Abstract

The National Institute of Statistics of Rwanda (NISR) introduced the Labour Force Survey (LFS) program to avail statistics on employment and labour market in Rwanda on a continuous basis, providing bi-annual estimates of the main labour force aggregates. The main objective of the survey is to collect data on the size and characteristics of the labour force, employment, unemployment and other labour market characteristics of the population. The survey was also designed to measure different forms of work, in particular, own-use production work and other components of labour underutilization including time-related underemployment and potential labour force in line with the new international standards, adopted by the 19th International Conference of Labour Statisticians (ICLS) in 2013.

Geographic coverage

Labour force survey data are at the National level coverage but Employment and Labour force participation rate are represented at the District level as well as by residential area.

Analysis unit

Household and individual

Universe

The target population eligible for Labor force survey is 16 years old and above resident of selected households. However, the survey also collected data on certain particular labour-market related issues such as income from employment, migrant workers and workers with disabilities. The survey consider all persons living in private households. It excludes the institutional population permanently residing in houses such as hostels; health resorts; correctional establishments etc., as well as persons living in seasonal dwellings not covered in the survey. It also excludes workers living at their work-sites.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample size determination in most household-based surveys with multi-stage stratified design is based on the principle of first calculating the required sample size for a single «domain» assuming a simple random sample design and no non-response. A domain is a well-defined population group for which estimates with pre-determined accuracy are sought. The results are then extended to allow for non-response and deviation from simple random sampling.

The sample design of the LFS is a two-stage stratified design according to which at the first stage of sampling, a stratified sample of enumeration areas from the latest population census is drawn with probabilities proportional to size measured in terms of the census number of households or census number of household members, and at the second stage of sampling, a fixed number of sample of households is selected with equal probability within each sample enumeration areas. Finally, all household members in the sample households are selected for survey interviewing.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire of the Rwanda Labour Force Survey 2018 in its present form contains a total of 149 questions organized into 9 sections and a cover page, dealing with following topics: A. Household roster (All Household member) B. Education (Person with 14 years and above) C. Identification of employed, time-related underemployed, unemployed and potential labour force (Person with 14 years and above) D. Characteristics of main job/activity (Person with 14 years and above) E. Characteristics of secondary job/activity (Person with 14 years and above) F. Past employment (Person with 14 years and above) G. Own-use production of goods and services (Person with 14 years and above) H. Subsistence foodstuff production (Person with 14 years and above & Household) I. Housing and household assets (Household)

Not all questions are addressed to every household member. For children below 14 years of age, a minimum number of questions are asked. For older youngsters and adults 14 years of age and above, the number of questions depends on the situation and activities of the person during the reference period. The basic reference period is the last 7 days prior to the date of the interview. For certain questions, however, other reference periods are used. In each case, the relevant reference period is indicated in the text of the question.

Cleaning operations

Since August 2017 an electronic data collection system has replaced paper based questionnaire and data were collected using computerized assisted interview (CAPI). Data was uploaded to NISR severs from the field via wireless network channel by synchronizing every day with the NISR server. It was carried every day to have a daily back up of data. All the activity of codification were also done to the field by interviewers who were trained. Several questions with textual responses were pre-coded in tabled in cascaded way. These concerned education (major field of study in highest qualification attained, and subject of training), occupation and branch of economic activity (at main and secondary job and past employment experience). They were coded into the corresponding national standard classifications using on-screen coding with corresponding dictionaries in Kinyarwanda. Coding of geographic areas and addresses was incorporated in the data entry program as look-up. Following coding, responses of each questionnaire were edited for blanks, missing values, duplicates, out-of-range values, and inconsistencies such as no head of household or age of child greater than age of head of household using developed batches of controlling inconsistence in CsPro and Stata. Edit rules were developed for consistency checks on questions related to the measurement of the main labour force variables, including employment, unemployment, multiple jobholding, total hours usually worked at all jobs, total hours actually worked at all jobs, status in employment at main job, etc. Corrections were made mostly with reference to the original physical questionnaire

Response rate

The response rate for labor force survey 2019 is 98.6%

Abstract

Labour statistics play an essential role in the efforts of the country to achieve decent work for all. These statistics are needed for the development of policies towards this goal and for assessing progress towards decent work.

The government of Rwanda needs updated information for monitoring progress on programs and policies as stipulated in the first National Strategy for Transformation (NST1), Sustainable Development Goals (SDGs) as well as vision 2050. To monitor progress towards these goals and targets, relevant, reliable, coherent, timely and accessible labour statistics have to be produced.

The National Institute of Statistics of Rwanda introduced the labour force survey (LFS) program since 2016 to provide key stakeholders, Ministry of Public Service and Labour and Ministry of Finance and Economic Planning, the Ministry of Education, International Labour Organization and other users, with needed labour statistics. The ultimate goal of the labour force survey is to collect data on employment and labour underutilization characteristics of the population on a continuous basis, providing quarterly estimates of the main labour force aggregates. The Rwanda Labour Force survey programme begun in 2016 with an annual sample spread into two rounds to provide bi-annual estimates of main indicators at the National level. From February 2019, the annual sample was spread into four rounds to provide estimates of main labour market indicators on quarterly basis at the National level. This specific report combine data of all four rounds for which the data collection was conducted in 2021, specifically in February, May, August and November, to provide 2021 annual estimates at national and district level where applicable.

Geographic coverage

Labor force survey data are at the National level coverage but Employment and Labour force participation rate are represented at District level as well as by residential area.

Analysis unit

Household and individual

Universe

The target population eligible for Labor force survey is 16 years old and above resident of selected households. However, the survey also collected data on certain particular labour-market related issues such as income from employment, migrant workers and workers with disabilities.

It is important to note that the suirvey is limited to persons living in private households. It excludes the institutional population permanently residing in houses such as hostels; health resorts; correctional establishments etc., as well as persons living in seasonal dwellings not covered in the survey. It also excludes workers living at their work-sites. A household is a group of persons who live together and make common provision for food and other essentials for living. The people in the group may be related or unrelated or a combination of both. A household may consist of only one person or several persons.

Kind of data

Sample survey data [ssd]

Frequency of data collection

Rwanda Labour Force Survey is conducted by quarterly basis.

Sampling procedure

The sample design of the LFS is a two-stage stratified design according to which at the first stage of sampling, a stratified sample of enumeration areas from the latest population census is drawn with probabilities proportional to size measured in terms of the census number of households or census number of household members, and at the second stage of sampling, a fixed number of sample of households is selected with equal probability within each sample enumeration areas. Finally, all household members in the sample households are selected for survey interviewing.

The scope of the survey is all persons living in private households. It excludes the institutional population permanently residing in houses such as hostels; health resorts; correctional establishments etc., as well as persons living in seasonal dwellings not covered in the survey. It also excludes workers living at their work-sites. A household is a group of persons who live together and make common provision for food and other essentials for living. The people in the group may be related or unrelated or a combination of both. A household may consist of only one person or several persons.

Sample size determination in most household-based surveys with multi-stage stratified design is based on the principle of first calculating the required sample size for a single «domain» assuming a simple random sample design and no non-response. A domain is a well-defined population group for which estimates with pre-determined accuracy are sought. The results are then extended to allow for non-response and deviation from simple random sampling. The application of this principle with the choice of parameters described below leads to a sample size requirement of 18,691 households for measuring annual unemployment with margin of errors of +/-0.3% at 95% confidence level. In these calculations, the main indicator is the ratio of unemployment to the working age population, set at r=0.024 according to the 2012 population census of Rwanda.

For more detailed information on sampling, see the survey final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The Rwanda LFS questionnaire consisted of nine sections and it was prepared in Kinyarwanda and in English.

Abstract

The main objective of the Seasonal Agriculture Survey is to provide timely, accurate, reliable and comprehensive agricultural statistics that describe the structure of agriculture in Rwanda in terms of land use, crop production and livestock to monitor current agricultural and food supply conditions and to facilitate evidence based decision making for the development of Agriculture sector.

In this regard, the National Institute of Statistics of Rwanda conducted the Seasonal Agriculture Survey (SAS) from November 2017 to October 2018 to gather up-to-date information for monitoring progress on agriculture programs and policies in Rwanda, including the Second Economic Development and Poverty Reduction Strategy (EDPRS II) and Vision 2020. This 2018 RSAS covered three agricultural seasons (A, B and C) and provides data on background characteristics of the agricultural operators, farm characteristics (area, yield and production), agricultural practices, agricultural equipments, use of crop production by agricultural operators and by large scale farmers.

