Here is a strange thing. I took the real GDP per capita (chain) from China and USA (Penn World Tables, Gretl, Database). I used the whole sample (1950-2004, if I am not wrong)

So I started a basic work with time series. I applied an ADF test in the China's variable using constant and trend, with general-to-particular approach in lags, starting with 10 lags.

Here is the result.

Dickey-Fuller test for CHN_RGDPCH

sample size 52

unit-root null hypothesis: a = 1

with constant and trend

model: (1-L)y = b0 + b1*t + (a-1)*y(-1) + e

1st-order autocorrelation coeff. for e: 0.092

estimated value of (a - 1): 0.0677971

test statistic: tau_ct(1) = 7.65922

p-value 1

Look, why is this p-value equal "one"? Any tips?

Best Wishes

Claudio D. Shikida