project document for planning and design of the baseline survey … · 2018-02-05 · project...

Project Document for Planning and Design of the Baseline

Survey for The Abbreviated Women's Empowerment in

Agriculture Index (A-WEAI)

DRAFT FINAL

05th December 2017

Project Document for Planning and Design of the Baseline Survey for the A-WEAI 2

Table of Contents

Report Proper ......................................................................................................................3

1 Introduction ............................................................................................................................. 3

1.1 Background .......................................................................................................................................3

1.2 Objectives .........................................................................................................................................3

2 Methodology ........................................................................................................................... 5

2.1 Sample Design .................................................................................................................................5

2.2 Survey Implementation .....................................................................................................................9

3 Detailed work plan and timeline ............................................................................................. 14

3.1 Work Plan for A-WEAI Baseline Survey at Province Level ........................................................... 14

3.2 Work Plan for A-WEAI Baseline Survey at District Level .............................................................. 15

3.3 Timeline of the Survey Activities (at Province and District Level) ................................................. 17

4 Estimated budget of the A-WEAI baseline survey ................................................................. 18

4.1 Estimated Budget of the A-WEAI Baseline Survey at Province Level .......................................... 18

4.2 Estimated Budget of the A-WEAI Baseline Survey at District Level ............................................. 21

4.3 Budget Narrative of A-WEAI Baseline Survey ............................................................................... 24

Annex 1 Sample Design for Women aged 18 and above by Province ........................................................ 27

Tables

Table 1: Proportion of Population with 18 years and above by District ............................................................... 5 Table 2: Sample Allocation of Villages and Households, and Sample Precision by District ............................... 7 Table 3: Timeline of Survey Activities................................................................................................................ 17 Table 4: Estimated Budget of the A-WEAI Baseline Survey at Province Level ................................................ 18 Table 5: Estimated Budget of the A-WEAI Baseline Survey at District Level ................................................... 21 Table 6: Proportion of Population with 18+ Years Old by Province and Sex .................................................... 27 Table 7: Sample Allocation of Villages and Households and Survey Precision by Province ............................ 28

Figures

No table of figures entries found.

Disclaimer

The British Government’s Department for International Development (DFID) financed this work as part of the United Kingdom’s aid programme. However, the views and recommendations contained in this report are those of the consultant, and DFID is not responsible for, or bound by the recommendations made.

Lead Author: Prosper Mutijima QA’d, in whole or in part, by: Liberal Seburikoko, Caritas Kayilisa and Stine Joergensen


Report Proper

1 INTRODUCTION

1.1 Background

Rwanda’s National Gender Policy requires all sectors to have a gender mainstreaming strategy. The

Ministry of Agriculture and Animal Resources (MINAGRI) developed its Gender Strategy in 2010 with a

view to ensuring that both men and women get equal access and opportunities in agriculture related

interventions. Different interventions were designed to implement the above-mentioned strategy. However,

statistics still show persistent gender gaps e.g. access to different inputs and services by men and women

in agriculture, women poverty status, etc. but very few go further and analyse the underlying disempowering

factors.

This is where the Women’s Empowerment in Agriculture Index (WEAI) comes in. In December 2016,

MINAGRI requested Agri-TAF for support in producing this survey-based index, as it is one of the core

indicators of the World Bank’s Program for Results (PforR) as well as a requirement for biennial reporting

on the Malabo Commitment.

The WEAI was designed by IFPRI to measure the empowerment, agency and inclusion of women in the

agriculture sector. It was first used by USAID under its Feed the Future Programme, with the support of the

International Food Policy Research Institute (IFPRI) and Oxford Poverty and Human Development Initiative

(OPHI). In 2014, USAID prepared a baseline report on this index in 13 of its 19 Feed the Future (FTF)

countries. Rwanda was one of these and all 30 Districts were covered except those in Kigali. As the results

for Rwanda seem overly positive due to the weighting of a land rights related measure, Agri-TAF undertook

an analysis of how to apply the abbreviated WEAI (A-WEAI) differently to get more useful results to inform

policies, strategies, and plans. The Abbreviated WEAI was proposed to the Ministry as the most appropriate

methodology. IFPRI has shared a concept note from a study carried out in Kenya as well as a toolkit. Agri-

TAF worked with IFPRI and the Regional Strategic Analysis and Knowledge Support System (Re-SAKKS)

to develop a concept note on the revised methodology for computing this index for Rwanda. A technical

note on the practicability and conduct of the survey was also elaborated. Additionally, a technical note

comparing A-WEAI and WEAI was also produced.

In March 2017, Agri-TAF produced a preliminary concept note on conducting an adapted WEAI (or A-WEAI)

to provide a better baseline of the status of women’s empowerment in the agriculture sector. The aim was

to develop a full Planning and Design proposal for a fundable project to include in the P4R budget support

programme as a baseline for the PSTA4. This document is intended to be used in mobilizing resources in

order to carry out the survey.

1.2 Objectives

Three main objectives are envisaged in this conducting this survey: a) To provide baseline on the status of women in Agriculture. Gender responsive plans cannot

happen without gender-disaggregated data. It is therefore crucial to avail data that guide the design of appropriate programmes, which tackle and respond to the existing gender gaps in the sector. This will contribute to the empowerment of women in agriculture as equally important players in the sector. It will help to deliver and attain expected production, which in return contribute to the realisation of the sector’s goals and targets.

b) To guide the planning on identification of key areas in which empowerment for both men and women needs to be enhanced. A-WEAI will facilitate the identification of priority areas of empowerment. This is done through monitoring the five key domains of empowerment, which are: (i) decisions about agricultural production, (ii) access to and decision-making power about


productive resources, (iii) control of use of income, (iv) leadership in the community and (v) time allocation.

c) To track progress of empowerment through PSTA4 implementation. The A-WEAI will facilitate

the impact assessment of the PSTA4 with gender lenses. It will measure the Gender Parity Index

(GPI) within surveyed households. GPI reflects the percentage of women who are equally

empowered as the men in their households. For those households that have not achieved gender

parity, GPI shows the empowerment gap that needs to be closed for women to reach the same

level of empowerment as men.


