13 citations · 20 across the 14 of their papers we have counts for
16 papers
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…
Identification and Estimation of Production Function with Unobserved Heterogeneity
Hiroyuki Kasahara, Paul Schrimpf, Michio Suzuki
This paper examines the nonparametric identifiability of production functions, considering firm heterogeneity beyond Hicks-neutral technology terms. We propose a finite mixture mod…
Testing the Number of Components in Finite Mixture Normal Regression Model with Panel Data
Yu Hao, Hiroyuki Kasahara
This paper develops the likelihood ratio-based test of the null hypothesis of a M0-component model against an alternative of (M0 + 1)-component model in the normal mixture panel re…
A Response to Philippe Lemoine's Critique on our Paper "Causal Impact of Masks, Policies, Behavior on Early Covid-19 Pandemic in the U.S."
Victor Chernozhukov, Hiroyuki Kasahara, Paul Schrimpf
Recently, Phillippe Lemoine posted a critique of our paper "Causal Impact of Masks, Policies, Behavior on Early Covid-19 Pandemic in the U.S." [arXiv:2005.14168] at his post titled…
The Association of Opening K-12 Schools with the Spread of COVID-19 in the United States: County-Level Panel Data Analysis
Victor Chernozhukov, Hiroyuki Kasahara, Paul Schrimpf
This paper empirically examines how the opening of K-12 schools and colleges is associated with the spread of COVID-19 using county-level panel data in the United States. Using dat…
Nonparametric Identification of Production Function, Total Factor Productivity, and Markup from Revenue Data
Hiroyuki Kasahara, Yoichi Sugita
Commonly used methods of production function and markup estimation assume that a firm's output quantity can be observed as data, but typical datasets contain only revenue, not outp…
Identification of Regression Models with a Misclassified and Endogenous Binary Regressor
Hiroyuki Kasahara, Katsumi Shimotsu
We study identification in nonparametric regression models with a misclassified and endogenous binary regressor when an instrument is correlated with misclassification error. We sh…
Testing the Order of Multivariate Normal Mixture Models
Hiroyuki Kasahara, Katsumi Shimotsu
Finite mixtures of multivariate normal distributions have been widely used in empirical applications in diverse fields such as statistical genetics and statistical finance. Testing…
Testing the Number of Regimes in Markov Regime Switching Models
Hiroyuki Kasahara, Katsumi Shimotsu
Markov regime switching models have been used in numerous empirical studies in economics and finance. However, the asymptotic distribution of the likelihood ratio test statistic fo…
Asymptotic Properties of the Maximum Likelihood Estimator in Regime Switching Econometric Models
Hiroyuki Kasahara, Katsumi Shimotsu
Markov regime switching models have been widely used in numerous empirical applications in economics and finance. However, the asymptotic distribution of the maximum likelihood est…