Combining Forecasts: An Application to Elections

By Andreas Graefe, J. Armstrong, Randall J. Jones, Alfred G. Cuzán. 2014

170 citations recorded by the source corpus.

Subfields: Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/a9032e6a22ff69bbaf9c402e51114d62ebdad9f3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Science and Operations Research

1. Fotios Petropoulos
2. Rob J Hyndman
3. Konstantinos Nikolopoulos
4. Nikolaos Kourentzes
5. Vassilios Assimakopoulos
6. Spyros Makridakis
7. Evangelos Spiliotis
8. Christoph Bergmeir

Citations in the corpus

• Forecasting the realized range-based volatility using dynamic model averaging approach (2017, background): “Also, this evidence is consistent with Graefe et al. (2014), which states that simple average is expected to perform better.”
• Golden Rule of Forecasting: Be conservative (2015, unknown): “In another example, independently prepared forecasts of U.S. presidential election vote shares are unbiased and extremely accurate (Graefe et al., 2014).”
• Forecasting: theory and practice (2020, background): “Finally, there is need for the results of combined forecasts to be more interpretable and suitable for decision making (Bordignon et al., 2013; Graefe et al., 2014; Barrow and Kourentzes, 2016; Todini, 2018).”
• The Forecast Combination Puzzle: A Simple Theoretical Explanation (2016, background): “Its history is elegantly summarized in Section 4 of Graefe et al. (2014).”