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  • ivhettest after ivreg2h: last estimates not found

    Dear Statalist community,

    I run -ivreg2h- command from SSC with the fe option to implement the estimator proposed by Lewbel (2012, JBES) "Using heteroskedasticity to identify and estimate mismeasured and endogenous regressor models" for a dynamic panel of macroeconomic data with time and country fixed effects. I follow the guide by Baum and Lewbel (2019, The Stata Journal) "Advice on using heteroskedasticity-based identification" when implementing the command.

    Baum and Lewbel (2019) suggest to run -ivhettest- after -ivreg2h- in order to test for heteroskedasticity in the residuals of the first stage regression, conditional on the constructed instruments. However, when using -ivhettest-, I get the following error "last estimates not found, r(301)".

    I am using Stata/SE 16.0 on Windows 10.

    I run the following code where d_L1Y is the endogenous variable to be instrumented. I also include a time fixed effect (i.quarter) which I then partial out. Moreover, z() reports the (assumed exogenous) variables used to build the instruments. These variables are used in the first stage regression. The outcome variable of the second stage regression is fa_Y. I use the xi: option in order to account for time dummies.

    Code:
    xi: ivreg2h  fa_Y L1d_L1Y L2d_L1Y L1fa_Y L2fa_Y dlrealgdp dstock_prices dgov_bond_yields ///
                       i.quarter (d_L1Y =) if noIRE==1, fe robust bw(2) gmm2s ///
                       z(L1d_L1Y L2d_L1Y L1fa_Y L2fa_Y dlrealgdp dstock_prices dgov_bond_yields) ///
                       partial(i.quarter)
    I get the following results:

    Code:
    
    IV with Generated Instruments only
    Fixed Effects by(CountryCode), 16 groups
    Instruments created from Z:
    L1d_L1Y L2d_L1Y L1fa_Y L2fa_Y dlrealgdp dstock_prices dgov_bond_yields
    Warning - collinearities detected
    Vars dropped:       _Iquarter_41 _Iquarter_235
    Warning - collinearities detected
    Vars dropped:  _Iquarter_41 _Iquarter_235
    
    2-Step GMM estimation
    ---------------------
    
    Estimates efficient for arbitrary heteroskedasticity and autocorrelation
    Statistics robust to heteroskedasticity and autocorrelation
      kernel=Bartlett; bandwidth=2
      time variable (t):  quarter
      group variable (i): CountryCode
    
                                                          Number of obs =     1389
                                                          F(  8,  1172) =    18.03
                                                          Prob > F      =   0.0000
    Total (centered) SS     =  50718.29679                Centered R2   =   0.5192
    Total (uncentered) SS   =  50718.29679                Uncentered R2 =   0.5192
    Residual SS             =  24387.76391                Root MSE      =    4.215
    
    
    ----------------------------------------------------------------------------------
                     |               Robust
                fa_Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
    -----------------+----------------------------------------------------------------
               d_L1Y |   1.098956   .1145213     9.60   0.000     .8744988    1.323414
             L1d_L1Y |  -.1575488   .0408916    -3.85   0.000    -.2376948   -.0774028
             L2d_L1Y |  -.1898572    .055578    -3.42   0.001    -.2987881   -.0809263
              L1fa_Y |   .0513925   .0330912     1.55   0.120     -.013465      .11625
              L2fa_Y |   .1006611   .0362383     2.78   0.005     .0296354    .1716868
           dlrealgdp |  -.3768432   .2409836    -1.56   0.118    -.8491624     .095476
       dstock_prices |   .0123677   .0375827     0.33   0.742     -.061293    .0860284
    dgov_bond_yields |  -.5828282   .4648038    -1.25   0.210    -1.493827    .3281705
    ----------------------------------------------------------------------------------
    Underidentification test (Kleibergen-Paap rk LM statistic):              5.054
                                                       Chi-sq(7) P-val =    0.6534
    ------------------------------------------------------------------------------
    Weak identification test (Cragg-Donald Wald F statistic):               11.374
                             (Kleibergen-Paap rk Wald F statistic):          1.657
    Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    19.86
                                             10% maximal IV relative bias    11.29
                                             20% maximal IV relative bias     6.73
                                             30% maximal IV relative bias     5.07
                                             10% maximal IV size             31.50
                                             15% maximal IV size             17.38
                                             20% maximal IV size             12.48
                                             25% maximal IV size              9.93
    Source: Stock-Yogo (2005).  Reproduced by permission.
    NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
    ------------------------------------------------------------------------------
    Hansen J statistic (overidentification test of all instruments):         2.331
                                                       Chi-sq(6) P-val =    0.8869
    ------------------------------------------------------------------------------
    Instrumented:         d_L1Y
    Included instruments: L1d_L1Y L2d_L1Y L1fa_Y L2fa_Y dlrealgdp dstock_prices
                          dgov_bond_yields
    Excluded instruments: d_L1Y_L1d_L1Y_g d_L1Y_L2d_L1Y_g d_L1Y_L1fa_Y_g
                          d_L1Y_L2fa_Y_g d_L1Y_dlrealgdp_g d_L1Y_dstock_prices_g
                          d_L1Y_dgov_bond_yields_g
    Partialled-out:       _Iquarter_42 _Iquarter_43 --  _Iquarter_234
                          nb: total SS, model F and R2s are after partialling-out;
                              any small-sample adjustments include partialled-out
                              variables in regressor count K
    Dropped collinear:    _Iquarter_41 -------------- _Iquarter_235
    ------------------------------------------------------------------------------
    
