International Monetary Fund World Economic Outlook October 2012
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International Monetary Fund World Economic Outlook October 2012 Resilience in Emerging Market and Developing Economies: Will It Last? Abdul Abiad, John Bluedorn, Jaime Guajardo, and Petia Topalova with support from Angela Espiritu and Katherine Pan
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International Monetary Fund World Economic Outlook October 2012. Resilience in Emerging Market and Developing Economies: Will It Last?. Abdul Abiad, John Bluedorn, Jaime Guajardo, and Petia Topalova with support from Angela Espiritu and Katherine Pan. - PowerPoint PPT Presentation
Transcript of International Monetary Fund World Economic Outlook October 2012
International Monetary FundWorld Economic OutlookOctober 2012
Resilience in Emerging Market andDeveloping Economies: Will It Last?
Abdul Abiad, John Bluedorn, Jaime Guajardo, and Petia Topalovawith support from Angela Espiritu and Katherine Pan
EMDEs have done well over the past decade,and through the global crisis
2
-6
-4
-2
0
2
4
6
8 Growth of Real GDP per Capita
Emerging Market and Developing Economies
Advanced Economies
Perc
ent
-3
-2
-1
0
1
2
3
4
5
Emerging Market and Developing Economies
Advanced Economies
World GrowthPe
rcen
t
Contribution to Growth in World Real GDP per Capita
Source: World Economic Outlook database.
EMDE resilience has improved since the 1970s and 1980s.
3
Peak t + 1 t + 2 t + 3 t + 4 t + 5 t + 6 t + 7 t + 8 t + 9 t + 1080
90
100
110
120
130
140Emerging Market and Developing Economies
Peak t + 1 t + 2 t + 3 t + 4 t + 5 t + 6 t + 7 t + 8 t + 9 t + 1080
90
100
110
120
130
140 Advanced Economies
Dynamics of Output per Capita Following Peaks
50s and 60s 70s and 80s 1990s Great Recession2000–06
Years Years
4
In fact, from the 2000s, EMDEs spent more time in expansion—and had smaller downturns—than AEs
Advanced Economies Emerging Market and Developing Economies
0
20
40
60
80
100 Time Spent in Expansion
Perc
ent
Advanced Economies Emerging Market and Developing Economies
-25
-20
-15
-10
-5
0
5
Perc
ent
Median Downturn (Peak-to-Trough Amplitude)
50s and 60s 70s and 80s 1990s 2000s
Source: IMF staff calculations.
5
While AE growth in expansion has fallen over time, EMDE growth in expansion has been more stable.
0
1
2
3
4
5 Median Growth in Real GDP per Capita during Expansion
Per
cen
t
Source: IMF staff calculations.
50s and 60s 70s and 80s 1990s 2000s
6
Unpacking further, what factors are associated with greater resilience?
We look at three broad areas:• External and domestic shocks• Policy frameworks and policy space• Structural characteristics
Analytical approach: Look at how these factors affect the length of expansions and the speed of recoveries using standard tools of duration analysis
• Bivariate – consider factors one-by-one• Multivariate – consider multiple factors simultaneously
7
Shocks, both external and domestic, tend to bring EMDE expansions to an end…
Average Probability of Expansion Coming to an End
EXTERNAL SHOCKS
Spike in global uncertainty*
Large rise in U.S. real interest rates*
Recessions in AEs*
Sudden stop in capital flows*
Terms-of-trade bust*
DOMESTIC SHOCKS
Banking crisis*
Credit boom*
0 5 10 15 20 25 30 35
With shockWithout shock
Percent
Source: IMF staff calculations.Note: Statistically significant differences at the 10 percent level are denoted by starred labels.
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…but improved policy frameworks and enhanced policy space help prolong expansions, and hasten recoveries…
Effects of Policies on Expansion Duration
POLICY FRAMEWORKS
Inflation targeting*
Countercyclical fiscal policy*
Nonpegged exchange rate*
POLICY SPACE
Low inflation*
Fiscal surplus*
Low public debt
Current account surplus*
Low external debt*
High reserves*
0 2 4 6 8 10 12 14 16
With characteristic Without characteristic
Years
Effects of Policies on Speed of Recovery
POLICY FRAMEWORKS
Inflation targeting*
Countercyclical fiscal policy*
Nonpegged exchange rate
POLICY SPACE
Low inflation*
Fiscal surplus
Low public debt*
Current account surplus*
Low external debt*
High reserves*
0 2 4 6 8 10 12 14 16
With characteristic Without characteristic
Years
Source: IMF staff calculations.Note: Statistically significant differences at the 10 percent level are denoted by starred labels. Recovery is defined as the number of years required to get back to pre-downturn levels of per capita output.
