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´Tale of two cities´
Latin America along the commodity price cycle: performance and challenges
Guillermo Perry
´All happy families are alike; each unhappy family is unhappy in its own way´
Ana Karenina, Leon Tolstoi.
Recent economic slowdown in all developing regions, especially in South America and, less so, in Mexico
*Also includes Afghanistan and PakistanSource: World Economic Outlook database, IMF projections, WEO April 2018
GDP growth rate (%)
Actualizada
6,5
2,0
3,4
3,4
6,6
-3.5
-1.5
0.5
2.5
4.5
6.5
8.5
10.5
12.5
14.5
Emerging and developing AsiaLatin America and the CaribbeanMiddle East, North Africa, Afghanistan, and PakistanSub-Saharan AfricaChina
2.31.91.5
-6
-4
-2
0
2
4
6
8
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
p
Mexico Central America South America
Mainly explained by the slump in commodity prices, after a long boom since 2003
Source: World Bank
0
20
40
60
80
100
120
140
160
180
Jan-
00Ap
r-00
Jul-0
0O
ct-0
0Ja
n-01
Apr-0
1Ju
l-01
Oct
-01
Jan-
02Ap
r-02
Jul-0
2O
ct-0
2Ja
n-03
Apr-0
3Ju
l-03
Oct
-03
Jan-
04Ap
r-04
Jul-0
4O
ct-0
4Ja
n-05
Apr-0
5Ju
l-05
Oct
-05
Jan-
06Ap
r-06
Jul-0
6O
ct-0
6Ja
n-07
Apr-0
7Ju
l-07
Oct
-07
Jan-
08Ap
r-08
Jul-0
8O
ct-0
8Ja
n-09
Apr-0
9Ju
l-09
Oct
-09
Jan-
10Ap
r-10
Jul-1
0O
ct-1
0Ja
n-11
Apr-1
1Ju
l-11
Oct
-11
Jan-
12Ap
r-12
Jul-1
2O
ct-1
2Ja
n-13
Apr-1
3Ju
l-13
Oct
-13
Jan-
14Ap
r-14
Jul-1
4O
ct-1
4Ja
n-15
Apr-1
5Ju
l-15
Oct
-15
Jan-
16Ap
r-16
Jul-1
6O
ct-1
6Ja
n-17
Apr-1
7Ju
l-17
Oct
-17
Jan-
18Ap
r-18
Mon
thly
indi
ces
base
d on
nom
inal
US
dolla
rs (2
010=
100)
Commodity Price Index
Energy
Agriculture
Other Metals andMinerals
Actualizada
That led to a boom and bust in Terms of Trade
Source: Citi Bank-World Bank
Terms of Trade Index (2002=100)
80
100
120
140
160
180
200
220
2000 2004 2008 2012 2016
ChileColombiaMexicoPeru
80
90
100
110
120
130
140
2000 2004 2008 2012 2016
Argentina
Brazil
50
100
150
200
250
300
Venezuela
Actualizada
We see today quite unhappy and less unhappy countries: differences are not fully explained by TOT
GDP growth rates (simple averages, %)*
*Less unhappy: Chile, Colombia, Mexico and Peru; Quite unhappy: Argentina, Brazil and Venezuela Source: World Economic Outlook database, IMF projections, WEO October 2017
-10
-5
0
5
10
15
1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017
Less unhappy countries Quite unhappy countries
GDP growth: The less unhappy ones look quite alike
GDP growth rate (%)
Source: World Economic Outlook database, IMF projections, WEO October 2017
-15
-10
-5
0
5
10
15
1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017
Chile Colombia Mexico Peru
GDP growth: The more unhappy ones look much less alike
Source: World Economic Outlook database, IMF projections, WEO October 2017
GDP growth rate (%)
-20
-15
-10
-5
0
5
10
15
20
25
1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017
Argentina Brazil Venezuela
An early symptom of unhappiness in Venezuela and Argentina: loss of reserves (ACT)
International Reserves (includes gold, % of GDP)
Source: World Development indicators, World Bank, Ministry of Finance of Chile
0
5
10
15
20
25
30
35
40
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
Chile (includes Gov's Funds) ColombiaBrazil MexicoPeru
0
5
10
15
20
25
30
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
Argentina Venezuela, RB
And sovereign risk hikesEMBI stripped spreads; end of period
(simple averages, basis points)
