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  • Search: subject:"doubly/locally robust score"
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Year of publication
Subject
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Artificial intelligence 2 Counterfactual analysis 2 Estimation theory 2 Künstliche Intelligenz 2 Robust statistics 2 Robustes Verfahren 2 Schätztheorie 2 debiased machine learning 2 doubly/locally robust score 2 Debiased machine learning 1 Derivat 1 Derivative 1 Doubly/locally robust score 1 Forecasting model 1 Heterogeneity 1 Local average structural derivative 1 Nichtparametrisches Verfahren 1 Nonparametric statistics 1 Prognoseverfahren 1 Regression analysis 1 Regressionsanalyse 1 Semiparametric efficiency bound 1 Statistical distribution 1 Statistische Verteilung 1 Unconditional quantile partial effect 1
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Online availability
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Free 2 CC license 1 Undetermined 1
Type of publication
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Article 3
Type of publication (narrower categories)
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Article in journal 2 Aufsatz in Zeitschrift 2 Article 1
Language
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English 3
Author
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Sasaki, Yuya 2 Ura, Takuya 2 Zhang, Yichong 2 Jin, Zequn 1 Lin, Lihua 1 Zhang, Zhengyu 1
Published in...
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Journal of business & economic statistics : JBES ; a publication of the American Statistical Association 1 Quantitative Economics 1 Quantitative economics : QE ; journal of the Econometric Society 1
Source
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ECONIS (ZBW) 2 EconStor 1
Showing 1 - 3 of 3
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Unconditional quantile regression with high-dimensional data
Sasaki, Yuya; Ura, Takuya; Zhang, Yichong - In: Quantitative Economics 13 (2022) 3, pp. 955-978
This paper considers estimation and inference for heterogeneous counterfactual effects with high-dimensional data. We propose a novel robust score for debiased estimation of the unconditional quantile regression (Firpo, Fortin, and Lemieux (2009)) as a measure of heterogeneous counterfactual...
Persistent link: https://www.econbiz.de/10014537042
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Unconditional quantile regression with high‐dimensional data
Sasaki, Yuya; Ura, Takuya; Zhang, Yichong - In: Quantitative economics : QE ; journal of the … 13 (2022) 3, pp. 955-978
This paper considers estimation and inference for heterogeneous counterfactual effects with high‐dimensional data. We propose a novel robust score for debiased estimation of the unconditional quantile regression (Firpo, Fortin, and Lemieux (2009)) as a measure of heterogeneous counterfactual...
Persistent link: https://www.econbiz.de/10013382057
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Identification and auto-debiased machine learning for outcome-conditioned average structural derivatives
Jin, Zequn; Lin, Lihua; Zhang, Zhengyu - In: Journal of business & economic statistics : JBES ; a … 42 (2024) 4, pp. 1318-1330
Persistent link: https://www.econbiz.de/10015533780
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