Geographic coverage

National coverage allowing district-level estimation of key indicators

Analysis unit

This seasonal agriculture survey focused on the following units of analysis: Agricultural Operators and Large Scale Farmers

Universe

The RSAS 2018 targeted potential agriicultural land and large scale farmers

Kind of data

Sample survey data [ssd]

Sampling procedure

In order to provide the basis for conducting probability surveys based on complete coverage of the farm level, and as a better way of collecting agricultural data and finding better precise survey estimates, SAS used a Multiple-Frame Sampling (MFS) methodology by which, area frame was constructed and survey sample was drawn from it. Apart from that, a list frame of large-scale farmers (LSF), with at least 10 hectares of agricultural holdings, was done to complement the area frame just to cover crops mostly grown by large scale farmers and that cannot be easily covered in area frame.For detailed information regarding the sampling procedures, refer to the component of Methodology in the report.

Mode of data collection

Face-to-face [f2f]

Research instrument

There were two types of questionnaires used for this survey namely Screening questionnaire and plot questionnaires. A Screening questionnaire was used to collect information that enabled identification of a plot and its land use using the plot questionnaire. For point-sampling , the plot questionnaire is concerned with the collection of data on characteristics of crop identification, inputs (seeds, fertilizers, labor …), agricultural practices, crop production and use of production. All the surveys questionnaires used were published in English.

Cleaning operations

The CAPI method of data collection allows the enumerators in the field to collect and enter data with their tablets and then synchronize to the server at headquarters where data are received by NISR staff, checked for consistency at NISR and thereafter transmitted to analysts for tabulation using STATA software, and reporting using office Excel and word as well.

Response rate

Data collection was done in 780 segments and 222 large scale farmers holdings for Season A, whereas in Season C data was collected in 232 segments, response rate was 100% of the sample.

Data appraisal

All Farm questionnaires were subjected to two/three rounds of data quality checking. The first round was conducted by the enumerator and the second round was conducted by the team leader to check if questionnaires had been well completed by enumerators. And in most cases, questionnaires completed by one enumerator were peer-reviewed by another enumerator before being checked by the Team leader.

Abstract

The main objective of the new agricultural statistics program is to provide timely, accurate, credible and comprehensive agricultural statistics that would not only describe the structure of agriculture in Rwanda in terms of land use, crop production and livestock and can be used for food and agriculture policy formulation and planning; but also which can be used for the compilation of national accounts statistics.

In this regard, the National Institute of Statistics of Rwanda (NISR) conducted the Seasonal Agriculture Survey (SAS) from November 2012 to September 2013 to gather up-to-date information for monitoring progress on agriculture programs and policies in Rwanda, including the Economic Development and Poverty Reduction Strategy (EDPRS), the Millennium Development Goals (MDGs) and Vision 2020. This 2013 RSAS covered three agricultural seasons (A, B and C) and provides data on background characteristics of the agricultural operators, farm characteristics (area, yield and production), agricultural practices, agricultural equipment, use of crop production by agricultural operators and by large scale farmers.

Geographic coverage

National coverage

Analysis unit

Agricultural holdings

Universe

The RSAS 2013 targeted agricultural operators and large scale farmers operating in Rwanda.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was composed of two categories of respondents: Agricultural Operators and Large Scale Farmers (LSF). For the category of Agricultural Operators, the 2013 RSAS benefited from a dual frame sampling design called Multiple Frame Survey (MFS). For the category of LSF, everyone has been enumerated.

The 2013 Rwanda Seasonal Agricultural Survey (RSAS) used imagery from Rwanda Natural Resources Authority (RNRA) with a very high resolution of 25 centimeters. During the construction of the area sampling frame, the entire land area of Rwanda was subdivided into 10 non-overlapping land-use strata defined by proportion of cultivated land or other land-use characteristics. Three of these strata were chosen to be used for the survey since they were composed of agricultural land. Thereafter, agricultural land strata were delineated into segments within the Primary Sampling Units (PSU) with identifiable physical boundaries. For agricultural operators, the segments were the Second Stage Sampling (SSU) units.

The 2013 RSAS covered 327 segments, spread throughout the country during the two main agricultural seasons (A and B) and 251 segments during the Season C both in mountains and marshlands areas.

The survey covered 15,441 Agricultural Operators and 562 LSF in season A; 15,730 Agricultural Operators and 503 LSF in Season B; and 1,412 Agricultural Operators in Season C. In Season C, LSF were not covered. Each selected PSU having a size of 200 - 400 hectares was subdivided into Second Stage Sampling Units (SSUs) of around 20 hectares each, following natural boundaries. Note that for stratum 3 PSUs, a segment had a size of around 50 hectares. In every selected PSU, one SSU (or segment) was randomly selected for data collection purposes.

It is important to note that in each of agricultural season A and B, data collection was undertaken in two phases. Phase I was mainly used to collect data on demographic and social characteristics of interviewees, area under crops, crops planted, rainfall, livestock, etc. Phase II was mainly devoted to the collection of data on yield and production of crops.

Regarding the selection of respondents, from the list of LSF in Phase I of Season A or Season B, all 562 LSF were enumerated. The LSF were engaged in either Crop farming activities only or Livestock farming activities only or both Crop and Livestock farming activities. For Agricultural Operators (being the Small Scale Farmers within the segment), every selected segment was firstly screened using the screening form. That means enumerators accounted for every plot inside the segment. All tracts were either agricultural (cultivated land and fallow land) or non-agricultural land (water, forests, roads, rocky and bare soils and buildings).

During Phase I, a complete enumeration of all farmers having agricultural land and operating within the selected segment was undertaken by using a farm questionnaire. In Phase II, 25% of the Agricultural Operators undertaking either Crop farming activities only or both Crop and Livestock farming were selected and interviewed using a farm questionnaire for this phase. In Phase II, Season A, a sample of 1,799 Agricultural Operators was selected using the method of Probability Proportional to Size (PPS) in each district.

In Phase II, Season B, a sample of 1,941 Agricultural Operators was selected as follows: a) 1,545 Agricultural Operators were selected of which 1500 were from Strata 1 and 2 selected at district level, and 45 Agricultural Operators were from Stratum 3 selected at country level (they were mainly from Nyagatare, Gatsibo and Kayonza districts). Again the PPS method was used, area under crops being the measure of size in each district; also b) 500 Agricultural Operators were selected using area under crops in each district. Due to the previous selection explained in a) above only 396 were retained due to the removal of duplicates. This second sample gave weight to major crops and thus increased representativeness of crop yield in the districts.

In Season C, a screening form was used to undertake a complete enumeration and account for every plot inside the segment on which land use was taking place. From a list of Agricultural Operators having agricultural land and cultivating Season C Crops: a) A 10% sample of operators in Marshlands was selected for data collection that combined farm inputs, expenditure and production questions; b) A complete enumeration in Mountain sites was undertaken for data collection that combined farm inputs, expenditure and production questions.

Mode of data collection

Face-to-face paper [f2f]

Research instrument

There were two types of questionnaires used for this survey namely screening questionnaire and farm questionnaires. A screening questionnaire was used to collect information that enabled identification of an Agricultural Operator or Large Scale Farmer and his or her land use.

The following were the two farm questionnaires administered: a) Phase I Farm Questionnaire was used to collect data on characteristics of Agricultural Operators, crop identification and area, inputs (seeds, fertilizers, labor, …) for Agricultural Operators and large scale farmers. b) Phase 2 Farm Questionnaire was used in the collection of data on crop production and use of production.

It is important to mention thatl these Farm Questionnaires were subjected to two/three rounds of data quality checking. The first round was conducted by the enumerator and the second round was conducted by the team leader to check if the questionnaires had been well completed by the enumerators. For season C, after screening, an interview was conducted for each selected tract/Agricultural Operator using one consolidated farm questionnaire.

Questionnares are provided as external resources.

Cleaning operations

Data editing took place at different stages. First, the filled questionnaires were repatriated at NISR for office editing and coding before data entry started. Data entry of the completed and checked questionnaires was undertaken at NISR offices by 20 trained staff members using CSPro software. To ensure appropriate matching of data in questionnaires and plot area measurements from the GIS unit, a LOOKUP file was integrated in the CSPro data entry program to confirm the identification of each Agricultural Operator/LSF before starting data entry. Thereafter, data was entered in computers, edited and summarized in tables using SPSS software.

