Re: [Gretl-users] help with SVAR
On Tue, 22 May 2012, Claudio Shikida wrote:
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?
It's equal to (well, approximately equal to) 1 because this sample
of 52 observations provides no evidence whatever against the null
hypothesis that Chinese real GDP per capita is a unit-root process
(allowing for a linear trend). That's not very surprising if you run
an OLS regression of CHN_RGDPCH on a time trend and look at the
residuals. They are anything but white noise; it's obvious to the
eye they are non-stationary.
Allin Cottrell