Short-Term Inflation Projections: A Bayesian Vector Autoregressive Approach

By Domenico Giannone, M. Lenza, Daphne Momferatou, Luca Onorante. 2014

139 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/86d7a9d1a3bc5d1d3a5a02dbab2ca8360d325d1b

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In Economics and Econometrics

Citations in the corpus

An Inflation-Predicting Measure of the Output Gap in the Euro Area (2018, methodology): “The small-scale Phillips curve model of Kuttner (1994) initiated this literature. Planas et al. (2008) estimate a Bayesian version of Kuttner’s model and we build on their priors.”
Adaptive Shrinkage in Bayesian Vector Autoregressive Models (2019, background): “Especially in large models, variants of the priors discussed have been particularly successful in forecasting applications (Carriero, Kapetanios, and Marcellino 2009; Bańbura, Giannone, and Reichlin 2010; Carriero, Kapetanios, and Marcellino 2012; Koop 2013; Giannone et al. 2014).”
Combining expert forecasts: Can anything beat the simple average? (2013, methodology): “10 Our real time data is fully consistent with the estimates in the real time database of the Euro Area Business Cycle Network as described in Giannone et al. (2010a). 11 The importance of such data revisions for the euro area is similar to the evidence for the US which is reviewed in Croushore and ”
Conditional Forecasts and Scenario Analysis with Vector Autoregressions for Large Cross-Sections (2015, background): “Factor models are appealing also because many popular economic models can be cast in their format.”
Large time-varying parameter VARs (2013, background): “Many recent papers (see, among many others, Banbura et al., 2010; Carriero et al., 2011, 2009;Giannone et al., 2010; Koop, 2013) have found large VARs, which have dozens or even hundreds of dependent variables, to forecast well.”