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  • Arranging and plotting coefficients based on age-group using coefplot

    Dear Statalist,

    I am running a model with 20 explanatory variables of interest. Each variable is an exposure to a specific shock at a specific age. For example, (e14, s14, d14 and q14) are shocks experienced at age 1-4; (e58, s58, d58 and q58) are shocks at age 5-8; (e912, s912, d912 and q912) are shocks at age 9-12; (e1316, s1316, d1316 and q1316) are shocks at age 13-16; and (e1719, s1719, d1719 and q1719) are shocks at age 17-19.

    I regress the 20 explanatory variables on four different outcomes (See model below please).

    local out “out1 out2 out3 out4”

    foreach v in `out’ {
    eststo `v’: reghdfe `v’ e14 s14 d14 q14 e58 s58 d58 and q58 e912 s912 d912 q912 e1316 s1316 d1316 q1316 e1719 s1719 d1719 q1719, a(`fe’) cluster(country)
    }

    I would like to use coefplot to plot all the coefficients but arrange the coefficients based on age. I want a plot like the one shown below. I thought about grouping the estimates using matrix, e.g., mat A = [e14, s14, d14, q14] and applying coefplot, but it is still not clear to me how to go about it.


    Any assistance given would be appreciated.
    Thank you
    Click image for larger version

Name:	stata_exam.png
Views:	1
Size:	86.7 KB
ID:	1744605

  • #2
    Dear all,

    Can some experts help address my question with this example data?

    . dataex out1 out2 fe1 fe2 e14-d912 clustvar, count(100)