0
500
1,000
1,500
2,000
2,500
3,000
3,500
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Less unhappy countries Quite unhappy countries
*Less unhappy: Brazil, Chile, Colombia, Mexico and Peru; Quite unhappy: Argentina and Venezuela Source: Banco de Bogotá, JP Morgan
Spreads: The less unhappy bunch look again quite alike
Source: Bloomberg, JP Morgan
EMBI stripped spreads; end of period (basis points)
0
200
400
600
800
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Chile Colombia Mexico Peru
Spreads: The very unhappy ones again look less alike
Source: Bloomberg, JP Morgan
EMBI stripped spreads; end of period (basis points)
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Argentina Brazil Venezuela
A closer look to the less unhappy bunch and Brazil: Credit Default Swaps (ACT)
Source: Bloomberg
5-Year Credit Default Swaps (basis points)
93,7
146,3
100,3
44,566,9
30
80
130
180
230
280
330
380
430
480
530
Mar
-13
May
-13
Jul-1
3
Sep-
13
Nov
-13
Jan-
14
Mar
-14
May
-14
Jul-1
4
Sep-
14
Nov
-14
Jan-
15
Mar
-15
May
-15
Jul-1
5
Sep-
15
Nov
-15
Jan-
16
Mar
-16
May
-16
Jul-1
6
Sep-
16
Nov
-16
Jan-
17
Mar
-17
May
-17
Jul-1
7
Sep-
17
Nov
-17
Jan-
18
Colombia Brasil México Chile Perú
Two macroeconomic factors behind differences in unhappiness:
Fiscal deficits andexchange rate regimes and interventions
Behind deep unhappiness: fiscal deficitsGeneral Government Net Lending/Borrowing
(% of GDP)
*Less unhappy: Brazil, Chile, Colombia, Mexico and Peru; Quite unhappy: Argentina and Venezuela Source: World Economic Outlook database, IMF Projections, WEO April 2018
-20
-15
-10
-5
0
5
2001 2003 2005 2007 2009 2011 2013 2015 2017
Happy countries Unhappy countries
Actualizada
Some differences in fiscal deficits among the less unhappy
General Government Net Lending/Borrowing (% of GDP)
Source: World Economic Outlook database, IMF Projections, WEO April 2018
-8
-6
-4
-2
0
2
4
6
8
10
2001 2003 2005 2007 2009 2011 2013 2015 2017
Chile Colombia México Perú
Actualizada
Wider fiscal deficits and differences among the very unhappy
General Government Net Lending/Borrowing (% of GDP)
Source: World Economic Outlook database, IMF Projections, WEO April 2018
-35
-30
-25
-20
-15
-10
-5
0
5
10
2001 2003 2005 2007 2009 2011 2013 2015 2017
Argentina Brasil Venezuela
Actualizada
Sovereign debt levels are also a concern in Brazil
Source: World Economic Outlook database, IMF projections, WEO April 2018
0
20
40
60
80
100
120
140
160
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Argentina Brasil Chile
Colombia México Perú
Venezuela
General Government Gross Debt (% of GDP)
Actualizada
Argentina and Venezuela attempted to keep nominal exchange rates constant but had sharp recent devaluations
Source: Banco de Bogotá, author’s calculations
Nominal Exchange Rate (year-on-year variation, %)
-200
0
200
400
600
800
1,000
1999 2001 2003 2005 2007 2009 2011 2013 2015 2017
Argentina Venezuela
Both had inflationary pressures since the beginning of the boom; Venezuela has hyperinflation now
Source: Bloomberg. *Data for Argentina is extracted from independent sources
Inflation, end of period (year-on-year variation, %)
0
200
400
600
800
1,000
1,200
0
5
10
15
20
25
30
35
40
45
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Argentina* Venezuela (right axis)
Their Real Exchange Rates did not appreciate much during the early boom but showed significant
appreciation latter, even during the bust.
Source: FRED-BIS.
