Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/170753
Authors: 
Hohberg, Maike
Landau, Katja
Kneib, Thomas
Klasen, Stephan
Zucchini, Walter
Year of Publication: 
2017
Series/Report no.: 
Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 240
Abstract: 
This paper analyzes several modifications to improve a simple measure of vulnerability as expected poverty. Firstly, in order to model income, we apply distributional regression relating potentially each parameter of the conditional income distribution to the covariates. Secondly, we determine the vulnerability cutoff endogenously instead of defining a household as vulnerable if its probability of being poor in the next period is larger than 0.5. For this purpose, we employ the receiver operating characteristic curve that is able to consider prerequisites according to a particular targeting mechanism. Using long-term panel data from Germany, we build both mean and distributional regression models with the established 0.5 probability cutoff and our vulnerability cutoff. We find that our new cutoff considerably increases predictive performance. Placing the income regression model into the distributional regression framework does not improve predictions further but has the advantage of a coherent model where parameters are estimated simultaneously replacing the original three step estimation approach.
Subjects: 
vulnerability to poverty
distributional regression
generalized additive model for location
scale and shape
receiver operating characteristic curve
JEL: 
C13
C18
C52
I32
Document Type: 
Working Paper

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