Central and Eastern Europe 34 0.29 0.24 0.00 0.06 0.29 0.45 0.77East Asia and Pacific 46 0.08 0.08 0.00 0.02 0.05 0.11 0.35Industrialized 90 0.02 0.03 0.00 0.01 0.01 0.03 0.13Latin America and Caribbean 109 0.10 0.13 0.00 0.01 0.05 0.15 0.62Middle East and North Africa 63 0.12 0.20 0.00 0.01 0.04 0.12 0.91Total 535 0.11 0.16 0.00 0.01 0.04 0.13 0.95Product-Years lost (Integral)Africa 151 1.42 2.94 0.00 0.02 0.10 0.93 16.40Asia 42 0.51 1.16 0.00 0.02 0.07 0.26 5.51Central and Eastern Europe 34 2.71 2.81 0.00 0.06 2.15 4.03 9.79East Asia and Pacific 46 0.31 0.54 0.00 0.02 0.07 0.26 2.46Industrialized 90 0.07 0.16 0.00 0.01 0.02 0.06 1.16Latin America and Caribbean 109 1.05 2.35 0.00 0.01 0.06 0.62 13.78Middle East and North Africa 63 1.16 2.88 0.00 0.01 0.06 0.20 12.73Total 535 1.00 2.36 0.00 0.01 0.06 0.44 16.40

The real exchange rate is much more volatile at 1 & 5-year horizons

1YR

Volatility

5YRS

Volatility

Developing 1.292 1.283

Industrial 0.506 0.513

Difference 0.786 0.770

t-statistic 4.262 4.818

P (Dev > Ind) 1.000 1.000

Industrialized countries Developing countries

Volatility of Real Exchange rate over 5-year periodsN

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Bur

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Zam

bia Rom

ania

Bol

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Nig

eria

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Volatility is bad

It is bad for growth Excess volatility (relative to OECD) accounts for 1

percent less growth in LAC It is bad for inequality It is bad for poverty It is bad for educational attainment

Volatility is bad

Volatility and inequality

Hausmann and Gavin (1996)

Should volatility be bad?

• Arrow-Debreu • If there are complete insurance markets, then

volatility should not affect welfare• So you need to argue some form of market

incompleteness

Should volatility be that costly?• Assume no insurance markets but good financial markets• …then volatility should not be that big of a problem• There are shocks

– Terms of trade, natural phenomena, technology• People smooth consumption

– Borrow in bad times, pay back in good times– Anti-cyclical finance

• Governments smooth tax rates, spending– Anti-cyclical fiscal policy, deficits

• Country smoothes domestic demand– Borrow in bad times, pay back in good times– Anti-cyclical international finance

In the real world

• Bank lending looks pro-cyclical• Fiscal policy looks pro-cyclical• Capital flows look pro-cyclical

A real story

Oil exporting countries: two decades of poor performance

Country group 1960-98 1960-1980 1980-1998 Number of

countries

All developing 1.7 3.0 0.2 115

- oil exporters 1.1 5.2 -2.1 15

- others 1.8 2.7 0.5 100

Oil exporting countries have performed very poorly

PP

PG

DP

capi

ta c

onst

ruct

ed P

enn&

WB

year1960 1990

3884

13766

Saudi Arabia

PP

PG

DP

capi

ta c

onst

ruct

ed P

enn&

WB

year1950 1996

456

1515


Nigeria


Ln

(yn

oilp

w)

year1950 1960 1970 1980 1990 2000

3.80631

4.53617 VenezuelaProductivity per worker, non-oil economy

…accompanied by a collapse in capital per worker

Capital per worker

Output per worker

Venezuela: non-oil private sector

50

100

150

200

250

300

1950 1955 1960 1965 1970 1975 1980 1985 1990 1995

30

40

50

60

70

80

90

100

…and a rise in real exchange rate volatility

Venezuela

Volatility in:

0

5

10

15

20

25

30

35

1950-82 1982-2000

Oil Revenues

Real exchange rate

Countries less dependent on oil did betterP

PP

GD

Pcap

ita c

onstr

uc

ted

Pe

nn&

WB

year1960 1996

608

2782.71

Indonesia

PP

PG

DP

capi

ta c

onst

ruct

ed P

enn&

WB

year1950 1996

2198

6467

Mexico

Countries less dependent on oil did better

Not only oil exporters

Not only oil countries

What might explain the “resource curse”?

• Dutch disease?– Argues that oil booms cause contraction in manufacturing– But why did countries do so poorly when oil prices

declined?• Rent-seeking

– But why did countries do so well for so long?• Sparse forest?• Volatility

– But what is the mechanisms?

Oil exporters are in a sparse part of the forest

ALB

ARGAUS

AUT

BDI

BEN

BFA

BGD

BGR

BHR

BHSBLZ

BOL

BRA

CAF

CAN

CHL

CHN

CIV

CMR

COL

CRI

CYP

DNK

DOM

DZAECU

EGY

ESP

ETH

FIN

FJI

GAB

GBR

GHA

GMB

GRC

GTM

GUY

HKG

HND

HTI

HUN

IDN

IND

IRL

IRN

ISL

ISR

ITA

JAMJOR

JPN

KEN

KNA

KOR

LKAMAC

MAR

MDG

MEX

MLI

MLT

MNGMOZ

MUS

MWI

MYS

NER

NGA

NIC

NLD

NOR

NPL

NZL

OMN

PAK

PANPER

PHL

PNG

PRT

PRY

RWA

SAU

SDN SEN

SGP

SLE

SLV

SWE

SYR

TGO

THA

TTO

TUR

UGA

URY

USA

VEN

WSM

ZAF

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IRN

MEX

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NOR

OMN

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VEN

1112

1314

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pen_

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6 7 8 9 10LYPPPK

lopen_forest1b lopen_forest1b

Could oil income volatility really be a problem?

• Assume perfect international mobility of capital• Assume perfectly mobile labor nationally• Assume three sectors

– Oil: manna from heaven– Tradables: use capital and labor– Non-tradables: use capital and labor

• Oil income is transferred to householdsPunchline

• The production possibility frontier is flat. • Resources can move without changes in relative

prices

YN

YT

CTB

YTA

YTB

YNBYNA

THE BENCHMARK MODEL: THE DIVERSIFIED ECONOMY

The non-oil economy adjustswithout any relative price movements or losses

Is volatility that serious?

• Assume oil is 30 percent of GDP• Assume oil income volatility is 30 percent• Assume country is very risk averse

– CRRA = 3• Country would be willing to give up 4.1

percent of national income in order to eliminate uncertainty

• But what would explain declines of 50 percent of national income?

