Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/198907 
Erscheinungsjahr: 
2019
Schriftenreihe/Nr.: 
CESifo Working Paper No. 7547
Verlag: 
Center for Economic Studies and ifo Institute (CESifo), Munich
Zusammenfassung: 
We study the effect of spatial inequality on economic activity. Given that the relationship is highly simultaneous in nature, we use exogenous variation in geographic features to construct an instrument for spatial inequality, which is independent from any man-made factors. Inequality measures and instruments are calculated based on grid-level data for existing countries as well as for artificial countries. In the construction of the instrumental variable, we use both a parametric regression analysis as well as a random forest classification algorithm. Our IV regressions show a significant negative relationship between spatial inequality and economic activity. This result holds if we control for country-level averages of different geographic variables. Therefore, we conclude that geographic heterogeneity is an important determinant of economic activity.
Schlagwörter: 
regional inequality
spatial inequality
economic activity
development
geography
machine learning
JEL: 
R12
O15
Dokumentart: 
Working Paper
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