Response rate

The response rate for the Seasonal Agriculture Survey is 98%.

Data appraisal

All farm questionnaires were subjected to two/three rounds of data quality checking. The first round was conducted by the enumerator and the second round was conducted by the team leader to check if questionnaires had been completed successfully by enumerators. Additionally, in most cases, questionnaires completed by one enumerator were peer-reviewed by another enumerator before being checked by the team leader.

Overview Identification COUNTRY Rwanda TITLE Integrated Household Living Conditions Survey 2010-2011

TRANSLATED TITLE Enquête Intégrale sur les conditions de vie des ménages 2010-2011

STUDY TYPE Income/Expenditure/Household Survey SERIES INFORMATION This is the third in a series of periodic standardized income and expenditure surveys. The Rwanda EICV is conducted with a periodicity of 5 years. The surveys in the series are as follows:

EICV1 2000-2001

EICV2 2005-2006

EICV3 2010-2011

ID NUMBER RWA-NISR-EICV3-02 Version VERSION DESCRIPTION Version 2.0: Final public-use dataset

PRODUCTION DATE 2012-10-19 NOTES Version 2.0

The date of this version corresponds to the date of NISR approval of the final public-use datasets.

Overview ABSTRACT The 2010/11 Integrated Household Living Conditions Survey or EICV3 (Enquête Intégrale sur les Conditions de Vie des Ménages) is the third in the series of surveys which started in 2000/01 and is designed to monitor poverty and living conditions in Rwanda. The survey methodology has changed little over its 10 years, making it ideal for monitoring changes in the country. In 2010/11, for the first time the achieved sample size of 14,308 households in the EICV3 was sufficient to provide estimates which are reliable at the level of the district.

KIND OF DATA Sample survey data [ssd]

UNITS OF ANALYSIS For the purposes of this study, the following units of analysis are considered:

-communities

-households

-persons

Scope NOTES The scope of survey is defined by the need to evaluate poverty determinants and effects of poverty in various domains. This includes gathering data in specific sectors and examning summary statistics and computed indicators by consumption indicator, gender etc. The survey primarily seeks to compute household consumption aggregates and correlate consumption to the following areas are within the scope and integrated into the survey:

• Education (education expenditures): general education, curriculum, vocational training and, higher learning, school-leaving, literacy and apprenticeship.

• Health (health expenditures): disability and health problems, general health and preventative vaccination over the past 12 months.

• Migration (travel expenditures): rural-urban migration, internal and external migration.

• Housing (expenditures on utilities, rent etc.): status of the housing occupancy, services and installations, physical characteristics of the dwelling, access and satisfaction towards basic services.

• Economic activity (revenue): unemployment, underemployment and job search, occupation, wage or salaried employment characteristics, VUP Activities, all other activities, domestic work.

• Non-agricultural activities (revenue): activity status, formal and informal sector activity.

• Agriculture (income and expenditure) : livestock, land and agricultural equipment, details of holding parcels/blocs and agricultural policy changes, crop harvests and use on a large and small scale crop production, harvests and use, transformation (processing) of agricultural products.

In addition to the specific sector information, consumption and/or wealth holding information was collected:

• Consumption: Expenditure on non food items, food expenditure, subsistence farming (own consumption) with different recall periods.

• Other cash flows : transfers out by household, transfers received by the household, income support programs & other revenues (excluding all incomes accrued from saving), VUP, UBUDEHE & RSSP schemes, other expenditure (excluding expenditures related to any form of saving).

• Stock items: credit, durable assets and savings (household assets and liabilities)

TOPICS Topic Vocabulary URI consumption/consumer behaviour [1.1] CESSDA http://www.nesstar.org/rdf/common economic conditions and indicators [1.2] CESSDA http://www.nesstar.org/rdf/common EDUCATION [6] CESSDA http://www.nesstar.org/rdf/common general health [8.4] CESSDA http://www.nesstar.org/rdf/common employment [3.1] CESSDA http://www.nesstar.org/rdf/common unemployment [3.5] CESSDA http://www.nesstar.org/rdf/common housing [10.1] CESSDA http://www.nesstar.org/rdf/common time use [13.9] CESSDA http://www.nesstar.org/rdf/common migration [14.3] CESSDA http://www.nesstar.org/rdf/common information technology [16.2] CESSDA http://www.nesstar.org/rdf/common Coverage GEOGRAPHIC COVERAGE This is a national survey with representivity at the (5) provicial and (30) district level and includes urban and rural households.

GEOGRAPHIC UNIT The cluster

UNIVERSE All household members.

Producers and Sponsors PRIMARY INVESTIGATOR(S) Name Affiliation National Institute of Statistics of Rwanda (NISR) Ministry of finance and economics planning (MINECOFIN) OTHER PRODUCER(S) Name Affiliation Role Oxford Policy Management DFID Permanante assistance Geoffrey Greenwell UNDP Designer of data system David...

Abstract

The Estimating the Size of Populations through a Household Survey (EPSHS), sought to assess the feasibility of the network scale-up and proxy respondent methods for estimating the sizes of key populations at higher risk of HIV infection and to compare the results to other estimates of the population sizes. The study was undertaken based on the assumption that if these methods proved to be feasible with a reasonable amount of data collection for making adjustments, countries would be able to add this module to their standard household survey to produce size estimates for their key populations at higher risk of HIV infection. This would facilitate better programmatic responses for prevention and caring for people living with HIV and would improve the understanding of how HIV is being transmitted in the country.

The specific objectives of the ESPHS were: 1. To assess the feasibility of the network scale-up method for estimating the sizes of key populations at higher risk of HIV infection in a Sub-Saharan African context; 2. To assess the feasibility of the proxy respondent method for estimating the sizes of key populations at higher risk of HIV infection in a Sub-Saharan African context; 3. To estimate the population size of MSM, FSW, IDU, and clients of sex workers in Rwanda at a national level; 4. To compare the estimates of the sizes of key populations at higher risk for HIV produced by the network scale-up and proxy respondent methods with estimates produced using other methods; and 5. To collect data to be used in scientific publications comparing the use of the network scale-up method in different national and cultural environments.

Geographic coverage

National

Analysis unit

• Household
• Individual

Sampling procedure

The Estimating the Size of Populations through a Household Survey (ESPHS) used a two-stage sample design, implemented in a representative sample of 2,125 households selected nationwide in which all women and men age 15 years and above where eligible for an individual interview. The sampling frame used was the preparatory frame for the Rwanda Population and Housing Census (RPHC), which was conducted in 2012; it was provided by the National Institute of Statistics of Rwanda (NISR).

The sampling frame was a complete list of natural villages covering the whole country (14,837 villages). Two strata were defined: the city of Kigali and the rest of the country. One hundred and thirty Primary Sampling Units (PSU) were selected from the sampling frame (35 in Kigali and 95 in the other stratum). To reduce clustering effect, only 20 households were selected per cluster in Kigali and 15 in the other clusters. As a result, 33 percent of the households in the sample were located in Kigali.

The list of households in each cluster was updated upon arrival of the survey team in the cluster. Once the listing had been updated, a number was assigned to each existing household in the cluster. The supervisor then identified the households to be interviewed in the survey by using a table in which the households were randomly pre-selected. This table also provided the list of households pre-selected for each of the two different definitions of what it means "to know" someone.

For further details on sample design and implementation, see Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Estimating the Size of Populations through a Household Survey (ESPHS) used two types of questionnaires: a household questionnaire and an individual questionnaire. The same individual questionnaire was used to interview both women and men. In addition, two versions of the individual questionnaire were developed, using two different definitions of what it means “to know” someone. Each version of the individual questionnaire was used in half of the selected households.

Cleaning operations

The processing of the ESPHS data began shortly after the fieldwork commenced. Completed questionnaires were returned periodically from the field to the SPH office in Kigali, where they were entered and checked for consistency by data processing personnel who were specially trained for this task. Data were entered using CSPro, a programme specially developed for use in DHS surveys. All data were entered twice (100 percent verification). The concurrent processing of the data was a distinct advantage for data quality, because the School of Public Health had the opportunity to advise field teams of problems detected during data entry. The data entry and editing phase of the survey was completed in late August 2011.

Response rate

A total of 2,125 households were selected in the sample, of which 2,120 were actually occupied at the time of the interview. The number of occupied households successfully interviewed was 2,102, yielding a household response rate of 99 percent.

