Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: http://hdl.handle.net/10419/203656
Autoren: 
Bertsche, Dominik
Brüggemann, Ralf
Kascha, Christian
Datum: 
2019
Schriftenreihe/Nr.: 
Beiträge zur Jahrestagung des Vereins für Socialpolitik 2019: 30 Jahre Mauerfall - Demokratie und Marktwirtschaft - Session: Econometrics - Time Series No. A04-V3
Zusammenfassung: 
We represent the dynamic relation among variables in vector autoregressive (VAR) models as directed graphs. Based on these graphs, we identify so-called strongly connected components (SCCs). Using this graphical representation, we consider the problem of variable selection. We use the relations among the strongly connected components to select variables that need to be included in a VAR if interest is in forecasting or impulse response analysis of a given set of variables. We show that the set of selected variables from the graphical method coincides with the set of variables that is multi-step causal for the variables of interest by relating the paths in the graph to the coefficients of the "direct" VAR representation. Empirical applications illustrate the usefulness of the suggested approach: Including the selected variables into a small US monetary VAR is useful for impulse response analysis as it avoids the well-known "price-puzzle". We also find that including the selected variables into VARs typically improves forecasting accuracy at short horizons.
Schlagwörter: 
Vector autoregression
Variable selection
Directed graphs
Multi-step causality
Forecasting
Impulse response analysis
JEL: 
C32
C51
C55
E52
Dokumentart: 
Conference Paper

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