2 METHODOLOGY

The A-WEAI baseline survey is an essentially quantitative survey that will be administered to members of

households aged 18 and above using the questionnaires on tablets (CAPI-based surveys), on a sufficiently

representative sample to inform the MINAGRI and its partners on the extent to which the agriculture budget

is empowering women in terms of productive resources, participation in decision-making in agriculture and

access to finance.

To do so, the Consulting firm assigned to this task will first have to determine the size of the required sample

according to the objectives of the study, but also taking into account the available means available in terms

of budget and time for carry out this baseline survey now and in future.

He will then have to follow the required steps for the implementation of such a survey, and thus ensure

quality work which gives more light on the present situation in order to take appropriate measures for better

participation of women in the agricultural sector.

2.1 Sample Design

The sample design of A-WEAI is a two-stage stratified sampling process:

The first stage focused on a stratified sample of villages (Enumeration Areas) from the latest

Population and Housing Census (RPHC-2012) to be drawn with probability proportional to size

(PPS) measured in terms of the census number of households;

The second stage looks at a fixed number of sample households to be selected with equal

probability within each sample Enumeration Area (EA).

Finally, all household’s members with eighteen years and above in the sample households will be

selected for interview. Table 1 (below) shows the proportion of the population aged 18 years and above per

District.

Table 1: Proportion of Population with 18 years and above by District

District Sex

Male (%) Female (%) Total (%)

Nyarugenge 2.1 1.9 4 Gasabo 3.7 3.7 7.4 Kicukiro 2.5 2.3 4.8 Nyanza 1.3 1.6 2.9 Gisagara 1.2 1.5 2.7 Nyaruguru 1.2 1.3 2.5 Huye 1.4 1.6 3 Nyamagabe 1.5 1.7 3.2 Ruhango 1.5 1.5 3 Muhanga 1.4 1.8 3.2 Kamonyi 1.9 2.1 4 Karongi 1.3 1.6 2.9 Rutsiro 1.1 1.4 2.5 Rubavu 1.5 1.8 3.3 Nyabihu 0.8 1.1 1.9 Ngororero 1.1 1.4 2.5 Rusizi 1.6 2.1 3.7 Nyamasheke 1.3 1.8 3.1 Rulindo 1.2 1.5 2.7 Gakenke 1.6 1.8 3.4 Musanze 1.6 1.9 3.5


District Sex

Male (%) Female (%) Total (%) Burera 1.4 1.8 3.2 Gicumbi 1.8 2 3.8 Rwamagana 1.4 1.8 3.2 Nyagatare 2.3 2.3 4.6 Gatsibo 1.6 1.8 3.4 Kayonza 1.4 1.5 2.9 Kirehe 1.3 1.5 2.8 Ngoma 1.1 1.4 2.5 Bugesera 1.6 1.8 3.4

Total 46.7 53.3 100.0

Source: Rwanda labour force survey (2017) - Base population: All household members with 18 years old and above

2.1.1 Sample Size

The sample size proposed is designed to get sufficiently precise estimates for the main indicators targeted

by this baseline survey.

Equation (1) indicates the formula to calculate the sample size. Given that the aim of this study is to measure

the women’s empowerment in the agricultural sector at both national and province level, the indicator of

interest (r) is unknown. Thus, the sample size is calculated using the prevalence rate of 50% to maximize

the sample size and reduce the margin of error (standard errors are inversely proportional to the square

root of the sample size: e=z*σ⁄√n). According to the Labor Force Survey (NISR: LFS, February 2017), the

proportion of households with at least one female aged 18+ years old equal to 0.89.

xe

ppzDeftn

*2

)-1(*2

(1)

Where:

n = Sample size in terms of number of respondents to be selected.

z = z-statistics corresponding to the level of confidence desired. The commonly used level of

confidence is 95% for which z is 1.96.

p = Estimate of the indicator of interest to be measured by the survey (0.5).

e = Margin of error, sampling errors or level of precision (2%). It depends very much on the size of

the sample, and very little on the size of the population. Margin of error, ranging from approximately

1% to 5% at national level and 5% to 10% at domain level.

x =proportional of households with at least one female aged eighteen years old and above.

Deft=Design effect (2)

Using the information describe above the sample size needed for this baseline survey is:

10801

89.0*2

0.0199

)5.0-1(*5.0*2

96.1*22

n Households


The sample size of households needed for this baseline survey are 10,801 households. In each primary

sampling unit (PSUs), 15 households will be selected for interview; therefore, the sample size for this

baseline will be 10,800 households.

2.1.2 Sampling Frame and Sample Allocation

The sample design provides 10,800 households in 720 Primary Sampling Unit (PSU). A primary sampling

unity is an Enumeration Area (Village) of the Rwanda Population and Housing Census 2012 (RPHC-2012).

To ensure adequate geographical distribution of the sample and given that the results should be analyzed

up to District level, the sample will be allocated equally among 30 districts (360 households per District).

Prior to sample selection, the sampling frame (RPHC-2012) will be sorted by urban and rural areas within

districts. This provides an implicit stratification of the population by urban and rural areas.