    Code:
    * Example generated by -dataex-. For more info, type help dataex
    clear
    input float(out1 out2) byte(fe1 fe2) float(e14 s14 q14 d14 e58 s58 q58 d58 e912 s912 q912 d912) int clustvar
      .0919287 -.007475017 44 1 -.6650371 -.30397725 -.1659081 -.10402028 .19223966 -.3390412 -.15784046   2.384596 -.01901869 -.3672469 -.16199577  -.7314057 44
      .0919287   .28591144 22 1 -.6650371 -.30397725 -.1659081  -.8479494 -.7633781 -.3390412 -.15784046 -1.0039667  -.8828008 -.3672469 -.16199577 -1.0610813 22
      .5849437    .5792981 44 1 -.6650371 -.30397725 -.1659081 -.10402028 .19223966 -.3390412 -.15784046   2.384596 -.01901869 -.3672469 -.16199577  -.7314057 44
      .0919287    .5792981 45 1 -.6650371 -.30397725 -.1659081  1.0571783 .19223966 -.3390412 -.15784046  1.3364686 -.01901869 -.3672469 -.16199577  -.8810784 45
      .5849437    .5792981 40 1  .4828812 -.30397725 -.1659081  -.2980709 -.7633781 -.3390412 -.15784046 -.12205097 -.01901869 -.3672469 -.16199577   2.521961 40
      .5849437    .5792981 46 1 -.6650371 -.30397725 -.1659081  1.9362162 1.1478574 -.3390412 -.15784046   .4942202  -.8828008 -.3672469 -.16199577  -.9179304 46
     -.4907253 -.072672024 28 1 -.6650371 -.30397725 -.1659081 -1.0226473 -.7633781 -.3390412 -.15784046 -1.0592517  -.8828008 -.3672469 -.16199577  -.7793982 28
     -.1545787 -.007475017 42 1 -.6650371 -.30397725 -.1659081  -.7878087 -.7633781 -.3390412 -.15784046   1.976216   .8447635 -.3672469 -.16199577    .562846 42
      .5849437    .5792981 33 1 -.6650371 -.30397725 -.1659081 -1.0037041 .19223966 -.3390412 -.15784046  -.8041514  -.8828008 -.3672469 -.16199577 -.29128608 33
      .5849437    .5792981 39 1  .4828812 -.30397725 -.1659081  -.3333256 -.7633781 -.3390412 -.15784046  -.8674082  -.8828008 -.3672469 -.16199577   2.732938 39
      .5849437    .5792981 37 1  .4828812 -.30397725 -.1659081  -.7672562 -.7633781 -.3390412 -.15784046   -.329943  -.8828008 -.3672469 -.16199577  1.1618173 37
      .3384363    .5792981 34 1 -.6650371 -.30397725 -.1659081  -.8041486 .19223966 -.3390412 -.15784046  -.4727512  -.8828008 -.3672469 -.16199577  -.8046436 34
      .3384363    .5792981 37 1  .4828812 -.30397725 -.1659081  -.7672562 -.7633781 -.3390412 -.15784046   -.329943  -.8828008 -.3672469 -.16199577  1.1618173 37
      .5849437    .5792981  7 1 -.6650371 -.30397725 -.1659081 -.13313164 -.7633781 -.3390412 -.15784046 -.50287265  -.8828008 -.3672469 -.16199577 -1.0570301  7
      .3160265     .253313 32 1 -.6650371 -.30397725 -.1659081 -1.0153013 -.7633781 -.3390412 -.15784046  -.8009288 -.01901869 -.3672469 -.16199577 -.28266147 32
      .5849437    .5792981 25 1 -.6650371 -.30397725 -.1659081  -.9357632 -.7633781 -.3390412 -.15784046 -1.0710821  -.8828008 -.3672469 -.16199577 -1.0347534 25
      .3160265     .253313  5 1 -.6650371 -.30397725 -.1659081  -.8174706 -.7633781 -.3390412 -.15784046  .11515166  -.8828008 -.3672469 -.16199577  -.8211402  5
      .5849437    .5792981 39 1  .4828812 -.30397725 -.1659081  -.3333256 -.7633781 -.3390412 -.15784046  -.8674082  -.8828008 -.3672469 -.16199577   2.732938 39
      .0919287   .28591144 42 1 -.6650371 -.30397725 -.1659081  -.7878087 -.7633781 -.3390412 -.15784046   1.976216   .8447635 -.3672469 -.16199577    .562846 42
      .3384363    .5792981 29 1 -.6650371 -.30397725 -.1659081 -1.0268047 -.7633781 -.3390412 -.15784046 -1.0473244 -.01901869 -.3672469 -.16199577  -.7827379 29
      .3384363    .5792981 42 1 -.6650371 -.30397725 -.1659081  -.7878087 -.7633781 -.3390412 -.15784046   1.976216   .8447635 -.3672469 -.16199577    .562846 42
      .5849437    .5792981 21 1 -.6650371 -.30397725 -.1659081  -.8763263 -.7633781 -.3390412 -.15784046  -.9774512  -.8828008 -.3672469 -.16199577  -1.059375 21
     .28913468    .5792981 42 1 -.6650371 -.30397725 -.1659081  -.7878087 -.7633781 -.3390412 -.15784046   1.976216   .8447635 -.3672469 -.16199577    .562846 42
      .0919287   .28591144 38 1  .4828812 -.30397725 -.1659081  -.4450214 -.7633781 -.3390412 -.15784046  -.8252884  -.8828008 -.3672469 -.16199577   2.098731 38
      .3160265     .253313 20 1 -.6650371 -.30397725 -.1659081  -.8747015 -.7633781 -.3390412 -.15784046  -.9837708  -.8828008 -.3672469 -.16199577 -1.0549439 20
      .5849437    .5792981 45 1 -.6650371 -.30397725 -.1659081  1.0571783 .19223966 -.3390412 -.15784046  1.3364686 -.01901869 -.3672469 -.16199577  -.8810784 45
      .5849437    .5792981 31 1 -.6650371 -.30397725 -.1659081 -1.0304538 -.7633781 -.3390412 -.15784046  -.7853453 -.01901869 -.3672469 -.16199577 -.32023725 31
      .0471092     .253313 39 1  .4828812 -.30397725 -.1659081  -.3333256 -.7633781 -.3390412 -.15784046  -.8674082  -.8828008 -.3672469 -.16199577   2.732938 39
      .3160265    .5792981 40 1  .4828812 -.30397725 -.1659081  -.2980709 -.7633781 -.3390412 -.15784046 -.12205097 -.01901869 -.3672469 -.16199577   2.521961 40
      .3384363    .5792981 37 1  .4828812 -.30397725 -.1659081  -.7672562 -.7633781 -.3390412 -.15784046   -.329943  -.8828008 -.3672469 -.16199577  1.1618173 37
      .5849437    .5792981 20 1 -.6650371 -.30397725 -.1659081  -.8747015 -.7633781 -.3390412 -.15784046  -.9837708  -.8828008 -.3672469 -.16199577 -1.0549439 20
      .5849437    .5792981 41 1 -.6650371 -.30397725 -.1659081  -.3061628 -.7633781 -.3390412 -.15784046  1.0721755 -.01901869 -.3672469 -.16199577  1.4357208 41
      .3384363   .28591144 28 1 -.6650371 -.30397725 -.1659081 -1.0226473 -.7633781 -.3390412 -.15784046 -1.0592517  -.8828008 -.3672469 -.16199577  -.7793982 28
