Nonparametric methods for inference in the presence of instrumental variables
We suggest two nonparametric approaches, based on kernel methods and orthogonal series to estimating regression functions in the presence of instrumental variables. For the first time in this class of problems, we derive optimal convergence rates, and show that they are attained by particular estimators. In the presence of instrumental variables the relation that identifies the regression function also defines an ill-posed inverse problem, the ``difficulty'' of which depends on...[Show more]
|Collections||ANU Research Publications|
|Source:||Annals of Statistics 2005, Vol. 33, No. 6, 2904-2929|
|Hall and Horowitz Nonparametric methods 2005.pdf||257.35 kB||Adobe PDF|
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