9 datasets found
  1. w

    Pacific Labor Mobility Survey 2021-2023 - Australia, Kiribati, New...

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Jan 9, 2025
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    Dung Doan (2025). Pacific Labor Mobility Survey 2021-2023 - Australia, Kiribati, New Zealand...and 2 more [Dataset]. https://microdata.worldbank.org/index.php/catalog/6420
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    Dataset updated
    Jan 9, 2025
    Dataset provided by
    Ryan Edwards
    Matthew Dornan
    Dung Doan
    Time period covered
    2021 - 2023
    Area covered
    Kiribati, New Zealand, Australia
    Description

    Abstract

    Previous surveys on labor migration from Pacific Island countries are often cross-sectional, not readily available, and focusing on one migration scheme, country, or issue and hence incompatible. Such limitation of existing data restricts analysis of a range of policy-relevant issues that present themselves over the migrants' life cycle such as those on migration pathways, long-term changes in household livelihood, and trajectory of migrants’ labor market outcomes, despite the significant impacts of labor migration on the economy of the Pacific Island countries. To address these shortfalls in the Pacific migration data landscape, the PLMS is designed to be longitudinal, spanning multiple labor sending and receiving countries and collecting omnibus information on both migrants, their households and non-migrant households. The survey allows for disaggregation and reliable comparative analysis both within and across countries and labor mobility schemes. This open-access and high-quality data will facilitate more research about the Pacific migration, help inform and improve Pacific migration policy deliberations, and engender broader positive change in the Pacific data ecosystem.

    Geographic coverage

    Tonga: Tongatapu, ‘Eua, Vava’u, Ha’apai, Ongo Niua. Vanuatu: Malampa, Penama, Sanma, Shefa, Tafea, Torba. Kiribati: Abaiang, Abemama, Aranuka, Arorae, Banaba, Beru, Butaritari, Kiritimati, Maiana, Makin, Marakei, Nikunau, Nonouti, North Tabiteuea, North Tarawa, Onotoa, South Tabiteuea, South Tarawa, Tabuaeran, Tamana, Teraina.

    Analysis unit

    • Households in Kiribati, Tonga, and Vanuatu.
    • Temporary migrant workers from Kiribati, Tonga and Vanuatu who participated in the Pacific Australia Labour Mobility scheme in Australia and the Recognised Seasonal Employers scheme in New Zealand

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Sampling frame: The PLMS sample was designed based on a Total Survey Error framework, seeking to minimize errors and bias at every stage of the process throughout preparation and implementation.

    The worker sample frame is an extensive list of approximately 11,600 migrant workers from Kiribati, Tonga and Vanuatu who had participated in the RSE and PALM schemes. Due to the different modes of interviews, sampling strategies for the face-to-face segment of the household survey in Tonga was different from the rest of the surveys implemented via phone interviews. The face-to-face segment of the household survey selected households using Probability Proportional to Size sampling based on the latest population census listing and our worker sample frame, with technical inputs from the Tonga Statistics Department. The phone-based segment of the household survey used a combination of Probability Proportional to Size sampling based on the existing sample frame and random digit dialing. The design of the sample benefited from technical inputs from the Tonga Statistics Departments and the Vanuatu National Statistics Office, as well as World Bank staff from Kiribati.

    As participation in the survey is voluntary, a worker might agree to participate while their household did not, and vice versa. Because of this, the survey did not achieve a complete one-to-one match between interviewed workers and sending households. Of all interviewed respondents, 418 workers in the worker survey are linked to their households in the household survey. However, after removing incomplete interviews, 341 worker-household pairs remain. They are matched by either pre-assigned serial ID numbers or contact details collected in the household and worker surveys during the post-fieldwork data cleaning process.

    Sampling deviation

    The survey was originally planned to be conducted face-to-face and was so for most of the collection of household data in Tonga. However, due to COVID-19, it was switched to phone-based mode and the survey instruments were adjusted accordingly to better suit the phone-based data collection while ensuring data quality. In particular, the household questionnaire was shortened, and sampling strategy changed to a combination of Probability Proportional to Size sampling based on the existing household listing and random digit dialing.

    Compared to in-person data collection, the usual caveats of potential biases in phone-based survey related to disproportional phone ownership and connectivity apply here. The random digit dialing approach provides data representative of the phone-owning population. Yet due to lack of information, it is difficult to judge whether sending households in Kiribati, Tonga, and Vanuatu are more or less likely to own a phone and/or respond positively to survey request than non-sending households.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    • The questionnaires were jointly designed in English by the World Bank and researchers at the Development Policy Centre, Australian National University. They were translated into Bislama, Gilbertese and Tongan, scripted into CAPI/CATI programs, tested and piloted before being finalized. The design of the questionnaires and the samples benefited from technical inputs from the Tonga Statistics Departments, Pacific consultants, and academic experts specialized in Pacific labor mobility and remittances.
    • Enumerators are native speakers from the labor-sending countries covered in the survey and were trained to elicit information asked in the questionnaire in local languages.
    • The phone-based household questionnaire is moderately shorter than the in-person version.

    Cleaning operations

    The published data have been cleaned and anonymized. All incomplete interview records have been removed from the final datasets. The anonymization process followed the theory of Statistical Disclosure Control for microdata, aiming to minimize re-identification risk, i.e. the risk that the identity of an individual (or a household) described by a specific record could be determined with a high level of confidence. The anonymization process employs the k-anonymity method to calculate the re-identification risk. Risk measurement, anonymization and utility measurement for the PLMS were done using sdcMicro, an add-on package for the statistical software R for Statistical Disclosure Control (SDC) of microdata.

    Since the household questionnaire was shortened when the survey switched from face-to-face to phone-based data collection, there face-to-face datasets and phone-based datasets are not identical, but they are consistent and can be harmonized. The mapping guide enclosed in this publication provides a guide to data users to wish to harmonize them.

    Household expenditure variables in the household dataset and individual wage variable in the household member dataset are in USD. Local currencies were converted into USD based on the following exchange rates: 1 Tongan Pa'anga= 0.42201412 USD; 1 Vanuatu Vatu= 0.0083905322 USD; 1 Kiribati dollar= 0.66942499 USD.

    Response rate

    Face-to-face segment of the PLMS household survey: not applicable. Phone-based segment of the PLMS household survey: 26%. The PLMS Worker survey: 31%

  2. d

    Second European Union Minorities and Discrimination Survey (EU-MIDIS II),...

