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Hi, from what I am aware of, if Y = b0 + b1*X + e then b1 = COV(X,Y)/VAR(X) Also, if X = c0 + c1*Y + e then c1 = COV(X,Y)/VAR(Y) In this case, if we know b1, VAR(X) and VAR(Y), can I estimate c1 using c1 = b1*VAR(X)/VAR(Y) and without estimating Y=c0 + c1*X + e explicitly? Are there any errors to my...

Hi, From what I know, cointegrating regression (COINTREG method in eveiws) is used when both the dependent and independent variables are I(1) processes. Under these circumstances, cointegrating regression is preferred over OLS-type specification because it is able to detect spurious regressions. My ...

awesome,

so since the quantities of interest for my research is both the slope coefficient (and its significance) and also the R squared, I was wondering if there are any other way of treating autoregressive behaviour other than using ARMA structure.

thank you for answering my questions!

Thanks for the reply :) I think I will have to clarify on the concept, so if Newey West HAC variance is used, are test results will be robust against autocorrelation and heteroskedasticity? So in that case, is there no need for me to worry about autocorrelation once I use the HAC variance? (although...

I've tried and eviews does indeed allows for MA(48) structure. However, the MA structure is found to be insignificant

Oh yes, I referred to the R^2 just to point out that it might be due to the autocorrelation

Hmm MA sounds like a good alternative, I'll give that a try. Thank you :)

Hi, I have a model that tries to link the yield spread to future changes in GDP/industrial production. The specification that I have is: %change in industrial production over t, t+48 = c + beta*yield spreadt + errort and this data is run over a monthly frequency and estimated using OLS with HAC vari...