Livelihood Baseline Survey Report Tanzania 2014 - Final 30 Apr 2014

Livelihoods in Tanzania – Findings of a Field Survey

African Livelihoods Partnership (ALPs)

Livelihood Basix Inc.

April 2014

Acknowledgement

We would like to thank Swiss Agency for Development and Cooperation (SDC), for their

sponsorship of the African Livelihoods Partnership (ALPs). The SDC Office in Dar-Es-

Salam gave us many insights into the livelihood issues of Tanzania.

We would also like to thank the Ministry of Information, Culture, Youth and Sports,

Government of Tanzania, as well as the Mwanza Regional Administrator’s Office and

the Mwanza City Council for giving us guidance and access.

The Vocational Education and Training Authority (VETA) of Tanzania were kind enough

to share their Graduate Tracer Study report which we found very useful as a

background document.

The insights of the faculty from the Business Management and Entrepreneurship

Department of St Augustine University of Tanzania (SAUT) were also useful in conduct

of the study.

The ALPs team for the survey was guided by Vijay Mahajan and Sanjay Behuria and

led by Suman Laskar in the field. Narayan Reddy also supervised part of the survey

while Navn T. provided valuable support in data analysis using SPSS.

The survey would not have been possible but for the field support of the team from the

Youth of United Nations Association (YUNA) of Tanzania, comprising

1. Lwidiko Edward - Overall Supervisor 2. Omary Hassan - Finances Director 3. Shadrack Msuya - Field Coordinator 4. Hajji Mussa - Supervisor Kilimanjaro 5. Innocent Mkota - Supervisor Morogoro 6. Abinoam Msiliwa - Data Collector 7. Mzee Mandawa - Supervisor Mwanza

Data collectors:

Morogoro: 1. Abbinoam Wingi 2.Yusuph Mayo 3. Alex Daud 4. Innocent Mkota

Mwanza: 1. Mzee Mandawa 2. Hussein Melele 3. Lucy Malisa 4. Neema Moses

Kilimanjaro: 1. Justina Haule 2. Noel Ligate 3.Colman Mosty 4. Hildagelda Urassa

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Disclaimer

The views expressed herein can in no way be taken to reflect the official opinion of the

SDC. The SDC and other donors to ALPs shall have no responsibility or liability

whatsoever in respect of any information in any external website or in any document

mentioned in this report. The present material is for information only, and the reader

relies upon it at his/her own responsibility.

Dissemination

This publication may be reproduced in whole or in part and in any form for educational

or non-profit purposes without special permission from ALPs, provided the source is

acknowledged. The ALPs would appreciate receiving a copy of any publication that

uses this publication as a source.

No use of this publication may be made for resale or for any other commercial purpose

whatsoever without prior permission in writing from the ALPs, email:

[email protected]

mailto:[email protected]

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Regions Covered by ALPs Baseline Survey in Tanzania

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Abbreviations and Acronyms

ALIF African Livelihoods Investment Fund ALPs African Livelihoods Partnership BASICS Ltd. Bhartiya Samruddhi Investments and Consulting Services Limited BDS Business Development Services

CIDR Centre International de Développement et de Recherche GAPI Mozambique Small Scale Investment Support Office

IDSM Institutional Development for Scaling up and Mainstreaming LBI Livelihoods BASIX Inc

MFI Micro Finance Institution

MIFED Microfinance et Developpement, Cameroon

NGO Non-Government Organisation PAMIGA Participatory Microfinance Group of Africa

PPI Progress out of Poverty Index PRIDE Promotion of Rural Initiative and Development Enterprises Limited

SDC Swiss Agency for Development and Cooperation SPSS A software package used for statistical analysis

TLS The Livelihood School TSH Tanzanian Shilling

VETA Vocational Educational and Training Authority

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Table of Contents

Foreword and Key Findings of the Survey………………………………………… 1

1. Introduction .................................................................................................... 5

2. Objectives, Methodology and Coverage of the Survey ......................................... 7

2.1 Objectives ............................................................................................... 7

2.2 Sampling Methodology .............................................................................. 7

2.3 Questionnaire .......................................................................................... 8

2.4 Field work resources and logistics .............................................................. 9

2.5 Data Analysis ........................................................................................... 9

2.6 Research Limitations................................................................................. 9

2.7 Survey Coverage ...................................................................................... 9

2.8 Respondent information .......................................................................... 10

3. Findings ...................................................................................................... 11

3.1 Demographic Information ........................................................................ 11

3.1.1 Education ........................................................................................... 11

3.1.2 Marital Status ...................................................................................... 12

3.1.3 Working Male and Female in Family ...................................................... 12

3.1.4 Poverty .............................................................................................. 15

3.1.5 Household Income ............................................................................... 16

3.1.6 Household Expenditure ........................................................................ 16

3.1.7 Income Variability ................................................................................ 17

3.1.8 Gender Dimension ............................................................................... 18

3.2 Financial Inclusion .................................................................................. 22

3.2.1 Bank Accounts .................................................................................... 22

3.2.2 Borrowing ........................................................................................... 24

3.2.3 Savings .............................................................................................. 26

3.2.4 Insurance ........................................................................................... 27

3.2.5 Remittance / Money Transfer ................................................................ 29

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3.3 Smallholder Farming as a Livelihood ......................................................... 30

3.3.1 Farm Practices .................................................................................... 30

3.3.2 Livestock and Veterinary Services ......................................................... 35

3.3.3 Farm Training and Extension Services: .................................................. 36

3.3.4 Farmers Groups .................................................................................. 37

3.3.5 Demand for Services ........................................................................... 39

3.4 Non-Farm Livelihoods ............................................................................. 42

3.4.1 Ownership .......................................................................................... 42

3.4.2 Problems faced by micro-enterprises ..................................................... 43

3.4.3 Skills and Services Received ................................................................ 44

3.4.4 Producers’ Groups ............................................................................... 45

3.4.5 Access to Finance ............................................................................... 47

3.4.6 Demand for Services ........................................................................... 48

3.4.7 Skill Development ................................................................................ 50

4. Conclusion ................................................................................................. 52

Annexure ........................................................................................................... 53

1. List of Wards/Villages, Divisions, Districts and Regions Covered ..................... 53

2. Questionnaire – Farm................................................................................. 55

5. Questionnaire – Non Farm .......................................................................... 72

Foreword

This survey is meant to draw attention to the urgent task of promoting livelihoods in

Tanzania. The findings show that while almost everyone of working age is working, as

many as 60 percent are not making enough income to even cross the poverty line. In

addition, there is high variability in incomes, with risks due to various kinds of adverse

events - illness, drought, floods, pest attack, and sudden fall in market prices and so on.

Instead of further dwelling on the details of the situation, which the report does, I would

like to draw the attention of the reader to the fact that the three foci of livelihoods in

Tanzania have to be

Rural – since a large part of the population is still living in rural areas

Agricultural – since the predominant livelihood in rural areas is agriculture, including

livestock rearing and horticulture, and

Youth – since a large number of Tanzanians, male and female, are still very young.

And the way ALPs intends to address these is through a “Livelihood Triad” strategy:

Rural Inclusive Financial Services – particularly access to credit for farmers and

youth micro-entrepreneurs

Agricultural Productivity Enhancement for Smallholder and Linking them with Value

Chains, and

Youth Entrepreneurship and Self-employment in farm and non-farm sectors

All these will themes will be addressed through Hybrid Organisations of Producers and

Entrepreneurs (HOPE). By this term we mean those organisations which

Produce in rural areas and sell in urban areas where there is more purchasing

power;

Are involved in not just primary agricultural production but full value addition chain,

and

Are a combination of individual producer-owned enterprises for primary production

and producer-owned or individual entrepreneur owned companies for the more

capital-intensive secondary and tertiary parts of the value chain.

We hope this survey report provides the basis for a whole set of new generation hybrid

livelihood promotion organisations in Tanzania, which are sustainable, financially,

institutionally, as also environmentally. This constitutes the RAY of HOPE strategy for

livelihood promotion in Tanzania.

Vijay Mahajan, Founder and CEO, BASIX Social Enterprise Group, India, and

Founder, African Livelihoods Partnership (ALPs)

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Key Findings of the Survey

Survey introduction

The survey covered three zones of Tanzania, viz. Lake zone (Mwanza Region), Mountain

zone (Kilimanjaro Region) and Plain zone (Morogoro Region). The sample was 1800

households, covering the categories men / women; youth / non-youth and farmers / non-

farm workers

Demographics and Poverty

Half of surveyed youth ended their education by primary level.

Surveyed households had 2.8 dependents for every working person

Men and women participated equally in the workforce in surveyed households

Three-fifths of surveyed households were poor

Wages contributed a major share to cash income of poor surveyed households

Income poverty was six times higher among surveyed poor farm households

Surveyed households spend about four-fifth of expenditure on food

Surveyed households are not covered against risks to lives nor livelihoods

Role of women

Equal numbers of females participated in workforce in surveyed households.

Women played a partial role in decision making related to livelihoods and

household issues in over half of the surveyed households

Women were partially free in terms of their social mobility in over four-fifth of surveyed households

Women were individual or joint owners in two-fifth of surveyed non-farm

enterprises

Access to Financial Services

Only about one-third of surveyed households had access to any financial

services from formal institutions Two-third of surveyed households were indebted.

Three-fifth among indebted house-holds depended on non-institutional agencies

for credit.

Two-thirds of the indebted households borrowed for livelihood purposes.

Only about one-third of surveyed households saved in formal institutions

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Large proportion of surveyed households were not covered against risks to lives

or livelihoods. Only about one-fourth of surveyed households were protected

under life risk coverage. Only about one-sixth covered had enterprise insurance

coverage.

Farm Based Livelihoods

Three-fourths of surveyed households used mobile technology for money transfer

Seven-eighths of surveyed farmers used traditional technology for land

preparation

Two-thirds of the surveyed farm households used seeds retained from own

production

Close to half of the surveyed households used chemical fertilizer for productivity

enhancement

One-third surveyed households had difficulties in marketing agricultural produce

Lack of transportation and non-remunerative prices were the major reasons for

the inability to market of agricultural produce

Post-harvest practices were utilized by only about half of the surveyed farmers

About one-fifth of the surveyed households did not practice storage in protected

structures

About four-fifth of the surveyed households practiced livestock rearing

Half of surveyed farm households were not able to get any extension services

Extension services by the government had very limited outreach – only 1% of the

surveyed farmers

Two-fifth of the surveyed households were part of farmers’ groups

About three-fourth of the surveyed households wish to be part of or continue to

be in farmers’ groups

Over four-fifth of the surveyed farm households expressed the need for training

and extension services

About two-fifth of the surveyed farmers wanted credit services, while half wanted

composite financial services inclusive of credit

While one third of the surveyed farmers expressed the need for market linkage

services (input and output) about half preferred a combination of services which

also incorporated extension and post-harvest services

4

Non-farm activity based livelihoods

Women were individual or joint owners in two-fifth of surveyed non-farm

enterprises

Access to finance and marketing were the two major challenges affecting

surveyed non-farm enterprises, affecting two-fifth of them

About half of the surveyed non-farm households had received training for

business development

About one-third of surveyed non-farm enterprises had membership in

associations

About three out of ten surveyed non-farm enterprises had access to credit

Four-fifths of the surveyed non-farm households expressed the need for BDS

services

Half of the surveyed non-farm households wanted a combination of services

While a little less than half of those surveyed had attended skills training, only about one-sixth received formal skills training

About seven-eighths of the surveyed non-farm enterprise were desirous of attending skills training

About seven-eighths of the surveyed non-farm enterprise were desirous of attending skills training

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1. Introduction

The African Livelihoods Partnership (ALPs), funded by the Swiss Agency for

Development and Cooperation (SDC), is to promote the concept of South-South co-

operation in development. Livelihood BASIX Inc. (LBI, a US based non-profit), BASICS

Ltd. (an India based Social Enterprise Group) and PAMIGA (A France based

Microfinance platform that was founded by CIDR a French NGO) are the 3 founding

members and members of the Executive Committee. MIFED in Cameroun, PRIDE in

Tanzania and GAPI in Mozambique are strategic partners in each of the countries.