    • b2find.dkrz.de
    Updated May 17, 2023
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    (2023). Second European Union Minorities and Discrimination Survey (EU-MIDIS II), 2016 - Dataset - B2FIND [Dataset]. https://b2find.dkrz.de/dataset/16662a0f-d1b4-59bf-ad22-a57a9dd0daf4
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    Dataset updated
    May 17, 2023
    Area covered
    European Union
    Description

    The second European Union Minorities and Discrimination Survey (EU-MIDIS II) was conducted in 2016 by the European Union Agency for Fundamental Rights (FRA) as a follow-up to the first survey on minorities´ and immigrants´ experiences of discrimination and criminal victimisation conducted by the Agency in 2008. The EU-MIDIS II survey collected information from 25,515 respondents from different ethnic minority and migrant backgrounds, including Roma, in all EU Member States (2016: EU-28 including the UK). The EU-MIDIS II sample is representative of the selected populations that were interviewed. The sample includes persons belonging to ethnic or national minorities, Roma and Russians, persons born outside the EU (first generation respondents) and persons with at least one parent born outside the EU (second generation respondents). All respondents were 16 years or older and had lived in a private household for at least 12 months before the interview. People living in institutional settings - for example, hospitals or prisons - were not interviewed. The selection of groups to be surveyed in each country was based on several criteria, including the size of the target population, the feasibility of surveying the target population in terms of cost and accessibility, the risk of certain groups experiencing ´racial´, ´ethnic´ or ´religious´ discrimination and victimisation, their vulnerability to the risk of social exclusion and, finally, comparability with previous FRA surveys. The target groups of the EU-MIDIS II survey are immigrants and descendants of immigrants from North Africa; immigrants and descendants of immigrants from Turkey; immigrants and descendants of immigrants from Sub-Saharan Africa; immigrants and descendants of immigrants from Asia and South Asia; new immigrants; Roma; members of the Russian minority. In Slovenia and Poland, people who immigrated to the EU in the last 10 years were included, regardless of country of origin. The fieldwork was conducted between September 2015 and September 2016 by Ipsos MORI under the supervision of FRA staff who monitored compliance with strict quality control procedures. The questionnaire includes questions on perceived discrimination in various areas, such as employment, education, housing, health and in the use of public or private services. It also covers police checks, criminal victimisation (including hate crime), and awareness of rights and of institutions that provide victim support. In addition, respondents were asked about issues of social participation and integration, including trust in public institutions and the degree of attachment to the country in which they live.

  3. g

    Immigration Statistics: work | gimi9.com

    • gimi9.com
    Updated Aug 26, 2011
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    (2011). Immigration Statistics: work | gimi9.com [Dataset]. https://gimi9.com/dataset/uk_immigration-statistics-work
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    Dataset updated
    Aug 26, 2011
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    This release replaces the previous annual and quarterly publications Control of Immigration Statistics and the annual British Citizenship, following a public consultation. Each topic now has its own entry, links to these related reports can be found under the "additional links" section. There are a range of measures that can be used to understand trends in immigration to the United Kingdom for work, for those people who are subject to immigration control. These include: issues of visas for entry clearance, providing information about those intending to come to the United Kingdom for work; work-related admissions data, providing information on migrants at the border; number of people allocated national insurance numbers, giving an indication of migrants entering the labour market; and estimates on non-EU immigration from the International Passenger Survey on migrants intending to stay for at least a year for work purposes. In addition, grants of (in-country) extensions of stay for work purposes provide information on migrants in-country, while work-related grants of settlement provides a measure of longer term migration.

  4. d

    Culture, education, skills, migration and consumption in Nepal 2013-2018 -...

    • b2find.dkrz.de
    Updated Oct 23, 2023
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    (2023). Culture, education, skills, migration and consumption in Nepal 2013-2018 - Dataset - B2FIND [Dataset]. https://b2find.dkrz.de/dataset/35d024ad-845d-53ed-94d4-69b8eabd77e3
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    Dataset updated
    Oct 23, 2023
    Area covered
    Nepal
    Description

    It contains survey data collected in Kaski and Chitwan districts of Nepal between 2014 and 2016, related to education and skills, migration, caste relations, and cultural consumption. Survey data entails 837 variables and 1203 respondents. Field research were carried out for a year and half in these villages and in their migration satellites in the Tarai (the Gangetic strip of south Nepal abutting India), in urban centres, and international migrants also were included. Participant observation and interviews were combined with detailed surveys of both households and individuals in order to reveal changing attitudes to education, employment, and migration. The two next-biggest local ethnic groups, the Chhetris and Gurungs, who rank in between Bahuns and Dalits in the traditional caste hierarchy, were also included in the quantitative part of the study in order to bring out contrasts and comparisons. By producing an empirically sound, ethnographically sensitive, and quantitatively sophisticated study of the social history and migration of these two key Nepali groups, one of which is the most significant disadvantaged caste bloc, the research aimed having considerable potential policy impact in Nepal. The timing of research, coming as it did during the ongoing peace process and while disadvantage and exclusion are still very much part of the political debate, was appropriate and indeed advantageous.Nepal, like India, has traditionally been a caste society, with Bahuns (Brahmans) at the top, Chhetris (Kshatriyas) second, and Dalits (ex-Untouchables) at the bottom. Groups that used to be known as tribes and are now called Janajatis (the groups most commonly recruited to the Gurkha regiments) were slotted into the middle of the hierarchy. Between 1854 and 1951 this caste hierarchy was enforced in an authoritarian way by the state, and until 1963 regulated by law. In India, Dalits have, since 1947, if not before, benefited from positive discrimination in government employment and gradually in education. In Nepal there were till recently no such provisions. Comparing different groups in the country, Nepali Dalits today have the lowest life expectancy, the highest rates of illiteracy, the worst job prospects, the lowest incomes and wealth, and the worst rates of achievement in education. Of all groups of any size they are most disadvantaged and the most discriminated against. Bahuns, by contrast, do extremely well in education, have higher levels of educational attainment, and obtain more elite and professional jobs than any other group. They also provide the bulk of the political elite. Neither Dalits nor Bahuns have been studied as much they should have, given their importance in Nepali society, and this study aims to fill this gap. The political situation in Nepal is in flux. The Constituent Assembly, elected in April 2008 on the most inclusive franchise ever used in Nepal (surpassing even India's measures to ensure representation for marginal groups), failed ignominiously to produce a constitution, even after four years and four extensions of time, in May 2012. The Supreme Court refused to prolong the Assembly, leaving Nepal with a caretaker Prime Minister, no parliament, and an uncertain future. The key issue, over which the constitution-writing faltered, was that of ethnicity. In this context, it was essential to understand from the bottom up, the new process of ethnic identity formation among Bahuns and Dalits - a reaction to the much longer-standing and politically more assertive ethnicity formation among ex-tribal Janajati groups. This project aimed to examine in detail exactly how the patterns of disadvantage and exclusion, on the one hand, and achievement and success, on the other, are produced and reproduced. In doing so it focused on six neighbouring villages in west central Nepal where the two largest population groups are Bahuns and Dalits. The qualitative data was collected through semi-structured interviews with Dalit activists, scholars and politicians using purposive sampling. The quantitative data was collected through a survey of individuals. It was built upon an initial census-type household exploration representing different caste groups, including Bahuns and Dalits, from a set of six neighbouring villages. First, households were selected using stratified random sample (caste and class) taking 50% of the original households, and individuals 13 years or older were administered the survey questionnaire. Some temporarily migrated individuals, as well as some permanent migrants, were also interviewed at their migration destinations in Nepal. Altogether 1,203 respondents were covered in the face to face survey.

