Hi, I am getting an error message these days when I try to run the STAR package. This just recently started. I cannot figure out why this problem is occurring, as the package was working fine just yesterday. Hi, It is because the LM_1 statistical is negative, It has never happened to me. Could you ...
The second suggestion would be more general for any lag desierd by the user, but the first will be easy to implement in the current version of the add-in. Thanks for the idea, I will see what I can do.
If the p value of the test is under the significance level the hypothesis that a series X does not cause a series Y in the frequency wj is rejected. Also a graph with the label var1_var2 means that the variable var1 is the dependent and var2 the independent, therefore the hypothesis is that var2 doe...
Hi, You are not doing anything wrong, it is because what I mention in my previous post. You have two options, increase the maximum number lags or select the AIC criteria, in the case that any of this work ir means that a VAR(p) with p>2 it is not suggested to be fitted to the data and the test can n...
Hi, The LLC test estimates a single coefficient of the lagged variables to perform the unit root test while the IPS test estimates one coefficient of the lagged variables for each series and then calculates the test with those. For what i remember the LLC has a diferent distribution than the ADF. Re...
Hi, Because the test is based in two linear restrictions and you can not perfom a Wald (or an F) test if the number of restriccions in greater than the number of parameters, and since you are testing if the past of one variable (all its lags) at some frequency Granger-cause another variable 2>p wher...
I am conducting research on the real exchange rates of 28 countries against the us dollar. I am using ESTAR model to test for PPP and I would greatly appreciate some help. I am using a starting values for the vector coefficients of 0.5. Do you think that can work fine? Why in running the LSTR and E...
Dear Nicolas, I am attempting some testing of adequacy in the post estimation of my STAR model. Specifically I'm attempting to test for the presence of no autocorrelation using the methods of Eitrheim and Terasvirta (1996). This is a Serial Correlation LM test which is Chi-squared distributed. Howe...
Hi Trubador, In the test you can apply the Toda and Yamamoto result. Nevertheless theoretically, to estimate a traditional spectrum conditions must be achived, some of them are related to a second order stationary process. By they way, great blog about your recent add-in, seems to be a better strate...
This add-in calculates a Spectral Granger Causality Test based on Breitung and Candelon (2006), the test decompose the causality relations in the spectrum of frequencies which can be attributed to short run and long run causality relations. You can find the add-in help document and the example data ...
The final test that one should always do is to compare the linear model with the nonlinear in terms of adjustment, if the nonlinear one gives you better results you should keep it. Regarding the stationarity of the transition variable, since you apply a funcion which codomine is bounded the resultin...