13 citations · 20 across the 14 of their papers we have counts for
7 papers · 1 filter
Modeling Shipping Emissions: Machine Learning, Engineering, and Policy Counterfactuals
Hiroyuki Kasahara, Allen Peters, Oliver Xu
Machine learning predicts outcomes well, but predictive accuracy does not ensure reliable counterfactual responses. We examine how to combine machine learning and theory for measur…
Testing for Unobserved Heterogeneity in Censored Duration Models: EM Approach
Hiroyuki Kasahara, Hirokazu Matsuyama, Katsumi Shimotsu +1
Ignoring unobserved heterogeneity in duration models biases parameter estimates and invalidates inference, but testing for it is non-regular: the null hypothesis lies on the bounda…
Sequential Estimation of Dynamic Discrete Choice Models with Unobserved Heterogeneity
Ertian Chen, Hiroyuki Kasahara, Katsumi Shimotsu
Unobserved heterogeneity is empirically central in dynamic discrete choice models but computationally costly to incorporate: estimation requires repeatedly solving fixed-point equa…
When Is GMM Actually LATE? Weighting Matrices and Causal Interpretation in Overidentified IV
Chun Pang Chow, Hiroyuki Kasahara
Under heterogeneous treatment effects, the weighting matrix of overidentified IV-GMM selects the estimand, not just its precision. We characterize the selection exactly: for any pa…
Gender-Specific Effects of Prenatal Famine Exposure on Educational Attainment: Accounting for Selective Mortality
Hiroyuki Kasahara, Weina Zhou
Selective mortality and fertility issues are persistent challenges in estimating the fetal origin effect, with attempts to address these issues being notably scarce. Evidence furth…
Identification and Estimation of Production Function and Consumer Demand Function under Monopolistic Competition from Revenue Data
Chun Pang Chow, Hiroyuki Kasahara, Yoichi Sugita
We establish nonparametric identification of production functions, total factor productivity (TFP), price markups, and firms' output prices and quantities, as well as consumer dema…
Event-Study Designs for Discrete Outcomes with Latent Transition Heterogeneity
Young Ahn, Hiroyuki Kasahara
We develop an identification strategy for average treatment effects on the treated (ATT) in panel data with discrete outcomes. For such outcomes, the parallel trends assumption und…