            name:  <unnamed>
             log:  C:\Users\isyoo\OneDrive - Singapore Management University\Desktop\
      > Work\JAR AI Aanalysts\JAR Replication Package\Log flies\Appendix B and Figure
      >  2.smcl
        log type:  smcl
       opened on:  19 Jul 2026, 09:01:01
      
     1 . do "C:\Users\isyoo\AppData\Local\Temp\STD1ffc_000003.tmp"
      
     2 . /*Appendix B - Comparing the AI job posting based measure and the AI disclosu
      > res*/
     3 . cd "C:\Users\isyoo\OneDrive - Singapore Management University\Desktop\Work\JA
      > R AI Aanalysts"
      C:\Users\isyoo\OneDrive - Singapore Management University\Desktop\Work\JAR AI A
      > analysts
      
     4 . use "analystfirmyear_sample", clear
      
     5 . rename *, lower 
      
     6 . keep if year>2009
      (12,489 observations deleted)
      
     7 . keep if year<2020
      (67,068 observations deleted)
      
     8 . egen broker=group(estimator)
      
     9 . gen aihiringratio=ai_hiring/total_jobs
      
    10 . gen nonaihiringratio=nonaitech_hiring/total_jobs
      
    11 . gen aidisclosure=log(1+total_ai_mentions)
      (21,409 missing values generated)
      
    12 . replace num_words=log(1+num_words)
      (130,832 real changes made)
      
    13 . gen totalj=log(1+total_jobs)
      
    14 . collapse aidisclosure aihiringratio nonaihiringratio logbrokersize num_words 
      > totalj, by (brokergvkey broker year)
      
    15 . winsor2 aidisclosure aihiringratio nonaihiringratio logbrokersize num_words t
      > otalj, cuts(1 99) replace 
      
    16 . replace aidisclosure=0 if aidisclosure==.
      (31 real changes made)
      
    17 . replace aihiringratio=0 if aihiringratio==.
      (0 real changes made)
      
    18 . replace nonaihiringratio=0 if nonaihiringratio==.
      (0 real changes made)
      
    19 . eststo clear
      
    20 . local controls "logbrokersize num_words totalj"
      
    21 . eststo: reghdfe aidisclosure aihiringratio `controls', noabsorb vce(robust)
      (MWFE estimator converged in 1 iterations)
      
      HDFE Linear regression                            Number of obs   =        129
      Absorbing 1 HDFE group                            F(   4,    124) =       2.89
                                                        Prob > F        =     0.0251
                                                        R-squared       =     0.1126
                                                        Adj R-squared   =     0.0839
                                                        Within R-sq.    =     0.1126
                                                        Root MSE        =     0.5388
      
      -------------------------------------------------------------------------------
                    |               Robust
       aidisclosure | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
      --------------+----------------------------------------------------------------
      aihiringratio |   5.833769   1.770438     3.30   0.001     2.329576    9.337961
      logbrokersize |   .0509687    .101229     0.50   0.616    -.1493919    .2513292
          num_words |  -.0128779   .0843075    -0.15   0.879     -.179746    .1539901
             totalj |  -.0191703   .0248759    -0.77   0.442    -.0684066    .0300659
              _cons |   .2526465   .7949043     0.32   0.751    -1.320692    1.825985
      -------------------------------------------------------------------------------
      (est1 stored)
      
    22 . outreg2 using 1.doc, nolabel tstat tdec(2) dec(3) replace
      1.doc
      dir : seeout
      
    23 . eststo: reghdfe aidisclosure nonaihiringratio `controls', noabsorb vce(robust
      > )
      (MWFE estimator converged in 1 iterations)
      
      HDFE Linear regression                            Number of obs   =        129
      Absorbing 1 HDFE group                            F(   4,    124) =       0.50
                                                        Prob > F        =     0.7336
                                                        R-squared       =     0.0123
                                                        Adj R-squared   =    -0.0196
                                                        Within R-sq.    =     0.0123
                                                        Root MSE        =     0.5684
      
      -------------------------------------------------------------------------------
      ---
                       |               Robust
          aidisclosure | Coefficient  std. err.      t    P>|t|     [95% conf. interv
      > al]
      -----------------+-------------------------------------------------------------
      ---
      nonaihiringratio |   1.337329   1.206615     1.11   0.270      -1.0509    3.725
      > 558
         logbrokersize |   .0960057   .1054822     0.91   0.365    -.1127731    .3047
      > 845
             num_words |  -.1008198   .1091398    -0.92   0.357     -.316838    .1151
      > 983
                totalj |   .0003578   .0264733     0.01   0.989    -.0520402    .0527
      > 558
                 _cons |   .8260689   .9639786     0.86   0.393    -1.081915    2.734
      > 053
      -------------------------------------------------------------------------------
      ---
      (est2 stored)
      
    24 . outreg2 using 1.doc, nolabel tstat tdec(2) dec(3) append
      1.doc
      dir : seeout
      
    25 . noisily: esttab, r2 star(* 0.1 ** 0.05 *** 0.01)  nonote b(%9.3f) keep(aihiri
      > ngratio nonaihiringratio `controls') order(aihiringratio nonaihiringratio `co
      > ntrols')
      
