Jeu de données: Migrations between Africa and Europe - MAFE Ghana (2009-2010)

Résumé

Le projet de recherche MAFE est une initiative de grande ampleur dont l'objectif est d'étudier les migrations entre l'Afrique subsaharienne et l'Europe. - Attention, la documentation des enquêtes MAFE est en langue anglaise. -

__________


The MAFE project is a major research initiative focused on migration between Sub-Saharan Africa and Europe. It brings together ten European and African research centres working on international migration.

In the early XXIth Century, international migration from Sub-Saharan Africa to Europe has generated increasing public and policy attention. The flotilla of boats bringing would-be migrants to the Canary Islands, and attempts to reach Spanish territory in Ceuta and Mellila have drawn a rapid response from Europe in the form of new policy measures. Yet the scope, nature and likely development of Sub-Saharan African migration to Europe remained poorly understood, and, as a result, European polices may be ineffective. A major cause of this lack of understanding was the absence of comprehensive data on the causes of migration and circulation between Africa and Europe.

The MAFE project aimed at overcoming this lack of understanding by collecting unique data on the characteristics and behavior of migrants from Sub-Saharan countries to Europe. The key notion underpinning the project was that migration must not only be seen as a one-way flow from Africa to Europe. The argument was that return migration, circulation and transnational practices are significant and must be understood in order to design better migration policy.

The MAFE project focused on migration flows between Europe (Belgium, France, Italy, the Netherlands, Spain and the UK) and Senegal, the Democratic Republic of Congo and Ghana, which together accounted for over a quarter of all African migration to the EU at the time of the survey. In each of these "migration systems", the survey was designed to document four key areas:
    - Patterns of migration :
              *the socio-demographic characteristics of migrants,
              *the routes of migration from Africa to Europe, and
              *the patterns of return migration and circulation.
    - Determinants of migration: looking at departure, but also return and circulation and taking into account the whole set of possible destinations.
    - Migration and Development: MAFE documents some of the socio-economic changes driven by international migration, looking as often as possible at both ends of the Afro-European migration system, at the individual level.
    - Migrations and Families: the data collected by the MAFE project can be used to study all sorts of interactions between family formation and international migration. Although the survey was primarily designed to study international migration, it can also be used to study other phenomena, especially in Africa: domestic mobility, labor market participation, family formation, etc.
Comparable data was collected in both 3 sending and 6 destination countries, i.e. in sub-Saharan Africa and in Europe. The data are longitudinal - including retrospective migration, education, work and family histories for individuals - and multi-level - (with data collected at the individual and household levels, in addition of macro-contextual data).
     
Please consult the official MAFE website for further details : https://mafeproject.site.ined.fr/en/

Titre

Migrations between Africa and Europe - MAFE Ghana (2009-2010)

Titre alternatif

MAFE Ghana

Titre parallèle

Migrations entre l'Afrique et l'Europe - MAFE Ghana (2009-2010)

Numéro d'identification

IE0216C

Auteur

Nom Affiliation
BEAUCHEMIN Cris INED

Autres contributeurs et remerciements

Nom Affiliation Rôle
ADDOQUAYE TAGOE Cynthia CMS
AMETEPE Fofo INED
AWUMBILA Mariama CMS
BINAISA Nalu U. Sussex
BLACK Richard U. Sussex Project coordinator
BRINGE Arnaud INED
CAARLS Kim U. Maastricht
CASTALDO Adriana U. Sussex
DAURELE Catherine INED Coordination assistant
FREMPONG Faustina CMS
GARBIN David U. Sussex
GENT Saskia U. Sussex
KABBANJI Lama INED
LAURENT Raphaël INED
LEJBOWICZ Tania INED
LESSAULT David INED
MANUH Takyiwaa CMS
MAZZUCATO Valentina U. Maastricht Project coordinator
MEZGER Cora INED
NAPPA Jocelyn INED
QUAGLIA Martine INED
QUARTEY Peter CMS Project coordinator
RAZAFINDRATSIMA Nicolas INED
SCHANS Djamila U. Maastricht
SWARD Jon U. Sussex
THEVENIN Marc INED
TOMA Sorana INED
VICKSTROM Erik INED
VIVIER Géraldine INED

Producteur

Nom Affiliation Abréviation: Rôle
Institut National d'Etudes Démographiques France INED
University of Ghana Ghana UG
Maastricht University Netherlands U. Maastricht
University of Sussex United Kingdom U. Sussex

Date de production

2010

Commanditaire

Nom Abréviation: Rôle Soumission
European Community's Seventh Framework Programme 217206

Diffuseur des données

Nom Affiliation Abréviation:
Institut National d'Etudes Démographiques INED

Notes

The MAFE project involved 10 organisations representing a wide range of disciplines and institutions. Through the researchers involved, it combined the approaches of demographers, geographers, economists and of socio-anthropologists.
The partners brought a combination of quantitative and qualitative skills. Each of the work packages brought together researchers with strong quantitative background and know-how in processing statistical analysis and large-scale data-sets, and researchers with a strong qualitative knowledge on migration patterns and African contexts.

Both for project organisation and the relevance of project results, it was essential to involve European and African partners on the same footing. In addition to the North/South balance, attention has been paid to the balance within the receiving countries, between Western European countries and Southern European countries, new and older receiving countries.

Liste des mots-clés

Classification des sujets

4. Migrations internationales, discrimination, intégration

Dates de collecte

Début Fin Cycle
2009-05 2009-05 Ghana pilot survey
2009-07 2010-01 Ghana (Accra & Kumasi) survey
2009-06 2009-11 United Kingdom survey
2009-04 2009-07 Netherlands survey - 1st phase
2009-11 2010-04 Netherlands survey - 2nd phase

Pays

Couverture géographique

Six European countries and three African countries participated in the MAFE surveys. Data collection was carried out in both sending countries in Africa and destination countries in Europe, in order to constitute transnational samples.
For MAFE Ghana, data was collected in Ghana (African part), and the Netherlands and United Kingdom (European part).

Unité d'analyse

Household
Individual

Univers

GHANA
Household: Households selected randomly from the updated list of households in the selected primary sampling units. Three strata were distinguished: households with return migrants, with migrants abroad, and without migrants.
Individual: People aged 25-75, born in Ghana. This lower age limit was set in order to obtain informative life histories. By not including respondents younger than 25, the resources were used more effectively. The place of birth criterion was used to exclude people who were born out of their country of origin in order to exclude second generation migrants in Europe and to increase the homogeneity of sample.
All the return migrants and partners of migrants, and one randomly selected other eligible person. Return migrants were eligible if their first departure was above at 18 or over.

EUROPE
In all the European countries, the surveys were conducted among males and females who were aged 25 and over at the time of the surveys, and who were 18 or over when they had left Africa for the first time for at least one year. Migrants from only Ghana were interviewed.

Entité responsable de la collecte des données

Fréquence de collecte des données

GHANA
In Ghana, the preparation of data collection started in February 2009, and a pilot survey was organized in May 2009. The selection of survey sites and the listing of households in the sites were carried out in May 2009. Fieldwork started in July 2009 and lasted approximately 6 months (from July 2009 to January 2010). Several interviewers dropped out during data collection and could not be replaced, which contributed to lengthening the fieldwork. Editing and data coding were done in parallel with data collection, and were over by the end of January 2010. Data entry and data cleaning started in February 2010, and ended in March 2010.

