I am delighted to announce the details of the 12th Yamakawa Kenjiro Memorial Lecture at the University of Tokyo.



The talks will be delivered by Professor Fredrik Savje (Assistant Professor of Political Science (and Statistics and Data Science) and Resident Fellow, Institution for Social and Policy Studies, Yale University)



(if you have any questions, please contact Nobuhiro Hiwatari <hiwatari@iss.u-tokyo.ac.jp>)



1. The first talk at Hongo Campus

Title: "Average treatment effects in the presence of unknown interference"

Date: May 21 (Monday) 10:25~12:15

Venue: Seminar room 1, Kojima Hall (Economics Research Annex building)

<http://www.e.u-tokyo.ac.jp/fservice/address/map-e.html>



Abstract: "We investigate large-sample properties of treatment effect estimators under unknown interference in randomized experiments. The inferential target is a generalization of the average treatment effect estimand that marginalizes over potential spillover effects. We show that estimators commonly used to estimate treatment effects under no-interference are consistent for the generalized estimand for most experimental designs under limited but otherwise arbitrary and unknown interference. The rates of convergence depend on the rate at which the amount of interference grows and the degree to which it aligns with dependencies in treatment assignment. Importantly for practitioners, the results imply that if one erroneously assumes that units do not interfere in a setting with limited, or even moderate, interference, standard estimators are nevertheless likely to be close to an average treatment effect if the sample is sufficiently large."



Sponsors: CIRJE (Center for International Research on the Japanese Economy), CREPE (Center for Research and Education in Program Evaluation), Center for Comparative Law and Politics, MacMillan Center (Yale University,

Supported by FUTI (Friends of UTokyo, Inc)



2. The second talk at Komaba Campus

Title: "Causality and Data"

Date：May 22 (Tuesday), 17:00-18:30

Venue：Seminar Room, 2nd Floor, Building 101, Komaba Campus, University of Tokyo



Abstract: One of the core enterprises of the social sciences is causality. Scholars ask not only how things are, but also why they are that way. Researchers and policymakers ask how one can intervene in the world to change it; thus, they inquire about the effects of their actions. This talk will focus on how quantitative information ("data") can help us answer these questions. We will start with some ontological aspects of causality. The discussion will focus on a minimal definition of causality that encapsulates some core ideas from several perspectives of causality. The definition is not rich enough to resolve important philosophical disagreements about the nature of causality, but it may be sufficiently precise to allow us to investigate some causal questions empirically. The second part discusses the epistemological consequences of the definition and how may be able to overcome them.



Sponsored by and MacMillan Center, Yale University, HMC (The University of Tokyo, Humanities Center)

Supported by: FUTI (Friends of UTokyo Inc.)

Organised by: UTCP (University of Tokyo, Center of Philosophy)