Arild AngelsenAssociate Professor, Norwegian University of Life Sciences
(UMB), Ås, Norway &Senior Associate, Center for International Forestry Research
(CIFOR), Bogor, Indonesia &Visiting scholar, University of Western Australia, Perth
Practical experiences on policies and incentives to reduce
deforestation in dev. countries (& getting the basics right)
UNFCCC WORKSHOP ON REDUCING EMISSIONS FROM DEFORESTATION IN DEVELOPING COUNTRIES, 7 - 9 March, 2007, Cairns, Australia
Why are policies and incentives important?
Problems of local baseline, leakage and additionality
Hard to set national baseline (& monitor change)
Cons
Easier to deal with more localized effects
Broad & country-specific policies applied
Pros
Key to identify P&I, develop criteria & measure impact
For agreement: Only indirect: countries choose best P&I. Advisory role?
Role of P&I
Measurement of change
Key issues
Example
Approach CDMMain Kyoto
Assessing net impact: Baselines, leakage, additionality.
Setting baselines at national (regional) level! Hot air vs. acceptability
At different scales, and for specific P&I
At national level
Policies & incentives (P&I)National targets
Deforestation
A deforestation framework(Kaimowitz and Angelsen 1998)
Agents of deforestation (choices)
Decision variables (e.g,. prices)
Institutions Infrastructure Markets Tech.
Macro level variables and policy instruments
Sources
Immediate causes
Underlying causes
Some implicationsThe importance of knowing at which level we are in the analysis/discussion
“Defor caused by agric expansion, inappropriate technologies, misguided macroeconomic policies and foreign debt”
Must link land users’ decisions (decision parameters) with policy variables, and be consistent
“Defor caused by poverty and devaluation that made agric more profitable”
Increasingly difficult to predict deforestation effects as move down to underlying causes
A major challenge for making general policy recommendations!
The forest transitionForest cover
Time
1. Triggers(road)
2. Reinforcing loops (localdemand, infrastr, capitalaccum, pop dynamics)
3. Stabilizing loops(off-farm jobs, GE effects, forest scarcity)
4.Forest/plantations/ agric. mosaics
1.Undisturbed forests
3.Forest/agric.mosaics
2.Forest frontiers
What’s driving the FT?(Rudel et al 2005; Angelsen 2007)
A von Thünen (1826) framework: 1. land use determined by land rent/profit (highest win)2. rent depends on location (distance from centre)
Stage 2: agric rent ↑Stage 3-4:
1. Economic development path (ag rent↓)2. Forest scarcity path (forest rent ↑)
Stage 1 Stage 2 Stage 3-4
Agric. rent
Forest rent
$
Km (ha)
Key policy implications
1. How to slow down increase in agric rent?Don’t make frontier agric more profitable
2. How to speed up the economic development and thereby slow down agric rent?
Create alternative employment3. How to speed up/induce forest scarcity
Create markets for forest products (but careful)
Difficulties in using policies1. Defor the aggregate outcome of decisions made
by millions of land users, responding to profitable opportunities for forest conversion
profitability is determined by underlying causes, which are not easy to apply as policies made on non-forest considerations (e.g., exchange rate)
2. Often a trade-off between poverty reduction & forest conservation
win-lose appears to be the rule rather than exception (agric prices, roads)
3. Defor in remote ‘state-less’ or ‘state-thin’ placesregulations and enforcement difficult/ineffective high transaction costs
