The Microeconomics of Household Collection of Wild Coffee in Ethiopia: Some Policy Implications for in-situ

Conservation of Coffea arabica Genetic Diversity

Degnet Abebaw and Detlef Virchow

Center for Development Research (ZEF), Univ. of Bonn, Germany

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Outline

1. Introduction2. Background of the study3. Overview of the sample and hypotheses of the study4. Theoretical framework and analytical model5. Analytical results6. Conclusion and policy implications

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1.      Introduction 

• rich sources of genetic resources • means of livelihood and safety nets• crucial source of agricultural inputs (farm implements, seedlings, seeds) • household furnitures (dining tables, beds, spoons, chairs,

etc)• carbon sequestration• Local/regional/national climate regulation

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Challenges

Deforestation and degradation of natural resources • Population pressure• Market developments• Migration• Inappropriate policies/policy failures

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Models of conservation and development

• Fence and fine rule

• Integrated conservation and

development

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2.      Background of the study

Ethiopia has a rich diversity of crops

- one among the eight Vivilovian gene center in the world

Origin and center of diversity for Coffea arabica High diversity in coffee land races on peasant farms and wild gene pool Local benefits from the wild populations:

• for income and

• for family consumption

• for breeding values

• Contributes about 6% to the total coffee production in Ethiopia

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Some factors leading to depletion of wild coffee population in the Ethiopian Highlands

• rapid population growth

• resettlement in the nearby areas

• lack of favorable inter-sectoral linkages (agriculture with forestry)

• lack of coherent forest and agricultural policies

• lack of human resources and finance

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Recent Developments:

Interest is growing for genetic resource conservation

- from within the country (govt, academics, research)

- from outside the country (donors, international univ.,

research centers)

e.g., Initiatives to conserve wild coffee genetic diversity has been in progress since recently

Ethiopian Government/European Union,

ZEF in collaboration with EARO

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Objectives:

1. To identify the main features of household dependent on the collection of wild coffee from the places proposed for the conservation of forest coffee genetic diversity

2 To draw decision support inputs for integrating local needs and behavior with in-situ conservation of forest coffee genetic resources in Ethiopia.

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Study areas• 1. Yayu district (Geba-Dogi)

= 10,000 ha of forest coffee demarcated

• 2. Gewata district (Boginda-Yeba)

= 2,764 ha

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Yayu district

• 520 kilo meters from Addis Ababa

• Mixed farming systems (maize, sorghum, cattle and small ruminants)

• Coffee is a major cash crop and major source of livelihood followed by chat

• Perennial crops are very important

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Land use characteristics

Total Area 1353 sq.km

Arable land percentage

853.74 (63.1%)

Cultivated land 297.10 (21.96%)

Pasture 129.89 (9.60%)

Forest and shrub 261.13 (19.30%)

Degraded 108.24 (8.0%)

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2.3 Survey Design and data type

A two-stage random sampling technique

was employed

121 farm families in the region

Primary and secondary data

July 2002 to April 2003

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3. Overview of the sample and hypotheses of the study

Ethnic composition of the sample

77%

16%

5% 2%

Oromo

Amhara

Tigre

Others

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Most important reasons for wild coffee extraction

23.9 23.1

8.3 7.4

35.5

05

10152025303540

Percentage of sample

households

Crop failure Expected fallin coffee

price

Expectedrise in coffee

price

High currentprice ofcoffee

Expectedcash

shoratge

Reasons

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Access to wild coffee in the last 5 years

0.815.7

78.5

50

10

20

30

40

50

60

70

80

% of thesample

Increased Decreased Permanent No answer

Perceived change by the sample households

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Farmers´ perceptions of the stock of wild coffee and montane rain forest in the study area

28.914

56.2

0.80102030405060

Percentage of the sample households

Deteriorated Improved Permanent No answ er

Stock of wild coffee and montane rain forest

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Household distribution by wild coffee collection

37%

63%

Collectors of Wild coffee

Non-Collectors of wildcoffee

Explanatory variables

Measurement Mean Std.Dev. Expected sign

AGE Age of hh head 42.88 13.63 +

ADUL Number of adults 3.02 1.85 +

SEX Sex of head, 1 if male 0.86 0.34 +

FMSZ Family size 5.50 2.26 +

RESID Redidence hist. , 1 if non-migrant 0.64 0.48 +

ANNC Land with annual crops 1.37 0.95 -/+

PERC Land with perrenial crops 1.38 1.17 -/+

ADJC Plots adjacent to forest, 1 if yes 0.39 0.49 +

PRISK Price risk perception 3.56 1.25 +

ASSET1 Value of farm equipments 63.02 57.42 -

ASSET2 Value of livestock 833.86 948.94 -

DIVER Number of crop enterprises 3.21 1.74 -

DISTW Minutes to reach the nearest market town

122.81 101.51 -/+

DISFR Minutes to rearch forest edge 50.40 27.71 -

Table 2. Hypothese and descriptive statistics

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4. Theoretical framework and empirical approach Conservation of Wild coffee (center for arabica coffee genetic diversity)

provides short-term and long-term benefits to local people, national and international communities

As elsewhere in other tropical forests, local people practice forest-based activities in general and extract NTFP (wild coffee ) from these forests and a sudden exclusion of these people will push them to further poverty and marginalization. Therefore, one way of alleviating the conflict of interst between conservation and current extraction needs is to look into the socioeconomics of participation in the wild coffee, NTFP (case study examples for NTFP elsewhere include Gunatileke and Chakravorty, 2003; Pattanayak and Sills, 2001)

Farm household model Production Consumption Collection Risk and uncertainty in the coffee sector

Expected utility maximization

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Empirical approach

• Define: U1i = sum current and expected utility

that the ith household gets from wild

coffee collection U0i = sum of current and expected utility that

the ith household gets from non-

collection of wild coffee

A rational household is assumed to participate in wild coffee collection as far as:

U1i -U0i >0

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Empirical Approach (contd.)

• Ii =´X+vi

• Ci=1 if Ii>0• Ci=0 if not• Probit Regression

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Explanatory variables coefficients Marginal effects

Age -0.1706

Number of adults -0.3027** -0.1087

Sex 0.9019* 0.3237

Famly size 0.1485* 0.0533

Residence 0.2946

Annual crops 0.3463

Perrenial crops 0.1342

Adjacent plot 0.5694* 0.2044

Perception of price risk -0.0003

Value of farm equipments -0.0002

Value of livestock

Crop diversification

0.1E-4

-0.1016

Distance from Mkt. town -0.0017** -0.0006

Distance from forest edge -0.0098* -0035

Intercept -0.4912

Log likelihood function -79.86

Chi-squared 34.19***

Correct ly predicted sample cases 74.38%

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6. Conclusions and Policy implications

The proposed wild coffee conservation area is an important source of income and employment to the local people

Complete prohibition of picking wild coffee from such areas will harm a significant portion of the society

Use pressure could be minimized by providing compensations and incentives while at the same time working through proper settlement/resettlemnt, family planning and crop diversification .............

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Thank you!