Locally Regular and Efficient Tests in Non-Regular Semiparametric Models
This paper considers hypothesis testing in semiparametric models which may be non-regular. I show that C($\alpha$) style tests are locally regular under mild conditions, including in cases where locally regular estimators do not exist, such as models which are (semiparametrically) weakly identified. I characterise the appropriate limit experiment in which to study local (asymptotic) optimality of tests in the non-regular case and generalise classical power bounds to this case. I give conditions under which these power bounds are attained by the proposed C($\alpha$) style tests. The application of the theory to a single index model and an instrumental variables model is worked out in detail.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
A Likelihood Ratio Framework for High Dimensional Semiparametric Regression
We propose a likelihood ratio based inferential framework for high dimensional semiparametric generalized linear models. This framework addresses a variety of challenging problems in high dimensional data analysis, inclu…
regressionSelection biasVocal Bursts Intensity PredictionSemiparametrically Optimal Cointegration Test
This paper aims to address the issue of semiparametric efficiency for cointegration rank testing in finite-order vector autoregressive models, where the innovation distribution is considered an infinite-dimensional nuisa…
Regularized Generalized Covariance (RGCov) Estimator
We introduce a regularized Generalized Covariance (RGCov) estimator as an extension of the GCov estimator to high dimensional setting that results either from high-dimensional data or a large number of nonlinear transfor…
Locally robust semiparametric estimation of sample selection models without exclusion restrictions
Existing identification and estimation methods for semiparametric sample selection models rely heavily on exclusion restrictions. However, it is difficult in practice to find a credible excluded variable that has a corre…
regressionSemiparametrically Point-Optimal Hybrid Rank Tests for Unit Roots
We propose a new class of unit root tests that exploits invariance properties in the Locally Asymptotically Brownian Functional limit experiment associated to the unit root model. The invariance structures naturally sugg…
valid