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  • whether there is an integrated command to do AR including choosing the optimal lags?

    Dear all,
    I have a question about AutoRegression(AR): whether there is an integrated command to do AR including choosing the optimal lags?
    As I know, the procedure of doing AR are:
    1.choose the optimal lags "x" of the variable,i.e. find the optimal d.x var for the regression. (the varsoc command can be used for this)
    2.reg var d.x var

    Actually, to do AR need at least two command: 'varsoc' and 'reg', if I just have one group of time series data, that's fine, however I have a panel data. I want to do AR separately for each individual in the panel data, which means that I need to repeat the two procedures above by many many times(there are above 100 thousand individuals in the data). So I think if there is an integrated command about realizing AR then I can do this by a simple loop command.

    Here is the data example and related command:
    Code:
    clear
    input long cc float(ym seg1)
    32 624  .04445176
    32 625 .036192816
    32 626 .031618048
    32 627 .021474427
    32 628 .018776406
    32 629  .04074349
    32 630  .06222288
    32 631  .11409732
    32 632  .07309593
    32 633  .06792204
    32 634  .05304918
    32 635  .04487377
    32 636 .069375455
    32 637  .04845903
    32 638  .04594228
    32 639  .04550489
    32 640  .02831592
    32 641  .04477861
    32 642 .008422818
    32 643  .02045061
    32 644  .01491553
    32 645  .02663895
    32 646  .01889766
    32 647  .02050653
    32 648 .036607914
    32 649  .04809784
    32 650  .07823643
    32 651  .07154015
    32 652  .10459977
    32 653  .03831887
    32 654  .04900071
    32 655  .05963827
    32 656  .08837937
    32 657  .13331659
    32 658  .14064579
    32 659 .032867603
    32 660  .08356508
    32 661  .14442798
    32 662   .1650359
    32 663  .16835807
    32 664   .1584352
    32 665  .16954015
    32 666  .16671365
    32 667  .14384073
    32 668  .14769012
    32 669  .10536052
    32 670  .08170154
    32 671  .14344585
    32 672  .17022115
    32 673  .13671105
    32 674   .1110411
    32 675  .04305949
    32 676  .05226843
    32 677  .06650428
    32 678  .06246117
    32 679 .031141937
    32 680  .01348335
    32 681    .016822
    32 682  .03281092
    32 683  .08940174
    82 624  .06147674
    82 625  .10292392
    82 626  .14144202
    82 627  .13713068
    82 628  .14034407
    82 629  .13211797
    82 630  .14213976
    82 631   .1012358
    82 632  .09124867
    82 633   .1077327
    82 634  .09531018
    82 635  .10788896
    82 636   .0709384
    82 637  .07343553
    82 638  .10693694
    82 639  .11173867
    82 640  .14394651
    82 641  .13862461
    82 642   .1603671
    82 643  .14747722
    82 644  .11673568
    82 645   .1353928
    82 646   .1635395
    82 647  .15163447
    82 648   .1528629
    82 649   .1580043
    82 650   .1536663
    82 651  .16621074
    82 652  .14184435
    82 653  .20829704
    82 654  .15925044
    82 655  .14139512
    82 656  .13164993
    82 657   .0899644
    82 658  .07109592
    82 659  .15700375
    82 660  .15451227
    82 661  .13299246
    82 662  .06453852
    82 663  .06730772
    end
    format %tm ym
    xtset cc ym
    varsoc seg1, max(10) //bysort is ok and the lag periods are chosen under 10
    If you know an integrated command of AR or have the other way to solve my problem,I will be very glad to hear it! Thank you!
    QINGSHI WANG

  • #2
    Maybe our ardl command can be useful.
    https://twitter.com/Kripfganz

    Comment


    • #3
      Originally posted by Sebastian Kripfganz View Post
      Maybe our ardl command can be useful.
      Thank you so much Professor Kripfganz! Your command perfectly solves my problem!

      Comment


      • #4
        I was trying to estimate an ARDL model with interactions between the dependent variables, but Stata returns the error
        interactions not allowed
        , I don't really understand the reason, but I would like to know if there is any econometric intuition for the non-interaction of variables in ARDL.

        Comment

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