FAVARFactor Augmented Vector Autoregressive
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2005), we use a FAVAR approach to study the influence that financial conditions from developed and emerging economies may have on Colombia's macroeconomic variables.
If this is not the case, the equation (1) is called FAVAR.
Although we theoretically expect that the behavior of a small economy have no effect on the performance of the stock markets of developed economies, we estimate the effects of the SMDI on GDP using a bivariate FAVAR without imposing strong exogeneity assumptions; that is, considering that Colombia's economic activity may affect the stock market performance of developed countries.
This paper advances in this direction applying a FAVAR approach.
As noted earlier, we augment our FAVAR model with eight or nine factors.
In the full sample, the FAVAR models generally do not forecast PCE inflation as well as the AO model.
Table 4 clearly indicates that adding the inflation expectations factor to the FAVAR model produces markedly smaller RMSEs for both inflation measures than either the AO or AR(12) models.
Los modelos FAVAR tienen su origen en los trabajos de Bernanke y Boivin (2003) y Bernanke et al.
De esta forma, los modelos FAVAR evitarian los problemas de grados de libertad que suelen afectar a los VAR estandar al intentar considerar un mayor numero de variables (21).
Dado que el modelo FAVAR contiene al VAR estandar seria posible comparar los resultados obtenidos en ambos modelos y evaluar la contribucion marginal de la informacion adicional incluida en los Ft (factores no observables que deben ser estimados).
Del Negro and Otrok (2007), Vargas-Silva (2008b), and Gupta and Kabundi (2010) employ FAVAR models in their analyses.
Gupta and Ka bundi (2010) use the FAVAR approach, which also accommodates large number of economic variables, and find similar results.