EUROPE
In the Netherlands and United Kingdom, data collection was conducted in 2009-2010. Data collection lasted about five months in the UK and three months in the Netherlands. Editing was done along data collection. Data entry was done between October and December 2009 in the UK, and between June 2009 and September 2009 in the Netherlands. The Netherlands started a second phase of data collection in November 2009 (they had some funds left which allowed them to increase the sample size).

Procédure d'échantillonnage

GHANA

A three-stage stratified random sample was used. At the first stage, primary sampling units (census district) were selected randomly with varying probabilities. At the second stage, households were selected randomly in each of the selected primary sampling units (PSUs). At the third stage, individuals were selected within the households.

a) Selection of primary sampling units (first stage)
For Ghana, the target areas were the cities of Accra and Kumasi. In each of the cities, a sampling frame of primary sampling units was prepared. In Senegal and Ghana, recent censuses were available and served as sampling frames at the first stage.
At the first stage, census enumeration areas were randomly selected. In Ghana, 80 enumeration areas were selected with a probability proportional to size. As no information was available for stratifying, the sample was not stratified in the first stage in Ghana.

b) Selection of households (second stage)
A listing operation was carried out in each of the selected survey sites to prepare the sampling frame of households. The listing consisted in enumerating all the households in the selected sites, and in identifying whether these households included migrants of not. In DR Congo and Ghana, three categories of households were distinguished (households with return migrants, with migrants abroad, and without migrants). 8 households were selected in each of the 3 strata (if less than 8 households were available in one or several strata, the remaining households were selected in the other stratum). The sampling rate was higher in strata of households with migrants, in order to get a sufficient sample of such households.

c) Selection of individuals (third stage)
In each of the selected households, one or several respondents were selected among the eligible people (people aged between 25 and 75, and born in the origin country). In DR Congo and Ghana, all the return migrants and partners of migrants currently abroad were selected. In addition, one other eligible member was randomly selected. A special tool had been designed so that the interviewers could randomly select the people during the fieldwork.  

Two types of questionnaires were used in the departure countries: the household questionnaire and the individual life history questionnaire.
- The first questionnaire was used among a representative sample of households in the target region.
- The second questionnaire was used among a sample of individuals in the selected households, targeting both return migrants and non-migrants. The household questionnaire was thus used as the sampling frame for the selection of individual respondents.



EUROPE

The objective of the survey was to obtain a sample 'as representative as possible' of the African populations (Congolese, Ghanaian, Senegalese) in the destination countries (150 individuals per origin and destination country). The way the sample was constituted may vary across countries, but some common principles were respected:
- The composition of the sample should be as close as possible to the population of (Congolese, Ghanaian, Senegalese) migrants in the country in terms of gender, geographic distribution, age, socio-economic category or occupation.
- One exception: the sample should be gender balanced. Males and females should be equally represented in order to allow gender analyses.
- Samples in origin and destination may be linked, but migrants with weak or no relationships at origin should not be excluded from the sample.
- Both documented and undocumented migrants should be represented in the sample.

As no suitable frame was available to select randomly individual respondents in five of the six European countries (Spain being the exception), it was decided to use quota sampling. In all the countries, the quotas were set by age and gender at least. In the UK, the place of residence was also used in the quotas.

In the Netherlands, sub-regions concentrating the majority of migrants were selected. In the United Kingdom, the surveys were concentrated in the London area and in the places where Ghanaian migrants were living.

Randomness was also included in the samples in different ways. For instance, in Belgium, a random sample of places was selected according to the number of people of Congolese origin living in these places. Respondents were selected in these places. The combination of different recruitment methods also ensured that different types of persons had a non zero probability of being included in the sample. For instance, some respondents were recruited in public spaces (street, metro station, hairdresser...), others were randomly selected from list of volunteers identified in churches...

*The Netherlands*
- Target areas: 3 cities (in 3 different provinces): Amsterdam, The Hague and Almere
- Sample size: 272
- Quotas: By age, gender
- Recruitment methods: Public spaces, churches, snowballing, interviewers' contacts

*United Kingdom*
- Target areas: Whole country
- Sample size: 149
- Quotas: By age, gender and place of residence
- Recruitment methods: Public spaces, churches, snowballing, interviewers' contacts

Mode de collecte des données

The general strategy was the following one:  
1. A household survey was conducted among a sample of households in the capital cities in Africa (household questionnaire in origin countries);
2. A life history survey among a sample of individual respondents was conducted in the departure countries (non migrants, return migrants and spouses of migrants). The individual respondents were selected from the households in the origin countries (individual questionnaire in origin countries);
3. A life history survey was carried out among migrants in destination countries (individual questionnaire in destination countries).
All the surveys were done using paper questionnaires through face-to-face interviews.

GHANA
In Ghana, both household and individual surveys were carried out at the same time. It necessitated drawing individuals within the households through the Kish selection method.
The average duration of interviews for the household questionnaire was about 45 minutes-1 hour in Senegal, and a little shorter in DR Congo and Ghana. The average duration of the biographic questionnaire was also around 45 minutes, but it varied greatly depending on the age and migration status of the respondents.

EUROPE
In Europe, the moment for data collection depended on the selection method. In MAFE Senegal, the fieldwork could start only after completion of the household survey. As a consequence, the fieldwork for the biographic questionnaires was done almost at the same time in all countries.
The work of the interviewers included three stages:
o The interviewers first had to set up an appointment with respondents by using the phone contacts or another source of recruitment (except in cases persons were directly available). Interviewers needed to confirm the appointment. The choice of the place and time of the interview were left to the respondents.
o The interview was then done. The average duration of interviews was between 1 and 1.5 hours. In most cases, interviews were carried out at the house of the respondents, but it also took places in various places (pubs, street, office…). The interviews were done during weekdays or week-ends, at various times.
o Finally interviewers were asked to read quickly the completed questionnaire as soon as possible after the interview, in order to detect any missing parts or inconsistencies, and correct them on the spot. Approximately one additional hour was necessary for this. In Belgium, the Netherlands and the UK, interviewers also had to transcribe the information from the ageven grid to the questionnaire directly after the interview (this was done by the editors in the other countries).

In all the countries, the respondents were offered a small gift at the end of the interview. In most countries, this was a calling card. In the UK, money was given to the respondents and in Belgium, respondents were given the choice between a calling card and a voucher in a supermarket. The value of the gift varied between 5 € (Italy) and £15 (UK). In all the countries, the gift was very much appreciated. Although the gift was offered after the interview, some participants knew in advance they would receive it. For instance, a few surveys were conducted in a center for asylum seekers in Belgium, and the information about the gift quickly spread among the Congolese migrants. Recruitment by snowballing also meant that respondents were sometimes aware they would receive a gift. Although this may have facilitated the recruitments of some persons, it may have affected negatively the composition of the sample.

