The WageIndicator web survey for worldwide social science research on wages

1. The WageIndicatorweb survey for worldwide social science research on wages 25 April 2007, OECD

2. Paulien Osse Director WageIndicator Foundation Journalist Web manager Coordinator GLOBAL projects (2005-2009)

3. Wiemer Salverda Director Amsterdam Institute for Advanced Labour Studies, University of Amsterdam, NL Economist Coordinator LoWER network

4. Victor Beker Director Centro de Estudios de la Nueva Economía (CENE), University of Belgrano, AR Economist Manager www.Elsalario.com.ar

5. Kea Tijdens Research Coordinator Amsterdam Institute for Advanced Labour Studies, University of Amsterdam, NL Sociologist Coordinator WOLIWEB project FP6 (2004-2007) and applicant WARIWEB proposal for FP7

6. The concept • National WageIndicator websites • with up-to-date work-related information • most of them managed by web journalists • answering visitor’s emails • Salary Checker (free of charge) • providing occupation-specific wage information • controlling for age, gender, education and region • Web survey • asking the visitors a favor in return • completing a 20-minutes web survey on work and wages (prize incentive) • data is used for research and as input for the Salary Checker

7. A brief history NL • 1999 desire for wage information on Internet detailed occupation wage data needed for research • 2000 survey about work and wages in women’s magazines • 2001 launch women’s WageIndicator website with web surveyand Salary Check for 45 occupations • 2002 launch websites for men, 40+, youth • 2004Salary Check for 400 occupations • 2006 400,000 web visitors per month in NL

8. To other countries • 2004 Belgium, Denmark, Germany, Spain, Finland, Italy, Poland, United Kingdom (EU funding 6th Framework Program) • 2005 Hungary(EU funding Equal)Argentina, Brazil, Mexico India, S-Korea, S-Africa(funding NL development aid- FNV Mondiaal) • 2006 USA(funding Harvard Law School) • 2007 China, Russia, Sweden(funding pending) • 2008Austria, Bulgaria, Czeck Republic, France, Romania, Slovenia, Turkey(application for FP7)

9. The Foundation owns the WageIndicator concept is a not-for-profit organization Its mission statement “Share and compare wage information.Contribute to a transparent labor market.Provide free, accurate wage data through salary checks on national websites.Collect wage data through web surveys.” Founded in 2003 under Dutch law by University of Amsterdam NL branch of the international career website Monster NL Dutch Confederation of Trade Unions (FNV) WageIndictator Foundation

10. Web traffic • Websites are frequently visited • worldwide, the public at large shows a great desire for information about wages • visitors use the website for decisions about schooling, occupational choice, wage negotiations, and job mobility • on average after one-three years of web-marketing a national website reaches a stable level of visitors • Unique visitors totals • 2005: 5 million • 2006: 8 million • 2007: 10 million (prognosis) • Variation across countries • NL: > 400,000/month (since 2001, household name) • DE: > 100,000/month (since 2004, large population) • BR/AR: 25,000/month (since 2006, well linked) • ZA/IT/KR: < 1,000/month (weaker teams)

11. WageIndicator Websites more than 40 websites in 20 countries, extra websites for multilingual countries, for women, elderly workers, IT staff (India) thousands of links in other websites Web visitors must trust the information provided in a Salary Check (thus it must offer high quality information) volunteering their data in the survey receiving a response to visitor’s email Web-marketing is critical cooperation with media groups, career sites, trade unions, all with a strong Internet presence Web marketing

12. Partners • Worldwide partners • Career site Monster • MSN • Dutch World Broadcasting Service • Research partners • University of Amsterdam, Erasmus of Rotterdam, NL • Harvard Law School, USA • Research network with academic partners in 17 countries • Trade union partners • national federations: DGB, TUC, FNV, SAK, etc • international federations: UNI, ETUC • Newspaper and portal partners • Gazeta Wyborcza (PL) • El Pais (ES) • La Nacion (AR) • UOL (BR - portal) • Sueddeutsche (DE) • Mail & Guardian (ZA) • etceteras

13. The survey • Target population: labor force • wage-earners in formal and informal economy • self-employed, free lancers, home workers (with SEWA in India) • parallel questions addressing rare groups in the labor force to prevent break-off • Questionnaire: 6 sections • (1) occupation and education • (2) workplace characteristics • (3) employment history • (4) working hours • (5) employment contract, wages, benefits • (6) personal questions • on many items factual and attitudinal questions