      .5849437    .5792981 26 1 -.6650371 -.30397725 -.1659081  -.9615455 -.7633781 -.3390412 -.15784046 -1.0727285  -.8828008 -.3672469 -.16199577  -.8220592 26
      .5849437    .5792981 36 1 -.6650371 -.30397725 -.1659081  -.7641228 .19223966 -.3390412 -.15784046   -.321621  -.8828008 -.3672469 -.16199577 -.07583452 36
      .3384363    .5792981 40 1  .4828812 -.30397725 -.1659081  -.2980709 -.7633781 -.3390412 -.15784046 -.12205097 -.01901869 -.3672469 -.16199577   2.521961 40
      .5849437    .5792981 35 1 -.6650371 -.30397725 -.1659081  -.7489703 .19223966 -.3390412 -.15784046  -.3578784  -.8828008 -.3672469 -.16199577   -.848295 35
      .5849437    .5792981 38 1  .4828812 -.30397725 -.1659081  -.4450214 -.7633781 -.3390412 -.15784046  -.8252884  -.8828008 -.3672469 -.16199577   2.098731 38
      .3384363    .5792981 36 1 -.6650371 -.30397725 -.1659081  -.7641228 .19223966 -.3390412 -.15784046   -.321621  -.8828008 -.3672469 -.16199577 -.07583452 36
      .5849437    .5792981 42 1 -.6650371 -.30397725 -.1659081  -.7878087 -.7633781 -.3390412 -.15784046   1.976216   .8447635 -.3672469 -.16199577    .562846 42
      .5849437    .5792981 32 1 -.6650371 -.30397725 -.1659081 -1.0153013 -.7633781 -.3390412 -.15784046  -.8009288 -.01901869 -.3672469 -.16199577 -.28266147 32
      .5849437    .5792981 31 1 -.6650371 -.30397725 -.1659081 -1.0304538 -.7633781 -.3390412 -.15784046  -.7853453 -.01901869 -.3672469 -.16199577 -.32023725 31
      .3384363   .28591144 32 1 -.6650371 -.30397725 -.1659081 -1.0153013 -.7633781 -.3390412 -.15784046  -.8009288 -.01901869 -.3672469 -.16199577 -.28266147 32
      .5849437    .5792981 20 1 -.6650371 -.30397725 -.1659081  -.8747015 -.7633781 -.3390412 -.15784046  -.9837708  -.8828008 -.3672469 -.16199577 -1.0549439 20
      .5849437    .5792981 25 1 -.6650371 -.30397725 -.1659081  -.9357632 -.7633781 -.3390412 -.15784046 -1.0710821  -.8828008 -.3672469 -.16199577 -1.0347534 25
      .3160265    .5792981 34 1 -.6650371 -.30397725 -.1659081  -.8041486 .19223966 -.3390412 -.15784046  -.4727512  -.8828008 -.3672469 -.16199577  -.8046436 34
      .3384363   .28591144 39 1  .4828812 -.30397725 -.1659081  -.3333256 -.7633781 -.3390412 -.15784046  -.8674082  -.8828008 -.3672469 -.16199577   2.732938 39
      .3384363    .5792981 46 1 -.6650371 -.30397725 -.1659081  1.9362162 1.1478574 -.3390412 -.15784046   .4942202  -.8828008 -.3672469 -.16199577  -.9179304 46
      .5849437    .5792981 42 1 -.6650371 -.30397725 -.1659081  -.7878087 -.7633781 -.3390412 -.15784046   1.976216   .8447635 -.3672469 -.16199577    .562846 42
      .3160265    .5792981 41 1 -.6650371 -.30397725 -.1659081  -.3061628 -.7633781 -.3390412 -.15784046  1.0721755 -.01901869 -.3672469 -.16199577  1.4357208 41
     -.4907253  -.39865705 43 1 -.6650371 -.30397725 -.1659081  -.8287637 -.7633781 -.3390412 -.15784046  2.5881705   .8447635 -.3672469 -.16199577 -.14098415 43
    -.22180797     .253313 41 1 -.6650371 -.30397725 -.1659081  -.3061628 -.7633781 -.3390412 -.15784046  1.0721755 -.01901869 -.3672469 -.16199577  1.4357208 41
      .5849437    .5792981 46 1 -.6650371 -.30397725 -.1659081  1.9362162 1.1478574 -.3390412 -.15784046   .4942202  -.8828008 -.3672469 -.16199577  -.9179304 46
     -.1545787   -.3008616 26 1 -.6650371 -.30397725 -.1659081  -.9615455 -.7633781 -.3390412 -.15784046 -1.0727285  -.8828008 -.3672469 -.16199577  -.8220592 26
      .5849437    .5792981 35 1 -.6650371 -.30397725 -.1659081  -.7489703 .19223966 -.3390412 -.15784046  -.3578784  -.8828008 -.3672469 -.16199577   -.848295 35
     -.5982921   -.5209015 28 1 -.6650371 -.30397725 -.1659081 -1.0226473 -.7633781 -.3390412 -.15784046 -1.0592517  -.8828008 -.3672469 -.16199577  -.7793982 28
     -.1545787 -.007475017 37 1  .4828812 -.30397725 -.1659081  -.7672562 -.7633781 -.3390412 -.15784046   -.329943  -.8828008 -.3672469 -.16199577  1.1618173 37
      .5849437    .5792981 27 1 -.6650371 -.30397725 -.1659081 -1.0226473 -.7633781 -.3390412 -.15784046 -1.0748351  -.8828008 -.3672469 -.16199577  -.7632481 27
      .0471092     .253313 43 1 -.6650371 -.30397725 -.1659081  -.8287637 -.7633781 -.3390412 -.15784046  2.5881705   .8447635 -.3672469 -.16199577 -.14098415 43
      .0919287    .5792981 26 1 -.6650371 -.30397725 -.1659081  -.9615455 -.7633781 -.3390412 -.15784046 -1.0727285  -.8828008 -.3672469 -.16199577  -.8220592 26
      .5849437    .5792981 43 1 -.6650371 -.30397725 -.1659081  -.8287637 -.7633781 -.3390412 -.15784046  2.5881705   .8447635 -.3672469 -.16199577 -.14098415 43
      .5849437    .5792981 41 1 -.6650371 -.30397725 -.1659081  -.3061628 -.7633781 -.3390412 -.15784046  1.0721755 -.01901869 -.3672469 -.16199577  1.4357208 41
      .5849437    .5792981 28 1 -.6650371 -.30397725 -.1659081 -1.0226473 -.7633781 -.3390412 -.15784046 -1.0592517  -.8828008 -.3672469 -.16199577  -.7793982 28
    -.22180797     .253313 12 1 -.6650371 -.30397725 -.1659081  -.7421584 -.7633781 -.3390412 -.15784046 -1.0688194  -.8828008 -.3672469 -.16199577  -.8972574 12
      .3160265    .5792981 45 1 -.6650371 -.30397725 -.1659081  1.0571783 .19223966 -.3390412 -.15784046  1.3364686 -.01901869 -.3672469 -.16199577  -.8810784 45
      .3160265    .5792981 23 1 -.6650371 -.30397725 -.1659081  -.9142511 -.7633781 -.3390412 -.15784046 -1.0668064  -.8828008 -.3672469 -.16199577 -1.0632645 23