Table 2: Sample Allocation of Villages and Households, and Sample Precision by District

District Sample Villages

Sample Households

Relative Standard

Error (RSE)

Estimated 95% Confidence

Limits of P

SE P-2SE P+2SE

Nyarugenge 24 360 11% 5% 0.4 0.6 Gasabo 24 360 11% 5% 0.4 0.6 Kicukiro 24 360 11% 5% 0.4 0.6 Nyanza 24 360 11% 5% 0.4 0.6 Gisagara 24 360 11% 5% 0.4 0.6 Nyaruguru 24 360 11% 5% 0.4 0.6 Huye 24 360 11% 5% 0.4 0.6 Nyamagabe 24 360 11% 5% 0.4 0.6 Ruhango 24 360 11% 5% 0.4 0.6 Muhanga 24 360 11% 5% 0.4 0.6 Kamonyi 24 360 11% 5% 0.4 0.6 Karongi 24 360 11% 5% 0.4 0.6 Rutsiro 24 360 11% 5% 0.4 0.6 Rubavu 24 360 11% 5% 0.4 0.6 Nyabihu 24 360 11% 5% 0.4 0.6 Ngororero 24 360 11% 5% 0.4 0.6 Rusizi 24 360 11% 5% 0.4 0.6 Nyamasheke 24 360 11% 5% 0.4 0.6 Rulindo 24 360 11% 5% 0.4 0.6 Gakenke 24 360 11% 5% 0.4 0.6 Musanze 24 360 11% 5% 0.4 0.6 Burera 24 360 11% 5% 0.4 0.6 Gicumbi 24 360 11% 5% 0.4 0.6 Rwamagana 24 360 11% 5% 0.4 0.6 Nyagatare 24 360 11% 5% 0.4 0.6 Gatsibo 24 360 11% 5% 0.4 0.6 Kayonza 24 360 11% 5% 0.4 0.6 Kirehe 24 360 11% 5% 0.4 0.6 Ngoma 24 360 11% 5% 0.4 0.6 Bugesera 24 360 11% 5% 0.4 0.6

Total 720 10,800 2% 1% 0.5 0.5

A commonly used survey precision measurement is the Relative Standard Error (RSE). As for a national

level indicator, 5% RSE is a good precision and 10% RSE is acceptable, and for a domain level indicator

10% RSE is a good precision and 20% RSE is acceptable. Table 2 above shows that the survey precision

(RSE) for A-WEAI baseline survey at national level is a good precision (less than 5%) as well as for domain


level (District) is 10%. Therefore, this sample design of A-WEAI allows the researcher to estimate key

indicators up to the District level.

2.1.3 Listing Operation, Selection of Sample PSUs and Sample Households

A listing operation of households in all sample villages will be conducted before data collection in order to

provide an updated list of households for each sample village for selecting the sample households.

At first stage, 720 PSUs (Villages) will be drawn in each district by Probability Proportional to Size (PPS)

from the sampling frame. According to the sample design, 15 households will be selected from the list of

households in each sample villages by systematic sampling with equal probability. Women in dual

households and women heads of households will be represented in order to capture their dynamics.

2.1.4 Sample Weights

Two steps will be involved in the calculation of the sample weights: Calculation of the design weight and

Adjustment for non-response. The design weight of a given sample households is the inverse of the

probability of selection of a sample household. This probability is computed as the product of two

probabilities.

The first probability is the probability of selection of the village k where the sample household residing,

dmos

mospk

1

1*

Where

: Number of villages to be sampled in district h

mos1: Number of households listed RPHC-2012 in EA k

d

mos1: Total households listed from RPHC-2012 in district h

The second probability is the probability of selection of the sample household within the sample EA k.

mos2

15

hhkp Where 15 is the sample households in EA k and mos2

is the listed households in the

sample EA k.

The overall design weight is the inverse of the product of the two probabilities:

hhkPPkWk

*

1

The non-response adjusted weight is then obtained by the dividing the design weight with response rate.

Rk

WkWkAdjusted

,


Where AdjustedWK: Adjusted design weight and RK percentage of responding households among the

total eligible households in the sample EA.

2.2 Survey Implementation

The consulting firm will be responsible for delivering high quality data according to the expectation and wit

hin a timeframe defined by MINAGRI. Specifically, the consulting firm will be responsible for the following

activities and tasks:

2.2.1 Ethical Considerations

Scientific and ethical clearance will be sought from the Rwanda National Ethics Committee. Adequate measures should be taken to ensure that the process responds to quality and ethical requirements. As per United Nations Evaluation Group (UNEG) Standard and Norms, the Consulting firms should be sensitive to beliefs, manners and customs and act with integrity and honesty in relationship with all stakeholders. Furthermore, they should protect the anonymity of individual information, and respect the confidentiality of all information, which is being handled during the interview. The Consulting firms are allowed to use documents and information provided only for the tasks related to the terms of reference of the survey. Data will be stored in a secure location, kept confidential with access restricted to principal investigators. The data will be used only for planning purpose.

To this end, a "consent form" will be placed on the first page of the questionnaire, and the interviewer will wait for the respondent to give his consent before proceeding with the interview.

2.2.2 Questionnaire Review and Adaptation to the Rwanda Context

Since the A-WEAI survey was done elsewhere, the consulting firm will be given an English language copy

of the A-WEAI household questionnaire by the MINAGRI. This is a standardized questionnaire and major

changes should be avoided. The consulting firm, however, will be responsible for adapting the

questionnaires to get context-specific responses, carefully considering the importance of cross-country

comparability. The consulting firm will review the questionnaire and improve the wording, ordering, and

placement of questions where necessary to ensure objectivity and accuracy. Additionally, the firm will

collect requisite background information to inform data collection activities.

The consulting firm will be responsible for the translation of the questionnaires into the local language

(Kinyarwanda) as agreed in the preparatory meeting with the MINAGRI. One way checking whether the

translation is well done is to have the questionnaire translated, and then have someone else to do a back-

translation.

The consulting firm will carry out tablet-based surveys, preferably using CSPro software to carry out

electronic surveys. For this, the consulting firm will develop necessary scripts/programs, enter the

questionnaires electronically into tablets in suitable formats, and develop necessary web-server with the

capability to receive the completed questionnaires via internet (using Wi-Fi technology) and process them.

The programs will have the basic capabilities of tablet-based questionnaires such as efficient response

entry, skip patterns, basic validation of the data to mention a few. Paper-based surveys will only be allowed

in specific cases upon agreement, especially during the training of the interviewers to allow them

understanding the logic of the questionnaire, before the use of the questionnaires on tablets (CAPI-based

surveys).

2.2.3 Pre-Test of Questionnaires

Pretesting will ensure that the questions are relevant, well sequenced, non-ambiguous, have the

appropriate response codes, and the duration of the interviews are within reasonable limits of what is


expected. A cognitive pretesting will also be conducted to check whether respondents understand the

intended meaning of questions, and to make sure that interviewers are implementing the questionnaire and

entering responses correctly.

