Colas Chervier, Julia Naime, Malte Ladewig, Arild Angelsen
Global typology of policies to reduce
deforestation

Rationale
• Contribution to the context-policy matrix
• And more generally: contribution towards synthetizing the current knowledge on the influence of
context on impact of “forest policies and measures”.
• Large diversity of policies and measures & commonalities in the way they intend to bring about
change: need to simplify and identify types
Types of policies and measures
P1 P2 P3
Context
archetypes
A1
A2
A3

Gap and objective
• Previous typologies and classification: not
encompassing enough, predefined types (top-
down), unclear and non-reproductible
classification methods
 Objective: to define a typology of public
policies based on a method that is bottom-up,
reproductible and systematic (using criteria
derived from the theories of change of policies).

Element 1: The universe of forest policies and measures considered
• Our definition is meant to be:
• Not too narrow (missing policies and measures that
key actors use to reduce deforestation)
• Not too broad (the link with deforestation reduction
has to be relatively direct)
• To establish the list of relevant policies and interventions,
we relied on: (i) Previous studies that have done a review
of the literature & (ii) Review national REDD+ strategy
documents from our target countries.
• We have identified 35 policies and interventions….but
this list is not exhaustive!
Any policy, program, or action
aimed at changing or significantly
affecting the behavior of forest-
related actors and thereby directly
or indirectly contribute to avoiding
deforestation.
Road construction in a forested area = Y
Devaluation/depreciation of national currencies = N

Element 2: A generic theory of change of forest policies and measure
Forest policies and measures
implemented (transfer of
material incentives or
information)
Change in
behavior of
targeted
stakeholder(s)
Deforestation and
forest degradation
reduced
Psychological
mechanism
activated
Cause of
deforestation
mitigated
Inputs Outputs
Short-term
intermediary
outcomes
Long-term
intermediary
outcomes
Impacts
Theory-based typology: we intend to classify policies and measures according to the way they are
supposed to bring about change

Element 3: attributes and sub-attributes characterizing forest policies and measures
Attributes
Change in behavior of targeted
stakeholder(s)
Psychological mechanism activated Cause of deforestation mitigated
Psychological mechanism activated by
forest policies and measures
Actors targeted by forest
policies and measures
Causes of deforestation mitigated
by forest policies and measures
Theory of
change
Maximization of material payoffs
Compliance/ Obedience
Social belongingness satisfaction
Competence/ self-efficacy
Sub-attributes
Producers
Supply chain actors
Consumers
Governments and public actors
Finance actors and investors
Limited values of forests and
benefits of forest-friendly activities
Large benefits from forest-
degrading activities
Weak governance
Inadequate human development
conditions
Inadequate demand for forest-
related commodities

First results (1/2)
• Identification of dominant
sub-attributes for each
policy/measure
• E.g., PES = payoffs + land
users + increase forest
values
• Different levels of
aggregation possible:
• 10 middle-level types
(orange line) with at least
two common sub-
attributes.
3 4 1 2 5 6
7
8
9
10

First results (2/2)
Type 1 = producers + material payoffs (e.g. PES)
Type 2 = producers + compliance/ obedience (e.g. PA)
Type 3 = producers + broader development conditions + psychological mechanism other than material payoffs and
obedience (family planning campaigns)
Type 4 = producers + improving forest values and benefits + psychological mechanisms other than material payoffs and
obedience (e.g. logging concessions)
Type 5 = Increasing linkages between multiple stakeholders to improve governance (e.g. MSP)
Type 6 = government actors + aimed at improving governance (e.g. EFT)
Type 7 = End-consumers + demand (e.g. consumer awareness campaigns)
Type 8 = intermediate supply-chain actors + demand (e.g. disclosure)
Type 9 = increasing values of forests and the benefits of forest-friendly activities + material payoffs + broader range of
supply-chain actors (e.g. subsidies)
Type 10 reduce the benefits of forest-degrading activities + material payoffs + broader range of supply-chain actors (e.g.
reduction of credit access)

Next steps

Improving the typology based on feedback from GCS REDD+
target countries
 Does the classification method make sense,
including in particular the list of attributes and
sub-attributes?
 Do we forget any policy and measure that
influence forest fate in Indonesia?
 Does the current classification in 10 types makes
sense in the Indonesian context?

Adding the context dimension
 The global typology is just one step
towards generating information that is
useful for policy makers:
 what policy and measure is more
likely to be effective in what
context?
 Need to add the context dimension by:
 Summarizing the information
generated by the impact evaluation
literature
 And using a systematic framework
to characterize context
characteristics
Source: Ostrom and Cox 2010

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