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dissertation-chapter-x-analysis-barnett-salomon-replication.do
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dissertation-chapter-x-analysis-barnett-salomon-replication.do
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***===================================================***
* NARROW REPLICATION 1 *
* SAME DESIGN, SAME POPULATION, SAME SAMPLE *
***===================================================***
/*** Variables from Barnett and Salomon 2012
Performance
- ROA = Net Income / Total Assets ($millions)
- Net Income = Earnings after interest, taxes, depreciation, amortization ($millions)
Social Responsibility (proxy for what they call "stakeholder influence capacity"
- Net KLD Score = KLD strengths - KLD concerns
Controls
- Firm size = Number of employees (1000s)
- Debt ratio = Long-term debt / Total assets
- R&D intensity = R&D expenditures / sales
- Advertising intensity = Advertising expenditures / sales
- Industry =
*/
*** LOAD DATA
use data/kld-cstat-bs2012.dta, clear
*** DATA DECISIONS
* Barnett & Salomon assume missing advertising data = 0
keep if in_bs2012==1
replace ad=0 if ad==.
*** BS TABLE 1: CORRELATION TABLE
corr roa lroa ni lni net_kld_adj net_kld_adj_sq emp debt rd ad, means
pwcorr roa lroa ni lni net_kld_adj net_kld_adj_sq emp debt rd ad, st(.05) list
*** KEEP OBSERVATIONS WITH ALL NEEDED VARIABLES
gen comp=(net_kld_adj!=. & net_kld_adj!=. & lroa!=. & emp!=. & debt!=. & rd!=. & ad!=.)
keep if comp==1
*** BS TABLE 2: ROA REGRESSION
est clear
qui reg roa lroa emp debt rd ad
est sto t21
qui reg roa net_kld_adj lroa emp debt rd ad
est sto t22
qui reg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad
est sto t23
qui reg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad i.year
est sto t24
qui reg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad i.year i.naics_n
est sto t25
qui xtreg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad i.year, fe
est sto t26
estout *, cells(b(star fmt(%9.3f)) z(par)) ///
stats(N N_g r2_a, fmt(%9.0g %9.0g %9.0g %9.4g) ///
labels("N" "Firms" "Adj. R^2")) ///
legend collabels(none) ///
keep(net_kld_adj net_kld_adj_sq lroa emp debt rd ad _cons) ///
order(net_kld_adj net_kld_adj_sq lroa emp debt rd ad _cons) ///
starlevels(* .1 ** .05 *** .01)
outreg2 [t21 t22 t23 t24 t25 t26] using "tables-and-figures/barnett-salomon-replicated-figures/bs2012-table-2-roa-regression", excel ///
stats(coef tstat) ///
keep(net_kld_adj net_kld_adj_sq lroa emp debt rd ad) ///
sortvar(net_kld_adj net_kld_adj_sq lroa emp debt rd ad) ///
e(N_g r2_a r2_o r2_b r2_w) ///
dec(2) fmt(f) ///
replace
*** BS TABLE 3: NI REGRESSION
est clear
qui reg ni lni emp debt rd ad
est sto t31
qui reg ni net_kld_adj lni emp debt rd ad
est sto t32
qui reg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad
est sto t33
qui reg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad i.year
est sto t34
qui reg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad i.year i.naics_n
est sto t35
qui xtreg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad i.year, fe
est sto t36
estout *, cells(b(star fmt(%9.3f)) t(par)) ///
stats(N N_g r2_a, fmt(%9.0g %9.0g %9.0g %9.4g) ///
labels("N" "Firms" "Adj. R^2")) ///
legend collabels(none) ///
keep(net_kld_adj net_kld_adj_sq lni emp debt rd ad _cons) ///
order(net_kld_adj net_kld_adj_sq lni emp debt rd ad _cons) ///
starlevels(* .1 ** .05 *** .01)
outreg2 [t31 t32 t33 t34 t35 t36] using "tables-and-figures/barnett-salomon-replicated-figures/bs2012-table-3-ni-regression", excel ///
stats(coef tstat) ///
keep(net_kld_adj net_kld_adj_sq lni emp debt rd ad) ///
sortvar(net_kld_adj net_kld_adj_sq lni emp debt rd ad) ///
e(N_g r2_a r2_o r2_b r2_w) ///
dec(2) fmt(f) ///
replace
*** BS FIGURE 1
/* B&S2012: "We use the models with the most explanatory power to graph these relationships.
For ROA, we base Figure 1 on Model 5 from Table 3.
NOTE: B&S are wrong in the above quote. Table 3 reports regressions of NI, not ROA.
I assume they mean Model 5 from Table 2, which reports regressions of ROA.
*/
reg roa i.net_kld_adj i.net_kld_adj_sq lroa emp debt rd ad i.year i.naics_n
margins net_kld_adj
/* Margins not estimable. I'm guessing what they did is take the point estimates from
the regression and plot them against a y-axis labeled as the DV
But margins works when I exclude net_kld_adj_sq from the model.
Is that what they did, simply drop one of the independent variables?!*/
reg roa i.net_kld_adj lroa emp debt rd ad i.year i.naics_n
margins net_kld_adj
marginsplot, xti("Adjusted Net KLD Score") yti("ROA Impact") ///
xlab(0(1)26) ///
scheme(s1mono) ///
scale(.8) ///
yline(0,lp(dot)) ///
xline(11,lp(dot)) ///
note("Vertical line at x = 11 indicates unadjusted net KLD score of 0")
*** BS FIGURE 2
/* B&S2012: "For net income, we use Model 4 from Table 4.
