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clear
|
|
|
u "${data}Clients_Main.dta"
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|
|
tab follow
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clear
|
|
|
u "${data}Clients_MPL.dta"
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tab follow
|
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clear
|
|
|
u "${data}Clients_Blinding.dta"
|
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|
|
tab follow
|
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u "${data}nochoice.dta", clear
|
|
|
drop if alphavaluefinal==.
|
|
|
tab seeincentivefirst
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|
u "${data}choice_experiments.dta", clear
|
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|
drop if study!=1 & alphavaluefinal==.
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|
|
tab condition if Highx10==0 & Highx100==0
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tab condition if Highx10==1
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tab condition if Highx100==1
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u "${data}Choice_Deterministic.dta", clear
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|
|
drop if alphavaluefinal==.
|
|
|
tab Deterministic
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u "${data}stakes.dta", clear
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drop if alphavaluefinal==.
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|
tab condition
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u "${data}InformationArchitect.dta", clear
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drop if alphavaluefinal==.
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|
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tab IAAdvisor
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di 152+147+712+2574+1562+1067+275+110+385+369+483+511+478+245+253
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clear
|
|
|
u "${data}nochoice.dta"
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drop if alphavaluefinal==.
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prtest recommendincentive if conflict==1, by(seeincentivefirst)
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prtest recommendincentive if conflict==0, by(seeincentivefirst)
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mean recommendincentive if seeincentivefirst==1 & conflict==1
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mean recommendincentive if seeincentivefirst==0 & conflict==1
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reg recommendincentive seeincentivefirst##noconflict female age, vce(hc3)
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estpost summarize recommendincentive
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recommendincentive_before recommendincentive_after if conflict==1,detail
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eststo d_nochoice
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forvalues i=0(1)1{
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estpost summarize recommendincentive
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|
recommendincentive_before recommendincentive_after if incentiveA==`i' & conflict==1,detail
|
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|
eststo d_nochoice`i'
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|
|
}
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tabstat recommendincentive if incentiveB==1 & noconflict==1, stats(mean n)
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gen notrecommendincentive=1-recommendincentive
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tabstat notrecommendincentive if incentiveB==1 & noconflict==1, stats(mean n)
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bys before conflict: egen meanrec=mean(recommendincentive)
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bys before conflict: egen sdrec=sd(recommendincentive)
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bys before conflict: egen nrec=count(recommendincentive)
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g lorec=meanrec-1.96*(sqrt((meanrec*(1-meanrec))/nrec))
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g hirec=meanrec+1.96*(sqrt((meanrec*(1-meanrec))/nrec))
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gen xaxis=0 if before==1 & conflict==1
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replace xaxis=1 if before==0 & conflict==1
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replace xaxis=2.5 if before==1 & conflict==0
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replace xaxis=3.5 if before==0 & conflict==0
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twoway (bar meanrec xaxis if before==1 & conflict==1, color(black) barw(0.7))
|
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|
(bar meanrec xaxis if before==0 & conflict==1, fcolor(white) lcolor(black) barw(0.7) )
|
|
|
(bar meanrec xaxis if before==1 & conflict==0, color(black) barw(0.7))
|
|
|
(bar meanrec xaxis if before==0 & conflict==0, color(white) lcolor(black) barw(0.7))
|
|
|
(rcap lorec hirec xaxis , lcolor(black*0.3) lwidth(medthick))
|
|
|
, xtitle(" ")
|
|
|
ytitle("{bf: Incentivized Product Recommendation}")
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|
|
graphr(c(white)) plotr(c(white))
|
|
|
ylabel(0(0.1)1, gmax)
|
|
|
xlabel(0.5 "{bf: Conflict}" 3 "{bf: No Conflict}" )
|
|
|
xscale(r(-0.5 3.5)) legend(order(1 "See Incentive First" 2 "See Quality First"))
|
|
|
graph export "${main}/nochoice_recommendations.png", replace
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clear
|
|
|
u "${data}nochoice.dta"
|
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|
|
est clear
|
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|
eststo:reg recommendincentive seeincentivefirst noconflict incentiveB female age stdalpha if missingalpha==0 & conflict==1, vce(hc3)
|
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|
eststo:reg recommendincentive seeincentivefirst noconflict incentiveB female age stdalpha if missingalpha==0 & conflict==0, vce(hc3)
|
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|
eststo:reg recommendincentive seeincentivefirst noconflict seeincentivefirst_noconflict incentiveB female age stdalpha if missingalpha==0, vce(hc3)
|
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|
local panel "\begin{table}[h!]" "\centering" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{10}{11}\selectfont" "\caption{Recommendations}" "\begin{tabular}{l*{3}{c}} \hline"
|
|
|
local dv "$\ \ \ \ \ \ \ \ \ \ \ \ \ \ $ &\multicolumn{1}{c}{\textbf{Conflict }} &\multicolumn{1}{c}{\textbf{No Conflict}} & \multicolumn{1}{c}{\textbf{Both}} \\\hline & & & \\"
|
|
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|
|
esttab using "${appendix}NoChoice_Recommendations.tex", se r2 replace nolines cells(b(star fmt(3)) se(par fmt(3)))
|
|
|
coeflabel (seeincentivefirst "See Incentive First" noconflict "No Conflict" seeincentivefirst_noconflict "See Incentive First * No Conflict"
|
|
|
incentiveB "Incentive for B"
|
|
|
female "Female" age "Age" stdalpha "Selfishness" )
|
|
|
order ( seeincentivefirst noconflict seeincentivefirst_noconflict incentiveB female age stdalpha) collabels(none)
|
|
|
drop ( female age)
|
|
|
star( * 0.10 ** 0.05 *** 0.01)
|
|
|
nomtitle label substitute(" 0.000 " " " " (.) " " ")
|
|
|
prehead("`panel'") posthead("`dv'") postfoot("\hline" "\end{tabular}%" "\captionsetup{width=0.7\textwidth}" "\caption*{\footnotesize \textit{Notes:} This table displays the estimated coefficients from linear probability models on the advisors' recommendations. See Incentive first is a binary indicator coded as 1 for participants who were randomly assigned to see the incentive first. Selfishness is a standardized measure of the number of times the advisor chose to recommend the incentivized product in the MPL task aimed at measuring moral costs. The sample includes attentive participants who did not switch multiple times in this elicitation. The regression includes individual controls for the advisor's gender and age. Robust standard errors (HC3) in parentheses}" "\label{tab:nochoicerec}" "\end{table}")
|
|
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|
|
|
|
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|
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|
|
clear
|
|
|
u "${data}nochoice.dta"
|
|
|
|
|
|
|
|
|
|
|
|
est clear
|
|
|
eststo:reg recommendincentive seeincentivefirst noconflict incentiveB female age if conflict==1, vce(hc3)
|
|
|
eststo:reg recommendincentive seeincentivefirst noconflict incentiveB female age if conflict==0, vce(hc3)
|
|
|
eststo:reg recommendincentive seeincentivefirst noconflict seeincentivefirst_noconflict incentiveB female age, vce(hc3)
|
|
|
|
|
|
local panel "\begin{table}[h!]" "\centering" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{10}{11}\selectfont" "\caption{Recommendations including Inattentive}" "\begin{tabular}{l*{3}{c}} \hline"
|
|
|
local dv "$\ \ \ \ \ \ \ \ \ \ \ \ \ \ $ &\multicolumn{1}{c}{\textbf{Conflict }} &\multicolumn{1}{c}{\textbf{No Conflict}} & \multicolumn{1}{c}{\textbf{Both}} \\\hline & & & \\"
|
|
|
|
|
|
esttab using "${appendix}NoChoice_Recommendations_Inattentive.tex", se r2 replace nolines cells(b(star fmt(3)) se(par fmt(3))) collabels(none)
|
|
|
coeflabel (seeincentivefirst "See Incentive First" noconflict "No Conflict" seeincentivefirst_noconflict "See Incentive First * No Conflict"
|
|
|
incentiveB "Incentive for B"
|
|
|
female "Female" age "Age" )
|
|
|
order ( seeincentivefirst noconflict seeincentivefirst_noconflict incentiveB female age)
|
|
|
drop ( female age)
|
|
|
star( * 0.10 ** 0.05 *** 0.01)
|
|
|
nomtitle label substitute(" 0.000 " " " " (.) " " ")
|
|
|
prehead("`panel'") posthead("`dv'") postfoot("\hline" "\end{tabular}%" "\captionsetup{width=0.7\textwidth}" "\caption*{\footnotesize \textit{Notes:} This table displays the estimated coefficients from linear probability models on the advisors' recommendations. See Incentive first is a binary indicator coded as 1 for participants who were randomly assigned to see the incentive first. The sample includes all participants, including those who switched multiple times in the MPL task to measure moral costs. The regression includes individual controls for the advisor's gender and age. Robust standard errors (HC3) in parentheses}" "\label{tab:nochoicerec_inattentive}" "\end{table}")
|
|
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|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
clear
|
|
|
u "${data}choice_experiments.dta"
|
|
|
|
|
|
|
|
|
drop if study!=1 & alphavaluefinal==.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
prtest choicebefore if study==1, by(sample)
|
|
|
|
|
|
reg recommendincentive cloudresearch conflict female age locatedus if study==1
|
|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
reg choicebefore incentiveshigh##incentiveleft if study==4, ro
|
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|
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|
|
|
reg recommendincentive incentiveshigh##incentiveleft if study==4 & conflict==1, ro
|
|
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|
|
|
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|
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|
|
|
|
|
|
|
|
|
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|
|
global covariates "wave2 wave3 professionalscloudresearch incentiveshigh##incentiveleft age female"
|
|
|
global covariates2 "professionalsfree seeincentivecostly seequalitycostly wave2 wave3 professionalscloudresearch incentiveshigh incentiveleft incentiveshigh_incentiveleft age female"
|
|
|
|
|
|
|
|
|
|
|
|
eststo:reg choicebefore i.treatment $covariates if Highx10==0 & Highx100==0, vce(hc3)
|
|
|
margins i.treatment, atmeans saving("${main}Choice_adjusted_demand", replace)
|
|
|
|
|
|
|
|
|
matrix coeffs=r(table)
|
|
|
matrix list coeffs
|
|
|
|
|
|
g preddemand=coeffs[1,1] if treatment==0
|
|
|
g sepreddemand=coeffs[2,1] if treatment==0
|
|
|
forval i=2(1)4{
|
|
|
local j=`i'-1
|
|
|
replace preddemand=coeffs[1,`i'] if treatment==`j'
|
|
|
replace sepreddemand=coeffs[2,`i'] if treatment==`j'
|
|
|
}
|
|
|
g ubpreddemand=preddemand+1.96*sepreddemand
|
|
|
g lbpreddemand=preddemand-1.96*sepreddemand
|
|
|
|
|
|
g xaxis=1 if treatment==1
|
|
|
replace xaxis=3.10 if treatment==2
|
|
|
replace xaxis=2.10 if treatment==0
|
|
|
replace xaxis=4.10 if treatment==3
|
|
|
|
|
|
g meancommit=1
|
|
|
|
|
|
twoway (bar meancommit xaxis,
|
|
|
lcolor(gs10) fcolor(white) barw(0.5) )
|
|
|
(bar preddemand xaxis, color(gs10) barw(0.5) )
|
|
|
(rcap ubpreddemand lbpreddemand xaxis if xaxis!=., color(gs9) lwidth(*0.5))
|
|
|
, xtitle(Study)
|
|
|
ytitle("Advisor preference")
|
|
|
graphr(c(white)) plotr(c(white))
|
|
|
ylabel(0(0.2)1, gmax)
|
|
|
xlabel( 2.10 `" "Choice" "Free" "'
|
|
|
1 `" "Choice Free" "- Professionals" "'
|
|
|
4.10 `" "Quality First" "Costly" "'
|
|
|
3.10 `" "Incentive First" "Costly" "')
|
|
|
xscale(r(0.5 3.5)) legend(lab(1 "Prefer to assess quality first")
|
|
|
lab(2 "Prefer to see incentive first") order(2 1))
|
|
|
xtitle("")
|
|
|
text(0.8 1 "0.55", color(black)) text(0.30 1 "0.45", color(black))
|
|
|
text(0.8 2.10 "0.45") text(0.30 2.10 "0.55")
|
|
|
text(0.8 3.10 "0.59")text(0.30 3.10 "0.41")
|
|
|
text(0.8 4.10 "0.30") text(0.30 4.10 "0.70")
|
|
|
|
|
|
graph export "${main}Choice_Demand_predicted_errorbars.pdf", replace
|
|
|
|
|
|
|
|
|
|
|
|
est clear
|
|
|
eststo:reg choicebefore $covariates2 if Highx10==0 & Highx100==0, vce(hc3)
|
|
|
eststo:reg choicebefore $covariates2 stdalpha if Highx10==0 & Highx100==0 & professionals==0, vce(hc3)
|
|
|
eststo:reg choicebefore $covariates2 stdalpha selfishseeincentivecostly selfishseequalitycostly if Highx10==0 & Highx100==0, vce(hc3)
|
|
|
|
|
|
local panel "\begin{table}[h!]" "\centering" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{10}{11}\selectfont" "\caption{Preference for Information Order}" "\begin{tabular}{l*{3}{c}} \hline"
|
|
|
local dv "$\ \ \ \ \ \ \ \ \ \ \ \ \ \ $ &\multicolumn{3}{c}{\textbf{Prefer to See Incentive First}} \\\hline & & & \\"
|
|
|
|
|
|
esttab using "${main}Choice_Demand.tex",
|
|
|
se r2 replace nolines cells(b(star fmt(3)) se(par fmt(3)))
|
|
|
coeflabel (professionalsfree "Choice Free -- Professionals $ \ \ \ \ \ \ \ $" seeincentivecostly "See Incentive First Costly " seequalitycostly "Assess Quality First Costly" wave2 "Wave 2" wave3 "Wave 3"
|
|
|
female "Female" age "Age" stdalpha "Selfishness" professionalscloudresearch "Professionals x Cloudresearch" selfishseeincentivecostly "See Incentive First Costly X Selfishness " selfishseequalitycostly "See Quality First Costly X Selfishness "
|
|
|
incentiveshigh "Probabilistic Incentive Mturk" incentiveleft "Order" incentiveshigh_incentiveleft "Probabilistic Incentive X Order")
|
|
|
