1. 1 The challenges of mining Rio de Janeiro August 16, 2012

2. 2 A successful case Metals price behavior 1 2 Populist times 3 Agenda

3. 3 A successful case 1 2 3 Metals price behavior Populist times

4. 4 Investment 6678,24812.4x Revenue 1,72621,12612.2x Net income 2707,83429.0x Dividend 722,04128.3x ¹ nominal values deflated by the US CPI State-ownedPrivate sector owned 1943-19971998-2011 (A)(B) (B)/(A) Annual avg in US$ million¹ Vale, a successful case of privatization

5. 5 Vale in 1997 Brazil China Japan USA Belgium Legend Operations Offices Exploration offices Headquarter Stock Exchange Fifteen years ago Vale was a typical Brazilian export-oriented company

6. 6 Vale in 2012 A global reach Hong Kong Stock Exchange

7. 7 Investment to meet the long-term growth dynamics of emerging economies ■Investment-based demand products for housing and infrastructure. ■Consumption-based demand products for durable goods and proteins.

8. 8 Success was not due to chance or to cyclical factors Real metals price index¹ Real terms ¹ The IMF metals price index is based on a basket of metals (copper, aluminum, iron ore, tin, nickel, zinc, lead, and uranium). Sources: IMF and Vale index

9. 9 ¹ Long-term trend according to Hodrick-Prescott filter Sources: Vale and USGS After plunging from 1980 to 2000, real iron ore prices are trending upward US$ per metric ton Iron ore real prices US$ per metric ton

10. 10 A successful case 1 2 3 Metals price behavior Populist times

11. 11 Macro factors have a large influence on commodity prices % Food45-50 Oil85-90 Natural gas¹17-20 Base metals60-65 Price variance associated to macro factors 1979-2011 ¹ US Source: IMF

12. 12 Commodity price co-movement CopperAluminumIron oreCoalOilCornSoybeansWheat Nickel0.540.530.330.180.340.22 0.15 Copper0.720.280.370.630.230.27 Aluminum0.260.450.560.29 0.20 Iron ore0.190.290.180.200.32 Coal0.500.240.360.24 Oil0.290.310.21 Corn0.760.53 Soybeans0.57

13. 13 Metals prices are associated to industrial production Metals price index¹ Global IP ¹ The IMF metals price index is based on a basket of metals (copper, aluminum, iron ore, tin, nickel, zinc, lead, and uranium). Sources: IMF and JPMorgan

14. 14 Global IP growth volatility¹ ¹ 24-month rolling standard deviation of %3m, saar monthly IP change Source: JP Morgan Industrial production is the most volatile component of the GDP, imparting a volatile environment to base metals prices

15. 15 Metal prices in recoveries from past global recessions¹ ¹ Global recessions: 1974, 1981-82, 1990-91, 1998 and 2001. ² Percentage change from last trough to recent peak (Al: 2,785$/t on 3/5/11; Cu: 10,148$/t on 14/2/11; Ni: 29,030$/t on 21/2/11) Sources: Vale and JPMorgan The strong EM-led recovery in IP growth has generated metal price increases much greater than in the recoveries from past recessions Global industrial production % 3mma, saar¹

16. 16 Correlation between US NEER and metals prices¹ ¹ Correlation between rolling two-year standard deviations of monthly changes in US NEER and commodity prices; Jan/10 – May/12. Commodity prices tend to be negatively correlated with shocks to the value of the US dollar

17. 17 Changes in financial markets instability tend to be negatively correlated with base metals prices Two-year rolling correlation between daily changes in the VIX and base metals prices Metals prices and the VIX

18. 18 Copper Sources: DIRI/DETM and Bloomberg Nickel Daily returns % Nickel and copper prices are highly volatile

19. 19 Daily returns % As well as iron ore prices

20. 20 Shaded areas represent periods of downswings. ¹ Real prices, base year = 2012. Nickel real prices cycles 1

21. 21 Copper real prices cycles 1 Shaded areas represent periods of downswings. ¹ Real prices, base year = 2012.

22. 22 Commodity Number of peak-to- trough episodes Number of trough-to- peak episodes Peak-to- trough average length¹ Trough-to- peak average length¹ Average cycle length¹ Length of the latest period ¹ Copper9815.219.634.816 Nickel7622.521.043.516 Real metals price cycles ¹ months

23. 23 The behavior of metals prices shows some similarities to stock prices: difficult to predict, fat tails and volatility clustering 1987-20122002-2012 NickelCopperS&P 500NickelCopperS&P 500 Cumulative return548%462%456%165% 426% 21% Mean0.06%0.04%0.03%0.07%0.08%0.02% Standard deviation2.53%1.84%1.21%2.52%1.90%1.36% Kurtosis105.885.9020.724.652.628.53 Autocorrelation in returns-0.01-0.09-0.050.02-0.05-0.10 Autocorrelation in squared returns0.020.270.160.180.20

24. 24 A successful case 1 2 3 Metals price behavior Populist times

25. 25 Natural resources nationalism

26. 26 Some fallacies about commodities ■A gift from God. ■The Dutch disease. ■The natural resources curse.

27. 27 US$ 5.7 bilion Vale - R&D investment – 2007- 2011

28. 28 Global mining capex US$ billion¹ Real prices ¹ 2009 prices. Source: Vale estimates.

29. 29 Source: “On the evolution of TFP in Latin America”, P. Ferreira, S. Pessôa and F. Veloso, Economic Inquiry, 2012. Despite the restrictions, natural resources have contributed to increase total productivity in Latin America Relative TFP (US=1.0)

30. 30 Is there a natural resources curse? Commodities and economic development ¹ 2011 values Sources: Vale, Haver Analytics, IMF, Penn World Tables, MIDC-SECEX, StatCan and Statistics Norway, USAAustraliaCanada New Zealand NorwayChileBrazil (A) Commodity¹ exports - US$ billion493.4215.3192.918.4120.157.4152.7 (B) GDP - US$ billion15,0941,4891,7381624842482,479 (A) / Total exports - %33.380.041.749.775.570.959.6 (A) / (B) - %3.314.511.111.424.823.16.1 Real GDP per capita relative to the US, 2009100.0104.287.767.5123.830.123.1 Average real GDP growth over the last 20 years 2.63.42.62.72.55.23.2 Average real GDP growth over the last 20 years Global 3.4 EM 5.1 DM 2.2

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