CIFOR Presentation: Oil and Forests - FLACSO

1. CIFOR Presentation: Oil and Forests - FLACSO

3. Center for International Forestry Research

4. Cross-sectoral forest impacts in the tropics: How much do they matter? Sven Wunder, Economist, Ph.D., D.Sc. Ahmad Dermawan, Economist, Ma.

5. Structure I. Variable causes of tropical deforestation II. Case study: Oil and forests III. Other tropical cross-sectoral studies IV. Conclusions and perspectives

6. I. Variable causes of tropical deforestation

7. Cattle dominates land-use change in Latin America….

8. …with land-extensive ranching systems replacing forests.

9. In Central Africa (and South Asia) staple crops dominate….

10. …as their production in swidden systems requires large land areas for crops and fallows.

11. In Southeast Asia and West Africa, logging of rich timbers has played a larger role in opening up forest frontiers...

12. …and relatively more land has been converted to cash and estate crops in the Southeast Asian context.

13. II. Case study: oil and forests

14. Mineral-rich countries hold a large share of remaining tropical forests…. FAO-FRA 2000 FAO-SOFO 1995 (FRA 1990 update) [Forests of 23 specialised oil & mineral exporters] [All tropical forests] 38.4% 47.7% [Forest of 23 specialised oil & mineral exporters] [All tropical forests (excl. Brazil)] 56.3% 72.1%

15. Mineral-rich countries hold a large share of remaining tropical forests…. • …. and oil/ mineral exporters lose forests at a significantly lower rate than other tropical countries • This is valid even when you control for third factors in a multiple regression model (Mainardi 1998; Sunderlin and Wunder 2000) • In other words: there is something special about oil and mineral exports that in most (though not all) cases protects forests. • The example of oil countries might tell us more generally how trade and macroeconomics link to land use and forests.

16. Oil Wealth and the Fate of the ForestA comparative study of eight tropical countries VENEZUELA CAMEROON PNG GABON ECUADOR Primary Country Focus: Long-run land-use changes and links to macroeconomy

17. Primary Country Secondary Country Oil Wealth and the Fate of the ForestA comparative study of eight tropical countries NIGERIA VENEZUELA INDONESIA CAMEROON MEXICO PNG GABON ECUADOR Focus: Long-run land-use changes and links to macroeconomy

20. Linking resource booms to the forest Level of analysis Causal mechanism Transmission stage Oil boom (price or quantity) External borrowing (1) External (A) (2) Macroeconomic Higher national income (transitory or permanent) Structure of demand (+/-) • Policies and budgets: • Road budgets (+) • Transport subsidies (+) • Agricultural budgets (+) • Trade protection (+) • Forestry budgets (-) • Conservationbudgets (-) Poverty Labour costs Saving (+)(-) (B) Higher domestic spending (consumption, investment) (C) Real currency apperication/ Relative price of NT goods rises (D) (3) Sectoral NT production rises* Quasi NT production rises* Semi T sector ambiguous* T production declines* (E) ... ... ... ... ... ... ...

21. Level of analysis Causal mechanism Transmission stage ... ... ... (2) Macroeconomic Higher national income (transitory or permanent) Structure of demand (+/-) • Policies and budgets: • Road budgets (+) • Transport subsidies (+) • Agricultural budgets (+) • Trade protection (+) • Forestry budgets (-) • Conservationbudgets (-) Poverty Labour costs Saving (+)(-) (B) Higher domestic spending (consumption, investment) (C) Real currency apperication/ Relative price of NT goods rises (D) (3) Sectoral NT production rises* Quasi NT production rises* Semi T sector ambiguous* T production declines* (E) Agricultural production declines* Timber production declines* Other land using sectors decline* Accelerated urbanisation* Construction boom* (F) ... ... ... ...

22. Level of analysis Causal mechanism Transmission stage ... ... ... (3) Sectoral NT production rises* Quasi NT production rises* Semi T sector ambiguous* T production declines* (E) Agricultural production declines* Timber production declines* Other land using sectors decline* Accelerated urbanisation* Construction boom* (F) Expansion of cultivated area is reduced* Forest area logged is reduced* Other land clearing and extraction is reduced* (4) Land-use (G) (5) Forest Deforestation is reduced* Forest degradation is reduced* NOTES: T Traded sector NT Non-traded sector * Relative to pre-existing trends (growth and structural change) Core causality mechanism - ‘Dutch Disease protecting forests’ Opposite causality mechanism - ‘Dutch Disease deprotecting forests’ (+) Factor expected to accelerate forest loss and degradation (-) Factor expected to decelerate forest loss and degradation