NOTE: B&S are wrong in the above quote. There is no Table 4 in the paper.
I assume they mean Model 4 from Table 3, which reports regressions of NI.
*/
reg ni i.net_kld_adj net_kld_adj_sq lni emp debt rd ad i.year
margins net_kld_adj, cont
/* Margins not estimable. I'm guessing what they did is take the point estimates from
the regression and plot them against a y-axis labeled as the DV
But margins works when I exclude net_kld_adj_sq from the model.
Is that what they did, simply drop one of the independent variables?!
*/
* Set net_kld_adj base to 11, which is 0 prior to adjustment
fvset base 11 net_kld_adj
reg ni i.net_kld_adj lni emp debt rd ad i.year
margins net_kld_adj
*see https://www.ssc.wisc.edu/sscc/pubs/stata_margins.htm
marginsplot, xti("Adjusted Net KLD Score") yti("Net Income Impact") ///
xlab(0(1)26) ///
scheme(s1mono) ///
scale(.8) ///
yline(0,lp(dot)) ///
xline(11,lp(dot)) ///
note("Vertical line at x = 11 indicates unadjusted net KLD score of 0") ///
plotopts(connect(none)) ///
saving(predictive-margins-net_kld_adj, replace)
margins, dydx(net_kld_adj) base
marginsplot, xti("Adjusted Net KLD Score") yti("Net Income Impact") ///
xlab(,angle(90)) ///
scheme(s1mono) ///
scale(.8) ///
yline(0,lp(dot)) ///
xline(11,lp(dot)) ///
note("Vertical line at x = 11 indicates unadjusted net KLD score of 0") ///
plotopts(connect(none)) ///
saving(marginal-effects-net_kld_adj, replace)
graph combine predictive-margins-net_kld_adj.gph marginal-effects-net_kld_adj.gph, cols(1) ycommon xcommon
***===================================================***
* NARROW REPLICATION 2 *
* SAME DESIGN, SAME POPULATION, NEW SAMPLE *
***===================================================***
*** LOAD DATA
use data/kld-cstat-bs2012.dta, clear
*** DATA DECISIONS
* Barnett & Salomon assume missing advertising data = 0
replace ad=0 if ad==.
* Post 1998 to align with Barnett & Salomon's claim that KLD reporting changed in 1998
drop if year<1998
*** CORRELATION TABLE
corr roa lroa ni lni net_kld_adj net_kld_adj_sq emp debt rd ad, means
pwcorr roa lroa ni lni net_kld_adj net_kld_adj_sq emp debt rd ad, st(.05) list
*** ROA REGRESSION
est clear
qui reg roa lroa emp debt rd ad
est sto m1
qui reg roa net_kld_adj lroa emp debt rd ad
est sto m2
qui reg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad
est sto m3
qui reg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad i.year
est sto m4
set matsize 800
qui reg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad i.year i.naics_n
est sto m5
qui xtreg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad i.year, fe
est sto m6
estout *, cells(b(star fmt(%9.3f)) z(par)) ///
stats(N N_g r2_a r2_o r2_b r2_w, fmt(%9.0g %9.0g %9.0g %9.4g) ///
labels("N" "Firms" "Adj. R^2" "R^2 Overall" "R^2 Between" "R^2 Within")) ///
legend collabels(none) ///
keep(net_kld_adj net_kld_adj_sq lroa emp debt rd ad _cons) ///
order(net_kld_adj net_kld_adj_sq lroa emp debt rd ad _cons) ///
title("Regressions of ROA using KLD data from 1998 - 2015.") ///
starlevels(* .1 ** .05 *** .01)
outreg2 [m1 m2 m3 m4 m5 m6] using "tables-and-figures/barnett-salomon-replicated-figures/rep2-roa-regression", excel ///
stats(coef tstat) ///
keep(net_kld_adj net_kld_adj_sq lroa emp debt rd ad) ///
sortvar(net_kld_adj net_kld_adj_sq lroa emp debt rd ad) ///
dec(3) fmt(f) ///
e(N_g r2_a r2_o r2_b r2_w) ///
replace
*** NET INCOME REGRESSION
est clear
qui reg ni lni emp debt rd ad
est sto ni1
qui reg ni net_kld_adj lni emp debt rd ad
est sto ni2
qui reg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad
est sto ni3
qui reg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad i.year
est sto ni4
qui reg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad i.year i.naics_n
est sto ni5
qui xtreg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad i.year, fe
est sto ni6
estout *, cells(b(star fmt(%9.3f)) z(par)) ///
stats(N N_g r2_a r2_o r2_b r2_w, fmt(%9.0g %9.0g %9.0g %9.4g) ///
labels("N" "Firms" "Adj. R^2" "R^2 Overall" "R^2 Between" "R^2 Within")) ///
legend collabels(none) ///
keep(net_kld_adj net_kld_adj_sq lni emp debt rd ad _cons) ///
order(net_kld_adj net_kld_adj_sq lni emp debt rd ad _cons) ///
title("Regressions of NET INCOME using KLD data from 1998 - 2015.") ///
starlevels(* .1 ** .05 *** .01)
outreg2 [ni1 ni2 ni3 ni4 ni5 ni6] using "tables-and-figures/barnett-salomon-replicated-figures/rep2-ni-regression", excel ///
stats(coef tstat) ///
keep(net_kld_adj net_kld_adj_sq lni emp debt rd ad) ///
sortvar(net_kld_adj net_kld_adj_sq lni emp debt rd ad) ///
dec(3) fmt(f) ///
e(N_g r2_a r2_o r2_b r2_w) ///
replace
***===================================================***
* QUASI-REPLICATION 3 *
* SAME DESIGN, NEW POPULATION, NEW SAMPLE *
***===================================================***
*** LOAD DATA TO CREATE SAMPLE FROM NEW POPULATION
/*
use data/csrhub-all.dta, clear
* Randomly sample 4,000 firms
drop if ticker==""
drop if ticker=="NA" & firm!="National Bank of Canada"
bysort ticker: gen n=_n
keep if n==1
drop n
set seed 61047
gen rngstate=c(rngstate)
label var rngstate "Stata rngstate from set seed 61047
sample 4000, count
gen in_rando=1
label var in_rando "=1 if a firm in the random sample of CSRHub firms"
compress
save data-csrhub/random-4000-csrhub-firms.dta
*/
*** MATCH THE SAMPLE WITH KLD
use data/random-4000-csrhub-firms.dta, clear
keep firm ticker tic_csrhub year in_csrhub
gen firm_csrhub=upper(firm)
rename year year_csrhub
drop if strpos(firm_csrhub,"FUND")>0
merge 1:m ticker using data/kld-cstat-bs2012.dta
/*
Result # of obs.
