WageIndicator Survey

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WageIndicator Foundation, 2023, "WageIndicator Survey", https://doi.org/10.15185/wif.1, Research Data Center of IZA (IDSC), V2

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Description	The WageIndicator Survey is a continuous, multilingual, multi-country web-survey, counducted across 65 countries since 2000. The web-survey generates cross sectional and longitudinal data which might provide data especially about wages, benefits, working hours, working conditions and industrial relations. The survey has detailed questions about earnings, benefits, working conditions, employment contracts and training, as well as questions about education, occupation, industry and household characteristics. The WageIndicator Survey is a multilingual questionnaire and aims to collect information on wages and working conditions. As labour markets and wage setting processes vary across countries, country specific translations have been favoured over literal translations. The WageIndicator Survey includes regularly extra survey questions for project targeting specific countries, for specific groups or about specific events. These projects usually address a specific audience (employees of a company, employees in an industry, readers of a magazine, members of a trade union or an occupational association, and alike). The data of the project questions are included in the dataset. Bias: Non-Probability web based surveys are problematic because not every individual has the same probability of being selected into the survey. The probability of being selected depends on national or regional internet access rates and on numbers of visitors accessing the webiste. Data of such surveys form a convenience rather than a probability sample. Due to the non-probability based nature of the survey and its selectivity the obtained results cannot be generalized for the population of interest; i.e. the labor force. Comparisons with representative studies found an underrepresentation of male labour force, part-timers, older age groups, and low educated persons. Besides other strategies to reduce the bias the WageIndicators provides different weighting schemes in order to correct for selection bias. Data Characteristics: The data is organised in annual releases. The data of the period 2000-2005 is released as one dataset. Each data release consists of a dataset with continuous variables and one with project variables. The continuous variables can be merged across years. All variable and value labels are in English. The data does not include the text variables and verbatims form open-ended survey questions, these are available in Excel-Format upon request. Spatial Coverage: The survey started in 2000 in the Netherlands. Since 2004, websites have been launched in many European countries, in North and South America and in countries in Asia. From 2008 on web sites have been launched in more African countries, as well as in Indonesia and in a number of post-Soviet countries. For each country, the questions have been translated. Multilingual countries employ multilingual questionnaires. Country-specific translations and locally accepted terminology have been favored over literal translations.
Subject	Social Sciences
Keyword	Benefits, Earnings, Employment Contracts, Housing, Income, Job Characteristics, Industrial Relations, Labor Markets, Wages, Working Hours
Related Publication	Bennell, P. (2023). How well paid are primary school teachers in Sub-Saharan Africa? A review of recent evidence. International Journal of Educational Development, 98, 102755.
License/Data Use Agreement	IIL-1.0

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	Documentation.zip ZIP Archive - 3.9 MB Published Nov 9, 2023 32 Downloads MD5: b9e6001a7dd0ef280b47015c524e84ea The documentation contains all essential data necessary for the successful replication or execution of individual research projects. Documentation	Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX

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Persistent Identifier	doi:10.15185/wif.1
Publication Date	2023-11-09
Title	WageIndicator Survey
Author	WageIndicator Foundation
Point of Contact	Use email button above to contact. Research Data Center of IZA (IDSC)
Description	The WageIndicator Survey is a continuous, multilingual, multi-country web-survey, counducted across 65 countries since 2000. The web-survey generates cross sectional and longitudinal data which might provide data especially about wages, benefits, working hours, working conditions and industrial relations. The survey has detailed questions about earnings, benefits, working conditions, employment contracts and training, as well as questions about education, occupation, industry and household characteristics. The WageIndicator Survey is a multilingual questionnaire and aims to collect information on wages and working conditions. As labour markets and wage setting processes vary across countries, country specific translations have been favoured over literal translations. The WageIndicator Survey includes regularly extra survey questions for project targeting specific countries, for specific groups or about specific events. These projects usually address a specific audience (employees of a company, employees in an industry, readers of a magazine, members of a trade union or an occupational association, and alike). The data of the project questions are included in the dataset. Bias: Non-Probability web based surveys are problematic because not every individual has the same probability of being selected into the survey. The probability of being selected depends on national or regional internet access rates and on numbers of visitors accessing the webiste. Data of such surveys form a convenience rather than a probability sample. Due to the non-probability based nature of the survey and its selectivity the obtained results cannot be generalized for the population of interest; i.e. the labor force. Comparisons with representative studies found an underrepresentation of male labour force, part-timers, older age groups, and low educated persons. Besides other strategies to reduce the bias the WageIndicators provides different weighting schemes in order to correct for selection bias. Data Characteristics: The data is organised in annual releases. The data of the period 2000-2005 is released as one dataset. Each data release consists of a dataset with continuous variables and one with project variables. The continuous variables can be merged across years. All variable and value labels are in English. The data does not include the text variables and verbatims form open-ended survey questions, these are available in Excel-Format upon request. Spatial Coverage: The survey started in 2000 in the Netherlands. Since 2004, websites have been launched in many European countries, in North and South America and in countries in Asia. From 2008 on web sites have been launched in more African countries, as well as in Indonesia and in a number of post-Soviet countries. For each country, the questions have been translated. Multilingual countries employ multilingual questionnaires. Country-specific translations and locally accepted terminology have been favored over literal translations.
Subject	Social Sciences
Keyword	Benefits Earnings Employment Contracts Housing Income Job Characteristics Industrial Relations Labor Markets Wages Working Hours
Related Publication	Bennell, P. (2023). How well paid are primary school teachers in Sub-Saharan Africa? A review of recent evidence. International Journal of Educational Development, 98, 102755. url: https://www.sciencedirect.com/science/article/pii/S0738059323000329 Ahmad, I. (2023) Kuwait Decent Work Check 2023. Amsterdam, WageIndicator Foundation, July. url: https://wageindicator.org/documents/decentworkcheck/gulf-middle-east/kuwait-arabic.pdf Lakemann, T. (2023). How Vulnerable are the Self-Employed? Evidence from Ugandan Small-Scale Entrepreneurs. The Journal of Development Studies, 1-18. url: https://www.tandfonline.com/doi/full/10.1080/00220388.2023.2217996 Tijdens, K., van Klaveren, M., Adib, A., Ceccon, D., & Chowdhury, T. T. (2023). COVID-19, absence from work and coping strategies with income loss in Bangladesh. Journal of Social and Economic Development, 1-22. url: https://link.springer.com/article/10.1007/s40847-023-00255-y Tijdens, K., Besamusca, J., & van Klaveren, M. (2023). Workers and Labour Market Outcomes of Informal Jobs in Formal Establishments: A Job-Based Informality Jobs job-based informality Index for Nine Sub-Saharan African Countries. In Global Labour in Distress, Volume II: Earnings,(In) decent Work and Institutions (pp. 287-314). Cham: Springer International Publishing. url: https://link.springer.com/chapter/10.1007/978-3-030-89265-4_13 Oakes, M., & Ji, M. (2022). Introduction: Quantitative methods in health, environmental, and theoretical translation research. Meta, 67(1), 5-17. url: https://doi.org/10.7202/1092188ar Yoon, Y., & Sengupta, S. (2022). Can cutting pay be an alternative to cutting people when maintaining work attitudes is a concern? It can be if employees trust you. Journal of General Management, 0(0). url: https://doi.org/10.1177/03063070221091227 Zavala-Rojas, D., Sorato, D., Hareide, L. & Hofland, K. (2022). The Multilingual Corpus of Survey Questionnaires: A tool for refining survey translation. Meta, 67(1), 71–93. url: https://doi.org/10.7202/1092191ar Ahmad, A. H., Llewellyn, D. T. & Murinde, V. (2021). Inclusive Financial Development. Edward Elgar Publishing. url: https://play.google.com/store/books/details?id=j5dKEAAAQBAJ&rdid=book-j5dKEAAAQBAJ&rdot=1&source=gbs_atb&pcampaignid=books_booksearch_atb Dingeldey, I. Grimshaw,D. & Schulten, T. (Eds.) (2021). Minimum Wage Regimes: Statutory Regulation, Collective Bargaining and Adequate Levels. Routledge Research in Comparative Politics. Routledge. url: https://play.google.com/store/books/details?id=evcrEAAAQBAJ&rdid=book-evcrEAAAQBAJ&rdot=1&source=gbs_atb&pcampaignid=books_booksearch_atb Lenaerts, K., Ramioul, M., Nelson, K., Steinmetz, S., Esteve, A., Gábos, A., György Tóth, I., Besamusca, J., Articus, C., Münnich, R., & Shlomo, N. (2021). Potential pathways for the future development and sustainability of the InGRID research infrastructure, Deliverable 7.9, Leuven, InGRID-2 project 730998 – H2020. url: https://www.inclusivegrowth.eu/files/Output/D7.9-Roadmap.pdf Tijdens, K., Besamusca, J., & van Klaveren, M. (2023). Workers and Labour Market Outcomes of Informal Jobs in Formal Establishments: A Job-Based Informality Jobs job-based informality Index for Nine Sub-Saharan African Countries. In Global Labour in Distress, Volume II: Earnings,(In) decent Work and Institutions (pp. 287-314). Cham: Springer International Publishing. url: https://link.springer.com/chapter/10.1007/978-3-030-89265-4_13 Bennell, P. (2023). How well paid are primary school teachers in Sub-Saharan Africa? A review of recent evidence. International Journal of Educational Development, 98, 102755. url: https://www.sciencedirect.com/science/article/pii/S0738059323000329 Tijdens, K., van Klaveren, M., Adib, A., Ceccon, D., & Chowdhury, T. T. (2023). COVID-19, absence from work and coping strategies with income loss in Bangladesh. Journal of Social and Economic Development, 1-22. url: https://link.springer.com/article/10.1007/s40847-023-00255-y Ahmad, I. (2023) Kuwait Decent Work Check 2023. Amsterdam, WageIndicator Foundation, July. url: https://wageindicator.org/documents/decentworkcheck/gulf-middle-east/kuwait-arabic.pdf Shevchenko, Y., Huber, N., & Reips, U. D. (2023). Psychological well-being during the COVID-19 pandemic: Combining a web survey with experience sampling methodology. Plos one, 18(3), e0282649. url: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0282649 Peycheva, D.N., Sakshaug, J.W. & Calderwood, L. (2021). Occupation Coding during the Interview in a Web-First Sequential Mixed-Mode Survey. Journal of Official Statistics , 37 (4) pp. 981-1007. https://dx.doi.org/10.2478/jos-2021-0042 url: https://discovery.ucl.ac.uk/id/eprint/10142716/ Smyk, M., Tyrowicz, J., & Van der Velde, L. (2021). A cautionary note on the reliability of the online survey data: the case of wage indicator. Sociological Methods & Research, 50(1), 429-464. url: https://doi.org/10.1177/0049124118782538 Andreadis, I., & Kartsounidou, E. (2020). The Impact of Splitting a Long Online Questionnaire on Data Quality. Survey Research Methods, 14(1), 31-42. url: https://doi.org/10.18148/srm/2020.v14i1.7294 Baiocco, S., Kilhoffer, Z., & Niang, Mouhamadou M. (2020). The Measurement of Skills Needs, Skills Transferability and Skills Imbalances with Data from International Surveys,Web Sources and Web-Based Surveys. Ingrid deliverable 12.1. url: http://www.inclusivegrowth.eu/files/Output/D12.1-Measuring-skills.pdf Biavaschi, C., Burzyński, M., Elsner, B., & Machado, J. (2020). Taking the skill bias out of global migration. Journal of Development Economics, 142, 102317. url: https://doi.org/10.1016/j.jdeveco.2018.12.006 de Pedraza, P., Guzi, M. & Tijdens, K. (2020). Life satisfaction of employees, labour market tightness and matching efficiency. International Journal of Manpower, Vol. ahead-of-print No. ahead-of-print. url: https://doi.org/10.1108/IJM-07-2019-0323 Fabo, B., & Kahanec, M. (2020). The role of computer skills on the occupation level. European Journal of Business Science and Technology, 87. url: http://journal.ejobsat.cz/contents/ejo/2020/02.pdf#page=6 Fabo, B. (2020). The English and Russian Language Proficiency Premium in the post-Maidan Ukraine–an Analysis of Web Survey Data. CELSI Discussion Paper No. 57. url: https://www.celsi.sk/media/discussion_papers/DP57_CAgXQ8w.pdf Smith, T. W. (2020). Optimizing Questionnaire Design in Cross‐National and Cross‐Cultural Surveys. Advances in Questionnaire Design, Development, Evaluation and Testing, 471-492. url: https://doi.org/10.1002/9781119263685.ch19 van Klaveren, M., & Tijdens, K. (2020). Social aspects of multinationals in the Netherlands. University of Amsterdam. url: https://wageindicator.org/documents/publicationslist/publications-2020/2020-wi-paper-mnes-in-nl-1.pdf Vontroba, J., Balcar, J., & Šimek, M. (2020). Commuting pays off: Evidence on wage returns to inter-urban and intra-urban commuting. Moravian Geographical Reports, 28(2) 112, 28(2): 112–123 url: https://doi.org/10.2478/mgr-2020-0009 de Coning, J. A., Rothmann, S., & Stander, M. W. (2019). Do wage and wage satisfaction compensate for the effects of a dissatisfying job on life satisfaction?. SA Journal of Industrial Psychology, 45(1), 1-11. url: http://dx.doi.org/10.4102/sajip.v45i0.1552 de Pedraza, P., Visintin, S., Tijdens, K., & Kismihók, G. (2019). Survey vs scraped data: comparing time series properties of web and survey vacancy data. IZA Journal of Labor Economics, 8(1), 20190004. url: https://doi.org/10.2478/izajole-2019-0004 Shannon, G., Jansen, M., Williams, K., Cáceres, C., Motta, A., Odhiambo, A., ... & Mannell, J. (2019). Gender equality in science, medicine, and global health: where are we at and why does it matter?. The Lancet, 393(10171), 560-569. url: https://doi.org/10.1016/S0140-6736(18)33135-0 Chala, S. A., Ansari, F., Fathi, M., & Tijdens, K. (2018). Semantic matching of job seeker to vacancy: a bidirectional approach. International Journal of Manpower. url: https://doi.org/10.1108/IJM-10-2018-0331 Fabo, B., & Kahanec, M. (2018). Can a voluntary web survey be useful beyond explorative research?. International Journal of Social Research Methodology, 21(5), 591-601. url: https://doi.org/10.1080/13645579.2018.1454639 Tijdens, K., De Vries, D. H., & Steinmetz, S. (2013). Health workforce remuneration: comparing wage levels, ranking, and dispersion of 16 occupational groups in 20 countries. Human resources for health, 11(1), 11. url: https://doi.org/10.1186/1478-4491-11-11 Fabo, B., Beblavý, M., & Lenaerts, K. (2017). The importance of foreign language skills in the labour markets of Central and Eastern Europe: assessment based on data from online job portals. Empirica, 44(3), 487-508. url: https://link.springer.com/article/10.1007/s10663-017-9374-6 de Vries, D. H., Steinmetz, S., & Tijdens, K. G. (2016). Does migration ‘pay off’for foreign-born migrant health workers? An exploratory analysis using the global WageIndicator dataset. Human resources for health, 14(1), 40. url: https://link.springer.com/article/10.1186/s12960-016-0136-5 Tijdens, K., & Steinmetz, S. (2016). Is the web a promising tool for data collection in developing countries? An analysis of the sample bias of 10 web and face-to-face surveys from Africa, Asia, and South America. International Journal of Social Research Methodology, 19(4), 461-479. url: https://www.tandfonline.com/doi/abs/10.1080/13645579.2015.1035875 Askitas, N., Zimmermann, K. F., Guzi, M., & de Pedraza García, P. (2015). A web survey analysis of subjective well-being. International Journal of Manpower. url: https://www.emerald.com/insight/content/doi/10.1108/IJM-12-2014-0237/full/html Kureková, L. M., Beblavý, M., & Thum-Thysen, A. (2015). Using online vacancies and web surveys to analyse the labour market: a methodological inquiry. IZA Journal of Labor Economics, 4(1), 18. url: https://link.springer.com/article/10.1186/s40172-015-0034-4 Tijdens, K. (2015). Self-identification of occupation in web surveys: requirements for search trees and look-up tables. Survey Methods: Insights from the Field, 11. url: https://nbn-resolving.org/urn:nbn:de:0168-ssoar-440543 