It will be the consulting firm’s responsibility to pretest the questionnaires. The pretesting should be

conducted for at least 75 households and two communities prior to finalizing the questionnaires.

After the pretest, a feedback session will be arranged and the questionnaires will be checked for errors

detected and issues raised during the pretesting and then the questionnaires will be revised.

2.2.4 NISR Visa Application and MINALOC Introduction Letter

As soon as the questionnaire is approved by MINAGRI, the latter submits a visa application to NISR for

approval of the methodology adopted and the questionnaire to be used in collecting the data.

Let's remember that all survey undertakers are requested to approach NISR (National Institute of Statistics

of Rwanda) two times: first in the design stage so as to get NISR approval on the proposed survey

procedures and arrangement, second after preparation of the survey report to get the approval for

publishing the results.

To facilitate collaboration between the Consulting firm and the grassroots authorities in the collection of

data, an introduction letter from MINALOC to all Mayors is required. It will be shared with community leaders

when the Consulting firm starts to work in the community.

2.2.5 Listing and Selection of Households in the Sample Villages

Prior to the A-WEAI survey interviews the listing of households will be conducted in each sample village in

order to provide the sampling frame for selection of sample households and household members to be

interviewed. Indeed, for each household the listing form will provide the total number of household members

in each household of the sample village.

The field supervisor of the listing operation will work closely with local authorities. He should verify the

boundaries of the sample village in order to ensure good coverage of the sample households. The number

of households listed in each village should be compared to the corresponding number from the frame, and

any large differences should be investigated using the maps, which will be provided by NISR. This will

facilitate the quality control of the listing coverage.

The operation of listing and selecting households to be surveyed in the sample villages will be done

nationwide by:

5 teams each composed of 1 listing supervisor and 3 listing agents for 6 working days (for a

representative sample at the Province level), keeping in mind that in the listing activities the

collaboration with the village leader is indispensable.

5 teams each composed of 1 listing supervisor and 6 listing agents for 10 working days (for a

representative sample at the District level).

The household listing exercise will be completed in a few weeks prior to the start of the pilot survey. The

advance team will visit each of the selected enumeration areas (EAs) to collect names of all household

heads of the village with the help of the head of the village or his representative. The advance team will

also verify boundaries of the village using EAs maps of the 2012 Census as provided by NISR.

Upon receipt of complete listing information for a selected EA (villages), the Consulting firm will enter the

information into an excel spreadsheet, which will be encrypted and sent through a secure file transport

protocol to a dedicated server.


Once listing information from all EAs (villages) has been received, the Consulting firm will implement the

household selection procedure. The final lists of randomly selected households along with cluster and

household identification numbers will be sent to the Field Manager, who will assign clusters and provide

the lists of selected households in those clusters to the Field Supervisors. The lists of selected households

will be used in field management tasks, and will be programmed into the CSPro instrument loaded onto

each interviewer’s tablet computer.

2.2.6 Recruit and Train Interviewers and Field Supervisors

The Consulting firm will be responsible for hiring and training of survey interviewers, field supervisors and

data entry operators (in case of a paper survey). All these field staff should be able to interact with all

classes of people, be skilled at building rapport, be experienced with dealing with numbers and have skills

on gender dynamics in households. It is recommended to recruit the same number of male and female

interviewers.

They should have at least Bachelors level of education and experience in survey work, and be available for

the entire survey period. The field staff should be trained for at least 3 days, and longer if needed. The

training will be also open to the MINAGRI Office staff. Participants will be required to attend all sessions

and prove competence through tests and exercises administered during the training.

It is also recommend allocating sufficient time for hands-on training, such as role playing and mock

interviews

It is advisable that the consulting firm will trains few extra individuals to make up for any absentee or non-

performance.

2.2.7 Pilot Survey

At the conclusion of the interviewers’ training, the entire field team will conduct a pilot survey of all survey

procedures, logistics, systems, the revised instrument, and the translations. The pilot survey will be

conducted in areas that are not part of the sample. The pilot survey will last about one day. At the end of

the day, everyone participating in the pilot survey will meet to discuss issues and challenges and to identify

solutions.

At the conclusion of the pilot, all proposed changes to the survey instrument, translations, procedures,

logistics, and systems will be documented and prioritized. The MINAGRI will work with the Survey Director

and the Field Manager to revise the survey instruments.

2.2.8 Integration of Feedback as Observed during Pilot Survey

Proposed revisions to the survey instrument and data entry program will be communicated to the Data

Manager, who will coordinate implementation, documentation, and testing of the final changes. The IT

Specialist will ensure the survey instrument, translations, and translated data entry program labels align.

Revisions to the instrument and data entry program will take some days, so there will be a hiatus between

the pilot and the initiation of fieldwork.

Once the program has passed testing, the revised program will be downloaded from the servers and loaded

onto all of the tablets by the supervisory staff of the survey organization, at the express instruction of the

Survey Director.


2.2.9 Provide Logistical and other Support to Interviewers and Field Supervisors

The interviewers and field supervisors will require logistical support and subsistence during the survey work.

The support and relevant expenses (for transport, per-diem, etc.) have to be borne by the consulting firm

in a manner consistent with the norm of similar surveys in the country.

2.2.10 Carry out the Survey in the Sample Villages

The household and village survey should be conducted during a single visit. In exceptional cases (for

example, if the respondent does not have time to continue or is not at home) it may be necessary to return

to a household or village on more than one occasion, but this should not be the norm.

For household survey, the questionnaire would preferably be administered to those who are self-identified

as members responsible for decision making within the household, usually husband and wife. However,

they should also be other members as long as there is one male or female aged 18 and above.

Also, because the subject of the survey is highly sensitive, we recommend that male enumerators interview

the male respondents, and female enumerators interview the female respondents.

To collect data in 2,880 households (representative sample at Province level), the survey will need 10

teams each composed of 1 field supervisor and 4 enumerators for a period of 12 working days.

