*! version 1.0.0 16may2026

Title

qqgcause -- Nonparametric Quantile Granger Causality

Syntax

qqgcause effect cause [if] [in] [, options]

tau(numlist) τ grid (default 0.05(0.05)0.95)

type(string) mean or variance (default mean)

bandwidth(#) base bandwidth (Silverman by default)

saving(filename) save results .dta

replace overwrite

noprogress suppress progress

Description

Implements the nonparametric quantile Granger-causality test of
Jeong, Härdle & Song (2012) as adapted by Balcilar et al. (2016).
Tests whether cause_ Granger-causes effect_t in the τ-quantile.
type(variance) tests second-moment (volatility) spillover.

Under H₀ (no causality), the statistic is asymptotically N(0,1).
Critical values: 10% = 1.645, 5% = 1.96, 1% = 2.58.

Saved dataset format

Columns: tau tstat p sig5 sig1.

Example

. qqgcause sp500 oil, saving(cause.dta) replace

. qqcauseplot using cause.dta, title("Oil -> S&P 500")

. qqgcause sp500 oil, type(variance) saving(cause_var.dta) replace

References

Jeong, Härdle & Song (2012). Econometric Theory 28(4).

Balcilar et al. (2016). Resources Policy 49.

See also

qqcauseplot, qqr