An introduction to Latin America André Loes Executive Director FGC

Middle-income, resource-rich countries, with low investment and poor education

• Most of resource-rich LatAm has reached what the World Bank defines as upper middle-income status (GNI per capita between USD 4,036 and USD 12,475); Chile and Uruguay already at high-income status

• Economists see the upper middle-income range as a trap, as next step implies moving towards more value added activities, requiring high investment and better education, in order to boost productivity ‒ Investment/GDP remains low compared to developing Asia ‒ LatAm scores quite poorly on the PISA exam, and the velocity of the improvement is not inspiring

Scores on the 2015 PISA Exam Investment as % of GDP (average 1Q15 to 4Q16)

Source: OECD Source: Bloomberg and IMF

13,4

16,6

22,9 24,1 21,4

23,6

15,5

19,3

Argentina Brazil Chile Colombia Mexico Peru Paraguay Uruguay

40

9

37

7 42

3

39

0

40

0

40

8 4

90

38

7

41

8

42

5

40

7 45

9

42

5

42

7

42

3 4

93

39

8

43

7

43

2

40

1 44

7

41

6

42

0

41

6 4

93

39

7

43

5

Argentina Brazil Chile Colombia Costa Rica Mexico OECDaverage

Peru Uruguay

Maths Reading Science

Commodities a key element of LatAm’s international trade…

• South American economies present a significant participation of commodities in their exports ‒ Soft commodities affect mainly the southern cone countries, such as Argentina, Brazil, Paraguay and Uruguay ‒ Metals are key for countries like Chile and Peru, and to a lesser extent to Brazil ‒ Oil & gas heavily affect Colombia’s and Venezuela’s exports, potentially important for Argentina given its shale gas reserves

• Mexico a manufacturing exporter, an exception in the region – trend initiated after the inception of NAFTA

South America primary exports, by product (as of 2015) LatAm exports, selected countries (as of 2015)

Source: UNCTAD; Products presented according to SITC classification Source: UNCTAD; Products presented according to Lall classification

Exports of primary goods and resource based manufactures

Exports of manufactured goods

Argentina 73.4% 26.6%

Brazil 68.1% 31.9%

Chile 91.2% 8.8%

Colombia 78.5% 21.5%

Costa Rica 48.2% 51.8%

Mexico 18.1% 81.9%

Paraguay 89.5% 10.5%

Peru 87.9% 12.1%

Uruguay 80.1% 19.9%

Venezuela 94.1% 5.9%

Food 45,2%

Iron and ores 22,8%

Fuel 22,5%

Others 9,5%

… with impacts going far beyond trade

• In the smaller countries of South America, commodities affect the broader economy and fiscal accounts ‒ Wealth effect and currency swings affect private consumption ‒ Viability of new projects (for which the price of the commodity is a key element) affects fixed investments

• Impact of commodities on fiscal accounts quite relevant in South American smaller economies, less important in larger commodity countries such as Brazil; in Venezuela the dependence is extreme

• In Mexico, oil retains significant influence on fiscal accounts despite preponderance of industry

Fiscal revenues from commodities (% of GDP) Carteras inversionales de la última década

Source: IMF Regional Economic Overview, Western Hemisphere, April 2016, Chart 2.17 Source: Inversion en la minería Chilena – Cartera de proyectos 2016/2015, Cochilco, DEPP 17/2016

The recent commodity super cycle has been powered by the rise of China

• Commodity prices have been materially influenced by more than one decade of very strong China growth • With the slowdown of China, commodity prices dropped and should remain at a lower level for a while

Commodity prices (4Q202=100) and China GDP growth Effect of Chinese demand on commodity prices

Source: Bloomberg and IMF Source: Jenkins, R., The China effect on commodity prices and Latin American export earnings, Cepal Review 103, 2011, compiled from tables 3 and 4, page 80

China's demand effect* China price effect**

Crude Oil 2.7 10.8

Iron Ore 38.4 96.0

Copper 12.3 49.1

Soybean 3.1 5.1

Coffee 0.1 0.2

Sugar 1.5 3.1

Beef 2.0 3.3

* How much higher demand was in 2007 than it would have been if the demand in China had grown as in the rest of the world in 2002-2007

** How much higher price was in 2007 than it would have been if the demand in China had grown as in the rest of the world in 2002-2007

4%

6%

8%

10%

12%

14%

16%

20

02

Q4

20

03

Q3

20

04

Q2

20

05

Q1

20

05

Q4

20

06

Q3

20

07

Q2

20

08

Q1

20

08

Q4

20

09

Q3

20

10

Q2

20

11

Q1

20

11

Q4

20

12

Q3

20

13

Q2

20

14

Q1

20

14

Q4

20

15

Q3

20

16

Q2

0

100

200

300

400

500

600

700

China GDP (%) Brent Oil Copper Soybean

Rising trade between LatAm and China means increased synchronicity

• China now the main trade partner of a number of LatAm countries; volumes increased, not only prices • Synchronicity of cycles of China and LatAm increased over time; some countries now heavily influenced • US remains quite relevant for the region as well, vital in the case of Mexico and Central American countries • Having two different external drivers is good for LatAm; US and China cycles are less synchronized

Long term elasticity of LatAm growth to 1% change in China growth China and US as export destinations for LatAm countries

Source: Cesa-Bianchi, A. et alli, China’s emergence in the world economy and business cycles in Latin America, IADB working paper 266, 2011, pages 31 and 32

