Title: Addressing measurement error in the estimation of labor market transitions
Authors: Daniel Borowczyk-Martins - Copenhagen Business School (Denmark) [presenting]
Abstract: A new approach is developed to estimate transition probabilities based on a series of repeated cross sections and when the variable recording individuals' past state is exposed to classification and recall errors. The problem and the solution are motivated by the estimation of the canonical model of worker flows using the International Labor Organization classifications of labor market states and microdata from the European Union Labor Force Survey. We specify the data-generating process of observed individual-level transition probabilities as a mixture of two multinomial logit models (one for the unobserved transition probabilities and another for the measurement-error process) and inform its estimation with two sources of auxiliary data.