Zobrazeno 1 - 10
of 77
pro vyhledávání: '"Taisuke Otsu"'
Autor:
Yukitoshi Matsushita, Taisuke Otsu
Publikováno v:
Journal of Econometrics. 232:346-366
This paper studies second-order properties of the many instruments robust t -ratios based on the limited information maximum likelihood and Fuller estimators for instrumental variable regression models with homoskedastic errors under the many instrum
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::68ea128bae7a3fa925bac4cf020cb035
https://doi.org/10.1016/j.jeconom.2021.07.006
https://doi.org/10.1016/j.jeconom.2021.07.006
Publikováno v:
Taylor, L N, Otsu, T & Dong, H 2022, ' Estimation of Varying Coefficient Models with Measurement Error ', Journal of Econometrics, vol. 230, no. 2, pp. 388-415 . https://doi.org/10.1016/j.jeconom.2020.12.013
We propose a semiparametric estimator for varying coefficient models when the regressors in the nonparametric components are measured with error. Varying coefficient models are an extension of other popular semiparametric models, including partially
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a7433f98d7529e6707744758ea60be81
https://doi.org/10.1016/j.jeconom.2020.12.013
https://doi.org/10.1016/j.jeconom.2020.12.013
Publikováno v:
International Economic Review. 63:1165-1188
We propose a multiplicity-robust estimation method for static or dynamic games. The method allows for distinct behaviors and strategies across markets by treating market-specific behaviors as correlated latent variables, with their conditional probab
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f9316696def19db8791c85d5cffe581
https://doi.org/10.1111/iere.12564
https://doi.org/10.1111/iere.12564
This paper proposes an empirical likelihood inference method for monotone index models. We construct the empirical likelihood function based on a modified score function developed by Balabdaoui et al. (Scand J Stat 46:517–544, 2019), where the mono
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::65b24441272953e51ceeda7e214b3527
http://eprints.lse.ac.uk/118123/
http://eprints.lse.ac.uk/118123/
Publikováno v:
Econometric Theory. 37:1214-1237
This paper develops a new test statistic for parameters defined by moment conditions that exhibits desirable relative error properties for the approximation of tail area probabilities. Our statistic, called the tilted exponential tilting (TET) statis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7cfba7cb019f1538a2620e63c0aef4ea
https://doi.org/10.1017/s0266466621000074
https://doi.org/10.1017/s0266466621000074
Autor:
Yukitoshi Matsushita, Taisuke Otsu
Publikováno v:
Biometrika. 108:661-674
Summary This article aims to shed light on inference problems for statistical models under alternative or nonstandard asymptotic frameworks from the perspective of the jackknife empirical likelihood. Examples include small-bandwidth asymptotics for s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c64961f3184edee2c499791d8d00fdf1
https://doi.org/10.1093/biomet/asaa081
https://doi.org/10.1093/biomet/asaa081
Autor:
Mengshan Xu, Taisuke Otsu
Publikováno v:
Journal of Nonparametric Statistics. 32:838-863
This paper studies semiparametric estimation of a partially linear single index model with a monotone link function. Our estimator is an extension of the score-type estimator developed by Balabdaoui et al. (2019) for the monotone single index model,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3ad70a9b47e36e67b83758693e1f6bbe
https://doi.org/10.1080/10485252.2020.1834105
https://doi.org/10.1080/10485252.2020.1834105
Publikováno v:
Journal of Econometrics. 215:131-164
This paper is concerned with inference on the cumulative distribution function (cdf) F X ∗ in the classical measurement error model X = X ∗ + ϵ . We consider the case where the density of the measurement error ϵ is unknown and estimated by repe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8fc0ab676149886f52a8f1773b9cd1c3
http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100806369
http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100806369
Autor:
Taisuke Otsu, Daisuke Kurisu
This paper studies the uniform convergence rates of Li and Vuong’s (1998, Journal of Multivariate Analysis 65, 139–165; hereafter LV) nonparametric deconvolution estimator and its regularized version by Comte and Kappus (2015, Journal of Multivar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c572f117251a1b1781309d12e1c5c4b3
http://eprints.lse.ac.uk/107533/
http://eprints.lse.ac.uk/107533/
Publikováno v:
Dong, H, Otsu, T & Taylor, L N 2021, ' Average Derivative Estimation Under Measurement Error ', Econometric Theory, vol. 37, no. 5, pp. 1004-1033 . https://doi.org/10.1017/S0266466620000432
In this paper, we derive the asymptotic properties of the density-weighted average derivative estimator when a regressor is contaminated with classical measurement error and the density of this error must be estimated. Average derivatives of conditio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::307b3a5f720af059c6763d241f22d9f0
https://pure.au.dk/portal/da/publications/average-derivative-estimation-under-measurement-error(1088277d-b88d-43fa-be49-90e33517562f).html
https://pure.au.dk/portal/da/publications/average-derivative-estimation-under-measurement-error(1088277d-b88d-43fa-be49-90e33517562f).html