order (seeincentivecostly seequalitycostly professionalsfree stdalpha selfishseeincentivecostly selfishseequalitycostly female age wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch )
|
|
|
star(* 0.10 ** 0.05 *** 0.01) collabels(none)
|
|
|
drop(wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch)
|
|
|
nomtitle label substitute(" 0.000 " " " " (.) " " ")
|
|
|
prehead("`panel'") posthead("`dv'") postfoot("\hline" "\end{tabular}%" "\captionsetup{width=0.8\textwidth}" "\caption*{\footnotesize \textit{Notes:} This table displays the estimated coefficients from linear probability models on the preference to see the incentive first. See Incentive First Costly and Assess Quality First Costly are indicator variables that take value 1 in the respective treatment, 0 otherwise. Selfishness was elicited at the end of the experiment, using a multiple price list (MPL) with 5 decisions. The variable is a standardized measure of the number of times the advisor chose to recommend the incentivized product in the MPL task. The regression models in columns (2) and (3) include individual controls for the advisor's gender and age, each wave of the experiment, whether incentives were probabilistic, the position of the products on the screen and the interaction between these two variables. Robust standard errors (HC3) in parentheses. * p$<$.10; ** p$<$.05; *** p$<$.01}" "\label{tab:demand}" "\end{table}")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
tabstat avoid_incentiveinfo if wave3==1 & Highx10==0 & Highx100==0 & age!=. & female!=., by(choiceafter)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
prtest avoid_incentiveinfo if wave3==1 & Highx10==0 & Highx100==0 & age!=. & female!=., by(choiceafter)
|
|
|
|
|
|
|
|
|
|
|
|
bys choicebefore: egen blind=mean(avoid_incentiveinfo) if Highx10==0 & Highx100==0 & age!=. & female!=. & wave3==1
|
|
|
bys choicebefore: egen blindsd=sd(avoid_incentiveinfo) if Highx10==0 & Highx100==0 & age!=. & female!=. & wave3==1
|
|
|
bys choicebefore: egen blindn=count(avoid_incentiveinfo) if Highx10==0 & Highx100==0 & age!=. & female!=. & wave3==1
|
|
|
|
|
|
summ avoid_incentiveinfo if Highx10==0 & Highx100==0, d
|
|
|
return list
|
|
|
|
|
|
g loblind=blind-1.96*(blindsd/sqrt(blindn))
|
|
|
g hiblind=blind+1.96*(blindsd/sqrt(blindn))
|
|
|
|
|
|
|
|
|
tab blind
|
|
|
|
|
|
twoway (bar meancommit choiceafter, lcolor(black) fcolor(white) barwidth(0.3))
|
|
|
(bar blind choiceafter, color(gs8) barwidth(0.3))
|
|
|
(rcap loblind hiblind choiceafter, color(gs12))
|
|
|
, graphr(c(white)) xlabel(0 "Prefer to See Incentive First" 1 "Prefer to Assess Quality First")
|
|
|
xscale(r(-0.4 1.4)) legend(order(1 "Prefer Not to Blind Incentive Information"
|
|
|
2 "Prefer Blinding Incentive Information") rows(2)) ylabel(0(0.2)1)
|
|
|
ytitle("Advisor Preference to Blind" " ")
|
|
|
xtitle(" " "Advisor Preference in Choice Experiment")
|
|
|
text(0.2 0 "0.32") text(0.2 1 "0.55")
|
|
|
text(0.8 0 "0.68") text(0.8 1 "0.45")
|
|
|
graph export "${main}Choice_Blinding.png", replace
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
reg avoid_incentive choicebefore notgetyourchoice choicebeforenotgetyourchoice $covariates2 noconflict if Highx10==0 & Highx100==0, vce(hc3)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
u "${data}Choice_coding_explanations.dta", clear
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
tab study
|
|
|
|
|
|
|
|
|
|
|
|
tabstat nocategory if choicebefore!=., s(mean n)
|
|
|
|
|
|
|
|
|
kap mergedcategory1 mergedcategory2
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
tab nomatter if choicebefore!=.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
tabstat limitbias if nocategory==0 & condition!="ChoiceFree_Professionals", by(choicebefore)
|
|
|
tabstat limitbias if nocategory==0 & condition=="ChoiceFree_Professionals", by(choicebefore)
|
|
|
tab limitbias choicebefore, chi2
|
|
|
|
|
|
|
|
|
tabstat commission_expl if nocategory==0 & condition=="ChoiceFree_Professionals", by(choicebefore)
|
|
|
tabstat commission_expl if nocategory==0 & condition!="ChoiceFree_Professionals", by(choicebefore)
|
|
|
|
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preserve
|
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collapse limitbias nomatter commission_expl otherreason
|
|
|
(count) nlimitbias=limitbias if nocategory==0, by(choicebefore)
|
|
|
egen sumn=total(nlimitbias)
|
|
|
drop nlimitbias
|
|
|
save "${appendix}taba.dta", replace
|
|
|
restore
|
|
|
preserve
|
|
|
collapse limitbias nomatter commission_expl otherreason
|
|
|
(count) nlimitbias=limitbias if nocategory==0 & condition!="ChoiceFree_Professionals", by(choicebefore)
|
|
|
egen sumn=total(nlimitbias)
|
|
|
drop nlimitbias
|
|
|
save "${appendix}tabb.dta", replace
|
|
|
restore
|
|
|
preserve
|
|
|
collapse limitbias nomatter commission_expl otherreason
|
|
|
(count) nlimitbias=limitbias if nocategory==0 & condition=="ChoiceFree_Professionals", by(choicebefore)
|
|
|
egen sumn=total(nlimitbias)
|
|
|
drop nlimitbias
|
|
|
save "${appendix}tabc.dta", replace
|
|
|
restore
|
|
|
|
|
|
preserve
|
|
|
clear
|
|
|
u "${appendix}taba.dta"
|
|
|
append using "${appendix}tabb.dta"
|
|
|
append using "${appendix}tabc.dta"
|
|
|
export excel "${appendix}tablec15.xlsx", replace first(var) keepcellfmt
|
|
|
rm "${appendix}taba.dta"
|
|
|
rm "${appendix}tabb.dta"
|
|
|
rm "${appendix}tabc.dta"
|
|
|
restore
|
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|
u "${data}choice_experiments.dta", clear
|
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|
drop if study!=1 & alphavaluefinal==.
|
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|
gen incentiveBgetbefore=incentiveB*getbefore
|
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cap drop predrecommend_* ubpredrecommend_* lbpredrecommend_* sepredrecommend_*
|
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|
g predrecommend_dqf_gqf=.
|
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|
g sepredrecommend_dqf_gqf=.
|
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|
g predrecommend_dqf_gif=.
|
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|
g sepredrecommend_dqf_gif=.
|
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|
g predrecommend_dif_gqf=.
|
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|
g sepredrecommend_dif_gqf=.
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|
g predrecommend_dif_gif=.
|
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|
g sepredrecommend_dif_gif=.
|
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|
est clear
|
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|
eststo:reg recommendincentive i.treatment##i.getbefore incentiveB $covariates2
|
|
|
if choicebefore==1
|
|
|
& conflict==1 & Highx10==0 & Highx100==0, vce(hc3)
|
|
|
forval i=0(1)3{
|
|
|
margins i.getbefore if treatment==`i', atmeans saving("${main}adjusted_recommendations", replace)
|
|
|
matrix coeffs=r(table)
|
|
|
replace predrecommend_dif_gqf=coeffs[1,1] if treatment==`i' & choicebefore==1 & getbefore==0
|
|
|
replace sepredrecommend_dif_gqf=coeffs[2,1] if treatment==`i' & choicebefore==1 & getbefore==0
|
|
|
replace predrecommend_dif_gif=coeffs[1,2] if treatment==`i' & choicebefore==1 & getbefore==1
|
|
|
replace sepredrecommend_dif_gif=coeffs[2,2] if treatment==`i' & choicebefore==1 & getbefore==1
|
|
|
}
|
|
|
g ubpredrecommend_dif_gif=predrecommend_dif_gif+1.96*sepredrecommend_dif_gif
|
|
|
g lbpredrecommend_dif_gif=predrecommend_dif_gif-1.96*sepredrecommend_dif_gif
|
|
|
g ubpredrecommend_dif_gqf=predrecommend_dif_gqf+1.96*sepredrecommend_dif_gqf
|
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|
g lbpredrecommend_dif_gqf=predrecommend_dif_gqf-1.96*sepredrecommend_dif_gqf
|
|
|
|
|
|
|
|
|
|
|
|
est clear
|
|
|
eststo:reg recommendincentive i.treatment##i.getbefore incentiveB $covariates2
|
|
|
if choicebefore==0
|
|
|
& conflict==1 & Highx10==0 & Highx100==0, vce(hc3)
|
|
|
forval i=0(1)3{
|
|
|
margins i.getbefore if treatment==`i', atmeans saving("${main}adjusted_recommendations", replace)
|
|
|
matrix coeffs=r(table)
|
|
|
replace predrecommend_dqf_gqf=coeffs[1,1] if treatment==`i' & choicebefore==0 & getbefore==0
|
|
|
replace sepredrecommend_dqf_gqf=coeffs[2,1] if treatment==`i' & choicebefore==0 & getbefore==0
|
|
|
replace predrecommend_dqf_gif=coeffs[1,2] if treatment==`i' & choicebefore==0 & getbefore==1
|
|
|
replace sepredrecommend_dqf_gif=coeffs[2,2] if treatment==`i' & choicebefore==0 & getbefore==1
|
|
|
}
|
|
|
g ubpredrecommend_dqf_gif=predrecommend_dqf_gif+1.96*sepredrecommend_dqf_gif
|
|
|
g lbpredrecommend_dqf_gif=predrecommend_dqf_gif-1.96*sepredrecommend_dqf_gif
|
|
|
g ubpredrecommend_dqf_gqf=predrecommend_dqf_gqf+1.96*sepredrecommend_dqf_gqf
|
|
|
g lbpredrecommend_dqf_gqf=predrecommend_dqf_gqf-1.96*sepredrecommend_dqf_gqf
|
|
|
|
|
|
|
|
|
cap drop treatnumgraph2
|
|
|
g treatnumgraph2=2 if choicebefore==1 & getbefore==1 & condition=="ChoiceFree" & professionals==0
|
|
|
replace treatnumgraph2=2.1 if choicebefore==1 & getbefore==0 & condition=="ChoiceFree" & professionals==0
|
|
|
replace treatnumgraph2=2.2 if choicebefore==0 & getbefore==1 & condition=="ChoiceFree" & professionals==0
|
|
|
replace treatnumgraph2=2.3 if choicebefore==0 & getbefore==0 & condition=="ChoiceFree" & professionals==0
|
|
|
|
|
|
|
|
|
replace treatnumgraph2=1 if choicebefore==1 & getbefore==1 & condition=="ChoiceFree_Professionals"
|
|
|
replace treatnumgraph2=1.1 if choicebefore==1 & getbefore==0 & condition=="ChoiceFree_Professionals"
|
|
|
replace treatnumgraph2=1.2 if choicebefore==0 & getbefore==1 & condition=="ChoiceFree_Professionals"
|
|
|
replace treatnumgraph2=1.3 if choicebefore==0 & getbefore==0 & condition=="ChoiceFree_Professionals"
|
|
|
|
|
|
replace treatnumgraph2=4 if choicebefore==1 & getbefore==1 & condition=="PayAfter"
|
|
|
replace treatnumgraph2=4.1 if choicebefore==1 & getbefore==0 & condition=="PayAfter"
|
|
|
replace treatnumgraph2=4.2 if choicebefore==0 & getbefore==1 & condition=="PayAfter"
|
|
|
replace treatnumgraph2=4.3 if choicebefore==0 & getbefore==0 & condition=="PayAfter"
|
|
|
|
|
|
replace treatnumgraph2=3 if choicebefore==1 & getbefore==1 & condition=="PayBefore"
|
|
|
replace treatnumgraph2=3.1 if choicebefore==1 & getbefore==0 & condition=="PayBefore"
|
|
|
replace treatnumgraph2=3.2 if choicebefore==0 & getbefore==1 & condition=="PayBefore"
|
|
|
replace treatnumgraph2=3.3 if choicebefore==0 & getbefore==0 & condition=="PayBefore"
|
|
|
|
|
|
|
|
|
|
|
|
twoway (scatteri 1 0.7 1 1.7, bcolor(gs15) recast(area))
|
|
|
(scatteri 1 2.7 1 3.7, bcolor(gs15) recast(area))
|
|
|
(rcap lbpredrecommend_dif_gif ubpredrecommend_dif_gif treatnumgraph2, lcolor(red) lwidth(thin))
|
|
|
(rcap lbpredrecommend_dqf_gqf ubpredrecommend_dqf_gqf treatnumgraph2, lcolor(black) lwidth(thin))
|
|
|
(rcap lbpredrecommend_dif_gqf ubpredrecommend_dif_gqf treatnumgraph2, lcolor(red*0.3) lwidth(thin))
|
|
|
(rcap lbpredrecommend_dqf_gif ubpredrecommend_dqf_gif treatnumgraph2, lcolor(black*0.3) lwidth(thin))
|
|
|
(scatter predrecommend_dif_gif treatnumgraph2 if
|
|
|
condition=="ChoiceFree_Professionals" & professionals==1 , mcolor(red) msize(*0.75) ms(T))
|
|
|
(scatter predrecommend_dif_gqf treatnumgraph2 if
|
|
|
condition=="ChoiceFree_Professionals" & professionals==1 & choicebefore==1 & getbefore==0, mfcolor(white) msize(*0.8) mlcolor(red%50) ms(S))
|
|
|
(scatter predrecommend_dqf_gif treatnumgraph2 if
|
|
|
condition=="ChoiceFree_Professionals" & professionals==1 & choicebefore==0 & getbefore==1, mfcolor(white) mlcolor(black%50) msize(*0.8) ms(T))
|
|
|
(scatter predrecommend_dqf_gqf treatnumgraph2 if
|
|
|
condition=="ChoiceFree_Professionals" & professionals==1 & choicebefore==0 & getbefore==0, mcolor(black) msize(*0.8) ms(S))
|
|
|
(scatter predrecommend_dif_gif treatnumgraph2 if
|
|
|
condition=="ChoiceFree" , mcolor(red) msize(*0.75) ms(T))
|
|
|
(scatter predrecommend_dif_gqf treatnumgraph2 if
|
|
|
condition=="ChoiceFree" , mfcolor(white) msize(*0.8) mlcolor(red%50) ms(T))
|
|
|
(scatter predrecommend_dqf_gif treatnumgraph2 if
|
|
|
condition=="ChoiceFree", mfcolor(white) mlcolor(black*0.3) msize(*0.8) ms(S))
|
|
|
(scatter predrecommend_dqf_gqf treatnumgraph2 if
|
|
|
condition=="ChoiceFree", msize(*0.8) mcolor(black) ms(S))
|
|
|
(scatter predrecommend_dif_gif treatnumgraph2 if condition=="PayAfter", mcolor(red) msize(*0.75) ms(T))
|
|
|
(scatter predrecommend_dif_gqf treatnumgraph2 if condition=="PayAfter", mfcolor(white) msize(*0.8) mlcolor(red%50) ms(T))
|
|
|
(scatter predrecommend_dqf_gif treatnumgraph2 if condition=="PayAfter", mfcolor(white) mlcolor(black%50) msize(*0.8) ms(S))
|
|
|
(scatter predrecommend_dqf_gqf treatnumgraph2 if condition=="PayAfter", mcolor(black) msize(*0.8) ms(S))
|
|
|
(scatter predrecommend_dif_gif treatnumgraph2 if condition=="PayBefore", mcolor(red) msize(*0.75) ms(T))
|
|
|
(scatter predrecommend_dif_gqf treatnumgraph2 if condition=="PayBefore", mfcolor(white) msize(*0.8) mlcolor(red%50) ms(T))
|
|
|
(scatter predrecommend_dqf_gif treatnumgraph2 if condition=="PayBefore", mfcolor(white) mlcolor(black%50) msize(*0.8) ms(S))
|
|
|
(scatter predrecommend_dqf_gqf treatnumgraph2 if condition=="PayBefore", msize(*0.8) mcolor(black) ms(S))
|
|
|
, graphr(c(white)) plotr(c(white))
|
|
|
ylabel(0.3(0.1)1) yscale(r(0.3 1))
|
|
|
xtitle(" ")
|
|
|
xlabel(none)
|
|
|
xscale(r(0.7 4.6))
|
|
|
legend(order( - "{bf:Advisor Prefers to}" "{bf:See Incentive First}"
|
|
|
7 8 - "{bf:Advisor Prefers to}" "{bf:Assess Quality First}" 9 10)
|
|
|
lab(7 " Assigned to See Incentive First")
|
|
|
lab(8 " Assigned to Assess Quality First")
|
|
|
lab(10 " Assigned to Assess Quality First")
|
|
|
lab(9 " Assigned to See Incentive First")
|
|
|
rows(3) colfirst size(*0.7))
|
|
|
text(0.38 1.15 "{bf: Choice Free}", color(black) size(*0.8))
|
|
|
text(0.35 1.15 "{bf: - Professionals}", color(black) size(*0.8))
|
|
|
text(0.38 2.15 "{bf: Choice}", color(black) size(*0.8))
|
|
|
text(0.35 2.15 "{bf: Free }", color(black) size(*0.8))
|
|
|
text(0.38 4.15 "{bf: Quality First}", color(black) size(*0.8))
|
|
|
text(0.35 4.15 "{bf: Costly}", color(black) size(*0.8))
|
|
|
text(0.38 3.15 "{bf: Incentive First}", color(black) size(*0.8))
|
|
|
text(0.35 3.15 "{bf: Costly}", color(black) size(*0.8))
|
|
|
ytitle("{bf:Incentivized product recommendation}" " " )
|
|
|
|
|
|
graph export "${main}Choice_recommendations_conflict_pred.pdf", replace
|
|
|
|
|
|
|
|
|
ttest recommendincentive if getyourchoice==1 & Highx10==0 & Highx100==0 & age!=. & treatment==0, by(choicebefore)
|
|
|
ttest recommendincentive if getyourchoice==1 & Highx10==0 & Highx100==0 & age!=. & treatment==1, by(choicebefore)
|
|
|
ttest recommendincentive if getyourchoice==1 & Highx10==0 & Highx100==0 & age!=. & treatment==2, by(choicebefore)
|
|
|
ttest recommendincentive if getyourchoice==1 & Highx10==0 & Highx100==0 & age!=. & treatment==3, by(choicebefore)
|
|
|
|
|
|
|
|
|
|
|
|
tabstat recommendincentive if choicebefore==1 & conflict==1 & wave=="AMT-1" & condition=="PayBefore" & alphavaluefinal!=., by(getbefore) stats(mean sd)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
est clear
