1. Illegal logging in Indonesia: What do we know and what do we need to know?
Krystof Obidzinski, Ahmad Dermawan, Salwa Amira
Environmental Crimes Conference
21-23 February 2010 – Wollongong University

2. Structure of the presentation
Illegal logging in public discourse
Measuring illegal logging: Methods issues
Review of available analyses
Comparison across cases
What does the comparison of methods and results indicate?
Building on previous analyses
Different sources of (contradictory) data
Discussion
Conclusions
Photo: CIFOR Slide Library # Mapajo tree in Pando, Bolivia

3. 1. Illegal logging in public discourse
Still a big issue…but based on many assumptions, few hard facts
Large volumes involved, but how large?
Large tax losses, revenue losses, smuggling levels – all not clearly understood
Counterfactuals – IL holding or increasing despite falling demand and mill closures
Timber plantations increasingly a factor in reducing IL, but by how much?
FLE/G/T impact unclear

4. 2. Measuring illegal logging: Methods issues
There have been attempts at systematic assessment of IL in Indonesia – at least 5 in the last decade
Yet, the results are all different and often not comparable
Why is this?
Can reliable data on IL be produced?
Can greater coherence and consistency be achieved?
How can this be done?

5. 3. Review of available analyses
Scotland et al. (1999)
Brown et al. (2005)
Manurung et al. (2007)
Tacconi (2007)
Human Rights Watch (2009)

6. 3.1 Scotland et al. (1999)

7. 3.1 Scotland et al. (1999) Equations
Roundwood supply + Total imports – Exports = Net roundwood balance on external trade
Net roundwood balance on external trade – Domestic consumption = Net roundwood balance
Negative Net roundwood balance shows illegal logging
1997: net roundwood balance million m3
1998: net roundwood balance million m3
Issues
Limited comparability: only 2 years ( )
Various sources of data
Domestic market projections (ITFMP estimates)

8. 3.2 Brown et al. (2005)

9. 3.2 Brown et al. (2005)
The focus is to meet the installed industrial capacity (which is assumed to be fully utilized and constant)
Timber supplies are sourced from logging concessions, conversion, timber plantations, and other legal permits, based on productivity, growth, etc. per area unit.
There is no estimation of actual consumption
No attempt to estimate illegal logging, but how to increase the supply to meet the industrial capacity
Indication of the potential for illegal logging

10. 3.3 Manurung et al. (2007)

11. 3.3 Manurung et al. (2007)
Supply = forest concessions, timber plantations, and forest conversions, Perhutani (SOE timber plantation), other legal sources
Demand = production of sawnwood, plywood, veneer, woodworking, blockboard, particleboard, chipwood, pulp converted to roundwood equivalent
Demand > Supply (blue area) indicates illegal logging
Issues
Imports not included
Domestic consumption not clearly differentiated
Different sources of data: FAO, MoF, APKI (varying figures)

12. 3.4 Tacconi (2007)

13. 3.4 Tacconi (2007)
Supply = legal supply (forest concessions, timber plantations, and forest conversions) + illegal supply
Demand = domestic production of all sectors (log exports+ illegal log exports – log imports + production of sawnwood + fiberboard + particle board + plywood + veneer + pulp in roundwood equivalent)
Illegal supply = domestic production of all sectors – legal supply
Issues
Limited time frame (2000 and 2003)
Include domestic consumption
Assumption about timber smuggling (3,000,000 m3/ year)

14. 3.5 Human Rights Watch (2009)

15. 3.5 Human Rights Watch (2009)
Legal wood supply = logging concessions, clear-cuts, timber plantation harvest, imports
Wood consumption = sum of consumption by “all timber industries” x roundwood equivalent
Illegal supply = total wood consumption – legal wood supply
Issues
Limited time frame ( )
Different sources of data
No inclusion of domestic markets
Possible double counting of pulp fiber

16. 4. Comparison across cases
Issues
Scotland (1999)
Brown et al. (2005)
Manurung et al. (2007)
Tacconi (2007)
Human Rights Watch (2009)
Timeframe
2000,2003
Sources of data
MOF, APKI, BPS, ITFMP estimates
MOF, own estimates
FAO, MOF, APKI
FAO, MOF, own estimates
MOF, ITTO
Domestic markets
Yes
n.a.
Imports No

17. 4. Comparison across cases
Supply sources
Scotland (1999)
Brown et al. (2005)
Manurung et al. (2007)
Tacconi (2007)
Human Rights Watch (2009)
Concession Logging 
Forest conversion
Timber plantations
Perhutani
Other legal sources
Wastepaper

18. 4. Comparison across cases
Demand commodities
Scotland (1999)
Brown et al. (2005)
Manurung et al. (2007)
Tacconi (2007)
Human Rights Watch (2009)
Plywood 
Full capacity utilization assumed
across all industries
Sawnwood
Veneer
Blockboard
Particleboard
Woodchips
Pulp
Paper
Woodworking

19. 5. What does the comparison of methods and results indicate?
Only one year (2003) where direct comparison of multiple studies is possible
Different sources of (contradictory) data
Limited range of demand commodities
Varying supply sources
Significantly different estimates of illegal logging
Source
IL estimate (million m3)
Manurung et al. (2007) 41
Tacconi (2007) 24
Human Rights Watch (2009) 45

20. 6. Building on previous analyses
Hypothesis: Maximizing the use of data source closest to the object of study (MoF) will lead to greater reliability of analysis
Long term – at least 10 years period
Complete account of supply sources
Complete range of demand commodities

21. 6. Building on previous analyses

22. 6. Building on previous analyses
Is there a “correct” source of information?
Even data between Indonesian agencies are (very) different….

23. 6. Building on previous analyses
Is timber plantation supply indeed growing?

24. 7. Different sources of (contradictory) data
Vastly different data on production and consumption in the sector from key sources
E.g. Sawnwood FAO, ITTO, MOF

25. 8. Discussion Why difference between MOF and FAO/ITTO?
Why FAO/ITTO data is uniform and consistent across the year?
Need to know more about conversion factor and consumption assumptions (e.g. a function to GDP)
Why differences between key domestic forestry institutions (housed in the same building – MOF, BRIK, APKI)

26. 8. Conclusions
Differences of data sets and data sources make available estimates incomparable and uncertain
More information is needed on assumptions, definitions, and techniques involved in generating data sets by different agencies
Because of internal (national forestry agencies) and external (international agencies) differences in data, no single source can be relied on for data
All available sources (or as many as possible) should be used to cancel out differences and mistakes by source
Is greater synchronization possible, or is it too political?