Spatial dependencies in German matching functions

This paper proposes a spatial panel model for German matching functions to avoid possibly biased and inefficient estimates due to spatial dependence. We provide empirical evidence for the presence of spatial dependencies in matching data. Based on an official data set containing monthly information for 176 local employment offices, we show that neglecting spatial dependencies in the data results in upward-biased coefficients. For the incorporation of spatial information into our model, we use data on commuting relations between local employment offices. Furthermore, our results suggest that a dynamic modeling is more appropriate for matching functions.

Research highlights
► Empirical evidence for positive spatial autocorrelation in German matching data.
► Ignoring spatial autocorrelation in matching data yields overestimated coefficients.
► Dynamic modeling is more appropriate for matching functions.