To collect data in 10,800 households (representative sample at District level), the survey will use 15 teams

each consisting of 1 field supervisor and 4 enumerators for a period of 30 working days.

The duties of the interviewers will be:

Visit the selected households and ensure their participation;

Conduct face-to-face interviews with the selected respondents, not without first obtaining their

permission;

Record accurately the answers and code them accordingly;

Ensure completeness and accuracy of the answers and perform accuracy checks on the

questionnaires whenever applicable (for tablet-based surveys many of these will be done

automatically);

Take note on any values for categorical variables that are not already defined in the questionnaire;

Deliver completed questionnaires to field supervisors (for paper-based interviews) or transmit them

to central server over internet (tablet-based interviews);

Safeguard the confidentiality and privacy of the collected information.

The duties of the field supervisors will be:

Explain clearly to each interviewer his/her duties and responsibilities;

Provide all logistical support and materials to interviewers;

Supervise all activities of the interviewers during the data collection process through random spot

checks;

Ensure that the interviewers undertake the survey in the households chosen for the sample without

substitution;

Assess the quality of the work of the interviewers and the quality of the data from each completed

questionnaire;

Provide feedback to interviewers on quality assurance;

Liaise and report activities to the survey coordinator;

Audit 10% of the completed questionnaires for accuracy;

Check completed questionnaires and approve them for data entry.


2.2.11 Clean Data and Archive them in Suitable Form

After completion of the survey, the firm is responsible for data entry and cleaning. For tablet-based surveys

data entry is automatic as it only involves transmitting the data from tablets to a central web server and

then converting into usable format using statistical software, such as STATA. Many of the data cleaning

issues can be taken care of with tablet-based questionnaire development as most of the basic value checks

can be implemented in questionnaire scripting. At the end of data cleaning, the consulting firm should hand

over the data to the MINAGRI in STATA format, with all variables labeled and adequately documented.

2.2.12 Carry out Data Analysis, Draft Report Writing and Final Report

The consulting firm will write on the findings based on the survey and data analysis. All such findings will

be part of the survey completion report. The report will include, among others, evidence-based findings,

conclusions, lessons and recommendations, and should be free of information that is not relevant to the

overall analysis, and identify the necessary actions required to be undertaken, who should undertake those

and possible timelines. The consulting firm will submit a draft version of the report to the MINAGRI team for

comments, and will revise it after receiving comments. The consulting firm is responsible for the overall

quality of the report.

2.2.13 Prepare a GIS Database of Households

The surveys will collect GPS coordinates of the households surveyed. The consulting firm will develop a

GIS database based on those GPS coordinates. The database will have the capability of displaying

locations of the households on a map.

2.2.14 Provide Training to the MINAGRI and Districts

Upon the completion of the survey exercise, the consulting firm will provide training to the MINAGRI and

Districts to build their staff capacity to conduct similar surveys in the future.

2.2.15 Data Dissemination

The last phase to plan for in a survey is the communication of findings to respondents, to any partners and

institutions with which the data were collected. It is also a means of thanking the people who helped with

the study, but it also provides an opportunity to communicate the survey objectives and results to an

audience that is not necessarily familiar with surveys.


3 DETAILED WORK PLAN AND TIMELINE

The detailed work plan of the A-WEAI baseline survey activities is presented in the tables below according to the scenario considered.

3.1 Work Plan for A-WEAI Baseline Survey at Province Level

The baseline survey "at Province level" would be carried out during 24 working weeks, approximately 6 calendar months.

No. Activity 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

1 Questionnaire review and adaptation to Rwandan context

2 Pre-test of the questionnaire

3 Sampling design

4 NISR visa application

5 Listing of households in sample villages

6 Recruit and train enumerators and supervisors

7 Pilot survey

8 Integration of feedback as observed during Pilot exercise

9 Provide logistical and other support to enumerators and supervisors

10 Data collection in the sample villages

11 Clean data and archive them in suitable form

12 Preparer the GIS database of households

13 Data analysis and draft report writing

14 Revised Draft and Final Report

15 Provide training to the MINAGRI and Districts

16 Data dissemination


3.2 Work Plan for A-WEAI Baseline Survey at District Level

The baseline survey "at District level" would be carried out during 38 working weeks, approximately 9 calendar months.

No. Activity 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22



3 Sampling design




7 Pilot survey











Work Plan for A-WEAI Baseline Survey at District Level (cont’d)

No. Activity 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38



3 Sampling design




7 Pilot survey











3.3 Timeline of the Survey Activities (at Province and District Level)

The assignment is expected to last for about 24 weeks (approx. 6 weeks) with a representative sample at

Province level, and for about 38 weeks (approx. 9 months) with a representative sample at Province level.

The milestones are display in the table below:

Table 3: Timeline of Survey Activities

No. Milestones Timing (weeks)

At Province Level

At District Level

1 Questionnaire review and adaptation to Rwandan context 2 2

2 Pre-test of the questionnaire 1 1

3 Sampling design 1 1

4 NISR visa application 2 2

5 Listing of households in sample villages 3 3

6 Recruit and train enumerators and supervisors 2 2

7 Pilot survey 1 1

8 Integration of feedback as observed during Pilot exercise 1 1


1 1

10 Carry out the survey in the sample villages 4 12

11 Clean data and archive them in suitable form 3 4

12 Data analysis and draft report writing 3 6

13 Revised Draft and Final Report 2 3

14 Prepare the GIS database of households 1 1

15 Provide training to the MINAGRI and Districts 1 1

16 Data dissemination 3 5


4 ESTIMATED BUDGET OF THE A-WEAI BASELINE SURVEY

4.1 Estimated Budget of the A-WEAI Baseline Survey at Province Level.

Representative Sample at Province Level (Sample size = 2,880 HHs)