Type d'instrument de collecte

The MAFE surveys rely on two different questionnaires: household and biographic. The questionnaires are almost entirely identical from one country to another. The few differences consist in:
- Cultural variables (religion, ethnic groups, matrimonial status etc.)
- New questions introduced on fostered children in the MAFE DR Congo and MAFE Ghana biographic questionnaires (Module on Children)
- The order of the questions relating to migration in the household questionnaire (Module A)

The Household Questionnaire:
- Used only in African countries
- Answered by a unique respondent who is usually the household head
- Contains information on the members of the household (age, sex, education...) and also on people who live outside the household and who are related to it (head's children, partners living abroad, other relatives of the head or his/her spouse who live abroad and with whom the household has been in touch within the last 12 months). In addition, it contains specific modules on short migration histories, on relationships between each migrant and the household, and on housing conditions and owned assets.  
- Topics: socio-demographic variables of each individual, short migration histories, remittances, household assets, housing history
- Available in French (MAFE-Senegal, MAFE-DR Congo) and English (MAFE-Ghana)

The Biographic Questionnaire:
- Used in all African and European countries
- Answered by the migrant him/herself
- Contains life histories of all the surveyed individuals, whatever their migratory status at the time of the survey (non-migrant, return migrant, current migrant). The questionnaire contains retrospective information on the following topics: dwelling, family, work, international migration of the interviewee (including attempts to migrate, return trips to the country of origin, transit migration and legal status in foreign countries), migration history of the migrant's relatives (list of their stays abroad, including dates and country names), goods and assets, and remittances and contributions to associations in the country of origin.  
- A grid was used, jointly to the questionnaire, to help the interviewee to recall important dates of his/her history
- Topics: family formation, education and employment, housing, migration, investments (housing, business, community amenities or infrastructure)...
- Available in French (MAFE-Senegal, MAFE-DR Congo), English (MAFE-Ghana), Italian and Spanish (MAFE-Senegal)

Caractéristiques de la collecte de données

The MAFE surveys collect information on potentially vulnerable populations (undocumented migrants) and on sensitive subjects (remittances, legal status…). In order to facilitate the fieldwork and increase the quality of the data, it was important to carefully inform the people who were to be interviewed.  

The legal pre-requisites changed according to the country. In France (only), a legal authorization had to be obtained before starting the fieldwork. The CNIL (Commission nationale informatique et libertés) was concerned by the way the contacts were going to be obtained in Senegal and, most of all, by the sensitivity of certain variables contained in the questionnaires (ethnic group, religion). We obtained the authorization to ask these questions, but in order to keep them in our files, we had to ask to the interviewees to sign a written informed consent.
According to legal prescriptions, in all European countries, a letter was designed to explain their rights to the interviewees.

In most countries, a leaflet was designed and used to sensitize respondents and authorities about the MAFE project.

In advance of the survey, several communication actions have been undertaken:
- In Africa, inform neighbourhood heads / municipalities of survey by an official letter or by a visit
- Use local radio / migrants radio and chat show to present the survey
- Inform an organisation of migrants who can support the survey
- Visit the key places of the community (churches…)

Because of the complexity of the questionnaires, only interviewers with a good experience in complex surveys were recruited.  
In African countries, it was highly recommended to hire the same interviewers to conduct both household surveys and individual surveys. This approach proved to be very efficient in all the surveys.
In Europe, interviewers had to be able both to recruit the migrants and to fill correctly the questionnaire. As a general rule, it was preferable to have a relatively small number of well-trained interviewers than a large number of interviewers.
Overall, around 20 to 25 interviewers and supervisors were involved in data collection in each country.

The number of the interviewers per survey varied between 8 (survey among Ghanaians in the UK) and 17 (Netherlands). In all the countries, both male and females interviewers were hired; most of them had higher education and some experience with data collection. In some countries (e.g. France), some of them were professional interviewers. The selected interviewers were not necessarily from the same country as the respondents, but most of them also had foreign origins.
For instance, 7 of the 12 interviewers in Belgium were of foreign origin, 5 of them from DR Congo. In the Netherlands, most interviewers were from Ghanaian origin. The fact that many of the interviewers were themselves of foreign origin seemed to have positively influenced the willingness of interviewees to participate in the survey.

Directly after being filled, questionnaires were checked by the interviewers and supervisors. They were then sent to a small team of editors for an in-depth reading. The editors consisted of 9 people in Senegal, 6 in Ghana and 5 in DR Congo. The team had followed the same training as the interviewers, and also received a specific training for editing the questionnaires.
Data entry was performed using MS Access programs prepared by INED.

Pondération

GHANA
The computation of sampling weights relies on computing sampling probabilities at each stage. The product of sampling probabilities at each stage gives the overall sampling probability. Taking the inverse of the sampling probability gives the inflation factor. These factors are adjusted (trimming, adjusting for population size). They are normalized, so that their sum is equal to the sample size.

EUROPE
In the European countries, similar sample sizes were selected for males and females, resulting in an overrepresentation or underrepresentation in the MAFE samples. Similarly, older people were usually oversampled. For these reasons, post-stratification weights are computed to give each observation its proper weight and to match the samples as closely as possible to selected population characteristics.

In the MAFE data, all survey weights have been rescaled (normalized) so that the sum of weights corresponds to the sample sizes of households and individuals respectively while the mean of the weight variables equals one.
For further details about weights, please read the MAFE methodological note 6 entitled "Sampling and Computation Weights in the MAFE Surveys" (see related materials).

Taux de réponse

GHANA

For the household questionnaire, 1920 households were selected (1440 in Accra and 480 in Kumasi), only 1246 were successfully interviewed, including:
- Non-migrant household: 449
- Household with at least 1 returnee: 346
- Household with at least 1 current migrant: 675
- Household with returnee(s) and current migrant(s): 224
This represents a response rate of 64.9%.

For the biographic questionnaire, 1 490 individuals were selected, only 1 243 were interviewed, including:
- Returnees: 319
- Partners left behind: 84
- Other non-migrants: 840
This represents a response rate of 83.4%.

The overall response rate in Ghana is 54.1%.

EUROPE
417 Ghanaians migrants were successfully interviewed: 279 in the Netherlands and 138 in the United Kingdom.

Autres formes d'évaluation des données

A methodological note entitled "Sampling international migrants with origin-based snowballing method: New evidence on biases and limitations", written by Cris Beauchemin and Amparo González-Ferrer, can be found in the study's related materials, as well as another methodological note in french "Biais de non-réponse dans l'enquête Migrations entre l'Afrique et l'Europe (MAFE-Sénégal)" written by Nicolas Razafindratsima, Stéphane Legleye and Cris Beauchemin.

Intégralité de la collection entreposée

GHANA
In the three African countries, data entry started only after the end of data collection.
In Ghana, data entry staff was trained at the same time as interviewers, and received an additional training for data entry (3 days). Data entry was done in an office in the University of Accra, and supervised by a computer scientist recruited by the local coordinating team. His role was similar as in Senegal. Contrary to what was done in Senegal, consistency tests were not run every day. They were run at the end of data entry, using the program prepared by INED. On average, around 8 questionnaires were entered per day per interviewer.