  5. C

    Migration chain: Departure - DT&V Identity verification and (replacement)...

    • ckan.mobidatalab.eu
    Updated Jul 13, 2023
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    OverheidNl (2023). Migration chain: Departure - DT&V Identity verification and (replacement) travel documents - LP and T&O travel documents [Dataset]. https://ckan.mobidatalab.eu/dataset/migratieketen-vertrek-dt-v-identiteitsvaststelling-en-reisdocumenten-reisdocumenten
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    http://publications.europa.eu/resource/authority/file-type/json, http://publications.europa.eu/resource/authority/file-type/csv, http://publications.europa.eu/resource/authority/file-type/htmlAvailable download formats
    Dataset updated
    Jul 13, 2023
    Dataset provided by
    OverheidNl
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    See the 'State of Migration' or 'Rapportage Immigration Chain' (until 2020) for a substantive explanation of the data in this dataset. See chapter 'Methodology' for a number of aspects that should be taken into account when interpreting the data. The 'State of Migration' and 'Rapportage Immigration Chain' can be downloaded from the site www.Rijksoverheid.nl Below you will find an updated substantive explanation of the data in the files. In order to be able to return, foreign nationals must be given access to the country of origin. This can be done on the basis of a valid passport or a replacement travel document, usually a laissez-passer issued by the country of origin. Foreign nationals who no longer have the correct documents can, possibly with the support of the DT&V, apply for (replacement) travel documents at their diplomatic representation for independent departure. However, some of the foreign nationals without lawful residence do not leave the Netherlands independently and are not prepared to cooperate in establishing identity and nationality. For these foreign nationals, the DT&V asks the presumed country of origin to determine the nationality and to provide a (replacement) travel document for return. This is the so-called laissez-passer process. A return or readmission request is submitted to countries with which a return and readmission agreement (T&O) has been concluded. This is called the T&O process. A request to determine the nationality has three possible outcomes: 1) The authorities of the country in question establish that the person concerned possesses the nationality of that country or otherwise has a right of residence in the country; 2) The authorities of the country in question determine that the person concerned does not have the nationality of the country or that this cannot be confirmed; 3) The DT&V decides to withdraw the request. Ad 1. As a rule, a nationality determined by the country of origin means that the country of origin also agrees to issue a replacement travel document (laissez-passer). The DT&V asks the country of origin to actually provide a laissez-passer only for a scheduled flight. Among other things, subsequent residence law procedures and interim evasion from central government supervision mean that not all established nationalities result in the actual issue of a laissez-passer and departure from the Netherlands. Re 2. This means that the person concerned is not a national or that the nationality cannot be determined on the basis of the information provided. Such an answer can give direction to the follow-up process. The response that the person concerned does not have the nationality of the country cannot, in principle, be blamed on that country. These often concern cases in which foreign nationals themselves have not provided sufficient information to be able to establish their identity and/or actually come from another country. Ad 3. The DT&V can withdraw a request for various reasons, for example because there has been no response from the country of origin for some time. In addition, foreign nationals sometimes evade supervision by the central government or are still granted a residence permit. There are a number of aspects that need to be taken into account when interpreting the data. - The individual tables do not form a cohort. - All numbers are rounded to tens. For privacy reasons, numbers less than 5 are not shown. - Because the numbers are rounded to the nearest tens, deviations may occur when adding detailed numbers compared to, for example, the annual total. For detailed rules with nationalities, the deviation can be significant. For this reason, the totals are also included in the file. - Each line in the file contains at least a column 'Total of' and a number. The 'Total of' column shows the contents of the number. For example, the line with 'Year' in the 'Total of' column indicates the year total. The lines with 'Year, Month' in the 'Total of' column indicate the total number for each year and month. - Always use only one 'total of' per item to avoid double counting. - The numbers stated in the 'Reporting on the Immigration Chain' serve as a frame of reference. The files are published annually for the previous year. Files from previous years remain available and will no longer be updated.

  6. o

    Das Wahlverhalten der Deutschen mit Migrationshintergrund, qualitative...

    • explore.openaire.eu
    • doi.pangaea.de
    Updated Jan 1, 2020
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    Achim Goerres; Dennis C Spies; Sabrina J Mayer (2020). Das Wahlverhalten der Deutschen mit Migrationshintergrund, qualitative Phase. Transkripte der Fokusgruppeninterviews [Dataset]. http://doi.org/10.1594/pangaea.919342
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    Dataset updated
    Jan 1, 2020
    Authors
    Achim Goerres; Dennis C Spies; Sabrina J Mayer
    Area covered
    Deutschland
    Description

    DE: Dieser Datensatz besteht aus den Transkripten von vier Fokusgruppeninterviews der Migrantenwahlstudie. Ziel des Projektes war es, für die Bundestagswahl 2017 die erste deutsche Wahlstudie unter deutschen Staatsbürger/innen mit Migrationshintergrund durchzuführen, d.h. unter solchen Personen, die entweder selbst nach Deutschland immigriert sind oder die mindestens einen Elternteil mit eigener Migrationserfahrung haben. Die Migrantenwahlstudie umfasst eine qualitative und eine quantitative Phase. Ziel der ersten qualitativen Phase (Oktober 2016 bis Juli 2017) war der explorative Zugang zur Themen- und Kandidatenorientierung von Migrant/innen, um die Ergebnisse für eine Publikation sowie die Fragebogenentwicklung der quantitativen Phase zu nutzen: Welche Themenfelder werden als wichtig erachtet? Welche Vorstellung von Links-Rechts gibt es? Welche Kandidateneigenschaften sind besonders relevant? Wie stark ist die Bindung an das Herkunftsland? Als Methode haben wir dabei auf Gruppendiskussionen mit Russlanddeutschen zurückgegriffen, die in Duisburg und Köln durchgeführt wurden. Dabei haben wir mit etwa 5-6 Teilnehmer/innen jeweils knapp zwei Stunden lang diskutiert. Die Forschungsdaten der quantitativen Phase wurden beim Forschungsdatenzentrum GESIS archiviert.EN: This dataset is composed of the transcripts of four focus group interviews for the Immigrant German Election Study. The project aims to conduct the first Immigrant German Election Study for the federal election in 2017, targeting German citizens with an immigrant background, i.e. people who either migrated to Germany themselves (first generation) or have at least one parent who was born in another country (second generation). The Immigrant German Election Study encompasses a qualitative and a quantitative phase. The first qualitative stage of the project (October 2016 until July 2017) explored the issue and candidate orientations of migrants. The results were used for a publication as well as for the development of the questionnaire for the quantitative stage. The core questions are: Which political issues are classified as important to all Germans/all migrants from the same group? What political issues do Germans of immigrant origin perceive as "left" and "right"? What are the identity contents that Germans of migrant origin associate with being German? We used focus group interviews as the research method in the Duisburg/Cologne area that consisted of 5-6 participants each and lasted for about 90 minutes.The research data originating from the quantitative phase have been archived at GESIS Data Archive. Transcription method: Standardorthographie, geglättetStudy-Materials note: verfügbare Kontexmaterialien sind Stimuli, Leitfaden, standardisierter Fragebogen, Liste der Kodes, StudienberichtDE: Die Forschungsdaten können auf Anfrage beim Forschungsdatenzentrum Qualiservice erhalten werden. Für weitere Informationen besuchen Sie bitte die Qualiservice-Website: https://www.qualiservice.org/de/daten-nutzen.html