Table 4: Estimated Budget of the A-WEAI Baseline Survey at Province Level

Position Days Units/people Daily Rate

Total $US

USD1=RWF850

A. Regular/Permanent Personnel - all phases

71,500

Survey Director 45 1 600 27,000

Field Manager 40 1 550 22,000

Data Manager 35 1 400 14,000

IT Specialist 20 1 350 7,000

Logistics Assistant 10 1 150 1,500

B. Translation of Questionnaire 900

Translators 2 2 150 600

Translation Manager 2 1 150 300

C. Pretest 1,100

Managers 2 2 150 600

Pre-test Team Members 2 5 50 500

D. Household Listing 6,300

Listing Supervisors 6 5 60 1,800

Listers 6 15 50 4,500

E. Translation of Interviewer's Manual 900



F. Data Collection 25,200

Field Supervisors 12 10 60 7,200

Field Interviewers 12 10 50 6,000

Total Labor 105,900

II. Travel and Transportation

A. Travel (Per Diem) 25,150

1. Pre-test (2 days) 100

Managers 2 2 0 0

Team Members 2 5 10 100

2. Household Listing (6 days) 1,200

Listing Supervisors 6 5 10 300

Listers 6 15 10 900

3. Training of Trainers (2 days) 100

Master Trainer 2 3 0 0

Trainees 2 5 10 100

4. Training of Interviewers (3 days) 1,650



Trainers (suggested 1 trainer per 8 trainees)

3 10 10 300

Trainees (40 Interviewers + 5 Backups)

3 45 10 1,350

IT Specialist 3 1 0 0

5. Pilot Survey (1 day) 550

Field Manager 1 1 0 0


Field Supervisors 1 10 10 100

Trainees 1 45 10 450

6. Questionnaire/Procedures review after Pilot (1 day) 50

Field Manager & IT Specialist 1 2 0 0


7. Data Collection (20 days) 21,500

Field Coordinators 10 2 50 1,000




B. Transportation 34,140


Vehicles for Pre-test 2 1 120 240


Vehicles for Listing Supervisors 7 5 120 4,200

Motorcycles for Listers 7 15 20 2,100

3. Pilot Survey (1 day) 1,200

Vehicles for Pilot Survey 1 10 120 1,200


Vehicles for Field Coordinators 10 2 120 2,400

Vehicles for Field Teams 20 10 120 24,000

Total Travel and Transportation 59,290

III. Training Venue and Materials

A. Venue Rental 6,500

1. Listing Training (1 day) 650

Training room rental 1 1 100 100

Lunch and refreshments 1 22 25 550






Lunch and refreshments 3 60 25 4,500

4. Questionnaire/Procedures Review after Pilot (1 day) 350



B. Training Materials 3,115


1. Training Supplies 1,915

Toner cartridges 1 1 200 200

Plug adaptors 1 5 10 50

Pens 1 100 0.15 15

Writing pads 1 45 10 450

Clipboards 1 5 15 75

Bags 1 45 25 1,125

2. Printing 1,200

Total Training Venue and Materials 9,615

IV. Communication & Insurance

A. Communication Fees 6,400

Domestic Calls for Supervisors 20 15 5 1,500

Domestic Calls for Interviewers 20 40 2 1,600

Connectivity Services for Uploads 20 55 3 3,300

B. Insurance for Field Staff 10,000

Insurance for Data collection teams 20 50 10 10,000

Total Communication & Insurance 16,400

V. Administrative Cost

A. Administrative Cost 3 1 350 1,050

Total Administrative Cost 1,050

TOTAL COSTS 192,255


4.2 Estimated Budget of the A-WEAI Baseline Survey at District Level.

Representative Sample at District Level (Sample size = 10,800 HHs)

Table 5: Estimated Budget of the A-WEAI Baseline Survey at District Level

Position Days Units/people Daily Rate Total $US

I. Labor

USD1=RWF850

A. Regular/Permanent Personnel - all phases 96,500

Survey Director 60 1 600 36,000

Field Manager 55 1 550 30,250

Data Manager 50 1 400 20,000

IT Specialist 25 1 350 8,750

Logistics Assistant 10 1 150 1,500

B. Translation of Questionnaire 900



C. Pretest 2,100

Managers 2 2 150 600

Pre-test Team Members 2 15 50 1,500

D. Household Listing 18,000

Listing Supervisors 10 5 60 3,000

Listers 10 30 50 15,000

E. Translation of Interviewer's Manual 900



F. Data Collection 117,000



Total Labor 235,400

II. Travel and Transportation

A. Travel (Per Diem) 51,350


Managers 2 2 0 0

Team Members 2 5 10 100

2. Household Listing (1 days) 350

Listing Supervisors 1 5 10 50

Listers 1 30 10 300







Trainers (suggested 1 trainer per 4 trainees) 3 15 10 450

Trainees (60 Interviewers + 5 Backups) 3 65 10 1,950


5. Pilot Survey (1 day) 800

Field Managers 1 2 0 0




6. Questionnaire/Procedures review after Pilot (1 day) 150

Field Manager & IT Specialist 1 3 0 0



Field Coordinators 15 2 50 1,500




B. Transportation 90,120


Vehicles for Pre-test 2 3 120 720


Vehicles for Listing Supervisors 10 5 120 6,000

Motorcycles for Listers 10 30 20 6,000

3. Pilot Survey (1 day) 1,800

Vehicles for Pilot Survey 1 15 120 1,800


Vehicles for Field Coordinators 15 2 120 3,600

Vehicles for Field Teams 30 15 120 54,000

Total Travel and Transportation 123,470

III. Training Venue and Materials

A. Venue Rental 11,900

1. Listing Training (1 day) 1,025



2. Training of Trainers (2 days) 1,100





Lunch and refreshments 3 115 25 8,625

4. Questionnaire/Procedures Review after Pilot (1 day) 550



B. Training Materials 6,138


1. Training Supplies 4,638

Toner cartridges 1 1 200 200

Plug adaptors 1 15 10 150

Pens 1 250 0.15 38

Writing pads 1 115 10 1,150

Clipboards 1 15 15 225

Bags 1 115 25 2,875

2. Printing 1,500

Total Training Venue and Materials 18,038

IV. Communication & Insurance

A. Communication Fees 13,500

Domestic Calls for Supervisors 30 18 5 2,700

Domestic Calls for interviewers 30 60 2 3,600

Connectivity Services for Uploads 30 80 3 7,200

B. Insurance for Field Staff 15,000

Insurance for Data collection teams 20 75 10 15,000

Total Communication & Insurance 28,500

V. Administrative Cost

Administrative Cost 6 1 350 2,100

Total Administrative Cost 2,100

TOTAL COSTS 407,508


4.3 Budget Narrative of A-WEAI Baseline Survey

4.3.1 Permanent Personnel:

To carry out all the activities of the survey including training, analysis, reporting and dissemination, the

consulting firm will provide MINAGRI with key personnel, from beginning to end of the survey, composed of

