Report NEP-FOR-2015-09-05

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.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-FOR

The following items were announced in this report:

• Lorenzo Boldrini & Eric Hillebrand, 2015. "Supervision in Factor Models Using a Large Number of Predictors," CREATES Research Papers 2015-38, Department of Economics and Business Economics, Aarhus University.
• Guillen, Osmani Teixeira Carvalho & Hecq, Alain & Issler, João Victor & Saraiva, Diogo Vinícius Menezes, 2015. "Forecasting multivariate time series under present-value-model short- and long-run co-movement restrictions," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 763, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
• Mehmet Balcilar & Reneé van Eyden & Josine Uwilingiye & Rangan Gupta, 2014. "The impact of oil price on South African GDP growth: A Bayesian Markov Switching-VAR analysis," Working Papers 15-13, Eastern Mediterranean University, Department of Economics.
• Lorenzo Boldrini & Eric Hillebrand, 2015. "The Forecasting Power of the Yield Curve, a Supervised Factor Model Approach," CREATES Research Papers 2015-39, Department of Economics and Business Economics, Aarhus University.
• Daniya Tlegenova, 2015. "Forecasting Exchange Rates Using Time Series Analysis: The sample of the currency of Kazakhstan," Papers 1508.07534, arXiv.org.
• Mehmet Balcilar & Rangan Gupta & Mawuli Segnon, 2015. "The Role of Economic Policy Uncertainty in Predicting U.S. Recessions: A Mixed-Frequency Markov-Switching Vector Autoregressive Approach," Working Papers 201558, University of Pretoria, Department of Economics.
• Cunha, Ronan & Pereira, Pedro L. Valls, 2015. "Automatic model selection for forecasting Brazilian stock returns," Textos para discussão 398, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
• Florian Ziel & Rick Steinert, 2015. "Electricity Price Forecasting using Sale and Purchase Curves: The X-Model," Papers 1509.00372, arXiv.org, revised Aug 2016.
• Castro, Andressa Souza Campos Monteiro & Issler, João Victor, 2015. "Consumption-Wealth Ratio and Expected Stock Returns: Evidence from Panel Data on G7 Countries," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 767, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
• Gaglianone, Wagner Piazza & Issler, João Victor, 2015. "Microfounded forecasting," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 766, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
• Assarsson, Bengt & Österholm, Pär, 2015. "Do Swedish Consumer Confidence Indicators Do What They Are Intended to Do?," Working Papers 139, National Institute of Economic Research.
• Rocha, Jordano Vieira & Pereira, Pedro L. Valls, 2015. "Forecast comparison with nonlinear methods for Brazilian industrial production," Textos para discussão 397, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
• Benedikt Mandel, 2014. "Contemporary Airport Demand Forecasting: Choice Models and Air Transport Forecasting," International Transport Forum Discussion Papers 2014/7, OECD Publishing.
• Kroujiline, Dimitri & Gusev, Maxim & Ushanov, Dmitry & Sharov, Sergey V. & Govorkov, Boris, 2015. "Forecasting stock market returns over multiple time horizons," MPRA Paper 66175, University Library of Munich, Germany.
• Glaeser, Edward L. & Nathanson, Charles G., 2015. "An Extrapolative Model of House Price Dynamics," Working Paper Series rwp15-012, Harvard University, John F. Kennedy School of Government.
• Lorenzo Boldrini, 2015. "Forecasting the Global Mean Sea Level, a Continuous-Time State-Space Approach," CREATES Research Papers 2015-40, Department of Economics and Business Economics, Aarhus University.
• Niels Erik Kaaber Rasmussen & Peter Stephensen, 2014. "A Microsimulation Model for Educational Forecasting," DREAM Working Paper Series 201402, Danish Rational Economic Agents Model, DREAM.
• G.Levieuge, 2015. "Explaining and forecasting bank loans. Good times and crisis," Working papers 566, Banque de France.
• Matusiak, M. & de Koster, M.B.M. & Saarinen, J., 2015. "Data-driven warehouse optimization," ERIM Report Series Research in Management ERS-2015-008-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
• G.Levieuge, 2015. "the coherence and the predictive content of the French Bank Lending Survey’s indicators (in French)," Working papers 567, Banque de France.
• Kevin Clinton & Charles Freedman & Michel Juillard & Ondrej Kamenik & Douglas Laxton & Hou Wang, 2015. "Inflation-Forecast Targeting; Applying the Principle of Transparency," IMF Working Papers 15/132, International Monetary Fund.
• Tommaso Ciarli & Alex Coad & Ismael Rafols, 2015. "Quantitative Analysis of Technology Futures: A review of Techniques, Uses and Characteristics," SPRU Working Paper Series 2015-23, SPRU - Science Policy Research Unit, University of Sussex Business School.
• Zhi-Qiang Jiang & Askery A. Canabarro & Boris Podobnik & H. Eugene Stanley & Wei-Xing Zhou, 2015. "Early warning of large volatilities based on recurrence interval analysis in Chinese stock markets," Papers 1508.07505, arXiv.org.