ALPs seeks innovative solutions to poverty by working at the grass roots to improve the

social, physical and financial capital of the poor. Specifically it works with rural

population, mainly women and the young to provide them opportunities in the local

context that are sustainable and generate self-employment.

We currently work in Cameroun, Mozambique and Tanzania through a graded

partnership model. Together we select local partners (Field Innovation Testing) to pilot

interventions that have high chance of impact for achieving our objectives. To document

and disseminate the results, The Livelihood School in India (TLS) and local universities

partner with us for action research and knowledge management.

As part of its evaluation strategy, ALPs is mandated to conduct baseline surveys in all

the three 1st phase operational countries. The current report is on Tanzania where we

have covered 3 regions, 6 districts and 12 divisions to provide information that could be

used to assess the outcomes and impacts of this support. This document presents the

findings of the baseline survey.

Under ALPs the results to be achieved are better living conditions of poor end users

and better performing, transparent institutions, gender equality etc. through three

instruments being applied – 1) Knowledge building, dissemination and utilization; 2)

Entrepreneurship and leadership training and institutional development and 3)

Promoting innovations through collaborations and synergistic interventions.

A grant fund has been approved by SDC for implementing the 1st phase of ALPs from

April 2013 to December 2015, during which the ALPs Executive Committee through its

officials and advisors will implement the ALPs project as envisaged in the Project

Document and Yearly Plan Operations. The 1st phase targets the following Outcomes:

6

Overall Goal: The overall goal and impact hypothesis of ALPs is that vulnerable

segments of the population, namely smallholders, women and youth, have stabilised

and enhanced their livelihoods in a sustainable manner by using financial, agricultural,

business and entrepreneurship support services and vocational training; and key

institutions and their leadership have become engaged in and capable of addressing

this goal in the selected countries by the end of six years.

In terms of impact we expect improvement in the livelihoods (10% higher average and

10% lower variability in incomes compared to control group by end of third year and

25% each by the sixth year) of smallholders, women and youth in Cameroon,

Mozambique and Tanzania. Increased institutional commitment to the target groups in

each country as observed through programs, outreach and budgets rising by 20% and

50% compared to control institutions, over three/six years. The following outcomes are

planned:

Particulars: By the end of:

Outcome 1: Smallholders, women, agro-entrepreneurs and youth,

particularly in poorer geographies have access to a wider range of

financial services – savings, payments, insurance and credit - through

improved delivery channels, in a sustainable and responsible manner.

2015

Outcome 2: Smallholders produce more crops and livestock with lower

risk and a higher number of MSEs participate in value chains to increase

smallholder incomes. Smallholder productivity enhancement and linking

them with value chains

2015

Outcome 3: Young men and women have started enterprises in

agriculture and other growing economic sectors. Following vocational

education and training, a higher proportion has become self-employed

or young entrepreneurs in agro-enterprises and franchises

2015

Outcome 4: At least one national/major regional level developmental

institution in each theme in each country has been transformed and

adopts more pro-smallholder/ women/youth policies, programs,

processes and products, practices good governance and achieves/is on

the way to achieve sustainability.

2016

Outcome 5: African, Indian and Northern development practitioners and

policymakers adopt experiences and good practices of ALPs, and their

conceptualisation of development in Africa and of development

cooperation evolves.

2016/17

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Outcome 6: ALPs is institutionalised as an African entity and has

become operational and later sustainable beyond SDC support. 2015/18

Outcome 7: ALIF is established as an investment vehicle for

developmental enterprises in Africa. 2015

The cross-cutting themes of transformational change, gender, scale and sustainability

are considered along project and intervention cycle management processes.

2. Objectives, Methodology and Coverage of the Survey

2.1 Objectives

The ALPs livelihoods baseline survey in Tanzania aimed to provide representative

quantitative information on livelihoods in terms of three thematic areas, viz. financial

inclusion, smallholder agri value chain development and youth entrepreneurship & self-

employment with three segments, viz. women, youth and smallholder farmer covering

three regions viz. Kilimanjaro, Morogoro and Mwanza. Baseline information was

required to represent the three broad agro-ecological zones.

The livelihoods baseline survey results will be a fundamental part of ALPs’s evaluation

strategy that includes a before-after assessment of ALPs interventions and a “with

treatment / without treatment” analysis using results from control villages.

The livelihoods baseline survey aims to provide the basis to evaluate the effectiveness

and outcomes of the ALPs. Findings of the survey in ALPs intervention areas and

control areas will be compared with findings at mid-term and, more importantly, the end

of the project.

2.2 Sampling Methodology

The sampling methodology was designed to allow statistical comparisons amongst the

three zones, Viz. Lake zone (Mwanza Region), Mountain zone (Kilimanjaro Region)

and Plain zone (Morogoro Region). The sampling also required to consider the three

themes, viz. financial inclusion, smallholder agri value chain development and youth

entrepreneurship and self-employment and three segments, viz. women, youth and

smallholder. For any group of region-thematic-segmental minimum representative

sample size had to be 30. Hence the sample size for the survey worked out to 810.

Considering missed responses and errors the total sample size was increased to 900.

This target was doubled to 1800 considering half of the sample as intervention group

and half of the sample as control group. The strata wise sampling is given below:

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2.3 Questionnaire

The questionnaire for the livelihoods baseline survey was designed around key

expected outcomes and associated indicators of the ALPs project. Indicators were also

identified for critical questions and key assumptions inherent within the ALPs strategy.

However, not all of these indicators were selected for inclusion in the evaluation

strategy. The aim was to have a questionnaire that was simple to answer and record

responses, and not take more than 45 minutes on average to complete. There were no

open questions in the questionnaire making recording of answers simple and quick.

Two sets of questionnaires were developed, one for the mainly farm dependent

household and the other for non-farm micro-enterprise dependent household. There

were questions which were common for all the households like basic informations on

demographic details, skills, poverty, access to financial and non-financial services,

income-expenditure, income variability, gender and decision making by women etc. In

case of farm, specific questions were incorporated regarding farm practices, post-

harvest practices, access to services, livestock, farmer’s group participation etc. In case

of non-farm, questions were asked regarding enterprise related issues, access to

finance and other services, participation in groups etc. In both farm and non-farm,

concluding questions were asked on the demand for skill, finance and services.

Strata 1 Strata 2 Strata 3 Strata 4 Samples Women Youth Farm Non-farm Morogoro Moshi Mwanza

Total -> 1800 900 900 900 900 600 600 600

Morogoro Youth Man Farm 75 75 75 75

Morogoro Youth Man Non-Farm 75 75 75 75

Morogoro Youth Women Farm 75 75 75 75 75

Morogoro Youth Women Non-Farm 75 75 75 75 75

Morogoro Not Youth Man Farm 75 75 75

Morogoro Not Youth Man Non-Farm 75 75 75

Morogoro Not Youth Women Farm 75 75 75 75

Morogoro Not Youth Women Non-Farm 75 75 75 75

Kilimanjaro Youth Man Farm 75 75 75 75

Kilimanjaro Youth Man Non-Farm 75 75 75 75

Kilimanjaro Youth Women Farm 75 75 75 75 75

Kilimanjaro Youth Women Non-Farm 75 75 75 75 75

Kilimanjaro Not Youth Man Farm 75 75 75

Kilimanjaro Not Youth Man Non-Farm 75 75 75

Kilimanjaro Not Youth Women Farm 75 75 75 75

Kilimanjaro Not Youth Women Non-Farm 75 75 75 75

Mwanza Youth Man Farm 75 75 75 75

Mwanza Youth Man Non-Farm 75 75 75 75

Mwanza Youth Women Farm 75 75 75 75 75

Mwanza Youth Women Non-Farm 75 75 75 75 75

Mwanza Not Youth Man Farm 75 75 75

Mwanza Not Youth Man Non-Farm 75 75 75

Mwanza Not Youth Women Farm 75 75 75 75

Mwanza Not Youth Women Non-Farm 75 75 75 75

Strata Wise Sample Division

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2.4 Field work resources and logistics

The household interview field work for the livelihoods baseline survey started in mid-

July 2013, and was completed by mid-September 2013. Three teams of each 4

interviewers totalling to 12 interviewers (5 females and 7 males) were involved in three

regions. Each interviewer covered one division under each district and completed

around 150 questionnaires covering equal number of farm and non-farm samples.

Each group of interviewers were supervised and guided by a Supervisor. All

interviewers and Supervisors were carefully trained in administering the questionnaires.

Interviewers were selected through a basic research aptitude test.

2.5 Data Analysis

Questionnaires were checked by supervisors and sent for data entry. A different set of

people got engaged for the data entry job. The data entry process was closely

monitored by the supervisors. Analysis was then undertaken using SPSS. The large

dataset offers opportunities for considerable further analysis than presented below.

However, it is upon completion of subsequent evaluations that the analysis will be most

informative, particularly in the assessment of ALPs outcomes and effectiveness.

2.6 Research Limitations

Intervention and Control Villages: It was bit difficult to identify intervention villages

and control villages as in all the regions the implementation partners were not finalized,

apart from the fact that ALPs would primarily focus in the surveyed six districts. The

implementation team has been instructed by the ALPs management to select

intervention villages from the surveyed divisions and also keep some divisions

untouched so that they can be treated as control group. Hopefully this will be followed

religiously so that at later stage the evaluation job does not face challenge in this regard.

Questionnaire: The questionnaires covered several aspects of livelihoods in the form

of farm and non-farm. Interviewer’s understanding were at different levels and was a

challenge. Interviewing is an art of asking question to collect specific information and

also engaging the interviewee in the subject of discussion.

Respondent recall, perceptions and bias: It is important to acknowledge that the

data collected are influenced, as in all question-based surveys, on respondent

knowledge of their own household, on the accuracy of their recall, and on various biases

that influence responses, among other factors. Interviewer skills and approach are also

important, particularly the extent of probing in questions demanding multiple responses.

2.7 Survey Coverage

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The study covered about

1,793 respondents from the

three regions namely

Kilimanjaro, Morogoro and

Mwanza. An equal number

of respondents were from

the three regions. They were

about 599 from Kilimanjaro,

596 from Morogoro and 598

from Mwanza. Close to 300 i.e., about one-sixth were represented from six districts. An

equal number were represented from the districts – which were 304 from Moshi, 295

from same, 303 from Morogoro Rural, 293 from Mvomero, 316 from Geita and 282 from

Sengerema.

2.8 Respondent information

Age: More than half i.e., 54.6% of

the respondents were youth below 30

years. About a less than half i.e.,

45.5% belonged to more than 30

years category. A significant percent

of population i.e., about 41% were in

the age group of 25 to 30 years.

Sex: The study provided almost equal

representation to both male and

female respondents. A little over half of

the respondents i.e. 52.9% were male

and a little less than half i.e., 47.1%

were females.

Region District Frequency Percent Cumulative Percent

Kilimanjaro Moshi Rural 304 17.0 17.0

Same 295 16.5 33.5

Morogoro Morogoro

Rural

303 16.9 50.4

Mvomero 293 16.3 66.7

Mwanza Geita 316 17.6 84.3

Sengerema 282 15.7 100.0

1793 100.0

Frequency Percent

Cumulative Percent

Less than 25 years 243 13.6 13.6

Between 25 and 30 years

735 41.0 54.5

More than 30 years 815 45.5 100.0

Total 1793 100.0

Frequency Percent

Cumulative Percent

Male 948 52.9 52.9

Female 845 47.1 100.0

Total 1793 100.0

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3. Findings

3.1 Demographic Information

3.1.1 Education

Half of the surveyed persons ended their education by primary level.

Low education levels are a defining characteristic of surveyed youth. About half of the

surveyed youth do not go beyond primary level education. The findings reveal that

about half of the youth (52.3%) were educated till primary education. This was more in

the case of Morogoro at 75.9% followed by Kilimanjaro at 54.2%. Over one-third

(37.9%) finished secondary education. Only about one-tenth (9.7%) completed their

graduation. Mwanza had a higher population (68.3%) who completed either secondary

or a graduation. Overall educational levels were comparatively better at Mwanza

followed by Kilimanjaro and Morogoro. Low levels of education have implications for

employability of youth. Low employability means youth end up joining the ranks of

unskilled labour force in their future employment.