Visintin, S., Tijdens, K., & van Klaveren, M. (2015). Skill mismatch among migrant workers: evidence from a large multi-country dataset. IZA Journal of Migration, 4(1), 14. url: https://link.springer.com/article/10.1186/s40176-015-0040-0 Steinmetz, S., de Vries, D. H., & Tijdens, K. G. (2014). Should I stay or should I go? The impact of working time and wages on retention in the health workforce. Human resources for health, 12(1), 23. url: https://link.springer.com/article/10.1186/1478-4491-12-23 Tijdens, K. (2014). Dropout rates and response times of an occupation search tree in a web survey. Journal of Official Statistics, 30(1), 23-43. url: https://doi.org/10.2478/jos-2014-0002 Steinmetz, S., Lars, K., De Pedraza, P., Reips, U. D., Tijdens, K., Lozar Manfreda, K., & Bernardo, W. (2012). WEBDATANET: a Network on Web-based Data Collection, Methodological Challenges, Solutions, and Implementation. International Journal of Internet Science, 7(1), 78-89. url: http://nbn-resolving.de/urn:nbn:de:bsz:352-286531 Tijdens, K. G., De Ruijter, J., & De Ruijter, E. (2012). Measuring work activities and skill requirements of occupations. European Journal of Training and Development. url: https://www.emerald.com/insight/content/doi/10.1108/03090591211255575/full/html Garzarelli, G., Keeton, L., Schoer, V., & Sitoe, A. (2011). Workers’ Compensation, minimum wages and moral hazard scope: stylized considerations on a South African case. Occupational Health Southern Africa, 17(6), 34-39. url: https://www.researchgate.net/profile/Lyndal_Keeton/publication/312839720_Workers'_compensation_minimum_wages_and_moral_hazard_scope_stylized_considerations_on_a_South_African_case/links/58888590a6fdcc6b79205b06/Workers-compensation-minimum-wages-and-moral-hazard-scope-stylized-considerations-on-a-South-African-case.pdf Williams, C. C., & Gurtoo, A. (2011). Evaluating women entrepreneurs in the informal sector: some evidence from India. Journal of Developmental Entrepreneurship, 16(03), 351-369. url: https://doi.org/10.1142/S1084946711001914 Athanasou, J. A. (2010). Decent work and its implications for careers. Australian Journal of Career Development, 19(1), 36-44. url: http://journals.sagepub.com/doi/abs/10.1177/103841621001900108 de Pedraza, P., Tijdens, K., de Bustillo, R. M., & Steinmetz, S. (2010). A Spanish continuous volunteer web survey: sample bias, weighting and efficiency. Revista Española de Investigaciones Sociológicas (Reis), 131(1), 109-130. url: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.983.7234&rep=rep1&type=pdf Muñoz de Bustillo, R., & De Pedraza, P. (2010). Determinants of job insecurity in five European countries. European Journal of Industrial Relations, 16(1), 5-20. url: https://journals.sagepub.com/doi/abs/10.1177/0959680109355306 Kahanec, M. (2009). The Decade of Roma Inclusion: A unifying framework of progress measurement and options for data collection. Institute for the Study of Labor (IZA) Research Report, (21). url: http://www.iza.org/de/webcontent/prize/en/webcontent/publications/reports/report_pdfs/iza_report_21.pdf Wetzels, C. Are workers in the cultural industries paid differently? Journal of Cultural Economics, Springer US, 2008, 32, 59-77 url: http://dx.doi.org/10.1007/s10824-007-9055-6 Freeman, R. B. (2005). From the Webbs to the web: The contribution of the internet to reviving union fortunes (No. w11298). National Bureau of Economic Research. url: https://www.nber.org/papers/w11298 url: Tijdens, K. (2002). The impact of a career break on a woman's wage. Transfer: European Review of Labour and Research, 8(1), 123-127. https://doi.org/10.1177%2F102425890200800119
Language	English
Producer	WageIndicator Foundation (AIAS)
Depositor	Research Data Center of IZA (IDSC)
Deposit Date	2023-11-09
Time Period	Start Date: 2000 ; End Date: 2021
Data Type	Survey Data

Geospatial Metadata

Geographic Coverage

Angola
Argentina
Armenia
Azerbaijan
Belarus
Belgium
Botswana
Brazil
Chile
China
Congo
Czech Republic
Denmark
Egypt
El Salvador
Finland
France
Georgia
Germany
Guatemala
Hungary
India
Indonesia
Italy
Kazakhstan
Korea, Republic of
Kyrgyzstan
Latvia
Lithuania
Malawi
Mozambique
Namibia
Netherlands
Paraguay
Poland
Russian Federation
Slovakia
South Africa
Spain
Sweden
Turkmenistan
Ukraine
United Kingdom
United States
Uzbekistan
Zambia
Zimbabwe

Social Science and Humanities Metadata

Unit of Analysis	Individuals; Households
Time Method	Cross-Sectional
Collection Mode	Web-based Interview

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