Survey Director, Field Manager, Data Manager, IT Specialist and Logistics Assistant for a total cost estimated

at :

At Province level1 At District level2 a) Survey Director USD 27,000 USD 36,000

b) Field Manager USD 22,000 USD 30,250

c) Data Manager USD 14,000 USD 20,000

d) IT Specialist USD 7,000 USD 8,750

e) Logistics Assistant USD 1,500 USD 1,500

4.3.2 Preparatory works:

Preparatory works will be carried out by key personnel prior to commencing the actual activities of the survey at a total estimated cost to: At Province level At District level

a) Translation of the questionnaire: USD 900 USD 900 b) Pretest:

Fees USD 1,100 USD 2,100

Travel (Per Diem) USD 100 USD 100

Transportation USD 240 USD 720 c) Translation of interviewer’s manual USD 900 USD 900

4.3.3 Household Listing:

The first activity to be conducted in the field will be the "Household Listing" that will be carried out by 5 supervisors and 15 listing agents for 6 days (at Province level) or by 5 supervisors and 30 listing agents for 10 days (at District level ), as the case may be, for a total amount estimated at:

At Province level At District level a) Household listing:

Fees USD 6,300 USD 18,000

Travel (Per Diem) USD 1,200 USD 3,50

Transportation USD 6,300 USD 12,000

Venue rental USD 650 USD 1,025

4.3.4 Training of Field Staff and Pilot Survey:

The training of the field staff will be done in two stages: first the training of the trainers (field supervisors) for 2 days, then the training of the investigators to which will take part 5 field supervisors, 25 investigators and 5 reserves (at Province level) or 15 field supervisors and 75 interviewers and 5 reserves (at District level), as the case may be. This training will last 3 days, after which a pilot survey will be conducted outside the sampled villages. All these activities will be carried out for an amount estimated at:

At Province level At District level a) Training of Trainers:


Venue rental USD 700 USD 1,100

b) Training of interviewers:

1 "At Province level" means "in the hypothesis of a representative sample at the Province level". 2 "At District level" means "in the hypothesis of a representative sample at District level".


Travel (Per Diem) USD 1,650 USD 2,400

Venue rental USD 4,800 USD 9,225

c) Pilot survey:


Transportation USD 1,200 USD 1,800

4.3.5 Training Materials and Printing:

Training supplies and printing will be distributed to all participants in the training, including equipment for data collection, in addition to individual tablets, for an estimated amount of:

At Province level At District level a) Training supplies USD 1,915 USD 4,638

b) Printing USD 1,200 USD 1,500

4.3.6 Review of Questionnaires:

After conducting the pilot field survey, trainers and field supervisors will meet for one day to review the observations from the pilot survey to finalize the collection instruments for an estimated amount of:

At Province level At District level a) Field supervisors:


Venue rental USD 350 USD 550

4.3.7 Data Collection:

The collection of data in the field will be carried out by the respective teams for each category of investigation and will benefit from Per Diems and means of transport for all the time they will spend in the field, for an amount estimated at:

At Province level At District level a) Fees:

Field supervisors USD 7,200 USD 27,000

Interviewers USD 6,000 USD 90,000

b) Travel (Per Diem):

Field coordinators USD 1,000 USD 1,500

IT Specialist USD 500 USD 750

Field supervisors USD 4,000 USD 9,000

Interviewers USD 16,000 USD 36,000

c) Transportation:

Vehicles for Field coordinators USD 2,400 USD 3,600

Vehicles for Field teams USD 24,000 USD 54,000

4.3.8 Communication and Insurance:

To enable the survey staff to communicate with one another and with various local authorities, communication costs will be granted. And to deal with eventual ground incidents insurance will be paid for all collection staff. These two activities will be covered for an amount estimated at:

At Province level At District level a) Communication fees USD 6,400 USD 13,500

b) Insurance for field staff USD 10,000 USD 15,000


4.3.9 Administrative Cost:

Administrative costs will also be paid to cover at least the office rent during the time of the operations, i.e. from the design of the collection instruments to the production of the final report of the study, for an amount of estimated to:

At Province level At District level a) Administrative cost USD 1,050 USD 2,100

4.3.10 Total Budget:

The total cost of A-WEAI baseline survey is estimated at:

At Province level At District level USD 192,255 USD 407,508


Annex 1 Sample Design for Women aged 18 and above by Province

Sample Design

The sample design of A-WEAI is a two-stage stratified design according to which at the first stage of sampling,

a stratified sample of villages (Enumeration Areas) from the latest Rwanda Population and Housing Census

(RPHC-2012) conducted in 2012 by National Institute of Statistics of Rwanda (NISR) will be drawn with

probability proportional to size (PPS) measured in terms of the census number of households or census number

of households members, and at the second stage of sampling, a fixed number of sample households will be

selected with equal probability within each sample Enumeration Area (EA). Finally, all household’s members

with eighteen and above years old in the sample households will be selected for interview.

Table 6: Proportion of Population with 18+ Years Old by Province and Sex

Province Sex

Male Female Total

Kigali city 8.5 8.3 16.7

Southern Province 11.3 13.1 24.4

Western Province 8.9 10.9 19.8

Northern Province 7.5 8.9 16.4

Eastern Province 10.7 12.1 22.8

Total 46.7 53.3 100.0

Source: Rwanda labour force survey (2017) - Base population: All household members with 18 years old and above

Sample Size

The sample size proposed is designed to get sufficiently precise estimates for the main indicators targeted by

this baseline survey.