Should we be talking of stabilization policies or should we talk about the

“curse”?

Our central message

• The “curse” is caused by the interaction of three factors:– Domestic spending of oil income

• Mean and volatility

– “Specialization” away from non-oil tradables– Financial frictions

Building blocks

• Same as before• …but capital investments are made ex ante

and are irreversible– By themselves this does not buy much

• Government spends only in non-tradables• Consumers do not value government

spending– To eliminate standard consumption smoothing

argument for stabilization

YT

CTB

= YNBYNA

CTA

=

THE BENCHMARK MODEL: THE SPECIALIZEDIED ECONOMY

SpecializationNow, relative prices dohave to move to induceexpenditure switching

Financial frictions

• We assume that there is costly bankruptcy– Lenders are risk neutral and perfectly competitive– There is costly contract enforcement in case projects do

not have enough money to pay back in full. • This makes interest rates go up with volatility

– Lenders loose in the downside, but do not benefit from the upside. The larger the volatility, the larger the average premium they must charge

• We assume that lenders can distinguish between tradable and non-tradable borrowers and charge a different interest rate

Anatomy of the curse

• As the economy becomes more specialized • …relative prices become more volatile• …interest rates for tradables go up• …the tradable sector shrinks further• …making the economy even more specialized• …until the tradable sector disappears• …forcing an inefficient specialization• The economy is left in an environment of high

volatility, high interest rates and low capital

The frontier of specialization

0.15

0.20.

25

0.30.

35

0.40.

45

0.45

0.45

2

0.45

4

0.45

6

0.45

8

0.46

0.46

2

0.46

4

0.46

6

0.46

8

0.47

Volatility

Mean

Specialization

Mean

Volatility

Real exchange rate becomes dramatically more sensitive to volatility

0.15

0.20.

25

0.30.

35

0.40.

45

0.45

0.45

2

0.45

4

0.45

6

0.45

8

0.46

0.46

2

0.46

4

0.46

6

0.46

8

0.47

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

Volatility

Mean

CV

…interest rates in the non-tradable sector shoot up

0.15

0.20.

25

0.30.

35

0.40.

45

0.45

0.45

2

0.45

4

0.45

6

0.45

8

0.46

0.46

2

0.46

4

0.46

6

0.46

8

0.47

0.1

0.12

0.14

0.16

0.18

0.2

0.22

Volatility

Mean

Rhon

…and investment in non-tradables collapses

0.15

0.20.

25

0.30.

35

0.40.

45

0.45

0.45

2

0.45

4

0.45

6

0.45

8

0.46

0.46

2

0.46

4

0.46

6

0.46

8

0.47

1.5

1.6

1.7

1.8

1.9

2

2.1

2.2

2.3

2.4

2.5

Volatility

Mean

Investment NT

…causing a major decline in welfare

0.15

0.20.

25

0.30.

35

0.40.

45

0.45

0.45

2

0.45

4

0.45

6

0.45

8

0.46

0.46

2

0.46

4

0.46

6

0.46

8

0.47

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0.55

Volatility

Mean

EU

Venezuela: the collapse in capital per worker

Capital per worker

Output per worker

Venezuela: non-oil private sector

50

100

150

200

250

300

1950 1955 1960 1965 1970 1975 1980 1985 1990 1995

30

40

50

60

70

80

90

100

…and a rise in real exchange rate volatility

Venezuela

Volatility in:

0

5

10

15

20

25

30

35

1950-82 1982-2000

Oil Revenues

Real exchange rate

From stable real exchange rates…

220

270

320

370

420

470

520

570

620

670

720

770

820

870

920

970

19

57

M0

1

19

58

M0

3

19

59

M0

5

19

60

M0

7

19

61

M0

9

19

62

M1

1

19

64

M0

1

19

65

M0

3

19

66

M0

5

19

67

M0

7

19

68

M0

9

19

69

M1

1

19

71

M0

1

19

72

M0

3

19

73

M0

5

19

74

M0

7

19

75

M0

9

19

76

M1

1

19

78

M0

1

19

79

M0

3

19

80

M0

5

19

81

M0

7

19

82

M0

9

19

83

M1

1

19

85

M0

1

19

86

M0

3

19

87

M0

5

19

88

M0

7

19

89

M0

9

19

90

M1

1

19

92

M0

1

19

93

M0

3

19

94

M0

5

19

95

M0

7

19

96

M0

9

19

97

M1

1

19

99

M0

1

20

00

M0

3

20

01

M0

5

20

02

M0

7

…to dramatic instability

220

270

320

370

420

470

520

570

620

670

720

770

820

870

920

970

19

57

M0

1

19

58

M0

3

19

59

M0

5

19

60

M0

7

19

61

M0

9

19

62

M1

1

19

64

M0

1

19

65

M0

3

19

66

M0

5

19

67

M0

7

19

68

M0

9

19

69

M1

1

19

71

M0

1

19

72

M0

3

19

73

M0

5

19

74

M0

7

19

75

M0

9

19

76

M1

1

19

78

M0

1

19

79

M0

3

19

80

M0

5

19

81

M0

7

19

82

M0

9

19

83

M1

1

19

85

M0

1

19

86

M0

3

19

87

M0

5

19

88

M0

7

19

89

M0

9

19

90

M1

1

19

92

M0

1

19

93

M0

3

19

94

M0

5

19

95

M0

7

19

96

M0

9

19

97

M1

1

19

99

M0

1

20

00

M0

3

20

01

M0

5

20

02

M0

7

Venezuela: BRER 1957-2002Monthly

Explaining the curse

• Some countries became inefficiently specialized and were trapped by the curse– No expansion of non-oil exports after the collapse

in oil• Venezuela, Nigeria

– Collapse in capital per worker and output– Increase in real exchange rate volatility

• More diversified countries were unaffected– Mexico, Indonesia

Policy implications

Three types of countries• Efficiently specialized countries

– Countries that would specialize even if there were no financial frictions or no volatility

– e.g. The Gulf states?• Inefficiently specialized

– Countries that would diversify in the absence of financial frictions or volatility but are trapped by the curse

– e.g. Nigeria, Venezuela• Diversified

– Countries that have a large non-oil tradable sector– e.g. Ecuador, Indonesia, Mexico

Determinants of the frontier of specialization

• Average (expected) “government spending” – Primary non-oil deficit

• Volatility in government spending• Commercial “risk-free” interest rate

– Can be interpreted to include “country” risk– Higher rates cause the economy to specialize at

lower levels of spending and volatility

The impact of government volatility on utility

0.94

0.95

0.96

0.97

0.98

0.99

1

1.01

1.02

0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45

3.6

3.65

3.7

3.75

3.8

3.85

3.9

Eu® Eu(ns)® Eu®®

Diversified

Specialized

Ratio

Diversified countries

• Stay that way– Volatility is not that hurtful by itself

• …unless you have other rigidities (e.g. labor market)

