2019/02/28 by Alain Hecq, Hecq, Alain, Luca Margaritella +3
Economics, Econometrics and Finance · Mathematics · #Econometrics (econ.EM) #Economic Policies and Impacts #FOS: Computer and information sciences #FOS: Economics and business #Market Dynamics and Volatility #Methodology (stat.ME) #Monetary Policy and Economic Impact #econ.EM #stat.ME
paper · pdf · doi:10.48550/arxiv.1902.10991
openalex publication_date 2019/02/28 · arxiv created 2020/12/04 · arxiv updated 2020/12/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We develop an LM test for Granger causality in high-dimensional 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 high-dimensional compared to standard low-dimensional VARs.