Efficiency in Large Dynamic Panel Models with Common Factor
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- Gagliardini, Patrick & Gourieroux, Christian, 2014. "Efficiency In Large Dynamic Panel Models With Common Factors," Econometric Theory, Cambridge University Press, vol. 30(05), pages 961-1020, October.
- Patrick GAGLIARDINI & Christian GOURIEROUX, 2008. "Efficiency in Large Dynamic Panel Models with Common Factor," Swiss Finance Institute Research Paper Series 09-12, Swiss Finance Institute, revised Mar 2009.
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- Matteo Barigozzi & Brownlees Christian & Gallo Giampiero & David Veredas, "undated".
"Disentangling systematic and idiosyncratic risks for large panels of assets,"
ULB Institutional Repository
2013/136237, ULB -- Universite Libre de Bruxelles.
- Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2010. "Disentangling Systematic and Idiosyncratic Risk for Large Panels of Assets," Econometrics Working Papers Archive wp2010_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
- repec:eee:econom:v:201:y:2017:i:2:p:176-197 is not listed on IDEAS
- Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014.
"Disentangling systematic and idiosyncratic dynamics in panels of volatility measures,"
Journal of Econometrics,
Elsevier, vol. 182(2), pages 364-384.
- Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2014. "Disentangling Systematic and Idiosyncratic Dynamics in Panels of Volatility Measures," Econometrics Working Papers Archive 2014_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
- Chen, Liang & Dolado, Juan J. & Gonzalo, Jesús, 2014.
"Detecting big structural breaks in large factor models,"
Journal of Econometrics,
Elsevier, vol. 180(1), pages 30-48.
- Chen, Liang & Dolado, Juan Jose & Gonzalo, Jesus, 2011. "Detecting big structural breaks in large factor models," MPRA Paper 31344, University Library of Munich, Germany.
- Liang Chen & Juan Dolado & Jesus Gonzalo, 2013. "Detecting Big Structural Breaks in Large Factor Models," Economics Series Working Papers 677, University of Oxford, Department of Economics.
- Gonzalo, Jesús & Dolado, Juan José & Chen, Liang, 2011. "Detecting big structural breaks in large factor models," UC3M Working papers. Economics we1141, Universidad Carlos III de Madrid. Departamento de Economía.
- Carlos Perez Montes, 2015. "Estimation of Regulatory Credit Risk Models," Journal of Financial Services Research, Springer;Western Finance Association, vol. 48(2), pages 161-191, October.
- Francesco Audrino & Fulvio Corsi & Kameliya Filipova, 2016.
"Bond Risk Premia Forecasting: A Simple Approach for Extracting Macroeconomic Information from a Panel of Indicators,"
Taylor & Francis Journals, vol. 35(2), pages 232-256, February.
- Francesco Audrino & Fulvio Corsi & Kameliya Filipova, 2010. "Bond Risk Premia Forecasting: A Simple Approach for Extracting¨Macroeconomic Information from a Panel of Indicators," University of St. Gallen Department of Economics working paper series 2010 2010-09, Department of Economics, University of St. Gallen.
- Dhaene, Geert & Jochmans, Koen, 2016.
"Likelihood Inference In An Autoregression With Fixed Effects,"
Cambridge University Press, vol. 32(05), pages 1178-1215, October.
- Geert Dhaene & Koen Jochmans, 2013. "Likelihood inference in an Autoregression with fixed effects," Working Papers hal-01070434, HAL.
- Geert Dhaene & Koen Jochmans, 2013. "Likelihood inference in an Autoregression with fixed effects," Sciences Po publications 2013-07, Sciences Po.
- Geert Dhaene & Koen Jochmans, 2013. "Likelihood inference in an Autoregression with fixed effects," Sciences Po Economics Discussion Papers 2013-07, Sciences Po Departement of Economics.
- Geert Dhaene & Koen Jochmans, 2016. "Likelihood Inference in an Autoregression with Fixed Effects," Sciences Po publications info:hdl:2441/1mc4dip81d9, Sciences Po.
- Torben G. Andersen & Nicola Fusari & Viktor Todorov & Rasmus T. Varneskov, 2018. "Unified Inference for Nonlinear Factor Models from Panels with Fixed and Large Time Span," CREATES Research Papers 2018-03, Department of Economics and Business Economics, Aarhus University.
More about this item
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
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