From the households interviewed, 2,629 women were found to be eligible and 2,567 were interviewed, giving a response rate of 98 percent. Interviews with men covered 2,102 of the eligible 2,149 men, yielding a response rate of 98 percent. The response rates do not significantly vary by type of questionnaire or residence.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) non-sampling errors, and (2) sampling errors. Non-sampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made to minimize this type of error during the implementation of the Rwanda ESPHS 2011, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the ESPHS 2011 is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the ESPHS 2011 sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the ESPHS 2011 is a SAS program. This program uses the Taylor linearization method for variance estimation for survey estimates that are means or proportions.

A more detailed description of estimates of sampling errors are presented in Appendix B of the survey report.

Abstract

The Establishment Census 2011 was conducted as a joint undertaking by the Ministry of Public Service and Labour (MIFOTRA), Ministry of Trade and Industry (MINICOM), Private Sector Federation (PSF) and the National Institute of Statistics of Rwanda (NISR). The Census provides a comprehensive picture of Establishments in Rwanda, both formal and informal, for the first time. It will allow Government, private sector associations, researchers and others to base economic planning, policy design, analysis and beyond upon robust information leading to more effective results and findings. An establishment is defined as an enterprise or (part of) with a constant site that performs one or more economic activities under one administration. The holder of the establishment could be a natural or nominal person, or governmental body.

The 2011 Establishment Census is designed to achieve the following objectives: a) To produce a comprehensive and updated data profile of all economic activities practiced by establishments operating in Rwanda; b) To provide detailed tabulations for the establishments' characteristics, e.g. geographical location, number of employees, registration status, legal status, ownership, sector, manager/owner gender; c) To produce data necessary to classify establishments according to size into Micro, small, middle, large and very large; d) To lay out the data foundation needed to identify formal and informal economic sectors in Rwanda; e) To help establishing a Business Register that can be utilized in carrying out future economic sample surveys and creating comprehensive data base and Geographic Information System (GIS) of the business community in Rwanda.

Geographic coverage

National coverage

Analysis unit

Establishment

Universe

All Rwandan establishments from the nationally sampled area. An establishment is defined as an enterprise or (part of) with a constant site that performs one or more economic activities under one administration. The holder of the establishment could be a natural or nominal person, or governmental body. The definition of an establishment used in the 2011 Census does not include: a) Street Vendors b) Taxis and Motor drivers

Kind of data

Census/enumeration data [cen]

Sampling procedure

With the aim of avoiding omissions and/or duplications the enumerators followed a rigorous approach in enumerating all establishments in a village. A thorough and systematic canvassing of the whole village was performed by the enumerator before completing the Census questionnaires.

Step 1: In the first working day, the enumerator started with identification of the village boundaries and illustration of a sketch map showing these boundaries. This indicated whether one or two banks of a boundary are included in the village.

Step 2 (Boundaries): Boundaries are then allocated a number, with the first being selected in such a way that the whole village is located on the right hand side (B1 on the Illustrative Diagram of village canvassing). Whilst walking along this boundary, the enumerator lists the establishments along the right bank by entering their serial numbers on the sketch map and on the wall right to the entrance as well as in the Establishment Listing Form of serial numbers, establishment names and establishment addresses. If both banks of the boundary lied in the village, the enumerator returned back on the boundary to count the establishments existing on the other bank of the boundary.

Step 3 (Roads): Once establishments along the boundary are listed, the enumerator enters the first road inside the village from the boundary, counting all establishments on the right bank of this boundary followed by the establishments on the left bank (R1 on the Illustrative Diagram). After counting, listing and locating on the sketch map each of the establishments on the road (R1), the enumerator enters the first branch on the right hand side (R2) following the same process, and then carries the same out for all other branches. When all roads and branches associated with the boundary (B1) are finished, the enumerator continues the process from the next boundary (B2). However attention is paid to the possibility that some of the establishments may have already been counted (for example R3 has already been counted as an associated branch of R1). In the case of a market place that include several establishments, the enumerator need not to locate on the sketch map each and every establishment present in the market, instead writing a range of serial numbers and filling in the listing form for each establishment.

Sampling deviation

In total, the Establishment Census 2011 enumerated 127,662 establishments. Despite 127,662 establishments being recorded, the majority of the results presented within this report focus on a slightly reduced sample of 123,526 operating establishments (most of the others were permanently closed).

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was developed according to the objectives specified in Chapter 1 in English, and then translated into Kinyarwanda. In order to minimise potential problems arising in the field, several tests were performed. Feedback was provided by trainees in the central training centre in Kigali, which was then followed by a formal pre-test (see below). After this, revisions were incorporated into the survey with additional feedback being given by trainees at the local training centres around the country. The final version of the questionnaire was developed in Kinyarwanda and translated back into English

Cleaning operations

Data editing was continuously performed during and after the data entry phase in order to detect out-of-range and/or inconsistent data values. Appropriate actions were taken to introduce necessary corrections or deal with incorrect data. In many cases follow up contacts with the establishments were made in order to verify previously reported data. Upon producing the clean data file, statistical tabulations have been generated and are subsequent chapters present these census tabulations.

Abstract

The EICV4 survey (Enquête Intégrale sur les Conditions de Vie des ménages) was conducted over a 12-month cycle from October 2013 to October 2014. Data collection was divided into 10 cycles in order to represent seasonality in the income and consumption data. A main cross-sectional sample survey, a panel survey and a VUP sample survey were conducted simultaneously.

The EICV4 provides information on poverty and living conditions in Rwanda and measures changes over time as part of the on-going monitoring of the Poverty Reduction Strategy and other Government policies. The survey data are also very important for national accounts and updating the consumer price index (CPI).

Geographic coverage

National coverage

Analysis unit

Households

Universe

All household members (variable s1q15 identifies household membership).

Kind of data

Sample survey data [ssd]

Sampling procedure

The EICV4 cross sectional (CS) sample includes two independent subsets selected using different sampling frames: 1) a new EICV4 sample of households in enumeration areas (EAs) selected using the 2012 Rwanda Population and Housing Census frame and 2) a panel of households selected from 177 EICV3 villages. A new listing of households was conducted in both the panel and new sample clusters in order to update the frame for the CS Survey. The sample households in the new CS sample EAs were selected from the new listing.

1) The new EICV4 sample The main sampling frame for the EICV4 is based on the 2012 Rwanda Census. The primary sampling units (PSUs) are the 2012 census Enumeration Areas (EAs). In the Census, each EA was classified as urban, semi-urban, peri-urban or rural. The urban areas include Kigali-Ville and the district capitals. The semi-urban areas generally correspond to smaller towns that have service facilities and markets. The peri-urban areas currently have the characteristics of rural areas, but they are located on the periphery of urban areas and are designated for future development. For the EICV4 sampling frame, the semi-urban areas were grouped with the urban strata, and the peri-urban areas with the rural strata. This results in a final distribution of 17.2% urban households and 82.8% rural households in the sampling frame. EAs in the 177 EICV3 sample villages selected for the panel study were excluded from the sampling frame, in order to avoid any overlap between the two samples.

The new EICV4 sample of 12,312 households was selected using a stratified two-stage design. At the first stage, sample EAs were selected within each stratum (district) with probability proportional to size (PPS) from the ordered list of EAs in the sampling frame. The EAs are implicitly stratified by urban and rural strata within each district, ordered first by urban, semi-urban, peri-urban and rural areas, and then geographically by sector, cellule, village and EA codes. This first stage sampling procedure provides a proportional allocation of the sample to the urban and rural areas of each district. At the second stage, households in each sample EA are selected from the listing. For the three districts in Kigali Province, 9 households were selected in each sample EA as original households; for the remaining 27 districts, 12 households were selected in each sample EA as original households. In addition, a reserve sample of 3 replacement households were selected for each sample EA in Kigali Province and 4 replacement households for each sample EA in the remaining provinces.

This new EICV4 sample contains 12,312 households, including 12,233 original households and 79 replacement households.

2) Households from 177 EICV3 villages used for panel study The second component of the EICV4 cross sectional sample consists of all the sample households interviewed inside the 177 EICV3 villages selected for the panel study (including any replacements households and panel split households inside the clusters). Within each of the 177 villages, all households that were interviewed during EICV3 were included in the cross-sectional sample. When an EICV3 sample household moved and a new household occupied the same house in the cluster, it was interviewed for the Cross-Sectional Survey, and assigned a PID (dependency) code of 94. If an EICV3 household was empty or not found, a random replacement household was selected for the EICV4 Cross-Sectional Survey from the new listing of the sample cluster, and assigned a PID code of 95. The sample households with PID codes 94 and 95 are only used for the cross-sectional study, not the panel study.

