If your underlying question is what is the actual co-integrating relationship, then yes, the signs are in fact reversed. Thus, in your case, the co-integrating relationship is
I did have another more general question - i understand that EViews can report both the loadings and the eigenvectors, why would these be the same when using the covariance method of PCA? The reason that loadings and eigenvectors can sometimes be identical is because a loading vector is just a scal...
Econometrically, there is no issue if you log only some of your variables. At the end of the day, ARDL is just a LS regression. Nevertheless, the interpretation of what coefficients mean will depend on which variables are logged. Have a look at the attached document to better understand coefficient ...
In broad strokes, EViews performs the following steps: 1. Compute correlation/covariance matrix (depending on specification chosen), and the default scaling is 1/n as opposed to 1/(n-1). This makes no difference asymptotically, of course. 2. Compute eigenvectors and eigenvalues from the correlation/...
Hi SANhedrin, I just looked a bit more carefully into your request. The reason that -1 appears is because the Narayan (2005) Applied Economics paper, "The saving and investment nexus for China: evidence from cointegration tests", from which the Narayan tables are obtained, does not support...
The statistic next to the F-statistic entry is the usual F-statistic using no HAC adjustment. Thus, the variance of the parameter estimate is sigma^2(X'X)^(-1). The statistic next to the Wald F-statistic entry is the F-statisitc using the HAC variance adjustment. You can adjust the nature of the HAC...
The White test is in many ways a pecial case of the BPG test. Both tests are appropriate, but the BPG allows more flexibility in modelling the nature of heteroscedasticity by explicitly specifying its functional form.
Actually, we have our own three part blog series on ARDL estimation, and your are strongly encouraged to read it. http://blog.eviews.com/2017/04/autoregressive-distributed-lag-ardl.html?m=1 http://blog.eviews.com/2017/05/autoregressive-distributed-lag-ardl_8.html?m=1 http://blog.eviews.com/2017/05/a...
Have a look at this document to help you out. Indeed, two trend stationary variables can be co-integrated. What happens, however, is that the cointegrating relationship purges the effect of the deterministic trend. If this was not the case, it would imply the presence of a trend in the cointegrating...
OLS Is just an estimation method which may or may not produce consistent estimates. Although I'm not sure of which mostly in particular you refer to in your post, I am almost certain that the inclusion of an AR(1) term in your regression will not invalidate (in terms of consistency) the OLS estimato...
The procedures of which you speak are generally termed "second generation" panel models. At the moment, these are not available in EViews. Nevertheless, they are on our to-do list and will be introduced in a future release.
Please refer to our three part blog post on ARDL estimation. Virtually all of your questions will be answered there if you take the time to study the material carefully. Part 1: http://blog.eviews.com/2017/04/autoregressive-distributed-lag-ardl.html Part 2: http://blog.eviews.com/2017/05/autoregress...
You mean Eviews does not have the capability to conduct a long run Wald test using these variables or any other variables at this time? No! EViews has the capacity to do almost anything you want, however, it may not be automated at the moment and you may have to write the program yourself. What I m...