Region * Education Cross tabulation

Education

Total

Graduate Secondary Primary

Not completed

primary Never gone

to school Any other

Kilimanjaro Count 55 218 268 36 21 1 599

% within Region

9.2% 36.4% 44.7% 6.0% 3.5% .2% 100.0%

Morogoro Count 9 163 368 21 31 0 592

% within Region

1.5% 27.5% 62.2% 3.5% 5.2% .0% 100.0%

Mwanza Count 110 296 155 14 14 5 594

% within Region

18.5% 49.8% 26.1% 2.4% 2.4% .8% 100.0%

Total Count 174 677 791 71 66 6 1785

% within Region

9.7% 37.9% 44.3% 4.0% 3.7% .3% 100.0%

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3.1.2 Marital Status

Over three-fourths (78.4%) of the respondents were married. Of this 13% are either

widowed or single parents. The larger number of unmarried which is over one-fourth

were from Kilimanjaro (27.9%) and Morogoro (25.2%).

Region * Marital status

Marital status

Total

Married Unmarried Widow Single Mother

Single Father

Region Kilimanjaro

Count 353 167 57 14 8 599

% within Region

58.9% 27.9% 9.5% 2.3% 1.3% 100.0%

Morogoro Count 360 149 31 32 20 592

% within Region

60.8% 25.2% 5.2% 5.4% 3.4% 100.0%

Mwanza Count 454 69 25 29 17 594

% within Region

76.4% 11.6% 4.2% 4.9% 2.9% 100.0%

Total Count 1167 385 113 75 45 1785

% within Region

65.4% 21.6% 6.3% 4.2% 2.5% 100.0%

3.1.3 Working Male and Female in Family

Surveyed households have 2.8 dependents for every working person.

There were about 2,830 working population above 17 years. Male and female working

population was similar. Male working population was 1,412 and female working

population was 1,418. There were about 3,439 persons below 17 from the sample

households. Assuming about one non-working member above 17 years per family

among 1793 households, there are about 8,062 persons from sample households. This

makes the dependency ratio among sample households at 2.8. There were about 1.6

person working members per household.

Equal numbers of men and women participated in workforce in surveyed households.

Gender-wise an equal number of working persons were found. While there were about

1,412 male earning members, there were about 1,418 working female. This indicates

equal participation of women in workforce.

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The total working male within

the households was about

1,412. A little less than one-

third (31.2%) of the households

are dependent on one male

earning member. A little less

than one-fifth (18.6%)

households depend on two

male earning members and

similarly one-fifth (19.8%)

depend on four earning

members. A little less than one-

fifth (19.2%) households did

not have any male earning member.

Region * Male 17 years or more

Male 17 years or more

Total Four or

more Three Two One None

Region Kilimanjaro Count 51 54 95 247 152 599

% within Region 8.5% 9.0% 15.9% 41.2% 25.4% 100.0%

Morogoro Count 140 25 14 27 15 221

% within Region 63.3% 11.3% 6.3% 12.2% 6.8% 100.0%

Mwanza Count 88 81 153 166 104 592

% within Region 14.9% 13.7% 25.8% 28.0% 17.6% 100.0%

Total Count 279 160 262 440 271 1412

% within Region 19.8% 11.3% 18.6% 31.2% 19.2% 100.0%

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The number of female earning members is

equivalent to number of male earning

members. There were about 1,418 female

earning members in comparison to 1,412 male

earning members. More than one-third of the

households (36.6%) had one female earning

member. A little less than one-fifth (18.9%)

households had four or more earning female

members. One-fifth households (20.2%) did

not have any female earning members.

Region * Female 17 years or more

Female 17 years or more

Total

Four or

more Three Two One None

Regio

n

Kilimanjaro Count 68 82 42 287 119 598

% within

Region 11.4% 13.7% 7.0% 48.0% 19.9% 100.0%

Morogoro Count 142 35 4 35 10 226

% within

Region 62.8% 15.5% 1.8% 15.5% 4.4% 100.0%

Mwanza Count 58 91 91 197 157 594

% within

Region 9.8% 15.3% 15.3% 33.2% 26.4% 100.0%

Total Count 268 208 137 519 286 1418

% within

Region 18.9% 14.7% 9.7% 36.6% 20.2% 100.0%

15

3.1.4 Poverty

Three-fifths of surveyed households were poor

While about one-fourth surveyed households are poor by national standards, about three-fifth are poor by international standards. As

per the PPI calculations done on 1604 households, about 22.6% of the households fell below the Tanzanian national poverty line. As

per international poverty lines of $1.25 per earning member per day, 58.8% of households fell below the same. About 29.6% fell above

international poverty line but in low income category. Only about 11.6% households were above poor and low income category. A high

level of poverty has a bearing on poor human development outcomes of Tanzanian households. This would also mean working

towards reducing the poverty levels would result in improving human development outcomes.

Food 100% 150% 200% $1.25 $2.5 Food 100% 150% 200% $1.25 $2.5

0-4 55.2 81.3 95.7 98.6 70.2 99.4 100.0 0 0.0% 0.0 0.0 0.0 0.0 0.0 0 0

5-9 45.9 17.8 93.3 97.9 50.0 99.1 100.0 4 0.2% 0.1 0.0 0.2 0.2 0.1 0.2 0.2

10-14 33.8 64.8 88.4 97.9 37.3 99.2 100.0 11 0.7% 0.2 0.4 0.6 0.7 0.3 0.7 0.7

15-19 31.2 57.2 82.1 93.6 35.2 96.9 99.7 29 1.8% 0.6 1.0 1.5 1.7 0.6 1.8 1.8

20-24 30.9 53.5 81.5 92.2 33.9 90.6 99.7 50 3.1% 1.0 1.7 2.5 2.9 1.1 2.8 3.1

25-29 26.1 48.4 81.5 92.2 25.9 90.6 99.7 58 3.6% 0.9 1.8 2.9 3.3 0.9 3.3 3.6

30-34 17.6 38.7 73.1 89.6 16.6 88.6 99.3 114 7.1% 1.3 2.8 5.2 6.4 1.2 6.3 7.1

35-39 13.2 29.6 57.9 81.0 12.9 77.7 98.9 178 11.1% 1.5 3.3 6.4 9.0 1.4 8.6 11.0

40-44 7.7 22.8 54.3 75.1 7.3 70.5 95.3 224 14.0% 1.1 3.2 7.6 10.5 1.0 9.8 13.3

45-49 7.4 21.2 50.8 70.8 7.3 65.1 92.7 250 15.6% 1.2 3.3 7.9 11.0 1.1 10.1 14.4

50-54 7.4 17.0 40.8 62.7 6.0 48.9 86.8 268 16.7% 1.2 2.8 6.8 10.5 1.0 8.2 14.5

55-59 5.4 12.0 31.5 54.2 4.0 32.9 81.6 175 10.9% 0.6 1.3 3.4 5.9 0.4 3.6 8.9

60-64 3.5 7.8 27.1 45.8 2.8 29.1 71.3 116 7.2% 0.3 0.6 2.0 3.3 0.2 2.1 5.2

65-69 0.7 7.0 19.4 37.7 0.6 19.3 62.3 83 5.2% 0.0 0.4 1.0 2.0 0.0 1.0 3.2

70-74 0.7 3.2 12.8 34.0 0.6 11.7 53.0 21 1.3% 0.0 0.0 0.2 0.4 0.0 0.2 0.7

75-79 0.7 2.0 6.9 22.0 0.6 6.0 48.5 12 0.7% 0.0 0.0 0.1 0.2 0.0 0.0 0.4

80-84 0.6 2.0 6.8 19.1 0.5 4.8 47.5 8 0.5% 0.0 0.0 0.0 0.1 0.0 0.0 0.2

85-89 0.0 0.0 1.7 11.5 0.0 0.0 29.1 3 0.2% 0.0 0.0 0.0 0.0 0.0 0.0 0.1

90-94 0.0 0.0 0.0 5.9 0.0 0.0 6.6 0 0.2% 0.0 0.0 0.0 0.0 0.0 0.0 0.0

95-100 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0.0% 0.0 0.0 0.0 0.0 0.0 0 0

1604 100.0% 9.9 22.6 48.4 68.1 9.5 58.8 88.4

Tanzania ScorecardSample Scores

Sample Results

Distribution of poverty likelihoods (%) by poverty line Poverty Likelihood (%)

National USAID

Extreme

Intl. 2005 PPP

Poverty rate by Poverty Levels - Sample

ScoreNational USAID

Extreme

Intl. 2005 PPP Frequen

cy%

16

3.1.5 Household Income

Wages contributed a major share to the cash income of surveyed households

About 60% of income for both farm and non-farm households are contributed by wage

income. While the average income of farm households in 529.4, about 310.2 is contributed

by wages. In the case of Non-farm households, while average income is 3,378.4 about

2,036.4 is contributed by wages.

Income poverty was six times higher among surveyed poor farm households

While income levels of both non-farm and farm households continues to be low, income

poverty among farm households is six times higher than the non-farm households. While

average non-farm income is 3,378.4, the farm income is only 529.4. This suggests that a

great inequality exists in income among farm and non-farm households. It also indicates

the need to improve agricultural incomes.

3.1.6 Household Expenditure Surveyed households spent about four-fifth of expenditure on food A key feature found among expenditure patterns in poor households is its spending on food. Poor households normally spend over 50% of the income on food. This is much higher among surveyed households. Here over four-fifth (84%) expenditure is incurred on food. Lesser levels of income for other requirements results in this financial behaviour for poor households. This has major implications. This means lesser amount is spent on other important necessities such as education and health resulting in poor human development outcomes for the household.

17

3.1.7 Income Variability

Surveyed households were not covered against risks to lives nor livelihoods

While about 30% of surveyed households are affected by weather related risks to crop,

only 8% are covered under insurance for the same.

18

3.1.8 Gender Dimension

Women played a partial role in decision making related to livelihoods and household

issues in over half of the surveyed households

While in about two-third (64.2%)

household’s women only played a

partial role in decision making

related to crops and animals, in

about one-fourth (27.2%)

households, they played a major

role in decisions related to crops

and animals. This indicates that

while women are not fully

empowered, they do play a

decent role and are provided

space for the same in surveyed households.

Region * Women control over decisions related to crops and animals Cross tabulation

Women control over decisions related to crops and animals

Total Major role Partial role No say

Region KILIMANJARO Count 124 402 23 549

% within Region 22.6% 73.2% 4.2% 100.0%

MOROGORO Count 142 365 69 576

% within Region 24.7% 63.4% 12.0% 100.0%

MWANZA Count 182 292 50 524

% within Region 34.7% 55.7% 9.5% 100.0%

Total Count 448 1059 142 1649

% within Region 27.2% 64.2% 8.6% 100.0%

Similarly in decision making related to household expenses and purchase, about two-third (66.6%) women played a partial role in making choices and a little less than one-fourth (23.8%) women did play a major role in making such choices. This indicates that while women are not empowered in decision making related to expenditure, they do have a space which however needs to expand.

19

Region * Women control over decision related to expenses and purchase

Women control over decision related to expenses and purchase



% within Region 17.4% 75.9% 6.6% 100.0%


% within Region 24.4% 64.2% 11.4% 100.0%


% within Region 29.9% 59.5% 10.6% 100.0%

Total Count 396 1109 159 1664

% within Region 23.8% 66.6% 9.6% 100.0%

About half of the women (51.8%) had a partial say in decisions related to having a baby. In about one-fourth households (28%) they did have a major say. In about one-fifth households women did not have any say at all in matters related to decision making on having a baby. Compared to livelihood and financial matters in matters related to having children, women’s role is much more limited.

20

Region * Women control over decision related to having baby and when to have

Women control over decision related to having baby and when to have



% within Region 22.2% 60.4% 17.5% 100.0%


% within Region 23.5% 56.3% 20.2% 100.0%

MWANZA Count 206 200 121 527

% within Region 39.1% 38.0% 23.0% 100.0%

Total Count 465 861 335 1661

% within Region 28.0% 51.8% 20.2% 100.0%

Women were partially free in terms of their social mobility in over four-fifth of surveyed households

In about four-fifths households (81.9%) women had mobility outside the household either complete (26.6%) or partial (55.3%). In little less than one-fifths households (18.1%) their mobility was restricted outside the village.