This second component of the cross-sectional sample includes 2108 households drawn from the 177 EICV3 villages sampled for the panel study. These include 1604 original EICV3 households, 181 dependent household splitting from the original household in the same cluster, along with 243 households living in the dwelling formerly occupied by a panel household and 80 replacement households in the cluster in order to have 9/12 households per cluster.

The reason why we combine the EICV4 data from the new and panel clusters for the CS analysis is to obtain the most accurate CS estimates. In the case of the CS estimates from the combined samples, the additional data from the 177 sample panel clusters will result in a significant reduction in the variance component of the MSE. Although the bias of the CS data from the sample panel clusters may slightly increase the bias component, this bias is very small compared to the corresponding reduction in the variance component. Therefore, the CS results from the EICV4 data for the combined new and panel clusters can be considered more accurate than the corresponding results using only the EICV4 data for the new sample clusters.

In total, the final EICV4 cross-sectional sample contains 14,419 households.

3) Assignment of EAs to cycles and sub-cycles Data collection covering a period of 12 month is divided into 10 cycles to represent seasonality in consumption, income, employment and agricultural activity patterns. For rural enumeration, each cycle is further divided into two sub-cycles. For the 177 EICV3 villages, the cycle and sub-cycle were pre-determined. Households were re-interviewed in the same cycle, corresponding to the same time of the year as they were in EICV3. To assign cycles to the new EICV4 sample EAs, random cycle numbers from 1 to 10 were generated to identify the selection sequence. For the 27 districts outside Kigali, sub-cycle numbers of 1 or 2 were assigned systematically with a random start. This process ensured that the final distribution of the sample EAs to cycles and sub-cycles was geographically representative within each district.

Mode of data collection

Face-to-face [f2f]

Research instrument

The same questionnaire was used for cross-sectional, panel and VUP samples. Part A of the questionnaire contains modules on household and individual information. Part B is on agriculture and consumption. The questionnaire was developed in English, and translated into Kinyarwanda.

Questionnaire design took into account the requests raised by major data users and stakeholders, as well as consistency with the previous EICV questionnaires. In addition to methodological improvements, some simplifications were made:

-The major changes introduced in this survey were changes to Section 6, the Economic Activity. Further questioning was added on unemployment and underemployment in response to questions from users, and also to comply with international standards. The section was simplified to enable the analysis to be undertaken by local analysts.

-The Section on the VUP participation was expanded to provide more information, better classification of beneficiaries and to provide greater consistency within the questionnaire. The same questionnaire is to be used on the separate VUP sample which runs in parallel with the EICV4

-The health section was reduced to try to cut respondent burden, as health-related information is being collected by Demographic and Health Surveys (DHS).

-The expenditure section was changed in minor ways to provide better information for national accounts (housing investment) and for CPI weights (retail outlets).

Questionnaire was tested in pilot surveys and amended in time prior to the fieldwork starting in October 2013. The complete questionnaire is provided as external resources.

Cleaning operations

A day before the interview started, the enumerator, accompanied by a controller, did an introduction to household, explaining how often they will come in that household and delivering a letter indicating that the HH has been selected.

During the field work, after each cycle, the data processing team produced tables and reports of inconsistencies, which were checked by the field supervisor. The data entry system also contained consistency checks that alerted the data entry operators. In case of an alert, the questionnaire was sent back to the supervisor of data entry for correction.

Response rate

Out of the 12,312 sample households selected in the new sample clusters for EICV4, only 79 were non-interviews, for a response rate of 99.4% for this sample. All of the 79 non-interviews were replaced. There were only 12 refusals, and there were few cases of houses that were empty or not found, given that the listing was conducted very close to the interviewing period.

Abstract

The 2010/11 Integrated Household Living Conditions Survey or EICV3 (Enquête Intégrale sur les Conditions de Vie des Ménages) is the third in the series of surveys which started in 2000/01 and is designed to monitor poverty and living conditions in Rwanda. The survey methodology has changed little over its 10 years, making it ideal for monitoring changes in the country. In 2010/11, for the first time the achieved sample size of 14,308 households in the EICV3 was sufficient to provide estimates which are reliable at the level of the district.

Geographic coverage

This is a national survey with representivity at the (5) provicial and (30) district level and includes urban and rural households.

Analysis unit

Households

Universe

All household members.

Kind of data

Sample survey data [ssd]

Sampling procedure

The EICV3 sampled a total of 14,310 households in 1,230 sample villages. The sample selection methodology for EICV3 was based on a stratified two-stage sample design.

At the first sampling stage the sample villages for EICV3 were selected within each stratum (district) systematically with PPS from the ordered list of villages in the sampling frame. The measure of size for each village was based on the total number of households identified in the sampling frame of villages. The villages within each district were ordered first by urban, mixed and rural areas, and then geographically by secteur, cellule and village codes. This provided implicit geographic stratification of the sampling frame for each district, and ensured a proportional allocation of the sample to the urban and rural areas of each district.

A listing of households was conducted in each sample village prior to the EICV3 enumeration in order to select the sample households. A systematic sample of 9 households was selected from the listing for each sample village in Kigali Province and 12 households for each sample rural village in the remaining provinces. A reserve sample of 3 replacement households was selected for each sample village in Kigali Province and 4 replacement households for each sample village in the remaining provinces.

Sampling deviation

Two households were dropped due to incomplete data. These were in the urban zone (Kigali). These include Nyraungenge and Kikukiro. These have been adjusted in the weights.

Mode of data collection

Face-to-face paper [f2f]

Research instrument

SECTION 1: Information on members of household

SECTION 2: Education PART A: General education PART B1: Curriculum PART B2: Vocational training and, higher learning PART C: Leaving school PART D: Literacy and apprenticeship

SECTION 3: Health PART A: Disability and health problems during the past 2 weeks PART B: Health and preventative vaccination over the past 12 months

SECTION 4: Migrations and domestic trips PART A: Migration PART B: Domestic trips

SECTION 5: Housing PART A: Background and status of the housing occupancy PART B: Housing expenses PART C: Services and installations PART D: Physical characteristics of the dwelling PART E: Access and satisfaction towards basic services

SECTION 6A: Economic activity in last 12 months & last 7 days PART A: Filter questions and all the occupations you have carried out over the last 12 months.

SECTION 6B: Unemployment, underemployment and job search

SECTION 6C: Occupation (for members of the household aged 6 years and above who have been employed)

SECTION 6D: Waged or salaried employment (farm and non-farm)

SECTION 7A: Non-agricultural activities (business)

SECTION 7B: Non-agricultural activities (business))

SECTION 8: Agriculture PART A1: Livestock PART A2: Livestock (continued) one cow per poor family policy, animals and pasture PART A3: Livestock (continued) sale of livestock products PART A4: Livestock (continued) expenditure on livestock during the last 12 months PART B: Land and agricultural equipment PART C: Details of holding parcels/blocs and agricultural policy changes PART D: Crop harvests and use on a large scale PART E: Small scale crops - harvests and use. PART F: Other income from agriculture PART G: The cost and expenditure on agricultural activities. PART H: Transformation (processing) of agricultural products.

SECTION 9: Household expenditure and subsistence farming
PART A: Expenditure on non-food items PART B: Food expenditure PARTC: Subsistence farming

SECTION 10: Transfers of incomes, other revenues and expenditures PART A: Transfers made by household (out) PART B: Transfers received by the household (in) PART C: Income support programmes & other revenues PART D: VUP, UBUDEHE & RSSP SCHEMES PART E: Other expenditure (excluding expenditures related to any form of saving)

SECTION 11: Credit, durables and savings PART A: Credit PART B: Durable household goods PART C: Savings

Cleaning operations

Extensive cleaning was carried out on the EICV-W3 data. A detailed report on this process is available at the NISR.

Response rate

Traditionally response rates are high in Rwanda so it is not surprising to have response rates greater than 95%. For computing the response rates, the DHS definition is used:

1. The numerator are the number of households with a completed household interview.
2. The denominator: is the sum of number of households with a completed household interview, households that live in the dwelling but no competent respondent was at home, households with permanently postponed or refused interviews, and households for which the dwelling was not found.
3. Unoccupied or abandoned dwelling are excluded (no household lives in the dwelling, address is not a dwelling, or the dwelling is destroyed).

