Factors affecting Income Strategies among households in Tanzanian Coastal Villages: Implications for Development-conservation

initiatives

Jennifer SesaboInternational Max Planck Research School for Maritime Affairs

Research Unit Sustainability and Global Change, Hamburg University

June 09, 2005

Structure of presentation

• Introduction and objectives

• Conceptual framework

• Results and discussion

• Conclusion

• Methodology

Introduction

• 2/3 of the world population lives within 60km of the coastal shorelines.

• This makes coastal resource utilization and other employment opportunities to be potential to the livelihood of coastal population

• In Tanzania , 25% of the population depend on coastal resources for

•Employment•Food•Recreation services

continued

• For a long time , these coastal resources have been under severe pressure due population growth, tourism, imperfect markets, institutional failures and weak governmental management policies. This resulting into:

-overexploitation of fishing resources- cutting of mangrove for fuel and construction-destruction of coral reefs and sand mining-use of fishing destructive methods-pollution- conversion of coastal areas to other land uses

Continued…

• As a result it is becoming increasingly uncertain for the coastal people to support themselves

• For about two decades there have been initiatives from international, NGOs and government organizations to promote sustainable use of resources

• But most of these initiatives as failed due to knowledge gap about the characteristics and behavior of households along the coast regarding their income strategies and their knowledge about the resources

objectives

• To examine the pattern of income strategies and their share in total household income.

• To enhance the understanding of the factors that influence their behavior regarding their participation in different income strategies, so as to give policy makers better informed strategies for designing effective conservation-development policies

Conceptual framework• Several forces influence the decison of the household

to participate in different activities. This includes: - incentives offered - risk associated - capacity of the households, which is determined by

the assets endowment.

• The conceptual framework based on the concept developed, link assets endowment and activity choice in order to shed light on households activities participation decision-making process in the study area.

Continued..•Facilitating Factors

Strategy choice

HouseholdAssets

Household structure

Objective of the study•Physical •Social•Human•Financial•Natural•Facilitating Factors•Household structure

•Income strategy -Agriculture -Fishing -Seaweed farming•Total income

Methodology

•Data from 2 villages (Nyamanzi & Mlingotini) collected between January and March 2004)

•Information collected include - demographic structure -income sources -assets endowments -problems inherent in coastal resources -attitude on management issues•Sample 217 households (mlingotini=117 and Nyamanzi=100

continued..

Variable Views Implication/R-Hypothesis

Measurement

Physical assets

Physical assets indicate the wealth status and the capacity of household to participate in a certain income strategy.

1. Physical assets endowment is positively associated with a strategy which household has comparative advantage.

Land: The size of agricultural land in Hacters (LANDEQ), Fishing assets: Dummy fishing gears ownership (FISHGEARS) Dummy boat ownership (BOATOWN). Dummy fish to total asset ratio (FISHASR0)

Social Capital

Relates to the ability of households to access production resources through memberships in social networks, groups or organization

2. Households with higher amount of social capital enlarge economic opportunities hence high participation rate

Dummy Participation (PARTIC) Dummy share of fishing assets (SHREBT)

continued..

Variable Views Implication/R-Hypothesis

Measurement

Financial capital

Access to other income generating opportunity (such as wage employment and self employment) help to provide capital for investments.

3. Increases participation rate to different activities through capital provision for investment 4. Decrease participation rate through labour reallocation

Other income per adult equivalent (OTHERY)

Human Capital

Human capital include the ability and skills that enhance productivity

5. The variation in households heads’ skills and knowledge lead to a differential decision regarding which activity to participate

- The Mean age of adult members (ADULTAGE)

- Fishing experience (EXPF)

- Household age Dummy (HHAGE0)

continued..

Variable Views Implication/R-Hypothesis

Measurement

Natural capital

The natural resource endowments determine the livelihood paths which rural households can undertake.

6. Increases the participation rate in natural resource-based activities

- Dummy fish resources trend (FISHTREND0).

- Area used for seaweed farming in m2 (SWLAND)

Household structure

Households composition helps - to capture productive and consumptive units in the households, - to measure entrepreneurial motivation and managerial skills

7. Households with different households structure participate in different income strategies

Gender of Households head (GENDER1) Female-male ratio in the household (FEMRAT) Household size (HHSIZE/CWRAT)

continued..

Variable Views Implication/R-Hypothesis

Measurement

Facilitating factors

Market accessibility: market access reduces transaction costs. location: Capture the households and villages variation in terms of resources and development

8. Households with market constraint decrease their participation rate in various activities 9. Households residing in Mlingotini decrease their participation in different income strategies due to poor infrastructure.

- Dummy of credit market constraint (CRDTCOT)

- Dummy of output market constraint (OUTCOT)

- Dummy location (V2).

Methodology- Models

1. Estimate activity participation (Tobit Model)

*

*

*

where

if 0 and 0 if 0

is a partial latent dependent variable

is a matrix of variables

is a parameter vector to be estimated

is a random disturbance

i i

i i i i i i i

i

i

y X

y y X y X

y

X

continued..