|
|
|
eststo: reg recommendincentive choicebefore choicebeforenoconflict
|
|
|
noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==1, vce(hc3)
|
|
|
test choicebefore+choicebeforenoconflict==0
|
|
|
|
|
|
|
|
|
eststo: reg recommendincentive choicebefore choicebeforenoconflict
|
|
|
noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==0, vce(hc3)
|
|
|
|
|
|
|
|
|
eststo: reg recommendincentive choicebefore choicebeforenoconflict
|
|
|
noconflict notgetyourchoice choicebeforenotgetyourchoice notgetyourchoicenoconflict incentiveB $covariates2
|
|
|
if Highx10==0 & Highx100==0, vce(hc3)
|
|
|
test choicebefore+choicebeforenoconflict==0
|
|
|
test choicebefore+notgetyourchoice+choicebeforenotgetyourchoice==0
|
|
|
test notgetyourchoice+choicebeforenotgetyourchoice==0
|
|
|
|
|
|
lincom notgetyourchoice+choicebeforenotgetyourchoice
|
|
|
|
|
|
|
|
|
local panel "\begin{table}[h!]" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{10}{10}\selectfont" "\caption{Advisor Recommendations}" "\hspace{-1cm}" "\begin{tabular}{l*{3}{c}} \hline"
|
|
|
local dv "&\multicolumn{3}{c}{\textbf{Recommend incentivized product}} \\"
|
|
|
local groups "\multicolumn{1}{r}{\textit{Assignment:}}&\multicolumn{1}{c}{Assigned Pref.}&\multicolumn{1}{c}{Not Assigned Pref.}&\multicolumn{1}{c}{Both} \\\hline & & & \\ "
|
|
|
local conflict "&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict}&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict}&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict} \\ \hline & & & & & & \\"
|
|
|
|
|
|
esttab using "${main}recommendations_pref_assign.tex", se r2 replace cells(b(star fmt(3)) se(par fmt(3)))
|
|
|
coeflabel (noconflict "No Conflict" getbefore "Assigned to See Incentive First" getbeforenoconflict "Assigned to See Incentive First X No Conflict" professionalsfree "Choice Free--Professionals" seeincentivecostly "See Incentive First Costly" seequalitycostly "Assess Quality First Costly" wave2 "Wave 2" wave3 "Wave 3" notgetyourchoice "Not Assigned Preference"
|
|
|
female "Female" age "Age" selfish "Selfish" professionalscloudresearch "Professionals x Cloudresearch" selfishseeincentivecostly "Selfish X See Incentive First Costly" selfishseequalitycostly "Selfish X See Quality First Costly"
|
|
|
incentiveshigh "Probabilistic Incentive Mturk" incentiveleft "Order" incentiveshigh_incentiveleft "Probabilistic Incentive X Order"
|
|
|
incentiveB "Incentive for B" choicebefore "Prefer to See Incentive First"
|
|
|
choicebeforenoconflict "No Conflict X Prefer to See Incentive First"
|
|
|
choicebeforenotgetyourchoice "Prefer to See Incentive First X Not Assigned Preference"
|
|
|
notgetyourchoicenoconflict "No Conflict X Not Assigned Preference")
|
|
|
order (choicebefore notgetyourchoice choicebeforenotgetyourchoice noconflict choicebeforenoconflict notgetyourchoicenoconflict professionalsfree seeincentivecostly seequalitycostly incentiveB selfish female age wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch )
|
|
|
star(* 0.10 ** 0.05 *** 0.01) title("Advisor Recommendations")
|
|
|
drop(selfish wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch)
|
|
|
mlabels(none) label collabels(none) substitute(" 0.00 " " " " (.) " " ")
|
|
|
posthead("`dv'" "`groups'") prehead("`panel'") nolines postfoot("\hline" "\end{tabular}%" "\captionsetup{width=1.15\textwidth}" "\caption*{\footnotesize Note: This table displays the estimated coefficients from linear probability models on the advisor's decision to recommend the incentivized option. Column (1) focuses on individuals who are assigned their preference, while column (2) focuses on individuals who are not assigned their preference. Both groups are merged in column (3). Prefer to See Incentive First is an indicator of the advisor's preference, and Not Assigned Preference is an indicator for not receiving the preferred order. No Conflict is an indicator for the cases in which the signal of quality is not in conflict with the advisor's commission. See Incentive First Costly and Assess Quality First Costly are indicator variables that take value 1 in the respective treatment, 0 otherwise. All regression models include individual controls for the advisor's gender and age, each wave of the experiment, whether incentives were probabilistic, the position of the products on the screen and the interaction between these two variables. The same analysis including a measure of advisor's selfishness are shown in Online Appendix C. Robust standard errors (HC3) in parentheses. * p$<$.10; ** p$<$.05; *** p$<$.01}" "\label{tab:recommendations}" "\end{table}")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
reg recommendincentive i.getbefore incentiveB incentiveBgetbefore
|
|
|
$covariates2 if choicebefore==1 & conflict==1 & Highx10==0 & Highx100==0, vce(hc3)
|
|
|
|
|
|
|
|
|
|
|
|
reg recommendincentive choicebefore choicebeforenoconflict
|
|
|
noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==1 & treatment==0, vce(hc3)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
preserve
|
|
|
keep if treatment==0
|
|
|
gen seeincentivefirst=getbefore
|
|
|
append using "${data}nochoice.dta"
|
|
|
gen nochoice=0
|
|
|
replace nochoice=1 if choice=="No Choice"
|
|
|
replace nochoice=1 if seeincentivefirst==.
|
|
|
replace seeincentivefirst=0 if condition=="AfterA" | condition=="AfterB"
|
|
|
replace seeincentivefirst=1 if condition=="BeforeA" | condition=="BeforeB"
|
|
|
replace getbefore=1 if nochoice==1 & seeincentivefirst==1
|
|
|
replace incentiveshigh=0 if nochoice==1
|
|
|
replace incentiveleft=0 if nochoice==1
|
|
|
drop if Highx10==1
|
|
|
drop if Highx100==1
|
|
|
replace noconflict=1-conflict if nochoice==1
|
|
|
replace wave1=0 if nochoice==1
|
|
|
replace wave2=0 if nochoice==1
|
|
|
replace wave3=0 if nochoice==1
|
|
|
gen choice1=1-nochoice
|
|
|
replace seeincentivefirst_noconflict=seeincentivefirst*noconflict
|
|
|
gen seeincentivefirst_nochoice=seeincentivefirst*nochoice
|
|
|
gen seeincentivefirst_nochoiceNocon=seeincentivefirst*nochoice*noconflict
|
|
|
gen nochoice_noconflict=nochoice*noconflict
|
|
|
replace incentiveshigh_incentive=0 if nochoice==1
|
|
|
drop if alphavaluefinal==.
|
|
|
|
|
|
|
|
|
est clear
|
|
|
eststo: reg recommendincentive seeincentivefirst noconflict seeincentivefirst_noconflict incentiveB wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentive age female if choice=="No Choice"
|
|
|
eststo: reg recommendincentive seeincentivefirst noconflict seeincentivefirst_noconflict incentiveB wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentive age female if (getyourchoice==1 ) & choice=="Choice"
|
|
|
eststo: reg recommendincentive seeincentivefirst nochoice seeincentivefirst_nochoice noconflict seeincentivefirst_noconflict nochoice_noconflict seeincentivefirst_nochoiceNocon incentiveB wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentive age female if ((choice=="Choice" & getyourchoice==1) | choice=="No Choice")
|
|
|
|
|
|
|
|
|
|
|
|
local panel "\begin{table}[h!]" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{10}{10}\selectfont" "\caption{Advisor Recommendations}" "\begin{tabular}{l*{3}{c}} \hline"
|
|
|
local dv "&\multicolumn{3}{c}{\textbf{Recommend incentivized product}} \\"
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local groups "\multicolumn{1}{r}{\textit{Sample:}}&\multicolumn{1}{c}{NoChoice.}&\multicolumn{1}{c}{Choice}&\multicolumn{1}{c}{Both} \\\hline & & & \\ "
|
|
|
local conflict "\multicolumn{1}{r}{\textit{Assignment:}}&\multicolumn{1}{c}{Randomly Assigned}&\multicolumn{1}{c}{Prefer and Assigned}&\multicolumn{1}{c}{Both} \\\hline & & & \\ "
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esttab using "${appendix}choice_nochoice.tex", se r2 replace cells(b(star fmt(4)) se(par fmt(4)))
|
|
|
coeflabel (seeincentivefirst "See Incentive First" noconflict "No Conflict" seeincentivefirst_noconflict "See Incentive First X No Conflict"
|
|
|
nochoice "No Choice" seeincentivefirst_nochoice "See IncentiveFirst X NoChoice" nochoice_noconflict "No Choice X No Conflict" seeincentivefirst_nochoiceNocon "See Incentive First X No Choice X No Conflict"
|
|
|
wave2 "Wave 2" wave3 "Wave 3"
|
|
|
incentiveB "Incentive for B" choicebefore "Prefer to See Incentive First" )
|
|
|
star(* 0.10 ** 0.05 *** 0.01) title("Advisor Recommendations")
|
|
|
order(seeincentivefirst nochoice seeincentivefirst_nochoice noconflict nochoice_noconflict seeincentivefirst_noconflict seeincentivefirst_nochoiceNocon incentiveB)
|
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|
drop( wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft female age)
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mlabels(none) label collabels(none) substitute(" 0.000 " " " " (.) " " ")
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|
posthead("`dv'" "`groups'") prehead("`panel'") nolines postfoot("\hline" "\end{tabular}%" "\captionsetup{width=\textwidth}" "\caption*{\footnotesize Note: This table displays the estimated coefficients from linear probability models on the advisor's decision to recommend the incentivized option. Column (1) focuses on the NoChoice Experiment, while column (2) focuses on the Choice Experiment (ChoiceFree Treatment only) and on individuals who are assigned their preference. Both groups are merged in column (3). See Incentive First is an indicator for whether advisors are randomly assigned to see the incentive first in NoChoice, and whether, conditional on preferring to see the incentive first, they are assigned to see the incentive first in Choice. No Conflict is an indicator for the cases in which the signal of quality is not in conflict with the advisor's commission. All regression models include individual controls for the advisor's gender and age, each wave of the experiment, whether incentives were probabilistic, the position of the products on the screen and the interaction between these two variables. Robust standard errors (HC3) in parentheses. * p$<$.10; ** p$<$.05; *** p$<$.01}" "\label{tab:recommendations}" "\end{table}")
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restore
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reg recommendincentive i.getbefore incentiveB incentiveBgetbefore
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$covariates2 if choicebefore==0 & conflict==1 & Highx10==0 & Highx100==0, vce(hc3)
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cap program drop appendmodels
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program appendmodels, eclass
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syntax namelist
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tempname b V tmp
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foreach name of local namelist {
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qui est restore `name'
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mat `tmp' = e(b)
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local eq1: coleq `tmp'
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|
gettoken eq1 : eq1
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mat `tmp' = `tmp'[1,"`eq1':"]
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|
local cons = colnumb(`tmp',"_cons")
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if `cons'<. & `cons'>1 {
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mat `tmp' = `tmp'[1,1..`cons'-1]
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|
}
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|
mat `b' = nullmat(`b') , `tmp'
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|
mat `tmp' = e(V)
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|
mat `tmp' = `tmp'["`eq1':","`eq1':"]
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|
if `cons'<. & `cons'>1 {
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|
mat `tmp' = `tmp'[1..`cons'-1,1..`cons'-1]
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|
|
}
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capt confirm matrix `V'
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|
if _rc {
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|
mat `V' = `tmp'
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|
|
}
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|
else {
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|
|
mat `V' =
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|
( `V' , J(rowsof(`V'),colsof(`tmp'),0) ) \
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|
|
( J(rowsof(`tmp'),colsof(`V'),0) , `tmp' )
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}
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}
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local names: colfullnames `b'
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mat coln `V' = `names'
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|
mat rown `V' = `names'
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|
|
eret post `b' `V'
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eret local cmd "whatever"
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end
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est clear
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eststo belief_all0: reg logitbelief bad good
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if Highx10==0 & Highx100==0 & getyourchoice==1, vce(hc3) nocons
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test good=bad
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eststo belief_0: reg logitbelief bad good
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if Highx10==0 & Highx100==0 & getyourchoice==1 & choicebefore==0, vce(hc3) nocons
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test good=bad
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eststo belief_1: reg logitbelief bad good
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|
if Highx10==0 & Highx100==0 & getyourchoice==1 & choicebefore==1, vce(hc3) nocons
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test good=bad
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eststo bivar: appendmodels belief_all0 belief_1 belief_0
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reg logitbelief good bad goodchoicebefore badchoicebefore
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if Highx10==0 & Highx100==0 & getyourchoice==1, vce(hc3) nocons
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test goodchoicebefore==0
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estadd scalar test_good_ifirst=r(p): bivar
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test badchoicebefore==0
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estadd scalar test_bad_ifirst=r(p): bivar
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summ logitbelief if Highx10==0 & Highx100==0 & getyourchoice==1
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estadd scalar obs=r(N): bivar
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eststo belief_all1: reg logitbelief bad good
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|
|
