Title: Real-time estimation of unemployment with dynamic factor and time-varying state space models
Authors: Caterina Schiavoni - Maastricht University (Netherlands) [presenting]
Stephan Smeekes - Maastricht University (Netherlands)
Jan van den Brakel - Maastricht University (Netherlands)
Franz Palm - Maastricht University (Netherlands)
Abstract: Estimation of unobserved components is considered in high-dimensional state space models using a dynamic factor approach. Our method allows for variables to be observed at different frequencies and updates the estimation when new information becomes available. In addition, we account for potential time variation in the parameters of the model. We apply the methodology to unemployment estimation as done by Statistics Netherlands, who uses a multivariate state space model to produce monthly figures for the unemployed labour force using series observed with the Labour Force Survey (LFS). We extend the model by including auxiliary series about job search behaviour from Google Trends and claimant counts, partially observed at higher frequencies. Our factor model allows for nowcasting the variable of interest, providing unemployment estimates in real time before LFS data become available. In addition our method accounts for time-varying correlations between the LFS and auxiliary series.