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subject:"Nonparametric statistics"
~isPartOf:"Working paper / Department of Econometrics and Business Statistics, Monash University"
~person:"Zhao, Xueyan"
~subject:"Bootstrap-Verfahren"
~subject:"Zeitreihenanalyse"
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Nonparametric statistics
Bootstrap-Verfahren
Zeitreihenanalyse
Estimation theory
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Nichtparametrisches Verfahren
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Binary Dependent Variables
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Causality analysis
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Kausalanalyse
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Asymmetric Endogeneity
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Average Treatment Effect
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Endogeneity
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Estimation
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Instrument Relevance
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Partial Identification
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average treatment effect
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binary outcome models
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Zhao, Xueyan
Gao, Jiti
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Peng, Bin
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Poskitt, Donald Stephen
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Dong, Chaohua
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Yan, Yayi
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Koo, Bonsoo
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Nadarajah, K.
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Pan, Guangming
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Silvapulle, Paramsothy
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Vahid, Farshid
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Zhang, Lina
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Bailey, Natalia
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Working paper / Department of Econometrics and Business Statistics, Monash University
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Decomposing identification gains and evaluating instrument identification power for partially identified average treatment effects
Zhang, Lina
;
Frazier, David T.
;
Poskitt, Donald Stephen
; …
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2021
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(updated version of working paper no. 34/20)
Persistent link: https://www.econbiz.de/10012697939
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Decomposing identification gains and evaluating instrument identification power for partially identified average treatment effects
Zhang, Lina
;
Frazier, David T.
;
Poskitt, Donald Stephen
; …
-
2020
Persistent link: https://www.econbiz.de/10012610822
Saved in:
3
The bivariate probit model, maximum likelihood estimation, pseudo true parameters and partial identification
Li, Chuhui
;
Poskitt, Donald Stephen
;
Zhao, Xueyan
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2016
Persistent link: https://www.econbiz.de/10011781773
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