– But volatility might push you over the cliff

• Examples:– Ecuador will soon have much more oil– Indonesia now has much higher country risk

Efficiently specialized economies

• Volatility of government spending hurts welfare

• Adopt expenditure stabilization policies• Do not try to forcefully diversify

Inefficiently specialized countries

• Need a “big push” to get over the cliff– Lower average non-oil primary deficit

• Medium term saving– Lower volatility of spending

• Expenditure stabilization policy– Country risk

• Budget institutions• debt management• policy credibility

• Greater credibility means less need for spending cuts

Reduce financial frictions

• Make debt contracts more efficient to make them better – Contract enforcement– Facilitate the use of collateral– Bankruptcy procedures

• Help develop equity markets– Promote direct investment– Improve corporate governance

Second-best policies?• If distortions remain, there may be a case for second-best

policies, since the market outcome is inefficient• Get more capital efficiently invested in tradables so as to

lower overall volatility and interest rates• Potential instruments

– Contingent trade policy• Tariffs and export subsidies contingent on the real exchange rate

– Contingent financial guarantees to tradable sector• Puts on the real exchange rate for exporters• Note the fiscal implications for oil booms

– Beware of political economy pressures

The problem with commodity stabilization funds

• What are they?– Rules that force the government to put into a fund revenues when the

price is above a certain level, and allow them to withdraw money when the price is low

• The logic– Prevent the government from spending in a pro-cyclical fashion

• The implementation– Force the (gross) savings of oil revenues

• The problem– No restriction on the overall deficit– High oil revenues facilitate borrowing– No real control over aggregate spending

• The solution– Policies that control the overall budget

A comparative performance

Chile vs. Venezuela

Similar volatility in terms of trade50

100

150

200

250

300

Ter

ms

of tr

ade

(19

90=

100

)___

EIU

1980 1990 2000 2010year

Terms of trade (1990=100)___EIU Terms of trade (1990=100)___EIU

Venezuela

Chile

Fiscal balance: Chile saves, Venezuela enjoys

-50

510

Bud

get b

alan

ce (

% o

f GD

P)_

__E

IU

1998 2000 2002 2004 2006 2008year

Budget balance (% of GDP)___EIU Budget balance (% of GDP)___EIU

Chile

Venezuela

Real effective exchange rate60

8010

012

014

016

0R

eal

effe

ctiv

e ex

cha

nge

rate

(in

dex,

19

97=

100)

___E

IU

1985 1990 1995 2000 2005year

Real effective exchange rate (index, 1997=100)___EIUReal effective exchange rate (index, 1997=100)___EIU

Venezuela

Chile

Look at how each country is reacting to the boom

5010

015

020

025

030

0

1980 1990 2000 2010year

Export volume of goods (1996=100)___EIUImport volume of goods (1996=100)___EIU

5010

015

020

025

0

1985 1990 1995 2000 2005year

Export volume of goods (1996=100)___EIUImport volume of goods (1996=100)___EIU

Real Imports

Real exports

Real Imports

Real exports

Chile Venezuela

International dimensions of volatility:Original sin

Motivation• Most countries cannot borrow abroad in their own currencies, a

problem we referred to three years ago (Eichengreen and Hausmann, “Exchange Rates and Financial Fragility,” Kansas City Fed, ed., New Challenges for Monetary Policy, 1999) as “original sin”

• If a country has a net foreign debt, this creates an aggregate currency mismatch

• To avoid it, countries must either forgo gross borrowing or accumulate large reserves

• Original sin is associated with output and capital flow volatility• Monetary policies in such countries are rigid, while their central

banks are unable to act as LLRs.• They are vulnerable to crises, of the self-fulfilling variety and

otherwise.

Implications for Reform of the International Financial Architecture

• The conventional prescription of floating is problematic for countries with original sin

• Inflation targeting is more difficult for such countries• Stabilizing capital flows is more difficult• Strengthening financial systems is more difficult• Avoiding financial crises is more difficult• All this raises the question of whether the “architecture

agenda” can succeed without addressing original sin

Key Question from this Point of View

• Does the inability to borrow internationally in domestic currency reflect problems with country policies and institutions or global problems?

• We argue that the problem is too pervasive (and too weakly correlated with country characteristics) to be entirely explicable on the first set of grounds.

• This leads us to a systemic explanation for the problem, which in turn leads us to an international proposal for its solution

Outline and Summary• Definition and Facts

– Most countries do not borrow abroad in their own currencies, a problem we refer to as “original sin”

• If a country has a net foreign debt, this creates an aggregate currency mismatch

– Of course a country can decide not to have a mismatch by not borrowing or holding a lot of reserves

• Pain– We show that original sin is associated with limited XR

flexibility, high volatility, low credit ratings• Mystery

– We show that standard explanations based on poor policies or institutions do not do a good job at explaining original sin

Work on Original Sin• First papers on the topic:

– Eichengreen and Hausmann (1999)– Hausmann, Panizza, and Stein (2001)– Hausmann and Panizza (2003)

• Original Sin book: – Cespedes, Chang and Velasco, Corsetti and Mackowiak, Jeanne,

Jeanne and Zettelmeyer, Flandreau and Sussman, Bordo, Meissner and Redish, Chamon and Hausmann

• Critics:– Goldstein and Turner (2003)– Burger and Warnock (2003)– Reinhart, Rogoff, and Savastano (2003)– Eichengreen, Hausmann, and Panizza (2003)

Definition

• Eichengreen and Hausmann (1999) definition: “a situation in which the domestic currency is not used to borrow abroad or to borrow long term even domestically”

• Here we mostly focus on “international original sin”– Better data on international original sin– Domestic original sin seems easier to solve and some

countries are doing progress in this direction• However, we also try to say something on “domestic

original sin”

A first look at the problem:Distribution of international debt by issuers

and currencies (1999-2001)

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

USA Euroland Japan UK Switzerland Canada Australia

Debt by

country

Debt by currency

$4.5 trillion

$5.6 trillion

Is this because countries do their local currency funding on the home market and foreign

currency funding abroad?