…while structural characteristics are more of a mixed bag, with fewer robust relationships.
9
Effects of Structural Characteristics on Expansion Duration
Trade openness
Trade liberalization
High intra-EMDE exports
High financial integration
High capital account openness
High FDI flows*
Low income inequality*
0 2 4 6 8 10 12 14 16
With characteristic Without characteristicEffects of Structural Characteristics on Recovery Duration
Trade openness*
Trade liberalization
High intra-EMDE exports*
High financial integration*
High capital account openness*
High FDI flows*
Low income inequality
0 2 4 6 8 10 12 14 16
With characteristic Without characteristic
Source: IMF staff calculations.Note: Statistically significant differences at the 10 percent level are denoted by starred labels. Recovery is defined as the number of years required to get back to pre-downturn levels of per capita output.
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Improved performance from the 1980s to the 2000s has been mainly due to policies and policy space
Externalshocks
Domesticshocks
Policies Structure Total-20
-10
0
10
20
30
40
50
Perc
ent
Contribution to Change in Expected Mean Duration of Expansions from 1980s to 2000–07
Source: IMF staff calculations.
0
3
6
9
12
15
18
Year
s
Expected Mean Duration of Expansions
1990s 2010–11
11
Concluding remarks
EMDE resilience is not a recent phenomenon; it has been building over many years. Not just in EMs, but low-income countries as well
Better policymaking has a lot to do with it
But resilience cannot be taken for granted:
• These economies remain vulnerable to external and domestic shocks• Policy space, partly used up in response to the 2008-09 crisis, needs to be
rebuilt• Improvements in policymaking (e.g., greater ER flexibility, more countercyclical
policies, inflation targeting) should be maintained
It is not just a commodity story…
13
Peak t + 1 t + 2 t + 3 t + 4 t + 5 t + 6 t + 7 t + 8 t + 9 t + 1080
90
100
110
120
130Noncommodity Exporters
Peak t + 1 t + 2 t + 3 t + 4 t + 5 t + 6 t + 7 t + 8 t + 9 t + 1080
90
100
110
120
130 Commodity Exporters
Dynamics of Output per Capita Following Peaks
Years Years
50s and 60s 70s and 80s 1990s Great Recession2000–06
…nor is it only for the largest EMDEs.
14
Peak t + 1 t + 2 t + 3 t + 4 t + 5 t + 6 t + 7 t + 8 t + 9 t + 1080
90
100
110
120
130Other EMDEs(excluding the largest)
Peak t + 1 t + 2 t + 3 t + 4 t + 5 t + 6 t + 7 t + 8 t + 9 t + 1080
90
100
110
120
130 Largest EMDEs1
Dynamics of Output per Capita Following Peaks
1Refers to the 30 largest emerging market and developing economies based on their average real GDP over the sample period.Years Years
50s and 60s 70s and 80s 1990s Great Recession2000–06
Among EMDEs, EMs did better from the 1990s,while LICs improved most from the 2000s.
15
Peak t + 1 t + 2 t + 3 t + 4 t + 5 t + 6 t + 7 t + 8 t + 9 t + 1080
90
100
110
120
130
140Low-income Countries
Peak t + 1 t + 2 t + 3 t + 4 t + 5 t + 6 t + 7 t + 8 t + 9 t + 1080
90
100
110
120
130
140 Emerging Market Economies
Dynamics of Output per Capita Following Peaks
Years Years
50s and 60s 70s and 80s 1990s Great Recession2000–06
Among regions, EMD Asia and Latin America have seen the most dramatic improvements.