-----------------------------------------
not matched 38,073
from master 1,943 (_merge==1)
from using 36,130 (_merge==2)
matched 13,539 (_merge==3)
-----------------------------------------
*/
replace firm_kld=upper(firm_kld)
foreach v in "," "." {
replace firm_kld=subinstr(firm_kld,"`v'","",.)
replace firm_csrhub=subinstr(firm_csrhub,"`v'","",.)
}
ustrdist firm_kld firm_csrhub if _merge==3
stem strdist
/*Stem-and-leaf plot for strdist
0* | 0000000000000000000000000000000000000000000000000000000000000 ... (8700)
0* | 11111111111111111111111111111111111111111111111111111111111111 ... (135)
0* | 2222222222222222222222222222222
0* | 333333333333333333333333333333333333333333333333333333333333333 ... (94)
0* | 44444444444444444444444444444444444444444444444444444444444444 ... (576)
0* | 55555555555555555555555555555555555555555555555555555555555555 ... (141)
0* | 66666666666666666666666666666666666666666666666666666666666666 ... (125)
0* | 77777777777777777777777777777777777777777777777777777777777777 ... (379)
0* | 88888888888888888888888888888888888888888888888888888888888888 ... (137)
0* | 99999999999999999999999999999999999999999999999999999999999999 ... (344)
1* | 00000000000000000000000000000000000000000000000000000000000000 ... (277)
1* | 11111111111111111111111111111111111111111111111111111111111111 ... (171)
1* | 22222222222222222222222222222222222222222222222222222222222222 ... (236)
1* | 33333333333333333333333333333333333333333333333333333333333333 ... (244)
1* | 44444444444444444444444444444444444444444444444444444444444444 ... (109)
1* | 55555555555555555555555555555555555555555555555555555555555555 ... (243)
1* | 66666666666666666666666666666666666666666666666666666666666666 ... (222)
1* | 77777777777777777777777777777777777777777777777777777777777777 ... (206)
1* | 88888888888888888888888888888888888888888888888888888888888888 ... (163)
1* | 99999999999999999999999999999999999999999999999999999999999999 ... (147)
2* | 00000000000000000000000000000000000000000000000000000000000000 ... (150)
2* | 11111111111111111111111111111111111111111111111111111111111111 ... (142)
2* | 22222222222222222222222222222222222222222222222222222222222222 ... (136)
2* | 33333333333333333333333333333333333333333333333333333333333333 ... (105)
2* | 44444444444444444444444444444444444444444444444444444444444444444444444
2* | 555555555555555555555555555
2* | 666666666666666666666666666666666666666666666666666666
2* | 77777777777777777777777777777777777777777
2* | 88888888888888888888888888
2* | 99999999999999
3* | 00000000000
3* | 1111111111111111111111
3* | 2222222222222222222
3* | 33333333333333
3* | 44
3* | 55555555555
3* | 66666
3* | 7777
3* | 8
3* | 999
4* |
4* |
4* |
4* |
4* |
4* |
4* |
4* |
4* |
4* |
5* | 0
*/
*** SAVE
compress
capt save data/replication3.dta
*** DATA DECISIONS
* Barnett & Salomon assume missing advertising data = 0
replace ad=0 if ad==.
* Post 1998 to align with Barnett & Salomon's claim that KLD reporting changed in 1998
drop if year<1998
* Keep firms merged from CSRHub population
keep if _merge==3
xtset firm_n year, y
*** CORRELATION TABLE
corr roa lroa ni lni net_kld_adj net_kld_adj_sq emp debt rd ad, means
pwcorr roa lroa ni lni net_kld_adj net_kld_adj_sq emp debt rd ad, st(.05) list
/*
(obs=5,336)
Variable | Mean Std. Dev. Min Max
-------------+----------------------------------------------------
roa | .0125124 .1845652 -2.435433 1.625642
lroa | .0095886 .214167 -6.783386 1.625642
ni | 408.5504 2132.727 -16198 53394
lni | 379.3568 1979.551 -16198 41733
net_kld_adj | 11.49569 2.614856 1 29
net_kld_ad~q | 138.9871 70.17546 1 841
emp | 21.87611 114.2367 0 2300
debt | .1830017 .2154874 0 2.444689
rd | 9.624451 395.491 0 25684.4
ad | .0122439 .0499207 0 2.821317
| roa lroa ni lni net_kl~j net_kl~q emp debt rd ad
-------------+------------------------------------------------------------------------------------------
roa | 1.0000
lroa | 0.6022 1.0000
ni | 0.1405 0.0991 1.0000
lni | 0.1195 0.1334 0.8933 1.0000
net_kld_adj | 0.0675 0.0665 0.1019 0.1010 1.0000
net_kld_ad~q | 0.0780 0.0755 0.1382 0.1402 0.9751 1.0000
emp | 0.0525 0.0492 0.4173 0.4301 -0.0571 -0.0050 1.0000
debt | -0.0516 -0.0373 -0.0193 -0.0155 -0.0648 -0.0507 0.0430 1.0000
rd | -0.0924 -0.0585 -0.0075 -0.0073 0.0021 -0.0003 -0.0045 0.0272 1.0000
ad | -0.0562 -0.0403 -0.0001 -0.0012 0.0529 0.0540 -0.0037 0.0026 -0.0037 1.0000
*/
* Generate rep3 flag
gen in_rep3=(roa!=. & lroa!=. & ni!=. & lni!=. & net_kld_adj!=. & net_kld_adj_sq!=. & emp!=. & debt!=. & rd!=. & ad!=.)