    Warning: variables have been centered
    
    -----------------------------
        Variable |   GenInst    
    -------------+---------------
           d_L1Y |        1.099  
                 |         .115  
         L1d_L1Y |       -.1575  
                 |        .0409  
         L2d_L1Y |       -.1899  
                 |        .0556  
          L1fa_Y |       .05139  
                 |        .0331  
          L2fa_Y |        .1007  
                 |        .0362  
       dlrealgdp |       -.3768  
                 |         .241  
    dstock_pri~s |       .01237  
                 |        .0376  
    dgov_bond_~s |       -.5828  
                 |         .465  
    -------------+---------------
               N |         1389  
            rmse |         4.21  
               j |         2.33  
             jdf |            6  
              jp |         .887  
    -----------------------------
                     legend: b/se
    Warning - collinearities detected
    Vars dropped:  _Iquarter_41 _Iquarter_235
    Then, I run - ivhettest- and get the following error:
    Code:
    . ivhettest
    last estimates not found
    r(301);
    I use the following versions of -ivreg2h- and of - ivhettest- which should be also the last updates (at the best of my knowledge):
    Code:
    . which ivreg2h
    C:\Users\Giacomo.Rella\ado\plus\i\ivreg2h.ado
    *! ivreg2h  1.1.03  07feb2019  cfb/mes
    *! cloned from
    *! xtivreg2 1.0.13 28Aug2011
    *! author mes
    
    . which ivhettest
    C:\Users\Giacomo.Rella\ado\plus\i\ivhettest.ado
    *! ivhettest 1.1.9  15Aug2013
    *! author mes
    I hope the information I provided are useful to help me to figure out what I am doing wrong.
    Thank you very much in advance.

    Giacomo





    Last edited by Giacomo Rella; 08 Sep 2020, 13:22.

  • #2
    This problem has been fixed in the STATA update of 10 Jan 2023!

    Comment


    • #3
      I don't think the official Stata update had any effect on these two routines. But there are much more recent versions of ivreg2h and ivhettest on SSC. If you run the first example in the ivreg2h help file and add the gen option, ivhettest works.

      You should use the ado update command to see whether community-contributed routines are up to date on your machine.

      . which ivreg2h
      /Users/baum/Library/Application Support/Stata/ado/plus/i/ivreg2h.ado
      *! ivreg2h 1.1.04 11jul2021 cfb/mes


      . which ivhettest
      /Users/baum/Library/Application Support/Stata/ado/plus/i/ivhettest.ado
      *! ivhettest 1.2.0 24jan2023
      *! author mes

      . ivhettest
      IV heteroskedasticity test(s) using levels of IVs only
      Ho: Disturbance is homoskedastic
      Pagan-Hall general test statistic : 25.783 Chi-sq(24) P-value = 0.3643

      Kit

      Comment


      • #4
        I don't think the official Stata update had any effect on these two routines. But there are much more recent versions of ivreg2h and ivhettest on SSC. If you run the first example in the ivreg2h help file and add the gen option, ivhettest works.

        You should use the ado update command to see whether community-contributed routines are up to date on your machine.

        . which ivreg2h
        /Users/baum/Library/Application Support/Stata/ado/plus/i/ivreg2h.ado
        *! ivreg2h 1.1.04 11jul2021 cfb/mes


        . which ivhettest
        /Users/baum/Library/Application Support/Stata/ado/plus/i/ivhettest.ado
        *! ivhettest 1.2.0 24jan2023
        *! author mes

        . ivhettest
        IV heteroskedasticity test(s) using levels of IVs only
        Ho: Disturbance is homoskedastic
        Pagan-Hall general test statistic : 25.783 Chi-sq(24) P-value = 0.3643

        Kit

        Comment

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