16
Peak t + 1 t + 2 t + 3 t + 4 t + 5 t + 6 t + 7 t + 8 t + 9 t + 1080
90
100
110
120
130
140Latin America
Peak t + 1 t + 2 t + 3 t + 4 t + 5 t + 6 t + 7 t + 8 t + 9 t + 1080
90
100
110
120
130
140 Emerging and Developing Asia
Dynamics of Output per Capita Following Peaks
Years Years
50s and 60s 70s and 80s 1990s Great Recession2000–06
Sub-Saharan Africa also improved, but mostly in the 2000s. CIS-EM Europe was derailed by the crisis.
17
Peak t + 1 t + 2 t + 3 t + 4 t + 5 t + 6 t + 7 t + 8 t + 9 t + 1080
90
100
110
120
130
140Commonwealth of Independent States and Emerging Europe
Peak t + 1 t + 2 t + 3 t + 4 t + 5 t + 6 t + 7 t + 8 t + 9 t + 1080
90
100
110
120
130
140 Sub-Saharan Africa
Dynamics of Output per Capita Following Peaks
Years Years
50s and 60s 70s and 80s 1990s Great Recession2000–06
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What is behind the gains in EMDE resilience?Higher steady-state growth and lower variability
Advanced Economies Emerging Market and Developing Economies
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0 Median Steady-State Growth
Perc
ent
Advanced Economies Emerging Market and Developing Economies
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0Median Growth Variability
Perc
ent
50s and 60s 70s and 80s 90s and 2000s
Source: IMF staff calculations.
Why has performance improved? Some shocks have become less frequent, others more frequent…
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Relative frequency of shock in EMDEs (percent)
1970s1980s1990s 2000–07
2008–09
2010–11
0
20
40
60
80
100
120 Spikes in Global Uncertainty
0
1
2
3
4
5 Banking Crises
0
3
6
9
12
15 Credit Booms
1970s1980s1990s 2000–07
2008–09
2010–11
0
2
4
6
8
10
12 Sudden Stops in Capital Flows
1970s1980s1990s 2000–07
2008–09
2010–11
0
20
40
60
80
100
120 Recessions in AEs
…but EMDE policy frameworks have improved, and policy space has increased.
20
Share of EMDEs with characteristic (percent)
1970s1980s1990s 2000–07
2008–09
2010–11
0
10
20
30
40
50
60 Pegged Exchange Rate
1970s1980s1990s 2000–07
2008–09
2010–11
0
10
20
30
40
50 Countercyclical Fiscal Policy
1970s1980s1990s 2000–07
2008–09
2010–11
0
3
6
9
12
15
18 Inflation Targeting
1970s1980s1990s 2000–07
2008–09
2010–11
0
20
40
60
80
100 High International Reserves
1970s1980s1990s 2000–07
2008–09
2010–11
0
20
40
60
80
100 Low Public Debt
1970s1980s1990s 2000–07
2008–09
2010–11
0
30
60
90 Single-Digit Inflation
Structural factors are mixed – some are more supportive, others less so.
21
1970s1980s1990s 2000–07
2008–09
2010–11
0
20
40
60
80
100
120 High Financial Integration
0
20
40
60
80
100
120 High Trade Openness
0
20
40
60
80
100
120 High Intra-Emerging Market and Developing Economies
Trade
1970s1980s1990s 2000–07
2008–09
2010–11
0
30
60
90 High Net Foreign Direct Investment
1970s1980s1990s 2000–07
2008–09
2010–11
0
10
20
30
40
50
60
70 Low Income Inequality
Share of EMDEs with characteristic (percent)
Mixed patterns in other factors
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Relative frequency of shock in EMDEs (percent)
1970s1980s1990s 2000–07
2008–09
2010–11
0
10
20
30
40
50 Current Account Surplus
05
101520253035 Terms-of-Trade Busts
0
20
40
60
80 Spikes in U.S. Real Short-Term Interest Rate
1970s1980s1990s 2000–07
2008–09
2010–11
0
20
40
60
80 Low External Debt
1970s1980s1990s 2000–07
2008–09
2010–11
0
5
10
15
20
25
30 Fiscal Surplus
Share of EMDEs with characteristic (percent)
What Ends Expansions?Explanatory Variable