*** ID MIN/MAX VALUES
replace firm=upper(firm)
keep if in_rep3==1
sort roa
list firm year roa ni at in 1/5
/* MINIMUM 5 OBS ON ROA
+------------------------------------------------------------------------------------+
| firm year roa ni at |
|------------------------------------------------------------------------------------|
1. | NEOPROBE CORP. 2012 -2.435433 -29.157 11.972 |
2. | VERISIGN, INC. 2002 -2.074712 -4961.297 2391.318 |
3. | OPKO HEALTH, INC. 2008 -1.83027 -39.834 21.764 |
4. | CELL THERAPEUTICS, INC 2010 -1.542058 -82.642 53.592 |
5. | INTEGRATED DEVICE TECHNOLOGY, INC. (IDT) 2008 -1.54071 -1045.167 678.367 |
+------------------------------------------------------------------------------------+
*/
gsort -roa
list firm year roa ni at in 1/5
/* MAX 5 OBS ON ROA
+-------------------------------------------------------------------------------------+
| firm year roa ni at |
|-------------------------------------------------------------------------------------|
1. | LIGAND PHARMACEUTICALS INCORPORATED 2007 1.625642 281.688 173.278 |
2. | SYNTA PHARMACEUTICALS CORP. 2009 1.617011 79.08799999999999 48.91 |
3. | QUESTCOR PHARMACEUTICALS, INC. 2012 .7830853 197.675 252.431 |
4. | ZIX CORPORATION 2010 .6164812 41.213 66.852 |
5. | CAMBREX CORPORATION 2007 .5602926 209.248 373.462 |
+-------------------------------------------------------------------------------------+
*/
sort ni
list firm year roa ni at in 1/5
/* MINIMUM 5 OBS ON NI
+---------------------------------------------------------------+
| firm year roa ni at |
|---------------------------------------------------------------|
1. | LUCENT TECHNOLOGIES INC. 2001 -.4811668 -16198 33664 |
2. | FORD MOTOR COMPANY 2008 -.0672016 -14672 218328 |
3. | FORD MOTOR COMPANY 2006 -.0452803 -12613 278554 |
4. | LUCENT TECHNOLOGIES INC. 2002 -.6606149 -11753 17791 |
5. | CORNING INCORPORATED 2001 -.4297663 -5498 12793 |
+---------------------------------------------------------------+
*/
gsort -ni
list firm year roa ni at in 1/5
/* MAX 5 OBS ON NI
+--------------------------------------------------+
| firm year roa ni at |
|--------------------------------------------------|
1. | APPLE INC. 2015 .1838136 53394 290479 |
2. | APPLE INC. 2012 .2370331 41733 176064 |
3. | APPLE INC. 2014 .17042 39510 231839 |
4. | APPLE INC. 2013 .1789227 37037 207000 |
5. | CHEVRON CORP. 2011 .128393 26895 209474 |
+--------------------------------------------------+
*/
compress
save data/mergefile-csrhub-kld-random-sample
*** REPLICATION 3
* Load CSRHub sample data
use data/mergefile-csrhub-kld-random-sample, clear
* ROA regression
est clear
qui reg roa lroa emp debt rd ad
est sto m1
qui reg roa net_kld_adj lroa emp debt rd ad
est sto m2
qui reg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad
est sto m3
qui reg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad i.year
est sto m4
set matsize 800
qui reg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad i.year i.naics_n
est sto m5
qui xtreg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad i.year, fe
est sto m6
estout *, cells(b(star fmt(%9.3f)) z(par)) ///
stats(N N_g r2_a r2_o r2_b r2_w, fmt(%9.0g %9.0g %9.0g %9.4g) ///
labels("N" "Firms" "Adj. R^2" "R^2 Overall" "R^2 Between" "R^2 Within")) ///
legend collabels(none) ///
keep(net_kld_adj net_kld_adj_sq lroa emp debt rd ad _cons) ///
order(net_kld_adj net_kld_adj_sq lroa emp debt rd ad _cons) ///
title("Regressions of ROA using CSRHub population.") ///
starlevels(* .1 ** .05 *** .01)
outreg2 [m1 m2 m3 m4 m5 m6] using "tables-and-figures/barnett-salomon-replicated-figures/rep3-roa-regression", excel ///
stats(coef tstat) ///
keep(net_kld_adj net_kld_adj_sq lroa emp debt rd ad) ///
sortvar(net_kld_adj net_kld_adj_sq lroa emp debt rd ad) ///
dec(2) fmt(f) ///
e(N_g r2_a r2_o r2_b r2_w) ///
replace
* Net income regression
est clear
qui reg ni lni emp debt rd ad
est sto ni1
qui reg ni net_kld_adj lni emp debt rd ad
est sto ni2
qui reg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad
est sto ni3
qui reg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad i.year
est sto ni4
qui reg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad i.year i.naics_n