      --------------------------------------------
                            (1)             (2)   
                   aidisclosure    aidisclosure   
      --------------------------------------------
      aihiringra~o        5.834***                
                         (3.30)                   
      
      nonaihirin~o                        1.337   
                                         (1.11)   
      
      logbrokers~e        0.051           0.096   
                         (0.50)          (0.91)   
      
      num_words          -0.013          -0.101   
                        (-0.15)         (-0.92)   
      
      totalj             -0.019           0.000   
                        (-0.77)          (0.01)   
      --------------------------------------------
      N                     129             129   
      R-sq                0.113           0.012   
      --------------------------------------------
      
    26 . 
    27 . /*Figure 2 - Obtaining numbers for the graphs from raw datasets*/
    28 . /*AI job postings*/
    29 . use "firm_data.dta", clear
      
    30 . /*These include the following tech bigrams: machine learnings, learning algor
      > ithms, and neural networks*/
    31 . keep if title=="Machine learning" | title=="Neural network"
      (49,416,428 observations deleted)
      
    32 . keep if poster_name=="alliancebernsteinlp" | poster_name=="morganstanley" | p
      > oster_name=="jpmorganchasecompany" | poster_name=="bankofamerica" | poster_na
      > me=="hsbc" | poster_name=="thegoldmansachsgroupinc" | poster_name=="creditsui
      > sse" | poster_name=="deutschebank" | poster_name=="nomuraholdingamericaincorp
      > orated" | poster_name=="macquarie" | poster_name=="raymondjamesfinancialincor
      > porated" | poster_name=="oppenheimerfunds" | poster_name=="stifelclientservic
      > es" | poster_name=="williamblaircompany"  | poster_name=="piperjaffrayandco" 
      >  | poster_name=="royalbankofcanada"  
      (437,678 observations deleted)
      
    33 . replace gvkey=1 if poster_name=="williamblaircompany"
      (44 real changes made)
      
    34 . replace gvkey=2 if poster_name=="piperjaffrayandco" 
      (40 real changes made)
      
    35 . collapse (max)total_jobs (sum)tech_hiring, by (year gvkey poster_name) 
      
    36 . collapse (sum)total_jobs (sum)tech_hiring, by (year) 
      
    37 . gen ratio=tech_hiring/total_jobs
      
    38 . format ratio %9.4f
      
    39 . list year ratio, noobs clean
      
          year    ratio  
          2010   0.0003  
          2011   0.0002  
          2012   0.0005  
          2013   0.0008  
          2014   0.0024  
          2015   0.0023  
          2016   0.0040  
          2017   0.0143  
          2018   0.0764  
          2019   0.0684  
      
    40 . /*Other technology job postings*/
    41 . use "firm_data.dta", clear
      
    42 . /*These include the following non-AI data analytics bigrams excluding machine
      >  learnings, learning algorithms, and neural networks*/
    43 . drop if title=="Machine learning" | title=="Neural network"
      (438,467 observations deleted)
      
    44 . keep if poster_name=="alliancebernsteinlp" | poster_name=="morganstanley" | p
      > oster_name=="jpmorganchasecompany" | poster_name=="bankofamerica" | poster_na
      > me=="hsbc" | poster_name=="thegoldmansachsgroupinc" | poster_name=="creditsui
      > sse" | poster_name=="deutschebank" | poster_name=="nomuraholdingamericaincorp
      > orated" | poster_name=="macquarie" | poster_name=="raymondjamesfinancialincor
      > porated" | poster_name=="oppenheimerfunds" | poster_name=="stifelclientservic
      > es" | poster_name=="williamblaircompany"  | poster_name=="piperjaffrayandco" 
      >  | poster_name=="royalbankofcanada"    
      (49,335,209 observations deleted)
      
    45 . replace gvkey=1 if poster_name=="williamblaircompany"
      (4,657 real changes made)
      
    46 . replace gvkey=2 if poster_name=="piperjaffrayandco" 
      (4,594 real changes made)
      
    47 . collapse (max)total_jobs (sum)tech_hiring, by (year gvkey poster_name) 
      
    48 . collapse (sum)total_jobs (sum)tech_hiring, by (year) 
      
    49 . gen ratio=tech_hiring/total_jobs
      
    50 . format ratio %9.4f
      
    51 . list year ratio, noobs clean
      
          year    ratio  
          2010   0.1623  
          2011   0.1565  
          2012   0.1729  
          2013   0.1508  
          2014   0.1974  
          2015   0.2014  
          2016   0.1982  
          2017   0.2140  
          2018   0.2394  
          2019   0.2355  
      
    52 . 
      end of do-file
      
    53 . log close
            name:  <unnamed>
             log:  C:\Users\isyoo\OneDrive - Singapore Management University\Desktop\
      > Work\JAR AI Aanalysts\JAR Replication Package\Log flies\Appendix B and Figure
      >  2.smcl
        log type:  smcl
       closed on:  19 Jul 2026, 09:01:57
      -------------------------------------------------------------------------------
