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~isPartOf:"Econometrics papers"
~isPartOf:"Essays in honor of Aman Ullah"
~isPartOf:"Handbook of applied econometrics and statistical inference"
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Essays in honor of Aman Ullah
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Adapting kernel estimation to uncertain smoothness
Kotlyarova, Yulia
;
Schafgans, Marcia M. A.
; …
-
2011
Persistent link: https://www.econbiz.de/10009531795
Saved in:
2
Smoothness: bias and efficiency of nonparametric kernel estimators
Kotlyarova, Yulia
;
Schafgans, Marcia M. A.
; …
- In:
Essays in honor of Aman Ullah
,
(pp. 561-589)
.
2016
Persistent link: https://www.econbiz.de/10011530328
Saved in:
3
Smoothness adaptive average derivative estimation
Schafgans, Marcia M. A.
(
contributor
); …
-
2008
Persistent link: https://www.econbiz.de/10003805783
Saved in:
4
Inference and testing breaks in nlarge dynamic panels with strong cross sectional dependence
Hidalgo, Javier
;
Schafgans, Marcia M. A.
-
2015
Persistent link: https://www.econbiz.de/10011280123
Saved in:
5
A method of moments estimator for semiparametric index models
Donkers, Bas
(
contributor
); …
-
2005
Persistent link: https://www.econbiz.de/10003048657
Saved in:
6
Selectivity and the gender wage gap decomposition in the presence of a joint decision process
Schafgans, Marcia M. A.
(
contributor
); …
-
2006
Persistent link: https://www.econbiz.de/10003401874
Saved in:
7
Inference without smoothing for large panels with cross-sectional and temporal dependence
Hidalgo, Javier
;
Schafgans, Marcia M. A.
-
2017
Persistent link: https://www.econbiz.de/10011889214
Saved in:
8
A selective review of Aman Ullah's contributions to econometrics
Bao, Yong
;
Fan, Yanqin
;
Su, Liangjun
;
Zinde-Walsh, Victoria
- In:
Essays in honor of Aman Ullah
,
(pp. 3-43)
.
2016
Persistent link: https://www.econbiz.de/10011529941
Saved in:
9
Measurement of the quality of autoregressive approximation, with econometric applications
Galbraith, John W.
;
Zinde-Walsh, Victoria
- In:
Handbook of applied econometrics and statistical inference
,
(pp. 401-421)
.
2002
Persistent link: https://www.econbiz.de/10001701984
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