Source: UNCTAD

China United States

1995 2005 2015 1995 2005 2015

Argentina 1.36% 7.86% 9.12% 8.60% 11.40% 6.03%

Brazil 2.59% 5.77% 18.63% 18.92% 19.24% 12.67%

Chile 1.81% 11.66% 26.31% 13.45% 16.00% 13.04%

Colombia 0.43% 1.12% 6.34% 35.56% 41.77% 28.17%

Costa Rica 0.92% 5.82% 5.08% 45.67% 33.17% 35.01%

Mexico 0.05% 0.53% 1.28% 83.40% 85.82% 81.18%

Paraguay 2.42% 2.82% 0.49% 4.61% 2.56% 2.17%

Peru 6.42% 10.87% 22.06% 17.23% 30.72% 15.10%

Uruguay 5.86% 3.56% 13.92% 6.00% 23.13% 6.87%

Venezuela 0.08% 1.40% 13.84% 51.79% 60.04% 34.53% 0,34

0,23

0,19

0,17

0,06

0,14

0,14

0,15

0,03

-0,05

Chile

Argentina

Peru

Brazil

Mexico1995

2009

LatAm emerges from commodity super cycle slightly better than in the past…

• In LatAm, strong commodity cycles historically led to wrong economic policies, current account deterioration and eventually the depletion of reserves and external debt crisis; this time it looks better

• While investment has barely improved during the super-cycle (Peru an exception), LatAm emerges with high reserves and allowing the currencies to depreciate and adjust the trade balance

• Inadequate policies carried by some countries during the bonanza times have been adapting to the new reality almost everywhere in the region, suggesting more realism and institutional strength

Real exchange rate (Dec 2010 = 100; the lowest the weaker) International reserves as % of GDP

Source: BIS and IMF Source: Bloomberg and IMF

0,0

6,0

19

,9

0,0

5,0

17

,0

11

,7

0,0

6,8

20

,5

16

,4

16

,5

17

,3

31

,6

24

,0

25

,5

Argentina Brazil Chile Colombia Mexico Peru Paraguay Uruguay

1999 2016

60

70

80

90

100

110

120

130

dez

/07

mai

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ou

t/0

8

mar

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ago

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jan

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jun

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11

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11

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12

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12

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3

mar

/14

ago

/14

jan

/15

jun

/15

no

v/1

5

abr/

16

set/

16

fev/

17

Argentina Brazil Chile Colombia Mexico Peru Uruguay

0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

4,0

1-j

an-1

6

1-f

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6

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6

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16

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6

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6

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16

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16

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6

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7

1-f

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7

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7

1-a

br-

17

LatAm Brazil Mexico

… but next years remain challenging, and structural reforms are badly needed

• GDP growth forecasts remain subdued at 1.4% for 2017 and 2.6% for 2018; low productivity growth suggest potential GDP growth not very different at this point

• Modest real wage growth may generate some short term competitiveness gains… • … but potential GDP growth will only converge up if we see solid improvements in education, business environment

Doing Business – higher scores mean better business environment Market forecasts for 2017 GDP (%)

Source: World Bank, as of 2017 Source: Bloomberg

[CELLRANGE] [CELLRANGE]

[CELLRANGE] [CELLRANGE]

[CELLRANGE]

[CELLRANGE] [CELLRANGE]

[CELLRANGE]

[CELLRANGE]

[CELLRANGE]

20

40

60

80

100

120

140

160

180

200

30 40 50 60 70 80

Ran

k

Score

Should commodity cycles be taken into account by LatAm’s DIs?

• We have identified the M2 monetary aggregate as the best proxy for eligible deposits in the emerging economies we have tracked

• As we will show in the next slides, there is stronger cyclicality of M2 in “commodity countries”…

• … and this suggests it may be interesting that these countries pursue more research in order to evaluate if commodity prices should be taken in consideration for two purposes:

‒ Calibrating the estimation of the “exposure at default” for the financial institutions of these jurisdictions according to the moment of the cycle a credit event takes place

‒ Considering the convenience of introducing a cyclical element on bank’s contribution to the DIs in order to maintain an adequate ratio of the DI size vis-à-vis eligible deposits throughout the commodity cycle

Findings suggest commodity cycle could affect M2, consequently deposits (1)

• We have calculated correlations between commodity prices and M2 of LatAm and Emerging Asia countries; not surprisingly, “commodity countries” have their M2 positively correlated to the CRB index, while this is not the case for “manufacturing countries”

Emerging Asia: correlation between CRB and M2 LatAm: correlation between CRB and M2

Source: FGC calculation Source: FGC calculation

Findings suggest commodity cycle could affect M2, consequently deposits (2)

• We have run 2000 regressions of M2 YoY in:

‒ Independent variables: CRB YoY, GDP YoY

‒ With lags ranging from 0 to 24 months

‒ To periods of time starting in: July 1995, January 2000, January 2004, January 2008

‒ Countries: Brazil, Chile, Colombia and Peru (we lacked data for Argentina, Mexico not correlated)

• As expected, we found that the explanatory power of YoY variations of GDP on YoY variations of M2 is significant, with the time lag which maximizes that influence varying from country to country

• We also found a significant explanatory power of YoY variations of the CRB index on YoY variations of M2; in fact, explanatory power of commodity prices extends beyond that of GDP, influencing M2 more or less with the same time lag

Regressions 𝑴𝟐 = 𝜶 + 𝜷. 𝑮𝑫𝑷𝒕−𝒊 | Heatmap 𝑹𝟐

Regressions 𝑴𝟐 = 𝜶 + 𝜷. 𝑪𝑹𝑩𝒕−𝒊 | Heatmap 𝑹𝟐

CRB increase M2 explanation (beyond GDP)

Commodity countries show more volatile M2 than Industrialized countries

• Commodity cycles apparently increase M2 volatility in “commodity countries” compared to “manufacturing countries”

The larger the volatilities, the greener the entry cells

Thank you! Gracias! Obrigado!