23. What factors matter? I. Oil raises incomes, prices, exchange rates => agriculture and timber extraction lose competitiveness (Dutch Disease) => less deforestation & degradation II. Oil money is spent in the cities => people move to the cities and abandon agriculture and timber harvesting => less deforestation & degradation III. Some policies reinforce the protection (oil money spent on forestry and conservation); others go against it (oil money spent on roads, colonization, transport and agricultural subsidies/ protectionism)

24. Petroleum production: direct impacts on forests

25. Comparing macroeconomic and deforestation trends Macroeconomic cycles Deforestation cycles Evaluation of the Core Hypothesis Gabon 1960 - 73: Pre-boom 1974 - 85: Boom 1986 - 89: Mini-bust 1990s: Fluctuations 1970 - 90s: Net forest regrowth Recent: Some periurban clearing, probably little net change Absolute confirmation (short and long run) Pre-WWII: Absolute confirmation Post-WWII: Relative confirmation 1920/30s: Rise of petro-economy 1956 - 58: Mini-boom 1974 - 83: Boom 1984 - : Crisis & mini-booms 1920 - 50: Forest regrowth 1950 - 80s: Slow loss 1980s/90s: More rapid loss Venezuela Cameroon 1960 - 78: Pre-boom 1979 - 85: Boom 1986 - 94: Bust, fixed CFA 1995 - : Devaluation, recovery 1973 - 85: Slow loss 1986 - 94: High loss After 1994: Probably high loss Relative confirmation Ecuador 1960 - 73: Pre-boom 1974 - 81: Boom (rising) 1982 - 85: Boom (declining) 1986 - 95: Bust 1996 - Mini-booms Before 1975: Moderate loss 1975 - 90: High loss 1990s: Probably slower loss Rejection - absolute and relative Whole period: Probably stable, low loss linked to food-crop expansion After 1994: Perhaps loss acceleration 1972 - 94: Mineral boom (rising), fixed overvalued kina 1995 - : Oil boom, financial capital outflows, devalued kina Relative confirmation (hesitant) PNG

26. III. Other cross-sectoral tropical studies

28. Price Changes • Higher agricultural prices, and other profitability boosts, tend to raise forest clearing. • Relative price changes between agricultural products also affect forest clearing. • Policies that favor agriculture in most cases promote deforestation. • Even agricultural intensification leads, more often than not, to higher local forest loss. • Higher timber prices have a similar effect, although the link to land clearing is weaker.

29. Policies Affecting Costs • Roads in forested areas lower transportation costs and strongly encourage forest clearing. • Higher rural wages & greater off-farm employment opportunities reduce clearing. • Subsidized agricultural credit often promotes deforestation. Not in all cases. • Fertilizer subsidies limit deforestation in some African contexts.

30. Land Tenure • Clearer land-tenure arrangements help the land user adopt long-term profitable solutions. • In some circumstances, that will favour forest management, but in many cases secure tenure comes to accelerate conversion to alternative uses • Forest clearing often helps establish property rights (“homesteading”) - which promotes “excessive” deforestation beyond what is mandated by the economic rationale.

31. IV. Conclusions and perspectives

32. How much does it matter? • When analyzing the forest effect of any cross-sectoral factor – look not only at the site, but at the whole economy! • Some cross-sectoral links are two-way – e.g. war & forest, timber rents & governance (issues not debated here)… • …but typically they are one-way; forests act as “land buffers” (in forest-rich countries) – and significant reforestation only occurs at elevated income levels.

33. Forest-cover policy effects • Policies that favour agriculture often encourage deforestation - even ‘intensification’! • To reduce deforestation, stop selling fuel cheaply, and stop building roads near tropical forests! • Stop moving/ directing people into forests • High urban labour absorption protects forests • Currency devaluation increases forest pressures • Some trade liberalisation can protect forests • High logging tax reduce forest degradation/access • Population growth is an important long-run driver

34. Main Policy Conclusions • Almost all agricultural investment in frontiers with flexible labour supply promote deforestation. • Unfortunately, many ‘good’ development policies are bad for forest conservation…. • … and some ‘bad’ development policies (for people) protect forests, • These de facto successful conservation outcomes are ‘blind’ strategies = unintentional side-effects from macro policies • Cross-sectoral policies tend to be much more important for forests than forest policies.   

35. Main Policy Conclusions • Still, there are some ‘win-win’ options: 1. Remove subsidies with ‘perverse’ forests impacts (fuel, some agricultural inputs) 2. Forestry sector reform - capture timber rents. 3. Liberalise imports for land-extensive home-market sectors (food crops, cattle, timber) 4. Careful adjustment policies can stabilise urban economic growth and off-farm labour absorption 5. Environmental service payments (direct compensation; quid pro quo)   