Testing and relaxing the exclusion restriction in the control function approach
Autor: | Yuya Sasaki, Stefan Hoderlein, Xavier D'Haultfœuille |
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Rok vydání: | 2021 |
Předmět: |
Economics and Econometrics
Applied Mathematics 05 social sciences Instrumental variable Causal effect Nonparametric statistics Structure (category theory) 01 natural sciences Outcome (probability) Control function 010104 statistics & probability Identification (information) 0502 economics and business Econometrics Endogeneity 0101 mathematics 050205 econometrics Mathematics |
Zdroj: | Journal of Econometrics. |
ISSN: | 0304-4076 |
Popis: | The control function approach which employs an instrumental variable excluded from the outcome equation is a very common solution to deal with the problem of endogeneity in nonseparable models. Exclusion restrictions, however, are frequently controversial. We first argue that, in a nonparametric triangular structure typical of the control function literature, one can actually test this exclusion restriction provided the instrument satisfies a local irrelevance condition. Second, we investigate identification without such exclusion restrictions, i.e., if the “instrument” that is independent of the unobservables in the outcome equation also directly affects the outcome variable. In particular, we show that identification of average causal effects can be achieved in the two most common special cases of the general nonseparable model: linear random coefficients models and single index models. |
Databáze: | OpenAIRE |
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