ExpansionsAll Years Z statistic Pre-1990 Z statistic Post-1989 Z statistic
Implied S&P 100 Volatility (VXO)1 0.951*** [-4.179] 0.981 [-0.985] 0.943*** [-4.565]U.S. Ex Ante Real Interest Rate 0.956 [-1.461] 0.993 [-0.158] 0.835*** [-3.479]Terms-of-Trade-Bust Indicator 0.968 [-0.214] 0.802 [-1.034] 1.134 [0.740]Sudden Stop (capital inflows) Indicator 0.590*** [-2.927] 0.497* [-1.885] 0.841 [-1.254]Advanced Economy Recession Indicator 0.642*** [-4.074] 0.668** [-2.420] 0.680* [-1.911]Credit Boom during Past Three Years 0.616*** [-3.913] 0.591*** [-2.621] 0.705*** [-2.610]Banking Crisis Indicator 0.550*** [-3.376] 0.504*** [-3.302] 0.538*** [-2.830]Single-Digit Inflation Indicator 1.473*** [3.185] 1.574** [2.474] 1.276** [2.102]Low Public Debt to GDP Indicator 1.009 [0.0713] 0.998 [-0.0117] 1.019 [0.132]International Reserves to GDP 1.009*** [2.866] 1.006 [1.289] 1.004 [0.903]Income Inequality (Gini coefficient) 0.986** [-2.144] 0.976*** [-2.833] 0.997 [-0.459]Trade Openness (exports plus imports to GDP) 0.999 [-0.451] 1.001 [0.373] 1.000 [-0.170]Financial Openness (external assets plus liabilities to GDP) 0.999*** [-3.121] 0.999*** [-4.840] 1.000 [-0.549]Observations 1,264Number of Episodes 188Number of Exits 126Number of Economies 75Weibull Shape Parameter 1.516 1.408 2.277Z statistic of Shape Parameter 6.829 3.258 2.928Log Likelihood -103.0 -88.1Model Chi-Squared p Value 0.000 0.000Source: IMF staff calculations. Note: Exponentiated coefficients shown are time ratios, which indicate whether the variable tends to shorten (less than 1) or lengthen (greater than 1) the expected time-in-episode. Z statistics are given in brackets underneath the coefficient estimates. A negative z statistic indicates that the associated variable tends to shorten an episode; if the z statistic is positive, it tends to lengthen an episode. *, **, and *** denote significance at the 10 percent, 5 percent, and 1 percent levels, respectively. 1VXO = Chicago Board of Exchange S&P 100 volatility index.
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Across regions and groups, some differences in drivers of improved resilience, but overall similar.
Exte
rnal
sho
cks
Do
mes
tic
sho
cks
Po
licie
s
Stru
ctu
ral
char
acte
risti
cs
Tota
l -20
-10
0
10
20
30
40
50Latin America
Per
cen
t
Source: IMF staff calculations.
Contribution of Shocks, Policies, and Structure to the Length of ExpansionsEx
tern
alsh
ock
s
Do
mes
tic
sho
cks
Po
licie
s
Stru
ctu
ral
char
acte
risti
cs
Tota
l-20
-10
0
10
20
30
40
50 Emerging and Developing Asia
Per
cen
t
25
Across regions and groups, some differences in drivers of improved resilience, but overall similar.
Source: IMF staff calculations.
Contribution of Shocks, Policies, and Structure to the Length of ExpansionsEx
tern
alsh
ock
s
Do
mes
tic
sho
cks
Po
licie
s
Stru
ctu
ral
char
acte
risti
cs
Tota
l-20
-10
0
10
20
30
40
50 Sub-Saharan Africa
Per
cen
t
Exte
rnal
shoc
ks
Dom
estic
shoc
ks
Polic
ies
Stru
ctur
alch
arac
teri
stics
Tota
l -20
-10
0
10
20
30
40
50Heavily Indebted Poor Countries
Perc
ent
26
And it’s not just commodities…
Source: IMF staff calculations.
Contribution of Shocks, Policies, and Structure to the Length of Expansions
Exte
rnal
shoc
ks
Dom
estic
shoc
ks
Polic
ies
Stru
ctur
alch
arac
teri
stics
Tota
l -20
-10
0
10
20
30
40
50Noncommodity Exporters
Perc
ent
Exte
rnal
shoc
ks
Dom
estic
shoc
ks
Polic
ies
Stru
ctur
alch
arac
teri
stics
Tota
l-20
-10
0
10
20
30
40
50 Commodity Exporters
Perc
ent