      .5849437    .5792981 35 1 -.6650371 -.30397725 -.1659081  -.7489703 .19223966 -.3390412 -.15784046  -.3578784  -.8828008 -.3672469 -.16199577   -.848295 35
      .5849437    .5792981 40 1  .4828812 -.30397725 -.1659081  -.2980709 -.7633781 -.3390412 -.15784046 -.12205097 -.01901869 -.3672469 -.16199577   2.521961 40
      .5849437    .5792981 46 1 -.6650371 -.30397725 -.1659081  1.9362162 1.1478574 -.3390412 -.15784046   .4942202  -.8828008 -.3672469 -.16199577  -.9179304 46
      .5849437    .5792981 33 1 -.6650371 -.30397725 -.1659081 -1.0037041 .19223966 -.3390412 -.15784046  -.8041514  -.8828008 -.3672469 -.16199577 -.29128608 33
      .3160265     .253313  1 1 -.6650371 -.30397725 -.1659081  -.8157464 -.7633781 -.3390412 -.15784046  -.8557939  -.8828008 -.3672469 -.16199577  .16999345  1
      .5849437    .5792981 22 1 -.6650371 -.30397725 -.1659081  -.8479494 -.7633781 -.3390412 -.15784046 -1.0039667  -.8828008 -.3672469 -.16199577 -1.0610813 22
      .5849437    .5792981 33 1 -.6650371 -.30397725 -.1659081 -1.0037041 .19223966 -.3390412 -.15784046  -.8041514  -.8828008 -.3672469 -.16199577 -.29128608 33
      .0471092     .253313 35 1 -.6650371 -.30397725 -.1659081  -.7489703 .19223966 -.3390412 -.15784046  -.3578784  -.8828008 -.3672469 -.16199577   -.848295 35
      .3384363    .5792981 32 1 -.6650371 -.30397725 -.1659081 -1.0153013 -.7633781 -.3390412 -.15784046  -.8009288 -.01901869 -.3672469 -.16199577 -.28266147 32
      .5849437    .5792981 35 1 -.6650371 -.30397725 -.1659081  -.7489703 .19223966 -.3390412 -.15784046  -.3578784  -.8828008 -.3672469 -.16199577   -.848295 35
      .5849437    .5792981 46 1 -.6650371 -.30397725 -.1659081  1.9362162 1.1478574 -.3390412 -.15784046   .4942202  -.8828008 -.3672469 -.16199577  -.9179304 46
     -.1545787 -.007475017 18 1 -.6650371 -.30397725 -.1659081 -1.0318102 -.7633781 -.3390412 -.15784046  -.8871397  -.8828008 -.3672469 -.16199577  -.9898191 18
      .3160265     .253313 41 1 -.6650371 -.30397725 -.1659081  -.3061628 -.7633781 -.3390412 -.15784046  1.0721755 -.01901869 -.3672469 -.16199577  1.4357208 41
      .3384363    .5792981 44 1 -.6650371 -.30397725 -.1659081 -.10402028 .19223966 -.3390412 -.15784046   2.384596 -.01901869 -.3672469 -.16199577  -.7314057 44
      .5849437    .5792981  4 1 -.6650371 -.30397725 -.1659081  -.8325666 -.7633781 -.3390412 -.15784046 .074372135  -.8828008 -.3672469 -.16199577  -.7559876  4
      .5849437    .5792981 41 1 -.6650371 -.30397725 -.1659081  -.3061628 -.7633781 -.3390412 -.15784046  1.0721755 -.01901869 -.3672469 -.16199577  1.4357208 41
      .5849437    .5792981 45 1 -.6650371 -.30397725 -.1659081  1.0571783 .19223966 -.3390412 -.15784046  1.3364686 -.01901869 -.3672469 -.16199577  -.8810784 45
      .5849437    .5792981 31 1 -.6650371 -.30397725 -.1659081 -1.0304538 -.7633781 -.3390412 -.15784046  -.7853453 -.01901869 -.3672469 -.16199577 -.32023725 31
      .5849437    .5792981 43 1 -.6650371 -.30397725 -.1659081  -.8287637 -.7633781 -.3390412 -.15784046  2.5881705   .8447635 -.3672469 -.16199577 -.14098415 43
      .3384363    .5792981 26 1 -.6650371 -.30397725 -.1659081  -.9615455 -.7633781 -.3390412 -.15784046 -1.0727285  -.8828008 -.3672469 -.16199577  -.8220592 26
     -.1545787 -.007475017 37 1  .4828812 -.30397725 -.1659081  -.7672562 -.7633781 -.3390412 -.15784046   -.329943  -.8828008 -.3672469 -.16199577  1.1618173 37
     .28913468    .5792981 34 1 -.6650371 -.30397725 -.1659081  -.8041486 .19223966 -.3390412 -.15784046  -.4727512  -.8828008 -.3672469 -.16199577  -.8046436 34
      .3384363   .28591144 41 1 -.6650371 -.30397725 -.1659081  -.3061628 -.7633781 -.3390412 -.15784046  1.0721755 -.01901869 -.3672469 -.16199577  1.4357208 41
      .3384363    .5792981 30 1 -.6650371 -.30397725 -.1659081 -1.0284055 -.7633781 -.3390412 -.15784046   -.842093 -.01901869 -.3672469 -.16199577  -.4392872 30
      .3384363   .28591144 38 1  .4828812 -.30397725 -.1659081  -.4450214 -.7633781 -.3390412 -.15784046  -.8252884  -.8828008 -.3672469 -.16199577   2.098731 38
      .5849437    .5792981 39 1  .4828812 -.30397725 -.1659081  -.3333256 -.7633781 -.3390412 -.15784046  -.8674082  -.8828008 -.3672469 -.16199577   2.732938 39
      .5849437    .5792981 44 1 -.6650371 -.30397725 -.1659081 -.10402028 .19223966 -.3390412 -.15784046   2.384596 -.01901869 -.3672469 -.16199577  -.7314057 44
     -.1545787 -.007475017 21 1 -.6650371 -.30397725 -.1659081  -.8763263 -.7633781 -.3390412 -.15784046  -.9774512  -.8828008 -.3672469 -.16199577  -1.059375 21
      .3160265    .5792981 28 1 -.6650371 -.30397725 -.1659081 -1.0226473 -.7633781 -.3390412 -.15784046 -1.0592517  -.8828008 -.3672469 -.16199577  -.7793982 28
      .5849437    .5792981 31 1 -.6650371 -.30397725 -.1659081 -1.0304538 -.7633781 -.3390412 -.15784046  -.7853453 -.01901869 -.3672469 -.16199577 -.32023725 31
      .3384363   .28591144 40 1  .4828812 -.30397725 -.1659081  -.2980709 -.7633781 -.3390412 -.15784046 -.12205097 -.01901869 -.3672469 -.16199577   2.521961 40
      .5849437    .5792981 33 1 -.6650371 -.30397725 -.1659081 -1.0037041 .19223966 -.3390412 -.15784046  -.8041514  -.8828008 -.3672469 -.16199577 -.29128608 33
      .5849437    .5792981 39 1  .4828812 -.30397725 -.1659081  -.3333256 -.7633781 -.3390412 -.15784046  -.8674082  -.8828008 -.3672469 -.16199577   2.732938 39
      .3384363    .5792981 38 1  .4828812 -.30397725 -.1659081  -.4450214 -.7633781 -.3390412 -.15784046  -.8252884  -.8828008 -.3672469 -.16199577   2.098731 38
    end

