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  • #16
    Anirudh:
    1. The speed-of-adjustment coefficient, \(\alpha\), is positive, as it should be to have convergence towards the long-run equilbrium. What is reported is \(- \alpha\). You cannot directly infer from the regression table that it is statistically significant because the usual p-values are not valid. You need to look at the results from the bounds test with estat ectest, precisely the bounds test for the t-statistic.
    2. That is correct.
    3. That is correct, too.
    To have a cointegrating relationship, the sign of the speed-of-adjustment coefficient must be positive. That means, the reported sign in the output section ADJ must be negative.

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    • #17
      Many thanks for this clarification, Sebastian.

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      • #18
        Hi Everyone,

        I am using STATA 13 and would like to know what is the command for performing the Bounds Test?

        Regards

        Alistair

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        • #19
          If you have not done so already, you first need to install the ardl package as follows:
          Code:
          net install ardl, from(http://www.kripfganz.de/stata/)
          or
          Code:
          ssc install ardl
          Subsequently, you can estimate an ARDL model in the equilibrium correction form with option ec of the ardl command. The bounds test can be obtained afterwards by using the estat ectest postestimation command. Here is an example:
          Code:
          webuse lutkepohl2
          ardl ln_inv ln_inc ln_consump, ec
          estat ectest
          Please see the following presentation for further information:

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          • #20
            I was kindly informed by one of the ardl users that there is a mismatch of the reported bounds test F-statistics between our Stata command and the Microfit program by Pesaran & Pesaran. I have tried to replicate the Stata results with Microfit 5.5. While the ARDL coefficient estimates coincide, I am unable to replicate the F-statistic reported by Microfit. I have double checked the F-statistic reported by our own postestimation command estat ectest and could verify by manual calculation that our F-statistic is correct. I thus want to issue a warning to everyone who uses Microfit that there is a potential problem with the bounds test F-statistic reported there.

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            • #21
              Dear Sebastian Kripfganz,

              I have a question regarding the ARDL module in Stata. Suppose I run an ARDL model using the "ec" option on a mix of I(1) and I(0) variables, where the estimated "Long-Run" coefficients are statistically insignificant. In this occasion, I presume that there is no cointegration among the variables, hence I would like to advance with an ARDL module excluding the "Error Correction Term".

              How do I proceed? Should I run a new ARDL model using all the variables (i.e. transform non-stationary variables to become stationary) without the "ec" option, or should I only proceed with the estimated "Short-Run" coefficients provided in the first exercise?

              Best regards,
              Emil S. Harberg

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              • #22
                All long-run coefficients being statistically insignificant is not sufficient for excluding the error correction term because the lagged dependent variable itself might still be relevant (indicated by a rejection of the null hypothesis from the t-statistic bounds test). If neither the F-test nor the t-test version of the bounds test reject the null hypothesis, then you can proceed with an ARDL model in first differences, excluding the EC term. You would need to transform the (nonstationary) variables into first differences first before running the ardl command without the ec option again.

                There is nothing wrong with sticking to the EC model and interpreting only the short-run coefficients. The idea of reestimating the model without the EC term is just to obtain more efficient estimates (if the null hypothesis of the bounds test is indeed true).

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                • #23
                  Dear @Sebastian Kripfganz,

                  I have one question on the long run coefficients in the ardl cointegration approach. The sign that it´s reported on LR section it´s directly interpretable or i´ts neccesary to be multiplied it by minus 1.
                  Best regards,
                  Joan Mannet

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                  • #24
                    The long-run coefficients can be direcly interpreted as the long-run level effects on the dependent variable; see slide 16 of my my presentation at last year's London Stata Conference.

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                    • #25
                      Dear @Sebastian Kripfganz,thanks for your prompt response. Just to clarify, in your slide 13 of your presentation at last year's London Stata Conference, where you estimate the long-run relationship between the consumption, income and investment; we can assure that the income affects possitively in the long-term to the consumption?

                      Best regards,
                      Joan Mannet

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                      • #26
                        That is correct. A 1% permanent increase in income raises consumption in the long-run by 1%.

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