Regression modelVolatility test

Causality in Variance Test

The causality-in-variance test detects whether shocks to one variable cause changes in the conditional variance (volatility) of another variable, distinct from mean-level causality. Introduced by Cheung and Ng (1996), it identifies volatility spillovers and contagion effects—crucial for risk management and understanding financial market interdependencies. This approach has become standard in studying shock transmission across asset classes and geographies.

Apply with EconMindSoonVideoSoon

Read the full method

Members only

Sign in with a free account to read this section.

Sign in

Sources

  1. Cheung, Y. W., & Ng, L. K. (1996). A causality-in-variance test and its application to financial market prices. Journal of Econometrics, 72(1-2), 33-61. DOI: 10.1016/0304-4076(94)01714-X
  2. Hafner, C. M., & Herwartz, H. (2006). Testing for causality in variance using multivariate GARCH models. Journal of Econometrics, 135(1-2), 129-153. DOI: 10.1016/j.jeconom.2005.07.012

Related methods

Referenced by

ScholarGateCausality in Variance Test (Test for Causality in Variance). Retrieved 2026-06-04 from https://scholargate.app/en/econometrics/causality-in-variance-test