Drive-Time Matrix for Germany's Kreis (Counties)

This paper analyzed the reasons for the stubbornly low labor productivity in East Germany. Specifically, we distinguished between two main causes, namely worker characteristics (e.g. skills) vs. job characteristics (e.g. capital or infrastructure). We built a spatial labor market model that allows for commuting. If less favorable worker characteristics cause the low labor productivity in the East, then there will be no commuting, and the unemployment rate increases discontinuously at the former border. If on the other hand less favorable job characteristics lower the labor productivity in the East, then unemployed East Germans living close to the former border will commute to the West, resulting in a gradual increase in unemployment rates along the former border.

We used county level data and tools of spatial econometrics to empirically analyze the slope of the unemployment rate along the former border, and calibrated the model to match the observed slope. The project calculated the estimated driving time and driving distance between each of the 439 Kreis, or counties, in Germany. The point affiliated with each Kreis will be the centroid of the most populous Gemeinden (town) in each Kreis. Two 439 x 439 matrices will be produced.

no links

Files:
germany_21.gif
germany_31.gif
germany_11.gif

Share