1. Conservation areas (example: Uganda)
Very good economic performance (5-7 % pa)Population growth: 3.4 % pa24 % forest cover
70 % privateDeforestation in 1990s: 2.45 % pa
Agoro-Agu Sector
Apac Sector
Chwero Sector
Kilak Sector
Lira Sector
Nangolibwel Sector
Pader Sec tor
Zulia Sector
Achwa River Range
NFA Range boundary
Administrative boundary
International boundary
District boundary
Swamp
Open Water
Hill Reserves Sector
Kagadi Sector
Kaniyo-Pabidi Sector
Kasongoire Sector
Kisindi Sector
Lubenge River Sector
Nyakafunjo Sector
Budongo System Range
Alungamosimosi Sector
Bunya Sector
Jinja Sector
Kadam Sector
Pingire Sector
West Bugwe Sector
Namatale Sector
Mt. Moroto Sector
Kyoga Range
Bugala Sector
Kumbu Sector
Lwamunda Sector
Lwankima Sector
Mpanga Sector
Sango Bay Sector
Zirimiti Sector
Lakeshore Range
Itwara Sector
Kasana-Kasambya Sector
Matiri Sector
Mwenge Sector
Singo Hills Sector
Muzizi River Range
Kalinzu Sector
Kasyoha-Kitomi Sector
Bugamba Sector
Mafuga Sector
Mbarara Plantations Sector
South West Range
Mt. Kei Sector
Okavu-Reru Sector
Otzi Sector
Pakwach Sector
Maracha Sector
Zoka Sector
West Nile Range
Kyoga Range
Achwa River Range
Lakeshore Range
Muzizi River Range
West Nile Range
South Western Range
Budongo System Range
MUKONO
BUGIRIMAYUGE
AMURU
KALANGALA
MASINDI
ABIM
HOIMA
BILIISA
KAABONG
KOTIDO
MOROTO
KITGUM
RAKAI
ADJUMANI
MASAKA
ARUA
KIBOGA
WAKISO
YUMBE
APAC
NAKASEKE
PADER
NAKAPIRIPIRIT
LIRA
MPIGI
GULU
BUKWA
BUSHENYI
BUNDIBUGYO
KUMI
MOYO
KASESE
NEBBI
KIRUHURA
SOROTI
KATAKWI
KIBAALE
KOBOKO
PALLISA
MUBENDE
SEMBABULE
OYAM
KYENJOJO
ISINGIRO
KAMWENGE
AMOLATAR
AMURIA
KAMULI
NAKASONGOLA
MARACHA_TEREGO
SIRONKO
LUWEERO
RUKUNGIRIKANUNGU
KABAROLE
KAPCHORWA
KAYUNGAMANAFWA
JINJA
KABALE
TORORO
KABERAMAIDO
IBANDA
KISORO
DOKOLO
KALIRO BUDAKA
NTUNGAMO
MBARARA
MITYANA
BUSIA
MBALE
IGANGA
BUTALEJANAMUTUMBA
KAMPA- LA
Zulia Sector
Kisindi Sector
Mt. Kei Sector
Kadam Sector
Otzi Sector
Mt. Moroto Sector
Kalinzu Sector
Pader Sector
Itwara SectorLwankima Sector
Kagadi Sector
Agoro-Agu Sector
Bunya Sector
Kasyoha-Kitomi Sector
Kilak Sector
Kumbu Sector
Nangolibwel Sector
Singo Hills Sector
Zoka Sector
Apac Sector
Matiri Sector
Sango Bay Sector
Lira Sector
Bugamba Sector
Nyakafunjo Sector
Hill Reserves Sector
Lubenge River Sector
Mpanga Sector
Lwamunda Sector
Kaniyo-Pabidi Sector
Mwenge Sector
Chwero Sector
Maracha Sector
Kasongoire Sector
Kasana-Kasambya Sector
Mafuga Sector
Alungamosimosi Sector
Jinja Sector
Zirimiti Sector
West Bugwe Sector
Okavu-Reru Sector
Bugala Sector
Mbarara Plantations Sector
Pingire Sector
Namatale Sector
Pakwach Sector
Zulia
Moroto
Mt. Kei
Kadam
Bugoma
Mabira
Agoro-Agu
Napak
Timu
Rom
Kasyoha-Kitomi
Kilak
Kagombe
Kalinzu
Otzi (East)
Taala
Kikonda
NangolibwelKano
Itwara
Kibeka
North Maramagambo
Akur
Nyangea-Napore
Rwoho
Zoka
Ogi li
Alerek
South Busoga
Kasagala
Era
Matiri
Budongo
Iyi
Luwunga
Lwala
Buyaga Dam
Maruzi
Mujuzi
Opi t
Kazooba
Malabigambo
Luku
Namwasa
Bajo
Jubiya
Morongole
Kyahi
Nsowe
Wiceri
Bujawe
Achwa River
South Maramagambo
Kapimpini
Lwamunda
Kafu
Kitechura
Bukaleba
Kagorra
Kyalwamuka
Kyamazzi
Laura
Kalombi
Kamusenene
Kasolo
Wankweyo
Kiula
Katuugo
Navugulu
Kachung
Mukihani
Lalak
Kifu
Ibambaro
Kasato
Kyalubanga
Lendu
Nawandigi
Omier
Echuya
Abiba
Bwezigolo-Gunga
Nyamakere
Lamwo
Kabwika-Mujwalanganda
Kaiso
Wabisi-Wajala
Wambabya
Nyakarongo
Alungamosimosi
Kisombwa
Kasana-Kasambya
Towa
Mafuga