2. Estimate Total Household Income (OLS)

0

0

ln

is the total income of the household in logarithmic form

is set of explanatory variables

and are coefficients to be estimated

is an error term

i i i i

i

i

i

i

Y X

Y

X

Results:Activities participation rates, shares in total income in two villages

Nyamanzi Mlingotini Both VillageAgriculture Participation rate 88% 76% 82% Income share 11.40% 16.8 14%Fishing Participation rate 64% 51% 57.10% Income share (range) 61.40% 43.60% 52.60%Seaweed farming Participation rate 50% 27% 37.70% Income share (range) 3.10% 5.60% 4.30%Other activities Participation rate 97% 93.20% 94.90% Income share (range) 24% 34.10% 28.90%Observation 100 117 217

Fishing income is more important for the livelihood of the coastal households in the study area

Results…The income shares by size of agriculture land

This indicate that variation of households in income sources is due to assets heterogeneity

0

500

1000

1500

2000

2500

3000

0 0.5 - 2.5 ha 2.6 - 5.5 ha > 5.5 ha

Agricultural land in Hectars

inco

me

in U

S$

Agriculture Fishing Seaweed Others

88.6$US 105.4$US 102.4 $US 341.7 $ US (fishing assets)

Results… Fishing activity

VariableEstimated coefficient

Standard error t-statistics

Marginal effects

Constant -608.6 329.2 -1.85* -Agriculture Land 130.4 74.8 1.74* 0.05Fish asset ratio -837.4 204.2 -4.10*** -0.3Experience 28.9 8.3 3.47*** 0.01Hhage0 536.5 221.1 2.43** 0.19Primshare 772.6 222.1 3.48*** 0.28Other income 0.6247 0.3193 1.96** 0.0002Fishtrend0 -930.5 263.3 -3.53*** -0.34Total assets 2.24 0.3705 6.06*** 0.0008Village -Mlingotini -400.3 213.1 -1.88* -0.14Observation N=124

The results shows that access to fishing assets through sharingand ownership and the resource trend are important factorsshaping them to undertake fishing livelihood pathway.

Results… Agriculture activity

VariableEstimated coefficient

Standard error t-statistics

Marginal effects

Constant -73 10.7 -6.83*** -Agricultural land 141.6 4.8 29.26*** 0.48Primshare -106.8 17.8 -6.0*** -0.37Ownboat -41.4 18.2 -2.28** -0.14Agrifish 26.1 3 8.82*** 0.09Market constraint 24.3 11.3 2.15** 0.08participation 24.7 12.7 1.95** 0.08Observation N=178

The results shows that agricultural pathway is associated with landownership, participation in groups, participation in both fishing and agriculture activities, fishing assets access..

Results… Seaweed activity

VariableEstimated coefficient

Standard error t-statistics

Marginal effects

Constant -196.4 58.1 -3.38*** -consumer worker ratio 55.1 35.6 1.55 0.21Agricultural land 14 7.1 1.96** 0.05Fish asset ratio 48.1 18.5 2.60*** 0.18female-male ratio 84.7 36.6 2.32** 0.32Seaweed farming Area 0.15 0.01 11.38*** 0.0006Participation 34.7 18.8 1.85* 0.13Village Mlingotini -44.8 18.3 -2.44** -0.17Observation N=82The results shows that seaweed farming pathway is associated

with land ownership, participation in groups, fishing assets access, number of female and location .

Results… Total Household income

VariableEstimated coefficient

Robust standarderror t-statistics

constant 5.4 0.25 21.56***Agricultural land 0.65 0.1 6.86***Agricultural land squared -0.05 0.02 -3.23***Seaweed farming Area 0.0002 0 4.57***Fishtrend0 -0.12 0.11 -1.23Sharing and renting fish assets 0.65 0.17 3.79***Adultage -0.01 0.01 -2.02**Fishgears 0.38 0.16 2.29**ownboat 0.87 0.23 3.83***R2 n=217 0.68

F-statistics (p-value) 48.97(0.0000)The results shows that the entitlement to physical assets, resource trend, the mean age of adult members are important factors influence the households total income.

Conclusion

• Households heterogeneity in decision-making process between various income strategies is shaped by asset endowment, households’ structures, local institutions and location specific characteristics

• Establishment of credits is more important

• Recognition of complementarities between income accrued from various income strategies is important

• Better understand of social networks is essential

• Promotion of investment in rural infrastructure is needed

continued..

• There is a need for policy makers and conservationists to take households heterogeneity into account when designing development-conservation policies

• This can be done through information gathering, so as to properly tailor in their approach when choosing initiatives for development and conservation issues

The future of rural coastal households and coastal resources may be bleak unless!!!!!

policy makers have a common vision and purpose of understanding their behavior as well as characteristics and recognize their knowledge about coastal resources

Thank you for you attention