Comparing Alternative Predictors Based on Large-Panel Factor Models

By Antonello D’Agostino, Domenico Giannone. 2012

204 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/8fe8aa1597200e162f66076d688205fc172cced6

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Citations in the corpus

Large Bayesian VARs (2008, unknown): “Those models have been successfully applied both in the context of forecasting (Bernanke and Boivin, 2003; Boivin and Ng, 2005; D’Agostino and Giannone, 2006; Forni, Hallin, Lippi, and Reichlin, 2005, 2003; Giannone, Reichlin, and Sala, 2004; Marcellino, Stock, and Watson, 2003; Stock and Watson,…”
Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics (2016, methodology): “Del Negro and Otrok (2008) show how the model can instead be estimated by numerical Bayes methods. Papers that apply this algorithm or variants to DFMs with time-varying parameters include Mumtaz and Surico (2012), Bjørnland and Thorsrud (2015a), and Stock and Watson (2015).”
Factor-Midas for Now- and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP (2010, unknown): “As an alternative to these approaches, we also consider an unrestricted lag order model ytm+hm = 0 +D(Lm)b F((3)) tm + "tm+hm ; (16) where D(Lm) = PK k=0DkL k m is an unrestricted lag polynomial of order K.”
Phillips Curve Inflation Forecasts (2008, background): “Additional papers which use estimated factors to forecast inflation include Watson (2003), Bernanke, Bovin, and Elias (2005), Boivin and Ng (2005, 2006), D’Agostino and Giannone (2006), Giaccomini and White (2006).”
Large Bayesian vector auto regressions (2010, methodology): “Those models have been successfully applied both in the context of forecasting (Bernanke and Boivin, 2003; Boivin and Ng, 2005; D’Agostino and Giannone, 2006; Forni et al., 2003, 2005; Giannone et al., 2004; Marcellino et al., 2003; Stock and Watson, 2002a,b) and structural analysis (Stock and…”
Are Disaggregate Data Useful for Factor Analysis in Forecasting French GDP (2010, methodology): “Using a large panel of US macroecon mic variables, Stock and Watson (2006) and D’Agostino and Giannone (2007) find that SW and FHLR methods perform similarly, while Boivin and Ng (2005) find that SW’s method largely outperforms the FHLR’s and, in particular, they conjecture that the dynamic…”