Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/148868 
Year of Publication: 
2016
Series/Report no.: 
SFB 649 Discussion Paper No. 2016-032
Publisher: 
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk, Berlin
Abstract: 
There are many environments in econometrics which require nonseparable modeling of a structural disturbance. In a nonseparable model, key conditions are validity of instrumental variables and monotonicity of the model in a scalar unobservable. Under these conditions the nonseparable model is equivalent to an instrumental quantile regression model. A failure of the key conditions, however, makes instrumental quantile regression potentially inconsistent. This paper develops a methodology for testing the hypothesis whether the instrumental quantile regression model is correctly speci ed. Our test statistic is asymptotically normally distributed under correct speci cation and consistent against any alternative model. In addition, test statistics to justify model simpli cation are established. Finite sample properties are examined in a Monte Carlo study and an empirical illustration.
Subjects: 
Nonparametric quantile regression
instrumental variable
specification test
local alternative
nonlinear inverse problem
Document Type: 
Working Paper

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