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

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
20 July 2021 | CWP28/21

Previous version

Testing identifying assumptions in fuzzy regression discontinuity designs

We propose a new specification test for assessing the validity of fuzzy regression discontinuity designs (FRD-validity). […]

Yoichi Arai, Yu-Chin Hsu, Toru Kitagawa, Ismael Mourifié, Yuanyuan Wan
23 March 2021 | CWP16/21

Previous version

Testing identifying assumptions in fuzzy regression discontinuity designs
Yoichi Arai, Yu-Chin Hsu, Toru Kitagawa, Ismael Mourifié, Yuanyuan Wan
20 March 2019 | CWP10/19
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

Previous version

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

Previous version

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

Previous version

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

Previous version