Schmidt and Phillips Unit Root Test

Performs the Schmidt and Phillips unit root test, where under the Null and Alternative Hypothesis the coefficients of the deterministic variables are included.

Usage

ur.sp(y, type = c("tau", "rho"), pol.deg = c(1, 2, 3, 4),
      signif = c(0.01, 0.05, 0.1))

Arguments

y: Vector to be tested for a unit root.
type: Test type, either tau or rho test.
pol.deg: Degree of polynomial in the test regression.
signif: Significance level for the critical value of the test statistic.

Details

Under the Null and the Alternative hypothesis the coefficients of the deterministic part of the test regression are included. Two test types are available: the rho-test and the tau-test. Both test are extracted from the LM principle.

Value

An object of class "ur.sp".

References

Schmidt, P. and Phillips, P.C.B. (1992), LM Test for a Unit Root in the Presence of Deterministic Trends, Oxford Bulletin of Economics and Statistics, 54(3), 257–287.

Download possible at: https://cowles.yale.edu/, see rubric 'Discussion Papers (CFDPs)'.

Author

Bernhard Pfaff

Examples

data(nporg)
gnp <- na.omit(nporg[, "gnp.r"])
sp.gnp <- ur.sp(gnp, type="tau", pol.deg=1, signif=0.01)
summary(sp.gnp)
#> 
#> ################################### 
#> # Schmidt-Phillips Unit Root Test # 
#> ################################### 
#> 
#> 
#> Call:
#> lm(formula = sp.data)
#> 
#> Residuals:
#>     Min      1Q  Median      3Q     Max 
#> -54.683  -8.176   2.394  11.843  27.884 
#> 
#> Coefficients:
#>             Estimate Std. Error t value Pr(>|t|)    
#> (Intercept) -1.80008    4.18871  -0.430    0.669    
#> y.lagged     0.98538    0.03301  29.849   <2e-16 ***
#> trend.exp1   0.50203    0.32292   1.555    0.125    
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> 
#> Residual standard error: 15.75 on 58 degrees of freedom
#> Multiple R-squared:  0.9926,	Adjusted R-squared:  0.9924 
#> F-statistic:  3896 on 2 and 58 DF,  p-value: < 2.2e-16
#> 
#> 
#> Value of test-statistic is: -1.3732 
#> Critical value for a significance level of 0.01 
#> is: -3.63 
#>