Research Staff

Toru Kitagawa

cemmap and University College London

Toru is a research staff member at the Centre for Microdata Methods and Practice (cemmap) and is also a Lecturer (Assistant Professor) in Economics. He has previously taught Microeconomectrics and Econometrics for Policy.

Selected Publications

A note on global identification in structural vector autoregressions

In a landmark contribution to the structural vector autoregression (SVARs) literature, Rubio-Ramirez, Waggoner, and Zha (2010, […]

Emanuele Bacchiocchi, Toru Kitagawa
17 February 2021 | CWP03/21
Non-Bayesian updating in a social learning experiment

In our laboratory experiment, subjects, in sequence, have to predict the value of a good. The […]

Roberta De Filippis, Antonio Guarino, Philippe Jehiel, Toru Kitagawa
14 December 2020 | CWP60/20

Previous version

Non-Bayesian updating in a social learning experiment
Roberta De Filippis, Antonio Guarino, Philippe Jehiel, Toru Kitagawa
4 July 2018 | CWP39/18
Who should get vaccinated? Individualized allocation of vaccines over SIR network

How to allocate vaccines over heterogeneous individuals is one of the important policy decisions in pandemic […]

Toru Kitagawa, Guanyi Wang
14 December 2020 | CWP59/20
Inference on winners

Many empirical questions concern target parameters selected through optimization. For example, researchers may be interested in […]

Isaiah Andrews, Toru Kitagawa, Adam McCloskey
7 September 2020 | CWP43/20

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Inference on winners
Isaiah Andrews, Toru Kitagawa, Adam McCloskey
31 December 2018 | CWP73/18
Locally- but not globally-identified SVARs

This paper analyzes Structural Vector Autoregressions (SVARs) where identification of structural parameters holds locally but not […]

Emanuele Bacchiocchi, Toru Kitagawa
27 July 2020 | CWP40/20
Uncertain Identification

Uncertainty about the choice of identifying assumptions is common in causal studies, but is often ignored […]

Raffaella Giacomini, Toru Kitagawa, Alessio Volpicella
6 July 2020 | CWP33/20

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Uncertain identification
Raffaella Giacomini, Toru Kitagawa, Alessio Volpicella
18 April 2017 | CWP18/17
Inference after Estimation of Breaks

In an important class of econometric problems, researchers select a target parameter by maximizing the Euclidean […]

Isaiah Andrews, Toru Kitagawa, Adam McCloskey
6 July 2020 | CWP34/20

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Inference after estimation of breaks
Isaiah Andrews, Toru Kitagawa, Adam McCloskey
15 October 2019 | CWP51/19
The Identification Region of the Potential Outcome Distributions under Instrument Independence

This paper examines the identifying power of instrument exogeneity in the treatment effect model. We derive […]

Toru Kitagawa
21 May 2020 | CWP23/20

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Robust Bayesian inference for set-identified models

This paper reconciles the asymptotic disagreement between Bayesian and frequentist inference in set-identified models by adopting […]

Raffaella Giacomini, Toru Kitagawa
15 April 2020 | CWP12/20

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Robust Bayesian inference for set-identified models
Raffaella Giacomini, Toru Kitagawa
7 November 2018 | CWP61/18
Robust Bayesian inference in proxy SVARs

We develop methods for robust Bayesian inference in structural vector autoregressions (SVARs) where the parameters of […]

Raffaella Giacomini, Toru Kitagawa, Matthew Read
15 April 2020 | CWP13/20

Previous version

Robust Bayesian Inference in Proxy SVARs
Raffaella Giacomini, Toru Kitagawa, Matthew Read
23 July 2019 | CWP38/19