Re: [Gretl-users] help with SVAR

Am 22.05.2012 23:42, schrieb Allin Cottrell: > 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. > Follow-up: From the point estimate the process would be explosive (a>1). That's not really covered by the one-sided unit-root test.

But what puzzles me is the large absolute value of the test statistic -- what is driving this is unclear to me, presuming that the precision of the estimate is not too high with 52 obs.