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  • High p-value after xtdidgregress

    Hello!

    I have panel data, and I conducted difference in differences to evaluate the effect of a policy on innovation (Patent Count and R&D Expenses).
    However, after all the commands, I have a high p-value.
    Could someone please look at my codes and see what could cause the high p-values?
    I appreciate the help in advance.

    Code:

    ***Import Excel File
    import excel "C:\Users\hwanseong.pak\Desktop\STATA Data_v0.2.xlsx", sheet("STATA") cellrange(A1:M3137) firstrow
    destring Ticker, replace force

    ***Set Panel Data
    xtset Ticker Year

    ***Summary Statistics
    summarize

    ***Create DiD Variables
    gen post2=1 if Year >= 2018
    replace post2=0 if Year < 2018
    gen phase2_treated = post2 * Phase2

    gen post1=1 if Year <=2017
    replace post1=0 if Year > 2017
    gen phase1_treated = post1 * Phase1

    replace PatentCount = PatentCount+1
    gen f_lnPC=ln(f.PatentCount)

    replace RDExp = RDExp+1
    gen lnRDE = ln(RDExp)

    ***Lag Control Variables
    gen l_lnTA = ln(l.TotalAssets)
    gen l_lnTR = ln(l.TotalRevenue)
    gen l_HHI = l.HHI
    gen l_ROA = l.ROA
    gen l_DE = l.DE
    gen l_RG = l.RevenueGrowth

    drop if Year == 2015
    drop if Year == 2022

    ***Run Fixed Effects DiD Regressions
    xtdidregress (f_lnPC phase1_treated l_lnTA l_lnTR l_ROA l_DE l_RG l_HHI Industry) (phase2_treated), group(Ticker) time(Year) aequations
    xtdidregress (lnRDE phase1_treated l_lnTA l_lnTR l_ROA l_DE l_RG l_HHI Industry) (phase2_treated), group(Ticker) time(Year) aequations


    Last edited by Hwanseong Pak; 28 Nov 2024, 03:15.

  • #2
    Maybe the treatment simply does not have a statistically significant effect. You should however not only focus on p-values, but also on economic significance, confidence intervals, etc.

    Also, instead of taking the log of the dependent variable and adding one, in line with Santos Silva and Tenreyro (2006), you should use PPML (ssc install ppmlhdfe)

    Comment


    • #3
      I am however confused by your two phase treatments leading to two treatment variables. Is your treatment staggered? If so you should employ xthdidregress

      Comment


      • #4
        Thank you for the insights Maxence Morlet .
        I will try the PPML method.
        My treament is somewhat staggered as the policy includes a few more companies in the 2nd phase.
        However, I wanted to evaluate the effect of the 2nd phase only, controlling the 1rst phase of the policy.
        Is this approach in appropriate, and should I employ xthdidregress instead?
        Again, thank you for the help in advance.
        Last edited by Hwanseong Pak; 28 Nov 2024, 18:04.

        Comment


        • #5
          I don't understand this "evaluate the effect of the 2nd phase only, controlling the 1rst phase of the policy.". From what I gather, this is staggered treatment adoption, so a staggered DiD.

          Comment


          • #6
            Dear Mr. Maxence Morlet,

            Thank you for the continued support.
            I tried the xthdidregress method, but my results are not statistically significant.
            I assume the prevalence of 0s in my dependent variable is causing this.
            Thus, I decided to use the ppmlhdfe method.
            However, the output from this ppmlhdfe method is similar to a classic regression model.
            As I have mentioned earlier, I want to know the effect of the 2nd phase only, which is why you suggested I use staggered DiD.
            Is there any method of knowing the effect of the 2nd phase only using ppmlhdfe method?

            Kind regards,
            Pak

            Comment

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