if Highx10==0 & Highx100==0 & getyourchoice==0, vce(hc3) nocons
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|
eststo belief_2: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & choicebefore==0, vce(hc3) nocons
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|
eststo belief_3: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & choicebefore==1, vce(hc3) nocons
|
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eststo bivar2: appendmodels belief_all1 belief_3 belief_2
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reg logitbelief good bad goodchoicebefore badchoicebefore
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|
|
if Highx10==0 & Highx100==0 & getyourchoice==0, vce(hc3) nocons
|
|
|
|
|
|
test goodchoicebefore==0
|
|
|
estadd scalar test_good_ifirst=r(p): bivar2
|
|
|
test badchoicebefore==0
|
|
|
estadd scalar test_bad_ifirst=r(p): bivar2
|
|
|
summ logitbelief if Highx10==0 & Highx100==0 & getyourchoice==0
|
|
|
estadd scalar obs=r(N): bivar2
|
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eststo belief_all2: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==1 & updatewrong==0, vce(hc3) nocons
|
|
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|
test good=bad
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|
eststo belief_4: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==1 & updatewrong==0 & choicebefore==0, vce(hc3) nocons
|
|
|
test good=bad
|
|
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|
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|
|
eststo belief_5: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==1 & updatewrong==0 & choicebefore==1, vce(hc3) nocons
|
|
|
test good=bad
|
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|
|
|
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|
|
eststo bivar3: appendmodels belief_all2 belief_5 belief_4
|
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|
reg logitbelief good bad goodchoicebefore badchoicebefore
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==1 & updatewrong==0, vce(hc3) nocons
|
|
|
|
|
|
test goodchoicebefore==0
|
|
|
estadd scalar test_good_ifirst=r(p): bivar3
|
|
|
test badchoicebefore==0
|
|
|
estadd scalar test_bad_ifirst=r(p): bivar3
|
|
|
summ logitbelief if Highx10==0 & Highx100==0 & getyourchoice==1 & updatewrong==0
|
|
|
estadd scalar obs=r(N): bivar3
|
|
|
|
|
|
|
|
|
|
|
|
eststo belief_all3: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & updatewrong==0, vce(hc3) nocons
|
|
|
test good=bad
|
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|
|
|
|
|
|
|
|
|
|
eststo belief_6: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & updatewrong==0 & choicebefore==0, vce(hc3) nocons
|
|
|
test good=bad
|
|
|
|
|
|
|
|
|
eststo belief_7: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & updatewrong==0 & choicebefore==1, vce(hc3) nocons
|
|
|
test good=bad
|
|
|
|
|
|
eststo bivar4: appendmodels belief_all3 belief_7 belief_6
|
|
|
|
|
|
reg logitbelief good bad goodchoicebefore badchoicebefore
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & updatewrong==0, robust nocons
|
|
|
|
|
|
test goodchoicebefore==0
|
|
|
estadd scalar test_good_ifirst=r(p): bivar4
|
|
|
test badchoicebefore==0
|
|
|
estadd scalar test_bad_ifirst=r(p): bivar4
|
|
|
summ logitbelief if Highx10==0 & Highx100==0 & getyourchoice==0 & updatewrong==0
|
|
|
estadd scalar obs=r(N): bivar4
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
local panel "\begin{table}[h!]" "\centering" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{9}{10}\selectfont" "\begin{tabular}{l*{4}{c}}\hline"
|
|
|
local dv "&\multicolumn{4}{c}{\textbf{Log-odds Belief}} \\"
|
|
|
local pref "\multicolumn{1}{r}{\textit{Assignment:}}&\multicolumn{1}{c}{Assigned Pref.}&\multicolumn{1}{c}{Not Assigned Pref.}&\multicolumn{1}{c}{Assigned Pref.}&\multicolumn{1}{c}{Not Assigned Pref.}\\ "
|
|
|
local groups "\multicolumn{1}{r}{\textit{Data:}} &\multicolumn{2}{c}{All}&\multicolumn{2}{c}{Excl. update in wrong direction} \\\hline & & & & \\"
|
|
|
|
|
|
esttab bivar bivar2 bivar3 bivar4 using "${main}beliefs_pref_assign.tex", se r2 replace nolines cells(b(star fmt(3)) se(par fmt(3)))
|
|
|
coeflabel (bad "$\beta_C$" good "$\beta_{NC}$")
|
|
|
order (bad good)
|
|
|
star(* 0.10 ** 0.05 *** 0.01)
|
|
|
mlabels(none) label collabels(none)
|
|
|
stats(obs test_bad_ifirst test_good_ifirst, fmt(%9.0g %9.3f %9.3f %9.3f %9.3f) labels("Observations" "$\beta^{f=q}_C=\beta^{f=i}_{C}$" "$\beta^{f=q}_{NC}=\beta^{f=i}_{NC}$" ))
|
|
|
addnotes("Note: * p$<$.10; ** p$<$.05; *** p$<$.01") posthead("`dv'" "`pref'" "`groups'") prehead("`panel'")
|
|
|
postfoot("\hline" "\end{tabular}%" "\captionsetup{width=\textwidth}"
|
|
|
"\caption*{\footnotesize \textit{Notes:} The outcome in all regressions is the log belief ratio. $\beta^f_C$ and $\beta^f_{NC}$ are the estimated effects of the log likelihood ratio for conflict and no conflict signals, respectively, for advisors who prefer order $f$ ($f=i$ indicates a preference to see the incentive first, and $f=q$ indicates a preference to see quality first). Columns(1) and (2) include all advisors. Columns (3) and (4) exclude advisors who updated in the wrong direction. Columns (1) and (3) include only advisors who were assigned their preference, while columns (2) and (4) include only advisors who were not assigned their preference. Robust standard errors (HC3) in parentheses.\sym{*} \(p<0.10\), \sym{**} \(p<0.05\), \sym{***} \(p<0.01\).}" "\label{tab:beliefs}" "\end{table}")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
preserve
|
|
|
|
|
|
|
|
|
u "${data}nochoice.dta", clear
|
|
|
drop if alphavaluefinal==.
|
|
|
tab seeincentivefirst
|
|
|
|
|
|
|
|
|
|
|
|
u "${data}choice_experiments.dta", clear
|
|
|
drop if study!=1 & alphavaluefinal==.
|
|
|
tab condition if Highx10==0 & Highx100==0 & wave1==1
|
|
|
|
|
|
|
|
|
tab condition incentiveshigh if wave2==1
|
|
|
|
|
|
|
|
|
tab condition if Highx10==0 & Highx100==0 & wave3==1
|
|
|
|
|
|
tab condition if Highx10==1
|
|
|
|
|
|
tab condition if Highx100==1
|
|
|
|
|
|
|
|
|
u "${data}stakes.dta", clear
|
|
|
drop if alphavaluefinal==.
|
|
|
tab condition
|
|
|
|
|
|
|
|
|
u "${data}InformationArchitect.dta", clear
|
|
|
drop if alphavaluefinal==.
|
|
|
tab IAAdvisor
|
|
|
|
|
|
|
|
|
u "${data}Choice_Deterministic.dta", clear
|
|
|
drop if alphavaluefinal==.
|
|
|
tab Deterministic
|
|
|
|
|
|
|
|
|
u "${data}NoChoiceSimoultaneous.dta", clear
|
|
|
drop if alphavaluefinal==.
|
|
|
tab treatment
|
|
|
|
|
|
|
|
|
u "${data}predictionsstudy.dta", clear
|
|
|
tab gap
|
|
|
|
|
|
|
|
|
|
|
|
di 152+147+1308+1347+511+542+712+213+1067+215+275+110+483+511+478+245+253+385+369+70+78+128
|
|
|
restore
|
|
|
|
|
|
preserve
|
|
|
u "${data}professionals_jobtitles.dta", clear
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
tab fiduciary_2 fiduciary_1
|
|
|
|
|
|
di 677/712
|
|
|
|
|
|
|
|
|
|
|
|
alpha fiduciary_2 fiduciary_1
|
|
|
tab fiduciary_2 fiduciary_1
|
|
|
di (247+341)/677
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
egen meanfiduciary=rowmean(fiduciary_2 fiduciary_1)
|
|
|
tab meanfiduciary
|
|
|
di 100-37.09
|
|
|
|
|
|
|
|
|
tab fiduciary_2 fiduciary_1
|
|
|
di 341/(247+341)
|
|
|
|
|
|
|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
cap drop account
|
|
|
gen account = regexm(jobtitle, "account") | regexm(jobtitle, "Account")
|
|
|
tab account
|
|
|
|
|
|
gen analyst = regexm(jobtitle, "analyst") | regexm(jobtitle, "Analyst")
|
|
|
tab analyst
|
|
|
|
|
|
gen lawyer = regexm(jobtitle, "lawyer") | regexm(jobtitle, "Lawyer") | regexm(jobtitle, "Legal") | regexm(jobtitle, "legal")
|
|
|
tab lawyer
|
|
|
|
|
|
gen manager = regexm(jobtitle, "manager") | regexm(jobtitle, "Manager")
|
|
|
tab manager
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
tab industry if cloudresearch==0, m
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
alpha industrycode_2 industrycode_1 if cloudresearch==1
|
|
|
alpha industrycode_2 industrycode_1 if cloudresearch==0 & industry==""
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
g agreedcode=industrycode_2==industrycode_1
|
|
|
tab industrytype_2 industrytype_1 if agreedcode==1, m cell
|
|
|
restore
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
preserve
|
|
|
collapse year choicebefore (count) countobs=choicebefore, by(wave condition incentivedesign)
|
|
|
|
|
|
order year wave condition incentivedesign countobs choicebefore
|
|
|
replace condition="Choice Free" if condition=="ChoiceFree"
|
|
|
replace condition="Incentive First Costly" if condition=="PayBefore"
|
|
|
replace condition="Quality First Costly" if condition=="PayAfter"
|
|
|
format choicebefore %9.3fc
|
|
|
format countobs %9.0fc
|
|
|
rename wave Wave
|
|
|
rename condition Treatment
|
|
|
rename incentivedesign Incentives
|
|
|
rename year Year
|
|
|
rename countobs N
|
|
|
rename choicebefore DemandIncentiveFirst
|
|
|
drop Incentives Year
|
|
|
dataout, save("${appendix}AppendixTable_Conditions_Choice.tex") tex head replace
|
|
|
restore
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
est clear
|
|
|
eststo: reg avoid_incentive choicebefore $covariates2 noconflict if Highx10==0 & Highx100==0 & getyourchoice==1, vce(hc3)
|
|
|
eststo: reg avoid_incentive choicebefore $covariates2 noconflict if Highx10==0 & Highx100==0 & getyourchoice==0, vce(hc3)
|
|
|
eststo: reg avoid_incentive choicebefore notgetyourchoice choicebeforenotgetyourchoice $covariates2 noconflict if Highx10==0 & Highx100==0, vce(hc3)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
local panel "\begin{table}[h!]" "\centering" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{10}{11}\selectfont" "\caption{Preferences for Blindness and Preferences for Information Order}" "\begin{tabular}{l*{3}{c}} \hline"
|
|
|
local dv "& \multicolumn{3}{c}{\textbf{Advisor Preference to Blind}} \\"
|
|
|
local pref "&\multicolumn{1}{c}{Assigned Pref.} &\multicolumn{1}{c}{Not Assigned Pref.} &\multicolumn{1}{c}{Both} \\\hline & & & \\"
|
|
|
|
|
|
|
|
|
esttab using "${appendix}Choice_Blinding.tex", se r2 replace nolines cells(b(star fmt(3)) se(par fmt(3)))
|
|
|
coeflabel (noconflict "No Conflict"
|
|
|
choicebefore "Prefer Incentive First" notgetyourchoice "Not Assigned Preference"
|
|
|
choicebeforenotgetyourchoice "Prefer Incentive First X Not Assigned Preference"
|
|
|
seequalitycostly "Assess Quality First Costly" seeincentivecostly "See Incentive First Costly")
|
|
|
order (choicebefore noconflict notgetyourchoice
|
|
|
choicebeforenotgetyourchoice seeincentivecostly seequalitycostly)
|
|
|
star(* 0.10 ** 0.05 *** 0.01)
|
|
|
mlabels(none) label collabels(none)
|
|
|
drop(professionalsfree wave2 wave3 professionalscloudresearch incentiveshigh incentiveleft
|
|
|
incentiveshigh_incentiveleft age female)
|
|
|
addnotes("Note: * p$<$.10; ** p$<$.05; *** p$<$.01") posthead("`dv'" "`pref'" ) prehead("`panel'")
|
|
|
postfoot("\hline" "\end{tabular}%" "\captionsetup{width=1\textwidth}"
|
|
|
"\caption*{\footnotesize \textit{Notes:} This table displays the coefficient estimates of OLS regressions on the advisor's preferences to blind themselves to incentives information in the Blinding task. Robust standard errors in parentheses. \sym{*} \(p<0.10\), \sym{**} \(p<0.05\), \sym{***} \(p<0.01\).}" "\label{tab:blinding1}" "\end{table}")
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est clear
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eststo: reg avoid_incentive choicebefore $covariates2 noconflict stdalpha if Highx10==0 & Highx100==0 & getyourchoice==1, vce(hc3)
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eststo: reg avoid_incentive choicebefore $covariates2 noconflict stdalpha if Highx10==0 & Highx100==0 & getyourchoice==0, vce(hc3)
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eststo: reg avoid_incentive choicebefore notgetyourchoice choicebeforenotgetyourchoice $covariates2 noconflict stdalpha if Highx10==0 & Highx100==0, vce(hc3)
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local panel "\begin{table}[h!]" "\centering" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{10}{11}\selectfont" "\caption{Preferences for Blindness, Information Order \& Selfishness}" "\begin{tabular}{l*{3}{c}} \hline"
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local dv "& \multicolumn{3}{c}{\textbf{Advisor Preference to Blind}} \\"
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local pref "&\multicolumn{1}{c}{Assigned Pref.} &\multicolumn{1}{c}{Not Assigned Pref.} &\multicolumn{1}{c}{Both} \\\hline & & & \\"
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esttab using "${appendix}Choice_Blinding_selfish.tex", se r2 replace nolines cells(b(star fmt(3)) se(par fmt(3)))
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coeflabel (noconflict "No Conflict"
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choicebefore "Prefer Incentive First" notgetyourchoice "Not Assigned Preference"
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choicebeforenotgetyourchoice "Prefer Incentive First X Not Assigned Preference"
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seequalitycostly "Assess Quality First Costly" seeincentivecostly "See Incentive First Costly"
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stdalpha "Selfishness")
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order (choicebefore noconflict notgetyourchoice
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choicebeforenotgetyourchoice seeincentivecostly seequalitycostly stdalpha)
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star(* 0.10 ** 0.05 *** 0.01)
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mlabels(none) label collabels(none)
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drop(professionalsfree wave2 wave3 professionalscloudresearch incentiveshigh incentiveleft
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incentiveshigh_incentiveleft age female)
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addnotes("Note: * p$<$.10; ** p$<$.05; *** p$<$.01") posthead("`dv'" "`pref'" ) prehead("`panel'")
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postfoot("\hline" "\end{tabular}" "\captionsetup{width=1\textwidth}"
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"\caption*{\footnotesize \textit{Notes:} This table displays the coefficient estimates of OLS regressions on the advisor's preferences to blind themselves to incentives information in the Blinding task, controlling for selfishness. Selfishness was elicited at the end of the experiment, using a multiple price list (MPL) with 5 decisions. The variable is a standardized measure of the number of times the advisor chose to recommend the incentivized product in the MPL task. Robust standard errors in parentheses. \sym{*} \(p<0.10\), \sym{**} \(p<0.05\), \sym{***} \(p<0.01\).}" "\label{tab:blinding2}" "\end{table}")
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cap drop predrecommend_* ubpredrecommend_* lbpredrecommend_* sepredrecommend_*
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g predrecommend_dqf_gqf=.