Region * Women mobility outside the village

Women mobility outside the village

Total Fully free Partially free Not free


% within Region 21.4% 64.2% 14.3% 100.0%


% within Region 24.6% 56.3% 19.1% 100.0%

MWANZA Count 180 235 110 525

% within Region 34.3% 44.8% 21.0% 100.0%

Total Count 440 914 299 1653

% within Region 26.6% 55.3% 18.1% 100.0%

21

In decisions related to engagement outside home for out of home economic activities, women have no or lesser say. About three-fourth (75%) households had similar or more say in engaging out of home commercial activities. In one-fourth (25%) of the households women were less free to engage in out of home commercial activities.

Region * Women difficulty in engaging in out of home commercial activity

Women difficulty in engaging in out of home commercial activity

Total More Same Less


% within Region 41.9% 37.0% 21.1% 100.0%


% within Region 41.4% 31.4% 27.2% 100.0%


% within Region 16.3% 56.9% 26.8% 100.0%

Total Count 555 684 414 1653

% within Region 33.6% 41.4% 25.0% 100.0%

Women face difficulty in being member of farmer associations. About fourth-fifth (78.1%) households expressed that women have more difficulty than men in being part of farmer associations. In about one-fifth (21.9%) households women had lesser difficulty in being part of farmer association. This has major implications in terms of women empowerment. As a result their

participation in collective action remains marginal.

22

Region * Women difficulty in being part of farmer association

Women difficulty in being part of farmer association

Total More Same Less


% within Region 38.5% 41.6% 19.8% 100.0%


% within Region 45.1% 30.1% 24.9% 100.0%

MWANZA Count 107 308 108 523

% within Region 20.5% 58.9% 20.7% 100.0%

Total Count 580 711 361 1652

% within Region 35.1% 43.0% 21.9% 100.0%

3.2 Financial Inclusion

Only about one-third of surveyed households had access to any financial services from

formal institutions

3.2.1 Bank Accounts

About one-third (34.2%) respondents had a bank account. This varied widely across the regions. Compared to Mwanza where about two-third (68.1%) respondents had a bank account, the same in the case of Kilimanjaro was one-fifth (21.8%) respondents and Morogoro one-eighth (12.4%) respondents. This means that there are large numbers of households (two-third) which are financially excluded.

23

Region * Have bank account

Have bank account

Total Yes No

Region KILIMANJARO Count 128 471 599

% within Region 21.4% 78.6% 100.0%

MOROGORO Count 72 507 579

% within Region 12.4% 87.6% 100.0%

MWANZA Count 407 191 598

% within Region 68.1% 31.9% 100.0%

Total Count 607 1169 1776

% within Region 34.2% 65.8% 100.0%

Similarly over one-third (36.3%) households had a bank account. This varied widely across the regions. Compared to Mwanza where a little less than three-fourth (74.4%) households had a bank account, the same in the case of Kilimanjaro was one-sixth (15.1%) households and Morogoro one-fifth (19.5%) households.

Region * Family bank account

Family bank account

Total Yes No


% within Region 15.1% 84.9% 100.0%


% within Region 19.5% 80.5% 100.0%


% within Region 74.4% 25.6% 100.0%


% within Region 36.3% 63.7% 100.0%

24

3.2.2 Borrowing

Two-third of surveyed Households were indebted.

Three-fifth among indebted house-holds depend on non-institutional agencies for credit.

Two-thirds of the indebted households borrow for livelihood purposes.

About over two-third (69%) had borrowed sometime or the other and one-third (31%) had never borrowed. Among those borrowed a large majority depended on

non-institutional sources of credit. About 30.1% were dependent on friends and relatives; about 6% on money lenders and 3% on buyer of produce. Only in the

case of 23.9% household’s dependence on formal sources of credit such as cooperative, MFIs and Banks existed. A point to be noted is that despite 34.2% households having a bank account, only 12.5% actually took loans from banks and thus dependent on non-institutional sources of credit. The dependence on non-institutional agencies was much more in Morogoro region (51.3%) as compared to Kilimanjaro (26%) and Mwanza (41.4%).

25

Among the households about two-fifths (42.3%) borrowed for livelihood purposes, one-third (15.9%) for household well-being purposes and one-twelfth (8.2%) on social events and other purposes. Loan borrowing for livelihood purposes was more in Morogoro region (58.8%) in comparison to Kilimanjaro (30.1%) and Mwanza (48.3%). Borrowing for household wellbeing purposes was more in Mwanza (30.2%) in comparison to Morogoro (11.2%) and Kilimanjaro (6.3%).

To buy

agricultur

e inputs

To buy

other

business

inputs

To buy

equipm

ent

To

construct

house

For

education

purpose

For

health

purpose

For social

events

Any

other

Not

applicable

Multiple

PurposesTotal

Count 142 19 19 2 32 4 0 30 338 13 599

% within Region 23.70% 3.20% 3.20% 0.30% 5.30% 0.70% 0.00% 5.00% 56.40% 2.20% 100.00%

Count 111 150 25 4 19 43 8 21 169 37 587

% within Region 18.90% 25.60% 4.30% 0.70% 3.20% 7.30% 1.40% 3.60% 28.80% 6.30% 100.00%

Count 48 186 52 19 147 13 20 66 41 0 592

% within Region 8.10% 31.40% 8.80% 3.20% 24.80% 2.20% 3.40% 11.10% 6.90% 0.00% 100.00%

Count 301 355 96 25 198 60 28 117 548 50 1778

% within Region 16.90% 20.00% 5.40% 1.40% 11.10% 3.40% 1.60% 6.60% 30.80% 2.80% 100.00%

MWANZA

Region

Total

Region * Why borrow money Crosstabulation

Why borrow money

KILIMANJARO

MOROGORO

26

3.2.3 Savings

Only about one-third of surveyed households saved in formal institutions

Savings across formal and informal sources was equally divided. About 47.3% households had savings either in the form of home savings or had lent out. About 32.2% had saved in formal sources such as cooperative (3.7%), MFI (2.8%) and Banks (25.7%). Informal savings was much more in Morogoro (73.3%) in comparison to Kilimanjaro (40.9%) and Mwanza (28.0%). Higher number of households in Mwanza had savings in formal

sources (67.4%) in comparison to Morogoro (18%) and Kilimanjaro (11.2%). This indicates high level of financial exclusion with two-third excluded from formal financial institutions.

At home

Borrowed

to friend

or relative

With

cooperative

or any group

With

MFIs/NGO Banks

Any

other

places

Multiple

ways Total

Count 230 15 11 4 52 70 217 599

% within Region 38.40% 2.50% 1.80% 0.70% 8.70% 11.70% 36.20% 100.00%

Count 385 43 24 26 55 26 25 584

% within Region 65.90% 7.40% 4.10% 4.50% 9.40% 4.50% 4.30% 100.00%

Count 150 16 30 20 349 28 0 593

% within Region 25.30% 2.70% 5.10% 3.40% 58.90% 4.70% 0.00% 100.00%

Count 765 74 65 50 456 124 242 1776

% within Region 43.10% 4.20% 3.70% 2.80% 25.70% 7.00% 13.60% 100.00%Total

Region * How save money Crosstabulation

How save money

KILIMANJARO

MOROGORO

MWANZA

Region

27

3.2.4 Insurance

Only about one-fourth of surveyed households were protected under life risk coverage.

Only about one-sixth covered had enterprise insurance coverage.

Only about one-fourth (23.9%) of the

households were insured. A large

majority i.e., three-fourths were outside

the risk coverage through insurance.

Coverage of household through

insurance was better in Mwanza

(51.1%) in comparison to Kilimanjaro

(7.4%) and Morogoro (13.2%). This

points to lack of protection from risks for surveyed households.

Region * Insurance for self and family

Insurance for self and family

Total Yes No


% within Region 7.4% 92.6% 100.0%


% within Region 13.2% 86.8% 100.0%


% within Region 51.1% 48.9% 100.0%


% within Region 23.9% 76.1% 100.0%

28

Only about one-sixth (17.1%) households had risk coverage of their business. A large majority i.e., about five-sixths (82.9%) were outside risk coverage of their business. Risk coverage of business was much lesser in Morogoro (5.1%) than Kilimanjaro (10.7%) and Mwanza (35.7%).

Region * Insurance for business / crop

Insurance for business / crop

Total Yes No


% within Region 10.7% 89.3% 100.0%


% within Region 5.1% 94.9% 100.0%


% within Region 35.7% 64.3% 100.0%


% within Region 17.1% 82.9% 100.0%

29

3.2.5 Remittance / Money Transfer

Three-fourths of surveyed households used mobile technology for money transfer

Over three-fourths (76.3%) households send and receive money through use of mobile technology. This was much more in Mwanza where about nine-tenth (89.3%) of the households use mobile technology as compared to Kilimanjaro 76% and Morogoro 63.6%.

Region * Money received sent from mobile

Money received sent from mobile

Total Yes No


% within Region 76.0% 24.0% 100.0%


% within Region 63.6% 36.4% 100.0%


% within Region 89.3% 10.7% 100.0%


% within Region 76.3% 23.7% 100.0%

30

3.3 Smallholder Farming as a Livelihood

3.3.1 Farm Practices

Seven-eighths of surveyed farmers used traditional technology for land preparation

Land Preparation: Almost half (45.5%) of the households use hand hoe for land

preparation, followed by use of cattle (37.8%), only 12.3% use tractors. Morogoro is

having higher use (19%) of tractors by farm household.

Inter-cropping practice is prevalent in three-fifth surveyed farm households

Intercropping: Overall 62.6% respondents practice intercropping. In Morogoro

practice of intercropping is comparatively very low at 29.9% compared with

Kilimanjaro and Mwanza at 80.5% and 85.6% respectively.

Two-thirds of the surveyed farm households used seeds retained from own

production

Seed: Majority of households (65.3%) use seeds retained from own production for

cultivation. Almost 28.5% households use indigenous seed from market and only

6.2% household use improved or certified seeds. The trend is analogous in all the

three regions.

31

Close to half of the surveyed households used chemical fertilizer for productivity

enhancement

Fertilizer: Overall 44.2% of the respondents use chemical fertilizers in their fields.

Compared to Kilimanjaro (59.5%) and Mwanza (58.2%) the application of chemical

fertilizer is minimal in Morogoro (15%).

Over one-sixth households used pesticides for dealing with pest attack

Crop Protection: Almost 84.4% farm households never used pesticides and herbicides

through spraying in the farm fields. The trend is similar across the three regions.

32

One-third the surveyed households had difficulties in marketing agricultural produce

Selling of Surplus Produce: Out of all 29% had difficulties in selling the surplus crops.

Around 16.1% reported that they did not face difficulties in selling the crops. This has

implications on agricultural incomes.

Lack of transportation and non-remunerative prices were the major reasons for the

inability to market of agricultural produce

High cost of transportation to the market (13.1%) and also low prices in the accessible

markets (14.6%) are the major reasons for difficulties in selling the crops. There are

also other reasons along with these two which are indicated in the table below. In 19%

cases combination of several reasons act as a barrier for selling. In Morogoro low

prices of the produce (26.9%) play as a major difficulty for selling the crops.

33

Post-Harvest Practices:

Post-harvest practices were utilized by only about half of the surveyed farmers

Overall 42.2% respondents said that commodity was dried to reduce spoilage before

storage. Also 35.5% reported it as not an applicable question. This practice is prevalent

in Morogoro with 57.8% people practicing drying of commodity before storing. About

one-fourth did not adopt this practice.

About one-fifth of the surveyed households did not practice storage in protected

structures

Overall almost 51.1% respondents said that commodity is stored in protected

structure to protect from rats, mice and moisture. This practice is widely followed

by most of the households. Amongst regions Morogoro reported better at 64.5%

following this practice.

Around 40% of the households reported that they have treated commodity with

chemicals during storage to control insects and pests. This practices is followed in

all the regions.

34

21.5% reported that pests and insects are main cause of loss during storage of

commodity. Around half 53.1% reported that cause of loss during storage of

commodity is not applicable to them. Rats, mice and other animals also contribute

to the extent of almost 16% towards loss during storage.

