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Luca Margaritella . Photo

Luca Margaritella

Associate senior lecturer

Luca Margaritella . Photo

Granger Causality Testing in High-Dimensional VARs: A Post-Double-Selection Procedure

Author

  • Alain Hecq
  • Luca Margaritella
  • Stephan Smeekes

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.

Department/s

  • Department of Economics

Publishing year

2023

Language

English

Pages

915-958

Publication/Series

Journal of Financial Econometrics

Volume

21

Issue

3

Document type

Journal article

Publisher

Oxford University Press

Topic

  • Economics

Keywords

  • Granger causality
  • high-dimensional inference
  • post-double-selection
  • vector autoregressive models
  • C55
  • C12
  • C32

Status

Published

ISBN/ISSN/Other

  • ISSN: 1479-8417