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g sepredrecommend_dqf_gqf=.
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g predrecommend_dqf_gif=.
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g sepredrecommend_dqf_gif=.
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g predrecommend_dif_gqf=.
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g sepredrecommend_dif_gqf=.
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g predrecommend_dif_gif=.
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g sepredrecommend_dif_gif=.
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est clear
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eststo:reg recommendincentive i.treatment##i.getbefore incentiveB incentiveBgetbefore $covariates2
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if choicebefore==1
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& conflict==0 & Highx10==0 & Highx100==0, robust
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forval i=0(1)3{
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margins i.getbefore if treatment==`i', atmeans saving("${main}adjusted_recommendations", replace)
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matrix coeffs=r(table)
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replace predrecommend_dif_gqf=coeffs[1,1] if treatment==`i' & choicebefore==1 & getbefore==0
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replace sepredrecommend_dif_gqf=coeffs[2,1] if treatment==`i' & choicebefore==1 & getbefore==0
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replace predrecommend_dif_gif=coeffs[1,2] if treatment==`i' & choicebefore==1 & getbefore==1
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replace sepredrecommend_dif_gif=coeffs[2,2] if treatment==`i' & choicebefore==1 & getbefore==1
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}
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g ubpredrecommend_dif_gif=predrecommend_dif_gif+1.96*sepredrecommend_dif_gif
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g lbpredrecommend_dif_gif=predrecommend_dif_gif-1.96*sepredrecommend_dif_gif
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g ubpredrecommend_dif_gqf=predrecommend_dif_gqf+1.96*sepredrecommend_dif_gqf
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g lbpredrecommend_dif_gqf=predrecommend_dif_gqf-1.96*sepredrecommend_dif_gqf
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est clear
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eststo:reg recommendincentive i.treatment##i.getbefore incentiveB incentiveBgetbefore $covariates2
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if choicebefore==0
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& conflict==0 & Highx10==0 & Highx100==0, robust
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forval i=0(1)3{
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margins i.getbefore if treatment==`i', atmeans saving("${main}adjusted_recommendations", replace)
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matrix coeffs=r(table)
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replace predrecommend_dqf_gqf=coeffs[1,1] if treatment==`i' & choicebefore==0 & getbefore==0
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replace sepredrecommend_dqf_gqf=coeffs[2,1] if treatment==`i' & choicebefore==0 & getbefore==0
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replace predrecommend_dqf_gif=coeffs[1,2] if treatment==`i' & choicebefore==0 & getbefore==1
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replace sepredrecommend_dqf_gif=coeffs[2,2] if treatment==`i' & choicebefore==0 & getbefore==1
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}
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g ubpredrecommend_dqf_gif=predrecommend_dqf_gif+1.96*sepredrecommend_dqf_gif
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g lbpredrecommend_dqf_gif=predrecommend_dqf_gif-1.96*sepredrecommend_dqf_gif
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g ubpredrecommend_dqf_gqf=predrecommend_dqf_gqf+1.96*sepredrecommend_dqf_gqf
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g lbpredrecommend_dqf_gqf=predrecommend_dqf_gqf-1.96*sepredrecommend_dqf_gqf
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twoway (scatteri 1 0.7 1 1.7, bcolor(gs15) recast(area))
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(scatteri 1 2.7 1 3.7, bcolor(gs15) recast(area))
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(rcap lbpredrecommend_dif_gif ubpredrecommend_dif_gif treatnumgraph2, lcolor(red) lwidth(thin))
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(rcap lbpredrecommend_dqf_gqf ubpredrecommend_dqf_gqf treatnumgraph2, lcolor(black) lwidth(thin))
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(rcap lbpredrecommend_dif_gqf ubpredrecommend_dif_gqf treatnumgraph2, lcolor(red*0.3) lwidth(thin))
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(rcap lbpredrecommend_dqf_gif ubpredrecommend_dqf_gif treatnumgraph2, lcolor(black*0.3) lwidth(thin))
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(scatter predrecommend_dif_gif treatnumgraph2 if
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condition=="ChoiceFree_Professionals" & professionals==1 , mcolor(red) msize(*0.75) ms(T))
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(scatter predrecommend_dif_gqf treatnumgraph2 if
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condition=="ChoiceFree_Professionals" & professionals==1 & choicebefore==1 & getbefore==0, mfcolor(white) msize(*0.8) mlcolor(red%50) ms(S))
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(scatter predrecommend_dqf_gif treatnumgraph2 if
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condition=="ChoiceFree_Professionals" & professionals==1 & choicebefore==0 & getbefore==1, mfcolor(white) mlcolor(black%50) msize(*0.8) ms(T))
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(scatter predrecommend_dqf_gqf treatnumgraph2 if
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condition=="ChoiceFree_Professionals" & professionals==1 & choicebefore==0 & getbefore==0, mcolor(black) msize(*0.8) ms(S))
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(scatter predrecommend_dif_gif treatnumgraph2 if
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condition=="ChoiceFree" , mcolor(red) msize(*0.75) ms(T))
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(scatter predrecommend_dif_gqf treatnumgraph2 if
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condition=="ChoiceFree" , mfcolor(white) msize(*0.8) mlcolor(red%50) ms(T))
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(scatter predrecommend_dqf_gif treatnumgraph2 if
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condition=="ChoiceFree", mfcolor(white) mlcolor(black*0.3) msize(*0.8) ms(S))
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(scatter predrecommend_dqf_gqf treatnumgraph2 if
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condition=="ChoiceFree", msize(*0.8) mcolor(black) ms(S))
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(scatter predrecommend_dif_gif treatnumgraph2 if condition=="PayAfter", mcolor(red) msize(*0.75) ms(T))
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(scatter predrecommend_dif_gqf treatnumgraph2 if condition=="PayAfter", mfcolor(white) msize(*0.8) mlcolor(red%50) ms(T))
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(scatter predrecommend_dqf_gif treatnumgraph2 if condition=="PayAfter", mfcolor(white) mlcolor(black%50) msize(*0.8) ms(S))
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(scatter predrecommend_dqf_gqf treatnumgraph2 if condition=="PayAfter", mcolor(black) msize(*0.8) ms(S))
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(scatter predrecommend_dif_gif treatnumgraph2 if condition=="PayBefore", mcolor(red) msize(*0.75) ms(T))
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(scatter predrecommend_dif_gqf treatnumgraph2 if condition=="PayBefore", mfcolor(white) msize(*0.8) mlcolor(red%50) ms(T))
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(scatter predrecommend_dqf_gif treatnumgraph2 if condition=="PayBefore", mfcolor(white) mlcolor(black%50) msize(*0.8) ms(S))
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(scatter predrecommend_dqf_gqf treatnumgraph2 if condition=="PayBefore", msize(*0.8) mcolor(black) ms(S))
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, graphr(c(white)) plotr(c(white))
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ylabel(0.3(0.1)1) yscale(r(0.3 1))
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xtitle("Treatment")
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xlabel(none)
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xscale(r(0.7 4.6))
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legend(order( - "{bf:Advisor Prefers to}" "{bf:See Incentive First}"
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|
7 8 - "{bf:Advisor Prefers to}" "{bf:Assess Quality First}" 9 10)
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lab(7 " Assigned to See Incentive First")
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lab(8 " Assigned to Assess Quality First")
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lab(10 " Assigned to Assess Quality First")
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lab(9 " Assigned to See Incentive First")
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rows(3) colfirst size(*0.7))
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|
text(0.38 1.15 "{bf: Choice Free}", color(black) size(*0.8))
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text(0.35 1.15 "{bf: - Professionals}", color(black) size(*0.8))
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text(0.38 2.15 "{bf: Choice}", color(black) size(*0.8))
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text(0.35 2.15 "{bf: Free }", color(black) size(*0.8))
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text(0.38 4.15 "{bf: Quality First}", color(black) size(*0.8))
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text(0.35 4.15 "{bf: Costly}", color(black) size(*0.8))
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text(0.38 3.15 "{bf: Incentive First}", color(black) size(*0.8))
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text(0.35 3.15 "{bf: Costly}", color(black) size(*0.8))
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|
ytitle("{bf:Incentivized product recommendation}" " " )
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|
graph export "${appendix}Choice_Recommendations_Noconflict.png", replace
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|
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|
|
|
est clear
|
|
|
eststo: reg recommendincentive choicebefore choicebeforenoconflict
|
|
|
noconflict incentiveB stdalpha $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==1, vce(hc3)
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|
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|
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eststo: reg recommendincentive choicebefore choicebeforenoconflict
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|
noconflict incentiveB stdalpha $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==0, vce(hc3)
|
|
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|
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|
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|
eststo: reg recommendincentive choicebefore choicebeforenoconflict
|
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|
noconflict notgetyourchoice choicebeforenotgetyourchoice notgetyourchoicenoconflict incentiveB
|
|
|
stdalpha $covariates2
|
|
|
if Highx10==0 & Highx100==0, vce(hc3)
|
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|
|
local panel "\begin{table}[h!]" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{10}{10}\selectfont" "\caption{Advisor Recommendations}" "\begin{tabular}{l*{3}{c}} \hline"
|
|
|
local dv "&\multicolumn{3}{c}{\textbf{Recommend incentivized product}} \\"
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|
|
local groups "\multicolumn{1}{r}{\textit{Assignment:}}&\multicolumn{1}{c}{Assigned Pref.}&\multicolumn{1}{c}{Not Assigned Pref.}&\multicolumn{1}{c}{Both} \\\hline & & & & \\ "
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|
local conflict "&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict}&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict}&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict} \\ \hline & & & & & & \\"
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|
esttab using "${appendix}Choice_Recommendations_Selfishness.tex", se r2 replace cells(b(star fmt(3)) se(par fmt(3)))
|
|
|
coeflabel (noconflict "No Conflict" getbefore "Assigned to See Incentive First" getbeforenoconflict "Assigned to See Incentive First X No Conflict" professionalsfree "Choice Free--Professionals" seeincentivecostly "See Incentive First Costly" seequalitycostly "Assess Quality First Costly" wave2 "Wave 2" wave3 "Wave 3" notgetyourchoice "Not Assigned Preference"
|
|
|
female "Female" age "Age" stdalpha "Selfishness" professionalscloudresearch "Professionals x Cloudresearch"
|
|
|
incentiveshigh "Probabilistic Incentive Mturk" incentiveleft "Order" incentiveshigh_incentiveleft "Probabilistic Incentive X Order"
|
|
|
incentiveB "Incentive for B" choicebefore "Prefer to See Incentive First"
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|
choicebeforenoconflict "No Conflict X Prefer to See Incentive First"
|
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|
choicebeforenotgetyourchoice "Prefer to See Incentive First X Not Assigned Pref."
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|
notgetyourchoicenoconflict "No Conflict X Not Assigned Preference")
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|
order (choicebefore notgetyourchoice choicebeforenotgetyourchoice noconflict choicebeforenoconflict notgetyourchoicenoconflict seeincentivecostly seequalitycostly professionalsfree incentiveB stdalpha female age wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch )
|
|
|
star(* 0.10 ** 0.05 *** 0.01) title("Advisor Recommendations")
|
|
|
drop(professionalsfree wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch)
|
|
|
mlabels(none) label collabels(none) substitute(" 0.000 " " " " (.) " " ")
|
|
|
posthead("`dv'" "`groups'") prehead("`panel'") nolines postfoot("\hline" "\end{tabular}%" "\captionsetup{width=\textwidth}" "\caption*{\footnotesize \textit{Notes:} This table displays the estimated coefficients from linear probability models on the advisor's decision to recommend the incentivized option. Column (1) focuses on individuals who are assigned their preference, while column (2) focuses on individuals who are not assigned their preference. Both groups are merged in column (3). Prefer to See Incentive First is an indicator of the advisor's preference, and Not Assigned Preference is an indicator for not receiving the preferred order. No Conflict is an indicator for the cases in which the signal of quality is not in conflict with the advisor's commission. Choice Free-Professionals, See Incentive First Costly and Assess Quality First Costly are indicator variables that take value 1 in the respective treatment, 0 otherwise. Selfishness was elicited at the end of the experiment, using a multiple price list (MPL) with 5 decisions. The variable is a standardized measure of the number of times the advisor chose to recommend the incentivized product in the MPL task. All regression models include controls for each wave of the experiment, whether incentives were probabilistic, the position of the products on the screen and the interaction between these two variables. Robust standard errors (HC3) in parentheses. * p$<$.10; ** p$<$.05; *** p$<$.01}" "\label{tab:recommendations_selfish}" "\end{table}")
|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
est clear
|
|
|
eststo: reg recommendincentive choicebefore choicebeforenoconflict
|
|
|
noconflict $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==1 & incentiveB==0, vce(hc3)
|
|
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|
|
|
|
|
|
eststo: reg recommendincentive choicebefore choicebeforenoconflict
|
|
|
noconflict $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==0 & incentiveB==0, vce(hc3)
|
|
|
|
|
|
|
|
|
eststo: reg recommendincentive choicebefore choicebeforenoconflict
|
|
|
noconflict notgetyourchoice choicebeforenotgetyourchoice notgetyourchoicenoconflict $covariates2
|
|
|
if Highx10==0 & Highx100==0 & incentiveB==0, vce(hc3)
|
|
|
|
|
|
|
|
|
|
|
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|
|
local panel "\begin{table}[h!]" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{10}{10}\selectfont" "\caption{Advisor Recommendations: Incentive for A}" "\begin{tabular}{l*{3}{c}} \hline"
|
|
|
local dv "&\multicolumn{3}{c}{\textbf{Recommend incentivized product}} \\"
|
|
|
local groups "\multicolumn{1}{r}{\textit{Assignment:}}&\multicolumn{1}{c}{Assigned Pref.}&\multicolumn{1}{c}{Not Assigned Pref.}&\multicolumn{1}{c}{Both} \\\hline & & & & \\ "
|
|
|
local conflict "&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict}&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict}&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict} \\ \hline & & & & & & \\"
|
|
|
|
|
|
esttab using "${appendix}Choice_Recommendations_IncentiveA.tex", se r2 replace cells(b(star fmt(3)) se(par fmt(3)))
|
|
|
coeflabel (noconflict "No Conflict" getbefore "Assigned to See Incentive First" getbeforenoconflict "Assigned to See Incentive First X No Conflict" professionalsfree "Choice Free--Professionals" seeincentivecostly "See Incentive First Costly" seequalitycostly "Assess Quality First Costly" wave2 "Wave 2" wave3 "Wave 3" notgetyourchoice "Not Assigned Preference"
|
|
|
female "Female" age "Age" selfish "Selfish" professionalscloudresearch "Professionals x Cloudresearch" selfishseeincentivecostly "Selfish X See Incentive First Costly" selfishseequalitycostly "Selfish X See Quality First Costly"
|
|
|
incentiveshigh "Probabilistic Incentive Mturk" incentiveleft "Order" incentiveshigh_incentiveleft "Probabilistic Incentive X Order"
|
|
|
choicebefore "Prefer to See Incentive First"
|
|
|
choicebeforenoconflict "No Conflict X Prefer to See Incentive First"
|
|
|
choicebeforenotgetyourchoice "Prefer to See Incentive First X Not Assigned Pref."
