CIFOR Presentation: Oil and Forests

CIFOR Presentation: Oil and Forests

Center for International Forestry Research

Does Oil Wealth Help Conserve Forests? Macroeconomic impacts on tropical forests and their utilisation Sven Wunder, Economist, Ph.D., D.Sc.

Q: Why is there so much forest in Gabon? A: It s because of oil!

Structure I. Basic concepts II. III. IV. Hypotheses and cases Conceptual framework Deforestation trends V. Macroeconomic linkages VI. Conclusions and policy considerations

I. Basic concepts

1. DEFORESTATION: A removal of tree-canopy cover to below 10% (FAO) - permanent or temporary Refers to land-cover & land-use changes Economics: Tends to be an investment in future land uses

2. FOREST DEGRADATION: All other significant changes in forest structure Often includes selective logging Economics: tends to be a cashing in of rents

II. Hypotheses and cases

A. Cross-country hypothesis Tropical countries specializing in oil and mineral exports tend to deforest and degrade forests less than other tropical countries

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

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.

B. Inter-temporal hypothesis Tropical countries specializing in oil and mineral exports will over time deforest and degrade forests less during boom periods and more during bust periods.

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

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

III. Conceptual framework

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

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

Level of analysis Causal mechanism Transmission stage......... (3) Sectoral NT production rises* Quasi NT production rises* Semi T sector ambiguous* T production declines* (E) Accelerated urbanisation* Construction boom* Agricultural production declines* Timber production declines* Other land using sectors decline* (F) (4) Land-use Expansion of cultivated area is reduced* Forest area logged is reduced* Other land clearing and extraction is reduced* (G) (5) Forest NOTES: Deforestation is reduced* 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 Forest degradation is reduced*

What factors matter? I. Oil raises incomes and prices => 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)

IV. Deforestation Trends

Cattle dominates land-use change in Latin America.

with land-extensive ranching systems replacing forests.

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

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

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

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

Differences in the 1990 tropical forest-cover estimates by TREES, IUCN and FAO Venezuela Papua New Guinea Gabon Ecuador Cameroon -40-30 -20-10 0 10 20 30 40 Difference from TREES estimates (%) IUCN FAO FRA 1990 FAO FRA 2000

Comparing yearly deforestation estimates (in '000 hectare) FRA 1990 FRA 2000 Own best guess Yearly deforestation 1980-1990 Yearly deforestation 1990-2000 Yearly deforestation ( ~1990s) Cameroon 122 222 150-200 Ecuador 238 137 >180 Gabon 116 10 0 PNG 113 113 50-70 Venezuela 599 218 250-400

Principles for deforestation assessment in this study 1. Get all national estimates 2. Evaluate critically their assumptions (canopy cover, spatial resolution, time scale, sample coverage) 3. Evaluate sub-national estimates - e.g. hot spot areas 4. Cross-check with agricultural area data (census, survey)

V. Macroeconomic Linkages

The effect of petroleum exports and capital inflows on the real exchange rate. General Least Square (GLS) estimates, Durbin-Watson approach Constant Petroleum exports (million constant 1995 US$) a Capital inflows (million constant 1995 US$) R 2 (%) Runs test Years Gabon Coefficient 13.9 0.00068 0.0011 16.5 0.30 1969-98 T-value 7.33 1.96 2.1 *** * * Venezuela Coefficient 46.2 0.0037 0.0006 25 1.00 1978-97 T-value 3.33 2.38 0.5 *** ** Cameroon Coefficient 56.7 0.05 0.03 93.6 0.54 1986-98 T-value Ecuador 4.82 *** 9.45 *** 8.29 ** Coefficient 12.4 0.02-0.003-41.93 60.2 0.67 1971-97 T-value 3.69 2.63-0.92 *** ** Papua New Guinea -5.34 *** Coefficient 48-0.004 0.04-24.1 52.5 0.19 1972-00 T-value 19.75 *** -0.81 0.56-4.31 *** Time dummy b Notes: Parameter T-value significant at the 10% level * Parameter T-value significant at the 5% level ** Parameter T-value significant at the 1% level *** a Mineral exports for PNG b Dummy: Ecuador: 1971-82=0; 1983-97 =1. PNG: 1971-1994 = 0, 1995-2000 = 1 (shifts in exchange rate regime)

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) Venezuela 1920/30s: Rise of petroeconomy 1956-58: Mini-boom 1974-83: Boom 1984 - : Crisis & mini-booms 1920-50: Forest regrowth 1950-80s: Slow loss 1980s/90s: More rapid loss Pre-WWII: Absolute confirmation Post-WWII: Relative confirmation 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 PNG 1972-94: Mineral boom (rising), fixed overvalued kina 1995 - : Oil boom, financial capital outflows, devalued kina Whole period: Probably stable, low loss linked to food-crop expansion After 1994: Perhaps loss acceleration Relative confirmation (hesitant)

Country Story: Cameroon Macroeconomics: I. Oil boom (1978-1985) II. Severe crisis, urban economic collapse (1986-1994) III. Devaluation, slow recovery (1995 - now)

Country Story: Cameroon Land use: CIFOR socioeconomic survey - 5000 hh, 125 villages Satellite imagery - land-use change analysis Oil boom: strong urban out-migration from rural areas; higher food imports. Economic crisis: fall back on S&B food crops; Deforestation tripled to quadrupled between boom period (0.3-0.6%) and crisis period (1.3-2.7%)

VI. Conclusions and policy considerations

What policies de facto protected forests? 1. Neglect rural road network 2. Spend all the oil money in the cities 3. Sell gasoline at its normal price 4. Keep over-valued exchange rates 5. Tax logging companies heavily continues

.continued What policies de facto protected forests? 6. Over-tax export agriculture 7. Liberalise food imports 8. Move people out of the forest to near roads 9. Waste budgets on agro-industrial white elephants and ignore rural smallholders 10. Create a business environment where few people find it worth wile to produce

How did tropical oil countries respond to oil booms? Some common elements (e.g. heavy urban spending bias) but vast variation in policies (e.g. roads) Oil wealth bought freedom in economic policy making Fluctuations over time make oil countries a macroeconomic laboratory

Main Policy Conclusions Policies that favour agriculture tend to encourage 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 Non-forestry (extra-sectoral) policies are much more important for forests than forest policies.

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) 6. If you are worried about an activity s environmental impacts, look at the effects on the whole system! 7. Other transfers of capital (debt relief, remittances, FDI) can have forest-protecting effects similar to oil wealth)