Opening the Black Box: Structural Factor Models Versus Structural Vars

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Do Euro Area Countries Respond Asymmetrically to the Common Monetary Policy (2014, unknown): “We consider here the Structural Dynamic Factor model firstly introduced by Giannone et al. (2005), Stock and Watson (2005), and Forni et al. (2009), which is a development of the model originally proposed by Stock and Watson (2002) and Bai (2003), and it is a particular case of the Generalized…”
Non-Stationary Dynamic Factor Models for Large Datasets (2016, methodology): “The few papers considering estimation of the IRFs in the non-stationary case model instead the dynamics of Ft as a VAR in differences (Stock and Watson, 2005; Forni et al., 2009).”
Generalized dynamic factor models and volatilities: recovering the market volatility shocks (2016, unknown): “Various refinements of that approach have been considered in the literature with the objective of taking better advantage of the dynamic nature of the data (see Stock and Watson, 2005; Bai and Ng, 2007; Forni et al., 2009, to quote only a few).”
Improved penalization for determining the number of factors in approximate factor models (2010, methodology): “In practice, the method they propose is known to often deliver non-robust results as the number of factors can be over- or under- estimated (see e.g. the application on U.S. macroeconomic data in Forni et al., 2009).”