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anybody have any idea? even a short answer will do..

dependant variable: L(sales) independent variables: L(price), L(income) where L means log Here are the results: Vector Error Correction Estimates Date: 02/02/10 Time: 13:45 Sample (adjusted): 1931 2004 Cointegrating Eq: CointEq1 L(SALES(-1)) 1.000000 L(PRICE(-1)) 0.412459 L(INCOME(-1)) 0.7035123 C -...

For example, I have tried a few VAR equations in Eviews and Microfit. Despite using the same data, they give different estimates for the coefficents inside the cointegrating vector. Is this normal? Or should the two software packages be giving the same results? I only ask this because in my elastici...

if you are finding that all of the coefficients are now not significant, you may want to test to see if all the I(1) nonstationary variables are cointegrated to do this, save the residuals from your original regression. Run an ADF test on the residuals to see if the residuals are also I(1). In theo...

I have an equation of the following form, where all variables are I(1): log(y) = log(x1) + log(x2) + C @trend This means that the equations should be estimated using first differences, however I have been told that if it is proven that the data is cointegrated, I can use the normal estimations inste...

also, when estimating in first differences, all my coefficients become insignificant :? is this normal?

thank you for your reply. Upon doing further research, it seems that if I estimate in first differences:

dlog(y) = dlog(x1) + dlog(x2) + C

this will only give me short term elasticties, whereas the normal equation:

log(y) = log(x1) + log(x2) + C

gives me long term elasticities. Is this true?

Ok so i've run the ADF test on all variables, and it revealed that they were all non stationary. After running the test on first diffrences, it revealed that they were all now stationary, so first differences are needed to get the variables to be stationary. The main problem i still have however, is...

any ideas? cheers

Hi, my study involves measuring the price elasticity, and income elasticity of certain goods. The elasticities are obtained by using the double log functional form. However, I am new to this and just have a few questions about the issue of 'stationarity' 1) To detect whether data is stationary, do i...

The number of iterations doesn't matter. You might read the section in the Help system under "How EViews Estimates AR Models." thanks that was very helpful, when referring to this is it ok if I refer to it as "the iterative procedure"? - or would a different name be more appropr...

This is almost (not quite) identical to the Cochrane-Orcutt iterative procedure, and it is okay to use with a lagged dependent variable. thanks for your help :D what is this procedure called? Also, do i need to pay attention to how many iterations it takes? (i.e, on a regression that i tried of the...

If you're doing a regression, add AR(1) to the variable list. thank you for your reply. How would this remove the serial correlation? Correct me if I'm wrong, but is this the 'cochrane-orchutt iterative procedure'? I read about this in a book today, however it didn't make it clear whether it was po...

how do I remove the serial correlation in eviews? Most the methods I have found I cannot use because I have a lagged dependant variable as an independent variable..

thanks

The majority of my vifs seem way too big :shock: I'm hoping that after I've corrected for the multicollinearity that price and income will be significant in more cases, as it is in other papers. Even after i've corrected for multicollinearity, serial correlation may still be an issue. I don't know w...