Report NEP-FOR-2016-06-09

This is the archive for NEP-FOR, a report on new working papers in the area of Forecasting. Rob J Hyndman issued this report. It is usually issued weekly.

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Other reports in NEP-FOR

The following items were announced in this report:

• Carlos Medel, 2016. "Forecasting Inflation with the Hybrid New Keynesian Phillips Curve: A Compact-Scale Global VAR Approach," Working Papers Central Bank of Chile 785, Central Bank of Chile.
• Thomadakis, Apostolos, 2016. "Do Combination Forecasts Outperform the Historical Average? Economic and Statistical Evidence," MPRA Paper 71589, University Library of Munich, Germany.
• Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland, Institute for Economies in Transition.
• Deryugina, Elena & Ponomarenko, Alexey, 2014. "A large Bayesian vector autoregression model for Russia," BOFIT Discussion Papers 22/2014, Bank of Finland, Institute for Economies in Transition.
• Alessandro Spelta, 2016. "Stock prices prediction via tensor decomposition and links forecast," DISCE - Working Papers del Dipartimento di Economia e Finanza def041, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
• Porshakov, Alexey & Deryugina, Elena & Ponomarenko, Alexey & Sinyakov, Andrey, 2015. "Nowcasting and short-term forecasting of Russian GDP with a dynamic factor model," BOFIT Discussion Papers 19/2015, Bank of Finland, Institute for Economies in Transition.
• Porth, Lysa & Tan, Ken Seng & Zhu, Wenjun, 2016. "A Relational Model for Predicting Farm-Level Crop Yield Distributions in the Absence of Farm-Level Data," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236278, Agricultural and Applied Economics Association.
• Man Chung Fung & Gareth W. Peters & Pavel V. Shevchenko, 2016. "A unified approach to mortality modelling using state-space framework: characterisation, identification, estimation and forecasting," Papers 1605.09484, arXiv.org.
• Achim Zeileis & Christoph Leitner & Kurt Hornik, 2016. "Predictive Bookmaker Consensus Model for the UEFA Euro 2016," Working Papers 2016-15, Faculty of Economics and Statistics, Universität Innsbruck.
• Nicol'o Musmeci & Tomaso Aste & Tiziana Di Matteo, 2016. "What does past correlation structure tell us about the future? An answer from network filtering," Papers 1605.08908, arXiv.org.