EUROPE
Data entry was done after the questionnaires had been corrected and coded.
In MAFE Senegal countries (France, Italy, Spain) a first version of the program developed at INED in 2008 was used. While several problems were encountered at the beginning of data entry, they were quickly fixed. Most of the problems with the program were experienced by the French team, but Spain and Italy did not have major troubles. Another version of the program was developed for the second series of country.
In spite of the problems encountered during data collection, the data entry programs were overall very good and allowed the research teams to produce data files that are directly comparable.
In all the countries, consistency tests were performed at the end of data entry, using the program prepared by INED. These programs allowed detecting inconsistencies due to errors during data entry, or that had gone unnoticed during the editing phase. These inconsistencies were corrected in the data base, and programs run again until no inconsistencies were left. Some difficulties were encountered with early versions of the program (some 'false errors' were identified), but most were quickly fixed by INED.

Texte à citer

Every user of the MAFE data must cite this paragraph in its publications:
English version : "The MAFE project is coordinated by INED (C. Beauchemin) and is formed, additionally by the Université catholique de Louvain (B. Schoumaker), Maastricht University (V. Mazzucato), the Université Cheikh Anta Diop (P. Sakho), the Université de Kinshasa (J. Mangalu), the University of Ghana (P. Quartey), the Universitat Pompeu Fabra (P. Baizan), the Consejo Superior de Investigaciones Científicas (A. González-Ferrer), the Forum Internazionale ed Europeo di Ricerche sull'Immigrazione (E. Castagnone), and the University of Sussex (R. Black). The MAFE project received funding from the European Community's Seventh Framework Programme under grant agreement 217206. The MAFE-Senegal survey was conducted with the financial support of INED, the Agence Nationale de la Recherche (France), the Région Ile de France and the FSP programme 'International Migrations, territorial reorganizations and development of the countries of the South'. For more details, see: http://www.mafeproject.com/"
French version : "Le projet MAFE est coordonné par l'INED (C. Beauchemin), en partenariat avec l'Université catholique de Louvain (B. Schoumaker), la Maastricht University (V. Mazzucato), l'Université Cheikh Anta Diop (P. Sakho), l'Université de Kinshasa (J. Mangalu), l'University of Ghana (P. Quartey), l'Universitat Pompeu Fabra (P. Baizan), le Consejo Superior de Investigaciones Científicas (A. González -Ferrer), le Forum Internazionale ed Europeo di Ricerche sull'Immigrazione (E. Castagnone), et l'University of Sussex (R. Black). Le projet MAFE a reçu un financement du Septième Programme-Cadre de la Communauté européenne (subvention 217206). L'enquête MAFE-Sénégal a été réalisée grâce au soutien financier de l'INED, de l'Agence Nationale de la Recherche, de la région Ile de France, et du programme FSP 'Migrations internationales, recompositions territoriales et développement dans les pays du Sud'. Pour plus d'information, voir : http://www.mafeproject.com/"

In addition, to refer to the survey design, the following documents can also be refered to:
Beauchemin, C. (2012). Migrations between Africa and Europe: Rationale for a Survey Design. MAFE Methodological Note 5. Paris, Ined: 45.
Schoumaker, B., C. Mezger, N. Razafindratsima and A. Bringé (2013). Sampling and Computation Weights in the MAFE Surveys. MAFE Methodological Note 6: 73.

These MAFE methodological notes are available at: http://mafeproject.site.ined.fr/en/methodo/methodological_notes/

Matériel relié

Website

Official website of the MAFE project

Leaflet

Presents the main objectives of the survey, and aims at informing the respondents on the use of the data. In addition to information on the objectives of the survey, the leaflet also includes contacts of the persons in charge of the MAFE project in the country.

Household questionnaire Ghana (EN)

Biographic questionnaire Ghana (EN)

Biographic questionnaire Netherlands (EN)

Events grid Netherlands (EN)

Biographic questionnaire United Kingdom (EN)

Events grid United Kingdom (EN)

Interviewer's handbook - Household questionnaire (EN)

Interviewer's handbook - Biographic questionnaire - part 1 (EN)

Interviewer's handbook - Biographic questionnaire - part 2 (EN)

Interviewer's handbook - Biographic questionnaire - part 3 (EN)

Interviewer's handbook - Biographic questionnaire - part 4 (EN)

Methodological note 1

Beauchemin, C., Kabbanji, L., Lessault, D., & Schoumaker, B., 'Migrations between Africa and Europe: Survey Guidelines', April 2010 (EN)

The objective of this document is to present the MAFE survey methodology. It includes a presentation of all the tools used in the 9 countries. This document is complemented by a data collection report. It was primarily written on the basis of the MAFE-Senegal experience in order to ease its replication on Congolese and Ghanaian populations.

Methodological note 2

Schoumaker, B, & Diagne, A., 'Migrations between Africa and Europe: Data Collection Report', May 2010 (EN)

This report is a synthesis of the country reports in Africa and Europe, and was prepared by the UCL team, in charge of the coordination of data collection in the countries participating in the MAFE project. The first part of the report is on data collection in Africa, and the second part on Europe.

Methodological note 3

Beauchemin, C. & González-Ferrer, A. 'Sampling international migrants with origin-based snowballing method: New evidence on biases and limitations', Demographic Research, 25 (3), 103-134, July 2011 (EN)

This paper provides a methodological assessment of the advantages and drawbacks of the origin-based snowballing technique as a reliable method to construct representative samples of international migrants in destination areas.

Methodological note 4

Razafindratsima, N., Legleye, S., Beauchemin, C., 'Biais de non-réponse dans l'enquête Migrations entre l'Afrique et l'Europe (MAFE-Sénégal)', (FR)

L'objectif de cette note est d'évaluer les biais engendrés par la non-réponse totale de niveau ménage et de niveau individuel dans le volet sénégalais de l'enquête MAFE.

Methodological note 5

Beauchemin, C., 'Migrations between Africa and Europe: Rationale for a Survey Design', January 2012 (EN)

The paper first presents the scientific objectives of the MAFE project, briefly pointing up the limitations of the existing literature in four domains: patterns of migration, determinants of departure and return, migration and family changes, migrants' economic integration and re-integration. The paper then presents the methodological principles of the MAFE survey design and the choices made to produce a new dataset containing information on the four aforementioned topics.
Beyond the MAFE project, the paper highlights the classical problems in survey methodology facing all data producers in the domain of international migration, and advocates a more (self-)critical approach in this field of literature.

Methodological note 6

Schoumaker, B. & Mezger, C., 'Sampling and computation weights in the MAFE Surveys', January 2013 (EN)

This note describes the sampling strategy and the computation of weights in the MAFE surveys. The first part explains designs in Ghana, DR Congo and Senegal, the second part describes the computation of weights in the European samples, followed by the description of the computation of normalized weights to be used with pooled data sets in the third part. The fourth part provides a short review of the literature about the use of weights in different types of analysis. The review provides the background to the final section, which contains indications regarding use of weights for analysis with MAFE data.

Methodological note 8

Thevenin, M., 'Manipulation des bases biographiques STATA', Janvier 2015 (FR)

L'objectif de ce tutoriel est de donner des outils de manipulation des modules biographiques de l'enquête MAFE avec STATA, en particulier lorsqu'il s'agit de mettre en oeuvre une analyse biographique à temps discret.

Methodological note 9

Thevenin, M., Rossi, D., 'Manipulation des bases biographiques SAS', Janvier 2015 (FR)

L'objectif de ce tutoriel est de donner des outils de manipulation des modules biographiques de l'enquête MAFE avec SAS, dans le cadre d'une mise en oeuvre dune analyse biographique à temps discret.