35

3.3.2 Livestock and Veterinary Services

About four-fifth of the surveyed households practiced livestock rearing

Interestingly 20.5% reported that they don’t rear any kind of livestock at home. In Morogoro

45.1% reported that they don’t rear any livestock. 30% of the households keep

combinations of different livestock like goats, pigs, cattle and chickens. Goats and Cattles

are reared by 16% and 20.3% families respectively. Cattle rearing and goat rearing are

more popular.

Almost half (49.6%) of the households reported that either they don’t rear livestock or

never availed any livestock services. The remaining 50% households, those who availed

veterinary services, got services mainly from veterinary doctor (17.5%), private

organizations (15.6%) and village para-vets (11.1%). Interestingly Morogoro reported

81.3% households either don’t rear livestock or never availed any livestock services.

Livestock services are quite prevalent in Kilimanjaro region with almost 80% of the

households having access to veterinary services.

36

3.3.3 Farm Training and Extension Services:

Half of surveyed farm households excluded from extension services

Almost half (49.6%) of the households reported that they have never availed any farm

related training or extension services. In Morogoro region 80.5% reported that they have

never availed any farm related training or extension services. The remaining 50%

households, those who availed training and extension services, got services towards input

(seed, fertilizer, and pesticide) supply (12%), trainings (13%), and other services (7%) as

indicated in the table below. About 18.5% reported that they have received a combination

of different services as listed in the table below.

Extension services by the government had very limited outreach – to only 1% of the

surveyed farmers

Only about 1% receives extension services from government. Farmer organization

provides the same in about half of the cases. Training and extension services were mainly

provided by the Farmers Organization (25.6%), Church (7.5%) and others (3.5%) like

National and International NGOs, private sector initiatives etc. More than half (58%)

reported not applicable or don’t know. The prevalence of Farmer’s organization providing

training and extension services is high in Kilimanjaro (36.2%) and Mwanza (35.8%).

37

3.3.4 Farmers Groups

Two-fifth of the surveyed households were part of farmers’ groups

Overall 40.4% respondents reported that they are member of farmer’s groups. In Morogoro

the percentage of households as member of farmer’s group is less at only 24.6%, where

as in Kilimanjaro and Mwanza it is at 48.8% and 47.8% respectively. This indicates a

positive despite the fact that three-fifths are still excluded.

Out of the around 40% who are member of farmer’s groups almost 25% reported that

regular group meetings are conducted to discuss common issues and problems related

to farm and other issues.

38

About three-fourth of the surveyed households wish to be part of or continue to be in

farmers’ groups

Out of all the respondents almost 74% reported that either they are interested to become

a new member of a farmer’s group or continue if already an existing member.

Interestingly around 26% of the respondents replied otherwise.

Out of the 40% who reported that they are part of farmer’s groups, 14% said that they

received input supply from the farmer’s group. Trainings, output transportation and

output storage services were received by 3.6%, 4.3% and 1.2% respectively. Around

8.4% reported that they had received multiple services from the farmer’s group.

39

3.3.5 Demand for Services

Skill Development:

Over four-fifths of the surveyed farm households expressed the need for training and

extension services

Of the 899 farm households, about 772 expressed the need for training and extension

services. 48.3% expressed the need for combinations of different skills as indicated in the

table below followed by 33% for farm management and production related of existing

crops. 11.3% of the respondent expressed the need for learning to grow new commercial

crops.

40

Financial Services:

About two-fifth of the surveyed farmers wanted credit services, while half wanted

composite financial services inclusive of credit

Around 51.2% expressed the need for combination of loan and other financial services.

Amongst financial services demand for loan for different purposes were quite evident.

18% and 18.9% respectively expressed the need for crop loan and farm equipment loan.

Very few exclusively expressed the need for savings, insurance and pension services.

41

Farm Related Services:

While one third of the surveyed farmers expressed the need for market linkage services

(input and output) about half preferred a combination of services which also incorporated

extension and post-harvest services

Exclusively around 30.9% expressed the need for quality inputs supply like seeds,

fertilizers and pesticides. The demand for extension services for crop and livestock

together was around 11.6%. Amongst all 54.3% expressed the need for a combination of

different farm related services.

42

3.4 Non-Farm Livelihoods

3.4.1 Ownership

Women individual or joint owners in two-fifth of the surveyed non-farm enterprises

In about two-fifth (41.6%) households women were either individually or jointly owners of non-farm enterprises. About one-fifth (19.1%) of non-farm households had a single female proprietor and a less than a quarter (22.5%) had joint proprietorship of husband and wife. Female ownership either individually or jointly was more in Mwanza (53.6%) in comparison to Kilimanjaro (19.9%) and Morogoro (49.7%).

43

Region * Ownership arrangement

Ownership arrangement

Total

Female,

one proprietor

Male, one proprietor

Multiple proprietors-husband and wife

Multiple proprietors

- blood relatives

Multiple proprietors

- non-family Other

Region KILIMANJARO

Count 11 59 38 29 27 82 246

% within Region

4.5% 24.0% 15.4% 11.8% 11.0% 33.3% 100.0

%

MOROGORO Count 61 92 82 16 22 15 288

% within Region

21.2% 31.9% 28.5% 5.6% 7.6% 5.2% 100.0

%

MWANZA Count 77 89 56 15 9 2 248

% within Region

31.0% 35.9% 22.6% 6.0% 3.6% .8% 100.0

%

Total Count 149 240 176 60 58 99 782

% within Region

19.1% 30.7% 22.5% 7.7% 7.4% 12.7% 100.0

%

3.4.2 Problems faced by micro-enterprises

Access to finance and marketing were the two major challenges affecting surveyed non-

farm enterprises, affecting two-fifth of them

Access to finance was the major problem faced by enterprises (19.8%) followed by

marketing of produce (19.4%). Access to finance as a major problem was most prevalent

in Morogoro with 25.3% enterprises facing the challenge. In Kilimanjaro quality of input

supply was the major problem faced by enterprises (29.8%). Mwanza had also about one-

sixth enterprises facing the challenge of access to new technology.

Access to

finance

Quality

input

supply

Availability

of new

technology

/ machinery

/ tools

Marketin

g /

selling

related

issues

Unavailabilit

y of proper

technical and

managerial

guidance

Labour

issues

(both

quality and

quantity)

Regulatory

/ Licencing

/ Tax issues

Combina

tion of

multiple

problems Total

Count 30 71 8 39 4 10 45 31 238

% within Region 12.60% 29.80% 3.40% 16.40% 1.70% 4.20% 18.90% 13.00% 100.00%

Count 70 11 19 65 26 1 12 73 277

% within Region 25.30% 4.00% 6.90% 23.50% 9.40% 0.40% 4.30% 26.40% 100.00%

Count 50 19 40 43 15 11 15 51 244

% within Region 20.50% 7.80% 16.40% 17.60% 6.10% 4.50% 6.10% 20.90% 100.00%

Count 150 101 67 147 45 22 72 155 759

% within Region 19.80% 13.30% 8.80% 19.40% 5.90% 2.90% 9.50% 20.40% 100.00%

KILIMANJARO

MOROGORO

MWANZA

Region

Total

Region * Kind of problems faced by enterprises Crosstabulation

Kind of problems faced by enterprises

44

3.4.3 Skills and Services Received

About half of the surveyed non-farm households had received training for business

development

About half households (46.9%) stated that they acquired skill which helped them in contributing their business. This was more so in the case of Kilimanjaro where the figure was 61.3%, followed by Mwanza at 58.7% and Morogoro with the least at 22.3%.

Region * Skill acquisition contributing to business

Skill acquisition contributing to business

Total Yes No


% within Region 61.3% 38.7% 100.0%


% within Region 22.3% 77.7% 100.0%


% within Region 58.7% 41.3% 100.0%


% within Region 46.9% 53.1% 100.0%

About 45% (45.8%) enterprises stated that they received business development services for their enterprises. This was more in the case of Mwanza at 84.3% followed by Kilimanjaro at 39.4% and Morogoro at 20.5%.

Region * Business development services received by enterprise

Business development services received by enterprise

Total Yes No


% within Region 39.4% 60.6% 100.0%


% within Region 20.5% 79.5% 100.0%


% within Region 84.3% 15.7% 100.0%


% within Region 45.8% 54.2% 100.0%

45

Among the non-farm households, about 12.9% received management training followed by technical advice and training by 10.1% households. This was followed with marketing assistance by 8.8% households. Overall about 37.5% enterprises in Kilimanjaro, 19.1% enterprises in Morogoro and 83.5% in Mwanza had received some or the other type of BDS services.

3.4.4 Producers’ Groups

About one-third of surveyed non-farm enterprises had membership in associations

About 30.7% of the non-farm enterprises had membership in business network /

association. This was more in Mwanza which had 40.8% enterprises with membership in

enterprises, followed by Kilimanjaro at 36.6%. In Morogoro membership in network /

association was the least at 17%. While the larger number of enterprises still continues to

be informal, there is still scope for formalization of about two-third enterprises.

Region * Membership in business network / association

Membership in business network / association

Total Yes No


% within Region 36.6% 63.4% 100.0%


% within Region 17.0% 83.0% 100.0%


% within Region 40.8% 59.2% 100.0%


% within Region 30.7% 69.3% 100.0%

Managem

ent

training

Technical

advice and

training

Marketing

assistance

Informal

advice/traini

ng

assistance

Other types

of Non-

Financial

assistance

Combinati

on of

services

Not

Applicable

Count 25 34 15 12 17 3 177 283

% within Region 8.80% 12.00% 5.30% 4.20% 6.00% 1.10% 62.50% 100.00%

Count 15 8 22 4 3 1 225 278

% within Region 5.40% 2.90% 7.90% 1.40% 1.10% 0.40% 80.90% 100.00%

Count 61 37 32 20 25 12 37 224

% within Region 27.20% 16.50% 14.30% 8.90% 11.20% 5.40% 16.50% 100.00%

Count 101 79 69 36 45 16 439 785


Region * Type of BDS services received by Enterprise Crosstabulation

Type of BDS services received by Enterprise

Total

Region

KILIMANJARO

MOROGORO

MWANZA

46

About one-fourth (28.1%) non-farm enterprises expressed that they received benefits through membership. This was more in Mwanza at 37.2% followed by Kilimanjaro at 32.8% and Morogoro at 16.3%.

Region * Benefits received from membership

Benefits received from membership

Total Yes No Not Applicable


% within Region 32.8% 3.8% 63.4% 100.0%


% within Region 16.3% .7% 83.0% 100.0%


% within Region 37.2% 3.7% 59.2% 100.0%

Total Count 222 21 548 791

% within Region 28.1% 2.7% 69.3% 100.0%

About 28.5% non-farm enterprises expressed the type of benefits they received from membership in associations. About 12.9% benefitted through exchange of information; 3.5% benefitted through jointly selling output; 3.4% received credit. The larger number of beneficiaries from membership were from Mwanza (33.7%) followed by Kilimanjaro (34.1%) and Morogoro (16.1%). Benefits through exchange of information was most prevalent at Kilimanjaro (20.8%).

Exchange

of

information

Purchase

d inputs

jointly

Sold

output

jointly

Received

credit

through

associatio

n/group

Access to

Non-

financial

assistance

Worked

together

Combinati

on of

multiple

benefits

Not

Applicable

Count 58 2 11 3 1 7 13 184 279

% within Region 20.80% 0.70% 3.90% 1.10% 0.40% 2.50% 4.70% 65.90% 100.00%

Count 17 5 3 12 2 1 5 235 280

% within Region 6.10% 1.80% 1.10% 4.30% 0.70% 0.40% 1.80% 83.90% 100.00%

Count 24 12 13 11 2 13 3 129 207

% within Region 11.60% 5.80% 6.30% 5.30% 1.00% 6.30% 1.40% 62.30% 100.00%

Count 99 19 27 26 5 21 21 548 766

% within Region 12.90% 2.50% 3.50% 3.40% 0.70% 2.70% 2.70% 71.50% 100.00%Total

Region * Type of benefits received from membership Crosstabulation

Type of benefits received from membership

Total

Region

KILIMANJARO

MOROGORO

MWANZA

47

3.4.5 Access to Finance

About three out of ten surveyed non-farm enterprises had access to credit

29.4% of non-farm enterprises received credit for investment purposes. Mwanza was leading in credit for investment purposes with 41.8% followed by Morogoro at 26.8% and Kilimanjaro at 21%.

