an article by Dimitris Pavlopoulos (VU University, Amsterdam, The Netherlands) and Ruud Muffels and Jeroen K. Vermunt (Tilburg University, The Netherlands) published in Journal of the Royal Statistical Society: Series A (Statistics in Society) Volume 175 Issue 3 (July 2012)
Summary
The aim of the paper is to investigate the effect of measurement error on low pay transition probabilities.
Our approach combines the virtues of panel regression and latent class models, though it does not require the use of validation or reinterview data. Using British, German and Dutch panel data, we show that the true estimated low pay transition probability is much lower that what previous research has found.
This implies that almost half of the observed transitions can be attributed to measurement error. The highest low pay transition probabilities are found in Germany and the lowest in the Netherlands. When applying this correction for measurement error in a multivariate model of low pay transitions, the results indicate that measurement error attenuates considerably the effects of the main covariates, such as training, job change, change in the type of employment contract and shift from part-time to full-time employment.
Subscribe to:
Post Comments (Atom)
No comments:
Post a Comment