Introduction to the MAFE datasets

The aim of this document is to provide an introduction to the MAFE datasets, giving basic information to help users understand the structure and content of all MAFE datasets.

MAFE Ghana complete codebook

Contains in one document the entire codebook of the MAFE Ghana databases + all information available about the survey

Études reliées

IE0216A - Migrations between Africa and Europe - MAFE Senegal (2008)

IE0216B - Migrations between Africa and Europe - MAFE DR Congo (2009)

Publications reliées

Bibliography

Description des fichiers de données

Nom du fichier

gh_qm_household.NSDstat

Contenu des fichiers

One line per HH, i.e. a total of 1246 HH in Ghana
The dataset contains information on:  
- HH characteristics (computed variables from modules A & B);
- HH head characteristics (all variables from module A, including the computed variables created for the dataset "qm_indiv"). Variables names: hh_a1 to hh_a21;
- Housing and assets of the HH head (module E);
- Information on the conduct of the interview (module O).

Structure du fichier

Groupe d'enregistrement

Nombre total de cas

1246

Nombre total de variables

193

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

The variable weight_hdd represents normalized weights to be used in the analyses related to the household data, whatever the file used.

Nom du fichier

gh_qm_indiv.NSDstat

Contenu des fichiers

One line per declared individual in the HH questionnaire, i.e. a total of 7135 individuals in Ghana

Observations in this data file correspond to:
- Individuals living in the household at the time of the survey (A4=1)
- Individuals living outside the household (A4=2) included in the roster if they enter into one of the following categories:
   */ children of the HH head who no longer live with her/him, whatever her/his place of residence;
   */ partners of household members who live outside Ghana;
   */ parents of household members who live outside Ghana;
   */ other people living outside Ghana and who had regular contact with the household during the 12 months before the survey.
    
WARNING! Don't forget that only part of the people listed in the household questionnaires, i.e. in "qm_indiv" are actual members of the households.
Furthermore, keep in mind that some individuals, in this dataset, never lived in Congo, Ghana or Senegal. For example:
- Descendants of migrants, born in the destination country of their parents. Ex: the HH head is a grandfather whose son has immigrated to France, where he had children. These children can be mentioned by the grandfather in the third category "other persons living outside Senegal but who have kept regular contact with the HH during the 12 months before the survey", even if they have never lived in Senegal.
- Relatives of immigrants in Congo, Ghana or Senegal. Ex: the HH head is an immigrant woman from Angola. She has left behind (in her home country) her husband and children. Even if they have never lived in Congo, she mentioned them in the HH questionnaire because they are in the third category.

The dataset contains all variables of the questionnaire and some additional computed variables.

Structure du fichier

Groupe d'enregistrement

Nombre total de cas

7135

Nombre total de variables

151

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

The variable weight_hdd represents normalized weights to be used in the analyses related to the household data, whatever the file used.

Nom du fichier

gh_qb_general.NSDstat

Contenu des fichiers

!! One line per interviewee !!
This dataset contains variables that do not very over time, i.e. answers to the introductory module of the questionnaire and to variables from the inter-modules of the questionnaire, plus some computed variables.

As for variables statu_mig, migr_cur, migr_ret, migr_cjt and migr_no: a same individual can be coded 1 in several of the migratory status variables; e.g. a same individual can be both returnee and a partner of a migrant at the time of the survey.
NB: these variables may show results different from the stratification variable (strata_ind), which content was determined by answers given by proxy respondents in the household surveys. These variables (migr_*, presented in this table) are computed using the information obtained in the biographic surveys.

All MAFE's biographic files include the same 18 variables listed below:
- ident
- id_country
- n_menage
- n_indiv
- num_dr
- strata_area
- strata_hh
- strata_ind
- q1
- q1a
- age_survey
- q18
- flag_age
- flag_arrival
- flag_visitor (exception: only available for MAFE Senegal)
- weight_eur
- weight_all
- weight_ctry

Nombre total de cas

1666

Nombre total de variables

153

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

There are three different weight variables in the data files of the MAFE individual surveys. They were computed at three different levels:
- weight_ctry is the variable to use when working on a single country (for example, the Senegalese population sampled only in Senegal, or in any single European country).
- weight_eur is the variable to use when working on the European countries pooled together (for example, the Senegalese population sampled in France, Italy and Spain). It shoud not be used if the analyses include individuals surveyed in Africa.
- weight_all is the variable to use when working on all countries of the MAFE survey (for example, Senegalese population from Senegalese, French, Italian and Spanish samples).
For details on weight computation, see Schoumaker et al. (2013), a document that also provides information on when and how to use weights with the MAFE data (Methodological note 6 - see related materials).

Nom du fichier

gh_qb_union.NSDstat

Contenu des fichiers

!! One line per union for the interviewees which declared at least one union, in addition of one line per individual who had no partnership !!
This dataset contains all the answers to the module Union.

All MAFE's biographic files include the same 18 variables listed below:
- ident
- id_country
- n_menage
- n_indiv
- num_dr
- strata_area
- strata_hh
- strata_ind
- q1
- q1a
- age_survey
- q18
- flag_age
- flag_arrival
- flag_visitor (exception: only available for MAFE Senegal)
- weight_eur
- weight_all
- weight_ctry

Nombre total de cas

2598

Nombre total de variables

32

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

There are three different weight variables in the data files of the MAFE individual surveys. They were computed at three different levels:
- weight_ctry is the variable to use when working on a single country (for example, the Senegalese population sampled only in Senegal, or in any single European country).
- weight_eur is the variable to use when working on the European countries pooled together (for example, the Senegalese population sampled in France, Italy and Spain). It shoud not be used if the analyses include individuals surveyed in Africa.
- weight_all is the variable to use when working on all countries of the MAFE survey (for example, Senegalese population from Senegalese, French, Italian and Spanish samples).
For details on weight computation, see Schoumaker et al. (2013), a document that also provides information on when and how to use weights with the MAFE data (Methodological note 6 - see related materials).

Nom du fichier

gh_qb_children.NSDstat

Contenu des fichiers

!! One line per child for the interviewees who declared at least one child, in addition of one line per individual who had no child !!
This dataset contains all the answers to the module Children.

All MAFE's biographic files include the same 18 variables listed below:
- ident
- id_country
- n_menage
- n_indiv
- num_dr
- strata_area
- strata_hh
- strata_ind
- q1
- q1a
- age_survey
- q18
- flag_age
- flag_arrival
- flag_visitor (exception: only available for MAFE Senegal)
- weight_eur
- weight_all
- weight_ctry

Nombre total de cas

4375

Nombre total de variables

32

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

There are three different weight variables in the data files of the MAFE individual surveys. They were computed at three different levels:
- weight_ctry is the variable to use when working on a single country (for example, the Senegalese population sampled only in Senegal, or in any single European country).
- weight_eur is the variable to use when working on the European countries pooled together (for example, the Senegalese population sampled in France, Italy and Spain). It shoud not be used if the analyses include individuals surveyed in Africa.
- weight_all is the variable to use when working on all countries of the MAFE survey (for example, Senegalese population from Senegalese, French, Italian and Spanish samples).
For details on weight computation, see Schoumaker et al. (2013), a document that also provides information on when and how to use weights with the MAFE data (Methodological note 6 - see related materials).