est sto ni5
qui xtreg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad i.year, fe
est sto ni6
estout *, cells(b(star fmt(%9.3f)) z(par)) ///
stats(N N_g r2_a r2_o r2_b r2_w, fmt(%9.0g %9.0g %9.0g %9.4g) ///
labels("N" "Firms" "Adj. R^2" "R^2 Overall" "R^2 Between" "R^2 Within")) ///
legend collabels(none) ///
keep(net_kld_adj net_kld_adj_sq lni emp debt rd ad _cons) ///
order(net_kld_adj net_kld_adj_sq lni emp debt rd ad _cons) ///
title("Regressions of NET INCOME using CSRHub population.") ///
starlevels(* .1 ** .05 *** .01)
outreg2 [ni1 ni2 ni3 ni4 ni5 ni6] using "tables-and-figures/barnett-salomon-replicated-figures/rep3-ni-regression", excel ///
stats(coef tstat) ///
keep(net_kld_adj net_kld_adj_sq lni emp debt rd ad) ///
sortvar(net_kld_adj net_kld_adj_sq lni emp debt rd ad) ///
dec(2) fmt(f) ///
e(N_g r2_a r2_o r2_b r2_w) ///
replace
***===================================================***
* QUASI-REPLICATION 4 *
* NEW DESIGN, SAME POPULATION, SAME SAMPLE *
***===================================================***
*** LOAD DATA
use data/kld-cstat-bs2012.dta, clear
*** DATA DECISIONS
* Barnett & Salomon assume missing advertising data = 0
keep if in_bs2012==1
replace ad=0 if ad==.
*** CORRELATION TABLE
corr roa lroa ni lni net_kld_adj net_kld_adj_sq emp debt rd ad, means
pwcorr roa lroa ni lni net_kld_adj net_kld_adj_sq emp debt rd ad, st(.05) list
*** 4.1 CLUSTERED STANDARD ERRORS // 4.1
* ROA
est clear
qui reg roa lroa emp debt rd ad, cluster(firm_n)
est sto m1
qui reg roa net_kld_adj lroa emp debt rd ad, cluster(firm_n)
est sto m2
qui reg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad, cluster(firm_n)
est sto m3
qui reg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad i.year, cluster(firm_n)
est sto m4
set matsize 800
qui reg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad i.year i.naics_n, cluster(firm_n)
est sto m5
qui xtreg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad i.year, fe cluster(firm_n)
est sto m6
estout *, cells(b(star fmt(2)) t(par)) ///
stats(N N_g r2_a r2_o r2_b r2_w, fmt(%9.0g %9.0g %9.0g %9.4g) ///
labels("N" "Firms" "Adj. R^2" "R^2 Overall" "R^2 Between" "R^2 Within")) ///
legend collabels(none) ///
keep(net_kld_adj net_kld_adj_sq lroa emp debt rd ad _cons) ///
order(net_kld_adj net_kld_adj_sq lroa emp debt rd ad _cons) ///
starlevels(* .1 ** .05 *** .01)
outreg2 [m1 m2 m3 m4 m5 m6] using "tables-and-figures/barnett-salomon-replicated-figures/rep4-roa-clustered-errors", excel ///
stats(coef tstat) ///
keep(net_kld_adj net_kld_adj_sq lroa emp debt rd ad) ///
sortvar(net_kld_adj net_kld_adj_sq lroa emp debt rd ad) ///
dec(2) fmt(f) ///
e(N_g r2_a r2_o r2_b r2_w) ///
replace
* Net income
est clear
qui reg ni lni emp debt rd ad, cluster(firm_n)
est sto ni1
qui reg ni net_kld_adj lni emp debt rd ad, cluster(firm_n)
est sto ni2
qui reg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad, cluster(firm_n)
est sto ni3
qui reg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad i.year, cluster(firm_n)
est sto ni4
qui reg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad i.year i.naics_n, cluster(firm_n)
est sto ni5
qui xtreg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad i.year, fe cluster(firm_n)
est sto ni6
estout *, cells(b(star fmt(2)) t(par)) ///
stats(N N_g r2_a r2_o r2_b r2_w, fmt(%9.0g %9.0g %9.0g %9.4g) ///
labels("N" "Firms" "Adj. R^2" "R^2 Overall" "R^2 Between" "R^2 Within")) ///
legend collabels(none) ///
keep(net_kld_adj net_kld_adj_sq lni emp debt rd ad _cons) ///
order(net_kld_adj net_kld_adj_sq lni emp debt rd ad _cons) ///
starlevels(* .1 ** .05 *** .01)
outreg2 [ni1 ni2 ni3 ni4 ni5 ni6] using "tables-and-figures/barnett-salomon-replicated-figures/rep4-ni-clustered-errors", excel ///
stats(coef tstat) ///
keep(net_kld_adj net_kld_adj_sq lni emp debt rd ad) ///
sortvar(net_kld_adj net_kld_adj_sq lni emp debt rd ad) ///
dec(2) fmt(f) ///
e(N_g r2_a r2_o r2_b r2_w) ///
replace
*** 4.2 HYBRID FIXED AND RANDOM EFFECTS MODELS // 4.2
* Generate firm means
sort firm_n
foreach v of varlist net_kld_adj net_kld_adj_sq lroa lni emp debt rd ad {
by firm_n: egen m_`v'=mean(`v')
gen dm_`v'=`v'-m_`v'