0

10

20

30

40

50

60

70

80

90

100

USA EURO JAPAN CANADA UK

Debt by currency

Debt by country

$473 billion

$632 billion

Measurement

• Measuring original sin is not straightforward• In principle, we want to measure external liabilities in

own currency as a share of total external liabilities• We use data gathered by the BIS on the currency

denomination of bonds and money market instruments

• We also consider BIS data on cross-border bank lending, although the data are less complete (both in country coverage and currency breakdown)

Main index used in the paper

0,

country by issued Securities

currency in Securities1max3

i

iOSIN i

It captures opportunities for hedging through swaps

It recognizes that you cannot hedge more than 100 percent of your debt

Alternative indexes

i

i iOSIN1

country by issued securities

country by issued currencyin securities1

OSIN2 Uses bank loans

OSIN3b Like OSIN3 but can take negative values

Measures of original sin by country groupings

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Financial Centers Euroland Other Developed Developing

OSIN1 OSIN3

Original Sin in Developing Countries

0.75

0.8

0.85

0.9

0.95

1

LAC ASIA&PAC ME&AFR ECA

1993-1998 1999-2001

Original sin is highly persistent: OSIN and Flandreau-Sussman classification

(circa 1850)

00.10.20.30.40.50.60.70.80.9

GoldClauses

MixedClauses

DomesticCurrency

The Pain of Original Sin

(The consequences)

• Exchange rate flexibility

• Output and capital flow volatility

• Credit ratings

Original Sin and Exchange Rate Flexibility

• If an original sin country has a net foreign debt, then there is an aggregate currency mismatch. Movements in the RER will have an aggregated wealth effect

• This renders the CB less willing to let the exchange rate move (fear of floating, Calvo and Reinhart, 2002)

• As a consequence, the CB holds more reserves and uses them, together with the interest rate, to intervene in the foreign exchange market (Hausmann, Panizza, Stein, 2001)


(1) (2) (3) (4) (5) (6) Dropping Financial Centers LYS RESM2 RVER LYS RESM2 RVER OSIN3 1.503 0.248 -0.801 1.112 0.339 -0.598 (3.56)***

(3.74)*** (2.02)** (2.45)** (3.10)*** (1.33)

GDP_PC 0.302 -0.053 0.026 0.285 -0.052 0.025 (2.89)***

(1.85)* (0.61) (2.77)**

* (1.81)* (0.56)

OPEN 0.198 -0.014 1.017 0.153 -0.014 1.021 (0.92) (0.41) (2.88)*** (0.72) (0.41) (2.93)*** EXD/GDP 0.290 -0.036 -0.570 0.297 -0.030 -0.544 (0.96) (0.66) (2.36)** (0.98) (0.54) (2.29)** Constant -2.188 0.531 0.104 -1.644 0.435 -0.084 (1.94)* (1.73)* (0.17) (1.46) (1.35) (0.13) Observations 75 65 65 71 62 62 R-squared 0.37 0.62 0.34 0.65

Floating at its best:Australia

4

4.2

4.4

4.6

4.8

5

5.2

5.4

5.6

5.8

61/

1/97

3/1/

97

5/1/

97

7/1/

97

9/1/

97

11/1

/97

1/1/

98

3/1/

98

5/1/

98

7/1/

98

9/1/

98

11/1

/98

1/1/

99

3/1/

99

5/1/

99

7/1/

99

9/1/

99

inte

rest

rat

e

1.2

1.3

1.4

1.5

1.6

1.7

1.8

exch

ange

rat

e

Floating Latin Style: Mexico

15

20

25

30

35

40

45

50

55

1/2/

97

3/2/

97

5/2/

97

7/2/

97

9/2/

97

11/2

/97

1/2/

98

3/2/

98

5/2/

98

7/2/

98

9/2/

98

11/2

/98

1/2/

99

3/2/

99

5/2/

99

7/2/

99

inte

rban

k ra

te

7

7.5

8

8.5

9

9.5

10

10.5

11

exch

ange

rat

e

interbank rate

exchange rate

Why this difference?

• Standard assumptions• Reduction in interest rates are expansionary

– Directly through the impact on investment and consumption

– Indirectly by weakening the currency through the interest parity condition, which depreciates the exchange rate

– Exchange rate depreciations are expansionary

What could be different?

• Sensitivity of aggregate demand to interest rates– How deep is the financial system?

• Are depreciations expansionary?• Three possible answers

– Yes– No, but the effect is smaller than the direct effect of lower

i – No, and the effect makes interest rate reductions

contractionary

Mapping of the issues

• Three possible answers– Yes

– No, but the effect is smaller than the direct effect of lower i

– No, and the effect makes interest rate reductions contractionary

• Three potential implications– Greenspan

– Need for larger interest rate movements to adjust to shocks

– Apparently counter-cyclical monetary policy


• The results are generally robust to alternative definitions of original sin, to dropping weights, and to augmenting the regressions with a developing country dummy

• Causality is a big issue (Burnside, Eichenbaum, and Rebelo, 2001)– IV regressions confirm the results but instrument (SIZE) is lousy

• We tried to go in the other direction. OSIN on the left and LYS on the right instrumented with openness. We found no correlation between LYS and OSIN

– Using lagged OSIN in a panel confirms the results– Devereux and Lane (2003)

Original Sin, Output and Capital Flow Volatility

• Original sin limits the scope and effectiveness of counter-cyclical policies (Cespedes, Chang and Velasco, 2003)

• Original Sin limits the CB ability of acting as a LOLR (Chang and Velasco, 2000)

• Dollar liabilities are likely to increase the cost of a currency crisis

• Dollar liabilities could be associated with Sudden Stops in capital flows (Calvo, Izquierdo and Mejia, 2003)

Original Sin, Output and Capital Flow Volatility

(1) (2) (3) (4) Dropping Financial Centers VOL_GROWTH VOL_FLOW VOL_GROWTH VOL_FLOW OSIN3 0.011 7.103 0.015 7.498 (1.96)* (3.58)*** (2.45)** (2.69)** LGDP_PC -0.012 -3.214 -0.012 -3.322 (2.14)** (2.56)** (2.09)** (2.40)** OPEN -0.001 -4.181 -0.000 -4.333 (0.12) (1.20) (0.08) (0.83) VOL_TOT -0.000 0.223 -0.000 0.223 (0.86) (1.08) (0.89) (1.02) SHARE2 -0.014 0.147 -0.015 0.949 (1.72)* (0.04) (1.51) (0.14) Constant 0.135 32.825 0.131 33.282 (2.25)** (2.39)** (2.15)** (2.22)** Observations 77 33 73 29 R-squared 0.40 0.64 0.40 0.62

Original Sin and Credit Ratings• If a country’s debt is denominated in foreign currency, its

capacity to pay will not be related to its LCU GDP but to its dollar GDP– Original Sin makes the real exchange rate matter for debt service

