From WageIndicator to BIG DATA - Enjoying my job - Thank you!

By Pablo de Pedraza García,  University Salamanca/Amsterdam - WEBDATANET - 

Happy birthday WageIndicator team.

I started to work for the WageIndicator foundation in 2005, more than ten years later, and as part the WageIndicator 15th anniversary celebration, I have been asked to explain how the WageIndicator has influenced my carrier development.  It is a pleasure to share it will you all.

I had my first contact with the WageIndicator when it was five years old. I had already graduated in Law (1997) and economics (2003), worked for the European Commission (1999) and been a scholarship holder of the Spanish Ministry of Technology (2000-2005). Difficult to guess what my carrier, and me as a person, would be if I would not have become a member of this family. In any case, it would have been, for sure, much more boring and much less challenging, innovative and funny than it has been.   

By the time when Kea and Pauline started this project, the WageIndicator idea was futuristic and, as such, at least challenging and risky: collecting worldwide information about works and wages. For me, that during the first two years combined WageIndicator with finishing my Phd (2007), and very often with teaching international economics at the University of Salamanca, an opportunity that I could not leave behind. Teaching about trade and indirect mobility of labour and, at the same time, contributing to the challenge of comparing working conditions worldwide: A perfect match to read and dream.

As a researcher, my first responsibility was to help in bringing the WageIndicator sample to scientific discussions and publications. We started comparing WageIndicator data with probabilistic samples, such as labour force surveys, evaluating bias and calculating weights to balance the WageIndicator sample (Pedraza et al 2007, 2010). Afterwards we started to tap into the WageIndicator to test theories from specific research topics such as job insecurity (Bustillo and Pedraza 2010), life satisfaction (Guzi and Pedraza 2015), Health Economics (Steinmetz and Tijdens). We have been showing and promoting the usefulness of the project for social sciences by focusing on its ability to offer an international view from two points of view: the methodological perspective of the internet to collect data and the content research approach exploring the relationships among the variables collected.

Maybe because we need to know the properties of our data to understand the results we obtain, we have been more active in the methodological discussion about representativeness, bias, statistical inference and so on. A discussion that, as a result of the data revolution, is currently one of the big scientific topics.  By 2010, Kea, Stephanie and I, realise that the Wage Indicator and the community of web based data collection methodologists could benefit and foster each other. We started to work on a proposal to develop a network of web based data collection experts. We aimed society to benefit from better data for better policy making by means of synergies and interactions between data collection methods and technology. Thanks to the support of the EU cost office for the coordination of Science and Technology,, we have been leading WebDataNet is a unique multidisciplinary European network bringing together leading web based data collection experts from 31 European member states plus USA, Brazil and Russia. In order to foster scientific use of web data, we have been organizing meetings, conferences, training schools, workshops and many other activities. Prestigious Universities, institutions and researchers have been involved in these activities. We have had the opportunity to meet, talk and discuss with key notes speakers like Edith de Leeuw, Don Dillman, Mick Couper, Richard Freeman or Alberto Cavallo. Institutions, like Eurostat, the European Commission, the World Bank and several central Banks and National Statistical Offices have also participated in our networking process and the research lines emerging from it. 

Kea´s Collaborations with Computers Scientist have gone further. In 2012 she leaded, together with Gabor Kismihók, a proposal to develop a training network to study supply and demand matching processes in the labour markets from the micro, meso and macro levels. The project started in 2013. I have been the principal investigator of the Spanish part of the project during its first year and a Marie Curie Fellow at the Amsterdam Institute for Advanced Labour Studies (AIAS) afterwards. During the two years I will be located in Amsterdam, I will have the opportunity to analyse and combine the WageIndicator data with other data obtained from the web such as vacancy data.  

As a researcher, the WageIndicator gave me many things: a feasible challenging long run goal; the best advice to build upon others´ work; the best teams to learn from and work with; the ability to coordinate multidisciplinary networking, training, contacts… All these has given me a better understanding of the world around us and have made possible me to bring back some contributions to the project.

As a person, it brought me good friends and people I enjoy very much spending my time with. There have been countless wonderful moments: the many meetings and discussions with Kea and Stephanie, the lunches at AIAS, the mushrooms walks with Dirk and Pauline talking about the future, the meetings with the Webdatanet Core Group and Management Committee, the research stays with Paulo in Sao Paulo and with Martin Guzi at IZA in Bonn and many others. And also difficult ones from which we learnt a lot. In overall, the WageIndicator has display a strong positive impact on my happiness and my job and life satisfaction.

I would like to use this opportunity to thank you, not only Kea and Pauline for their efforts, advice and help but to all the people that put its energy, time and efforts behind the WageIndicator. It is all of you that will make possible another wealthy fifteen years of growing. More and more researchers are now benefiting from the opportunities the WageIndicator data are opening. This is not only an indicator of the growing data quality but of how much the world needs projects like this. The challenges ahead are comparable, and even harder, to those we had in the past. From my side I am ready to continue fighting for a stronger WageIndicator aiming better data for a better society. I am also ready to continue enjoining my job, celebrating many more anniversaries and increasing the number of beautiful moments I spend with the WageIndicator family.  Thank you very much.