}
* ROA and NI hybrid regressions
qui xtreg roa dm_net_kld_adj dm_net_kld_adj_sq dm_lroa dm_emp dm_debt dm_rd dm_ad ///
m_net_kld_adj m_net_kld_adj_sq m_lroa m_emp m_debt m_rd m_ad i.year, re
est sto hyb_roa
qui xtreg ni dm_net_kld_adj dm_net_kld_adj_sq dm_lni dm_emp dm_debt dm_rd dm_ad ///
m_net_kld_adj m_net_kld_adj_sq m_lni m_emp m_debt m_rd m_ad i.year, re
est sto hyb_ni
testparm dm_net_kld_adj m_net_kld_adj, equal /// Test coefficient equality
test dm_net_kld_adj_sq = m_net_kld_adj_sq
estout hyb_roa hyb_ni, cells(b(star fmt(3)) z(par)) ///
stats(N N_g r2_a r2_o r2_b r2_w, fmt(%9.0g %9.0g %9.0g %9.4g) ///
labels("N" "Firms" "Adj. R^2" "R^2 Overall" "R^2 Between" "R^2 Within")) ///
legend collabels(none) ///
keep(dm_* m_* _cons) ///
order(dm_net_kld_adj dm_net_kld_adj_sq dm_lroa dm_lni dm_* m_* _cons) ///
starlevels(* .1 ** .05 *** .01)
outreg2 [hyb_roa hyb_ni] using "tables-and-figures/barnett-salomon-replicated-figures/rep4-hybrid-models", excel ///
stats(coef tstat) ///
keep(dm_* m_*) ///
sortvar(dm_net_kld_adj dm_net_kld_adj_sq dm_lroa dm_lni dm_* m_*) ///
dec(2) fmt(f) ///
e(N_g r2_a r2_o r2_b r2_w) ///
replace
*** 4.2 HYBRID FIXED AND RANDOM EFFECTS MODELS WITH CLUSTERED ERRORS // 4.2 continued
* ROA and NI hybrid regressions
qui xtreg roa dm_net_kld_adj dm_net_kld_adj_sq dm_lroa dm_emp dm_debt dm_rd dm_ad ///
m_net_kld_adj m_net_kld_adj_sq m_lroa m_emp m_debt m_rd m_ad i.year, re cluster(firm_n)
est sto hybc_roa
qui xtreg ni dm_net_kld_adj dm_net_kld_adj_sq dm_lni dm_emp dm_debt dm_rd dm_ad ///
m_net_kld_adj m_net_kld_adj_sq m_lni m_emp m_debt m_rd m_ad i.year, re cluster(firm_n)
est sto hybc_ni
estout hybc_roa hybc_ni, cells(b(star fmt(2)) z(par)) ///
stats(N N_g r2_a r2_o r2_b r2_w, fmt(%9.0g %9.0g %9.0g %9.4g) ///
labels("N" "Firms" "Adj. R^2" "R^2 Overall" "R^2 Between" "R^2 Within")) ///
legend collabels(none) ///
keep(dm_* m_* _cons) ///
order(dm_net_kld_adj dm_net_kld_adj_sq dm_lroa dm_lni dm_* m_* _cons) ///
starlevels(* .1 ** .05 *** .01)
outreg2 [hybc_roa hybc_ni] using "tables-and-figures/barnett-salomon-replicated-figures/rep4-hybrid-models-clustered-errors", excel ///
stats(coef tstat) ///
keep(dm_* m_*) ///
sortvar(dm_net_kld_adj dm_net_kld_adj_sq dm_lroa dm_lni dm_* m_*) ///
dec(2) fmt(f) ///
e(N_g r2_a r2_o r2_b r2_w) ///
replace
/*
*** 4.3 CORRELATED RANDOM EFFECTS MODELS WITH AND WITHOUT CLUSTERED ERRORS /// 4.3
* ROA and NI CRE regressions
qui xtreg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad ///
m_net_kld_adj m_net_kld_adj_sq m_lroa m_emp m_debt m_rd m_ad i.year, re
est sto cre_roa
qui xtreg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad ///
m_net_kld_adj m_net_kld_adj_sq m_lni m_emp m_debt m_rd m_ad i.year, re
est sto cre_ni
qui xtreg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad ///
m_net_kld_adj m_net_kld_adj_sq m_lroa m_emp m_debt m_rd m_ad i.year, re cluster(firm_n)
est sto crec_roa
qui xtreg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad ///
m_net_kld_adj m_net_kld_adj_sq m_lni m_emp m_debt m_rd m_ad i.year, re cluster(firm_n)
est sto crec_ni
estout cre_roa crec_roa cre_ni crec_ni, cells(b(star fmt(2)) z(par)) ///
stats(N N_g r2_a r2_o r2_b r2_w, fmt(%9.0g %9.0g %9.0g %9.4g) ///
labels("N" "Firms" "Adj. R^2" "R^2 Overall" "R^2 Between" "R^2 Within")) ///
legend collabels(none) ///
keep(net_kld_adj net_kld_adj_sq lroa lni emp debt rd ad m_* _cons) ///
order(net_kld_adj net_kld_adj_sq lroa lni emp debt rd ad m_* _cons) ///
starlevels(* .1 ** .05 *** .01)
outreg2 [cre_roa crec_roa cre_ni crec_ni] using "tables-and-figures/barnett-salomon-replicated-figures/rep4-cre", excel ///
stats(coef tstat) ///
keep(net_kld_adj net_kld_adj_sq lroa lni emp debt rd ad m_*) ///
sortvar(net_kld_adj net_kld_adj_sq lroa lni emp debt rd ad m_*) ///
dec(2) fmt(f) ///
e(r2_a r2_o r2_b r2_w) ///
replace
*/
* COMPARATIVE TABLES /// 4.4
* ROA, no clustered errors
qui xtreg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad i.year, re
est sto re_roa
qui xtreg roa net_kld_adj net_kld_adj_sq lroa emp debt rd ad i.year, fe
est sto fe_roa
hausman fe_roa re_roa // Clear rejection of coefficient equivalence. RE model differs from FE model.
