Transcript Luis Servén

Growth and welfare effects
of macroeconomic volatility
Luis Servén
The World Bank
Barcelona
March 2006
Figure 1. Standard
Deviation
1970-2001
Output volatility
and
consumption
volatility
Std Dev of Real Private Consumption Growth
0.18
0.16
0.14
0.12
0.10
0.08
0.06
0.04
Developing Countries
0.02
Industrial Countries
0.00
0.00
0.02
0.04
0.06
0.08
Std Dev of Real GDP Growth
Source: WDI - World Bank.
0.10
0.12
0.14
0.16
Why are LDCs more volatile ?



Three broad ingredients:
External shocks – often bigger in LDCs (e.g.,
terms of trade)
Domestic shocks – e.g., fiscal policy volatility
(higher in LDCs) [Fatás – Mihov]
Weaker “shock absorbers” – especially financial
– part of the problem rather than the solution:


Shallow domestic financial systems
Weak international financial links
Both limit risk sharing / smoothing of shocks
 Pro-cyclical macro policies that amplify fluctuations
Volatility of Terms of Trade Growth
(Regional Medians)
20
18
16
(In Percent)
14
12
1960s
1970s
10
1980s
8
1990s
6
4
2
0
Industrialized
Econom ies
East Asia and
Pacific 7
Latin Am erica
and the
Caribbean
Middle East
and North
Africa
South Asia
Sub-Saharan
Africa
Other East
Asia and
Pacific
Fiscal volatility
Volatility of public consumption growth
(medians by group)
12
10
8
6
4
2
0
Low income
Midlde income
60s
Source: Montiel and Serven (2005)
70s
Industrial
80s
90s
All developing
Why are LDCs more volatile ?



Bigger external shocks + macro policy shocks +
lower financial development -- each accounts
for about 1/3 of “excess volatility” of LAC over
OECD (WB 2001)
More recent emphasis on micro-policies for
shock absorption: microeconomic regulation
(higher in LDCs) may hamper the reallocation of
resources following shocks
Empirically, evidence that tighter regulation
(product, labor) may raise aggregate volatility
[Loayza et al] – likely the opposite of what
regulation intended !
.06
Micro regulation
and
macro volatility
Overall
Regulation
Correlation: 0.41***
SLE
TGO
MWI
.04
IDN
PNG
THA
MYS KORTUR
ZMB ARG
PER
.02
URY
CHL
HTI
ZWE
MAR
JOR
VEN
NER
MEX
ECU
NICCIV
IRN
HND
DOM
BRA
PHL SEN
NGA
TUN
PAK
PAN
IND
PRY GMBMDG
BOL
CRI
SYR
BFA
EGY
0
COL
TTO
PRT
FIN
BWA
IRLISL SWE
KEN
JPN
CAN
ISRZAF SLV
AUS
GBR
NOR BEL ESP
GRC
DNK
JAM
ITA
AUT
FRA
USA CHE NLD
LKA
BGD
GHA
GTM
COG
.2
.3
.4
.5
Overall Regulation Index
Source: Loayza, Oviedo and Servén 2005
.6
.7
Volatility and crises

Some evidence that “crisis volatility” [extreme
adverse realizations] has become more
important in LDCs:



High incidence of extreme events in the 1990s
(growth collapses, sudden stops, banking crises…)
Both consumption and output growth display higher
skewness in the 1990s than before
Crisis volatility accounts for a rising portion of overall
volatility (which has itself declined)
Normal and extreme GDP growth volatility
Figure II.2. Structure of GDP Growth Volatility
(percent
of mean
totalofvolatility,
average
(percent,
77 developing
countries) of
77 LDCs)
80
70
60
50
40
30
20
10
0
61-70
71-80
Normal
81-90
Extreme
Sources: Hnatkovska and Loayza (2004); authors' calculations.
Crisis
91-00
Boom
Source:
Montiel and Serven (2005)
Notes: Total volatility = Normal + Extreme; Extreme = Crisis + Boom. Extreme shocks are defined as those exceeding two
standard deviations of output growth over the respective decade.
Exchange rate collapses
Figure II.10: Developing Countries: Exchange Rate Crises, 1963-2002
(% of LDCs undergoing
a Frankel-Rose
(relative frequency,
percent) exchange rate
crisis)
35
30
25
20
%
15
10
5
LDC (77)
MIDDLE (41)
2001
1999
1997
1995
1993
1991
1989
1987
1985
1983
1981
1979
1977
1975
1973
1971
1969
1967
1965
1963
0
LOW (33)
Source: IMF-IFS.
Source:
Servenrate
(2005)
Note: ForMontiel
this figureand
an exchange
crisis is defined as in Frankel and Rose (1996): a depreciation of the (average)
nominal exchange rate that (a) exceeds 25 percent, (b) exceeds the preceding year’s rate of nominal depreciation by at
least 10 percent, and (c) is at least three years apart from any previous crisis. The countries featured are those for which
data is available over the entire period shown.
Growth collapses
Recessions lowering real GDP by over 5 percent
(annual frequency, 77 countries)
25
20
15
low income
middle income
Source: Montiel and Serven (2005)
all developing
industrial
2002
1999
1996
1993
1990
1987
1984
1981
1978
1975
1972
1969
1966
1963
10
5
0
Sudden
stops in capital
Sudden
stopsflows
(relative frequency in percent)
(% of LDCs undergoing a sudden stop)
50
40
30
20
10
19
78
19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
0
low income
Source: Montiel and Serven (2005)
middle income
All developing
Banking crises
of systemic banking crises
(number
ofIncidence
LDCs
undergoing
a year)
systemic crisis)
(number
of developing
countries in crisis, per
22
20
18
14
12
10
8
6
4
2
ALL DEVELOPING (60)
Source: Caprio and Klingebiel (2003).
MIDDLE (35)
LOW (24)
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1989
1988
1987
1986
1985
1984
1983
1982
0
1981
Number of Crisis
16
Volatility and crises

