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Report NEP-FOR-2016-06-04
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:
- Carlos Medel & Gilmour Camilleri & Hsiang-Ling Hsu & Stefan Kania & Miltiadis Touloumtzoglou, 2016, "Robustness in Foreign Exchange Rate Forecasting Models: Economics-Based Modelling After the Financial Crisis," Working Papers Central Bank of Chile, Central Bank of Chile, number 784, May.
- Wagner Piazza Gaglianone & João Victor Issler & Silvia Maria Matos, 2016, "Applying a Microfounded-Forecasting Approach to Predict Brazilian Inflation," Working Papers Series, Central Bank of Brazil, Research Department, number 436, May.
- Dhanya Jothimani & Ravi Shankar & Surendra S. Yadav, 2016, "Discrete Wavelet Transform-Based Prediction of Stock Index: A Study on National Stock Exchange Fifty Index," Papers, arXiv.org, number 1605.07278, May.
- Markus Jochmann & Gary Koop & Rodney W. Strachan, 2008, "Bayesian Forecasting using Stochastic Search Variable Selection in a VAR Subject to Breaks," Working Paper series, Rimini Centre for Economic Analysis, number 19_08, Jan.
- Francisco Salas-Molina & Francisco J. Martin & Juan A. Rodr'iguez-Aguilar & Joan Serr`a & Josep Ll. Arcos, 2016, "Empowering cash managers to achieve cost savings by improving predictive accuracy," Papers, arXiv.org, number 1605.04219, May.
- Li, Xiaofei & Coble, Keith H. & Tack, Jesse B. & Barnett, Barry J., 2016, "Estimating Site-Specific Crop Yield Response using Varying Coefficient Models," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts, Agricultural and Applied Economics Association, number 235798, DOI: 10.22004/ag.econ.235798.
- MacDonald, Stephen & Ash, Mark, 2016, "Detecting the Sources of Information Rigidity: Analyzing Forecast Bias and Smoothing in USDA’s Soybean Forecasts," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts, Agricultural and Applied Economics Association, number 235349, DOI: 10.22004/ag.econ.235349.