Region * Credit received for investment purposes

Credit received for investment purposes

Total Yes No


% within Region 21.0% 79.0% 100.0%


% within Region 26.8% 73.2% 100.0%


% within Region 41.8% 58.2% 100.0%


% within Region 29.4% 70.6% 100.0%

About 29.4% non-farm enterprises received credit. This was received more in Mwanza at 41.8%, followed by Morogoro at 26.8% and Kilimanjaro at 21.1%. Loan from informal sources was the most prevalent. 14% received credit from informal sources and 15.4% received from formal sources. About 8.4% households received loan from family and friends, followed by credit cooperative at 5.6%.

loan from

family and

friends

money

lenders

buyer of

your

produce

credit group

/ cooperative

microfinan

ce / NGObanks

other

sources

Not

Applicable

Count 5 8 8 9 2 10 19 229 290

% within Region 1.70% 2.80% 2.80% 3.10% 0.70% 3.40% 6.60% 79.00% 100.00%

Count 34 6 2 20 8 2 3 205 280

% within Region 12.10% 2.10% 0.70% 7.10% 2.90% 0.70% 1.10% 73.20% 100.00%

Count 30 10 12 17 7 28 1 146 251

% within Region 12.00% 4.00% 4.80% 6.80% 2.80% 11.20% 0.40% 58.20% 100.00%

Count 69 24 22 46 17 40 23 580 821


Region * Source of credit for the non farm business Crosstabulation

Source of credit for the non farm business

Total

Region

KILIMANJARO

MOROGORO

MWANZA

48

3.4.6 Demand for Services

Four-fifths of the surveyed non-farm households expressed the need for BDS services

Out of 900 households, about 744 (82%) have expressed the need for BDS. About one-

fourth expressed the need for training assistance, one-fourth marketing assistance, one-

fifth technical advice. The non-farm households expressed demand for business

development services. About one-fourth (25.9%) non-formal enterprises expressed the

need for informal advice & training assistance, followed by demand for marketing

assistance by 23.3% enterprises and technical advice by 21.1% enterprises. In Kilimanjaro

and Morogoro the major demand was for training assistance expressed the need for by

34.2% and 28.7% respectively. In Mwanza the major demand was for marketing

assistance.

Respondents expressed the need for services which covers both technical and business dimensions of the enterprise. Over three-fifths (60.7%) of the non-formal enterprises expressed the need for skills training with a combination of production, processing, marketing, equipment maintenance and entrepreneurial skills. In Morogoro the demand for such services came from fourth-fifth (78.9%) of the respondents. This was followed by Kilimanjaro at 63.3% and Mwanza at 38.8%.

Managem

ent

training

Technical

advice and

training

Marketing

assistanc

e

Informal

advice/trai

ning

assistanc

e

Other

types of

Non-

Financial

assistanc

e

Combinati

on of

services

Count 18 70 52 94 27 14 275

% within Region 6.50% 25.50% 18.90% 34.20% 9.80% 5.10% 100.00%

Count 38 55 67 76 7 22 265

% within Region 14.30% 20.80% 25.30% 28.70% 2.60% 8.30% 100.00%

Count 39 32 54 23 34 22 204

% within Region 19.10% 15.70% 26.50% 11.30% 16.70% 10.80% 100.00%

Count 95 157 173 193 68 58 744

% within Region 12.80% 21.10% 23.30% 25.90% 9.10% 7.80% 100.00%Total

Region * Type of BDS services would like to receive Crosstabulation

Type of BDS services would like to receive

Total

Region

KILIMANJARO

MOROGORO

MWANZA

49

Half of the surveyed non-farm households wanted a combination of services Over half of the enterprises (54.5%) expressed the need for a combination of non-financial services which covers input linkages services, advisory business development services, storage facilities, value addition services, output services etc. The demand for this large combination of services was about two-third from Morogoro and Kilimanjaro region and by about one-fourth respondents at Mwanza.

production

related

processing

of produce

marketing

skills

operating

equipment

starting

business

risk

manage

ment

franchising

Combinati

on of

above

Count 11 6 44 9 31 7 0 186 294

% within Region 3.70% 2.00% 15.00% 3.10% 10.50% 2.40% 0.00% 63.30% 100.00%

Count 6 18 15 8 8 5 0 225 285

% within Region 2.10% 6.30% 5.30% 2.80% 2.80% 1.80% 0.00% 78.90% 100.00%

Count 18 12 65 13 38 19 2 106 273

% within Region 6.60% 4.40% 23.80% 4.80% 13.90% 7.00% 0.70% 38.80% 100.00%

Count 35 36 124 30 77 31 2 517 852


Region * Skill development that will improve income Crosstabulation

Skill development that will improve income

Total

Region

KILIMANJARO

MOROGORO

MWANZA

Quality

input / raw

material

supply

advisory

services for

business

improvement

output

management,

packaging

and storage

services

local value

addition

marketing

of produce

any other

services

Combinati

on of

different

supports

Count 20 24 2 5 21 26 192 290

% within Region 6.90% 8.30% 0.70% 1.70% 7.20% 9.00% 66.20% 100.00%

Count 8 34 11 7 20 14 187 281

% within Region 2.80% 12.10% 3.90% 2.50% 7.10% 5.00% 66.50% 100.00%

Count 19 32 18 11 57 34 56 227

% within Region 8.40% 14.10% 7.90% 4.80% 25.10% 15.00% 24.70% 100.00%

Count 47 90 31 23 98 74 435 798


Region * Non financial services that will be helpful to improve production and income Crosstabulation

Non financial services that will be helpful to improve production and income

Total

Region

KILIMANJARO

MOROGORO

MWANZA

50

3.4.7 Skill Development

While a little less than half of those surveyed had attended skills training, only about one-sixth received formal skills training About 45.4% of the respondents stated that they attended skill training. The larger proportion of those who attended skill training was at Mwanza at 59.5%, followed by Kilimanjaro at 54.4% and the least at Morogoro at 22.4%.

Region * Skill training attended Cross tabulation

Skill training attended

Total Yes No


% within Region 54.4% 45.6% 100.0%


% within Region 22.4% 77.6% 100.0%


% within Region 59.5% 40.5% 100.0%


% within Region 45.4% 54.6% 100.0%

Only about one-sixth (15.3%) received the formal certification i.e., VETA certification. The larger proportion of VETA certification recipients were at Mwanza at 30.3% followed by Kilimanjaro at 9.3% and Morogoro at 6%.

Region * VETA Certification Cross tabulation

VETA Certification

Total Yes No


% within Region 9.3% 90.7% 100.0%


% within Region 6.0% 94.0% 100.0%


% within Region 30.3% 69.7% 100.0%


% within Region 15.3% 84.7% 100.0%

51

About seven-eighths of the surveyed non-farm enterprise were desirous of attending skills training About seven-eighth (87%) expressed that they would like to attend skill training. This was similar across all the three regions.

Region * Wish attending skill training Cross tabulation

Wish attending skill training

Total Yes No


% within Region 88.8% 11.2% 100.0%


% within Region 82.8% 17.2% 100.0%


% within Region 89.3% 10.7% 100.0%


% within Region 87.0% 13.0% 100.0%

52

4. Conclusion

The study revealed a high level of inadequacy of livelihoods i.e., in about 60% of

households, not enough to earn above the poverty line. This was true among both the

farm and non-farm households. While incomes among both the farm and non-farm

households were low, farm households were receiving one-sixth lesser income than non-

farm households. Wages tended to be the major contributors to household income.

Major reasons for the poor livelihood status were found to be

exclusion from financial services,

exclusion from agricultural extension,

lack of business development services and skills training,

lack of post-harvest support, and

low access to and under-developed markets,

The findings showed that about two-third households were financially excluded. About

three-fourth were indebted and from among them three-fifths were dependent on non-

institutional sources for credit. Over five-sixths were also not covered for any business /

livelihood risk.

It was found that farm households lacked access to finance, training and extension

services, post-harvest support, market linkage services etc. which in turn were contributing

low agricultural incomes. While there are farmer groups, there are large number still

uncovered and were to become part of the same.

Among non-farm enterprises, finance and marketing were the two major challenges. Most

of them were also non-formal enterprises with implications in mobilizing capital.

About four-fifths of households expressed the need for an integrated set of services which

included credit, insurance, extension services, market linkage services, post-harvest

services, business development services, skills training etc.

Among the youth, half had ended their education by the time they completed primary

education. But they were desirous and willing to take up vocational education and skills

training for employment.

A positive finding was equal participation of women in the workforce. They played partial

role both within household and in outside sphere. However, this needs to further widen.

The study showed that while there were livelihood challenges which need to be

addressed, the desire of the community and its search for livelihood solutions can be a

basis for a new generation of integrated livelihood promotion initiatives.

53

Annexure

1. List of Wards/Villages, Divisions, Districts and Regions Covered

55

2. Questionnaire – Farm

LIVELIHOOD BASELINE SURVEY QUESTIONNAIRE for the ALPs in TANZANIA

Farm

Investigators’ Sheet

Form Serial : Date :

(Région/District/Division/Location S. No.)

Form Category (round it) : Y – W / Y – M / NY – W / NY - M

Name of the Réspondent :

Mobile No: Rural (1) / Urban (2):

House No: Village (R) / Area (U) :

Ward : Division:

District: Region:

Investigator Code (Please enter the code alloted to you) :

(To be filled by Investigator) Name :

Signature :

Supervisor Code (Please enter the code alloted to you) :

(To be filled by Supervisor) Name:

Signature :

Verified and approved by Code (Please enter the code alloted to you)

(To be filled by Chief Investigator) Name

Signature

56

The following section has to be filled by the Data Entry Team

Data Entry Date :

Item of work: Team Member

Code Name Signature

Verified by :

Data entry by :

Quality check :

57

1. Individual Information / Respondent Information

(a) Name

(b) Age:

1 = less than 25 years 2 = between 25 and 30 years 3 = more than 30 years

(c) Sex:

1 = Male 2 = Female

(d) Education: 1 = Graduate 2 = Secondary 3 = Primary 4 = not completed primary 5 = never gone to school 6 = any other

(e) Marital Status:

1 = Married 2 = Unmarried 3 = Widow 4 = Single Mother 5 = Single Father

(f) Skill Training Attended:

1 = Yes 2 = No

(g) VETA Certification:

1 = Yes 2 = No

(h) Do you wish to attend skill training?

1 = Yes 2 = No

(i) Do you have a bank account?

1 = yes 2 = no

(j) Do anyone in your family has a bank account?

1 = yes 2 = no

(k) From which source often you borrow money?

1= from friends and relatives 2 = money lenders 3 = buyer of your produce 4 = farmers group / cooperative 5 = microfinance / NGO 6 = banks 7 = other sources 8 = never borrowed / not applicable

(l) Why do you borrow money? 1 = to buy agriculture inputs 2 = to buy other business inputs 3 = to buy equipment 4 = to construct house 5 = for education purpose 6 = for health purpose 7 = for social events 8 = any other 9 = not applicable

(m) How do you save money? 1 = at home 2 = borrowed to friend or relative 3 = with cooperative or any group 4 = with MFIs / NGOs 5 = banks 6 = any other places

(n) Have you taken any insurance product for self or family?

1 = yes 2 = no

(o) Have you taken any insurance for your business or crop?

1 = yes 2 = no

(p) Do you receive/send money from distant places by mobile phones?

1=yes 2=no

(q) How many male (more than 17 years) members you have in your family who work for earning?

1= four or more 2 = three 3 = two 4 = one 5 = none

(r) How many female (more than 17 years) members you have in your family who work for earning?


(s) How much land your family own?

Quantity: Unit: ( 1 = acres, 2 = hectares)

58

(t) How much land your family cultivate?


2. Family Information (PPI Questions)

(a) How many household members are 17-years-old or younger?


(b) Do all children ages 6 to 17 attend school?

1 = No 2 = Yes / no children ages 6 to 17

(c) Can the female head/spouse read and write?

1 = No 2 = Yes, but not in Kiswahili nor English 3 = No female head / spouse 4 = Yes, only in Kiswahili 5 = Yes, in English (regardless of others)

(d) What is the main building material of the floor of the main dwelling?

