Transcript titel - WageIndicator

The WageIndicator web survey
for worldwide social science
research on wages
Paulien Osse, WageIndicator Foundation
Kea Tijdens, University of Amsterdam
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March 2007, ILO
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The WageIndicator concept
• National WageIndicator websites
– with up-to-date work-related information
– answering visitor’s emails
• Salary Check
– providing free occupation-specific wage information
– controlling for age, gender, education and region
• Web survey
– asking the visitors a favor in return
– completing a web survey on work and wages (prize incentive)
– the data are used for research
and as input for the Salary Check
• Large numbers of visitors
– worldwide, the public shows a desire for wage information
– and is willing to complete the web survey
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A brief history
(Netherlands)
• 1999
• 2000
• 2001
• 2002
• 2004
• 2006
desire for wage information on Internet
detailed occupation wage data needed
for research
survey about work and wages
in women’s magazines
launch women’s WageIndicator website
with web survey
and Salary Check for 45 occupations
launch websites for men, 40+, youth
Salary Check for 400 occupations
400,000 web visitors per month in NL
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To other
countries
• 2004
Belgium, Denmark, Germany, Spain,
Finland, Italy, Poland, United Kingdom
(EU funding 6th Framework Program)
Hungary
(EU funding EQUAL fund)
• 2005
Argentina, Brazil, Mexico
India, S-Korea, S-Africa,
(funding NL development aid)
• 2006
USA
(funding Harvard Law School)
• 2007
China, Russia, Sweden
(contracts about to sign)
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WageIndictator
Foundation
• The WageIndicator 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)
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WageIndicator
websites
• 2007
– 35 websites in 17 countries, most of them
managed by web journalists
– 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
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Media parters and
web-marketing
• Worldwide partners
– Career site Monster
– MSN
– Dutch World Service
• Partners with established reputations
–
–
–
–
University of Amsterdam
Erasmus of Rotterdam
Harvard Law School
Leading national newspapers and portals
• Gazeta Wyborcza (PL)
• El Pais (ES)
• La Nacion (AR)
• UOL (BR)
• Sueddeutsche (DE)
• Mail & Guardian (ZA)
• Etc.
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The survey
• Target population: labor force
– wage-earners in formal and informal economy
– self-employed, free lancers, home workers
(with SEWA in India)
• Questions on
– Occupation (4 dgt ISCO), industry (4 dgt NACE),
education, work history, wages, benefits, hours,
personal questions
• Questionnaire
– completion takes approximately 20 minutes
– survey has parallel questions addressing rare
groups in the labor force to prevent break-off
– optimization as for the number of characters, clicks
and pages
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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
• Data storage
– the data is securely stored on servers
in USA, NL and India
– quarterly data releases
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Web traffic
• Visits totals
–
–
–
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2005: 4.5 million
2006: 7.8 million
January 2007: > 800,000
Prognosis 2007: 10 million
• Variation per country, some examples
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–
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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)
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The response(1)
• 2006
– Total visits 7.8 million
– Fully completed questionnaires 158,000
– Data for research and salary check 309,000
(2004-2006)
• Response rate overall
– 3.85 %
– Large variation across countries
– Cross-country analysis of response rates
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The response(2)
• Sample size (fully completed)
–
–
–
–
–
<2004
2004
2005
2006
2007
53,000 in NL
43,000 in 5 countries
135,000 in 11 countries
158,000 in 17 countries
250,000 in 19 countries (expected)
• Data quality is good
–
–
–
–
hardly any ‘click the first item only’ respondents
item non-response usually < 5%
very few multiple responding
in 2007 a study on break-off respondents
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Respondent-side
feedback
• Feedback on the websites
– visitors use the website for their decisions
about schooling, occupational choice,
wage negotiations, and job mobility
– we know from visitor’s email
• Feedback on the 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)
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Volunteer
web surveys
• 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 %)
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Findings on
selection bias
• In all countries
– the small groups in the labor force are underrepresented, 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 these socio-demographic
groups has declined in the past years
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Coping with
selection bias
• Web marketing
– addressing the target population at large
– sites 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
A I A Sexplored in the Netherlands
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Volunteer web
surveys are
advantageous
• … because they can be held continuously
– costs are not linear related to sample size
– investment costs are relatively large
-> conducting a continuous survey is profitable
– for WageIndicator continuity is a prerequisite
because of web marketing investments
– continuous surveys allow for temporary
plug-in questions
• … because they can lead to large sample sizes
– allows for analyses of sub-sets
– allows for presenting randomly items from a pool
– allows for questions addressing relatively small
groups, thus acting as a screening device
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The research
• Research community
– increasing numbers of researchers use the data
• 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
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Is this new?
• Yes, it is 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
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A Global
WageIndicator
• The plan
– a GlobalWageIndicator plan to enlarge the web
operation to 75 countries in 5 continents
– inspired by the globalizing economy and the need for
worldwide data on wages, currently not available
– jointly with International Labor Organization of the
United Nations, Harvard Law School, University of
Belgrano (AR), and Indian Institute of
Management/Ahmedabad (India)
• Its aims
– contributing to a transparent labor market by providing reliable data about wages to a worldwide public
– collecting data for worldwide wage trend reports and
for researching the impact of globalization
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A I A S plans to funding agencies in 2007
– submitting
The role of ILO
• Support for the 75-countries plan
• Using the dataset for wage data or
other data
• Input for funding options
– post Soviet area
– Arab speaking world
– Sub-Saharan Africa
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
• Thank you for your attention
– www.wageindicator.org
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