Reproduce the first row of the second half of Table 5 in Kwiatkowski et al., 1992.

Load the Nelson-Plosser Macroeconomic series data set.

Linearize the real gross national product series (RGNP).

Assess the null hypothesis that the series is trend stationary over a range of lags.

Warning: Test statistic #1 above tabulated critical values:
minimum p-value = 0.010 reported.
Warning: Test statistic #2 above tabulated critical values:
minimum p-value = 0.010 reported.
Warning: Test statistic #3 above tabulated critical values:
minimum p-value = 0.010 reported.
results =
0 0.0100 0.6299
1.0000 0.0100 0.3367
2.0000 0.0100 0.2421
3.0000 0.0169 0.1976
4.0000 0.0276 0.1729
5.0000 0.0401 0.1578
6.0000 0.0484 0.1479
7.0000 0.0589 0.1412
8.0000 0.0668 0.1370

Warnings appear because the tests using 0
`lags`

2 produce p-values that are less than 0.01. For `lags`

7, the tests indicate sufficient evidence to suggest that log rGNP is unit root nonstationary (i.e., not trend stationary) at the default 5% level.

Test whether the wage series in the manufacturing sector (1900-1970) has a unit root.

Load the Nelson-Plosser Macroeconomic data set.

Plot the wages series.

The plot suggests that the wages series grows exponentially.

Linearize the wages series.

The plot suggests that the log wages series has a linear trend.

Test the hypothesis that the log wages series is a unit root process with a trend (i.e., difference stationary), against the alternative that there is no unit root (i.e., trend stationary). Conduct the test by setting a range of lags around
, as suggested in Kwiatkowski et al., 1992.

Warning: Test statistic #1 below tabulated critical values:
maximum p-value = 0.100 reported.
Warning: Test statistic #2 below tabulated critical values:
maximum p-value = 0.100 reported.
Warning: Test statistic #3 below tabulated critical values:
maximum p-value = 0.100 reported.
Warning: Test statistic #4 below tabulated critical values:
maximum p-value = 0.100 reported.
h =
0 0 0 0
pValue =
0.1000 0.1000 0.1000 0.1000

All tests fail to reject the null hypothesis that the log wages series is trend stationary.

The warning messages do not indicate a problem. Rather, they indicate that the p-values are larger than 0.1. The software compares the test statistic to critical values and computes p-values that it interpolates from tables in Kwiatkowski et al., 1992.