Smooth minimum distance estimation and testing with conditional estimating equations: uniform in bandwidth theory. (English) Zbl 1285.62033
Summary: To study the influence of a bandwidth parameter in inference with conditional moments, we propose a new class of estimators and establish an asymptotic representation of our estimator as a process indexed by a bandwidth, which can vary within a wide range including bandwidths independent of the sample size. We study its behavior under misspecification. We also propose an efficient version of our estimator. We develop a procedure based on a distance metric statistic for testing restrictions on parameters as well as a bootstrap technique to account for the bandwidth’s influence. Our new methods are simple to implement, apply to non-smooth problems, and perform well in our simulations.
MSC:
| 62G05 | Nonparametric estimation |
| 62G20 | Asymptotic properties of nonparametric inference |
| 62G10 | Nonparametric hypothesis testing |
| 62G09 | Nonparametric statistical resampling methods |
Keywords:
semiparametric estimation; conditional estimating equations; smoothing methods; asymptotic efficiency; hypothesis testing; bootstrapReferences:
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