How did you determine the t-distribution (critical value) for the long run coefficients? Is there any references? My model is good, also get conintegrating relationship among variable. But I am confused regarding the statistical significance of the long-run coefficients. Please explain or refer any literature. Thanks.
Which cointegreation should be used in paper to vonclude the results. Suppose I am checking long-run relationship among GDP PG and FDI.gdp as DV population growth and fdi are InDV. I have run unit root lag lengh VECM but confuse for results conclusion
in my VECM independent variables, coefficients are negative but statistically significant, e.g in short-run estimates: D_NL New Real GDP _ce1 L1. = -.1084373; z value = -2.45; p value=0.014 NL New Real GDP LD.=.4752317 ; z value = 1.84 ; p value=0.066 NL Tour Forex LD. = -.0560698; z value = -2.64 p value= 0.008 How to interpret
Hello! Your videos are very usefull. And it open me a lot of opportunities for my economics researches. But I have a question with VECM. Is it necessary to perform seasonal adjustment before cointegration checking and estimation? I analize domestic and world wheat prices. And I think that price pairs for some countries are not cointegrated because it needs to first, exclude seasonality. Thank you in advance
I know it is only necessary when interpreting the long-run impact, and when looking at the speed of adjustment, you want to see negative signs as that indicates that the variable is adjusting back to equilibrium.
sir, i have 8 explanatory variables and johansen cointegration showing 7 cointegrating relationships. VECM will be very complicated in this way. Whats the solution.
my variables are daily for the whole year, to estimate the optimal lag, LR FPE AIC and HQ showed the optimal lag is 8. should i have to choose 8? can i test the optimal lags with original data?
How did you determine the t-distribution (critical value) for the long run coefficients? Is there any references? My model is good, also get conintegrating relationship among variable. But I am confused regarding the statistical significance of the long-run coefficients. Please explain or refer any literature. Thanks.
Which cointegreation should be used in paper to vonclude the results. Suppose I am checking long-run relationship among GDP PG and FDI.gdp as DV population growth and fdi are InDV. I have run unit root lag lengh VECM but confuse for results conclusion
in my VECM independent variables, coefficients are negative but statistically significant, e.g in short-run estimates:
D_NL New Real GDP
_ce1
L1. = -.1084373; z value = -2.45; p value=0.014
NL New Real GDP
LD.=.4752317 ; z value = 1.84 ; p value=0.066
NL Tour Forex
LD. = -.0560698; z value = -2.64 p value= 0.008
How to interpret
Hello! Your videos are very usefull. And it open me a lot of opportunities for my economics researches. But I have a question with VECM. Is it necessary to perform seasonal adjustment before cointegration checking and estimation? I analize domestic and world wheat prices. And I think that price pairs for some countries are not cointegrated because it needs to first, exclude seasonality.
Thank you in advance
I agree
Do we check the stationarity of logged variables or their original forms?
We check of both
Is it advisable to include the optimal lag we obtain when testing for cointegration?
depends on case to case basis
it it necessary to reverse the signs of the coefficients while interpreting the impact of each variable on an other one ?
I know it is only necessary when interpreting the long-run impact, and when looking at the speed of adjustment, you want to see negative signs as that indicates that the variable is adjusting back to equilibrium.
sir, i have 8 explanatory variables and johansen cointegration showing 7 cointegrating relationships. VECM will be very complicated in this way. Whats the solution.
Make subset and then run analysis
what about stability diagnostics?
Good evening Dr,
How can i find ECT+ and ECT- in eViews. Am stuck. Kindly assist. Thanks in advance.
Kind regards,
Tumelo Arthur Mohale
R u talking about NARDL
@DhavalSaifaleeAaryash Am using Vector Error Correction model. The error term is split into two, the negative and the positive (ect- and ect+)
my variables are daily for the whole year, to estimate the optimal lag, LR FPE AIC and HQ showed the optimal lag is 8. should i have to choose 8? can i test the optimal lags with original data?
No u hv to run VAR to check lags
@@DhavalSaifaleeAaryash yes dr. I did which showed me the choosing by LR FPE AIC and HQ showed the optimal is 8.
good day sir.. what if my time series are cointegrating but the coefficient of the error correction is positive
it is not good model.
Sir you tested that model is not homoscedastic is it right in VECM?
For garch we require heteroskedasticity
How 0.60 is Less than 0.05
Can u specify the time period