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Keyword: empirical likelihood;
7 results found.
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Yukitoshi Matsushita and Taisuke Otsu
This paper sheds light on problems of statistical inference under alternative or nonstandard asymptotic frameworks from the perspective of jackknife empirical likelihood (JEL). Examples include small bandwidth asymptotic...Read more...
22 July 2019
Karun Adusumilli and Taisuke Otsu
Missing or incomplete outcome data is a ubiquitous problem in biomedical and social sciences. Under the missing at random setup, inverse probability weighting is widely applied to estimate and make inference on the popul...Read more...
30 October 2018
In the past few decades, much progress has been made in semiparametric modeling and estimation methods for econometric analysis. This paper is concerned with inference (i.e., confidence intervals and hypothesis testing) ...Read more...
27 June 2017
Lorenzo Camponovo, Yukitoshi Matsushita and Taisuke Otsu
With increasing availability of high frequency financial data as a background, various volatility measures and related statistical theory are developed in the recent literature. This paper introduces the method of empiri...Read more...
21 February 2017
Hahn and Ridder (2013) formulated influence functions of semiparametric three step estimators where generated regressors are computed in the first step. This class of estimators covers several important examples for empi...Read more...
5 September 2016
Kirill Evdokimov, Yuichi Kitamura and Taisuke Otsu
This paper considers robust estimation of moment condition models with time series data. Researchers frequently use moment condition models in dynamic econometric analysis. These models are particularly useful when one w...Read more...
5 December 2014
Wolfgang Haerdle, Oliver Linton and Qihua Wang
We develop inference tools in a semiparametric regression model with missing response data. A semiparametric regression imputation estimator, a marginal average estimator and a (marginal) propensity score weighted estima...Read more...