Report NEP-ECM-2015-06-05

This is the archive for NEP-ECM, a report on new working papers in the area of Econometrics. Sune Karlsson issued this report. It is usually issued weekly.

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Other reports in NEP-ECM

The following items were announced in this report:

• Marcellino, Massimiliano & Sivec, Vasja, 2015. "Monetary, Fiscal and Oil Shocks: Evidence based on Mixed Frequency Structural FAVARs," CEPR Discussion Papers 10610, C.E.P.R. Discussion Papers.
• Quiroz, Matias & Villani, Mattias & Kohn, Robert, 2015. "Speeding Up Mcmc By Efficient Data Subsampling," Working Paper Series 297, Sveriges Riksbank (Central Bank of Sweden).
• Warne, Anders & Droumaguet, Matthieu & Woźniak, Tomasz, 2015. "Granger causality and regime inference in Bayesian Markov-Switching VARs," Working Paper Series 1794, European Central Bank.
• David Pacini & Frank Windmeijer, 2015. "Moment Conditions for AR(1) Panel Data Models with Missing Outcomes," Bristol Economics Discussion Papers 15/660, School of Economics, University of Bristol, UK.
• Item repec:esx:essedp:767 is not listed on IDEAS anymore

• Giuseppe De Luca & Jan Magnus & Franco Peracchi, 2015. "On the Ambiguous Consequences of Omitting Variables," Tinbergen Institute Discussion Papers 15-061/III, Tinbergen Institute.
• Lippi, Marco & Hallin, Marc & Forni, Mario & Zaffaroni, Paolo, 2015. "Dynamic Factor Models with Infinite-Dimensional Factor Space: Asymptotic Analysis," CEPR Discussion Papers 10618, C.E.P.R. Discussion Papers.
• Item repec:bri:uobdis:15/644 is not listed on IDEAS anymore

• Toshihiro Abe & Christophe Ley, 2015. "A Tractable, Parsimonious and Highly Flexible Model for Cylindrical Data, with Applications," Working Papers ECARES ECARES 2015-20, ULB -- Universite Libre de Bruxelles.
• Tommaso Proietti & Alessandra Luati, 2015. "Generalised partial autocorrelations and the mutual information between past and future," CREATES Research Papers 2015-24, Department of Economics and Business Economics, Aarhus University.
• Antoine Kornprobst & Raphael Douady, 2015. "An Empirical Approach to Financial Crisis Indicators Based on Random Matrices," Papers 1506.00806, arXiv.org, revised Sep 2017.
• Eric Delattre & Richard Moussa, 2015. "On the estimation of causality in a bivariate dynamic probit model on panel data with Stata software. A technical review," THEMA Working Papers 2015-04, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
• Thibault Fally, 2015. "Structural Gravity and Fixed Effects," NBER Working Papers 21212, National Bureau of Economic Research, Inc.
• Fabiana Gomez & David Pacini, 2015. "Counting Biased Forecasters: An Application of Multiple Testing Techniques," Bristol Economics Discussion Papers 15/661, School of Economics, University of Bristol, UK.
• Adam D. Bull, 2015. "Semimartingale detection and goodness-of-fit tests," Papers 1506.00088, arXiv.org, revised Jun 2016.
• Chiu, Ching-Wai (Jeremy) & Mumtaz, Haroon & Pinter, Gabor, 2015. "Forecasting with VAR models: fat tails and stochastic volatility," Bank of England working papers 528, Bank of England.
• Dongkoo Kim & Tae-hwan Rhee & Keunkwan Ryu & Changmock Shin, 2015. "Crowdsourcing of Economic Forecast – Combination of Forecasts Using Bayesian Model Averaging," Ruhr Economic Papers 0546, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
• Camba-Méndez, Gonzalo & Kapetanios, George & Papailias, Fotis & Weale, Martin R., 2015. "An automatic leading indicator, variable reduction and variable selection methods using small and large datasets: Forecasting the industrial production growth for euro area economies," Working Paper Series 1773, European Central Bank.
• Paola Cerchiello & Paolo Giudici, 2015. "A Bayesian h-index: how to measure research impact," DEM Working Papers Series 102, University of Pavia, Department of Economics and Management.
• Riccardo M. Masolo & Alessia Paccagnini, 2015. "Identifying Noise Shocks: a VAR with Data Revisions," Discussion Papers 1510, Centre for Macroeconomics (CFM).