  7. w

    Demographic and Health Survey 2011 - Nepal

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +2more
    Updated Jun 5, 2017
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    New ERA (2017). Demographic and Health Survey 2011 - Nepal [Dataset]. https://microdata.worldbank.org/index.php/catalog/1466
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    Dataset updated
    Jun 5, 2017
    Dataset provided by
    New ERA
    Population Division
    Time period covered
    2011
    Area covered
    Nepal
    Description

    Abstract

    The 2011 Nepal Demographic and Health Survey is the fourth nationally representative comprehensive survey conducted as part of the worldwide Demographic and Health Surveys (DHS) project in the country. The survey was implemented by New ERA under the aegis of the Population Division, Ministry of Health and Population. Technical support for this survey was provided by ICF International with financial support from the United States Agency for International Development (USAID) through its mission in Nepal.

    The primary objective of the 2011 NDHS is to provide up-to-date and reliable data on different issues related to population and health, which provides guidance in planning, implementing, monitoring, and evaluating health programs in Nepal. The long term objective of the survey is to strengthen the technical capacity of the local institutions to plan, conduct, process and analyze data from complex national population and health surveys. The survey includes topics on fertility levels and determinants, family planning, fertility preferences, childhood mortality, children and women’s nutritional status, the utilization of maternal and child health services, knowledge of HIV/AIDS and STIs, women’s empowerment and for the first time, information on women facing different types of domestic violence. The survey also reports on the anemia status of women age 15-49 and children age 6-59 months.

    In addition to providing national estimates, the survey report also provides disaggregated data at the level of various domains such as ecological region, development regions and for urban and rural areas. This being the fourth survey of its kind, there is considerable trend information on reproductive and health care over the past 15 years. Moreover, the 2011 NDHS is comparable to similar surveys conducted in other countries and therefore, affords an international comparison. The 2011 NDHS also adds to the vast and growing international database on demographic and health-related variables.

    The 2011 NDHS collected demographic and health information from a nationally representative sample of 10,826 households, which yielded completed interviews with 12,674 women age 15-49 in all selected households and with 4, 121 men age 15-49 in every second household.

    This survey is the concerted effort of various individuals and institutions.

    Geographic coverage

    The primary focus of the 2011 NDHS was to provide estimates of key population and health indicators, including fertility and mortality rates, for the country as a whole and for urban and rural areas separately. In addition, the sample was designed to provide estimates of most key variables for the 13 eco-development regions.

    Analysis unit

    Household, adult woman, adult man

    Kind of data

    Sample survey data

    Sampling procedure

    The primary focus of the 2011 NDHS was to provide estimates of key population and health indicators, including fertility and mortality rates, for the country as a whole and for urban and rural areas separately. In addition, the sample was designed to provide estimates of most key variables for the 13 eco-development regions.

    Sampling Frame

    Nepal is divided into 75 districts, which are further divided into smaller VDCs and municipalities. The VDCs and municipalities, in turn, are further divided into wards. The larger wards in the urban areas are divided into subwards. An enumeration area (EA) is defined as a ward in rural areas and a subward in urban areas. Each EA is classified as urban or rural. As the upcoming population census was scheduled for June 2011, the 2011 NDHS used the list of EAs with population and household information developed by the Central Bureau of Statistics for the 2001 Population Census. The long gap between the 2001 census and the fielding of the 2011 NDHS necessitated an updating of the 2001 sampling frame to take into account not only population growth but also mass internal and external migration due to the 10-year political conflict in the country. To obtain an updated list, a partial updating of the 2001 census frame was carried out by conducting a quick count of dwelling units in EAs five times more than the sample required for each of the 13 domains. The results of the quick count survey served as the actual frame for the 2011 NDHS sample design.

    Domains

    The country is broadly divided into three horizontal ecological zones, namely mountain, hill, and terai. Vertically, the country is divided into five development regions. The cross section of these zones and regions results in 15 eco-development regions, which are referred to in the 2011 NDHS as subregions or domains. Due to the small population size in the mountain regions, the Western, Mid-western, and Far-western mountain regions are combined into one domain, yielding a total of 13 domains. In order to provide an adequate sample to calculate most of the key indicators at an acceptable level of precision, each domain had a minimum of about 600 households.

    Stratification was achieved by separating each of the 13 domains into urban and rural areas. The 2011 NDHS used the same urban-rural stratification as in the 2001 census frame. In total, 25 sampling strata were created. There are no urban areas in the Western, Mid-western, and Far-western mountain regions. The numbers of wards and subwards in each of the 13 domains are not allocated proportional to their population due to the need to provide estimates with acceptable levels of statistical precision for each domain and for urban and rural domains of the country as a whole. The vast majority of the population in Nepal resides in the rural areas. In order to provide national urban estimates, urban areas of the country were oversampled.

    Sample Selection

    Samples were selected independently in each stratum through a two-stage selection process. In the first stage, EAs were selected using a probability-proportional-to-size strategy. In order to achieve the target sample size in each domain, the ratio of urban EAs to rural EAs in each domain was roughly 1 to 2, resulting in 95 urban and 194 rural EAs (a total of 289 EAs).

    Complete household listing and mapping was carried out in all selected EAs (clusters). In the second stage, 35 households in each urban EA and 40 households in each rural EA were randomly selected. Due to the nonproportional allocation of the sample to the different domains and to oversampling of urban areas in each domain, sampling weights are required for any analysis using the 2011 NDHS data to ensure the actual representativeness of the sample at the national level as well as at the domain levels. Since the 2011 NDHS sample is a two-stage stratified cluster sample, sampling weights were calculated based on sampling probabilities separately for each sampling stage, taking into account nonproportionality in the allocation process for domains and urban-rural strata.

    Mode of data collection

    Face-to-face

    Research instrument

    Three questionnaires were administered in the 2011 NDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. These questionnaires were adapted from the standard DHS6 core questionnaires to reflect the population and health issues relevant to Nepal at a series of meetings with various stakeholders from government ministries and agencies, nongovernmental organizations, EDPs, and international donors. The final draft of each questionnaire was discussed at a questionnaire design workshop organized by the MOHP, Population Division on 22 April 2010 in Kathmandu. These questionnaires were then translated from English into the three main local languages—Nepali, Maithali, and Bhojpuri—and back translated into English. Questionnaires were finalized after the pretest, which was held from 30 September to 4 November 2010, with a one-week break in October for the Dasain holiday.