estout re_roa fe_roa hyb_roa cre_roa, cells(b(star fmt(2)) z(par)) ///
stats(N N_g r2_a r2_o r2_b r2_w, fmt(%9.0g %9.0g %9.0g %9.4g) ///
labels("N" "Firms" "Adj. R^2" "R^2 Overall" "R^2 Between" "R^2 Within")) ///
legend collabels(none) ///
keep(net_kld_adj net_kld_adj_sq lroa emp debt rd ad dm_* m_*) ///
order(net_kld_adj net_kld_adj_sq lroa emp debt rd ad dm_* m_*) ///
starlevels(* .1 ** .05 *** .01)
outreg2 [re_roa fe_roa hyb_roa cre_roa] using "tables-and-figures/barnett-salomon-replicated-figures/rep4-roa-comparative-tables", excel ///
stats(coef tstat) ///
keep(net_kld_adj net_kld_adj_sq lroa emp debt rd ad dm_* m_*) ///
sortvar(net_kld_adj net_kld_adj_sq lroa emp debt rd ad dm_* m_*) ///
dec(2) fmt(f) ///
e(r2_a r2_o r2_b r2_w) ///
replace
* Net Income, no clustered errors
qui xtreg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad i.year, re
est sto re_ni
qui xtreg ni net_kld_adj net_kld_adj_sq lni emp debt rd ad i.year, fe
est sto fe_ni
estout re_ni fe_ni hyb_ni cre_ni, cells(b(star fmt(2)) z(par)) ///
stats(N N_g r2_a r2_o r2_b r2_w, fmt(%9.0g %9.0g %9.0g %9.4g) ///
labels("N" "Firms" "Adj. R^2" "R^2 Overall" "R^2 Between" "R^2 Within")) ///
legend collabels(none) ///
keep(net_kld_adj net_kld_adj_sq lni emp debt rd ad dm_* m_*) ///
order(net_kld_adj net_kld_adj_sq lni emp debt rd ad dm_* m_*) ///
starlevels(* .1 ** .05 *** .01)
outreg2 [re_ni fe_ni hyb_ni cre_ni] using "tables-and-figures/barnett-salomon-replicated-figures/rep4-ni-comparative-tables", excel ///
stats(coef tstat) ///
keep(net_kld_adj net_kld_adj_sq lni emp debt rd ad dm_* m_*) ///
sortvar(net_kld_adj net_kld_adj_sq lni emp debt rd ad dm_* m_*) ///
dec(2) fmt(f) ///
e(r2_a r2_o r2_b r2_w) ///
replace
*** 4.6 Controlling for industry and firm in the same model
* Assume missing industry is the same as industry in next non-missing year
sort firm year
forvalues v = 1/10 {
by firm: replace naics_n=naics_n[_n+1] if naics_n==.
}
forvalues v = 1/10 {
by firm: replace naics_n=naics_n[_n-1] if naics_n==. & _n!=1
}
sort firm year
by firm: gen ind=naics_n!=naics_n[_n-1] & _n!=1
tab ind
/* ind | Freq. Percent Cum.
------------+-----------------------------------
0 | 16,164 99.99 99.99
1 | 2 0.01 100.00
------------+-----------------------------------
Total | 16,166 100.00
*/
by firm: egen ind2=max(ind)
tab ind2
list firm year naics ind ind2 if ind2==1
/* TWO FIRMS CHANGE NAICS IN THE DATA
+---------------------------------------------------+
| firm year naics ind ind2 |
|---------------------------------------------------|
7885. | ITT INDUSTRIES, INC. 1998 334510 0 1 |
7886. | ITT INDUSTRIES, INC. 1999 334510 0 1 |
7887. | ITT INDUSTRIES, INC. 2000 333911 1 1 |
7888. | ITT INDUSTRIES, INC. 2001 333911 0 1 |
7889. | ITT INDUSTRIES, INC. 2002 333911 0 1 |
|---------------------------------------------------|
7890. | ITT INDUSTRIES, INC. 2003 333911 0 1 |
7891. | ITT INDUSTRIES, INC. 2004 333911 0 1 |
7892. | ITT INDUSTRIES, INC. 2005 333911 0 1 |
9012. | MANOR CARE, INC. 1998 531120 0 1 |
9013. | MANOR CARE, INC. 2000 623110 1 1 |
|---------------------------------------------------|
9014. | MANOR CARE, INC. 2001 623110 0 1 |
9015. | MANOR CARE, INC. 2002 623110 0 1 |
9016. | MANOR CARE, INC. 2003 623110 0 1 |
9017. | MANOR CARE, INC. 2004 623110 0 1 |
9018. | MANOR CARE, INC. 2005 623110 0 1 |
|---------------------------------------------------|
9019. | MANOR CARE, INC. 2006 623110 0 1 |
+---------------------------------------------------+
*/
* Generate firm means
sort firm_n
foreach v of varlist net_kld_adj net_kld_adj_sq lroa lni emp debt rd ad naics_n {
by firm_n: egen m_`v'=mean(`v')
gen dm_`v'=`v'-m_`v'
}
* Check industry variable to see if demeaning worked
tab dm_naics_n
/* APPEARS TO WORK
dm_naics_n | Freq. Percent Cum.