    Thank you.
    John

    Comment


    • #3
      Code:
      coefplot (out1, keep(*14)) (out1, keep(*58)) (out1, keep(*912)) ..., vert nokey
      coefplot (out2, keep(*14)) (out2, keep(*58)) (out2, keep(*912)) ..., vert nokey

      Comment


      • #4
        Hi Andrew,

        Many thanks for your response. Please I tried this option before posting. The plot did not suit what I wanted. Below is a (unrefined) copy of the plot using this option.

        Click image for larger version

Name:	stat_ex.png
Views:	1
Size:	55.0 KB
ID:	1744766

        Comment


        • #5
          You have to figure out the mid-points and show the labels for only these. Keep the categories if you want the colors to differ by age-group.

          Code:
          * Example generated by -dataex-. For more info, type help dataex
          clear
          input float(out1 out2) byte(fe1 fe2) float(e14 s14 q14 d14 e58 s58 q58 d58 e912 s912 q912 d912) int clustvar
            .0919287 -.007475017 44 1 -.6650371 -.30397725 -.1659081 -.10402028 .19223966 -.3390412 -.15784046   2.384596 -.01901869 -.3672469 -.16199577  -.7314057 44
            .0919287   .28591144 22 1 -.6650371 -.30397725 -.1659081  -.8479494 -.7633781 -.3390412 -.15784046 -1.0039667  -.8828008 -.3672469 -.16199577 -1.0610813 22
            .5849437    .5792981 44 1 -.6650371 -.30397725 -.1659081 -.10402028 .19223966 -.3390412 -.15784046   2.384596 -.01901869 -.3672469 -.16199577  -.7314057 44
            .0919287    .5792981 45 1 -.6650371 -.30397725 -.1659081  1.0571783 .19223966 -.3390412 -.15784046  1.3364686 -.01901869 -.3672469 -.16199577  -.8810784 45
            .5849437    .5792981 40 1  .4828812 -.30397725 -.1659081  -.2980709 -.7633781 -.3390412 -.15784046 -.12205097 -.01901869 -.3672469 -.16199577   2.521961 40
            .5849437    .5792981 46 1 -.6650371 -.30397725 -.1659081  1.9362162 1.1478574 -.3390412 -.15784046   .4942202  -.8828008 -.3672469 -.16199577  -.9179304 46
           -.4907253 -.072672024 28 1 -.6650371 -.30397725 -.1659081 -1.0226473 -.7633781 -.3390412 -.15784046 -1.0592517  -.8828008 -.3672469 -.16199577  -.7793982 28
           -.1545787 -.007475017 42 1 -.6650371 -.30397725 -.1659081  -.7878087 -.7633781 -.3390412 -.15784046   1.976216   .8447635 -.3672469 -.16199577    .562846 42
            .5849437    .5792981 33 1 -.6650371 -.30397725 -.1659081 -1.0037041 .19223966 -.3390412 -.15784046  -.8041514  -.8828008 -.3672469 -.16199577 -.29128608 33
            .5849437    .5792981 39 1  .4828812 -.30397725 -.1659081  -.3333256 -.7633781 -.3390412 -.15784046  -.8674082  -.8828008 -.3672469 -.16199577   2.732938 39
            .5849437    .5792981 37 1  .4828812 -.30397725 -.1659081  -.7672562 -.7633781 -.3390412 -.15784046   -.329943  -.8828008 -.3672469 -.16199577  1.1618173 37
            .3384363    .5792981 34 1 -.6650371 -.30397725 -.1659081  -.8041486 .19223966 -.3390412 -.15784046  -.4727512  -.8828008 -.3672469 -.16199577  -.8046436 34
            .3384363    .5792981 37 1  .4828812 -.30397725 -.1659081  -.7672562 -.7633781 -.3390412 -.15784046   -.329943  -.8828008 -.3672469 -.16199577  1.1618173 37
            .5849437    .5792981  7 1 -.6650371 -.30397725 -.1659081 -.13313164 -.7633781 -.3390412 -.15784046 -.50287265  -.8828008 -.3672469 -.16199577 -1.0570301  7
            .3160265     .253313 32 1 -.6650371 -.30397725 -.1659081 -1.0153013 -.7633781 -.3390412 -.15784046  -.8009288 -.01901869 -.3672469 -.16199577 -.28266147 32
            .5849437    .5792981 25 1 -.6650371 -.30397725 -.1659081  -.9357632 -.7633781 -.3390412 -.15784046 -1.0710821  -.8828008 -.3672469 -.16199577 -1.0347534 25
            .3160265     .253313  5 1 -.6650371 -.30397725 -.1659081  -.8174706 -.7633781 -.3390412 -.15784046  .11515166  -.8828008 -.3672469 -.16199577  -.8211402  5
            .5849437    .5792981 39 1  .4828812 -.30397725 -.1659081  -.3333256 -.7633781 -.3390412 -.15784046  -.8674082  -.8828008 -.3672469 -.16199577   2.732938 39
            .0919287   .28591144 42 1 -.6650371 -.30397725 -.1659081  -.7878087 -.7633781 -.3390412 -.15784046   1.976216   .8447635 -.3672469 -.16199577    .562846 42
            .3384363    .5792981 29 1 -.6650371 -.30397725 -.1659081 -1.0268047 -.7633781 -.3390412 -.15784046 -1.0473244 -.01901869 -.3672469 -.16199577  -.7827379 29
            .3384363    .5792981 42 1 -.6650371 -.30397725 -.1659081  -.7878087 -.7633781 -.3390412 -.15784046   1.976216   .8447635 -.3672469 -.16199577    .562846 42
            .5849437    .5792981 21 1 -.6650371 -.30397725 -.1659081  -.8763263 -.7633781 -.3390412 -.15784046  -.9774512  -.8828008 -.3672469 -.16199577  -1.059375 21