14. The technique • Questionnaire Management System QMS • developed for WageIndicator, using Open Source • manages a multi-country, multi-lingual survey • facilitates complicated routing, downloading codebooks and uploading languages • includes a search tree application for questions on occupation, industry, region • optimization for number of characters, clicks and pages • Data storage • the data is securely stored • dataportal with downloadable documentation

15. Sample size • Sample size (fully completed) • <2004 53,000 in NL • 2004 43,000 in 5 countries • 2005 135,000 in 11 countries • 2006 158,000 in 17 countries • 2007 250,000 in 19 countries (expected) • Feedback on the survey • the public is willing to complete the web survey • open-ended question “If you have any comments on the questionnaire, please do so here” • passive feedback through break-off • we want visitors to have fun in completing the questionnaire (and they report back that they do)

16. Data quality • Good quality • hardly any ‘click the first item only’ respondents • item non-response usually < 5% • very few multiple responding • 2007 a study on break-off scheduled • Variables • some 500 variables (varies across countries) • occupation (4 dgt ISCO), industry (4 dgt NACE), education (ISCED) • Data releases • quarterly data releases per country • annual data releases all countries

17. Volunteer survey • Selection bias and Internet access • worldwide Internet access rates are increasing fast • this population is becoming more and more representative of the population at large • it will boom with wireless access • Selection bias in choice of website? • web visitors can choose out of millions of websites • only a minor part visits a WageIndicator website • web traffic can be directed in number and in target group by means of web marketing • Selection bias in completing the survey • 1–10 % of the web visitors completes the questionnaire (f.e. Finland 10 %)

18. Selection bias • In all countries • the marginal groups in the labor force are under- represented, f.e. workers in small part-time jobs • low educated are increasingly not underrepresented • elderly workers 55+ are underrepresented • gender representation varies across countries • In Netherlands 2002-2006 • the underrepresentation of socio-demographic groups has declined in the past years

19. Coping with self-selection • Web marketing • addressing the target population at large • websites for sub-populations otherwise not fully reached • Routing through the questionnaire • to prevent rare groups from break-off • Weighting with aggregate data • aggregate socio economic LFS data is used for weighting national WageIndicator data • Weighting with micro data • micro-data from representative surveys will be used to develop weights, using similar questions in WageIndicator, currently explored in the US • Weighting with a reference survey • using a small reference survey for weighting, currently explored in the Netherlands

20. Continuity & large samples • Continuous survey • costs are not linear related to sample sizes, as in other survey modes • investment costs in QMS are relatively large • investments in web-marketing take time before paying off • conducting a continuous survey is profitable • Large sample sizes • allow for analyses of sub-sets • allow for survey questions addressing relatively small groups, thus acting as a screening device • large & continuous surveys allow for (FP7 proposal) • temporary plug-in questions • randomly drawn items from a pool

21. The research • On wages and working hours • cross-country wage differentials for occupations • gender pay gap and the motherhood penalty • modeling preferences for a change in working hours • On work place relations • attitudes towards collective bargaining coverage • effect of dismissals on self-perceived job insecurity • On labor markets • the multi-dimensionality of the informal labor market within and across countries • spill over effects of MNE’s in local employment

22. Is this new? • Yes, because … • worldwide, neither high quality aggregate data nor micro-data about wages, bonuses, and working hours are available • worldwide, WageIndicator is the first survey gathering wage data in so many countries • worldwide, it is one of the first surveys using web marketing for scientific data collection • … and because • the exchange of information from research to the public and from the public to research is not often seen

23. A Global WageIndicator • The plan • to enlarge the web operation to 75 countries • inspired by the globalizing economy and the need for worldwide data on wages, currently not available • advisor: International Labor Organization (ILO) • Its aims • contributing to a transparent labor market by provi- ding reliable data about wages to a worldwide public • collecting data for worldwide wage trend reports and for researching the impact of globalization • submitting plans to funding agencies in 2007/2008

24. A role for OECD? • This presentation aims to inform OECD about WageIndicator • Support for the 75-countries plan? • Using the dataset for wage analysis etc? • Input for funding options? • post Soviet area • Arab speaking world • Sub-Saharan Africa • Thank you for your attention! • www.wageindicator.org