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subject:"Volatility"
type_genre:"Article in journal"
~isPartOf:"Applied economics"
~isPartOf:"Economics letters"
~isPartOf:"Journal of forecasting"
~isPartOf:"Metrika : international journal for theoretical and applied statistics"
~isPartOf:"Statistical papers"
~person:"Parmeter, Christopher F."
~person:"Toutenburg, Helge"
~subject:"Estimation"
~subject:"Schätztheorie"
~subject:"Statistical distribution"
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Volatility
Estimation
Schätztheorie
Statistical distribution
Estimation theory
13
Regression analysis
5
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5
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5
Theory
5
Nichtparametrisches Verfahren
4
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3
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Parmeter, Christopher F.
Toutenburg, Helge
Baltagi, Badi H.
13
Krämer, Walter
13
Hahn, Jinyong
10
Tran-van-Hoa
10
Ullah, Aman
10
Giles, David E. A.
9
Ohtani, Kazuhiro
9
Wooldridge, Jeffrey M.
9
Li, Qi
8
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7
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7
Srivastava, Virendra K.
7
Stengos, Thanasēs
7
Han, Chirok
6
Shin, Dong-wan
6
Westerlund, Joakim
6
Zhang, Xinyu
6
Kim, Jong-Min
5
Lee, Lung-fei
5
Leybourne, Stephen James
5
Liu, Long
5
Pesaran, M. Hashem
5
Phillips, Garry D. A.
5
Silva, João Santos
5
Song, Seuck-heun
5
Su, Liangjun
5
Tsionas, Efthymios G.
5
Tu, Yundong
5
Abeysinghe, Tilak
4
Anatolyev, Stanislav
4
Godfrey, L. G.
4
Haldrup, Niels
4
Hall, Alastair R.
4
Henderson, Daniel J.
4
Hwang, Eunju
4
Kapetanios, George
4
King, Maxwell L.
4
Kiviet, J. F.
4
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Applied economics
Economics letters
Journal of forecasting
Metrika : international journal for theoretical and applied statistics
Statistical papers
Journal of productivity analysis
5
Journal of applied econometrics
3
Journal of productivity analysis : an official journal of the International Society for Efficiency and Productivity Analysis
3
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2
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2
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2
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1
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ECONIS (ZBW)
13
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1
The "wrong skewness" problem : moment constrained maximum likelihood estimation of the stochastic frontier model
Zhao, Shirong
;
Parmeter, Christopher F.
- In:
Economics letters
221
(
2022
),
pp. 1-5
Persistent link: https://www.econbiz.de/10014229929
Saved in:
2
Smooth coefficient estimation of stochastic frontier models
Lopez Gomez, Daniel
;
Parmeter, Christopher F.
- In:
Economics letters
193
(
2020
),
pp. 1-5
Persistent link: https://www.econbiz.de/10012509120
Saved in:
3
Quantile estimation of the stochastic frontier model
Jradi, Samah
;
Parmeter, Christopher F.
;
Ruggiero, John
- In:
Economics letters
182
(
2019
),
pp. 15-18
Persistent link: https://www.econbiz.de/10012122414
Saved in:
4
Pseudolikelihood estimation of the stochastic frontier model
Andor, Mark Andreas
;
Parmeter, Christopher F.
- In:
Applied economics
49
(
2017
)
55
,
pp. 5651-5661
Persistent link: https://www.econbiz.de/10011845285
Saved in:
5
When is it justifiable to ignore explanatory variable endogeneity in a regression model?
Ashley, Richard A.
;
Parmeter, Christopher F.
- In:
Economics letters
137
(
2015
),
pp. 70-74
Persistent link: https://www.econbiz.de/10011436234
Saved in:
6
A consistent bootstrap procedure for nonparametric symmetry tests
Henderson, Daniel J.
;
Parmeter, Christopher F.
- In:
Economics letters
131
(
2015
),
pp. 78-82
Persistent link: https://www.econbiz.de/10011422658
Saved in:
7
A simple estimator for partial linear regression with endogenous nonparametric variables
Delgado, Michael S.
;
Parmeter, Christopher F.
- In:
Economics letters
124
(
2014
)
1
,
pp. 100-103
Persistent link: https://www.econbiz.de/10010490581
Saved in:
8
The effect of measurement error on the estimated shape of the world distribution of income
Parmeter, Christopher F.
- In:
Economics letters
100
(
2008
)
3
,
pp. 373-376
Persistent link: https://www.econbiz.de/10003768787
Saved in:
9
Use of minimum risk approach in the estimation of regression models with missing observations
Toutenburg, Helge
;
Shalabh, ...
- In:
Metrika : international journal for theoretical and …
54
(
2001
)
3
,
pp. 247-259
Persistent link: https://www.econbiz.de/10001648259
Saved in:
10
Weighted modified first order regression procedures for estimation in linear models with missing X-observations
Toutenburg, Helge
;
Fieger, Andreas
;
Srivastava, Vijay …
- In:
Statistical papers
40
(
1999
)
3
,
pp. 351-361
Persistent link: https://www.econbiz.de/10001401671
Saved in:
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