• This is important because in developing countries the volatility of dollar GDP is much higher than the volatility of LCU GDP, and sudden drops of dollar GDP are usually associated with much smaller drops in real GDP

• Other things equal, countries with Original Sin should be riskier than countries that borrow in own currency

Original Sin and Credit Ratings

(1) (2) (3) (4) RATING RATING RATING RATING Dropping Financial

Centers OSIN3 -5.845 -5.644 -5.214 -4.955 (4.08)*** (4.01)*** (3.31)*** (3.21)*** DE_GDP -2.421 -2.285 (2.50)** (2.32)** DE_RE -0.999 -0.975 (2.49)** (2.39)** LGDP_PC 2.916 2.670 2.976 2.729 (8.48)*** (6.16)*** (8.36)*** (5.97)*** SHARE2 2.187 2.787 1.810 2.405 (1.43) (1.52) (1.09) (1.18) Constant -8.058 -5.962 -9.119 -7.037 (2.12)** (1.28) (2.29)** (1.44) Observations 56 49 53 46

The Mystery of Original Sin

(the causes)

Key Question from this Point of View

• Does the inability to borrow internationally in domestic currency reflect problems with country policies and institutions or systematic problems?

• We argue that the problem is too pervasive (and too weakly correlated with country characteristics) to be entirely explicable on the first set of grounds.

Five possible explanations

• Underdevelopment of institutions and policies in general

• Inadequate monetary credibility• Fiscal profligacy• Weak contract enforcement• Political economy stories

Original Sin and the Level of Development

(1) (2) (3) OSIN3 OSIN3 OSIN3 LGDP_PC -0.141 -0.128 -0.170 (1.59) (1.43) (2.99)*** SIZE -0.310 -0.310 -0.415 (3.37)*** (3.33)*** (4.51)*** FIN_CENTER -0.680 (1.99)* EUROLAND -0.126 -0.152 (0.62) (0.74) OTH_DEVELOPED 0.007 -0.021 (0.03) (0.10) Constant 2.522 2.414 2.833 (3.39)*** (3.24)*** (5.46)*** Observations 75 71 75

Original Sin and Monetary Credibility

• Lack of monetary credibility is the true cause of Original Sin (Jeanne, 2002)

• The government has an incentive to inflate away domestic currency debt held by foreigners, and the presence of foreign currency debt can act as commitment device and improve credibility (Tirole, 2002, Calvo and Guidotti, 1990)– Why don’t we observe inflation indexed debt? (Chamon,

2002)


(1) (2) (3) (4) (5) (6) Dropping

Financial Centers

OSIN3 OSIN3 OSIN3 OSIN3 OSIN3 OSIN3 AV_INF 0.306 0.436 (1.19) (0.69) AV_INF2 -0.116 (0.23) MAX_INF 0.067 (0.95) INF 0.085 0.083 0.175 (1.09) (1.07) (2.08)** SIZE -0.318 -0.318 -0.316 -0.318 -0.318 -0.503 (3.57)*** (3.54)*** (3.52)*** (3.55)*** (3.50)*** (5.75)*** FIN_CENTER -0.866 -0.897 -0.857 -0.881 (2.88)*** (2.99)*** (2.83)*** (2.93)*** EUROLAND -0.304 -0.329 -0.296 -0.315 -0.318 (2.12)** (2.31)** (1.99)* (2.21)** (2.21)** OTH_DEVELOPED -0.199 -0.224 -0.192 -0.211 -0.213 (1.47) (1.67)* (1.37) (1.56) (1.57) Constant 1.277 1.310 1.259 1.346 1.347 1.358 (10.87)*** (11.60)*** (8.83)*** (13.56)*** (13.46)*** (13.41)*** Observations 74 74 74 74 70 74


e( O

SIN

3 | X

)

e( AV_INF | X ) -.246179 1.48963

-.893699

.363081

BRB

BHR OMN

MLT BHS CYP PNG JOR

LUX

MUS

TTO

TUN MAR

SGP FIN

LKA GTM

PAK AUT

DNK

MDA

SLV

NOR

CHE

CZE

THA

BEL

NET

SWE

AUS

SVN

ZWE CAN DOM

SVK

PHL

ISL JAM

KOR

IND

PRT

DEU JPN

ESP

FRA ZAF

HUN

GBR

IDN

CRI

CHL GRC

ITA

USA

EST

SUR

COL

ECU LVA

VEN

URY

MEX

POL

ISR

BGR

TUR

BOL

ROM

PER

RUS

ARG

NIC

UKR


• Low inflation seems to be a necessary but not sufficient condition for escaping Original Sin

• Results are robust to longer lags (1970s)• They are robust to instrumenting inflation with an

index of CB independence

Original Sin and Fiscal Solvency

• A government with weak fiscal accounts has an incentive to debase its currency in order to erode the value of its real obligations (Lucas and Stokey, 1983)

• Corsetti and Mackowiack (2002) find that there is a vicious circle in which, in the presence of weak public finances, a large stock of foreign currency debt limits the ability to borrow in domestic currency

Original Sin and Fiscal Solvency

(1) (2) (3) (4) (5) (6) (7) OSIN3 OSIN3 OSIN3 OSIN3 OSIN3 OSIN3 OSIN3 DE_GDP -0.073 0.050 (0.50) (0.31) DEFICIT 1.777 (0.92) DE_RE 0.014 (0.24) FISC -0.025 -0.024 (0.30) (0.28) DE_GDP*DEV 0.247 (0.88) DE_GDP*IND -0.186 (1.13) SIZE -0.350 -0.327 -0.354 -0.342 -0.345 -0.330 -0.555 (3.71)*** (3.52)*** (3.51)*** (3.42)*** (3.40)*** (3.60)*** (5.92)*** FIN_CENTER -0.825 -0.926 -0.816 -0.839 -0.645 (2.72)*** (3.09)*** (2.57)** (2.66)** (2.01)** EUROLAND -0.344 -0.361 -0.327 -0.348 -0.348 -0.155 (2.61)** (2.66)*** (2.22)** (2.48)** (2.46)** (0.84) OTH_DEVELOPED -0.275 -0.215 -0.245 -0.272 -0.272 -0.094 (2.18)** (1.54) (1.73)* (2.01)** (1.99)* (0.53) Constant 1.426 1.311 1.370 1.382 1.385 1.260 1.374 (11.99)*** (11.46)*** (10.06)**

* (12.04)*** (11.93)*** (8.00)*** (11.66)***

Observations 64 74 57 57 54 64 64

Original Sin and Contract Enforcement

• Investors are reluctant to lend in countries where the institutions designed to enforce their claims are weak