           .28913468    .5792981 42 1 -.6650371 -.30397725 -.1659081  -.7878087 -.7633781 -.3390412 -.15784046   1.976216   .8447635 -.3672469 -.16199577    .562846 42
            .0919287   .28591144 38 1  .4828812 -.30397725 -.1659081  -.4450214 -.7633781 -.3390412 -.15784046  -.8252884  -.8828008 -.3672469 -.16199577   2.098731 38
            .3160265     .253313 20 1 -.6650371 -.30397725 -.1659081  -.8747015 -.7633781 -.3390412 -.15784046  -.9837708  -.8828008 -.3672469 -.16199577 -1.0549439 20
            .5849437    .5792981 45 1 -.6650371 -.30397725 -.1659081  1.0571783 .19223966 -.3390412 -.15784046  1.3364686 -.01901869 -.3672469 -.16199577  -.8810784 45
            .5849437    .5792981 31 1 -.6650371 -.30397725 -.1659081 -1.0304538 -.7633781 -.3390412 -.15784046  -.7853453 -.01901869 -.3672469 -.16199577 -.32023725 31
            .0471092     .253313 39 1  .4828812 -.30397725 -.1659081  -.3333256 -.7633781 -.3390412 -.15784046  -.8674082  -.8828008 -.3672469 -.16199577   2.732938 39
            .3160265    .5792981 40 1  .4828812 -.30397725 -.1659081  -.2980709 -.7633781 -.3390412 -.15784046 -.12205097 -.01901869 -.3672469 -.16199577   2.521961 40
            .3384363    .5792981 37 1  .4828812 -.30397725 -.1659081  -.7672562 -.7633781 -.3390412 -.15784046   -.329943  -.8828008 -.3672469 -.16199577  1.1618173 37
            .5849437    .5792981 20 1 -.6650371 -.30397725 -.1659081  -.8747015 -.7633781 -.3390412 -.15784046  -.9837708  -.8828008 -.3672469 -.16199577 -1.0549439 20
            .5849437    .5792981 41 1 -.6650371 -.30397725 -.1659081  -.3061628 -.7633781 -.3390412 -.15784046  1.0721755 -.01901869 -.3672469 -.16199577  1.4357208 41
            .3384363   .28591144 28 1 -.6650371 -.30397725 -.1659081 -1.0226473 -.7633781 -.3390412 -.15784046 -1.0592517  -.8828008 -.3672469 -.16199577  -.7793982 28
            .5849437    .5792981 26 1 -.6650371 -.30397725 -.1659081  -.9615455 -.7633781 -.3390412 -.15784046 -1.0727285  -.8828008 -.3672469 -.16199577  -.8220592 26
            .5849437    .5792981 36 1 -.6650371 -.30397725 -.1659081  -.7641228 .19223966 -.3390412 -.15784046   -.321621  -.8828008 -.3672469 -.16199577 -.07583452 36
            .3384363    .5792981 40 1  .4828812 -.30397725 -.1659081  -.2980709 -.7633781 -.3390412 -.15784046 -.12205097 -.01901869 -.3672469 -.16199577   2.521961 40
            .5849437    .5792981 35 1 -.6650371 -.30397725 -.1659081  -.7489703 .19223966 -.3390412 -.15784046  -.3578784  -.8828008 -.3672469 -.16199577   -.848295 35
            .5849437    .5792981 38 1  .4828812 -.30397725 -.1659081  -.4450214 -.7633781 -.3390412 -.15784046  -.8252884  -.8828008 -.3672469 -.16199577   2.098731 38
            .3384363    .5792981 36 1 -.6650371 -.30397725 -.1659081  -.7641228 .19223966 -.3390412 -.15784046   -.321621  -.8828008 -.3672469 -.16199577 -.07583452 36
            .5849437    .5792981 42 1 -.6650371 -.30397725 -.1659081  -.7878087 -.7633781 -.3390412 -.15784046   1.976216   .8447635 -.3672469 -.16199577    .562846 42
            .5849437    .5792981 32 1 -.6650371 -.30397725 -.1659081 -1.0153013 -.7633781 -.3390412 -.15784046  -.8009288 -.01901869 -.3672469 -.16199577 -.28266147 32
            .5849437    .5792981 31 1 -.6650371 -.30397725 -.1659081 -1.0304538 -.7633781 -.3390412 -.15784046  -.7853453 -.01901869 -.3672469 -.16199577 -.32023725 31
            .3384363   .28591144 32 1 -.6650371 -.30397725 -.1659081 -1.0153013 -.7633781 -.3390412 -.15784046  -.8009288 -.01901869 -.3672469 -.16199577 -.28266147 32
            .5849437    .5792981 20 1 -.6650371 -.30397725 -.1659081  -.8747015 -.7633781 -.3390412 -.15784046  -.9837708  -.8828008 -.3672469 -.16199577 -1.0549439 20
            .5849437    .5792981 25 1 -.6650371 -.30397725 -.1659081  -.9357632 -.7633781 -.3390412 -.15784046 -1.0710821  -.8828008 -.3672469 -.16199577 -1.0347534 25
            .3160265    .5792981 34 1 -.6650371 -.30397725 -.1659081  -.8041486 .19223966 -.3390412 -.15784046  -.4727512  -.8828008 -.3672469 -.16199577  -.8046436 34
            .3384363   .28591144 39 1  .4828812 -.30397725 -.1659081  -.3333256 -.7633781 -.3390412 -.15784046  -.8674082  -.8828008 -.3672469 -.16199577   2.732938 39
            .3384363    .5792981 46 1 -.6650371 -.30397725 -.1659081  1.9362162 1.1478574 -.3390412 -.15784046   .4942202  -.8828008 -.3672469 -.16199577  -.9179304 46
            .5849437    .5792981 42 1 -.6650371 -.30397725 -.1659081  -.7878087 -.7633781 -.3390412 -.15784046   1.976216   .8447635 -.3672469 -.16199577    .562846 42
            .3160265    .5792981 41 1 -.6650371 -.30397725 -.1659081  -.3061628 -.7633781 -.3390412 -.15784046  1.0721755 -.01901869 -.3672469 -.16199577  1.4357208 41
