(EViews10):Estimate VECM, Forecast Error Variance Decomposition

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  • Опубліковано 22 жов 2024

КОМЕНТАРІ • 35

  • @CrunchEconometrix
    @CrunchEconometrix  6 років тому

    UA-cam recently changed the way my content will be monetised. My channel now needs 1,000 subscribers. So it would be amazing if you show your support by both watching my videos and subscribing to my channel if you haven’t done so already. Monetising my videos allows me to invest back into the channel with some new equipment so this small gesture from you will be extremely huge for me. Many thanks for your support….CrunchEconometrix loves to teach, help me stay online.

  • @wanjadouglas3058
    @wanjadouglas3058 4 роки тому +1

    Good job Doc

  • @azizahr4878
    @azizahr4878 3 роки тому +1

    Thank you so much for the videos. I have a question. Do we have to check the stability of the vecm model? And if the model isn't stable, what should we do? Any methods for it?
    Thank you.

    • @CrunchEconometrix
      @CrunchEconometrix  3 роки тому

      Yes, Azizah testing for VECM stability is very important..Play around with the lags and re-test.

    • @azizahr4878
      @azizahr4878 3 роки тому +1

      @@CrunchEconometrix I see. Thank you so much for your reply.

    • @rifatunazizah8297
      @rifatunazizah8297 3 роки тому

      @@CrunchEconometrix Thank you for the explanation. I want to ask the same thing about stability. I read in a journal that if the model is not stable (there is a modulus > 1) then check the autocorrelation error and non normality distributed to make sure that the model is stable or not. Is it right to conduct these test?
      Thank you

    • @CrunchEconometrix
      @CrunchEconometrix  3 роки тому

      Hi Rifatun, you mentioned that "you read it in a Journal". May I know what confirmation you are asking for?

    • @rifatunazizah8297
      @rifatunazizah8297 3 роки тому

      @@CrunchEconometrix I just want to make sure if I can conduct those test. Because it's hard to find another literature that explain about it except that journal I mention before.

  • @aireliqi2484
    @aireliqi2484 2 роки тому +1

    Hi Professor, sorry for asking, is it important to make sure all the independent variables to be significant? Can we still do the forecast if they are not significant? Thank you😊

    • @CrunchEconometrix
      @CrunchEconometrix  2 роки тому

      Hi Airel, your question is ok. The most plausible reasoning is to use significant coefficients for forecasting.

    • @aireliqi2484
      @aireliqi2484 2 роки тому

      @@CrunchEconometrix it means I can still use the ‘not significant variables’ to do the forecast right?😊

    • @CrunchEconometrix
      @CrunchEconometrix  2 роки тому

      That is not what I said.

    • @aireliqi2484
      @aireliqi2484 2 роки тому

      @@CrunchEconometrix ooo understood Professor😊 my next question is, if the T statistics for my two independent variables are 0.8 and 0.7, are they considered significant too?

    • @aireliqi2484
      @aireliqi2484 2 роки тому

      @@CrunchEconometrix Professor, do we need to look at the Adjusted R Square too before forecast based on this VECM results?

  • @macro_finance
    @macro_finance 4 роки тому

    Thank you very much for the lecture. My question is, what happens if LM test detects autocorrelation at lag h?

    • @CrunchEconometrix
      @CrunchEconometrix  4 роки тому +1

      You can re-estimate the model at higher/lower-order lags and re-test.

  • @summeraraza5452
    @summeraraza5452 6 років тому

    CrunchEconometrix plz explain why and when we should take log of variables before checking the stationarity of the data?
    Thanks

    • @CrunchEconometrix
      @CrunchEconometrix  6 років тому

      Hi Summera, taking the log of a series is just a matter of choice. You can always perform stationary test either on the level or log of the series....it may depend on the functional form of your model.

  • @MShaf-ic9td
    @MShaf-ic9td 4 роки тому

    Dear Professor,
    Are there any differences between the VAR, VECM and Causal analysis in Time Series and Panel Data?
    I mean, can we estimate the Time Series and Panel Data using the same procedures, or they differ?

    • @CrunchEconometrix
      @CrunchEconometrix  4 роки тому

      Hi Shaf, the procedures are similar but you will have to seek other online resources in that regard since I don't have a video yet. Thanks.

    • @MShaf-ic9td
      @MShaf-ic9td 4 роки тому +1

      Thank you so much for the explanation!

    • @CrunchEconometrix
      @CrunchEconometrix  4 роки тому

      @@MShaf-ic9td U're welcome.

  • @ednaogundare9994
    @ednaogundare9994 6 років тому

    Thank you.

  • @monicasharma4344
    @monicasharma4344 5 років тому

    We are working with 10 year daily data. So what should be the optimal period selection for variance demposition

    • @CrunchEconometrix
      @CrunchEconometrix  5 років тому

      With daily data, you can use up to 30 lags. Watch my video on "Optimal lags selection" for more insights.

  • @abdullahiosman8654
    @abdullahiosman8654 5 років тому +1

    if the result from trace statistic is different from max - eigen statistic what is the way forward iin this case

    • @CrunchEconometrix
      @CrunchEconometrix  5 років тому

      Hi Abdullahi, I mentioned in my video on "Johansen Cointegration Test" that a researcher is disposed to using either of the two...may I know from where (location) you are reaching me?

    • @abdullahiosman8654
      @abdullahiosman8654 5 років тому +1

      thanks

  • @serentier3042
    @serentier3042 4 роки тому

    Hi, if the error correction term is not significant, my P-statistic was [-0.342], is that bad?

    • @CrunchEconometrix
      @CrunchEconometrix  4 роки тому

      Hi Serentier, "bad" is not the right word. The outcome simply indicates that the error correction mechanism is not statistically significant in your model. If you change your control variables, you may likely get improved results.