rohit jindal - estimating payments for smallholder agroforestry contracts in tanzania - august 2009

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Estimating payments for smallholder Agroforestry contracts in Tanzania World Congress of Agroforestry Nairobi (Aug 23-28, 2009) By: Rohit Jindal PhD Candidate - Michigan State University

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Estimating payments for smallholder Agroforestry contracts in Tanzania

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Page 1: Rohit Jindal - Estimating payments for smallholder Agroforestry contracts in Tanzania - August 2009

Estimating payments for smallholder Agroforestry contracts in Tanzania

World Congress of Agroforestry Nairobi (Aug 23-28, 2009)

By:

Rohit JindalPhD Candidate - Michigan State University

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Significance of payment in PES PES: payments to service providers from service

users / intermediaries for securing valuable environmental services (ES)

An inadequate payment will: underachieve program objectives exclude poor or be rejected outright

But, how much to pay if ES markets don’t exist?important methodological & practical question

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Research site: Ulugurus, Tanzania

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PES in Ulugurus Provides valuable ES:

biodiversity, watershed (source of water for Dar)

ES threatened due to rapid deforestation

Focus on conservation through smallholder agroforestry – woodlots on 0.5 acre plots, carbon and other co-benefits

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Stated preference method

Survey with 400 randomly selected households

Covered hh demographics, labor availability and agricultural profile

Choice Experiments: farmers asked to choose from a set of hypothetical tree planting contracts

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Choice experimentsAttributes Levels

Trees Khaya + Teak

Mango + Avocado

Khaya + Acacia

Seedlings Farmers pay

Free Free + upfront payment

Contract duration

3 years 10 years 25 years

Annual PES payment

None Tsh 15,000

Tsh 45,000

Page 7: Rohit Jindal - Estimating payments for smallholder Agroforestry contracts in Tanzania - August 2009

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Indicative Results

High level of willingness to plant trees: Most hh already protect trees on their farmsWant to put additional 0.5 - 1 acre under treesOnly < 25% respondents said ‘no’ to planting

treesMajor constraints – old age, non-availability of

land

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Conditional Logit

Dependent variable: choice to plant trees under a specific contract

Preferences for contract attributes:Annual payment: ++Timber trees: ++Longer duration contracts: -Upfront payment: +

Still working on more detailed data analysis

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Revealed preference: Auction

Stated preference methods may not resolve info asymmetry

In an auction, farmers bid for tree planting contracts

Competition ensures they reveal their true WTA

Bids selected as per uniform pricing with the last rejected bid setting the equilibrium price

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An example If PES budget = $140

We can either get just 1 ha, or Thro auction we select the two lowest bids

and pay $60 to each of them

If budget = $580 We select five lowest bids and pay $110 to

each of them

Vickrey auction: Incentive compatible as bidders reveal their true behavior

Bids received/ha

$150$140$110$95$87$60$45$30

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Field auction in the Ulugurus 300 farmers participated Two contracts from CE options

offered: Low intensity woodlots in 0.5

acre plots Trees to be maintained for 3

years 3 training rounds 2 auction rounds: 268 valid

bids received

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Indicative results (n=268)

Round 1 (Khaya + Teak): Round 2 (Khaya + Acacia):Mean bid: Tsh 157,402 Mean bid: Tsh 151,631 Median bid: Tsh 135,000 Median bid: Tsh 135,000

Estimating ES supply curve (Teak)

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

0.5 8

15.5 23

30.5 38

45.5 53

60.5 68

75.5 83

90.5 98 106

113

121

128

acres

Thou

sand

s of

TSH

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Implications Maximum enrollment under a given

budget – yields additionality Auction bids can be compared with

results from stated preference survey Comparison with other opportunity cost

studies A general method to determine payment

in PES projects

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Implications for policy makers Targeting poor farmers:

CE results can help in designing pro-poor PES contracts

Targeting priority areas: High risk areas (riparian,

steeply sloped etc.) given higher weights in the auction

Increases the probability of such lands being contracted

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Acknowledgements

John Kerr, Michigan State Univ. Brent Swallow, ICRAF Aichi Kitalyi, ICRAF Paul Ferraro, Univ. of Georgia Satish Joshi, MSU Mr. Sabas, TAFORI