Real Exchange Rate Index (2010=100)
30
50
70
90
110
130
Apr-0
2
Apr-0
3
Apr-0
4
Apr-0
5
Apr-0
6
Apr-0
7
Apr-0
8
Apr-0
9
Apr-1
0
Apr-1
1
Apr-1
2
Apr-1
3
Apr-1
4
Apr-1
5
Apr-1
6
Apr-1
7
Apr-1
8
Brazil Argentina
0
500
1000
1500
2000
2500
3000
3500
Apr-0
2
Apr-0
3
Apr-0
4
Apr-0
5
Apr-0
6
Apr-0
7
Apr-0
8
Apr-0
9
Apr-1
0
Apr-1
1
Apr-1
2
Apr-1
3
Apr-1
4
Apr-1
5
Apr-1
6
Apr-1
7
Apr-1
8
Venezuela
Actualizada
Major differences in Real Exchange Rate performance between Inflation Targetting and non-IT countries
*Happy Countries: Brazil, Chile, Colombia, Mexico and Peru; Unhappy Countries: Argentina and Venezuela Source: FRED-BIS
Real Exchange Rate Index (2010=100)
75
80
85
90
95
100
105
110
0
200
400
600
800
1000
1200
1400
1600
1800Unhappy Countries (LHS) Happy Countries
Actualizada
Some differences in Real Exchange Rate performance among IT countries: Chile and Peru appreciated less than Brazil and Colombia during the boom, in spite of higher TOT gains.
Source: FRED-BIS.
Real Exchange Rate Index (2000 jan=100)
35
55
75
95
115
135
155
175 Brazil Chile Colombia Mexico Peru
Actualizada
Due to the fact that Perú and Chile had both fiscal surpluses and higher accumulation of reserves
International Reserves as % of GDPGeneral Government Net Lending/Borrowing (% of GDP)
-15
-10
-5
0
5
10
2001 2003 2005 2007 2009 2011 2013 2015 2017
Argentina Brasil Chile
Colombia Perú
0
5
10
15
20
25
30
35
1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017
Brasil Chile
Colombia Perú
Source: FRED, Banco Central de Chile, Banco Central del Perú, Banco Central de Colombia, WEO April 2018 projections, IMF. Actualizada
As a consequence, there were sharper recent compensatory nominal devaluations in Brazil and Colombia
Source: Banco de Bogotá, FRED, Banco Central de Chile, Banco Central Perú y Banco de la República de Colombia
Nominal Exchange Rate (year-on-year variation, %)
-30
70
1999 2001 2003 2005 2007 2009 2011 2013 2015 2017
Brasil Chile Colombia México Perú
Actualizada
That contributed to recent inflationary pressures
Inflation, end of period (year-on-year variation, %)
Source: Bloomberg
-2
0
2
4
6
8
10
12
14
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Brasil Chile Colombia Mexico Peru
And led Brazil’s and (less so) Colombia’s Central Banks to adopt pro cyclical interest rate hikes (Mexico in 2016: Trump effect)
Monetary Policy Rate, end of period (%)
Source: Bloomberg
0
5
10
15
20
25
30
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Brasil Chile Colombia Mexico Peru
Not surprisinglyDUTCH DISEASE symptoms were
higher in COLOMBIA and BRAZIL than in PERU and CHILE:
Exports (% of total exports)
Source: WDI, World Bank
0
10
20
30
40
50
60
70
80
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
Colombia
Manufactures exportsFuel and Mineral exportsAgricultural raw materials exports
0
10
20
30
40
50
60
70
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
Brazil
Agricultural raw materials exports
Manufactures exports
Fuel and Mineral exports
0
10
20
30
40
50
60
70
80
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
Chile
Agricultural raw materials exports
Manufactures exports
Fuel and Mineral exports
0
10
20
30
40
50
60
70
80
90
Mexico
Agricultural raw materials exports
Manufactures exports
Fuel and Mineral exports
0
10
20
30
40
50
60
70
80
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
Perú
Agricultural raw materials exports
Manufactures exports
Fuel and Mineral exportsActualizada
Source: WDI, World Bank
Not surprisinglyDUTCH DISEASE symptoms were
higher in COLOMBIA and BRAZIL than in PERU and CHILE :Production (value
Added, %GDP)
29.4
32.6
15.0
12.6
0
10
20
30
40
50
60
70
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
Colombia
Agriculture Industry
Manufacturing Services
26.721.2
15.3
11.7
0
10
20
30
40
50
60
70
80
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
Brazil
Agriculture Industry
Manufacturing Services
34.9 32.7
20.3 19.1
0
10
20
30
40
50
60
70
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
Mexico
Agriculture Industry
Manufacturing Services
34.631.3
18.6
12.0
0
10
20
30
40
50
60
70
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
Chile
Agriculture Industry
Manufacturing Services
31.9 32.5
16.713.9
0
10
20
30
40
50
60
70
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
Perú
Agriculture Industry
Manufacturing ServicesActualizada
The key macro lessons• As expected, flexible exchange rate regimes operated as
important shock absorbers. Countries with fixed exchange rateregimes (Argentina and Venezuela) had higher variability of growth and inflation
• But significant Real Exchange Rate appreciations and depreciations created serious Dutch Disease, adjustment and inflationary costs during the commodity price cycle in Brazil and Colombia.