Nom du fichier

gh_qb_house.NSDstat

Contenu des fichiers

!! One line per house for all the interviewees (everybody had to declare at least one house) !!
This dataset contains:
- all the answers to the module Housing.
- a series of dichotomous variables created from the question q307.
 
All MAFE's biographic files include the same 18 variables listed below:
- ident
- id_country
- n_menage
- n_indiv
- num_dr
- strata_area
- strata_hh
- strata_ind
- q1
- q1a
- age_survey
- q18
- flag_age
- flag_arrival
- flag_visitor (exception: only available for MAFE Senegal)
- weight_eur
- weight_all
- weight_ctry

Nombre total de cas

7784

Nombre total de variables

49

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

There are three different weight variables in the data files of the MAFE individual surveys. They were computed at three different levels:
- weight_ctry is the variable to use when working on a single country (for example, the Senegalese population sampled only in Senegal, or in any single European country).
- weight_eur is the variable to use when working on the European countries pooled together (for example, the Senegalese population sampled in France, Italy and Spain). It shoud not be used if the analyses include individuals surveyed in Africa.
- weight_all is the variable to use when working on all countries of the MAFE survey (for example, Senegalese population from Senegalese, French, Italian and Spanish samples).
For details on weight computation, see Schoumaker et al. (2013), a document that also provides information on when and how to use weights with the MAFE data (Methodological note 6 - see related materials).

Nom du fichier

gh_qb_activity.NSDstat

Contenu des fichiers

!! One line per activity for all the interviewees (everybody declares at least one activity) !!
This dataset contains:
- all the answers to the module Activity.
- a series of dichotomous variables created from the question q407.

All MAFE's biographic files include the same 18 variables listed below:
- ident
- id_country
- n_menage
- n_indiv
- num_dr
- strata_area
- strata_hh
- strata_ind
- q1
- q1a
- age_survey
- q18
- flag_age
- flag_arrival
- flag_visitor (exception: only available for MAFE Senegal)
- weight_eur
- weight_all
- weight_ctry

Nombre total de cas

8148

Nombre total de variables

45

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

There are three different weight variables in the data files of the MAFE individual surveys. They were computed at three different levels:
- weight_ctry is the variable to use when working on a single country (for example, the Senegalese population sampled only in Senegal, or in any single European country).
- weight_eur is the variable to use when working on the European countries pooled together (for example, the Senegalese population sampled in France, Italy and Spain). It shoud not be used if the analyses include individuals surveyed in Africa.
- weight_all is the variable to use when working on all countries of the MAFE survey (for example, Senegalese population from Senegalese, French, Italian and Spanish samples).
For details on weight computation, see Schoumaker et al. (2013), a document that also provides information on when and how to use weights with the MAFE data (Methodological note 6 - see related materials).

Nom du fichier

gh_qb_assets.NSDstat

Contenu des fichiers

!! One line per property for each person who declares at least one property and one line per individual with no asset !!
This dataset contains:
- all the answers to the module Assets & Business.
- a series of dichotomous variables created from the questions q509, q514 and q515.

All MAFE's biographic files include the same 18 variables listed below:
- ident
- id_country
- n_menage
- n_indiv
- num_dr
- strata_area
- strata_hh
- strata_ind
- q1
- q1a
- age_survey
- q18
- flag_age
- flag_arrival
- flag_visitor (exception: only available for MAFE Senegal)
- weight_eur
- weight_all
- weight_ctry

Nombre total de cas

2241

Nombre total de variables

79

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

There are three different weight variables in the data files of the MAFE individual surveys. They were computed at three different levels:
- weight_ctry is the variable to use when working on a single country (for example, the Senegalese population sampled only in Senegal, or in any single European country).
- weight_eur is the variable to use when working on the European countries pooled together (for example, the Senegalese population sampled in France, Italy and Spain). It shoud not be used if the analyses include individuals surveyed in Africa.
- weight_all is the variable to use when working on all countries of the MAFE survey (for example, Senegalese population from Senegalese, French, Italian and Spanish samples).
For details on weight computation, see Schoumaker et al. (2013), a document that also provides information on when and how to use weights with the MAFE data (Methodological note 6 - see related materials).

Nom du fichier

gh_qb_mig_attempts.NSDstat

Contenu des fichiers

!! One line per attempt for each person who declared at least one attempt and one line for the other interviewees !!
This dataset contains:
- all the answers to the module Migration Attempts.
- a series of dichotomous variables created from the question q805.
 
All MAFE's biographic files include the same 18 variables listed below:
- ident
- id_country
- n_menage
- n_indiv
- num_dr
- strata_area
- strata_hh
- strata_ind
- q1
- q1a
- age_survey
- q18
- flag_age
- flag_arrival
- flag_visitor (exception: only available for MAFE Senegal)
- weight_eur
- weight_all
- weight_ctry

Nombre total de cas

1707

Nombre total de variables

49

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

There are three different weight variables in the data files of the MAFE individual surveys. They were computed at three different levels:
- weight_ctry is the variable to use when working on a single country (for example, the Senegalese population sampled only in Senegal, or in any single European country).
- weight_eur is the variable to use when working on the European countries pooled together (for example, the Senegalese population sampled in France, Italy and Spain). It shoud not be used if the analyses include individuals surveyed in Africa.
- weight_all is the variable to use when working on all countries of the MAFE survey (for example, Senegalese population from Senegalese, French, Italian and Spanish samples).
For details on weight computation, see Schoumaker et al. (2013), a document that also provides information on when and how to use weights with the MAFE data (Methodological note 6 - see related materials).

Nom du fichier

gh_qb_migration.NSDstat

Contenu des fichiers

!! One line per long & short stay outside Ghana for each person who declares at least one stay and one line per individual who did no stay abroad !!
This dataset contains:
- all the answers to the module Long & Short stay outside Ghana.
- a series of dichotomous variables created from the questions q610, q614, q615, q616, q617, q619.
 
All MAFE's biographic files include the same 18 variables listed below:
- ident
- id_country
- n_menage
- n_indiv
- num_dr
- strata_area
- strata_hh
- strata_ind
- q1
- q1a
- age_survey
- q18
- flag_age
- flag_arrival
- flag_visitor (exception: only available for MAFE Senegal)
- weight_eur
- weight_all
- weight_ctry

Nombre total de cas

1958

Nombre total de variables

154

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

There are three different weight variables in the data files of the MAFE individual surveys. They were computed at three different levels:
- weight_ctry is the variable to use when working on a single country (for example, the Senegalese population sampled only in Senegal, or in any single European country).
- weight_eur is the variable to use when working on the European countries pooled together (for example, the Senegalese population sampled in France, Italy and Spain). It shoud not be used if the analyses include individuals surveyed in Africa.
- weight_all is the variable to use when working on all countries of the MAFE survey (for example, Senegalese population from Senegalese, French, Italian and Spanish samples).
For details on weight computation, see Schoumaker et al. (2013), a document that also provides information on when and how to use weights with the MAFE data (Methodological note 6 - see related materials).

