qardlr (version 1.0.1)

qardl_wald: Wald Tests for QARDL Parameter Constancy

Description

Performs Wald tests for parameter constancy across quantiles in a QARDL model. Tests whether parameters are equal across different quantile levels.

Usage

qardl_wald(
  object,
  type = c("all", "beta", "phi", "gamma", "rho"),
  pairwise = FALSE
)

Value

An object of class "qardl_wald" containing:

tests

Data frame of test results with columns: test, statistic, df, pvalue

pairwise_tests

Data frame of pairwise test results (if pairwise = TRUE)

type

Type of test performed

tau

Vector of quantiles

Arguments

object

An object of class "qardl".

type

Character string specifying which parameters to test: "all" (default), "beta" (long-run), "phi" (AR), "gamma" (short-run impact), or "rho" (ECM speed of adjustment).

pairwise

Logical. If TRUE, perform pairwise tests between adjacent quantiles. Default is FALSE.

Details

The Wald test statistic is computed as: $$W = (R\hat{\theta} - r)' [R \hat{V} R']^{-1} (R\hat{\theta} - r) \sim \chi^2(q)$$

where \(R\) is a restriction matrix testing equality across quantiles, \(\hat{\theta}\) is the vector of parameter estimates, and \(\hat{V}\) is the estimated covariance matrix.

References

Cho, J.S., Kim, T.-H., & Shin, Y. (2015). Quantile cointegration in the autoregressive distributed-lag modeling framework. Journal of Econometrics, 188(1), 281-300. tools:::Rd_expr_doi("10.1016/j.jeconom.2015.01.003")

See Also

qardl, print.qardl_wald

Examples

data(qardl_sim)
fit <- qardl(y ~ x1 + x2, data = qardl_sim, tau = c(0.25, 0.50, 0.75), p = 2, q = 2)
wald_results <- qardl_wald(fit)
print(wald_results)

# Pairwise tests
wald_pairwise <- qardl_wald(fit, pairwise = TRUE)
print(wald_pairwise)