The 2023 Japanese Economic Association Nakahara Prize: Recipient—Prof. Toru Kitagawa, Brown University and University College London

Professor Kitagawa is a leading figure in theoretical econometrics.He has made several creative and fundamental contributions to various fields of econometrics.He has published seminal papers in the relevant literature, and they influence subsequent research including those by the top econometricians.His research on treatment allocation problems is a momentous contribution.Kitagawa and Tetenov (2018) develop and theoretically justify the Empirical Welfare Maximization (EWM) method.In the last decades, we have seen a significant development of causal inference methods in econometrics and their applications in various areas of economics.Arguably, we have now achieved a good understand of how to estimate treatment effects.A natural question, that comes next and would be policy relevant, is how one can decide whether the treatment should be implemented or to whom it should be assigned.EWM allocates the treatment by maximizing an estimated welfare.In traditional plug-in approaches, the treatment effect is first estimated and then the treatment is assigned to maximize the welfare.Instead, EWM directly targets the welfare.This approach has several advantages in terms of both theory and applications.Theoretically, Kitagawa and Tetenov (2018) make connections to rate optimality discussed in the statistical and machine learning literature.In terms of application, it can handle policy constraints in simple manners.Such applicability is appealing compared to another theoretically sophisticated approach based on minimax regret.EWM has caught attention from many researchers, as evidenced by the fact that Econometrica has already published two papers (Athey & Wager, 2021;Mbakop & Tabord-Meehan, 2021) that extend EWM.