           -.4907253  -.39865705 43 1 -.6650371 -.30397725 -.1659081  -.8287637 -.7633781 -.3390412 -.15784046  2.5881705   .8447635 -.3672469 -.16199577 -.14098415 43
          -.22180797     .253313 41 1 -.6650371 -.30397725 -.1659081  -.3061628 -.7633781 -.3390412 -.15784046  1.0721755 -.01901869 -.3672469 -.16199577  1.4357208 41
            .5849437    .5792981 46 1 -.6650371 -.30397725 -.1659081  1.9362162 1.1478574 -.3390412 -.15784046   .4942202  -.8828008 -.3672469 -.16199577  -.9179304 46
           -.1545787   -.3008616 26 1 -.6650371 -.30397725 -.1659081  -.9615455 -.7633781 -.3390412 -.15784046 -1.0727285  -.8828008 -.3672469 -.16199577  -.8220592 26
            .5849437    .5792981 35 1 -.6650371 -.30397725 -.1659081  -.7489703 .19223966 -.3390412 -.15784046  -.3578784  -.8828008 -.3672469 -.16199577   -.848295 35
           -.5982921   -.5209015 28 1 -.6650371 -.30397725 -.1659081 -1.0226473 -.7633781 -.3390412 -.15784046 -1.0592517  -.8828008 -.3672469 -.16199577  -.7793982 28
           -.1545787 -.007475017 37 1  .4828812 -.30397725 -.1659081  -.7672562 -.7633781 -.3390412 -.15784046   -.329943  -.8828008 -.3672469 -.16199577  1.1618173 37
            .5849437    .5792981 27 1 -.6650371 -.30397725 -.1659081 -1.0226473 -.7633781 -.3390412 -.15784046 -1.0748351  -.8828008 -.3672469 -.16199577  -.7632481 27
            .0471092     .253313 43 1 -.6650371 -.30397725 -.1659081  -.8287637 -.7633781 -.3390412 -.15784046  2.5881705   .8447635 -.3672469 -.16199577 -.14098415 43
            .0919287    .5792981 26 1 -.6650371 -.30397725 -.1659081  -.9615455 -.7633781 -.3390412 -.15784046 -1.0727285  -.8828008 -.3672469 -.16199577  -.8220592 26
            .5849437    .5792981 43 1 -.6650371 -.30397725 -.1659081  -.8287637 -.7633781 -.3390412 -.15784046  2.5881705   .8447635 -.3672469 -.16199577 -.14098415 43
            .5849437    .5792981 41 1 -.6650371 -.30397725 -.1659081  -.3061628 -.7633781 -.3390412 -.15784046  1.0721755 -.01901869 -.3672469 -.16199577  1.4357208 41
            .5849437    .5792981 28 1 -.6650371 -.30397725 -.1659081 -1.0226473 -.7633781 -.3390412 -.15784046 -1.0592517  -.8828008 -.3672469 -.16199577  -.7793982 28
          -.22180797     .253313 12 1 -.6650371 -.30397725 -.1659081  -.7421584 -.7633781 -.3390412 -.15784046 -1.0688194  -.8828008 -.3672469 -.16199577  -.8972574 12
            .3160265    .5792981 45 1 -.6650371 -.30397725 -.1659081  1.0571783 .19223966 -.3390412 -.15784046  1.3364686 -.01901869 -.3672469 -.16199577  -.8810784 45
            .3160265    .5792981 23 1 -.6650371 -.30397725 -.1659081  -.9142511 -.7633781 -.3390412 -.15784046 -1.0668064  -.8828008 -.3672469 -.16199577 -1.0632645 23
            .5849437    .5792981 35 1 -.6650371 -.30397725 -.1659081  -.7489703 .19223966 -.3390412 -.15784046  -.3578784  -.8828008 -.3672469 -.16199577   -.848295 35
            .5849437    .5792981 40 1  .4828812 -.30397725 -.1659081  -.2980709 -.7633781 -.3390412 -.15784046 -.12205097 -.01901869 -.3672469 -.16199577   2.521961 40
            .5849437    .5792981 46 1 -.6650371 -.30397725 -.1659081  1.9362162 1.1478574 -.3390412 -.15784046   .4942202  -.8828008 -.3672469 -.16199577  -.9179304 46
            .5849437    .5792981 33 1 -.6650371 -.30397725 -.1659081 -1.0037041 .19223966 -.3390412 -.15784046  -.8041514  -.8828008 -.3672469 -.16199577 -.29128608 33
            .3160265     .253313  1 1 -.6650371 -.30397725 -.1659081  -.8157464 -.7633781 -.3390412 -.15784046  -.8557939  -.8828008 -.3672469 -.16199577  .16999345  1
            .5849437    .5792981 22 1 -.6650371 -.30397725 -.1659081  -.8479494 -.7633781 -.3390412 -.15784046 -1.0039667  -.8828008 -.3672469 -.16199577 -1.0610813 22
            .5849437    .5792981 33 1 -.6650371 -.30397725 -.1659081 -1.0037041 .19223966 -.3390412 -.15784046  -.8041514  -.8828008 -.3672469 -.16199577 -.29128608 33
            .0471092     .253313 35 1 -.6650371 -.30397725 -.1659081  -.7489703 .19223966 -.3390412 -.15784046  -.3578784  -.8828008 -.3672469 -.16199577   -.848295 35
            .3384363    .5792981 32 1 -.6650371 -.30397725 -.1659081 -1.0153013 -.7633781 -.3390412 -.15784046  -.8009288 -.01901869 -.3672469 -.16199577 -.28266147 32
            .5849437    .5792981 35 1 -.6650371 -.30397725 -.1659081  -.7489703 .19223966 -.3390412 -.15784046  -.3578784  -.8828008 -.3672469 -.16199577   -.848295 35
            .5849437    .5792981 46 1 -.6650371 -.30397725 -.1659081  1.9362162 1.1478574 -.3390412 -.15784046   .4942202  -.8828008 -.3672469 -.16199577  -.9179304 46
