Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/82223 
Year of Publication: 
2000
Series/Report no.: 
Working Paper No. 2000:2
Publisher: 
Institute for Labour Market Policy Evaluation (IFAU), Uppsala
Abstract: 
We introduce a framework to test for exogeneity of a variable in a regression based on cross-sectional data. By sorting data with respect to a function (sorting score) of known exogeneous variables it is possible to utilize a battery of tools originally develped to detecting model misspecification in at time series context. Thus, we are able to propose graphical tools for the identification of endogeneity, as well as formal tests, including a simple-to-use Chow test, needing a minimum of assumptions on the alternative endogeneity hypothesis. Models of endogenous treatment and selectivity are utilized to illustrate the methods. With Monte Carlo experiments, including continous and discrete response cases, we compare small sample performances with existing tests for exogeneity.
Subjects: 
Chow test
Endogenous treatment
Propensity score
Recursive residuals
Sample selection
Sorting score
JEL: 
C12
C21
C52
Document Type: 
Working Paper

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