• Chamon (2002) and Aghion, Bacchetta and Banerjee (2001) show that if depreciation and default risk are correlated and, if in case of default, assets are divided among creditors in proportion to their nominal claims, domestic currency market will disappear

• This problem could be solved if courts could enforce complicated contracts that distinguish among creditors of different seniority

Original Sin and Contract Enforcement

(1) (2) (3) OSIN3 OSIN3 OSIN3 RULEOFLAW -0.050 -0.053 -0.182 (0.46) (0.49) (2.33)** SIZE -0.323 -0.322 -0.480 (3.53)*** (3.48)*** (5.32)*** FIN_CENTER -0.883 (2.65)** EUROLAND -0.326 -0.325 (1.81)* (1.79)* OTH_DEVELOPED

-0.203 -0.201

(1.03) (1.01) Constant 1.388 1.390 1.486 (13.17)*** (13.08)*** (12.33)*** Observations 75 71 75

Original Sin and Political Economy

• Original sin could be due to the absence of a domestic constituency of local currency debt-holders prepared to penalize a government that debase the currency

• Tirole (2002) suggests that Original Sin may arise from the government’s inability to commit to protect the rights of foreigners

Original Sin and Political Economy

(1) (2) (3) (6) OSIN3 OSIN3 OSIN3 OSIN3

DC_GDP -0.332 -0.554

(1.49) (2.99)***

FOR_DOM -7.289 7.224 (2.15)** (0.86)

SIZE -0.290 -0.360 -0.323 -0.399

(3.22)*** (4.02)*** (3.72)*** (4.47)***

FIN_CENTER -0.753 -0.843 -0.895 (2.40)** (3.02)*** (3.23)*** EUROLAND -0.226 -0.301 -0.299 (1.37) (2.34)** (2.42)** OTH_DEVELOPED -0.224 -0.223 -0.254 (1.75)* (1.86)* (2.16)** Constant 1.521 1.431 1.291 1.636

(10.13)*** (13.76)*** (11.15)*** (11.32)***

Observations 74 73 72 74

Digression on Domestic Original Sin

• It may be the case that the previous regressions do not yield any result because we are not able to measure the “real” size of the domestic local currency market

• This would require building a measure of domestic original sin and looking at how it relates to international original sin


• We were able to build such a measure for a small sample of 21 developing countries

DLTDLTIPDLTIIDSTFC

DLTIIDSTFCDSIN

Digression on Domestic Original SinD

SIN

2

OSIN30 .25 .5 .75 1

0

.25

.5

.75

1

POL

CZE

ZAF

HKG

TWN

SGP

SVKTHA

EGY

ARG

CHL

HUN

IDN

PHL

MEX

MYS

BRA

TUR

IND

ISR

VENDSIN=0.25+0.37*OSIN3 p value on slope coefficient 0.11 R2=0.13 N= 21


(1) (2) (3) (4) (5) (6) (7) (8) DSIN DSIN DSIN DSIN DSIN DSIN DSIN DSIN LGDP 0.134 (1.63) LGDP_PC 0.029 (0.36) AV_INF 0.134 0.176 0.215 (2.16)** (1.73) (3.75)*** RULEOFLAW -0.142 (1.59) DC_GDP -0.638 -0.263 (1.94)* (0.60) CAPCONTR -0.069 -0.140 (1.18) (3.24)*** Constant -0.064 0.335 0.217 0.607 0.906 0.218 0.576 0.008 (0.17) (0.49) (1.09) (6.38)*** (4.39)*** (0.43) (7.48)*** (0.04) Observations 21 21 21 20 18 18 21 21 R-squared 0.09 0.01 0.15 0.08 0.18 0.28 0.07 0.37

Digression on Domestic Original SinD

SIN

2

OSIN30 .25 .5 .75 1

0

.25

.5

.75

1

POL

CZE

ZAF

HKG

TWN

SGP

SVKTHA

EGY

ARG

CHL

HUN

IDN

PHL

MEX

MYS

BRA

TUR

IND

ISR

VEN

CC=0.45

CC=0.69

CC=0.50

Not significantly different


• There is some (weak) evidence that capital controls may help in reducing domestic original sin

• However, it looks as if capital controls are bad for international original sin

Back to International Original Sin

Putting Everything Together (1) (2) (3) (4) OSIN OSIN OSIN OSIN SIZE -0.302 -0.325 -0.326 -0.352 (3.32)*** (3.48)*** (3.50)*** (3.88)*** GDP per cap -0.262 -0.127 -0. 248 (2.08)** (1.31) (2.30)** AV_INF 0.288 0.150 0.070 0.274 (0.89) (0.4 9) (0.29) (0.88) DE_GDP -0.003 -0.102 0.044 -0.002 (0.02) (0.60) (0.26) (0.01) RULE of LAW 0.305 0.091

-0.291 (1.88)* (0.70)

(1.25) DC_GDP -0.313 -0.173 -0.403

0.255

(1.05) (0.59) (1.38)

(1.61)

FIN_CENTER -0.492 -0.453 -0.680

(1.45) (1.31) (2.06)**

EUROLAND 0.032 0.010 -0.220

(0.15) (0.04) (1.18) OTH_DEVEL. -0.053 0.030 -0.299 (0.24) (0.14) (1.55) Constant 3.506 2.505 1.516 3.437 (3.54)*** (3.22)*** (7.66)*** (4.03)*** Observations 63 63 63 63

(5) OSIN -0.374

(4.05)*** -0. 113

(1.82)* 0.099 (0.36) -0.062 (0.37)

-0.269 (1.14)

3.437 (4.03)***

63

• SIZE always significant• When we include one variable at a time, we find that:

– If we control for country groups there is no other variable that is significantly correlated with Original Sin

– If we do not control for country groups, GDP per capita, inflation, rule of law, and size of the financial system are correlated with Original Sin

• When we jointly test all the hypotheses, we find that:– When country groups are included, only SIZE is robustly

correlated with Original Sin– When country groups are dropped, GDP per capita is marginally

significant

• Original sin is not merely a problem of country policies (one need not deny the relevance of these, of course)

• It is also a problem with the operation of the international system

• In a world with transaction costs and decreasing returns to diversification, the global portfolio may have a limited number of currencies

• If larger countries offer better opportunity for diversification, country size will matter in the choice of the global portfolio

• Redemption therefore requires international action to overcome the inertia in the system

Lessons from outliers

• An interesting fact about the international issuance of bonds in exotic currency is that it is mostly done by non-residents who then swap the debt-service obligation back to US dollar