    The Household Questionnaire was used to list all of the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. For children under age 18, the survival status of the parents was determined. The Household Questionnaire was used to identify women and men who were eligible for the individual interview and women who were eligible for the interview focusing on domestic violence. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as source of water, type of toilet facilities, materials used for the floor of the house, ownership of various durable goods, ownership of mosquito nets, and household food security. The results of salt testing for iodine content, height and weight measurements, and anemia testing were also recorded in the Household Questionnaire.

    The Woman’s Questionnaire was used to collect information from women age 15-49. Women were asked questions on the following topics: - background characteristics (education, residential history, media exposure, etc.) - pregnancy history and childhood mortality - knowledge and use of family planning methods - fertility preferences - antenatal, delivery, and postnatal care - breastfeeding and infant feeding practices - vaccinations and childhood illnesses - marriage and sexual activity - work characteristics and husband’s background characteristics - awareness and behavior regarding AIDS and other sexually transmitted infections - domestic violence

    The Man’s Questionnaire was administered to all men age 15-49 living in every second household in the 2011 NDHS. The Man’s Questionnaire collected much of the same information as the Woman’s Questionnaire but was shorter

  8. e

    Labor Market Panel Survey, TLMPS 2014 - Tunisia

    • erfdataportal.com
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    Updated May 2, 2018
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    Economic Research Forum (2018). Labor Market Panel Survey, TLMPS 2014 - Tunisia [Dataset]. http://www.erfdataportal.com/index.php/catalog/105
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    Dataset updated
    May 2, 2018
    Dataset authored and provided by
    Economic Research Forum
    Time period covered
    2014 - 2015
    Area covered
    Tunisia
    Description

    Abstract

    The Egypt Labor Market Panel Surveys (ELMPSs) of 1998, 2006, and 2012 and Jordan Labor Market Panel Survey (JLMPS) of 2010 have become well-recognized data sources for labor market studies in the Middle East and North Africa (MENA). These two surveys have been used in numerous research endeavors including peer reviewed academic publications, dissertations, and international organization reports. As part of the same series of surveys, the Tunisia Labor Market Panel Survey (TLMPS) of 2014 is the first wave of what will eventually become a longitudinal survey of the Tunisian labor market. Being far richer than any currently available data, the TLMPS 2014 is a much-needed addition in a landscape of otherwise scarce publicly-accessible data on the Tunisian labor market. The TLMPS 2014 was collected in partnership between the Economic Research Forum (ERF) and the Tunisian National Institute of Statistics (INS).

    Similarly to its Egyptian and Jordanian counterparts, the TLMPS 2014 is a nationally representative survey that features detailed information on households and individuals, especially in regards to labor market characteristics. As in other countries in the MENA region, Tunisia suffers from high unemployment, particularly for university graduates, youth, and women, and from low female labor force participation.

    The survey allows for an in-depth investigation of current employment characteristics as well as analyses of broader labor market dynamics. For instance, analyses have already revealed the particularly long unemployment durations Tunisian youth experience, long even in comparison to other countries in the region.

    For more information, see the paper(s) cited in the "Citations" section: (Assaad, Ragui, Samir Ghazouani, Caroline Krafft, and Dominique J. Rolando, 2016).

    Geographic coverage

    The sample covered urban/rural areas of each of Tunisia's governorates

    Analysis unit

    1- Households. 2- Individuals.

    Universe

    The survey covered a national sample of households and all households members.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The initial sample frame included around 5,160 households drawn from a larger sample that is regularly used to conduct the quarterly survey on population and employment in Tunisia. This larger sample contained 18,000 households as of the last quarter of 2012. The drawing of the sample was done in two stages. In the first stage, 258 enumeration areas were randomly drawn according to the principle of probability proportional to size from the list of enumeration areas drawn up in the 2004 Census. This first sampling stage was carried out using 46 strata comprised of the urban/rural components of each of Tunisia's governorates. The final sample was made up of 253 clusters (out of a possible 40,377 nationally). In the second stage, 20 households were supposed to be drawn at random from each cluster. This procedure was, however, not strictly followed in the field.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The survey incorporates questionnaires to be administered at both the household and individual levels. At the household level, there was a general household questionnaire, as well as a questionnaire specifically about current migration, transfers, and agricultural and non-agricultural enterprises. At the individual level, there was a detailed questionnaire for working age individuals (15+) and an abbreviated version of the questionnaire for those 6-14 years old.

    The main household questionnaire and the migration/enterprise questionnaire were designed to be answered by the most knowledgeable individual in the household, usually the head or the spouse of the head. Along with information on the characteristics of the dwelling, access to public services, and ownership of durables, the household questionnaire includes a full household roster with information on basic demographic characteristics, such as age, sex, and relationship to the head of household. The migration/enterprise questionnaire includes information on any family members currently abroad, remittances, and other transfers, such as child support and pensions. Data were gathered on both non-agricultural and agricultural enterprises, including assets used and net revenues.

    The ELMPS and JLMPS had a single questionnaire for all individuals regardless of age. However, in Tunisia, a distinct questionnaire for individuals 6-14 was designed in order to more carefully incorporate measures of child labor. As very little child labor was detected even with this special design, in future LMPSs we plan to revert to a single questionnaire with a few additional questions targeted to children 6-14.

    The questionnaire includes a variety of modules on labor market experience and outcomes and related issues. On the labor market side, it elicits information on the current labor market status of the individual, detailed job characteristics (for the employed), wage earnings and non-wage benefits (for wage workers) and participation in domestic and subsistence work. Those who work were asked about both primary and secondary jobs (if any). The questionnaire also includes a detailed labor market history starting from the first labor market status after leaving school and moving forward towards the present for those who ever worked. Further, there is a detailed section on return migration for those who ever worked abroad.

    The labor market intersects with a number of other important life experiences, such as education, fertility, and marriage, which are also captured in the TLMPS individual questionnaire. For instance, there are modules on family background (parents and siblings), educational experiences, health, and residential mobility. For women, a section is devoted to fertility issues, the status of women in the household, and work-family issues such as child care and maternity leave. Data were also collected from both men and women on marriage and decisions around marriage, such as the incidence of kin marriage and living arrangements at marriage. Finally, there are modules on financial decision-making, with specific questions about savings and borrowing, as well as on the use of information technology.