Empirically, extreme volatility more harmful for
growth than “normal” volatility [Hnatkovska /
Loayza]



“Threshold effects”: volatility hampers growth only
when large enough. Aggregate volatility-investment
link negative only for high levels of volatility
Large adverse shocks more likely to make liquidity
constraints binding (and prevent restructuring)
Deep recessions more likely to lead to asset
destruction
Volatility and crises



Crises often the result of domestic policies /
rigidities magnifying external shocks [e.g.,
Argentina]
Some major crises of the 1990s [Gen 3] unlike
those of the 1980s: multiple equilibria under
financial fragilities – e.g., currency or time
mismatches making banks and firms vulnerable
to BoP runs and RER collapses
Emphasis on “crisis-proofing”: reducing
fragilities and increasing flexibility
Managing macro volatility
A strategy with several components:
 Reduce domestic policy-induced macro volatility
– e.g., fiscal volatility: fiscal institutions / rules
[“Fiscal Responsibility Laws”]
 Strengthen shock absorbers:




Countercyclical policies [e.g., Chile]
Reduce financial fragility by limiting mismatches – in
banks’ portfolios as well as their borrowers’
Move away from rigid exchange rate regimes
Enhance micro-flexibility – along with safety nets – to
adjust to shocks
Fiscal procyclicality
Procyclicality
of Public Consumption
(procyclicality of public
consumption,
15-year rolling windows,
(rolling 15-year windows, medians)
group medians)
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
-0.2
DEV (41)
Source: Montiel and Serven (2005)
G7
IND Non G7 (14)
20
00
19
99
19
98
19
97
19
96
19
95
19
94
19
93
19
92
19
91
19
90
19
89
19
88
19
87
19
86
19
85
19
84
19
83
19
82
-0.1
19
81
19
80
0.0
Managing macro volatility
…but after achieving all this still need to deal with
external shocks.
Three general options (Ehrlich-Becker):
1. Self-protection: lower exposure to risk (e.g., by
limiting specialization, “precautionary
recessions”)
2. Self-insurance: transfer resources across time
(e.g., commodity stabilization funds, foreign
reserve accumulation)
3. Insurance / hedging: transfer resources across
states of the world
Managing macro volatility
Three options for dealing with external shocks:
1. Self-Protection
2. Self-Insurance
3. Hedging /
Insurance
Source
of Volatility
 Trade diversification
(possibly away from
 Commodity
Terms of trade
stabilization funds
comparative
advantage)
 Strict current
account limits
[“precautionary
Capital flows
 Liquidity hoarding
recessions”]
 Capital controls
 Commodity-linked
options / futures
 Contingent credit
lines
In practice, few instruments to achieve # 3, so countries resort to # 1-2
Developing-country foreign
exchange reserves
$ billion
1800
Low-income countries
1600
Other middle-income countries
1400
China
1200
1000
800
600
400
200
0
1999
2000
2001
2002
2003
2004
Developing-country foreign
exchange reserves
Venezuela, Rep Bol de
India
Egypt
Indonesia
China
Brazil
Russian Federation
Argentina
Pakistan
0
6
12
18
Reserves as months of imports
24
Developing-country foreign
exchange reserves
Foreign Reserve / GDP by Region
35
30
25
20
%
15
10
5
0
All (154)
EAP (21)
ECA (44)
1997-98
LAC (30)
1999-00
2001-02
MENA (11)
2003-04
SAS (7)
SSA (41)
Managing macro volatility



Holding massive stocks of cash involves a huge
cost in terms of growth and consumption.
Big payoff to the development of new
instruments to hedge aggregate volatility exante – bigger than to developing ex-post crisis
resolution mechanisms
Even imperfect hedging by trading instruments
linked to world financial indicators (high yield
spread, commodity prices…) can be a big help
(Caballero-Panageas 2005)
Sudden stops:
Self-insurance vs hedging
Source: Caballero and Panageas 2005
Managing macro volatility

Why so few hedging instruments ?



Moral hazard (e.g., in GDP-linked securities)
Coordination problems in creating new markets
Potential role for IFIs:




A basic step: countercyclical lending (and aid
stability)
More lending in local currency – remove RER risk
Room for contingent credit lines ?
Lead the creation and trading of new financial
instruments for hedging
End
Domestic vs foreign factors
Across LDCs (unlike OECD), gov size not related
negatively to volatility – gov is source of shocks
(Suescún)
Fatas-Mihov: (discretionary) fiscal volatility reduces
LR growth [fiscal volatility is driven by political
constraints]
Pro-cyclicality not driven by political constraints (but
seems to matter less than volatility)
Micro regulation and macro volatility
Source: Loayza, Oviedo and Servén 2005
Micro regulation and macro volatility
Source: Loayza, Oviedo and Servén 2005
Estimated Welfare Gains from Diversification
COUNTRY
Argentina
Brazil
Chile
Colombia
Mexico
Peru
Venezuela, RB
Jamaica
United States
Germany
Japan
Spain
Ireland
Singapore
Thailand
Pakistan
Korea, Rep.
India
8.13%
9.49%
5.96%
4.87%
5.69%
6.34%
6.52%
26.39%
0.31%
0.98%
0.59%
0.70%
1.28%
6.98%
10.28%
3.93%
9.57%
1.01%
Note: Variances are over sample period 1990-01. Time
horizon is 35 years.
Source: World Bank staff calculations based on
Arthanasoulis and van Wicoop (2000).