399 citations · 441 across the 9 of their papers we have counts for
10 papers
A LATE-Targeting Experimental Design for Multi-Arm RCTs
Tetsuya Kaji
We study the design of multi-arm experiments that identify local average treatment effects under imperfect compliance. With three or more arms, conventional randomization fails to…
The Hellinger Bounds on the Kullback-Leibler Divergence and the Bernstein Norm
Tetsuya Kaji
The Kullback-Leibler divergence, the Kullback-Leibler variation, and the Bernstein "norm" are used to quantify discrepancies among probability distributions in likelihood models su…
Why Do the Elderly Save? Using Health Shocks to Uncover Bequests Motives
Tetsuya Kaji, Elena Manresa
We revisit the saving behavior of elderly singles using an adversarial structural estimation framework by Kaji, Manresa and Pouliot (2023). The method bridges the simulated method…
Assessing Heterogeneity of Treatment Effects
Tetsuya Kaji, Jianfei Cao
Heterogeneous treatment effects are of major interest in economics. For example, a poverty reduction measure would be best evaluated by its effects on those who would be poor in th…
Approximate Bayesian Computation via Classification
Yuexi Wang, Tetsuya Kaji, Veronika Ročková
Approximate Bayesian Computation (ABC) enables statistical inference in simulator-based models whose likelihoods are difficult to calculate but easy to simulate from. ABC construct…
Metropolis-Hastings via Classification
Tetsuya Kaji, Veronika Rockova
This paper develops a Bayesian computational platform at the interface between posterior sampling and optimization in models whose marginal likelihoods are difficult to evaluate. I…
An Adversarial Approach to Structural Estimation
Tetsuya Kaji, Elena Manresa, Guillaume Pouliot
We propose a new simulation-based estimation method, adversarial estimation, for structural models. The estimator is formulated as the solution to a minimax problem between a gener…
Asymptotic Theory of -Statistics and Integrable Empirical Processes
Tetsuya Kaji
This paper develops asymptotic theory of integrals of empirical quantile functions with respect to random weight functions, which is an extension of classical -statistics. They…
Theory of Weak Identification in Semiparametric Models
Tetsuya Kaji
We provide general formulation of weak identification in semiparametric models and an efficiency concept. Weak identification occurs when a parameter is weakly regular, i.e., when…
Extremal Quantile Regression: An Overview
Victor Chernozhukov, Iván Fernández-Val, Tetsuya Kaji
Extremal quantile regression, i.e. quantile regression applied to the tails of the conditional distribution, counts with an increasing number of economic and financial applications…