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- A 5 Minute Presentation - 3rd Global WageIndicator Conference. Amsterdam, April 16, 2008

Methodological Foundations of the Web-based PayWizard Dataset (USA) Isabelle Ferreras (Harvard Labor and Worklife Program/ FNRS/Louvain ) Damian Raess (MIT) Members of the team headed by Prof. Richard Freeman (HarvardLWP/NBER). - A 5 Minute Presentation -

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- A 5 Minute Presentation - 3rd Global WageIndicator Conference. Amsterdam, April 16, 2008

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  1. Methodological Foundations of the Web-based PayWizard Dataset (USA)Isabelle Ferreras (Harvard Labor and Worklife Program/FNRS/Louvain)Damian Raess (MIT) Members of the team headed by Prof. Richard Freeman (HarvardLWP/NBER) - A 5 Minute Presentation - 3rd Global WageIndicator Conference. Amsterdam, April 16, 2008

  2. General Approach How to generalize from a non-representative sample? • Building a strategy to probe the significance of the web-generated dataset: • 1/ Questionnaire design • 2/ Basic statistical tests (a simple model determining income) • 2.a. Correlation analysis • 2.b. Regression analysis • 2.c. Weighing might not be enough • 3/ More to come... With YOU! • 18 months after launching, a tough road in the US: a highly competitive market ; now 10 000 visitors a month, waiting for completed surveys! • Number of observations so far = 3000

  3. 1/ Questionnaire design • 1/ Locate the “reference survey” in your country = a random sample representative of the entire US population • In the USA: US Current Population Survey (generated by the Bureau of Labor Statistics and the Census Bureau) • 2/ Identify the questions of the WageIndicator survey that correspond to questions covered by that “reference survey”, and aim at matching these. • Example: the wage question(s) should be conformed to the one of your “reference survey”.

  4. 2/ Basic statistical tests • A simple model determining income by age, sex, education • Descriptive variables • Sex, percentage of men: CPS, 51%; PayW, 54% • Age, median: CPS, 41; PayW, 37 • Education, years of schooling

  5. 2/ Basic statistical tests • Weekly wage (logwage)

  6. 2/ Basic statistical tests • A simple model determining income • 2.a. Correlation analysis

  7. 2/ Basic statistical tests • A simple model determining income • 2.b. Regression analysis

  8. 2/ Basic statistical tests • A simple model determining income • 2.b. Regression analysis

  9. 2/ Basic statistical tests - 2.b. Regression analysis

  10. Conclusion: Weighing might not be enough 3/ More to come... We need YOU! • A collaborative effort... • THANK YOU ! • raess@mit.edu & iferreras@law.harvard.edu

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