1. Forestry Privatization in South Africa by Aditya Agarwal Siddharth Bafna Alok Gupta Ioannis Maniatis Ozlem Tanik

2. Agenda Background Key Parties Industry – Global & Local Analysis of Parameters & Risks Opportunities & Plans Class Discussion Valuation Results

3. Background South African Government offers 75% shareholding in SAT Pty, a timber plantation 10% of South Africa’s forestry assets Land to be leased and not sold 187 K hectares land out of which 126 K hectares plantations Equity to be held by a consortium with min 10% stake for Black Empowerment partner

4. Key Parties- CTI One of 3 bidders The largest cooling tower manufacturer in India One of the largest traders of timber in India $46.87 million revenues in 2001 Importer of logs from RSA and New Zealand Seeks to acquire overseas forestry assets

5. Key Parties-SAT Fully owned by South African Government Revenues (2000) - Rand 265m (US$ 35m) 1.8m m 3 of timber produced per year 80% sold under long-term contracts Export handling capacity of 200k m 3 at Richards Bay port

6. Key Parties-SAT Strengths High product quality Commanding local market share Fragmented local competition Imports are uncompetitive Debt free balance sheet Experienced forestry management staff Weaknesses High overhead costs Below average productivity standards Inability to retrench redundant labor

7. Industry characteristics Global supply of rainforest timber decreasing due to environmental concerns Environmentally certified (plantation) wood has more acceptability in global markets Demand for saw logs expected to increase faster than supply both globally and locally Export price realizations are higher than domestic prices

8. Global market outlook 20102020 Hardwood142 m m3200 m m3 Softwood410 m m3475 m m3 Forecasted global demand supply gap International prices expected to grow at 1.1% in the long term

9. Local Market outlook Demand supply gap in the medium term: 32% Demand supply gap in the long term: 40% –Based on customer surveys Domestic prices are expected to grow at 1.8% over the long term to achieve export price parity in 30 years Lower price volatility due to long term contracts

10. Sociopolitical Parameters Political Stability Government Committed to Privatization Highly Unionized Labor – Unions oppose privatization Black empowerment movement Regional instability – Crisis in Zimbabwe AIDS Pandemic Threat Moderate Corruption High Crime Rate

11. Economic Parameters Emerging markets crisis – Depreciating Rand Responsible Economic Policies –Growing Trade Surplus –Falling Inflation –Decreasing Budget Deficit High Unemployment

12. Key Economic Parameters South Africa Population 44.4m (2001)a Currency Rand R8.61:US$1 (average, 2001) GDP US$113bn (2001) US$350bn (2001, at PPP) GDP growth 2.2% (average, 1997-2001) 2.2% (2001) GDP per capita US$2,549 (2001) US$7,882 (2001, at PPP) Inflation 6.3% (average, 1997-2001) 5.6% (average, 2001)

13. SA Rand vs. US Dollar 1991-2001

14. Project Specific Risks Quality of accounting information Creeping expropriation – lease agreements Outstanding land claims Environmental lobbies Bloated workforce - no retrenchment (strikes possible) Exposure to natural disasters

15. Mitigation of Risks Currency risk hedging through exports Strong due diligence and use of benchmarks for valuation Creeping expropriation - lease rent to be escalated in line with inflation (PPI) Land claims - compensation from Government for upheld claims Environmental opposition – FSC certification for sustainable forest utilization Insurance against natural disasters

16. Future Opportunities / Plans Increase in output by around 200,000 m 3 through genetic improvements (already underway) Improvement in productivity through training and capital investments Build export handling facility at Maputo port (closer to the plantations) at the cost of R 55m Improve portfolio of customers by increasing exports and domestic spot sales

17. Case Discussion

18. Valuation methodology APV method Cash flow projections for 28 years Incorporated domestic and export price growths and volatilities Ran Monte Carlo for base case scenario Valued the option for investing in the export handling facility at Maputo using MC simulation

19. Key Valuation Assumptions Improved productivity incorporated as reduction in COGS Increased yields included in production forecasts Tax setoff to the extent of value of the plantations in total enterprise value

20. Proforma Profit & Loss statements

21. Cost of Capital – Base Case

22. Cost of Capital – with Maputo Option

23. Valuation results Base case Currency risk hedged for 12 years Cost of capital: 21.52% Enterprise value: R484 million With Maputo option Currency risk hedged for 21 years Cost of capital: 19.64% Enterprise value: R598 million Value of the Maputo option: R114 million

24. Enterprise value

25. Q & A