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Second order approximation in a linear regression with heteroskedasticity of unknown form
Linton, Oliver
- In:
Econometric reviews
15
(
1996
)
1
,
pp. 1-32
Persistent link: https://www.econbiz.de/10001197549
Saved in:
2
Nonparametric Euler equation identi cation and estimation
Escanciano, Juan Carlos
;
Hoderlein, Stefan
;
Lewbel, Arthur
-
2015
Persistent link: https://www.econbiz.de/10011455563
Saved in:
3
Estimation of a multiplicative covariance structure in the large dimensional case
Hafner, Christian M.
;
Linton, Oliver
;
Tang, Haihan
-
2016
Persistent link: https://www.econbiz.de/10011565160
Saved in:
4
Testing conditional independence restrictions
Linton, Oliver
;
Gozalo, Pedro L.
- In:
Econometric reviews
33
(
2014
)
5/6
,
pp. 523-552
Persistent link: https://www.econbiz.de/10010360794
Saved in:
5
Semiparametric nonlinear panel data models with measurement error
Linton, Oliver
;
Shiu, Ji-Liang
-
2019
Persistent link: https://www.econbiz.de/10012692254
Saved in:
6
Efficient estimation of nonparametric regression in the presence of dynamic heteroskedasticity
Linton, Oliver
;
Xiao, Zhijie
-
2019
Persistent link: https://www.econbiz.de/10012692312
Saved in:
7
Standard errors for nonparametric regression
Chu, Ba
;
Jacho-Chávez, David Tomás
;
Linton, Oliver
- In:
Econometric reviews
39
(
2020
)
7
,
pp. 674-690
Persistent link: https://www.econbiz.de/10012262514
Saved in:
8
The lower regression function and testing expectation dependence dominance hypotheses
Linton, Oliver
;
Whang, Yoon-jae
;
Yen, Yu-min
- In:
Econometric reviews
40
(
2021
)
8
,
pp. 709-727
Persistent link: https://www.econbiz.de/10012624535
Saved in:
9
Estimation of a multiplicative correlation structure in the large dimensional case
Hafnery, Christian
;
Linton, Oliver
;
Tang, Haihan
-
2018
Persistent link: https://www.econbiz.de/10012671159
Saved in:
10
The lower regression function and testing expectation dependence dominance hypotheses
Linton, Oliver
;
Whang, Yoon-jae
;
Yen, Yu-min
-
2018
Persistent link: https://www.econbiz.de/10012671331
Saved in:
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