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|
notgetyourchoicenoconflict "No Conflict X Not Assigned Preference"
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|
|
selfishchoicebefore "Prefer to See Incentive First X Selfish"
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|
|
selfishnotgetyourchoice "Not Assigned Preference X Selfish")
|
|
|
order (choicebefore notgetyourchoice choicebeforenotgetyourchoice noconflict choicebeforenoconflict notgetyourchoicenoconflict seeincentivecostly seequalitycostly professionalsfree female age wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch )
|
|
|
star(* 0.10 ** 0.05 *** 0.01) title("Advisor Recommendations")
|
|
|
drop(professionalsfree wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch)
|
|
|
mlabels(none) label collabels(none) substitute(" 0.000 " " " " (.) " " ")
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|
posthead("`dv'" "`groups'") prehead("`panel'") nolines postfoot("\hline" "\end{tabular}%" "\captionsetup{width=\textwidth}" "\caption*{\footnotesize \textit{Notes:} This table displays the estimated coefficients from linear probability models on the advisor's decision to recommend the incentivized option, focusing on the cases in which advisors were incentivized to recommend product A. Column (1) focuses on individuals who are assigned their preference, while column (2) focuses on individuals who are not assigned their preference. Both groups are merged in column (3). Prefer to See Incentive First is an indicator of the advisor's preference, and Not Assigned Preference is an indicator for not receiving the preferred order. No Conflict is an indicator for the cases in which the signal of quality is not in conflict with the advisor's commission. Choice Free-Professionals, See Incentive First Costly and Assess Quality First Costly are indicator variables that take value 1 in the respective treatment, 0 otherwise. All regression models include controls for each wave of the experiment, whether incentives were probabilistic, the position of the products on the screen and the interaction between these two variables. Robust standard errors (HC3) in parentheses. * p$<$.10; ** p$<$.05; *** p$<$.01}" "\label{tab:recommendations_A}" "\end{table}")
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|
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|
est clear
|
|
|
eststo: reg recommendincentive choicebefore choicebeforenoconflict
|
|
|
noconflict $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==1 & incentiveB==1, vce(hc3)
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|
|
|
|
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|
eststo: reg recommendincentive choicebefore choicebeforenoconflict
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noconflict $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==0 & incentiveB==1, vce(hc3)
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|
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|
eststo: reg recommendincentive choicebefore choicebeforenoconflict
|
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|
noconflict notgetyourchoice choicebeforenotgetyourchoice notgetyourchoicenoconflict $covariates2
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if Highx10==0 & Highx100==0 & incentiveB==1, vce(hc3)
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local panel "\begin{table}[h!]" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{10}{10}\selectfont" "\caption{Advisor Recommendations: Incentive for B}" "\begin{tabular}{l*{3}{c}} \hline"
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local dv "&\multicolumn{3}{c}{\textbf{Recommend incentivized product}} \\"
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local groups "\multicolumn{1}{r}{\textit{Assignment:}}&\multicolumn{1}{c}{Assigned Pref.}&\multicolumn{1}{c}{Not Assigned Pref.}&\multicolumn{1}{c}{Both} \\\hline & & & & \\ "
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local conflict "&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict}&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict}&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict} \\ \hline & & & & & & \\"
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esttab using "${appendix}Choice_Recommendations_IncentiveB.tex", se r2 replace cells(b(star fmt(3)) se(par fmt(3)))
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coeflabel (noconflict "No Conflict" getbefore "Assigned to See Incentive First" getbeforenoconflict "Assigned to See Incentive First X No Conflict" professionalsfree "Choice Free--Professionals" seeincentivecostly "See Incentive First Costly" seequalitycostly "Assess Quality First Costly" wave2 "Wave 2" wave3 "Wave 3" notgetyourchoice "Not Assigned Preference"
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female "Female" age "Age" selfish "Selfish" professionalscloudresearch "Professionals x Cloudresearch" selfishseeincentivecostly "Selfish X See Incentive First Costly" selfishseequalitycostly "Selfish X See Quality First Costly"
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incentiveshigh "Probabilistic Incentive Mturk" incentiveleft "Order" incentiveshigh_incentiveleft "Probabilistic Incentive X Order"
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choicebefore "Prefer to See Incentive First"
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choicebeforenoconflict "No Conflict X Prefer to See Incentive First"
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choicebeforenotgetyourchoice "Prefer to See Incentive First X Not Assigned Pref."
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notgetyourchoicenoconflict "No Conflict X Not Assigned Preference"
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selfishchoicebefore "Prefer to See Incentive First X Selfish"
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selfishnotgetyourchoice "Not Assigned Preference X Selfish")
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order (choicebefore notgetyourchoice choicebeforenotgetyourchoice noconflict choicebeforenoconflict notgetyourchoicenoconflict seeincentivecostly seequalitycostly professionalsfree female age wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch )
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star(* 0.10 ** 0.05 *** 0.01) title("Advisor Recommendations")
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drop(professionalsfree wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch)
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mlabels(none) label collabels(none) substitute(" 0.000 " " " " (.) " " ")
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posthead("`dv'" "`groups'") prehead("`panel'") nolines postfoot("\hline" "\end{tabular}%" "\captionsetup{width=\textwidth}" "\caption*{\footnotesize \textit{Notes:} This table displays the estimated coefficients from linear probability models on the advisor's decision to recommend the incentivized option, focusing on the cases in which advisors were incentivized to recommend product B. Column (1) focuses on individuals who are assigned their preference, while column (2) focuses on individuals who are not assigned their preference. Both groups are merged in column (3). Prefer to See Incentive First is an indicator of the advisor's preference, and Not Assigned Preference is an indicator for not receiving the preferred order. No Conflict is an indicator for the cases in which the signal of quality is not in conflict with the advisor's commission. Choice Free-Professionals, See Incentive First Costly and Assess Quality First Costly are indicator variables that take value 1 in the respective treatment, 0 otherwise. All regression models include controls for each wave of the experiment, whether incentives were probabilistic, the position of the products on the screen and the interaction between these two variables. Robust standard errors (HC3) in parentheses. * p$<$.10; ** p$<$.05; *** p$<$.01}" "\label{tab:recommendations_B}" "\end{table}")
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est clear
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eststo: reg recommendincentive choicebefore choicebeforenoconflict
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noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & getbefore==1, vce(hc3)
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test choicebefore+choicebeforenoconflict==0
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eststo: reg recommendincentive choicebefore choicebeforenoconflict
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noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & getbefore==0, vce(hc3)
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eststo: reg recommendincentive getbefore getbeforenoconflict
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noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & choicebefore==1, vce(hc3)
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eststo: reg recommendincentive getbefore getbeforenoconflict
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noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & choicebefore==0, vce(hc3)
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eststo: reg recommendincentive choicebefore choicebeforenoconflict
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noconflict getbefore choicebeforegetbefore getbeforenoconflict incentiveB $covariates2
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if Highx10==0 & Highx100==0, vce(hc3)
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test choicebefore=getbefore+choicebeforegetbefore
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local panel "\begin{table}[h!]" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{10}{10}\selectfont" "\caption{Advisor Recommendations - Role of Selection and Experience}" "\hspace{-1cm}" "\begin{tabular}{l*{5}{c}} \hline"
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local dv "&\multicolumn{5}{c}{\textbf{Recommend incentivized product}} \\"
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local assigned "\multicolumn{1}{r}{\textit{Sample:}}&\multicolumn{2}{c}{Assigned to See:}&\multicolumn{2}{c}{Prefer to See:}&\multicolumn{1}{c}{Full Sample} \\ "
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local groups "\multicolumn{1}{r}{\textit{}}&\multicolumn{1}{c}{Incentive First}&\multicolumn{1}{c}{Quality First}&\multicolumn{1}{c}{Incentive First}&\multicolumn{1}{c}{Quality First} & \\\hline & & & \\ "
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esttab using "${appendix}Choice_recommendations_selection.tex", se r2 replace cells(b(star fmt(3)) se(par fmt(3)))
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coeflabel (choicebefore "Prefer See Inc. First" noconflict "No Conflict" getbefore "Assigned See Inc. First" getbeforenoconflict "No Conflict X Assigned See Inc. First" professionalsfree "Choice Free--Professionals" seeincentivecostly "See Inc. First Costly" seequalitycostly "Assess Quality First Costly" wave2 "Wave 2" wave3 "Wave 3" notgetyourchoice "Not Assigned Preference"
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choicebeforegetbefore "Prefer X Assigned See Inc. First"female "Female" age "Age" selfish "Selfish" professionalscloudresearch "Professionals x Cloudresearch" selfishseeincentivecostly "Selfish X See Inc. First Costly" selfishseequalitycostly "Selfish X See Quality First Costly"
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incentiveshigh "Probabilistic Incentive Mturk" incentiveleft "Order" incentiveshigh_incentiveleft "Probabilistic Incentive X Order"
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incentiveB "Incentive for B" choicebefore "Prefer to See Incentive First"
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choicebeforenoconflict "No Conflict X Prefer See Inc. First"
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choicebeforenotgetyourchoice "Prefer See Inc. First X Not Assigned Preference" )
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order (choicebefore getbefore choicebeforegetbefore noconflict choicebeforenoconflict getbeforenoconflict professionalsfree seeincentivecostly seequalitycostly incentiveB selfish female age wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch )
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star(* 0.10 ** 0.05 *** 0.01) title("Advisor Recommendations")
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drop(selfish wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch)
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mlabels(none) label collabels(none) substitute(" 0.00 " " " " (.) " " ")
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posthead("`dv'" "`assigned'" "`groups'") prehead("`panel'") nolines postfoot("\hline" "\end{tabular}%" "\captionsetup{width=1.15\textwidth}" "\caption*{\footnotesize Note: This table displays the estimated coefficients from linear probability models on the advisor's decision to recommend the incentivized option. Column (1) and (2) focus on participants assigned to experience a given information order. Column (1) focuses on individuals who are assigned to see the incentive first, column (2) focuses on individuals who are assigned to see quality first. Columns (3) and (4) focus on individuals' who prefer to be assigned to a given order, with Column (3) focusing on those who prefer to see the incentive first, and Column (4) focusing on those who prefer to see quality first. These groups are merged in column (5). Prefer See Inc. First is an indicator of the advisor's preference to see her incentive first, and Assigned See Inc. First is a indicator for whether advisors are assigned to see their incentive first. No Conflict is an indicator for the cases in which the signal of quality is not in conflict with the advisor's commission. See Incentive First Costly and Assess Quality First Costly are indicator variables that take value 1 in the respective treatment, 0 otherwise. All regression models include individual controls for the advisor's gender and age, each wave of the experiment, whether incentives were probabilistic, the position of the products on the screen and the interaction between these two variables. The same analysis including a measure of advisor's selfishness are shown in Online Appendix C. Robust standard errors (HC3) in parentheses. * p$<$.10; ** p$<$.05; *** p$<$.01}" "\label{tab:recommendations}" "\end{table}")
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cumul relbeliefdistance if choicebefore==1 & getbefore==1 & badsignal==1, generate(bel_dif_gif_bad) equal
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cumul relbeliefdistance if choicebefore==0 & getbefore==0 & badsignal==1, generate(bel_dqf_gqf_bad) equal
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cumul relbeliefdistance if choicebefore==1 & getbefore==1 & badsignal==0, generate(bel_dif_gif_good) equal
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cumul relbeliefdistance if choicebefore==0 & getbefore==0 & badsignal==0, generate(bel_dqf_gqf_good) equal
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cumul relbeliefdistance if choicebefore==1 & getbefore==0 & badsignal==1, generate(bel_dif_gqf_bad) equal
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cumul relbeliefdistance if choicebefore==0 & getbefore==1 & badsignal==1, generate(bel_dqf_gif_bad) equal
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cumul relbeliefdistance if choicebefore==1 & getbefore==0 & badsignal==0, generate(bel_dif_gqf_good) equal
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cumul relbeliefdistance if choicebefore==0 & getbefore==1 & badsignal==0, generate(bel_dqf_gif_good) equal
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twoway (scatter bel_dif_gif_bad relbeliefdistance, sort c(J) ms(none) color(red) lpattern(longdash))