    Response rate

    There were several different problems with non-response during the fielding. First, households often refused to respond entirely. Second, in completing the household survey, some individuals were not captured and some households refused or failed to answer the migration/enterprise questionnaire. In this section we discuss the patterns of non-response, which are incorporated into the weights, discussed below:

    1. Non-response of the entire household While the initial goal was to collect data from 5,160 households, time pressures reduced the intended sample to 4,986 households. Of the 4,986 households initially selected, interviews were completed with only 4,521, generating an overall household non-response rate of 9.3%. Additionally, because several clusters were found not to have the requisite twenty households at the end of the data collection stage, additional households were added to some clusters to improve the response rate, leading to wide variation in the number of the households per cluster. The minimum number of households interviewed in a cluster was 8 and the maximum was 34. The mean was 19.7, and the median was 20, with the interquartile range going from 17 to 22 households.

    After this additional work to add households to the sample, non-response rates at a cluster level ranged from 0% (complete response), which occurred for 29% of clusters, to a maximum of 62.5%. The mean non-response at the cluster level was 10.2%, the median was 6.7%, the 75th percentile was 13.3%, and the 90th percentile was 24.8%. This household non-response is incorporated in the weights at a cluster level, with the households that did respond within a cluster representing those that did not.

    1. Non-response to child, adult, and migration/enterprise questionnaires As well as problems with non-response on the household level, there were problems with completing the child, adult, and migration/enterprise questionnaires. We developed weights to account for non-response to each of these questionnaires in their entirety. However, individuals often stopped answering partway through a questionnaire, suffered from incorrect skips, or other data problems, such that data is sometimes missing for a particular question within a questionnaire that contains some data. Additional data imputation techniques, implemented on a question-by-question basis, are required for these problems.
  9. International Social Survey Programme: National Identity I-III - ISSP...

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    Updated May 20, 2023
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    Kelley, Jonathan; Evans, Mariah; Gibson, Rachel K.; Haller, Max; Hoellinger, Franz; Hadler, Markus; Dimova, Lilia; Tilkidjiev, Nikolay; Pyman, Heather; Pammett, Jon H.; Fu, Yang-chih; Kostelecky, Tomáš; Mateju, Petr; Plecitá, Klára; Lund Clement, Sanne; Andersen, Johannes; Shamshiri-Petersen, Ditte; Andersen, Jørgen G.; Andersen, Morten H.; Lolle, Henrik; Larsen, Christian A.; Tobiasen, Mette; Tanskanen, Eero; Borg, Sami; Blom, Raimo; Melin, Harri; Lemel, Yannick; Bréchon, Pierre; Cautres, Bruno; Chauvel, Louis; Degenne, Alain; Gonthier, Frédéric; Forsé, Michel; TÁRKI, Budapest; Örkény, Antal; Kolosi, Tamás; Phadraig, Máire N. G.; Ward, Conor; Caithness, Philippa; Watson, Iarfhlaith; Aramaki, Hiroshi; Kobayashi, Toshiyuki; Murata, Hiroko; Seok, Hyunho; Kim, Sang-Wook; Tabuns, Aivars; Tabuna, Ausma; Zepa, Brigita; Becker, Jos; Ganzeboom, Harry B.G.; Gendall, Philip; Aagedal, Olaf; Knutsen, Oddbjorn; Skjak, Knut K.; Research Council of Norway; Kolsrud, Kirstine; Mangahas, Mahar; Cichomski, Bogdan; Villaverde Cabral, Manuel; Vala, Jorge; Ramos, Alice; Khakhulina, Ludmilla; Piscova, Magdalena; Bahna, Miloslav; Toš, Niko; Hafner-Fink, Mitja; Malnar, Brina; Rule, Stephen; Struwig, Jare; , Madrid; García-Pardo, Natalia; Díez-Nicolás, Juan; Svallfors, Stefan; Edlund, Jonas; , Neuchâtel; FORS swiss foundation for research in social sciences; Davis, James A.; Smith, Tom W.; Marsden, Peter V.; Hout, Michael; Harkness, Janet; Mohler, Peter Ph.; Scholz, Evi; Klein, Sabine; Wolf, Christof; Lewin-Epstein, Noah; Yuchtman-Yaar, Eppie; Jowell, Roger; Brook, Lindsay; Thomson, Katarina; Bryson, Caroline; Park, Alison; Jowell, Roger; Clery, Liz (2023). International Social Survey Programme: National Identity I-III - ISSP 1995-2003-2013 [Dataset]. http://doi.org/10.4232/1.13471
    Explore at:
    Dataset updated
    May 20, 2023
    Dataset provided by
    Finnish Social Science Data Archive
    TARKI Social Research Institute
    Institute of Sociology, Academy of Sciences of the Czech Republic, Prague, Czech Republic
    University of Tampere, Finland
    CIS (Centro de Investigaciones Sociológicas), Madrid, Spain
    SCP - Sociaal en Cultureel Planbureau, Netherlands
    Department of Sociology, Sungkyunkwan University, Seoul, Korea
    SCPR, London, Great Britain
    Diaconia College Centre, Oslo, Norway
    France-ISSP, France
    Harvard University, Cambridge, USA
    NHK Broadcasting Culture Research Institute, Tokyo, Japan
    Massey University, Palmerston North, New Zealand
    B.I. and Lucille Cohen, Institute for public opionion research, Tel Aviv, Israel
    Social Weather Stations, Quezon City, Philippines
    Spain
    Australia
    Dept. of Sociology and Anthropology, Tel Aviv University, Tel Aviv, Israel
    Human Sciences Research Council, Pretoria, South Africa
    Survey Research Center, Sungyunkwan University, Seoul, Korea
    Institut für Soziologie, Karl-Franzens-Universität Graz, Austria
    National Opinion Research Center (NORC), Chicago, USA
    Carleton University Survey Centre, Carleton University, Ottawa, Canada
    Instituto de Ciências Sociais da Universidade de Lisbon, Lisbon, Portugal
    ELTE University Budapest, Budapest, Hungary
    Latvia
    c
    Department of Political Science, Aalborg University, Denmark
    Levada-Center, Moscow, Russia
    Department of Economics, Politics and Public Administration, Aalborg University, Denmark
    SSRC (Social Science Research Centre), University College Dublin, Dublin, Ireland
    ISS (Institut for Social Studies), Warsaw University, Poland
    National Centre for Social Research (NatCen), London, Great Britain
    ZUMA, Mannheim, Germany
    Institute of Sociology, Academy of Sciences of the Czech Republic, Praha, Czech Republic
    University College Dublin, Ireland
    Department of Sociology, Umeå University, Umeå, Sweden
    New York University, New York, USA
    Human Science Research Council, Pretoria, South Africa
    LASMAS (Laboratoire d´Analyse Secondaire et de Méthodes Appliquées en Sociologie), Paris, France
    Institute for Sociology, Slovak Academy of Sciences, Bratislava, Slovakia
    Survey Research Unit, Statistics Finland, Finland
    Switzerland
    GESIS Leibnitz-Institut für Sozialwissenschaften, Mannheim, Germany
    ASEP (Análisis Sociológicos Económicos y Políticos), Madrid, Spain
    ACSPRI Centre for Social Research (ACSR) Research School of Social Sciences Canberra, The Australian National University, Australia
    CIDSP (Centre d´Infomatisation des Données Socio-Politiques) Institut d´Études Politiques de Grenoble, Domaine Universitaire, St. Martin D´Heres, France
    Social Science Research Center UCD and Economic and Social Research Institute (ESRI), Ireland
    Free University Amsterdam, Amsterdam, The Netherlands
    Norwegian Social Science Data Services (NSD), Bergen, Norway
    Department of Political Science, University of Oslo, Norway
    Public Opinion and Mass Communication Research Centre (CJMMK), University of Ljubljana, Slovenia
    Norway
    France-ISSP Association (Centre de Rechere en Économie et Statistique) Laboratorie de Sociologie Quantitative, Malkoff, France
    Institute of Philosophy and Sociology, University of Latvia, Riga, Latvia
    Hungary
    OFCE (Observatorie Français des Conjonctures Économiques), Paris, France
    Agency for Social Analyses (ASA), Sofia, Bulgaria
    Institute of Sociology, Academia Sinica, Nankang, Taipei, Taiwan
    Institute for Sociology, Slovak Academy of Science, Bratislava, Slovakia
    Authors
    Kelley, Jonathan; Evans, Mariah; Gibson, Rachel K.; Haller, Max; Hoellinger, Franz; Hadler, Markus; Dimova, Lilia; Tilkidjiev, Nikolay; Pyman, Heather; Pammett, Jon H.; Fu, Yang-chih; Kostelecky, Tomáš; Mateju, Petr; Plecitá, Klára; Lund Clement, Sanne; Andersen, Johannes; Shamshiri-Petersen, Ditte; Andersen, Jørgen G.; Andersen, Morten H.; Lolle, Henrik; Larsen, Christian A.; Tobiasen, Mette; Tanskanen, Eero; Borg, Sami; Blom, Raimo; Melin, Harri; Lemel, Yannick; Bréchon, Pierre; Cautres, Bruno; Chauvel, Louis; Degenne, Alain; Gonthier, Frédéric; Forsé, Michel; TÁRKI, Budapest; Örkény, Antal; Kolosi, Tamás; Phadraig, Máire N. G.; Ward, Conor; Caithness, Philippa; Watson, Iarfhlaith; Aramaki, Hiroshi; Kobayashi, Toshiyuki; Murata, Hiroko; Seok, Hyunho; Kim, Sang-Wook; Tabuns, Aivars; Tabuna, Ausma; Zepa, Brigita; Becker, Jos; Ganzeboom, Harry B.G.; Gendall, Philip; Aagedal, Olaf; Knutsen, Oddbjorn; Skjak, Knut K.; Research Council of Norway; Kolsrud, Kirstine; Mangahas, Mahar; Cichomski, Bogdan; Villaverde Cabral, Manuel; Vala, Jorge; Ramos, Alice; Khakhulina, Ludmilla; Piscova, Magdalena; Bahna, Miloslav; Toš, Niko; Hafner-Fink, Mitja; Malnar, Brina; Rule, Stephen; Struwig, Jare; , Madrid; García-Pardo, Natalia; Díez-Nicolás, Juan; Svallfors, Stefan; Edlund, Jonas; , Neuchâtel; FORS swiss foundation for research in social sciences; Davis, James A.; Smith, Tom W.; Marsden, Peter V.; Hout, Michael; Harkness, Janet; Mohler, Peter Ph.; Scholz, Evi; Klein, Sabine; Wolf, Christof; Lewin-Epstein, Noah; Yuchtman-Yaar, Eppie; Jowell, Roger; Brook, Lindsay; Thomson, Katarina; Bryson, Caroline; Park, Alison; Jowell, Roger; Clery, Liz
    Time period covered
    Nov 1994 - Mar 20, 2015
    Area covered
    Australia, Slovenia, Finland, France, Japan, Taiwan, Republic of, South Africa, New Zealand, United States of America
    Measurement technique
    Face-to-face interview: Computer-assisted (CAPI/CAMI), Face-to-face interview: Paper-and-pencil (PAPI), Telephone interview: Computer-assisted (CATI), Self-administered questionnaire: Paper, Self-administered questionnaire: Web-based (CAWI), Self-administered questionnaire: Computer-assisted (CASI)
    Description

