Report NEP-ETS-2013-08-31

This is the archive for NEP-ETS, a report on new working papers in the area of Econometric Time Series. Yong Yin issued this report. It is usually issued weekly.

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Other reports in NEP-ETS

The following items were announced in this report:

• Nima Nonejad, 2013. "A Mixture Innovation Heterogeneous Autoregressive Model for Structural Breaks and Long Memory," CREATES Research Papers 2013-24, Department of Economics and Business Economics, Aarhus University.
• Nima Nonejad, 2013. "Long Memory and Structural Breaks in Realized Volatility: An Irreversible Markov Switching Approach," CREATES Research Papers 2013-26, Department of Economics and Business Economics, Aarhus University.
• Nima Nonejad, 2013. "Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox," CREATES Research Papers 2013-27, Department of Economics and Business Economics, Aarhus University.
• Kees Jan van Garderen & H. Peter Boswijk, 2013. "Bias correcting adjustment coefficients in a cointegrated VAR with known cointegrating vectors," UvA-Econometrics Working Papers 13-05, Universiteit van Amsterdam, Dept. of Econometrics.
• Arturas Juodis, 2013. "First Difference Transformation in Panel VAR models: Robustness, Estimation and Inference," UvA-Econometrics Working Papers 13-06, Universiteit van Amsterdam, Dept. of Econometrics.
• Maurice J.G. Bun & Frank Kleibergen, 2013. "Identification and inference in moments based analysis of linear dynamic panel data models," UvA-Econometrics Working Papers 13-07, Universiteit van Amsterdam, Dept. of Econometrics.
• D. S. Grebenkov & J. Serror, 2013. "Following a Trend with an Exponential Moving Average: Analytical Results for a Gaussian Model," Papers 1308.5658, arXiv.org.
• Roland Langrock & Th'eo Michelot & Alexander Sohn & Thomas Kneib, 2013. "Semiparametric stochastic volatility modelling using penalized splines," Papers 1308.5836, arXiv.org, revised Jun 2014.
• Sucarrat, Genaro & Grønneberg, Steffen & Escribano, Alvaro, 2013. "Estimation and Inference in Univariate and Multivariate Log-GARCH-X Models When the Conditional Density is Unknown," MPRA Paper 49344, University Library of Munich, Germany.