Nom du fichier

gh_qb_return.NSDstat

Contenu des fichiers

!! One line per return to Ghana for each person who declared at least one return and one line for the other interviewees !!
Note: returns listed in this module are returns that lasted at least 1 year and shorter returns but with the intention of settling. Other returns (less than a year without intention to resettle) are listed in the qb_short_return datafiles.
This dataset contains:
- all the answers to the module Return to Ghana.
- a series of dichotomous variables created from the questions q707 and q708.
 
All MAFE's biographic files include the same 18 variables listed below:
- ident
- id_country
- n_menage
- n_indiv
- num_dr
- strata_area
- strata_hh
- strata_ind
- q1
- q1a
- age_survey
- q18
- flag_age
- flag_arrival
- flag_visitor (exception: only available for MAFE Senegal)
- weight_eur
- weight_all
- weight_ctry

Nombre total de cas

1717

Nombre total de variables

74

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

There are three different weight variables in the data files of the MAFE individual surveys. They were computed at three different levels:
- weight_ctry is the variable to use when working on a single country (for example, the Senegalese population sampled only in Senegal, or in any single European country).
- weight_eur is the variable to use when working on the European countries pooled together (for example, the Senegalese population sampled in France, Italy and Spain). It shoud not be used if the analyses include individuals surveyed in Africa.
- weight_all is the variable to use when working on all countries of the MAFE survey (for example, Senegalese population from Senegalese, French, Italian and Spanish samples).
For details on weight computation, see Schoumaker et al. (2013), a document that also provides information on when and how to use weights with the MAFE data (Methodological note 6 - see related materials).

Nom du fichier

gh_qb_network.NSDstat

Contenu des fichiers

!! One line per migration (for stays of at least one year) for each person in the network of the interviewee, and one line for each interviewee who has nobody abroad !!
This dataset contains:
- all the answers to the module Migrations of Family Members and Personal Network.
- computed variables: id_enf, id_uni, id_net and id_netmig.
 
All MAFE's biographic files include the same 18 variables listed below:
- ident
- id_country
- n_menage
- n_indiv
- num_dr
- strata_area
- strata_hh
- strata_ind
- q1
- q1a
- age_survey
- q18
- flag_age
- flag_arrival
- flag_visitor (exception: only available for MAFE Senegal)
- weight_eur
- weight_all
- weight_ctry

Nombre total de cas

6429

Nombre total de variables

34

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

There are three different weight variables in the data files of the MAFE individual surveys. They were computed at three different levels:
- weight_ctry is the variable to use when working on a single country (for example, the Senegalese population sampled only in Senegal, or in any single European country).
- weight_eur is the variable to use when working on the European countries pooled together (for example, the Senegalese population sampled in France, Italy and Spain). It shoud not be used if the analyses include individuals surveyed in Africa.
- weight_all is the variable to use when working on all countries of the MAFE survey (for example, Senegalese population from Senegalese, French, Italian and Spanish samples).
For details on weight computation, see Schoumaker et al. (2013), a document that also provides information on when and how to use weights with the MAFE data (Methodological note 6 - see related materials).

Nom du fichier

gh_qb_short_return.NSDstat

Contenu des fichiers

!! One line per return to Ghana of less than a year for each person who declared at least one short return (without a resettlement intention) or one line for a multiple return, and one line for all other individuals !!
This dataset contains all the answers to the module Return to Ghana of Less than a Year.

All MAFE's biographic files include the same 18 variables listed below:
- ident
- id_country
- n_menage
- n_indiv
- num_dr
- strata_area
- strata_hh
- strata_ind
- q1
- q1a
- age_survey
- q18
- flag_age
- flag_arrival
- flag_visitor (exception: only available for MAFE Senegal)
- weight_eur
- weight_all
- weight_ctry

Nombre total de cas

2263

Nombre total de variables

20

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

There are three different weight variables in the data files of the MAFE individual surveys. They were computed at three different levels:
- weight_ctry is the variable to use when working on a single country (for example, the Senegalese population sampled only in Senegal, or in any single European country).
- weight_eur is the variable to use when working on the European countries pooled together (for example, the Senegalese population sampled in France, Italy and Spain). It shoud not be used if the analyses include individuals surveyed in Africa.
- weight_all is the variable to use when working on all countries of the MAFE survey (for example, Senegalese population from Senegalese, French, Italian and Spanish samples).
For details on weight computation, see Schoumaker et al. (2013), a document that also provides information on when and how to use weights with the MAFE data (Methodological note 6 - see related materials).

Nom du fichier

gh_qb_short_stay.NSDstat

Contenu des fichiers

!! One line per stay of less than a year outside Ghana for each person who declared at least one stay !!
This dataset contains all the answers to the module Stays of Less than a Year outside Ghana.

All MAFE's biographic files include the same 18 variables listed below:
- ident
- id_country
- n_menage
- n_indiv
- num_dr
- strata_area
- strata_hh
- strata_ind
- q1
- q1a
- age_survey
- q18
- flag_age
- flag_arrival
- flag_visitor (exception: only available for MAFE Senegal)
- weight_eur
- weight_all
- weight_ctry

Nombre total de cas

2428

Nombre total de variables

22

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

There are three different weight variables in the data files of the MAFE individual surveys. They were computed at three different levels:
- weight_ctry is the variable to use when working on a single country (for example, the Senegalese population sampled only in Senegal, or in any single European country).
- weight_eur is the variable to use when working on the European countries pooled together (for example, the Senegalese population sampled in France, Italy and Spain). It shoud not be used if the analyses include individuals surveyed in Africa.
- weight_all is the variable to use when working on all countries of the MAFE survey (for example, Senegalese population from Senegalese, French, Italian and Spanish samples).
For details on weight computation, see Schoumaker et al. (2013), a document that also provides information on when and how to use weights with the MAFE data (Methodological note 6 - see related materials).

Nom du fichier

gh_qb_citizenship.NSDstat

Contenu des fichiers

!! One line per citizenship for each person (everybody should have at least one citizenship) !!
This dataset contains all the answers to the module Citizenship.
 
All MAFE's biographic files include the same 18 variables listed below:
- ident
- id_country
- n_menage
- n_indiv
- num_dr
- strata_area
- strata_hh
- strata_ind
- q1
- q1a
- age_survey
- q18
- flag_age
- flag_arrival
- flag_visitor (exception: only available for MAFE Senegal)
- weight_eur
- weight_all
- weight_ctry

Nombre total de cas

1794

Nombre total de variables

22

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

There are three different weight variables in the data files of the MAFE individual surveys. They were computed at three different levels:
- weight_ctry is the variable to use when working on a single country (for example, the Senegalese population sampled only in Senegal, or in any single European country).
- weight_eur is the variable to use when working on the European countries pooled together (for example, the Senegalese population sampled in France, Italy and Spain). It shoud not be used if the analyses include individuals surveyed in Africa.
- weight_all is the variable to use when working on all countries of the MAFE survey (for example, Senegalese population from Senegalese, French, Italian and Spanish samples).
For details on weight computation, see Schoumaker et al. (2013), a document that also provides information on when and how to use weights with the MAFE data (Methodological note 6 - see related materials).