Equation (1) indicates the formula to calculate the sample size. Given that the aim of this study is to measure

the women’s empowerment in the agricultural sector at both national and province level, the indicator of interest

(r) is unknown. Thus, the sample size is calculated using the prevalence rate of 50% to maximize the sample

size and reduce the margin of error (standard errors are inversely proportional to the square root of the sample

size: e=z*σ⁄√n). Margin of error, ranging from approximately 4% to 5.5% at national level. Since the non-

response rate is typically under 10% in developing countries (United Nations, 2011), a value of 1.1 for k (non-

response rate), therefore, would be considered as a conservative choice (United Nations, 2011, p42). According

to the Labor Force Survey (NISR: LFS, February 2017) the mean households with at least one female aged

18+ years old equal to 0.89.

me

kpzpDeftn

*2

)-1(2 (1)

Where:

n = Sample size in terms of number of respondents to be selected.

z = z-statistics corresponding to the level of confidence desired. The commonly used level of confidence

is 95% for which z is 1.96.

r = Estimate of the indicator of interest to be measured by the survey (0.5).

e = Margin of error, sampling errors or level of precision (4%). It depends very much on the size of the

sample, and very little on the size of the population. Margin of error, ranging from approximately 4% to

5.5% at national level and 5% to 10% at domain level.


m = Mean households with at least one female with eighteen years old and above (0.89).

Deft = Design effect (2)

Using the information describe above the sample size needed for this baseline study is:

householdsn _2698

89.0*20.04

)5.0-1(*5.0*296.1*2^2

The sample size needed for this baseline survey are 2,698 households. In each primary sampling unit (village),

16 households will be selected for interview; therefore, the sample size for this baseline will be increased up to

2,880 households.

Sampling Frame and Sample Allocation

The sample design provides 2,880 households in 180 Primary Sampling Unit (PSU). A primary sampling unity

is a village of the Rwanda Population and Housing Census 2012 (RPHC-2012).

To ensure adequate geographical distribution of the sample and given that the results should be analyzed up

to Province level, the sample is allocated proportional to measure of size (people with 18+ years old) among

the 5 Provinces and 30 Districts. Prior to sample selection, the sampling frame (RPHC-2012) will be sorted by

urban and rural areas within districts. This provides an implicit stratification of the population by urban and rural

areas.

Table 7: Sample Allocation of Villages and Households and Survey Precision by Province

Province District

Sample Survey Precision

Sample Villages

Sample Households

Percentage of Sample

Households per District

RSE

Estimated

95% Confidence Limits of P

SE P-2SE P+2SE

Nyarugenge 7 112 4%

Gasabo 14 224 8%

Kicukiro 9 144 5%

City of Kigali 30 480 17% 9% 5% 0.41 0.59

Nyanza 5 80 3%

Gisagara 5 80 3%

Nyaruguru 4 64 2%

Huye 5 80 3%

Nyamagabe 6 96 3%

Ruhango 5 80 3%

Muhanga 6 96 3%

Kamonyi 7 112 4%

Southern Province 43 688 24% 8% 4% 0.42 0.58

Karongi 5 80 3%

Rutsiro 4 64 2%

Rubavu 6 96 3%

Nyabihu 3 48 2%

Ngororero 4 64 2%

Rusizi 7 112 4%


Nyamasheke 6 96 3%

Western Province 35 560 19% 9% 4% 0.41 0.59

Rulindo 5 80 3%

Gakenke 6 96 3%

Musanze 6 96 3%

Burera 6 96 3%

Gicumbi 7 112 4%

Northern Province 30 480 17% 9% 5% 0.41 0.59

Rwamagana 6 96 3%

Nyagatare 8 128 4%

Gatsibo 6 96 3%

Kayonza 5 80 3%

Kirehe 5 80 3%

Ngoma 5 80 3%

Bugesera 6 96 3%

Eastern Province 41 656 23% 8% 4% 0.42 0.58

Total 180 2,880 100% 4% 2% 0.46 0.54

A commonly used survey precision measurement is the Relative Standard Error (RSE). As for a national level

indicator, 5% RSE is a good precision and 10% RSE is acceptable, and for a domain level indicator with 10%

RSE is a good precision and 20% RSE is acceptable. Table 2 above shows that the survey precision (RSE) for

A-WEAI baseline survey at national level is a good precision (less than 5%) as well as for domain level

(Province) is less than 10%. Therefore, this sample design of A-WEAI allows the researcher to estimate the

indicators of interest of this baseline survey up to Province level.

Listing Operation, Selection of Sample PSUs and Sample Households

A listing operation of households in all sample villages will be conducted before data collection in order to

provide an updated list of households for each sample village for selecting the sample households.

At first stage, 180 PSUs (villages) will be drawn in each district by probability proportional to size (PPS) from

the sampling frame. According to the sample design, 16 households will be selected from the list of households

in each sample village by systematic sampling with equal probability.

Sample Weights

Two steps will be involved in the calculation of the sample weights: (1) calculation of the design weight and (2)

adjustment for non-response. The design weight of a given sample households is the inverse of the probability

of selection of a sample household. This probability is computed as the product of two probabilities.

The first probability is the probability of selection of the village k where the sample household residing.

dmos

mospk

1

1*

Where

: Number of villages to be sampled in district h

mos1 : Number of households listed RPHC-2012 in village k


dmos1 : Total households listed from RPHC-2012 in district h

The second probability is the probability of selection of the sample household within the sample village k.

mos2

15

hhkp Where 15 is the sample households in village k and mos2 is the listed households in the

sample village k.

The overall design weight is the inverse of the product of the two probabilities,

hhKPPKWk

*

1

The non-response adjusted weight is then obtained by the dividing the design weight with response rate.

Rk

WkWkAdjusted

,

Where Adjusted WK: Adjusted design weight and RK: percentage of responding households among the total

eligible households in the sample AE.

`

Agriculture Technical Assistance Facility

MINAGRI KG 569 Street Kigali Rwanda

[email protected]

project document for planning and design of the baseline survey … · 2018-02-05 · project...

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