ARCH-LM test
This function computes univariate and multivariate ARCH-LM tests for a VAR(p).
arch.test(x, lags.single = 16, lags.multi = 5, multivariate.only = TRUE)
x |
Object of class ‘ |
lags.single |
An integer specifying the lags to be used for the univariate ARCH statistics. |
lags.multi |
An integer specifying the lags to be used for the multivariate ARCH statistic. |
multivariate.only |
If |
The multivariate ARCH-LM test is based on the following regression (the univariate test can be considered as special case of the exhibtion below and is skipped):
vech(\bold{\hat{u}}_t \bold{\hat{u}}_t') = \bold{β}_0 + B_1 vech(\bold{\hat{u}}_{t-1} \bold{\hat{u}}_{t-1}') + … + B_q vech(\bold{\hat{u}}_{t-q} \bold{\hat{u}}_{t-q}' + \bold{v}_t)
whereby \bold{v}_t assigns a spherical error process and vech is the column-stacking operator for symmetric matrices that stacks the columns from the main diagonal on downwards. The dimension of \bold{β}_0 is \frac{1}{2}K(K +1) and for the coefficient matrices B_i with i=1, …, q, \frac{1}{2}K(K +1) \times \frac{1}{2}K(K +1). The null hypothesis is: H_0 := B_1 = B_2 = … = B_q = 0 and the alternative is: H_1: B_1 \neq 0 or B_2 \neq 0 or … B_q \neq 0. The test statistic is:
VARCH_{LM}(q) = \frac{1}{2}T K (K + 1)R_m^2 \quad ,
with
R_m^2 = 1 - \frac{2}{K(K+1)}tr(\hat{Ω} \hat{Ω}_0^{-1}) \quad ,
and \hat{Ω} assigns the covariance matrix of the above defined regression model. This test statistic is distributed as χ^2(qK^2(K+1)^2/4).
A list with class attribute ‘varcheck’ holding the
following elements:
resid |
A matrix with the residuals of the VAR. |
arch.uni |
A list with objects of class ‘ |
arch.mul |
An object with class attribute ‘ |
This function was named arch in earlier versions of package
vars; it is now deprecated. See vars-deprecated too.
Bernhard Pfaff
Doornik, J. A. and D. F. Hendry (1997), Modelling Dynamic Systems Using PcFiml 9.0 for Windows, International Thomson Business Press, London.
Engle, R. F. (1982), Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation, Econometrica, 50: 987-1007.
Hamilton, J. (1994), Time Series Analysis, Princeton University Press, Princeton.
Lütkepohl, H. (2006), New Introduction to Multiple Time Series Analysis, Springer, New York.
data(Canada) var.2c <- VAR(Canada, p = 2, type = "const") arch.test(var.2c)
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