Parabongo
Mpinve
Namalala
Labala
Olwal
Kanangalo
Kijanebalola
Ating
Wamale
West BugweIgwe
North Rwenzori
Kasa
Tero (West)
Muhangi
Otukei
Mubuku
Mbale
AveAbera
Got-Gweno
Lokung
Busowe
Atigo
Kijuna
Gala
Kibego
Kaweri
Namatiwa
Wati
Lotim-Puta
Kabindo
Ayipe
Katabalalu Namanve
Kasongoire
Gangu
Guramwa
Amuka
Ruzaire
Keyo
Alui
Nakalanga
Butamira
Kyampisi
Kandanda-Ngobya
Zirimiti
Goyera
Buvuma
Eria
Usi
Liru
Nsube
Natyonko
Ogom
Kadre
Zimwa
Bugamba
Nkera
Mugoye
Bukaibale
Kisisita
Kitonya
Kakasi
Muinaina
Nonve
Ozubu
Enjeva
Kulua
Luvunya
Buhungiro
Lopeicubei
Nfuka-Magobwa
Opok
Kagogo
Lusiba
Pingire
NakizaMwola
Tero (East)
Ngereka
Kanaga
Tumbi
Otrevu
Kikumiro
Kakonwa
Akileng
Bugondo Hil l
Suru
Bira
Sirisiri
Nakalere
Musamya
Namatale
Semunya
Kaduku
Buyenvu
Sala
Iziru
Ihimbo
Lubani
Mugomba
Wadelai
Kahurukobwire
Mpanga
Kyansonzi
Buwa
Nadagi
Nimu
Rukara
Alit
Luleka
Enyau
Jumbi
Lomej
Kihaimira
Sitambogo
Acet
Kizinkuba
Lukale
Kyehara
Nile Bank
Ajupane
Bulondo
Namavundu
Buwanzi
Oruha
Luwafu
Koja
Sozi
Ayami
East Uru
Olia
Fumbya
Nakwaya
Irimbi
Telwa
Kabukira
Buga
Nabanga
Kitasi
Buuka
Arua
Lagute
Rwensambya
Madoci
Obel
Aloro
Mutai
Achwali
Bugonzi
Epor
Kisasa
Kinyo
Kigona River
Nyakunyu
Ayito
Kalandazi
Nyabiku
Kisangi
Koko
Ajuka
Nyabigoye
Luwawa
Olamusa
Muhunga
Mburamaizi
Abuje
Arweny
Awer
Buluku
Ogera Hill
Bululu Hi ll
Namyoya
Kagwara
Kajansi
Kasala
Adero
Ibamba
Lutoboka
Bundikeki
Kafumbi
Atiya
Lufuka
Matidi
Buloba
Kyahaiguru
Bufumira
Kigulya Hill
Acwao
Otzi (West)
Kigona
Nkogwe
Kijwiga
Lul Oming
Kyamurangi
Nanfuka
Kijogolo
Nakuyazo
Ilera
Okavu-Reru
Bugusa
Lukalu
Paonyeme
Lira
Kalangalo
Ojwiting
Degeya
Sambwa
Ochomil
Rwensama
Musoma
Opaka
Ogata-Akimenga
Rwengeye
Muko
Mwiri
West Uru
Abunga
Ongom
Lul Opio
Wantayi
Oliduro
Aneneng
Aminkec
Bugomba
Mako
Banga
Odudui
Gweri
Funve
Kachogogweno
Ochomai
Aram
Gung-Gung
Lukolo
Onekokeo
Kasenyi
Aminakulu
Okurango
Wabitembe
Kuzito
Kateta
Kyewaga
Paj imu
Aminteng
Awang
Kubanda
Angutewere
Walumwanyi
Lukodi
Kyantuhe
Achuna
Dakabela
Atungulo
Kifunvwe
Wabinyomo
Namatembe
Nkose
Bugana
Apworocero
Gulu
Onyurut
Buturume
Kabuye
Ocamo-Lum
Kabango-Muntandi
Kabira
Bulijjo
Wantagalala
Bukone
Kaliro
Namazingiri
Bumude-Nchwanga
Rwengiri
Anyara
Abuya
Mataa
Mukambwe
Wamasega
Nakitondo
Lobajo
Nabukonge
Kavunda
Kamera
Namasiga-Kidimbuli
Bugaali
Tororo
Kabale
Gwengdiya
Kasonke
Nakunyi
Kampala
Lukuga
Naludugavu
Nyaburongo
Nakindiba
Mbarara
Kyabona
Kagongo
Nakwiga
Walugondo
MonikakineiKabugeza (Kasanda)
BuzigaMulega
Nyabyeya
Lodonga
Along-Kongo
Tonde
Budunda
Namabowe
Lemutome
Bunjazi
Lokiragodo
Soroti
Walulumbu
Namafuma
Kitemu
Lul Kayonga
Manwa (South East)
Izinga Island
Kasokwa
Nagongera (West)
KalagalaFalls
Linga
Kimaka
Kasozi
Kumi
Lajabwa
Bikira
Namasagali
Fort Portal
Makoko
Wangu
Namalemba
Alito
Katakwi
Kaniabizo
Bwambara
Buwaiswa
Kumbu (South)
Aringa River
Pokoli
Bugiri
Ngogwe (Bwema Island)
Rukungiri
Ngeta
Luwungulu
Tebakoli
Ogur
Walugogo
Aboke
Kagadi
Bukedea
Bukakata
Ntungamo
Busembatya
Bobi
Aduku (South)
Bulogo
Nkese
Abili
Apac
Aduku (North)
Bala (South)
Ayer (Lira Road)
Rugongi
Kapchorwa
Ayer (Bala Road)
Sekazinga
Nsekuro Hill
Kagogo
Kande
Mbale
Mas indi
Kitonya Hill
Lake Kyoga
Lake Victoria
Lake
Albert
Lake Edward
Lake George
Masege
Kalandazi
Kanjaza
Kajonde
Kyirira
Mulundu
<Empty Picture>
N
100 0 100 200 Kilometers
Scale 1 : 800,000
CENTRAL FOREST RESERVES BY RANGES AND SECTORSNATIONAL FORESTRY AUTHORITY
Are parks and reserves effective?(Babigumira and Angelsen 2007)
