*! version 1.0.2 24may2026

Title

asycaus quantile -- Fang, Wang, Shieh & Chung (2026) quantile asymmetric causality (optional Fourier)

Syntax

asycaus quantile depvar causvar [if] [in] [, options]

Description

Combines the asymmetric causality framework (Hatemi-J 2012) with
quantile-VAR estimation (Koenker 2005), as in Fang, Wang, Shieh and
Chung (2026). For each requested quantile tau, a quantile regression is
fitted to the cumulative positive (or negative) components and a Wald test of
non-causality is computed using the asymptotic variance with sparsity
correction.

Optionally the Fourier basis can be projected out first (fourier),
matching the Fang et al. specification where smooth structural breaks are
absorbed by trigonometric expansions before quantile causality is tested.

Options

maxlag(#) max VAR lag (default 4)

ic(string) IC (default hjc)

intorder(#) TY augmentation lags (default 1)

shock(string) pos | neg | both

quantiles(numlist) quantiles in (0,1). Default 0.1 0.25 0.5 0.75 0.9

fourier detrend components with Fourier basis first

kmax(#) max Fourier frequency when fourier is set (default 3)

lnform log of inputs

nograph suppress graph

saving(name) save graph

Examples

webuse lutkepohl2, clear

tsset qtr

asycaus quantile dln_inv dln_inc, quantiles(0.1 0.25 0.5 0.75 0.9)

asycaus quantile dln_inv dln_inc, quantiles(0.1 0.25 0.5 0.75 0.9) fourier kmax(2)

Stored results

r(results) matrix: shock_id, tau, Wald, lag, asy_p, reject5

r(shock) option used

References

Fang, H., Wang, C.-H., Shieh, J. C. P., and Chung, C.-P. (2026). The asymmetric Granger causality between banking-sector and stock-market development and economic growth in quantiles considering Fourier. Applied Economics, 58(20), 3822–3838.

Koenker, R. (2005). Quantile Regression. Cambridge University Press.

Author

Dr Merwan Roudane -- merwanroudane920@gmail.com

See asycaus for the package overview.