1 = Earth 2 = Concrete, cement, tiles, timber or other

(e) What is the main building material of the roof of the main dwelling?

1 = mud and grass 2 = grass, leaves, bamboo 3 = concrete, cement, metal sheets (GCI), asbestos sheets, tiles, or other

(f) How many bicycles, mopeds, motorcycles, tractors, or motor vehicles does your household own?

1 = none 2 = one 3 = two or more

(g) Does your household own any radios or radio cassettes?

1 = Yes 2 = No

(h) Does your household own any lanterns?

1 = Yes 2 = No

(i) Does your household own any irons (charcoal or electric)?

1 = Yes 2 = No

(j) How many tables does your household own?

1 = None 2 = One 3 = Two 4 = Three or more

59

3. Savings (in kind) behaviour In the last two years, have you bought or sold any of these assets, and if so, how much worth?

Item/Asset Bought 1 = Yes 2 = No

Bought for Tsh (‘000)

Sold 1 = Yes 2 = No

Sold for Tsh (‘000)

Land

Livestock

Housing

Vehicles

Consumer durables

Jewellery

Other

Total

60

4. Family’s non-wage income from multiple activities (all figures are in ‘000 Tsh)

Months -> Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total

Agriculture Production

Revenue during the month (Tsh)

Expenditure during the month (Tsh)

Livestock Rearing



Processing/ Manufacturing



Services / Repairs



Trading Revenue during the month (Tsh)


Any Other Activities



Total from all Activities



Net income during the month (Tsh)

61

5 Wage income from multiple sources for each working members (in ‘000 Tsh)

5. a. Male members of the family (in ‘000 Tsh)

Months -> Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Total

Wage Labour in farms/plantations

No of Person Days

Average Daily Income (Tsh)

Other Wage Labour

No of Person Days


Salary – part-time or full-tme

No of Person Days


Pensions or other government/Church payments

No of Person Days


Remittances from migrant family members

No of Person Days


Wage work on migrating (farm/non-farm)

No of Person Days


Any Other (like rent, interest, etc.)

No of Person Days


Total from all Sources

No of Person Days


62

5. b. Female members of the family (in ‘000 Tsh)



No of Person Days


Other Wage Labour

No of Person Days



No of Person Days



No of Person Days



No of Person Days



No of Person Days



No of Person Days



No of Person Days


63

6. Family Expenditure (only household level, as expenditure for earning activities has been asked separately) (in ‘000 Tsh)

Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Total

Food

Liquor

Clothes and footwear

Education

Health

Rent if paid

Electricity for home

Water for home

Transport

Interest Payment

Hiring of Labour for home

Social events/entertainment

Others

Total revenue expenditure

64

7. Income Variability due to Shocks. In the last two years how many times have you faced the following? (Extent of loss in ‘000 Tsh)

No. Adverse event No of times Extent of loss Insured? (1=yes, 2=no)

a. The crop you sowed you could not harvest due to weather problems

b. The crop you sowed you could not harvest due to other problems

c. Severe fall in prices of a crop after you harvested

d. Some of the livestock owned by you died due to disease

e. A period longer than a month that you could not get any paid work

f. Illness of a family member which required his/her to stop work

g. Illness of a family member which required hospitalisation

h. Death of a family member other than due to old age

i. Fire/flood/theft in house or shop

j. Natural disaster – cyclone/earthquake/etc.

k. Any other

8. Agriculture and Farm Related Questions (This should be used only for Farmers)

8 What is the total amount of land your household owns/ cultivates on

a regular basis? (a) Quantity :

(b) Units :

Units codes 1 = hectares 2 = acres

9 How much land does your household use for agriculture (including land that is owned, rented/leased in, and borrowed, i.e., used without payment)?

(a) Quantity :

(b) Units :

10 With which source of draught power did you cultivate the most land during the past 12 months?

1 = Tractor 2 = Donkeys/Horses 3 = Cattle (cows & bulls) 4 = hand hoe / Other 5 = Not applicable/none

65

11 How do you divide agricultural work among household members and whether men and women have different responsibilities?

Codes for source of labour: 1 = Female household members 2 = Male household members 3 = Shared among male and female household members 4 = Hired labour 5 = Other 6 = Not applicable

(a) Ploughing

(b) Hoeing

(c) Planting

(d) Weeding

(e) Applying fertilizer/pesticides

(f) Irrigation

(g) Harvesting

(h) Shelling/threshing maize/beans/groundnuts/rice

(i) Post-harvest cleaning and sorting

(j) Marketing decisions (selling, transport to market, negotiating, etc.)

12 Which crops did you plant and harvest? (multiple answer possible) Season 1 Season 2 1 = Maize, 2 = Rice, 3 = Millet, 4 = Casava, 5 = Beans, 6 = Banana, 7 = Sweet Potato, 8 = Cotton, 9 = Sugar, 10 = Cashew nuts, 11 = Sunflower, 12 = Ground Nuts, 13 = Simsim, 14 = Soya 15 = Other

13 Did you intercrop this crop with another crop? 1 = Yes , 2 = No

14 How much area did you plant to this crop? (a) Quantity :

(b) Units :

(a) Quantity :

(b) Units :

1 = hectares, 2 = acres, 3 =?

15 How much did you harvest? (a) Quantity :

(b) Units :

(a) Quantity :

(b) Units :

1 = kilogrammes, 2 = 100 kg bags, 3 = 90 kg bags, 4 = 50 kg bags, 5 = metric tonnes, 7 = quintals 8 = Other ( )

16 What kind of seed have you used? 1: retained from your own production

66

2: indigenous seed, from market 3: improved/certified seed

17 How much did you spend on seed? in ‘000 Tsh

18 What quantity of chemical fertilizer from market have you used? (a) Quantity :

(b) Units :

(a) Quantity :

(b) Units :

1 = kilogrammes, 2 = 100 kg bags, 3 = 90 kg bags, 4 = 50 kg bags, 5 = quintals 6 = Other ( )

19 How much did you spend on chemical fertilizer? in ‘000 Tsh

20 What quantity of manure have you used? (a) Quantity :

(b) Units :

(a) Quantity :

(b) Units :

1 = kilogrammes, 2 = 100 kg bags, 3 = 90 kg bags, 4 = 50 kg bags, 5 = quintals 6 = Other ( )

21 How much did you spend on manure? in ‘000 Tsh

22 How many times had you used pesticide, herbicides, or any kind of spraying

0 = not used, 1 = once, 2 = twice , 3 = thrice, 4 = more than three times

23 How much did you spend on pesticide, herbicides, or any kind of spraying?

in ‘000 Tsh

24 How much did you spend on non-labor expenses incurred to plant, tend, and harvest this crop (for example, e.g., leasing land or irrigating,)?

in ‘000 Tsh

25 How many days of labor did you hire for preparing land, weeding, harvesting or any other activities for this crop?

26 Considering cash, and the value of in-kind payment, what was the total amount you paid for this labor?

in ‘000 Tsh

27 How much of the quantity that you harvested have you sold? (a) Quantity :

(b) Units :

(a) Quantity :

(b) Units:

1 = kilogrammes, 2 = 100 kg bags, 3 = 90 kg bags, 4 = 50 kg bags, 5 = metric tonnes, 7 = quintals 8 = Other

28 Did you have any difficulty selling this crop? 1 = Yes, 2 = No

67

29 What were the two most significant problems you had selling this crop?

Problems selling crop 1 = High cost of transport to market 2 = Low prices in accessible markets 3 = High market fees/taxes 4 = Poor transportation infrastructure 5 = Trade restrictions 6 = Difficult/unable to find buyer 7 = Not able to meet quality requirements of buyers 8 = Lack of price information 9 = Unpredictable prices 10 = Farmers’ organization not effective at selling your commodities 11 = Late or slow payment from buyers 12 = Other 13 = Not applicable (no other problem)

30 Did you sell within four weeks of harvest? 1 = Yes, 2 = No

31 Did you store and sell at a later date? 1 = Yes, 2 = No

32 Did you dry the commodity adequately to reduce spoilage during storage?

1 = Yes, 2 = No

33 Did you store the commodity in a structure that kept out rats, mice, and moisture?

1 = Yes, 2 = No

34 Did you treat the commodity with chemicals during storage to control insect pests?

1 = Yes, 2 = No

35 What was the main cause of loss during storage? 1 = Mould/spoilage 2 = Pests/insects 3 = Rats/mice/etc. 4 = Other animals 5 = Other 6 = Don’t know 7 = not applicable

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36 What are the types of livestock you have? 1 = Pig 2 = Goat 3 =Cattle (Cow and Buffalo) 4 = Chickens 5 = all of them 6 = none

37 In last 12 months how much have you invested in buying new livestock? Also convert the in kind exchanges.

in ‘000 Tsh

38 What value of livestock have you sold in last 12 months? Also convert the in kind exchange.

in ‘000 Tsh

39 What is the total value of all the livestock you have? in ‘000 Tsh

40 Who provides veterinary services for your livestock? 1 = village paravet 2 = veterinary doctor 3 = Private organization 4 = NGOs 5 = Government services 6 = any other 7 = not applicable / no services

41 Did you pay for the veterinary services? 1 = yes, 2 = no

42 What kind of training have you attended /extension services have you received?

1 = input (seed, fertilizer, pesticides) supply 2 = trainings 3 = crop monitoring visits by service provider 4 = harvesting equipment supply 5 = post-harvest services 6 = market information 7 = marketing services 8 = livestock vaccination and treatment 9 = any other services 10 = not applicable

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43 Who organized trainings/extension services for you? (multiple answers possible)

1 = National/international NGO 2 = National/local government 3 = Farmers’ organization 4 = Church 5 = Private sector service provider 6 = Other 7 = Don’t know 8 = Not applicable/no (other) organization

44 How much had you paid to avail the extension services? in ‘000 Tsh

45 Are you a member of any farmer’s group or community group? (if “NO” jump to 50 )

1 = yes, 2 = no

46 How many years are you part of this group? Number of years =

47 Does group regularly meet to discuss issues and common problems?

1 = yes, 2 = no

48 What services does this group provide (multiple choice possible) 1= Training 2= Input supply 3=Output transportation 4=Output storage 5= Output marketing 6=Output processing 7= Use of common facilities 8= Channelizes government subsidies/services 9= Provides credit 10=Other

49 Would you like to be a member of a farmers’ group which provides services (read options from 48) on a fee-basis?

1 = yes, 2 = no

Baseline Survey in Tanzania – Non-Farm Form Serial No: ______________

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50. Gender Dimension

These question should be asked to both women and men respondents

(a) Do you feel women have control over deciding for their household what crops to grow and what animals to rear?

1 = Major role 2 = Partial Role 3 = No say

(b) Do you feel women have control over deciding for their household what expenses to make and what assets to buy?


(c) Do you feel women have control over deciding whether to have a baby and when to have it?


(d) Do you feel women are free to move around safely outside the village as they like for social or work purposes?

1 = Fully free 2 = Partially free 3 = Not free

(e) Do you feel women have more difficulty than men in engaging in either out-of-home commercial activities?

1 = More 2 = Same 3 = Less

(f) Do you feel women have more difficulty than men in engaging in or in playing a public role like joining an association of farmers?


51. Concluding Questions:

(a) What kind of skill development do you feel will improve your income and also

the employability? (multiple answer possible)

1 = farm management and production related – existing crops 2 = learning to grow new, commercial crops 3 = livestock rearing and management –existing livestock 4= learning to rear new type of livestock 5= fishing and related 6 = primary processing of produce 7 = marketing skills 8 = operating farm equipment 9 = organic manure production 10 = organic farming methods 11 = starting business 12 = providing farm extension services 13 = providing veterinary services 14 = soil testing and other technical skills 15 = any other


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(b) What kind of financial services do you need to improve your income from your

current farm activities? (multiple answer possible)

1 = crop Loan 2 = farm equipment loan 3 = livestock loan 4 = loan for other purposes 5 = savings 6 = crop insurance 7 = health insurance for self and family 8 = remittance services 9 = pension services 10 = any other

(c) What kind of farm related support do you think will be helpful to have better

production and improve the income? (multiple answer possible)

1 = Quality input supply (seed, pesticides, fertilizer) 2 = Extension services for farm and crop management 3 = Extension services for livestock rearing and management 4 = Loan for farm equipment 5 = Loan for working capital 6 = post-harvest management and storage services 7 = local value addition 8 = marketing of produce 9 = any other services

(d) Would you like to start a business? If so which type

1 = Buying from other farmers and selling farm produce to towns 2 = Processing and selling farm produce (in village/ in town) 3 = Selling inputs bought from the town, to other farmers in village 4 = A grocery store (in village/ in town) 5 = A restaurant (in village/ in town) 6 = A mobile phone shop (in village/ in town) 7 = A workshop for repair of vehicles (in village/ in town) 8 = A school for children 9 = Migrate to big city 10 = any other


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5. Questionnaire – Non Farm

LIVELIHOOD BASELINE SURVEY QUESTIONNAIRE for the ALPs in TANZANIA

Non-Farm

Investigator’s Sheet

Form Serial : Date :

(Région/District/Division/Location S. No.)