Yes!Strong enforcement
Methods to measure netimpacts:
Passive protection (parks in remote areas?)Leakage (more clearing outside)
1.2
2.813.25 3.32
3.65
0
0.5
1
1.5
2
2.5
3
3.5
4
Inside 0-0.5 0.5-1 1-5 5-10
Deforestation rates 1990-2000 (% pa).Inside parks and reserves and in bufferzones (km)
2. Community forest management
Agric. rent
Forest rent w/local benefits
Distance (d)
Forest rent w/local & global benefitsG
C
dG dOdC
Communities taking local forestbenefits into account in theirdecisions on forest conversion
Payment for forest services (PES), or government regulation
$
Does CFM work?Emerging consensus:
Relatively successful in forest conservationRelatively unsuccessful in raising forest incomeEx. Malawi & Nepal: Higher forest income for non-members
Why?Driven by a conservation (& cost saving) agendaThe valuable stuff (timber) not handed to local communitiesAn incomplete reform
Policies?More authorityGet timber rights? Link to other benefits
3. Land tenure: a critical distinction1. Degree of (exogenous)
tenure insecurityTenure security promotes
higher investments and long term thinking:Tree plantingLand improvements
Good for forest!
2. How land rights are acquired
Deforestation an investment and a means to acquire and/or strengthen land rights.
Higher tenure security promotes deforestation!
• Land reforms to enhance tenure security often promotes both cutting and planting of trees!
• Depends on stage in forest transition: 2. effect dominate early in the transition
4. New agric technologiesKey questions to assess impact:
Does it make agric conversion of forest more profitable? Does it change the means (access to labour and capital) of land users to clear forest?
Critical factors for the impact of tech change on deforestation (Angelsen and Kaimowitz 2001)
Reduced Impact on deforestation Increased
Intensive (high) Labour and capital intensity Saving (low)Constrained (subs.) Farmer characteristics Well-off Local Output market Global Yield increasing Technology Cost saving Local, segmented Labour market Mobile labour
(migration)Intensive (lowland) Sectors experiencing tc. Frontier areas
(upland)Global Scale of adoption LocalShort-term Time horizon of analysis Long term
Examples of good and bad (for defor) agric technologies Agric technologies → more deforestation
Commodity booms (banana, sugar, cocoa, palm oil, soy bean)Livestock intensification in Latin America (casual effect reverse: the potentially forest saving technologies only adopted when forests are gone))New technologies for frontier agric (possibly also agroforestry, e.g., rubber in Sumatra, Indonesia)
Agric technologies → less deforestationIrrigated, lowland agriculture, e.g. Green RevolutionTechnologies for intensive systems, when farmers also involved in extensive ones, e.g., more intensive maize production vs. chitemene in Southern Africa
Concluding remarksForest transition as a useful framework to understand (stages of) deforestation and policy choice:
agric rent providing alternativesinduce forest scarcity
Hard to state generally even qualitatively the defor impact of policies & incentives, let alone quantify the impact. Also highly country-specific.
If P&I approach: Focus on direct projects and specific policies,e.g., conservation areas (like A&R under CDM); cannot include broader (and more forceful policies)An argument for a national target approach, but requires national baselines and good inventories and monitoring