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

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 #13531 -- Mapajo tree in Pando, Bolivia

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

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?

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

3.1 Scotland et al. (1999)

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 -41.2 million m3 1998: net roundwood balance -56.6 million m3 Issues Limited comparability: only 2 years (1997-1998) Various sources of data Domestic market projections (ITFMP estimates)

3.2 Brown et al. (2005)

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

3.3 Manurung et al. (2007)

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)

3.4 Tacconi (2007)

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)

3.5 Human Rights Watch (2009)

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 (2003-2006) Different sources of data No inclusion of domestic markets Possible double counting of pulp fiber

4. Comparison across cases Issues Scotland (1999) Brown et al. (2005) Manurung et al. (2007) Tacconi (2007) Human Rights Watch (2009) Timeframe 1997-1998 2006-2025 1980-2005 2000,2003 2003-2006 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

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

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

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

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

6. Building on previous analyses

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

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

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

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)

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?

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