Why do forecasters disagree? Lessons from the term structure of cross-sectional dispersion
By Andrew J. Patton, Allan G. Timmermann. 2010
325 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/b83d68faaa098ecea7a18055cee9fe654cdd99ad
Citations in the corpus
- Macroeconomic Uncertainty Through the Lens of Professional Forecasters (2019, unknown): “Our choice of prior distributions and their parameter values is very similar to Pitt and Shephard (1999). The prior for factor loadings is the Normal distribution, i.e., λi ∼ N(λ0,Λ0) with λ0 = 1 and Λ0 = 25, as in Pitt and Shephard (1999). The choice of large Λ0 represents a fair degree of uncertai”
- Inattentive professional forecasters (2013, unknown): “Table (4) provides the results for the 1-year rolling forecasts of 19This systematic disagreement pattern can be linked to disagreement stemming from heterogeneity in priors or in models as Patton & Timmermann (2010) put forth.”
- Survey Measurement of Probabilistic Macroeconomic Expectations: Progress and Promise (2017, unknown): “(See, e.g., Diether, Malloy, and Scherbina 2002; Mankiw, Reis, and Wolfers 2004; Patton and Timmermann 2010; Coibion and Gorodnichenko 2012.)”
- Forecast Rationality Tests Based on Multi-Horizon Bounds (2012, unknown): “We also thank seminar participants at the Triangle Econometrics Workshop, Federal Reserve Bank at St. Louis, University of Michigan, Penn, Rice University, UCSD, EC2 conference on real-time econometrics (December, 2009), IIF conference in San Diego (June, 2009), the sixth forecasting symposium at th”