The numerator is: 14,308. To compute the denominator the following are considered:

Completed:14,308
HH not found:132
Sick or died:59 Refused: 48 Other: 63* Dropped:2

Total:14,612

Thus, the response rate is computed at 98%.

Notes: *Other is included in the denominator despite the uncertainty of the reason. **Excluded from the denominator are 368 homes that were reported abandoned or changed.

Dwelling changed (Nyakatasi): 115

Dwelling changed other reason: 253

Sampling error estimates

Sampling errors for key indicators are provided in the Annexes of the EICV3 reports (main indicators report and thematic reports).

Abstract

Obtaining reliable size estimates for key populations is crucial for the Rwanda Biomedical Center/Institute of HIV/AIDS, Disease Prevention and Control (RBC/IHDPC) and their partners to design an effective HIV response in line with the national HIV strategy. Estimating the size of key populations at higher risk for HIV not only allows for an understanding of the magnitude of the response that is needed, but also helps in more accurately projecting the future of the epidemic in Rwanda. To be effective, it is important to produce consistent and comparable estimates over time. The following study utilized a single household survey to estimate the size of several key populations, including sex workers, men who have sex with men (MSM), injecting drug users (IDU), and clients of sex workers. These populations include several groups outlined in the National Strategic Plan for HIV and AIDS as most at risk for HIV infection, specifically sex workers and MSM.

Geographic coverage

National

Analysis unit

• Household
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

The ESPHS used a two-stage sample design, implemented in a representative sample of 2,125 households selected nationwide in which all women and men age 15 years and above where eligible for an individual interview. Each of these households was visited to obtain information using the Household Questionnaire. All women and all men age 15 years and above were eligible to be individually interviewed, if they were either usual residents of the household or visitors present in the household on the night before the survey. A total of 4,669 women and men were successfully interviewed.

The sampling frame used was the preparatory frame for the Rwanda Population and Housing Census (RPHC) 2012, provided by the National Institute of Statistics of Rwanda (NISR). The sampling frame is a complete list of natural villages covering the whole country (14,837 villages). Two strata were defined: the city of Kigali and the rest of the country. One hundred and thirty Primary Sampling Units (PSU) were selected from the sampling frame (35 in Kigali and 95 in the other stratum). To reduce clustering effect, only 20 households were selected per cluster in Kigali and 15 in the other clusters. As a result, 33 percent of the households in the sample were located in Kigali.

The list of households in each cluster was updated upon arrival of the survey team in the cluster. Once the listing had been updated, a number was assigned to each existing household in the cluster. The supervisor then identified the households to be interviewed in the survey by using a table in which the households were randomly pre-selected. This table also provided the list of households pre-selected for each of the two different definitions of what it means “to know” someone.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey used two types of questionnaires: a household questionnaire and an individual questionnaire. The same individual questionnaire was used to interview both women and men. In addition, two versions of the individual questionnaire were developed, using two different definitions of what it means “to know” someone. Each version of the individual questionnaire was used in half of the selected households.

Household questionnaire: The Household Questionnaire was a short version of the 2011 Rwanda DHS questionnaire. It was primarily used to list all the usual members and visitors in the selected households and to collect some basic information on the characteristics of each person listed, including age, sex, status of residence, and marital status. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, and ownership of various durable goods. This information was used to create an index representing the wealth of the households. The wealth index is a proxy for long-term standard of living of the households and is used in the following analysis as a background characteristic of the respondents who are members of these households.

Individual questionnaire: The individual questionnaire was organized accordingly and included six sections: - Respondent’s background; - Known population; - Summation; - Target population; - Proxy respondent; and - Stigma.

Cleaning operations

The processing of the ESPHS data began shortly after the fieldwork commenced. Completed questionnaires were returned periodically from the field to the SPH office in Kigali, where they were entered and checked for consistency by data processing personnel who were specially trained for this task. Data were entered using CSPro, a programme specially developed for use in DHS surveys. All data were entered twice (100 percent verification). The concurrent processing of the data was a distinct advantage for data quality, because the School of Public Health had the opportunity to advise field teams of problems detected during data entry. The data entry and editing phase of the survey was completed in late August 2011.

Response rate

The number of occupied households successfully interviewed was 2,102, yielding a household response rate of 99%. From the households interviewed, 2,629 women were found to be eligible and 2,567 were interviewed, giving a response rate of 98%. Interviews with men covered 2,102 of the eligible 2,149 men, yielding a response rate of 98%. The response rates do not significantly vary by type of questionnaire or residence.

Abstract

Rwanda has experienced fast socio, demographic and economic transformation since the year 2000. It recorded on average 8 percent GDP annual growth since then, mainly driven by agriculture and services. In addition socio-demographic indicators have witnessed substantial improvement from 2000 onward. Following the crisis period; the 1994 genocide against the Tutsi era, the country developed a long term vision “Vision 2020” with five year development programs: PRSP, EDPRS1 and EDPRS2, the main objective of each of the programs was poverty reduction. The need to adequately plan interventions and monitor progress in poverty reduction, estimation of absolute monetary poverty in Rwanda started in a regular manner since 2001 when the first Household Living Condition Survey (Enquête Intégrale sur les Conditions de Vie des Ménages- EICV1) was carried out. EICV 2013-14 provided an update on the level of poverty based on 2013-14 Integrated Household Living Conditions Survey (EICV4) focusing on poverty as measured in consumption terms. The survey also highlighted other trend dimensions of living conditions captured in other surveys that complemented and provided a holistic understanding of poverty and living conditions.

The results of the 2013-14 EICV indicated substantial progress in poverty reduction and improvement in other socio-economic and demographic indicators in the last three years. The survey shows that poverty went down from 44.9 percent in 2011 to 39.1 percent in 2014 and extreme poverty from 24.1 percent to 16.3 percent. This follows similar reduction between 2006 and 2011 where poverty dropped from 56.7 percent to 44.9 percent and extreme poverty decreased from 35.8 percent to 24.1 percent. Inequality reduced with both the Gini coefficient dropping from 0.49 in 2011 to 0.45 in 2014. The ratio of the wealthiest 10 percent to the poorest 10 percent dropped from 6.36 to 6.01 during the same period.

Generally the progress was impressive, however challenges have remained. Many Rwandans are still poor and for many others living conditions still needed to be improved especially in areas of education and employment. The frequency of Integrated Household Living Conditions Survey is every three years, the survey was conducted by the National Institute of Statistics of Rwanda (NISR) in collaboration with different stakeholders in the country over a period of 12 months between October 2013 and October 2014.

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Communities

Kind of data

Sample survey data [ssd]

Sampling procedure

Rwanda used a basic needs approach to measure poverty. In this survey households were classified as poor or non-poor based on consumption per adult equivalent compared with a total poverty line of 159,375 RWF or an extreme poverty line of 105,064 RWF in January 2014 prices. The essential idea was to determine how much it would cost to buy enough food to provide an adequate amount of calories, and then to add a provision for non-food essentials such as shelter and clothing for an adult.

A sub-sample of 1,920 households interviewed in EICV3 (2010-11) was selected to be revisited in EICV4 (2013-14) to allow for a more complete analysis of movements into and out of poverty overtime. The sample was designed to provide representative results at the national and urban/rural levels. The sampling frame for the panel was the list of 1,431 villages visited in EICV3. Households that relocated or split were tracked in order to obtain current information for the corresponding household members. A total of 2,423 households that were visited in 2010-11 were revisited in 2013-14 of which 1,898 were original households and 525 were households that split off from the original households. The same survey questionnaire was administered to both non-panel and panel households, so they were considered to be an integral part of both the EICV3 and EICV4 samples.

The EICV3 and EICV4 samples were each drawn from the 2002 and 2012 census frames respectively, and the sampling was stratified by district. Suitable weights were calculated within the panel samples, and as needed were used for adjustment to reflect the national population. The sample selection procedures were done efficiently taking into consideration the replacement of panel households. Since the EICV3 and EICV4 samples were drawn from different frames, the effect of using different sampling frames and strategies is unclear both for the panel and cross section analysis. One response was to investigate whether the panel is representative of the larger cross-section of households. This was done by testing the hypothesis of equality of sub-sample (i.e. panel) means to the means for the rest of the full sample, for key indicators. The three indicators selected were adult equivalents, household size, and consumption per adult equivalent. Households were divided into two mutually exclusive subsamples: selected panel households, and non-selected households.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey was comprised of the following questionnaires: 1. Agriculture questionnaire 2. Non-agricultural activities questionnaire 3. Credit, durables and savings questionnaire 4. Education questionnaire 5. Employment questionnaire 6. Household roster questionnaire 7. Health questionnaire 8. Housing and infrastructure questionnaire 9. Migration questionnaire 10. Transfers and income sources questionnaire 11. Household expenditures questionnaire

Abstract

The main objective of the Seasonal Agriculture Survey (SAS) 2015, was to provide timely, accurate, credible and comprehensive agricultural statistics that would not only describe the structure of agriculture in Rwanda in terms of land use, crop production and livestock and could be used for food and agriculture policy formulation and planning, but also which could also be used for the compilation of national accounts statistics.