           -.1545787 -.007475017 18 1 -.6650371 -.30397725 -.1659081 -1.0318102 -.7633781 -.3390412 -.15784046  -.8871397  -.8828008 -.3672469 -.16199577  -.9898191 18
            .3160265     .253313 41 1 -.6650371 -.30397725 -.1659081  -.3061628 -.7633781 -.3390412 -.15784046  1.0721755 -.01901869 -.3672469 -.16199577  1.4357208 41
            .3384363    .5792981 44 1 -.6650371 -.30397725 -.1659081 -.10402028 .19223966 -.3390412 -.15784046   2.384596 -.01901869 -.3672469 -.16199577  -.7314057 44
            .5849437    .5792981  4 1 -.6650371 -.30397725 -.1659081  -.8325666 -.7633781 -.3390412 -.15784046 .074372135  -.8828008 -.3672469 -.16199577  -.7559876  4
            .5849437    .5792981 41 1 -.6650371 -.30397725 -.1659081  -.3061628 -.7633781 -.3390412 -.15784046  1.0721755 -.01901869 -.3672469 -.16199577  1.4357208 41
            .5849437    .5792981 45 1 -.6650371 -.30397725 -.1659081  1.0571783 .19223966 -.3390412 -.15784046  1.3364686 -.01901869 -.3672469 -.16199577  -.8810784 45
            .5849437    .5792981 31 1 -.6650371 -.30397725 -.1659081 -1.0304538 -.7633781 -.3390412 -.15784046  -.7853453 -.01901869 -.3672469 -.16199577 -.32023725 31
            .5849437    .5792981 43 1 -.6650371 -.30397725 -.1659081  -.8287637 -.7633781 -.3390412 -.15784046  2.5881705   .8447635 -.3672469 -.16199577 -.14098415 43
            .3384363    .5792981 26 1 -.6650371 -.30397725 -.1659081  -.9615455 -.7633781 -.3390412 -.15784046 -1.0727285  -.8828008 -.3672469 -.16199577  -.8220592 26
           -.1545787 -.007475017 37 1  .4828812 -.30397725 -.1659081  -.7672562 -.7633781 -.3390412 -.15784046   -.329943  -.8828008 -.3672469 -.16199577  1.1618173 37
           .28913468    .5792981 34 1 -.6650371 -.30397725 -.1659081  -.8041486 .19223966 -.3390412 -.15784046  -.4727512  -.8828008 -.3672469 -.16199577  -.8046436 34
            .3384363   .28591144 41 1 -.6650371 -.30397725 -.1659081  -.3061628 -.7633781 -.3390412 -.15784046  1.0721755 -.01901869 -.3672469 -.16199577  1.4357208 41
            .3384363    .5792981 30 1 -.6650371 -.30397725 -.1659081 -1.0284055 -.7633781 -.3390412 -.15784046   -.842093 -.01901869 -.3672469 -.16199577  -.4392872 30
            .3384363   .28591144 38 1  .4828812 -.30397725 -.1659081  -.4450214 -.7633781 -.3390412 -.15784046  -.8252884  -.8828008 -.3672469 -.16199577   2.098731 38
            .5849437    .5792981 39 1  .4828812 -.30397725 -.1659081  -.3333256 -.7633781 -.3390412 -.15784046  -.8674082  -.8828008 -.3672469 -.16199577   2.732938 39
            .5849437    .5792981 44 1 -.6650371 -.30397725 -.1659081 -.10402028 .19223966 -.3390412 -.15784046   2.384596 -.01901869 -.3672469 -.16199577  -.7314057 44
           -.1545787 -.007475017 21 1 -.6650371 -.30397725 -.1659081  -.8763263 -.7633781 -.3390412 -.15784046  -.9774512  -.8828008 -.3672469 -.16199577  -1.059375 21
            .3160265    .5792981 28 1 -.6650371 -.30397725 -.1659081 -1.0226473 -.7633781 -.3390412 -.15784046 -1.0592517  -.8828008 -.3672469 -.16199577  -.7793982 28
            .5849437    .5792981 31 1 -.6650371 -.30397725 -.1659081 -1.0304538 -.7633781 -.3390412 -.15784046  -.7853453 -.01901869 -.3672469 -.16199577 -.32023725 31
            .3384363   .28591144 40 1  .4828812 -.30397725 -.1659081  -.2980709 -.7633781 -.3390412 -.15784046 -.12205097 -.01901869 -.3672469 -.16199577   2.521961 40
            .5849437    .5792981 33 1 -.6650371 -.30397725 -.1659081 -1.0037041 .19223966 -.3390412 -.15784046  -.8041514  -.8828008 -.3672469 -.16199577 -.29128608 33
            .5849437    .5792981 39 1  .4828812 -.30397725 -.1659081  -.3333256 -.7633781 -.3390412 -.15784046  -.8674082  -.8828008 -.3672469 -.16199577   2.732938 39
            .3384363    .5792981 38 1  .4828812 -.30397725 -.1659081  -.4450214 -.7633781 -.3390412 -.15784046  -.8252884  -.8828008 -.3672469 -.16199577   2.098731 38
          end
          
          local out "out1 out2"
          estimates clear
          foreach v in `out' {
              eststo `v': regress `v' e14 d14 e58 d58 e912 d912  
          }
          
          coefplot (out1, keep(d*) lab(d)) (out1, keep(e*) lab(e)),  vert order(*14 *58 *912) aseq xlab( 1.5 "1-4" 3.5 "5-8" 5.5 "9-12", notick)
          Click image for larger version

Name:	Graph.png
Views:	1
Size:	12.8 KB
ID:	1744787

          Comment


          • #6
            Hi Andrew,

            Thank you very much for the code. It worked perfectly. I wanted to show all the four types of shocks on the same plot. Since this does not produce a neat figure, I will adopt your approach and plot the four shocks on two separate figures.


            John

            Comment

            Working...
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