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(scatter bel_dqf_gqf_bad relbeliefdistance, sort c(J) ms(none) color(black) lpattern(longdash))
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, ytitle("CDF") xtitle("Relative Distance from Prior" "((Prior - Belief) / (Prior - Bayesian Posterior))")
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legend( pos(10) ring(0) col(1)
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label(2 "Prefer to See Quality First") label(1 "Prefer to See Incentive First") size(*0.8))
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xlabel(-2(0.5)2) xscale(r(0 1))
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graphr(c(white))
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xline(1, lcolor(gs12)) xline(0, lcolor(gs12))
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text(0.0 0.3 "Prior", color(gs10) size(*0.8))
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text(0.0 2 "Bayesian Posterior", color(gs10) size(*0.8))
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title("Conflict", color(black) size(*0.8))
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graph export "${appendix}Choice_Beliefs_Getchoice_Bad.png", replace
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graph save "${appendix}Choice_Beliefs_Getchoice_bad.gph", replace
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twoway (scatter bel_dif_gif_good relbeliefdistance, sort c(J) ms(none) color(red) lpattern(longdash))
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(scatter bel_dqf_gqf_good relbeliefdistance, sort c(J) ms(none) color(black) lpattern(longdash))
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, ytitle("CDF") xtitle("Relative Distance from Prior" "((Prior - Belief) / (Prior - Bayesian Posterior))")
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legend( pos(10) ring(0) col(1)
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label(2 "Prefer to See Quality First") label(1 "Prefer to See Incentive First") size(*0.8))
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xlabel(-2(0.5)2) xscale(r(0 1))
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graphr(c(white))
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xline(1, lcolor(gs12)) xline(0, lcolor(gs12))
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text(0.0 0.3 "Prior", color(gs10) size(*0.8))
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text(0.0 2 "Bayesian Posterior", color(gs10) size(*0.8))
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title("No Conflict", color(black) size(*0.8))
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graph save "${appendix}Choice_Beliefs_Getchoice_Good.gph", replace
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grc1leg "${appendix}Choice_Beliefs_Getchoice_bad.gph"
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"${appendix}Choice_Beliefs_Getchoice_Good.gph"
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, graphr(c(white))
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graph export "${appendix}Choice_Beliefs_Getchoice.pdf", replace
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twoway (scatter bel_dif_gqf_bad relbeliefdistance, sort c(J) ms(none) color(red) lpattern(longdash))
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|
(scatter bel_dqf_gif_bad relbeliefdistance, sort c(J) ms(none) color(black) lpattern(longdash))
|
|
|
, ytitle("CDF") xtitle("Relative Distance from Prior" "((Prior - Belief) / (Prior - Bayesian Posterior))")
|
|
|
legend( pos(10) ring(0) col(1)
|
|
|
label(2 "Prefer to See Quality First") label(1 "Prefer to See Incentive First") size(*0.8))
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|
xlabel(-2(0.5)2) xscale(r(0 1))
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|
graphr(c(white))
|
|
|
xline(1, lcolor(gs12)) xline(0, lcolor(gs12))
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|
text(0.0 0.3 "Prior", color(gs10) size(*0.8))
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text(0.0 2 "Bayesian Posterior", color(gs10) size(*0.8))
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title("Conflict", color(black) size(*0.8))
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graph export "${appendix}Choice_Beliefs_Notgetchoice_Bad.png", replace
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graph save "${appendix}Choice_Beliefs_Notgetchoice_Bad.gph", replace
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|
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twoway (scatter bel_dif_gqf_good relbeliefdistance, sort c(J) ms(none) color(red) lpattern(longdash))
|
|
|
(scatter bel_dqf_gif_good relbeliefdistance, sort c(J) ms(none) color(black) lpattern(longdash))
|
|
|
, ytitle("CDF") xtitle("Relative Distance from Prior" "((Prior - Belief) / (Prior - Bayesian Posterior))")
|
|
|
legend( pos(10) ring(0) col(1)
|
|
|
label(2 "Prefer to See Quality First") label(1 "Prefer to See Incentive First") size(*0.8))
|
|
|
xlabel(-2(0.5)2) xscale(r(0 1))
|
|
|
graphr(c(white))
|
|
|
xline(1, lcolor(gs12)) xline(0, lcolor(gs12))
|
|
|
text(0.0 0.3 "Prior", color(gs10) size(*0.8))
|
|
|
text(0.0 2 "Bayesian Posterior", color(gs10) size(*0.8))
|
|
|
title("No Conflict", color(black) size(*0.8))
|
|
|
graph save "${appendix}Choice_Beliefs_Notgetchoice_Good.gph", replace
|
|
|
|
|
|
grc1leg "${appendix}Choice_Beliefs_Notgetchoice_Bad.gph"
|
|
|
"${appendix}Choice_Beliefs_Notgetchoice_Good.gph"
|
|
|
, graphr(c(white))
|
|
|
graph export "${appendix}Choice_Beliefs_Notgetchoice.pdf", replace
|
|
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|
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|
|
|
|
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|
est clear
|
|
|
|
|
|
eststo belief_all0: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==1 & signalblue==0, vce(hc3) nocons
|
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|
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|
test good=bad
|
|
|
|
|
|
eststo belief_0: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==1 & choicebefore==0 & signalblue==0 , vce(hc3) nocons
|
|
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|
test good=bad
|
|
|
|
|
|
eststo belief_1: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==1 & choicebefore==1 & signalblue==0, vce(hc3) nocons
|
|
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|
|
test good=bad
|
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|
|
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|
eststo bivar: appendmodels belief_all0 belief_1 belief_0
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reg logitbelief good bad goodchoicebefore badchoicebefore
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==1 & signalblue==0, vce(hc3) nocons
|
|
|
test goodchoicebefore==0
|
|
|
estadd scalar test_good_ifirst=r(p): bivar
|
|
|
test badchoicebefore==0
|
|
|
estadd scalar test_bad_ifirst=r(p): bivar
|
|
|
summ logitbelief if Highx10==0 & Highx100==0 & getyourchoice==1 & signalblue==0
|
|
|
estadd scalar obs=r(N): bivar
|
|
|
|
|
|
|
|
|
eststo belief_all1: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & signalblue==0, vce(hc3) nocons
|
|
|
|
|
|
eststo belief_2: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & choicebefore==0 & signalblue==0, vce(hc3) nocons
|
|
|
|
|
|
test good=bad
|
|
|
|
|
|
|
|
|
eststo belief_3: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & choicebefore==1 & signalblue==0, vce(hc3) nocons
|
|
|
|
|
|
test good=bad
|
|
|
|
|
|
eststo bivar2: appendmodels belief_all1 belief_3 belief_2
|
|
|
|
|
|
reg logitbelief good bad goodchoicebefore badchoicebefore
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & signalblue==0, vce(hc3) nocons
|
|
|
|
|
|
test goodchoicebefore==0
|
|
|
estadd scalar test_good_ifirst=r(p): bivar2
|
|
|
test badchoicebefore==0
|
|
|
estadd scalar test_bad_ifirst=r(p): bivar2
|
|
|
summ logitbelief if Highx10==0 & Highx100==0 & getyourchoice==0 & signalblue==0
|
|
|
estadd scalar obs=r(N): bivar2
|
|
|
|
|
|
|
|
|
|
|
|
eststo belief_all2: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==1 & updatewrong==0 & signalblue==0, vce(hc3) nocons
|
|
|
test good=bad
|
|
|
|
|
|
eststo belief_4: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==1 & updatewrong==0 & choicebefore==0 & signalblue==0, vce(hc3) nocons
|
|
|
test good=bad
|
|
|
|
|
|
eststo belief_5: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==1 & updatewrong==0 & choicebefore==1 & signalblue==0, vce(hc3) nocons
|
|
|
test good=bad
|
|
|
|
|
|
|
|
|
eststo bivar3: appendmodels belief_all2 belief_5 belief_4
|
|
|
|
|
|
reg logitbelief good bad goodchoicebefore badchoicebefore
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==1 & updatewrong==0 & signalblue==0, vce(hc3) nocons
|
|
|
|
|
|
test goodchoicebefore==0
|
|
|
estadd scalar test_good_ifirst=r(p): bivar3
|
|
|
test badchoicebefore==0
|
|
|
estadd scalar test_bad_ifirst=r(p): bivar3
|
|
|
summ logitbelief if Highx10==0 & Highx100==0 & getyourchoice==1 & updatewrong==0 & signalblue==0
|
|
|
estadd scalar obs=r(N): bivar3
|
|
|
|
|
|
test goodchoicebefore==badchoicebefore
|
|
|
|
|
|
|
|
|
|
|
|
eststo belief_all3: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & updatewrong==0 & signalblue==0, vce(hc3) nocons
|
|
|
test good=bad
|
|
|
|
|
|
eststo belief_6: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & updatewrong==0 & choicebefore==0 & signalblue==0, vce(hc3) nocons
|
|
|
test good=bad
|
|
|
|
|
|
eststo belief_7: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & updatewrong==0 & choicebefore==1 & signalblue==0, vce(hc3) nocons
|
|
|
test good=bad
|
|
|
|
|
|
eststo bivar4: appendmodels belief_all3 belief_7 belief_6
|
|
|
|
|
|
reg logitbelief good bad goodchoicebefore badchoicebefore
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & updatewrong==0 & signalblue==0, robust nocons
|
|
|
|
|
|
test goodchoicebefore==0
|
|
|
estadd scalar test_good_ifirst=r(p): bivar4
|
|
|
test badchoicebefore==0
|
|
|
estadd scalar test_bad_ifirst=r(p): bivar4
|
|
|
summ logitbelief if Highx10==0 & Highx100==0 & getyourchoice==0 & updatewrong==0 & signalblue==0
|
|
|
estadd scalar obs=r(N): bivar4
|
|
|
|
|
|
|
|
|
local panel "\begin{table}[h!]" "\centering" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{9}{10}\selectfont" "\begin{tabular}{l*{4}{c}}\hline"
|
|
|
local dv "&\multicolumn{4}{c}{\textbf{Log-odds Belief}} \\"
|
|
|
local pref "\multicolumn{1}{r}{\textit{Assignment:}}&\multicolumn{1}{c}{Assigned Pref.}&\multicolumn{1}{c}{Not Assigned Pref.}&\multicolumn{1}{c}{Assigned Pref.}&\multicolumn{1}{c}{Not Assigned Pref.}\\ "
|
|
|
local groups "\multicolumn{1}{r}{\textit{Data:}} &\multicolumn{2}{c}{All}&\multicolumn{2}{c}{Excl. update in wrong direction} \\\hline & & & & \\"
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|
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|
|
|
esttab bivar bivar2 bivar3 bivar4 using "${appendix}beliefs_pref_assign_ball0.tex", se r2 replace nolines cells(b(star fmt(3)) se(par fmt(3)))
|
|
|
coeflabel (bad "$\beta_C$" good "$\beta_{NC}$")
|
|
|
order (bad good)
|
|
|
star(* 0.10 ** 0.05 *** 0.01)
|
|
|
mlabels(none) label collabels(none)
|
|
|
stats(obs test_bad_ifirst test_good_ifirst, fmt(%9.0g %9.3f %9.3f %9.3f %9.3f) labels("Observations" "$\beta^{f=q}_C=\beta^{f=i}_{C}$" "$\beta^{f=q}_{NC}=\beta^{f=i}_{NC}$" ))
|
|
|
addnotes("Note: * p$<$.10; ** p$<$.05; *** p$<$.01") posthead("`dv'" "`pref'" "`groups'") prehead("`panel'")
|
|
|
postfoot("\hline" "\end{tabular}%" "\captionsetup{width=0.8\textwidth}"
|
|
|
"\caption*{\footnotesize \textit{Notes:} The outcome in all regressions is the log belief ratio, when the advisors sees a \$0 ball for product $B$. $\beta^f_C$ and $\beta^f_{NC}$ are the estimated effects of the log likelihood ratio for conflict and no conflict signals, respectively, for advisors who prefer order $f$ ($f=i$ indicates a preference to see the incentive first, and $f=q$ indicates a preference to see quality first). Columns(1) and (2) include all advisors. Columns (3) and (4) exclude advisors who updated in the wrong direction. Columns (1) and (3) include only advisors who were assigned their preference, while columns (2) and (4) include only advisors who were not assigned their preference. Robust standard errors (HC3) in parentheses.\sym{*} \(p<0.10\), \sym{**} \(p<0.05\), \sym{***} \(p<0.01\).}" "\label{tab:beliefs1}" "\end{table}")
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est clear
|
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|
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|
eststo belief_all0: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==1 & signalblue==1, vce(hc3) nocons
|
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|
test good=bad
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|
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|
|
eststo belief_0: reg logitbelief bad good
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if Highx10==0 & Highx100==0 & getyourchoice==1 & choicebefore==0 & signalblue==1 , vce(hc3) nocons
|
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test good=bad
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|
eststo belief_1: reg logitbelief bad good
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if Highx10==0 & Highx100==0 & getyourchoice==1 & choicebefore==1 & signalblue==1, vce(hc3) nocons
|
|
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|
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|
test good=bad
|
|
|
|
|
|
eststo bivar: appendmodels belief_all0 belief_1 belief_0
|
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|
reg logitbelief good bad goodchoicebefore badchoicebefore
|
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|
if Highx10==0 & Highx100==0 & getyourchoice==1 & signalblue==1, vce(hc3) nocons
|
|
|
test goodchoicebefore==0
|
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|
estadd scalar test_good_ifirst=r(p): bivar
|
|
|
test badchoicebefore==0
|
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|
estadd scalar test_bad_ifirst=r(p): bivar
|
|
|
summ logitbelief if Highx10==0 & Highx100==0 & getyourchoice==1 & signalblue==1
|
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|
estadd scalar obs=r(N): bivar
|
|
|
|
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|
|
|
|
eststo belief_all1: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & signalblue==1, vce(hc3) nocons
|
|
|
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|
|
eststo belief_2: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & choicebefore==0 & signalblue==1, vce(hc3) nocons
|
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|
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|
test good=bad
|
|
|
|
|
|
eststo belief_3: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & choicebefore==1 & signalblue==1, vce(hc3) nocons
|
|
|
|
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|
test good=bad
|
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|
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eststo bivar2: appendmodels belief_all1 belief_3 belief_2
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reg logitbelief good bad goodchoicebefore badchoicebefore
|
|
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if Highx10==0 & Highx100==0 & getyourchoice==0 & signalblue==1, vce(hc3) nocons
|
|
|
|
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|
test goodchoicebefore==0
|
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|
estadd scalar test_good_ifirst=r(p): bivar2
|
|
|
test badchoicebefore==0
|
|
|
estadd scalar test_bad_ifirst=r(p): bivar2
|
|
|
summ logitbelief if Highx10==0 & Highx100==0 & getyourchoice==0 & signalblue==1
|
|
|
estadd scalar obs=r(N): bivar2
|
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|
|
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|