In this regard, the National Institute of Statistics of Rwanda (NISR) conducted the Seasonal Agriculture Survey (SAS) from November 2015 to October 2016 to gather up-to-date information for monitoring progress on agriculture programs and policies in Rwanda, including the Second Economic Development (SED) and Poverty Reduction Strategy (EDPRS II) and Vision 2020. This 2016 RSAS covered three agricultural seasons (A, B and C) and provides data on background characteristics of the agricultural operators, farm characteristics (area, yield and production), agricultural practices, agricultural equipment's, use of crop production by agricultural operators and by large scale farmers.

Geographic coverage

National coverage

Analysis unit

This seasonal agriculture survey focused on the following units of analysis: - Agricultural operators and large scale farmers

Universe

The SAS 2016 targeted agricultural operators and large scale farmers operating in Rwanda.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Seasonal Agriculture Survey (SAS) sample was composed of two categories of respondents: agricultural operators1 and large-scale farmers (LSF).

For the 2016 SAS, NISR used as the sampling method a dual frame sampling design combining selected area frame sample3 segments and a list of large-scale farmers. NISR used also imagery from RNRA with a very high resolution of 25 centimeters to divide the total land of the country into twelve strata. A total number of 540 segments were spread throughout the country as coverage of the survey with 25,346 and 23,286 agricultural operators in Season A and Season B respectively. From these numbers of agricultural operators, sub-samples were selected during the second phases of Seasons A and B.

It is important to note that in each of agricultural season A and B, data collection was undertaken in two phases. Phase I was mainly used to collect data on demographic and social characteristics of interviewees, area under crops, crops planted, rainfall, livestock, etc. Phase II was mainly devoted to the collection of data on yield and production of crops.

Phase I serves at collecting data on area under different types of crops in the screening process, whereas the Phase II is mainly devoted to the collection of data on demographic, social characteristics of interviewees, together with yields of the different crops produced. Enumerated large-scale farmers (LSF) were 558 in both 2015 Season A and B. The LSF were engaged in either crop farming activities only, livestock farming activities only, or both crop and livestock farming activities. Agricultural operators are the small-scale farmers within the sample segments. Every selected segment was firstly screened using the appropriate materials such as the segment maps, GIS devices and the screening form. Using these devices, the enumerators accounted for every plot inside the sample segments. All Tracts6 were classified as either agricultural (cultivated land, pasture, and fallow land) or non-agricultural land (water, forests, roads, rocky and bare soils, and buildings). During Phase I, a complete enumeration of all farmers having agricultural land and operating within the 540 selected segments was undertaken and a total of 25,495 and 24,911 agricultural operators were enumerated respectively in Seasons A and B. Season C considered only 152 segments, involving 3,445 agricultural operators.

In phase II, 50% of the large-scale farmers were undertaking crop farming activities only and 50% of the large-scale farmers were undertaking both crop and livestock farming and were selected for interview. A sample of 199 and 194 large-scale farmers were interviewed in Seasons A and B, respectively, using a farm questionnaire. From the agricultural operators enumerated in the sample segments during Phase I, a sample of the agricultural operators was designed for Phase II as follows: 5,502 for Season A, 5,337 for Season B and 644 for Season C. The method of probability proportional to size (PPS) sampling at the national level was used. Furthermore, the total number of enumerated large-scale farmers was 774 in 2016 Season A and 622 in Season B.

The Season C considered 152 segments counting 8,987 agricultural operators from which 963 agricultural operators were selected for survey interviews.

Mode of data collection

Face-to-face [f2f]

Research instrument

There were two types of questionnaires used for this survey namely; Screening Questionnaire and Farm Questionnaires. A Screening Questionnaire was used to collect information that enabled identification of an agricultural operator or large scale farmer and his or her land use.

Farm questionnaires were of two types: a) Phase I: Farm Questionnaire, this survey was used to collect data on characteristics of agricultural operators, crop identification and area, inputs (seeds, fertilizers, labor) for agricultural operators and large scale farmers. b) Phase 2: Farm Questionnaire was used in the collection of data on crop production and use of production.

It is important to mention that all these farm questionnaires were subjected to two/three rounds of data quality checking. The first round was conducted by the enumerator and the second round was conducted by the team leader to check if questionnaires had been well completed by enumerators.

For season C, after screening, an interview was conducted for each selected tract/agricultural operator using one consolidated Farm Questionnaire. All the survey questionnaires used were published in both English and Kinyarwanda languages.

Cleaning operations

Data editing took place at different stage. Firstly, the filled questionnaires were repatriated at NISR for office editing and coding before data entry started. Data entry of the completed and checked questionnaires was undertaken at the NISR office by 20 staff trained in using the CSPro software. To ensure appropriate matching of data in the completed questionnaires and plot area measurements from the GIS unit, a "lookup" file was integrated in the CSPro data entry program to confirm the identification of each agricultural operator or LSF before starting data entry. Thereafter, data were entered in computers, edited and summarized in tables using SPSS and Excel.

Response rate

The response rate for Seasonal Agriculture Survey is 98%.

Data appraisal

All Farm questionnaires were subjected to two/three rounds of data quality checking. The first round was conducted by the enumerator and the second round was conducted by the team leader to check if questionnaires had been well completed by enumerators. And in most cases, questionnaires completed by one enumerator were peer-reviewed by another enumerator before being checked by the Team leader.

Abstract

Since the 1994 Genocide and the total collapse of Rwanda's economy and social services, the country has embarked on rebuilding itself and improving the quality of life of its population. Agricultural production has been continuously increasing and the country is reporting to have produced enough food to feed its entire people since 2008. Health indicators have improved, as has school enrolment, parity between girls and boys in school and access to clean water.

Against this context of socio-economic progress mitigated by population growth, widespread poverty and high levels of chronic malnutrition and food insecurity, it was decided to undertake the third national Comprehensive Food Security and Vulnerability Analysis and Nutrition Survey (CFSVA and Nutrition Survey 2012) in Rwanda. Like previous CFSVAs, the overall objective is to analyze trends of food insecurity, malnutrition and vulnerability over time, measuring the extent and depth of food insecurity and identifying the underlying causes. In addition, building on the recently released EICV 3 and 2010 DHS surveys, this study looks into social protection issues, food insecurity and malnutrition in Rwanda to formulate recommendations so that interventions to tackle poverty, food insecurity and malnutrition can be adequately targeted and designed (including district plans to eliminate malnutrition) and to help monitor progress in the implementation of the Joint Action Plan to fight malnutrition in Rwanda.

Geographic coverage

National coverage

Analysis unit

• Household
• Community
• Anthropometric

Universe

Survey was administered to sample household heads, which also included an anthropometric section for women of reproductive age (15-49), children under five years, and a section on infant and young child feeding practices intended only for children between six months and two years.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame was based on the data from the recent EICV 3 (2010/2011) and was organized according to 30 districts. A two-stage cluster sample procedure was applied. In the first stage, 25 villages per district were randomly selected with probability proportional to population size. In the second stage, 10 households in each of the 25 villages in the 30 districts were selected for participation in the survey. A systematic random sampling technique was chosen for this stage. In total 748 key informant interviews were conducted, 7498 households were administered the household questionnaire, and valid anthropometric measurements were taken for 7418 women and 4651 children. The Infant and Young Child Feeding (IYCF) module was submitted to mothers or caretakers of all children between six and 24 months (1613 children in total).

Mode of data collection

Face-to-face [f2f]

Research instrument

Two instruments were used to collect primary data: a key informant questionnaire and a household questionnaire including an anthropometric section for women of reproductive age, and a section on infant and young child feeding practices intended only for children between six months and two years.