• Perú and Chile mitigated them through a combination of countercyclical fiscal and monetary policies and ´against the wind´exchange market interventions by central banks (´dirty´ floating) and thus suffered less DD and inflationary problems
Vulnerabilities to potential external shocks
FED interest rate hikes will impose threats to capital flows to Emerging Markets, with high external and fiscal vulnerabilities
Source: IMF, REO April 2017
Capital Flows in Emerging Markets (percent of trend GDP; median)
Though gross capital inflows are highly correlated with commodity prices in South America : a China
hard landing would impose huge risks.
Source: IMF, REO April 2017
Gross Inflows and Commodity Prices (percent of trend GDP; median)
Protectionist policies in the US would affect countries with high trade links: Mexico and Central A merica
Source: IMF, REO April 2017
South America has lower exposure to the US –mostly through commodities-, compared with Central America and Mexico
Brazil, Argentina and Chile export more manufactured goods to the US, compared to Peru and Colombia
Remittances and Direct Investment from the US are also quite high, especially to Mexico
Source: IMF, REO April 2017
A matrix of global risksfor Latin American Countries
Sources: Deutsche Bank, Bank of América, own estimates.36
Potentialimpact
Likely medium term impactLikely short run impact
A China hard landing and an additional fallin commodity prices
A showdown withCatalonia
Market turbulence due to FED hikesand balance sheet contraction
TerroristAttacks
Confrontation withNorth Corea
US protectionism
Market turbulencedue to a bank crisis
in Italy
Europeanslowdown due to
Brexit
US stock marketPrice collapse
Budget stalemate in US
Elections in LatinAmerica 2018
PolíticalRisks
EconomicRisks
Trump threats and actions1. Trade war against China
– Immediate effect: financial market volatility, postponment of investmentdecisions and reduction of capital flows to emerging markets
– Potential effects: slowdown of US and China trade and growth; slowdown of global trade; reduction of commodity prices; weakening of multilateralism(WTO, IMF)
2. Threats against Mexico, NAFTA, immigration– Observed effects in México: reduction of investment and capital flows ;
currency depreciation and rise in inflation; rise in interest rates; growthslowdown
– Potential effects: reduction of NAFTA trade; reduction in remittances to México; loss of competitiveness of some US manufacturing sectors; further growthslodown in México
3. Trump tax reform– US: higher short term investment but higher future uncertainty , due to higher
public debt– LA: reduction of FDI; some capital outflows; policy dilemmas (lower corporate
taxes vs fiscal sustainability)
The key challenge going forward:
productivity growth
The key long term challenge: closing the productivity gap
Source: Grazzi, M. & Pietrobelli, C., “Firm Innovation and Productivity in Latin America and the Caribbean”, IDB, June 2016
Growthin LatinAmericahas beendrivenbycapital and labor growth, not by total factor productivity growth
This will have to change: as investmentrates are already high in several countries..
5.0
10.0
15.0
20.0
25.0
30.0
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017p
Investment (% of GDP)
Argentina Brazil Chile Colombia Mexico Peru
Source: World Economic Outlook database, IMF projections, WEO October 2017
And the demographic bonus will soon be over
0
10
20
30
40
50
60
70
Brazil Chile Colombia Mexico Peru Venezuela, RB Argentina
Population ages 15-64 (% of total population, averages)
1970-1979 1980-1989 1990-1999 2000-2009 2010-2016
Source: World Development Indicators, World Bank
Summing Up1. The growth boom and posterior slowdown in most Latin American countries is
basically explained by the cycle of commodity prices (plus high international liquidity and low international interest rates).
2. Countries that saved more in the boom (fiscal surplus and reserve accumulation), like Chile and Peru, had lower symptoms of Dutch Disease, have had to engage in less painful fiscal and monetary pro cyclical adjustments in the bust and have now lower vulnerabilities to additional shocks.
3. Venezuela and Argentina engaged in unsustainable macro policies (and anti private sector micro policies) and lost access to international capital markets (and had sharp reserve losses) well before the fall in commodity prices. Venezuela is in full implosion while the new regime in Argentina is trying to cope.
4. Brazil problems began after 2013 (fiscal relaxation and temper tantrum) and were then aggravated by the political crisis.
5. The key going forward are increases in productivity: no tale winds in the horizon and lower capital and labour growth!
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