When applying the "urca" package function ur.df
, like
summary(ur.df(data$col1, type = c("none"), lags = 12, selectlags = c("AIC")))
I get following result:
###############################################
# Augmented Dickey-Fuller Test Unit Root Test #
###############################################
Test regression trend
Call:
lm(formula = z.diff ~ z.lag.1 + 1 + tt + z.diff.lag)
Residuals:
Min 1Q Median 3Q Max
-12928366 -2888728 1284718 4218373 7179531
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5.391984e+07 1.638362e+07 3.29108 0.0043123 **
z.lag.1 -2.438154e+00 7.557134e-01 -3.22629 0.0049588 **
tt 6.579260e+05 2.730453e+05 2.40959 0.0275861 *
z.diff.lag1 1.712004e+00 6.595980e-01 2.59553 0.0188537 *
z.diff.lag2 1.402824e+00 6.379412e-01 2.19899 0.0420083 *
z.diff.lag3 1.321555e+00 5.294537e-01 2.49607 0.0231329 *
z.diff.lag4 1.099430e+00 4.720412e-01 2.32910 0.0324428 *
z.diff.lag5 8.132753e-01 4.181477e-01 1.94495 0.0685140 .
z.diff.lag6 1.797331e-01 3.654326e-01 0.49184 0.6291254
z.diff.lag7 5.890640e-01 2.939590e-01 2.00390 0.0612825 .
z.diff.lag8 3.919041e-01 2.794371e-01 1.40248 0.1787705
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 6708593 on 17 degrees of freedom
Multiple R-squared: 0.7237276, Adjusted R-squared: 0.5613144
F-statistic: 4.253547 on 10 and 17 DF, p-value: 0.003348755
Value of test-statistic is: -3.2263 3.9622 5.2635
Critical values for test statistics:
1pct 5pct 10pct
tau3 -4.15 -3.50 -3.18
phi2 7.02 5.13 4.31
phi3 9.31 6.73 5.61
Now the question:
- I do understand that "-3.2263" is the critical value (t-value)
- There is a unit root with trend since -3.2263 > -3.18 (tau3@10pct) This means the time-series is non-stationary at a 10% significance level.
- But, what is the meaning of "p-value: 0.003348755"? Should I list this value in a table summarizing my unit root test results or rather mark the 0.1 significance level (*10%)?
The documentation says that critical values are based on Hamilton (1994) and Dickey and Fuller (1981)".