Zobrazeno 1 - 10
of 119
pro vyhledávání: '"Okui, Ryo"'
Autor:
Choi, Junho, Okui, Ryo
This paper concerns the estimation of linear panel data models with endogenous regressors and a latent group structure in the coefficients. We consider instrumental variables estimation of the group-specific coefficient vector. We show that direct ap
Externí odkaz:
http://arxiv.org/abs/2405.08687
Autor:
Hossain, Tanjim, Okui, Ryo
Publikováno v:
In Games and Economic Behavior July 2024 146:160-183
Autor:
Dzemski, Andreas1 (AUTHOR) andreas.dzemski@economics.gu.se, Okui, Ryo2 (AUTHOR) okuiryo@e.u-tokyo.ac.jp
Publikováno v:
Quantitative Economics. May2024, Vol. 15 Issue 2, p245-277. 33p.
Autor:
Dzemski, Andreas, Okui, Ryo
We study kmeans clustering estimation of panel data models with a latent group structure and $N$ units and $T$ time periods under long panel asymptotics. We show that the group-specific coefficients can be estimated at the parametric root $NT$ rate e
Externí odkaz:
http://arxiv.org/abs/2008.04708
Publikováno v:
In Journal of Econometrics March 2023 233(1):45-65
Autor:
Okui, Ryo, Yanagi, Takahide
This paper proposes a model-free approach to analyze panel data with heterogeneous dynamic structures across observational units. We first compute the sample mean, autocovariances, and autocorrelations for each unit, and then estimate the parameters
Externí odkaz:
http://arxiv.org/abs/1803.09452
Autor:
Okui, Ryo, Yanagi, Takahide
This paper proposes nonparametric kernel-smoothing estimation for panel data to examine the degree of heterogeneity across cross-sectional units. We first estimate the sample mean, autocovariances, and autocorrelations for each unit and then apply ke
Externí odkaz:
http://arxiv.org/abs/1802.08825
Autor:
Okui, Ryo, Wang, Wendun
This paper develops a new model and estimation procedure for panel data that allows us to identify heterogeneous structural breaks. We model individual heterogeneity using a grouped pattern. For each group, we allow common structural breaks in the co
Externí odkaz:
http://arxiv.org/abs/1801.04672
Autor:
Dzemski, Andreas, Okui, Ryo
Our confidence set quantifies the statistical uncertainty from data-driven cluster assignment in clustered panel models. It covers the true cluster memberships jointly for all units with pre-specified probability and is constructed by inverting many
Externí odkaz:
http://arxiv.org/abs/1801.00332
In this paper, we propose a doubly robust method to present the heterogeneity of the average treatment effect with respect to observed covariates of interest. We consider a situation where a large number of covariates are needed for identifying the a
Externí odkaz:
http://arxiv.org/abs/1601.02801