Zivot and Andrews Unit Root Test

Performs the Zivot and Andrews unit root test, which allows a break at an unknown point in either the intercept, the linear trend or in both.

Usage

ur.za(y, model = c("intercept", "trend", "both"), lag=NULL)

Arguments

y: Vector to be tested for a unit root.
model: Specification if the potential break occured in either the intercept, the linear trend or in both.
lag: The highest number of lagged endogenous differenced variables to be included in the test regression

Details

This test is based upon the recursive estimation of a test regression. The test statistic is defined as the minimum t-statistic of the coeffcient of the lagged endogenous variable.

Value

An object of class ur.za.

References

Zivot, E. and Andrews, Donald W.K. (1992), Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis, Journal of Business and Economic Statistics, 10(3), 251–270.

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

Author

Bernhard Pfaff

Examples

data(nporg)
gnp <- na.omit(nporg[, "gnp.r"])
za.gnp <- ur.za(gnp, model="both", lag=2)
summary(za.gnp)
#> 
#> ################################ 
#> # Zivot-Andrews Unit Root Test # 
#> ################################ 
#> 
#> 
#> Call:
#> lm(formula = testmat)
#> 
#> Residuals:
#>     Min      1Q  Median      3Q     Max 
#> -39.753  -9.413   2.138   9.934  22.977 
#> 
#> Coefficients:
#>              Estimate Std. Error t value Pr(>|t|)    
#> (Intercept)  21.49068   10.25301   2.096  0.04096 *  
#> y.l1          0.77341    0.05896  13.118  < 2e-16 ***
#> trend         1.19804    0.66346   1.806  0.07675 .  
#> y.dl1         0.39699    0.12608   3.149  0.00272 ** 
#> y.dl2         0.10503    0.13401   0.784  0.43676    
#> du          -25.44710    9.20734  -2.764  0.00788 ** 
#> dt            2.11456    0.84179   2.512  0.01515 *  
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> 
#> Residual standard error: 13.72 on 52 degrees of freedom
#>   (3 observations deleted due to missingness)
#> Multiple R-squared:  0.9948,	Adjusted R-squared:  0.9942 
#> F-statistic:  1651 on 6 and 52 DF,  p-value: < 2.2e-16
#> 
#> 
#> Teststatistic: -3.8431 
#> Critical values: 0.01= -5.57 0.05= -5.08 0.1= -4.82 
#> 
#> Potential break point at position: 21 
#>