Nom du fichier

gh_qb_asylum.NSDstat

Contenu des fichiers

!! One line per asylum application for each person who has made at least one application, and one line for the other individuals !!
This dataset contains all the answers to the module Asylum.

All MAFE's biographic files include the same 18 variables listed below:
- ident
- id_country
- n_menage
- n_indiv
- num_dr
- strata_area
- strata_hh
- strata_ind
- q1
- q1a
- age_survey
- q18
- flag_age
- flag_arrival
- flag_visitor (exception: only available for MAFE Senegal)
- weight_eur
- weight_all
- weight_ctry

Nombre total de cas

1673

Nombre total de variables

23

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

There are three different weight variables in the data files of the MAFE individual surveys. They were computed at three different levels:
- weight_ctry is the variable to use when working on a single country (for example, the Senegalese population sampled only in Senegal, or in any single European country).
- weight_eur is the variable to use when working on the European countries pooled together (for example, the Senegalese population sampled in France, Italy and Spain). It shoud not be used if the analyses include individuals surveyed in Africa.
- weight_all is the variable to use when working on all countries of the MAFE survey (for example, Senegalese population from Senegalese, French, Italian and Spanish samples).
For details on weight computation, see Schoumaker et al. (2013), a document that also provides information on when and how to use weights with the MAFE data (Methodological note 6 - see related materials).

Nom du fichier

gh_qb_residence_permit.NSDstat

Contenu des fichiers

!! One line per residence permit for each person who has had at least one permit, and one line for the other persons !!
This dataset contains all the answers to the module Residence Permits.

All MAFE's biographic files include the same 18 variables listed below:
- ident
- id_country
- n_menage
- n_indiv
- num_dr
- strata_area
- strata_hh
- strata_ind
- q1
- q1a
- age_survey
- q18
- flag_age
- flag_arrival
- flag_visitor (exception: only available for MAFE Senegal)
- weight_eur
- weight_all
- weight_ctry

Nombre total de cas

2380

Nombre total de variables

25

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

There are three different weight variables in the data files of the MAFE individual surveys. They were computed at three different levels:
- weight_ctry is the variable to use when working on a single country (for example, the Senegalese population sampled only in Senegal, or in any single European country).
- weight_eur is the variable to use when working on the European countries pooled together (for example, the Senegalese population sampled in France, Italy and Spain). It shoud not be used if the analyses include individuals surveyed in Africa.
- weight_all is the variable to use when working on all countries of the MAFE survey (for example, Senegalese population from Senegalese, French, Italian and Spanish samples).
For details on weight computation, see Schoumaker et al. (2013), a document that also provides information on when and how to use weights with the MAFE data (Methodological note 6 - see related materials).

Nom du fichier

gh_qb_work_permit.NSDstat

Contenu des fichiers

!! One line per work permit for each person who has had at least one permit, and one line for the others !!
This dataset contains all the answers to the module Work Permits.

All MAFE's biographic files include the same 18 variables listed below:
- ident
- id_country
- n_menage
- n_indiv
- num_dr
- strata_area
- strata_hh
- strata_ind
- q1
- q1a
- age_survey
- q18
- flag_age
- flag_arrival
- flag_visitor (exception: only available for MAFE Senegal)
- weight_eur
- weight_all
- weight_ctry

Nombre total de cas

2334

Nombre total de variables

24

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

There are three different weight variables in the data files of the MAFE individual surveys. They were computed at three different levels:
- weight_ctry is the variable to use when working on a single country (for example, the Senegalese population sampled only in Senegal, or in any single European country).
- weight_eur is the variable to use when working on the European countries pooled together (for example, the Senegalese population sampled in France, Italy and Spain). It shoud not be used if the analyses include individuals surveyed in Africa.
- weight_all is the variable to use when working on all countries of the MAFE survey (for example, Senegalese population from Senegalese, French, Italian and Spanish samples).
For details on weight computation, see Schoumaker et al. (2013), a document that also provides information on when and how to use weights with the MAFE data (Methodological note 6 - see related materials).

Nom du fichier

gh_qb_transfer.NSDstat

Contenu des fichiers

!! One line per transfer for each person who has sent remittances at least once, and one line for the other persons !!
This dataset contains:
- all the answers to the module Transfers.
- the created variable nom_transr which gives the total number of transfers made by Ego.
 
All MAFE's biographic files include the same 18 variables listed below:
- ident
- id_country
- n_menage
- n_indiv
- num_dr
- strata_area
- strata_hh
- strata_ind
- q1
- q1a
- age_survey
- q18
- flag_age
- flag_arrival
- flag_visitor (exception: only available for MAFE Senegal)
- weight_eur
- weight_all
- weight_ctry

Nombre total de cas

1731

Nombre total de variables

22

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

There are three different weight variables in the data files of the MAFE individual surveys. They were computed at three different levels:
- weight_ctry is the variable to use when working on a single country (for example, the Senegalese population sampled only in Senegal, or in any single European country).
- weight_eur is the variable to use when working on the European countries pooled together (for example, the Senegalese population sampled in France, Italy and Spain). It shoud not be used if the analyses include individuals surveyed in Africa.
- weight_all is the variable to use when working on all countries of the MAFE survey (for example, Senegalese population from Senegalese, French, Italian and Spanish samples).
For details on weight computation, see Schoumaker et al. (2013), a document that also provides information on when and how to use weights with the MAFE data (Methodological note 6 - see related materials).

Nom du fichier

gh_qb_association.NSDstat

Contenu des fichiers

!! One line per period during which each person has joined a migrant association, and one line for the other persons !!
This dataset contains all the answers to the module Associations.

All MAFE's biographic files include the same 18 variables listed below:
- ident
- id_country
- n_menage
- n_indiv
- num_dr
- strata_area
- strata_hh
- strata_ind
- q1
- q1a
- age_survey
- q18
- flag_age
- flag_arrival
- flag_visitor (exception: only available for MAFE Senegal)
- weight_eur
- weight_all
- weight_ctry

Nombre total de cas

1688

Nombre total de variables

20

Type de fichier

Nesstar 200801

Données manquantes

Due to the files conversion, all "Refuse to answer", "No answer" and "Don't know" values appear here in missing frequencies.

Notes

All "Yes" / "No" answers have been recoded, in order to facilitate analyses. In the questionnaire code, "No" was 2. It is now 0 in the dataset code. In both cases "Yes" is 1.
The multiple answers variables are those where respondents could give more than one answer. To have a better view of these answers and to make the analysis easier, these variables are dichotomised in the datasets: for each possible modality a dichotomous variable was created (0 = No ; 1 = Yes).

There are three different weight variables in the data files of the MAFE individual surveys. They were computed at three different levels:
- weight_ctry is the variable to use when working on a single country (for example, the Senegalese population sampled only in Senegal, or in any single European country).
- weight_eur is the variable to use when working on the European countries pooled together (for example, the Senegalese population sampled in France, Italy and Spain). It shoud not be used if the analyses include individuals surveyed in Africa.
- weight_all is the variable to use when working on all countries of the MAFE survey (for example, Senegalese population from Senegalese, French, Italian and Spanish samples).
For details on weight computation, see Schoumaker et al. (2013), a document that also provides information on when and how to use weights with the MAFE data (Methodological note 6 - see related materials).

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