This paper examines the significance of spatial externalities for youths’ school-to-training transitions in Germany. For this purpose, it is necessary to address the methodological question of how an individual’s sp...This paper examines the significance of spatial externalities for youths’ school-to-training transitions in Germany. For this purpose, it is necessary to address the methodological question of how an individual’s spatial context has to be operationalized with respect to both its extent and the problem of spatial autocorrelation. Our analyses show that the “zone of influence” comprises of the whole of Germany, not only close-by districts, and that these effects differ between structurally weak and strong regions. Consequently, assuming that only close proximity affects individual outcomes may disregard relevant contextual influences, and for spatial models that require an a priori definition of the weights for spatial units, it may be erroneous to make a decision based on this assumption. Concerning spatial autocorrelation, we found that neglecting local spatial autocorrelation at the context level causes considerable bias to the estimates, especially for districts that are close to the home district.展开更多
文摘This paper examines the significance of spatial externalities for youths’ school-to-training transitions in Germany. For this purpose, it is necessary to address the methodological question of how an individual’s spatial context has to be operationalized with respect to both its extent and the problem of spatial autocorrelation. Our analyses show that the “zone of influence” comprises of the whole of Germany, not only close-by districts, and that these effects differ between structurally weak and strong regions. Consequently, assuming that only close proximity affects individual outcomes may disregard relevant contextual influences, and for spatial models that require an a priori definition of the weights for spatial units, it may be erroneous to make a decision based on this assumption. Concerning spatial autocorrelation, we found that neglecting local spatial autocorrelation at the context level causes considerable bias to the estimates, especially for districts that are close to the home district.