Form Category (round it) : Y – W / Y – M / NY – W / NY - M

Name of the Réspondent :

Mobile No: Rural (1) / Urban (2):

House No: Village (R) / Area (U) :

Ward : Division:

District: Region:

Investigator Code (Please enter the code alloted to you) :

(To be filled by Investigator) Name :

Signature :

Supervisor Code (Please enter the code alloted to you) :

(To be filled by Supervisor) Name:

Signature :

Verified and approved by Code (Please enter the code alloted to you)

(To be filled by Chief Investigator) Name

Signature


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The following section has to be filled by the Data Entry Team

Data Entry Date :

Item of work: Team Member

Code Name Signature

Verified by :

Data entry by :

Quality check :


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1. Individual Information / Respondent Information

(u) Name

(v) Age:

1 = less than 25 years 2 = between 25 and 30 years 3 = more than 30 years

(w) Sex:

1 = Male 2 = Female

(x) Education: 1 = Graduate 2 = Secondary 3 = Primary 4 = not completed primary 5 = never gone to school 6 = any other

(y) Marital Status:

1 = Married 2 = Unmarried 3 = Widow 4 = Single Mother 5 = Single Father

(z) Skill Training Attended:

1 = Yes 2 = No

(aa) VETA Certification:

1 = Yes 2 = No

(bb) Do you wish to attend skill training?

1 = Yes 2 = No

(cc) Do you have a bank account?

1 = yes 2 = no

(dd) Do anyone in your family has a bank account?

1 = yes 2 = no

(ee) From which source often you borrow money?

1= from friends and relatives 2 = money lenders 3 = buyer of your produce 4 = farmers group / cooperative 5 = microfinance / NGO 6 = banks 7 = other sources 8 = never borrowed / not applicable

(ff) Why do you borrow money?

1 = to buy agriculture inputs 2 = to buy other business inputs 3 = to buy equipment 4 = to construct house 5 = for education purpose 6 = for health purpose 7 = for social events 8 = any other 9 = not applicable

(gg) How do you save money?

1 = at home 2 = borrowed to friend or relative 3 = with cooperative or any group 4 = with MFIs / NGOs 5 = banks 6 = any other places

(hh) Have you taken any insurance product for self or family?

1 = yes 2 = no

(ii) Have you taken any insurance for your business or crop?

1 = yes 2 = no

(jj) Do you receive/send money from distant places by mobile phones?

1=yes 2=no

(kk) How many male (more than 17 years) members you have in your family who work for earning?


(ll) How many female (more than 17 years) members you have in your family who work for earning?


(mm) How much land your family own?



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(nn) How much land your family cultivate?

Quantity: Unit: (oo) ( 1 = acres, 2 =

hectares)

2. Family Information (PPI Questions)

(k) How many household members are 17-years-old or younger?


(l) Do all children ages 6 to 17 attend school?

1 = No 2 = Yes / no children ages 6 to 17

(m) Can the female head/spouse read and write?

1 = No 2 = Yes, but not in Kiswahili nor English 3 = No female head / spouse 4 = Yes, only in Kiswahili 5 = Yes, in English (regardless of others)

(n) What is the main building material of the floor of the main dwelling?

1 = Earth 2 = Concrete, cement, tiles, timber or other

(o) What is the main building material of the roof of the main dwelling?

1 = mud and grass 2 = grass, leaves, bamboo 3 = concrete, cement, metal sheets (GCI), asbestos sheets, tiles, or other

(p) How many bicycles, mopeds, motorcycles, tractors, or motor vehicles does your household own?

1 = none 2 = one 3 = two or more

(q) Does your household own any radios or radio cassettes?

1 = Yes 2 = No

(r) Does your household own any lanterns?

1 = Yes 2 = No

(s) Does your household own any irons (charcoal or electric)?

1 = Yes 2 = No

(t) How many tables does your household own?

1 = None 2 = One 3 = Two 4 = Three or more


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3. Savings (in kind) behaviour In the last two years, have you bought or sold any of these assets, and if so, how much worth?

Item/Asset Bought 1 = Yes 2 = No

Bought for Tsh (‘000)

Sold 1 = Yes 2 = No

Sold for Tsh (‘000)

Land

Livestock

Housing

Vehicles

Consumer durables

Jewellery

Other

Total


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4. Family’s non-wage income from multiple activities (all figures are in ‘000 Tsh)

Months -> Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total

Agriculture Production



Livestock Rearing



Processing/ Manufacturing



Services / Repairs



Trading Revenue during the month (Tsh)


Any Other Activities



Total from all Activities



Net income during the month (Tsh)


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5 Wage income from multiple sources for each working members (in ‘000 Tsh)

5. a. Male members of the family (in ‘000 Tsh)



No of Person Days


Other Wage Labour

No of Person Days



No of Person Days



No of Person Days



No of Person Days



No of Person Days



No of Person Days



No of Person Days



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5. b. Female members of the family (in ‘000 Tsh)



No of Person Days


Other Wage Labour

No of Person Days



No of Person Days



No of Person Days



No of Person Days



No of Person Days



No of Person Days



No of Person Days



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6. Family Expenditure (only household level, as expenditure for earning activities has been asked separately) (in ‘000 Tsh)

Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Total

Food

Liquor

Clothes and footwear

Education

Health

Rent if paid

Electricity for home

Water for home

Transport

Interest Payment

Hiring of Labour for home

Social events/entertainment

Others

Total revenue expenditure


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7. Income Variability due to Shocks (In the last two years how many times have you faced the following? (Extent of loss in ‘000 Tsh)

No. Adverse event No of times Extent of loss Insured? (1=yes, 2=no)

l. The crop you sowed you could not harvest due to weather problems

m. The crop you sowed you could not harvest due to other problems

n. Severe fall in prices of a crop after you harvested

o. Some of the livestock owned by you died due to disease

p. A period longer than a month that you could not get any paid work

q. Illness of a family member which required his/her to stop work

r. Illness of a family member which required hospitalisation

s. Death of a family member other than due to old age

t. Fire/flood/theft in house or shop

u. Natural disaster – cyclone/earthquake/etc.

v. Any other


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Non - Farm Questions

8) What product or services you produce? (see the code list separately given)

9) When did you start this enterprise? (YYYY)

10) What is the ownership arrangement?

1 = Female, one proprietor 2 = Male, one proprietor 3 = Multiple proprietors-husband and wife 4 = Multiple proprietors - blood relatives 5 = Multiple proprietors - non-family 6 = Other

11) What kind of problems the enterprise face? (multiple answers possible)

1 = Access to finance 2 = Quality input supply 3 = Availability of new technology / machinery / tools 4 = Marketing / selling related issues 5 = Unavailability of proper technical and managerial guidance 6 = Labour issues (both quality and quantity) 7 = Regulatory / Licencing / Tax issues

12) Sales of Goods and Services over the last 12 months

2012 -2013 Did this enterprise have sales this month? 1 = Yes 0 = No

What is your estimate of the approximate value of sales during each of these months? (think in terms of summing over all days worked in each of these months) (in ‘000 TSh)

Total value of goods and services sold over 12 months (Total Revenue in ‘000 TSh)

Jun,2013

May,2013

Apr,2013

Mar,2013

Feb,2013

Jan,2013

Dec,2012

Nov,2012

Oct,2012

Sept,2012

Aug,2012

July,2012


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13) Expenditure for manufacturing or provisioning of services for past 12 months (in ‘000 TSh)

Jun May Apr Mar Feb Jan Dec Nov Oct Sept Aug July Total

Input / Raw Material

Labour

Transport

Rent

Taxes/Fees

Interest Payment

Repairs

Water

Fuel (if any)

Electricity / Energy

Other Expenses

Monthly Expenses (TSh)

Total Yearly Expenditure (in ‘000 TSh):

14) Net Income of the Enterprise in (in ‘000 TSh):


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15) Present Value of the business / enterprise (in ‘000 TSh)

Items The value of today (in ‘000 TSh)

Raw Material

Furniture / Fittings

Machinery / Equipment

Hand tools

Infrastructure (if owned by the proprietor)

Land (if owned by proprietor and used in the business)

Stored Outputs

Total Value of the Business

16) Did you acquire any skills through formal training that contribute to your ability to operate this business?

1 = yes 2 = no

17) Did this enterprise receive any kind of non-financial business development services?

1 = yes 2 = no

18) What kind of non-financial business development services did this enterprise receive? (multiple answers possible)

1 = Management training 2 = Technical advice and training 3 = Marketing assistance 4 = Informal advice/training assistance 5 = Other types of Non-Financial assistance

19) What type(s) of non-financial business development services would you like to receive? (multiple answers possible)

20) Do you (the owner) belong to any business support group or informal business network such as a women’s group, trade association, and cooperative, or informal business group? (if “NO” jump to 23)

1 = yes 2 = no

21) Have you (the owner) received any benefits from such membership?

1 = yes 2 = no

22) What type(s) of benefits did you (the owner) receive from such membership?

1 = Exchange of information 2 = Purchased inputs jointly 3 = Sold output jointly 4 = Received credit through association/group 5 = Access to Non-financial assistance 6 = Worked together


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23) Has this enterprise have received any type of credit for operating and/or investment purposes? (if “NO” jump to 25)

1 = yes 2 = no

24) From which source you received credit?

1 = loan from family and friends 2 = money lenders 3 = buyer of your produce 4 = credit group / cooperative 5 = microfinance / NGO 6 = banks 7 = other sources

25. Gender Dimension

These question should be asked to both women and men respondents

(g) Do you feel women have control over deciding for their household what crops to grow and what animals to rear?


(h) Do you feel women have control over deciding for their household what expenses to make and what assets to buy?


(i) Do you feel women have control over deciding whether to have a baby and when to have it?


(j) Do you feel women are free to move around safely outside the village as they like for social or work purposes?

1 = Fully free 2 = Partially free 3 = Not free

(k) Do you feel women have more difficulty than men in engaging in either out-of-home commercial activities?


(l) Do you feel women have more difficulty than men in engaging in or in playing a public role like joining an association of farmers?



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26. Concluding Questions:

(e) What kind of skill development do you feel will improve your income and also

the employability? (multiple answer possible)

1 = production related 2 = processing of produce 3 = marketing skills 4 = operating equipment 5 = starting business 6 = risk management 7 = franchising 8 = any other

(f) What kind of financial services do you need to improve your income from your

current farm activities? (multiple answer possible)

1 = enterprise Loan 2 = equipment loan 3 = loan for other purposes 4 = savings 5 = enterprise insurance 6 = health insurance for self and family 7 = remittance services 8 = pension services

(g) What kind of farm related support do you think will be helpful to have better

production and improve the income? (multiple answer possible)

1 = Quality input / raw material supply 2 = advisory services for business improvement 3 = output management, packaging and storage services 4 = local value addition 5 = marketing of produce 6 = any other services 7 = not applicable / don’t want


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(h) Would you like to start a business? If so which type

1 = Buying from others and selling produce to towns 2 = Processing and selling (in village/ in town) 3 = Selling inputs bought from the town, to others 4 = A grocery store (in village/ in town) 5 = A restaurant (in village/ in town) 6 = A mobile phone shop (in village/ in town) 7 = A workshop for repair of vehicles (in village/ in town) 8 = A school for children 9 = Migrate to big city 10 = any other

Livelihood Baseline Survey Report Tanzania 2014 - Final 30 Apr 2014

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