Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/46184 
Year of Publication: 
2010
Series/Report no.: 
IZA Discussion Papers No. 5216
Publisher: 
Institute for the Study of Labor (IZA), Bonn
Abstract: 
The linear IV estimator, in which the dependent variable is a linear function of a potentially endogenous regressor, is a major workhorse in empirical economics. When this regressor takes on multiple values, the linear specification restricts the marginal effects to be constant across all margins. This paper investigates the problems caused by the linearity restriction in IV estimation, and discusses possible remedies. We first examine the biases due to nonlinearity in the commonly used tests for non-zero treatment effects, selection bias, and instrument validity. Next, we consider three applications where theory suggests a nonlinear relationship, yet previous research has used linear IV estimators. We find that relaxing the linearity restriction in the IV estimation changes the qualitative conclusions about the relevant economic theory and the effectiveness of different policies.
Subjects: 
linear model
variable treatment intensity
nonlinearity
instrumental variables
JEL: 
C31
C14
Document Type: 
Working Paper

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