Share of local currency international debt issued by non-residents

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

CzechRepublic

SouthAfrica

NewZealand

Poland Hong Kong Denmark Canada Singapore Australia


• An interesting fact about the international issuance of bonds in exotic currencies is that it is mostly done by non-residents who then swap the debt-service obligation back to their own currency

• They do this to reduce cost of funding– But, why is this complex operation cheaper than

borrowing directly in dollars?– A possibility is that the market values the possibility

of separating currency and credit risk• The IFIs have an interest in lending in local

currency and could play a role in expanding this market

Conclusions

• Original Sin is a widespread phenomenon• It has costs

– Limits the ability to conduct monetary policy– Increases volatility– Increases credit risk

• It cannot be easily explained by weak policies or institutions

• Country size seems to be important• The IFIs could play a role in reducing Original Sin

Original Sin and Credit Ratings (1) (2) (3) (4) (5) (6) RATING RATING RATING RATING RATING RATING Original Sin -5.100 -4.751 (3.38)*** (3.32)*** Debt/GDP advanced 4.814 -2.659 -1.553 -2.451 (2.30)** (1.24) (1.31) (2.05)** Debt/GDP developing -8.627 -3.671 -3.557 -2.475 (4.96)*** (2.34)** (2.66)** (1.84)* Developing -9.027 -3.004 (5.78)*** (2.38)** Debt/GDP high rating 5.783 -1.511 (3.10)*** (0.83) Debt/GDP low rating -9.207 -4.438 (5.85)*** (3.36)*** High rating 8.917 (6.60)*** GDP per capita 2.663 1.936 (6.71)*** (4.00)*** Ex Debt/GDP 2.252 1.751 (1.50) (1.22) Constant 13.999 19.757 14.138 11.028 -6.314 1.606 (15.60)*** (15.27)*** (17.51)*** (15.03)*** (1.58) (0.32) Observations 61 61 61 61 56 56 DEG_DEV=DEG_ADV DEG_HR=DEG_LR

F(1,59)=41.31 F(1,58)=0.14 F(1,59)=62.7 F(1,58)=1.69

P=0.000 P=0.705 P=0.000 P=0.199

The road to redemption



• Countries that have recently escaped original sin seem to have done so through non-nationals issuing debt in domestic currency

• IFIs have played a major role in this process

• Borrowers swap their obligations with residents

Foreigners issue most of the debt in exotic currencies

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

CzechRepublic

SouthAfrica

New Zealand

Poland HongKong

Denmark Canada Singapore Australia

OSIN 3% Foreign

Countries with OSIN 3 below 0.8, excluding Financial Centers

IFIs are very important in the new OS outliers

0%10%20%30%40%50%60%70%80%90%

100%

CzechRepublic

Estonia HongKong

Poland Portugal SlovakRepublic

SouthAfrica

Spain

1993-98 1999-01

Our proposalOur proposal

We propose an index based on an inflation-We propose an index based on an inflation-adjusted basket of EM currenciesadjusted basket of EM currencies Historically it shows trend appreciation, low Historically it shows trend appreciation, low

volatility and negative correlation with volatility and negative correlation with industrial country consumptionindustrial country consumption

We propose that the WB, other IFIs and C-5 We propose that the WB, other IFIs and C-5 governments issue debt in this index and governments issue debt in this index and swap obligations with EMsswap obligations with EMs

Why is this so?

• Not because of a “developmental” goal– IDB issued in non-member currencies

• Only because it is cheaper– Swap back into US$

• What makes it more efficient?– Correlation between currency risk and default risk makes

local instruments inefficient– IFIs have no correlation between currency and default risk– Local borrowers on the other end pay to get rid of the

mismatch enough to encourage IFIs to issue

Our proposal

• Develop an index– based on a basket of currencies– Indexed to inflation– GDP PPP weighted

• We show that it has three characteristics– Trend appreciation– Low volatility: very diversified– Negative correlation with consumption in industrial

countries• Excellent for a developed country portfolio

0.3

0.5

0.7

0.9

1.1

1.3

1.5

1.7

198

0Q1

198

1Q1

198

2Q1

198

3Q1

198

4Q1

198

5Q1

198

6Q1

198

7Q1

198

8Q1

198

9Q1

199

0Q1

199

1Q1

199

2Q1

199

3Q1

199

4Q1

199

5Q1

199

6Q1

199

7Q1

199

8Q1

199

9Q1

200

0Q1

200

1Q1

20 in the 80's

22 from 93-02

DM Index

Yen Index

The EM is a stable index

Appreciation, stability, risk diversification

Table 20: EM Indexes: Average return, standard deviation and correlation with realprivate consumption.

EM Index 80 (1980-2001) EM Index 93 (1993-2001)Avg. Return St Dev Consumption

Correlation 1Avg. Return St Dev Consumption

Correlation 1

Canada 1.56 10.9 -14.5 1.49 10.5 -33.4France 2.58 13.6 -25.9 2.92 10.2 -36.4Germany 0.73 14.3 12.5 3.14 10.5 -14.5Italy 4.22 14.0 -27.5 3.36 11.1 15.8Spain 4.50 12.9 -62.0 4.30 10.5 -65.4Japan -3.12 13.9 4.3 0.13 11.8 34.3United Kingdom 2.45 12.2 -35.3 -0.24 11.8 -21.4United States 0.27 11.3 -23.4 -0.71 11.6 -25.51Note: Correlations with Real Consumption: for France, Germany, Italy and Spain it covers 1980-1998.

For Canada, UK, US and Japan it covers 1980-01. A negative number indicates that the returns tend to be high when realprivate consumption is low.

Step 2. Have the World Bank and other IFIs issue debt in EMs

• IFIs are AAA, so they have access to a broad asset class• They can hedge their currency exposure by converting

loans to EM-index members into indexed local currency loans– They become a solution, not a cause of OS

• Regional IFIs can swap with the WB or the governments themselves for non-regional index members

• WB would calculate index lowering manipulation risk

Step 3. Have C-5 countries issue debt denominated in index

• Also high-grade non-residents with an interest in lowering global risks

• Swap currency exposure with EM-member countries– This gets read of the mismatch

• Need not cost them anything– Make sure by providing put-option on the price of the

swap

• The swap is much safer than sovereign risk and can be made safer

Expected further developments

• If the EM-index market develops, mutual funds and institutional investors will try to add by buying local currency instruments issued by residents

• Evidence from exotic currencies is that IFI role dwindles in time as market develops

In conclusion

• We base our solution on the experience of outliers– Role of foreign issuers, IFIs, swaps

• We address the cause of OS by offering a well diversified synthetic currency

• We address the credibility problem of EMs by indexing to inflation

• Very limited downside risk if attempt to develop EM market fails

Should IDA lend in UFs?