    The International Social Survey Programme (ISSP) is a continuous programme of cross-national collaboration running annual surveys on topics important for the social sciences. The programme started in 1984 with four founding members - Australia, Germany, Great Britain, and the United States – and has now grown to almost 50 member countries from all over the world. As the surveys are designed for replication, they can be used for both, cross-national and cross-time comparisons. Each ISSP module focuses on a specific topic, which is repeated in regular time intervals. Please, consult the documentation for details on how the national ISSP surveys are fielded. The present study focuses on questions about national consciousness and national identity.
    The release of the cumulated ISSP ´National Identity´ modules for the years 1995, 2003 and 2013 consists of two separate datasets: ZA5960 and ZA5961. This documentation deals with the main dataset ZA5960. It contains all the cumulated variables, while the supplementary data file ZA5961 contains those variables that could not be cumulated for various reasons. However, they can be matched easily to the cumulated file if necessary. A comprehensive overview on the contents, the structure and basic coding rules of both data files can be found in the following guide:

    Guide for the ISSP ´National Identity´ cumulation of the years 1995, 2003, and 2013

    National Identity I-III:

    Identification with the town/ the city, the region (county), the country, and with the respective continent; important characteristics for national identity (to be born in the country, to have citizenship of the country, living most time of life in the country, to be able to speak country language, to be a (dominant religion in the country, to respect (country nationality) politicial institutions and laws, to feel country nationality, to have country nationality ancestry); agreement with different statements (I would rather be a citizen of (country) than of any other country in the world, things about country feel ashamed, the world would be a better place if people were more like the (country nationality), (country) is a better country than most other countries, people should support their country even if the country is in the wrong, when my country does well in international sports, it makes me proud to be (country nationality), often less proud of (country) than I would like to be); proud of: the way democracy works in the country, its political influence in the world, the country´s economic achievements, its social security system, its scientific and technological achievements, its achievements in sports, the achievements in the arts and literature, country´s armed forces, its history, and fair treatment of all groups in society; attitude towards the relations between one´s country and other countries (country should limit the import of foreign products in order to protect the national economy, international bodies should enforce solutions for certain problems like environment pollution, enforcing national interests regardless of evoking conflicts with other countries, rejection of the acquisition of land by foreigners, television should prefer national films and programs); large international companies damage local businesses; free trade leads to better products in the country; country should follow decisions of international organisations; international organisations are taking too much power from the government; attitude towards minorities in respondent´s country (without shared customs no full membership, ethnic minorities should be given government assistance to preserve their customs and traditions, better for a society if groups maintain their traditions vs. adapt in the larger society); attitude towards immigrants (immigrants increase crime rates, immigrants are generally good for country´s economy, immigrants take jobs away from people who were born in the country, immigrants bring new ideas and cultures, legal immigrants should have same rights as (country nationality) citizens, illegal immigrants should be excluded); attitude towards the number of immigrants in the country; national pride; respondents citizenship; citizenship of parents at the time of the respondent´s birth; attitutde towards the European Union (appropriate association for the continent/ subcontinent): how much heard or read about the European Union; country benefits from being member of the European Union; country should follow decisions of the European Union; EU should have more power than national government; decision at EU Referendum to become new member of the EU (for prospective members only); decision at EU Referendum to remain member of the EU; country should remain one nation vs. parts of the country should be allowed to become fully separate nations if they choose to; self-assessed affiliation of ethnic group.

