scholarly journals Impulse Response Functions from Structural Dynamic Factor Models: A Monte Carlo Evaluation

2006 ◽  
Author(s):  
George Kapetanios ◽  
Massimiliano Giuseppe Marcellino
Keyword(s):  
Monte Carlo ◽  
Impulse Response ◽  
Factor Models ◽  
Dynamic Factor ◽  
Impulse Response Functions ◽  
Response Functions ◽  
Dynamic Factor Models ◽  
Structural Dynamic ◽  
Monte Carlo Evaluation

scholarly journals OPENING THE BLACK BOX: STRUCTURAL FACTOR MODELS WITH LARGE CROSS SECTIONS

2009 ◽  
Vol 25 (5) ◽  
pp. 1319-1347 ◽  
Author(s):  
Mario Forni ◽  
Domenico Giannone ◽  
Marco Lippi ◽  
Lucrezia Reichlin
Keyword(s):  
Impulse Response ◽  
Cross Sections ◽  
Rates Of Convergence ◽  
Factor Models ◽  
Dynamic Factor ◽  
Impulse Response Functions ◽  
Response Functions ◽  
Structural Vector Autoregression ◽  
Dynamic Factor Models ◽  
Identification Schemes

This paper shows how large-dimensional dynamic factor models are suitable for structural analysis. We argue that all identification schemes employed in structural vector autoregression (SVAR) analysis can be easily adapted in dynamic factor models. Moreover, the “problem of fundamentalness,” which is intractable in SVARs, can be solved, provided that the impulse-response functions are sufficiently heterogeneous. We provide consistent estimators for the impulse-response functions and for (n,T) rates of convergence. An exercise with U.S. macroeconomic data shows that our solution of the fundamentalness problem may have important empirical consequences.

VALIDATING DSGE MODELS WITH SVARS AND HIGH-DIMENSIONAL DYNAMIC FACTOR MODELS

2021 ◽  
pp. 1-19
Author(s):  
Marco Lippi
Keyword(s):  
Measurement Errors ◽  
Factor Models ◽  
High Dimensional ◽  
Dynamic Factor ◽  
Dsge Models ◽  
Impulse Response Functions ◽  
Vector Autoregressions ◽  
Dynamic Factor Models ◽  
Structural Shocks ◽  
Dynamic Stochastic

A popular validation procedure for Dynamic Stochastic General Equilibrium (DSGE) models consists in comparing the structural shocks and impulse-response functions obtained by estimation-calibration of the DSGE with those obtained in an Structural Vector Autoregressions (SVAR) identified by means of some of the DSGE restrictions. I show that this practice can be seriously misleading when the variables used in the SVAR contain measurement errors. If this is the case, for generic values of the parameters of the DSGE, the shocks estimated in the SVAR are not “made of” the corresponding structural shocks plus measurement error. Rather, each of the SVAR shocks is contaminated by noncorresponding structural shocks. We argue that High-Dimensional Dynamic Factor Models are free from this drawback and are the natural model to use in validation procedures for DSGEs.

Impulse-response functions and anthropogenic CO2

1995 ◽  
Vol 22 (4) ◽  
pp. 413-416 ◽  
Author(s):  
Francesco N. Tubiello ◽  
Michael Oppenheimer
Keyword(s):  
Impulse Response ◽  
Impulse Response Functions ◽  
Response Functions ◽  
Anthropogenic Co2
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