The Generalized Dynamic Factor Model

By M. Forni, Marc Hallin, Marco Lippi, L. Reichlin. 2005

106 citations recorded by the source corpus.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/a1756053ad3d4fa6f9e8224e3ef457483f0e0d2c

Citations in the corpus

• Principal Component Analysis of High-Frequency Data (2016, unknown): “The above factor models are static, as opposed to the dynamic factor models discussed in Forni et al. (2000, 2004), Forni and Lippi (2001), and their recent extensions with infinite-dimensional factor space discussed in Forni et al. (2015, 2017), for which frequency domain PCA is applied.”
• Are Disaggregate Data Useful for Factor Analysis in Forecasting French GDP (2010, unknown): “Forni et al. (2004, 2005) To estimate the dynamic factors and their covariances, FHLR(2000, 2001, 2004, 2005) propose dynamic principal analysis in the frequency domain.”
• A two-step estimator for large approximate dynamic factor models based on Kalman filtering (2011, unknown): “As suggested by Forni et al. 2005, the VAR coefficients A0(L) can be estimated by OLS regression of Ĝt, on its own past.”
• Estimating and Forecasting the Euro Area Monthly National Accounts from a Dynamic Factor Model (2010, unknown): “9 ECB Working Paper Series No 953 October 2008 The fact that the dynamics of the latent factors is modelled explicitly, is a speci c feature of this model against alternative DFM versions (e.g. Stock and Watson, 2002: Forni et al., 2000, 2005).”
• Large Bayesian vector auto regressions (2010, unknown): “…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 Watson,…”
• A new core inflation indicator for New Zealand (2012, unknown): “For all the dynamic factor models estimated in this paper, we set M = √ T , as in Forni et al. (2005).”
• Determining the Number of Primitive Shocks in Factor Models (2007, unknown): “(2001), Stock and Watson (2002a), Forni et al. (2005) , Forni and Lippi (2001), Bai and Ng”
• Macroeconomic forecast accuracy in a data‐rich environment (2019, unknown): “DFM Contrary to the FAVAR(MA) approach, Forni et al. (2005) propose to use a nonparametric estimate of the common component to forecast the series of interest.6 The forecasting formula for the idiosyncratic component remains the same.”