------------+-----------------------------------
-91.875 | 1 0.01 0.01
-7.25 | 6 0.06 0.07
0 | 10,064 99.84 99.91
13.125 | 7 0.07 99.98
21.75 | 2 0.02 100.00
------------+-----------------------------------
Total | 10,080 100.00
ONLY TWO FIRMS CHANGE INDUSTRY IN THE PANEL, GIVEN ASSUMPTION THAT MISSING NAICS
IS EQUAL TO THE NEXT YEAR IN WHICH NAICS IS NOT MISSING
*/
drop ind ind2
* ROA and NI hybrid regressions
est clear
qui xtreg roa dm_net_kld_adj dm_net_kld_adj_sq dm_lroa dm_emp dm_debt dm_rd dm_ad dm_naics_n ///
m_net_kld_adj m_net_kld_adj_sq m_lroa m_emp m_debt m_rd m_ad m_naics_n i.year, re
est sto hyb_roa_ind
qui xtreg ni dm_net_kld_adj dm_net_kld_adj_sq dm_lni dm_emp dm_debt dm_rd dm_ad dm_naics_n ///
m_net_kld_adj m_net_kld_adj_sq m_lni m_emp m_debt m_rd m_ad m_naics_n i.year, re
est sto hyb_ni_ind
* ROA and NI hybrid regressions with clustered errors at firm level
qui xtreg roa dm_net_kld_adj dm_net_kld_adj_sq dm_lroa dm_emp dm_debt dm_rd dm_ad dm_naics_n ///
m_net_kld_adj m_net_kld_adj_sq m_lroa m_emp m_debt m_rd m_ad m_naics_n i.year, re cluster(firm_n)
est sto hybc_roa_ind
qui xtreg ni dm_net_kld_adj dm_net_kld_adj_sq dm_lni dm_emp dm_debt dm_rd dm_ad dm_naics_n ///
m_net_kld_adj m_net_kld_adj_sq m_lni m_emp m_debt m_rd m_ad m_naics_n i.year, re cluster(firm_n)
est sto hybc_ni_ind
estout hyb_roa hybc_roa hyb_roa_ind hybc_roa_ind hyb_ni hybc_ni hyb_ni_ind hybc_ni_ind, cells(b(star fmt(3)) z(par)) ///
stats(N N_g r2_a r2_o r2_b r2_w, fmt(%9.0g %9.0g %9.0g %9.4g) ///
labels("N" "Firms" "Adj. R^2" "R^2 Overall" "R^2 Between" "R^2 Within")) ///
legend collabels(none) ///
keep(dm_* m_* _cons) ///
order(dm_net_kld_adj dm_net_kld_adj_sq dm_lroa dm_lni dm_* m_net_kld_adj m_net_kld_adj_sq m_lroa m_lni m_* _cons) ///
starlevels(+ .1 * .05 ** .01 *** .001)
estout hyb_roa hybc_roa hyb_roa_ind hybc_roa_ind hyb_ni hybc_ni hyb_ni_ind hybc_ni_ind, cells(b(star fmt(3)) p(par)) ///
stats(N N_g r2_a r2_o r2_b r2_w, fmt(%9.0g %9.0g %9.0g %9.4g) ///
labels("N" "Firms" "Adj. R^2" "R^2 Overall" "R^2 Between" "R^2 Within")) ///
legend collabels(none) ///
keep(dm_* m_* _cons) ///
order(dm_net_kld_adj dm_net_kld_adj_sq dm_lroa dm_lni dm_* m_net_kld_adj m_net_kld_adj_sq m_lroa m_lni m_* _cons) ///
starlevels(+ .1 * .05 ** .01 *** .001)
outreg2 [hyb_roa hybc_roa hyb_roa_ind hybc_roa_ind hyb_ni hybc_ni hyb_ni_ind hybc_ni_ind] using "tables-and-figures/rep4-all-models-comparison-zstats", excel ///
stats(coef tstat) ///
keep(dm_* m_*) ///
sortvar(dm_net_kld_adj dm_net_kld_adj_sq dm_lroa dm_lni dm_* m_net_kld_adj m_net_kld_adj_sq m_lroa m_lni m_* _cons) ///
dec(2) fmt(f) ///
e(N_g r2_a r2_o r2_b r2_w) ///
replace
outreg2 [hyb_roa hybc_roa hyb_roa_ind hybc_roa_ind hyb_ni hybc_ni hyb_ni_ind hybc_ni_ind] using "tables-and-figures/rep4-all-models-comparison-pvalues", excel ///
stats(coef pval) ///
keep(dm_* m_*) ///
sortvar(dm_net_kld_adj dm_net_kld_adj_sq dm_lroa dm_lni dm_* m_net_kld_adj m_net_kld_adj_sq m_lroa m_lni m_* _cons) ///
dec(3) fmt(f) ///
e(N_g r2_a r2_o r2_b r2_w) ///
alpha(0.001,0.01,0.05,0.1) symbol(***,**,*,+) ///
replace
*/
***===================================================***
* QUASI-REPLICATION 5 *
* NEW DESIGN, SAME POPULATION, NEW SAMPLE *
***===================================================***
/* New sample: 1998 - 2015