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20152026
most citedEstimation and Inference for Moments of Ratios with Robustness against Large Trimming Bias

9 citations · 41 across the 18 of their papers we have counts for

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5 papers · 1 filter

stat.ME2018★ 5 cited

Identification and Inference of Network Formation Games with Misclassified Links

Luis E. Candelaria, Takuya Ura

This paper considers a network formation model when links are potentially misclassified. We focus on a game-theoretical model of strategic network formation with incomplete informa…

stat.ME2017★ 9 cited

Estimation and Inference for Moments of Ratios with Robustness against Large Trimming Bias

Yuya Sasaki, Takuya Ura

Empirical researchers often trim observations with small denominator A when they estimate moments of the form E[B/A]. Large trimming is a common practice to mitigate variance, but…

stat.ME2017

Non-separable Models with High-dimensional Data

Liangjun Su, Takuya Ura, Yichong Zhang

This paper studies non-separable models with a continuous treatment when the dimension of the control variables is high and potentially larger than the effective sample size. We pr…

stat.ME2016★ 4 cited

Instrumental Variable Quantile Regression with Misclassification

Takuya Ura

This paper considers the instrumental variable quantile regression model (Chernozhukov and Hansen, 2005, 2013) with a binary endogenous treatment. It offers two identification resu…

stat.ME2016

Inference in Dynamic Discrete Choice Problems under Local Misspecification

Federico A. Bugni, Takuya Ura

Single-agent dynamic discrete choice models are typically estimated using heavily parametrized econometric frameworks, making them susceptible to model misspecification. This paper…