grangersearch: An R Package for Exhaustive Granger Causality Testing with Tidyverse Integration

TL;DR

grangersearch is an R package that simplifies exhaustive Granger causality analysis across multiple time series with integrated visualization and tidyverse compatibility.

Contribution

it introduces a user-friendly R package that automates exhaustive causality testing, lag optimization, and integrates seamlessly with tidyverse tools.

Findings

enables comprehensive pairwise causality analysis

automates lag order selection with visualization

integrates with broom ecosystem for tidy results

Abstract

This paper introduces grangersearch, an R package for performing exhaustive Granger causality searches on multiple time series. The package provides: (1) exhaustive pairwise search across multiple variables, (2) automatic lag order optimization with visualization, (3) tidyverse-compatible syntax with pipe operators and non-standard evaluation, and (4) integration with the broom ecosystem through tidy() and glance() methods. The package wraps the vars infrastructure while providing a simple interface for exploratory causal analysis. We describe the statistical methodology, demonstrate the package through worked examples, and discuss practical considerations for applied researchers.