• HOUSEHOLD: Demographics, Housing and Facilities, Livelihoods, Household Assets and Productive Assets, Agricultural Production, Migration & Remittances, Sources of Credit, Expenditures, Food Sources and Consumption, Coping Strategies, Shocks and Food Security External Assistance/Programme participation.

• WOMEN and CHILD: Maternal Health and nutrition, Child Health, Nutrition and feeding practices.

• VILLAGE: Group composition, Demographic and Community Information, Community Infrastructure, Markets (prices of food, animals, daily labour wages), Crop calendar, Assistance projects, Shocks.

The instruments were first developed in English and subsequently translated into Kinyarwanda.

Response rate

99.99%

Abstract

The Household Living Conditions Survey, also known as Enquête Intégrale sur les Conditions de Vie des Ménages (EICV) in French, was conducted by the Statistics Department of the Ministry of Finance and Economic Planning. The survey was primarily intended to provide policy planners and decision-makers with basic data on household living standards in Rwanda.

In addition, the survey was to be used to: - calculate weights for the Consumer Price Index and estimate final household consumption, - measure the effect of macro-economic policies and projects on the conditions and living standards of the population, - produce key indicators of household welfare in order to assist policy-makers and development partners to improve the design of their development strategy, - identify policy target groups with a view to ensuring that state interventions are better targeted. - provide information on the socio-economic characteristics of households with a view to setting up a socio-economic data base. - carry out in-depth studies, for example on poverty, nutrition, housing conditions, etc, - improve the national capability to conduct statistical surveys, however complex they may be.

Geographic coverage

National coverage with all 11 former provinces (now 5 major provinces) and the City of Kigali.

Analysis unit

-Household -Individual -Commodity (for GDP computation)

Universe

Household members (institutional and itinerant populations excluded)

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling plan was drawn up with the technical support of the late Christopher Scott, Survey Consultant, during his mission in July 1997.

Constraints

The two main factors considered in designing the sampling plan were: - the objectives of the survey, - the fieldwork methodology given the available logistical resources. For the survey one objective was determinant: the Government wanted statistically reliable results at the level of each province, Kigali city and the "other urban sector". Thus, the objective called for 13 domain of analysis. Experience of conducting this type of survey shows that a minimum sample of 500 households per domain of study is required for sound analyses.

Sample size

The sample size was therefore 6,450 households, with 1,170 households for urban areas and 5,280 households for rural areas. Two stage sampling A two stage stratified sample was used: sampling at area level and at household level.

Sampling base

*At the area level, the chosen sampling base ( or at the enumeration district) was the "cellule"in the rural areas and the zone in urban areas, since they are usually fairly homogeneous in size and are well demarcated.

Knowledge of the size of each cellule enabled the use of the classical method of sampling with probability proportional to size at the first stage. A list of all cellules including estimates of the number of households in each was compiled from information provided by the local authorities.

*For sampling at the household level, an up-dated list of households was prepared for each of the selected first stage cellule by carrying out a listing in each sampled cellule simultaneously but with a lag in data collection before or while collecting the data. Part of this operation was carried out in collaboration with the National Population Office (ONAPO) and the Food Security Research Project (FSRP) of MINAGRI.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires are published in French.

Three types of questionnaire were used in the field for data collection: - the household questionnaire comprising of 12 modules divided in two parts, A and B. - the community questionnaire for collecting data on economic and social infrastructures in the sample units in rural areas and - a conversion form for non-standard units used by households.

Household questionnaires

Part A collects data on each member of the household. It covered the following areas: - demographic and migration characteristics, - education and health, - employment and housing.

Part B deals with the economic activity of the household. It comprises of the following five modules: - agro-pastoral activities and own-produce consumption, - household expenditure, - non-agricultural economic activities, - transfers, - durable goods, access to credit and savings.

Cleaning operations

Data Editing (see external resource entilted: Final Data Processing Report)

Questionnaires were reviewd by the controller in the field before they were dispatched for data entry. A control sheet was provided to the contollers to assist in the process of manually editing the questionnaires. Questionnaire structures were verified when the questionnaires were checked in prior to data entry. Three contracted persons reviewed the questionnaire and filled in a form that served as a primary data control sheet. Automated data editing was largely done during the data entry phase (see "Other Data Processing" for details). Some batch edit programs were used to identify inconsistent data.

Data Imputation

Data iimputation was largely done during the analysis phase by analysts. However, a "structural" imputation on the microdata was required for the own consumption data. This was done to adjust for erroneous pricing when the unit for measuring own consumption was buckets. For more information, please refer to the SPSS su=yntax files orthe data processing report.

Primary Data Issues

Coding of products was based on sequential codes for each section.

Response rate

In the course of the survey, some households did not respond, for one reason or the other. Of 6,450 households 6,431 responded, giving a response rate of 99.7%. In the course of processing the data, an additional 11 questionnaires were rejected because they did not contain useable information, in particular in respect to expenditure and consumption. Hence, the analysis was based on 6,420 households, giving a coverage rate of 99.5% of the sample households.

Sampling error estimates

Given that the survey estimates are subject to sampling variability, it is important to calculate the sampling errors for the most important estimates from each survey. The sampling error is measured by the standard error, or square root of the variance of the estimate. The CENVAR software, a component of the Integrated Microcomputer Processing System (IMPS) developed by the U.S. Census Bureau, was used for tabulating the standard errors and other measures of precision, taking into account the stratification and clustering in the sample design. The CENVAR output tables show the value of the estimates, standard errors, coefficients of variation, 95 percent confidence intervals, design effects and number of observations. Given that the confidence intervals provide a user-friendly interpretation of the sampling variability, an annex was produced with tables showing the 95 percent confidence intervals for the most important estimates from the EICV1 and EICV2 data appearing in the preliminary report. These tables provide a quick conservative test to determine whether any difference between the EICV1 and EICV2 estimates is statistically significant.

The INSR was also provided with tables showing the full CENVAR results. The design effect is defined as the variance of an estimate based on the actual sample design divided by the corresponding variance based on a simple random sample of the same size; it is a measure of the relative efficiency of the sample design. In comparing the CENVAR results from EICV1 and EICV2, it was found that the design effects are generally lower for EICV2, indicating that the stratification used for this survey was very effective. Given that the EICV1 was based on an older sampling frame from the 1991 Rwanda Census, this also contributed to the higher design effects for the EICV1 estimates.

Abstract

The establishment census 2017 consisted of a complete counting of all establishments practicing a specific economic activity in Rwanda except not-for-sale governmental services.

The main objectives of this census are: · To provide detailed information on the establishments' characteristics and their spatial distribution; · To provide detailed information about the economic activity of all establishments operating in Rwanda; · To update data of the enterprise database, the general sample frame of economic, administrative and public-service establishments for use in sample surveys.

The 2017 Establishment Census is designed to achieve the following specific objectives:

· To produce a comprehensive and updated data profile of all economic activities by establishments operating in Rwanda; · To provide detailed tabulations about the establishments' characteristics, e.g, geographical location, number of employees, registration status, legal status, ownership, sector of activity, manager or owner sex; · To produce data necessary to classify establishments according to their size (micro, small, medium, and large); · To lay out the data foundation needed to identify formal and informal economic sectors in Rwanda.

Geographic coverage

National coverage.

Analysis unit

The unit of analysis of this study is establishment excluding governmental establishments which provide not-for-sale services. However, for employment component, all institutions were covered including 'not-for-sale services' goverment institutions. It is important to note that this census excludes diplomatic misisons operating in Rwanda.

Universe

The study covered all establishments except governmental establishments that provide not-for-sale services. However, for employment component, all institutions were covered including 'not-for-sale services' goverment institutions. It is important to note that this census excludes diplomatic misisons operating in Rwanda.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was developed in English and translated into Kinyarwanda. Appropriate tests were performed which provided feedback to improve the questionnaire.

Cleaning operations

Since electronic devices were used for the data collection, data were directly sent to the NISR’s server. A drop box was created to receive daily data from the field and concatenate data into SPSS and STATA files. A daily progress report was sent back to team leaders and supervisors to ensure that progress is going well as planned and take appropriate measures if necessary. Data quality was assessed at daily basis and feedback sent back to the field so that they take appropriate measures wherever is necessary.

In fact, data editing has been performed continuously throughout data collection for the purpose of detecting out-of-range and/or inconsistent data values. Appropriate actions have been taken to cope with any doubtful data and to introduce necessary corrections.

Upon producing the clean data file, statistical tabulations have been generated.