27 citations · 80 across the 17 of their papers we have counts for
17 papers
Projection Inference for set-identified SVARs
Bulat Gafarov, Matthias Meier, José Luis Montiel Olea
We study the properties of the classical \emph{projection} method to conduct simultaneous inference about the coefficients of the structural impulse-response function and their ide…
Locally- but not Globally-identified SVARs
Emanuele Bacchiocchi, Toru Kitagawa
This paper analyzes Structural Vector Autoregressions (SVARs) where identification of structural parameters holds locally but not globally. In this case there exists a set of isola…
Individualized Treatment Allocation in Sequential Network Games
Toru Kitagawa, Guanyi Wang
Designing individualized allocation of treatments so as to maximize the equilibrium welfare of interacting agents has many policy-relevant applications. Focusing on sequential deci…
Asymptotically Optimal Fixed-Budget Best Arm Identification with Variance-Dependent Bounds
Masahiro Kato, Masaaki Imaizumi, Takuya Ishihara +1
We investigate the problem of fixed-budget best arm identification (BAI) for minimizing expected simple regret. In an adaptive experiment, a decision maker draws one of multiple tr…
Stochastic Treatment Choice with Empirical Welfare Updating
Toru Kitagawa, Hugo Lopez, Jeff Rowley
This paper proposes a novel method to estimate individualised treatment assignment rules. The method is designed to find rules that are stochastic, reflecting uncertainty in estima…
Best Arm Identification with Contextual Information under a Small Gap
Masahiro Kato, Masaaki Imaizumi, Takuya Ishihara +1
We study the best-arm identification (BAI) problem with a fixed budget and contextual (covariate) information. In each round of an adaptive experiment, after observing contextual i…
Treatment Choice with Nonlinear Regret
Toru Kitagawa, Sokbae Lee, Chen Qiu
The literature focuses on the mean of welfare regret, which can lead to undesirable treatment choice due to sensitivity to sampling uncertainty. We propose to minimize the mean of…
Policy Choice in Time Series by Empirical Welfare Maximization
Toru Kitagawa, Weining Wang, Mengshan Xu
This paper develops a novel method for policy choice in a dynamic setting where the available data is a multivariate time series. Overcoming challenges unique to time-series settin…
von Mises-Fisher distributions and their statistical divergence
Toru Kitagawa, Jeff Rowley
The von Mises-Fisher family is a parametric family of distributions on the surface of the unit ball, summarised by a concentration parameter and a mean direction. As a quasi-Bayesi…
Paternalism, Autonomy, or Both? Experimental Evidence from Energy Saving Programs
Takanori Ida, Takunori Ishihara, Koichiro Ito +4
Identifying who should be treated is a central question in economics. There are two competing approaches to targeting - paternalistic and autonomous. In the paternalistic approach,…
Testing Instrument Validity with Covariates
Thomas Carr, Toru Kitagawa
We develop a novel test of the instrumental variable identifying assumptions for heterogeneous treatment effect models with conditioning covariates. We assume semiparametric depend…
Evidence Aggregation for Treatment Choice
Takuya Ishihara, Toru Kitagawa
Consider a planner who has limited knowledge of the policy's causal impact on a certain local population of interest due to a lack of data, but does have access to the publicized i…
Constrained Classification and Policy Learning
Toru Kitagawa, Shosei Sakaguchi, Aleksey Tetenov
Modern machine learning approaches to classification, including AdaBoost, support vector machines, and deep neural networks, utilize surrogate loss techniques to circumvent the com…
Identification and Inference Under Narrative Restrictions
Raffaella Giacomini, Toru Kitagawa, Matthew Read
We consider structural vector autoregressions subject to 'narrative restrictions', which are inequality restrictions on functions of the structural shocks in specific periods. Thes…
On global identification in structural vector autoregressions
Emanuele Bacchiocchi, Toru Kitagawa
In a landmark contribution to the structural vector autoregression (SVARs) literature, Rubio-Ramirez, Waggoner, and Zha (2010, `Structural Vector Autoregressions: Theory of Identif…
Who Should Get Vaccinated? Individualized Allocation of Vaccines Over SIR Network
Toru Kitagawa, Guanyi Wang
How to allocate vaccines over heterogeneous individuals is one of the important policy decisions in pandemic times. This paper develops a procedure to estimate an individualized va…
Instrumental Variables Before and LATEr
Toru Kitagawa
The modern formulation of the instrumental variable methods initiated the valuable interactions between economics and statistics literatures of causal inference and fueled new inno…