    Demography: sex; age; education: years of schooling; highest completed education level...

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Dung Doan (2025). Pacific Labor Mobility Survey 2021-2023 - Australia, Kiribati, New Zealand...and 2 more [Dataset]. https://microdata.worldbank.org/index.php/catalog/6420

Pacific Labor Mobility Survey 2021-2023 - Australia, Kiribati, New Zealand...and 2 more

Explore at:
Dataset updated
Jan 9, 2025
Dataset provided by
Ryan Edwards
Matthew Dornan
Dung Doan
Time period covered
2021 - 2023
Area covered
Kiribati, New Zealand, Australia
Description

Abstract

Previous surveys on labor migration from Pacific Island countries are often cross-sectional, not readily available, and focusing on one migration scheme, country, or issue and hence incompatible. Such limitation of existing data restricts analysis of a range of policy-relevant issues that present themselves over the migrants' life cycle such as those on migration pathways, long-term changes in household livelihood, and trajectory of migrants’ labor market outcomes, despite the significant impacts of labor migration on the economy of the Pacific Island countries. To address these shortfalls in the Pacific migration data landscape, the PLMS is designed to be longitudinal, spanning multiple labor sending and receiving countries and collecting omnibus information on both migrants, their households and non-migrant households. The survey allows for disaggregation and reliable comparative analysis both within and across countries and labor mobility schemes. This open-access and high-quality data will facilitate more research about the Pacific migration, help inform and improve Pacific migration policy deliberations, and engender broader positive change in the Pacific data ecosystem.

Geographic coverage

Tonga: Tongatapu, ‘Eua, Vava’u, Ha’apai, Ongo Niua. Vanuatu: Malampa, Penama, Sanma, Shefa, Tafea, Torba. Kiribati: Abaiang, Abemama, Aranuka, Arorae, Banaba, Beru, Butaritari, Kiritimati, Maiana, Makin, Marakei, Nikunau, Nonouti, North Tabiteuea, North Tarawa, Onotoa, South Tabiteuea, South Tarawa, Tabuaeran, Tamana, Teraina.

Analysis unit

  • Households in Kiribati, Tonga, and Vanuatu.
  • Temporary migrant workers from Kiribati, Tonga and Vanuatu who participated in the Pacific Australia Labour Mobility scheme in Australia and the Recognised Seasonal Employers scheme in New Zealand

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling frame: The PLMS sample was designed based on a Total Survey Error framework, seeking to minimize errors and bias at every stage of the process throughout preparation and implementation.

The worker sample frame is an extensive list of approximately 11,600 migrant workers from Kiribati, Tonga and Vanuatu who had participated in the RSE and PALM schemes. Due to the different modes of interviews, sampling strategies for the face-to-face segment of the household survey in Tonga was different from the rest of the surveys implemented via phone interviews. The face-to-face segment of the household survey selected households using Probability Proportional to Size sampling based on the latest population census listing and our worker sample frame, with technical inputs from the Tonga Statistics Department. The phone-based segment of the household survey used a combination of Probability Proportional to Size sampling based on the existing sample frame and random digit dialing. The design of the sample benefited from technical inputs from the Tonga Statistics Departments and the Vanuatu National Statistics Office, as well as World Bank staff from Kiribati.

As participation in the survey is voluntary, a worker might agree to participate while their household did not, and vice versa. Because of this, the survey did not achieve a complete one-to-one match between interviewed workers and sending households. Of all interviewed respondents, 418 workers in the worker survey are linked to their households in the household survey. However, after removing incomplete interviews, 341 worker-household pairs remain. They are matched by either pre-assigned serial ID numbers or contact details collected in the household and worker surveys during the post-fieldwork data cleaning process.

Sampling deviation

The survey was originally planned to be conducted face-to-face and was so for most of the collection of household data in Tonga. However, due to COVID-19, it was switched to phone-based mode and the survey instruments were adjusted accordingly to better suit the phone-based data collection while ensuring data quality. In particular, the household questionnaire was shortened, and sampling strategy changed to a combination of Probability Proportional to Size sampling based on the existing household listing and random digit dialing.

Compared to in-person data collection, the usual caveats of potential biases in phone-based survey related to disproportional phone ownership and connectivity apply here. The random digit dialing approach provides data representative of the phone-owning population. Yet due to lack of information, it is difficult to judge whether sending households in Kiribati, Tonga, and Vanuatu are more or less likely to own a phone and/or respond positively to survey request than non-sending households.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

  • The questionnaires were jointly designed in English by the World Bank and researchers at the Development Policy Centre, Australian National University. They were translated into Bislama, Gilbertese and Tongan, scripted into CAPI/CATI programs, tested and piloted before being finalized. The design of the questionnaires and the samples benefited from technical inputs from the Tonga Statistics Departments, Pacific consultants, and academic experts specialized in Pacific labor mobility and remittances.
  • Enumerators are native speakers from the labor-sending countries covered in the survey and were trained to elicit information asked in the questionnaire in local languages.
  • The phone-based household questionnaire is moderately shorter than the in-person version.

Cleaning operations

The published data have been cleaned and anonymized. All incomplete interview records have been removed from the final datasets. The anonymization process followed the theory of Statistical Disclosure Control for microdata, aiming to minimize re-identification risk, i.e. the risk that the identity of an individual (or a household) described by a specific record could be determined with a high level of confidence. The anonymization process employs the k-anonymity method to calculate the re-identification risk. Risk measurement, anonymization and utility measurement for the PLMS were done using sdcMicro, an add-on package for the statistical software R for Statistical Disclosure Control (SDC) of microdata.

Since the household questionnaire was shortened when the survey switched from face-to-face to phone-based data collection, there face-to-face datasets and phone-based datasets are not identical, but they are consistent and can be harmonized. The mapping guide enclosed in this publication provides a guide to data users to wish to harmonize them.

Household expenditure variables in the household dataset and individual wage variable in the household member dataset are in USD. Local currencies were converted into USD based on the following exchange rates: 1 Tongan Pa'anga= 0.42201412 USD; 1 Vanuatu Vatu= 0.0083905322 USD; 1 Kiribati dollar= 0.66942499 USD.

Response rate

Face-to-face segment of the PLMS household survey: not applicable. Phone-based segment of the PLMS household survey: 26%. The PLMS Worker survey: 31%

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