Luca Margaritella
Biträdande universitetslektor
Granger Causality Testing in High-Dimensional VARs: A Post-Double-Selection Procedure
Författare
Summary, in English
We develop an LM test for Granger causality in high-dimensional (HD) vector autoregressive (VAR) models based on penalized least squares estimations. To obtain a test retaining the appropriate size after the variable selection done by the lasso, we propose a post-double-selection procedure to partial out effects of nuisance variables and establish its uniform asymptotic validity. We conduct an extensive set of Monte-Carlo simulations that show our tests perform well under different data generating processes, even without sparsity. We apply our testing procedure to find networks of volatility spillovers and we find evidence that causal relationships become clearer in HD compared to standard low-dimensional VARs.
Avdelning/ar
- Nationalekonomiska institutionen
Publiceringsår
2023
Språk
Engelska
Sidor
915-958
Publikation/Tidskrift/Serie
Journal of Financial Econometrics
Volym
21
Issue
3
Dokumenttyp
Artikel i tidskrift
Förlag
Oxford University Press
Ämne
- Economics
Nyckelord
- Granger causality
- high-dimensional inference
- post-double-selection
- vector autoregressive models
- C55
- C12
- C32
Status
Published
ISBN/ISSN/Övrigt
- ISSN: 1479-8417