Why IDA should lend in UFs

Arguments• Foreign currency debt is riskier than local currency inflation-

indexed (UF) debt– Service of $ debt is a function of the RER which is volatile and pro-

cyclical• International markets in UF do not exist preventing the IBRD

from funding itself in such terms– Eichengreen and Hausmann propose that the IBRD issue debt in a

basket of UFs• IDA has no such constraint• Converting IDA loans to UFs at current prices and contracted

interest rates would maintain the expected dollar value of IDA reflows and allow significant international risk sharing and inter-temporal smoothing

Arguments• Foreign currency debt is riskier than local currency inflation-

indexed (UF) debt– Service of $ debt is a function of the RER which is volatile and pro-

cyclical• International markets in UF do not exist preventing the IBRD

from funding itself in such terms– Eichengreen and Hausmann propose that the IBRD issue debt in a

basket of UFs• IDA has no such constraint• Converting IDA loans to UFs at current prices and contracted

interest rates would maintain the expected dollar value of IDA reflows and allow significant international risk sharing and inter-temporal smoothing

What would happen if IDA lent in UFs?

• How volatile would be a portfolio of IDA loans if each loans was converted into a country’s UF?

• The average volatility of a country’s UF vis a vis the US dollar is 15%

• The volatility of the IDA portfolio of UFs vis a vis the US$ would be 3%

• Great possibilities of risk sharing across IDA members

Volatility of the UFs and of the portfolio

LCA

KNA

VCT

BGD

GRD

LKA

DMA

DJI

MDV

PAK

IND

NPL

CRI

KHM

TUN

GIN

AZE

CHL

TWN

MAR

BTN

JOR

TON

MUS

CPV

THA

DOM

BWA

BOL

BDI

LSO

GMB

PHL

COL

TZA

CHN

MRT

PNG

SWZ

WSM

STP

MNG

MDG

SLB

MKD

TUR

TCD

SLV

KOR

CIV

RWA

GUY

ALB

NER

GEO

COM

BEN

TGO

ZWE

ECU

UGA

ETH

GNB

ZMB

PRY

MLI

SEN

COG

GHA

HND

ARM

GNQ

KEN

KGZ

BFA

CMR

MWI

TJK

MDA

SYR

EGY

IDN

SLE

LAO

ZAR

MOZ

NIC

AGO

YEM

NGA

VNM

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

rer Stdev basket StdevAve rer Stdev

15%

3%

We simulate a conversion to UFs• For country i, we convert the initial debt in the data base into local currency at the

prevailing exchange rate.• We leave unaffected the dollar value of IDA disbursements, but we covert them into local

currency at the prevailing exchange rate in each period. • We augment the nominal value of the debt by the domestic inflation rate in each period.

We then calculate the amortizations due as the same proportion of the debt that is amortized in the original data. This is equivalent to computing a amortization rate in the original data and maintaining it for the domestic currency denominated debt.

• From the original data, we compute the implied interest rate by dividing the interest payments by the outstanding debt. We assume that this interest rate (which reflects the average lending conditions for each year-country pair) remains the same, except for the fact that it will be increased by a constant premium.

• We compute a new interest rate on UFs by increasing the implied dollar interest rate by a premium. This premium will be used to make sure that the NPV of IDA reflows in dollars remains the same. We assume the premium to be the same for all countries.

• Using the new UF interest rate, we calculate the interest payment and the debt dynamics. • We iterate the calculation until we find a premium that achieves the same net present

value of IDA reflows from ALL countries as in the original data.

Implications

• Fixing the debt in UFs implies denominating the debt in domestic consumption units

• Over the 1985-2000 period, the required adjustment to keep the NPV constant was 8 bp

Actual and simulated interest payments: levels and percentage difference

0

100000000

200000000

300000000

400000000

500000000

600000000

1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001-15.0%

-10.0%

-5.0%

0.0%

5.0%

10.0%

15.0%

20.0%

Ave I/Y OldAve I/Y SimRelative

Actual and simulated total debt service: levels and percentage difference

0

200000000

400000000

600000000

800000000

1000000000

1200000000

1400000000

1600000000

1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001-15.0%

-10.0%

-5.0%

0.0%

5.0%

10.0%

15.0%

20.0%

Ave I+A/Y OldAve I+A/Y SimRelative

Conclusions

• Aggregate debt service is broadly in line with the US$ portfolio

• Deviations are bounded by +-15%• However, these deviations are consistent with

a constant NPV of the IDA reflows • …and they have excellent cyclical

characteristics

Debt service becomes much less procyclical and less sensitive to RER

movementsD/YD/Y I/YI/Y

OldOld NewNew OldOld NewNew

OutputOutput -0.13-0.13 -0.01-0.01 -0.16-0.16 -0.04-0.04

3.23.2 0.10.1 3.73.7 0.80.8

RERRER 0.350.35 0.140.14 0.320.32 0.090.09

13.013.0 4.54.5 11.211.2 2.82.8

What are the consequences of the change in the stochastic patterns of debt service?

• We do a Monte Carlo simulation of the debt to GDP ratio using the same volumes of IDA loans and reflows but we use the old and new variance-covariance matrix to simulate the distribution of debt/GDP ratios

Over the long run the debt/GDP ratio becomes more certain

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8

Old Simulated

Proposal

• We propose to do a balance sheet operation in which all IDA loans are re-indexed to each country’s UF

• All disbursements and repayments would still be made in foreign currency but debt service will be indexed to UFs

• The interest rate should remain the same as in the original contract

Why not change the interest rate

• In the 1985-2000 simulation we required an increase of 8bp to make the NPVs equal,

• This was driven by the fact that the 1985-2000 period was unusually difficult in poor countries

• We calculated that going forward the NPV of the UF portfolio would exceed the NPV of the $ portfolio if the sum of real appreciation plus US inflation exceeds 1.37%

• We believe this threshold will most likely be passed• Even if it is not, it would imply that a large real depreciation

has occurred (larger than expected US inflation) and the reduction in IDA reflows would prevent debt service from rising in terms of domestic consumption units

In synthesis

• IDA is not constrained by markets to denominate its lending in US$

• If it converted its loans into inflation-indexed local currency the expected value of the portfolio would be stable

• …debt service would be less risky from the point of view of shocks to the capacity to pay of its borrowers

• …and HIPC-style restructurings could be avoided

Documents

Understanding The Empirics Of Financial Volatility