eststo belief_all2: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==1 & updatewrong==0 & signalblue==1, vce(hc3) nocons
|
|
|
test good=bad
|
|
|
|
|
|
eststo belief_4: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==1 & updatewrong==0 & choicebefore==0 & signalblue==1, vce(hc3) nocons
|
|
|
test good=bad
|
|
|
|
|
|
eststo belief_5: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==1 & updatewrong==0 & choicebefore==1 & signalblue==1, vce(hc3) nocons
|
|
|
test good=bad
|
|
|
|
|
|
|
|
|
eststo bivar3: appendmodels belief_all2 belief_5 belief_4
|
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|
|
reg logitbelief good bad goodchoicebefore badchoicebefore
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==1 & updatewrong==0 & signalblue==1, vce(hc3) nocons
|
|
|
|
|
|
test goodchoicebefore==0
|
|
|
estadd scalar test_good_ifirst=r(p): bivar3
|
|
|
test badchoicebefore==0
|
|
|
estadd scalar test_bad_ifirst=r(p): bivar3
|
|
|
summ logitbelief if Highx10==0 & Highx100==0 & getyourchoice==1 & updatewrong==0 & signalblue==1
|
|
|
estadd scalar obs=r(N): bivar3
|
|
|
|
|
|
|
|
|
|
|
|
eststo belief_all3: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & updatewrong==0 & signalblue==0, vce(hc3) nocons
|
|
|
test good=bad
|
|
|
|
|
|
eststo belief_6: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & updatewrong==0 & choicebefore==0 & signalblue==1, vce(hc3) nocons
|
|
|
test good=bad
|
|
|
|
|
|
eststo belief_7: reg logitbelief bad good
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & updatewrong==0 & choicebefore==1 & signalblue==1, vce(hc3) nocons
|
|
|
test good=bad
|
|
|
|
|
|
eststo bivar4: appendmodels belief_all3 belief_7 belief_6
|
|
|
|
|
|
reg logitbelief good bad goodchoicebefore badchoicebefore
|
|
|
if Highx10==0 & Highx100==0 & getyourchoice==0 & updatewrong==0 & signalblue==1, robust nocons
|
|
|
|
|
|
test goodchoicebefore==0
|
|
|
estadd scalar test_good_ifirst=r(p): bivar4
|
|
|
test badchoicebefore==0
|
|
|
estadd scalar test_bad_ifirst=r(p): bivar4
|
|
|
summ logitbelief if Highx10==0 & Highx100==0 & getyourchoice==0 & updatewrong==0 & signalblue==1
|
|
|
estadd scalar obs=r(N): bivar4
|
|
|
|
|
|
|
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|
local panel "\begin{table}[h!]" "\centering" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{9}{10}\selectfont" "\caption{Belief Updating when Signal is \$2}" "\begin{tabular}{l*{4}{c}}\hline"
|
|
|
local dv "&\multicolumn{4}{c}{\textbf{Log-odds Belief}} \\"
|
|
|
local pref "\multicolumn{1}{r}{\textit{Assignment:}}&\multicolumn{1}{c}{Assigned Pref.}&\multicolumn{1}{c}{Not Assigned Pref.}&\multicolumn{1}{c}{Assigned Pref.}&\multicolumn{1}{c}{Not Assigned Pref.}\\ "
|
|
|
local groups "\multicolumn{1}{r}{\textit{Data:}} &\multicolumn{2}{c}{All}&\multicolumn{2}{c}{Excl. update in wrong direction} \\\hline & & & & \\"
|
|
|
|
|
|
esttab bivar bivar2 bivar3 bivar4 using "${appendix}beliefs_pref_assign_ball2.tex", se r2 replace nolines cells(b(star fmt(3)) se(par fmt(3)))
|
|
|
coeflabel (bad "$\beta_C$" good "$\beta_{NC}$")
|
|
|
order (bad good)
|
|
|
star(* 0.10 ** 0.05 *** 0.01)
|
|
|
mlabels(none) label collabels(none)
|
|
|
stats(obs test_bad_ifirst test_good_ifirst, fmt(%9.0g %9.3f %9.3f %9.3f %9.3f) labels("Observations" "$\beta^{f=q}_C=\beta^{f=i}_{C}$" "$\beta^{f=q}_{NC}=\beta^{f=i}_{NC}$" ))
|
|
|
addnotes("Note: * p$<$.10; ** p$<$.05; *** p$<$.01") posthead("`dv'" "`pref'" "`groups'") prehead("`panel'")
|
|
|
postfoot("\hline" "\end{tabular}%" "\captionsetup{width=0.8\textwidth}"
|
|
|
"\caption*{\footnotesize \textit{Notes:} The outcome in all regressions is the log belief ratio, when the advisors sees a \$2 ball for product $B$. $\beta^f_C$ and $\beta^f_{NC}$ are the estimated effects of the log likelihood ratio for conflict and no conflict signals, respectively, for advisors who prefer order $f$ ($f=i$ indicates a preference to see the incentive first, and $f=q$ indicates a preference to see quality first). Columns(1) and (2) include all advisors. Columns (3) and (4) exclude advisors who updated in the wrong direction. Columns (1) and (3) include only advisors who were assigned their preference, while columns (2) and (4) include only advisors who were not assigned their preference. Robust standard errors (HC3) in parentheses.\sym{*} \(p<0.10\), \sym{**} \(p<0.05\), \sym{***} \(p<0.01\).}" "\label{tab:beliefs2}" "\end{table}")
|
|
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|
|
|
|
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|
tab beliefinbin
|
|
|
|
|
|
tab correctdirbin
|
|
|
est clear
|
|
|
|
|
|
eststo: reg beliefcorrect choicebefore choicebeforenoconflict
|
|
|
noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==1, vce(hc3)
|
|
|
|
|
|
eststo: reg beliefcorrect choicebefore choicebeforenoconflict
|
|
|
noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==0, vce(hc3)
|
|
|
|
|
|
eststo: reg beliefcorrect choicebefore choicebeforenoconflict
|
|
|
noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==1 & correctdirbin==1, vce(hc3)
|
|
|
|
|
|
eststo: reg beliefcorrect choicebefore choicebeforenoconflict
|
|
|
noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==0 & correctdirbin==1, vce(hc3)
|
|
|
|
|
|
local panel "\begin{table}[h!]" "\centering" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{9}{10}\selectfont" "\caption{Belief Updating: Correct Choice}" "\begin{tabular}{l*{4}{c}}\hline"
|
|
|
local dv "&\multicolumn{4}{c}{\textbf{Belief Correct}} \\"
|
|
|
local pref "\multicolumn{1}{r}{\textit{Assignment:}}&\multicolumn{1}{c}{Assigned Pref.}&\multicolumn{1}{c}{Not Assigned Pref.}&\multicolumn{1}{c}{Assigned Pref.}&\multicolumn{1}{c}{Not Assigned Pref.}\\ "
|
|
|
local groups "\multicolumn{1}{r}{\textit{Data:}} &\multicolumn{2}{c}{All}&\multicolumn{2}{c}{Excl. update in wrong direction} \\\hline & & & & \\"
|
|
|
|
|
|
|
|
|
esttab using "${appendix}beliefcorrect.tex", se r2 replace cells(b(star fmt(3)) se(par fmt(3)))
|
|
|
coeflabel (noconflict "No Conflict" professionalsfree "Choice Free--Professionals" seeincentivecostly "See Incentive First Costly" seequalitycostly "Assess Quality First Costly" wave2 "Wave 2" wave3 "Wave 3" notgetyourchoice "Not Assigned Preference"
|
|
|
female "Female" age "Age" selfish "Selfish" professionalscloudresearch "Professionals x Cloudresearch" selfishseeincentivecostly "Selfish X See Incentive First Costly" selfishseequalitycostly "Selfish X See Quality First Costly"
|
|
|
incentiveshigh "Probabilistic Incentive Mturk" incentiveleft "Order" incentiveshigh_incentiveleft "Probabilistic Incentive X Order"
|
|
|
incentiveB "Incentive for B" choicebefore "Prefer to See Incentive First"
|
|
|
choicebeforenoconflict "No Conflict X Prefer to See Incentive First"
|
|
|
choicebeforenotgetyourchoice "Prefer to See Incentive First X Not Assigned Pref."
|
|
|
notgetyourchoicenoconflict "No Conflict X Not Assigned Preference")
|
|
|
order (choicebefore noconflict choicebeforenoconflict seeincentivecostly seequalitycostly professionalsfree incentiveB female age wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch )
|
|
|
star(* 0.10 ** 0.05 *** 0.01) title("Belief Updating: Choice of Correct Belief Bin")
|
|
|
drop(professionalsfree wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch)
|
|
|
mlabels(none) label collabels(none) substitute(" 0.000 " " " " (.) " " ")
|
|
|
posthead("`dv'" "`groups'") prehead("`panel'") nolines postfoot("\hline" "\end{tabular}%" "\captionsetup{width=\textwidth}" "\caption*{\footnotesize \textit{Notes:} This table displays the estimated coefficients from linear probability models on the advisor's beliefs that the quality of product B is low measured via their choice of one out of 10 possible belief bins (ranging from 0 to 100, in steps of 10). Column (1) focuses on individuals who are assigned their preference, while column (2) focuses on individuals who are not assigned their preference. Columns (3) and (4) exclude individuals who chose a bin that is consistent with updating in the incorrect direction. Prefer to See Incentive First is an indicator of the advisor's preference, and Not Assigned Preference is an indicator for not receiving the preferred order. No Conflict is an indicator for the cases in which the signal of quality is not in conflict with the advisor's commission. Choice Free-Professionals, See Incentive First Costly and Assess Quality First Costly are indicator variables that take value 1 in the respective treatment, 0 otherwise. All regression models include controls for each wave of the experiment, whether incentives were probabilistic, the position of the products on the screen and the interaction between these two variables. Robust standard errors (HC3) in parentheses. * p$<$.10; ** p$<$.05; *** p$<$.01}" "\label{tab:beliefcorrect}" "\end{table}")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
est clear
|
|
|
|
|
|
eststo: reg belief_prior choicebefore choicebeforenoconflict
|
|
|
noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==1, vce(hc3)
|
|
|
|
|
|
eststo: reg belief_prior choicebefore choicebeforenoconflict
|
|
|
noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==0, vce(hc3)
|
|
|
|
|
|
eststo: reg belief_prior choicebefore choicebeforenoconflict
|
|
|
noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==1 & correctdirbin==1, vce(hc3)
|
|
|
|
|
|
eststo: reg belief_prior choicebefore choicebeforenoconflict
|
|
|
noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==0 & correctdirbin==1, vce(hc3)
|
|
|
|
|
|
local panel "\begin{table}[h!]" "\centering" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{9}{10}\selectfont" "\caption{Belief Updating: Likelihood of Sticking to the Prior Belief - Incentivized Elicitation}" "\begin{tabular}{l*{4}{c}}\hline"
|
|
|
local dv "&\multicolumn{4}{c}{\textbf{Belief Bin Containing the Prior of 50\%}} \\"
|
|
|
local pref "\multicolumn{1}{r}{\textit{Assignment:}}&\multicolumn{1}{c}{Assigned Pref.}&\multicolumn{1}{c}{Not Assigned Pref.}&\multicolumn{1}{c}{Assigned Pref.}&\multicolumn{1}{c}{Not Assigned Pref.}\\ "
|
|
|
local groups "\multicolumn{1}{r}{\textit{Data:}} &\multicolumn{2}{c}{All}&\multicolumn{2}{c}{Excl. update in wrong direction} \\\hline & & & & \\"
|
|
|
|
|
|
|
|
|
esttab using "${appendix}beliefprior.tex", se r2 replace cells(b(star fmt(3)) se(par fmt(3)))
|
|
|
coeflabel (noconflict "No Conflict" professionalsfree "Choice Free--Professionals" seeincentivecostly "See Incentive First Costly" seequalitycostly "Assess Quality First Costly" wave2 "Wave 2" wave3 "Wave 3" notgetyourchoice "Not Assigned Preference"
|
|
|
female "Female" age "Age" selfish "Selfish" professionalscloudresearch "Professionals x Cloudresearch" selfishseeincentivecostly "Selfish X See Incentive First Costly" selfishseequalitycostly "Selfish X See Quality First Costly"
|
|
|
incentiveshigh "Probabilistic Incentive Mturk" incentiveleft "Order" incentiveshigh_incentiveleft "Probabilistic Incentive X Order"
|
|
|
incentiveB "Incentive for B" choicebefore "Prefer to See Incentive First"
|
|
|
choicebeforenoconflict "No Conflict X Prefer to See Incentive First"
|
|
|
choicebeforenotgetyourchoice "Prefer to See Incentive First X Not Assigned Pref."
|
|
|
notgetyourchoicenoconflict "No Conflict X Not Assigned Preference")
|
|
|
order (choicebefore noconflict choicebeforenoconflict seeincentivecostly seequalitycostly professionalsfree incentiveB female age wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch )
|
|
|
star(* 0.10 ** 0.05 *** 0.01) title("Belief Updating: Likelihood to Stick to the Prior Belief")
|
|
|
drop(professionalsfree wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch)
|
|
|
mlabels(none) label collabels(none) substitute(" 0.000 " " " " (.) " " ")
|
|
|
posthead("`dv'" "`groups'") prehead("`panel'") nolines postfoot("\hline" "\end{tabular}%" "\captionsetup{width=\textwidth}" "\caption*{\footnotesize \textit{Notes:} This table displays the estimated coefficients from linear probability models on the advisor's likelihood to stick to the bin containing the prior belief (50\%) in the incentivized belief elicitation. Column (1) focuses on individuals who are assigned their preference, while column (2) focuses on individuals who are not assigned their preference. Columns (3) and (4) exclude individuals who chose a bin that is consistent with updating in the incorrect direction. Prefer to See Incentive First is an indicator of the advisor's preference, and Not Assigned Preference is an indicator for not receiving the preferred order. No Conflict is an indicator for the cases in which the signal of quality is not in conflict with the advisor's commission. Choice Free-Professionals, See Incentive First Costly and Assess Quality First Costly are indicator variables that take value 1 in the respective treatment, 0 otherwise. All regression models include controls for each wave of the experiment, whether incentives were probabilistic, the position of the products on the screen and the interaction between these two variables. Robust standard errors (HC3) in parentheses. * p$<$.10; ** p$<$.05; *** p$<$.01}" "\label{tab:beliefcorrect}" "\end{table}")
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
est clear
|
|
|
|
|
|
eststo: reg belief_prior_continuos choicebefore choicebeforenoconflict
|
|
|
noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==1, vce(hc3)
|
|
|
|
|
|
eststo: reg belief_prior_continuos choicebefore choicebeforenoconflict
|
|
|
noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==0, vce(hc3)
|
|
|
|
|
|
eststo: reg belief_prior_continuos choicebefore choicebeforenoconflict
|
|
|
noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==1 & updatewrong==0, vce(hc3)
|
|
|
|
|
|
eststo: reg belief_prior_continuos choicebefore choicebeforenoconflict
|
|
|
noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==0 & updatewrong==0, vce(hc3)
|
|
|
|
|
|
local panel "\begin{table}[h!]" "\centering" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{9}{10}\selectfont" "\caption{Belief Updating: Likelihood of Sticking to the Prior Belief - Continuous Elicitation}" "\begin{tabular}{l*{4}{c}}\hline"
|
|
|
local dv "&\multicolumn{4}{c}{\textbf{Belief at Prior of 50\%}} \\"
|
|
|
local pref "\multicolumn{1}{r}{\textit{Assignment:}}&\multicolumn{1}{c}{Assigned Pref.}&\multicolumn{1}{c}{Not Assigned Pref.}&\multicolumn{1}{c}{Assigned Pref.}&\multicolumn{1}{c}{Not Assigned Pref.}\\ "
|
|
|
local groups "\multicolumn{1}{r}{\textit{Data:}} &\multicolumn{2}{c}{All}&\multicolumn{2}{c}{Excl. update in wrong direction} \\\hline & & & & \\"
|
|
|
|
|
|
|
|
|
esttab using "${appendix}beliefprior_continuous.tex", se r2 replace cells(b(star fmt(3)) se(par fmt(3)))
|
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coeflabel (noconflict "No Conflict" professionalsfree "Choice Free--Professionals" seeincentivecostly "See Incentive First Costly" seequalitycostly "Assess Quality First Costly" wave2 "Wave 2" wave3 "Wave 3" notgetyourchoice "Not Assigned Preference"
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female "Female" age "Age" selfish "Selfish" professionalscloudresearch "Professionals x Cloudresearch" selfishseeincentivecostly "Selfish X See Incentive First Costly" selfishseequalitycostly "Selfish X See Quality First Costly"
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incentiveshigh "Probabilistic Incentive Mturk" incentiveleft "Order" incentiveshigh_incentiveleft "Probabilistic Incentive X Order"
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incentiveB "Incentive for B" choicebefore "Prefer to See Incentive First"
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choicebeforenoconflict "No Conflict X Prefer to See Incentive First"
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choicebeforenotgetyourchoice "Prefer to See Incentive First X Not Assigned Pref."
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notgetyourchoicenoconflict "No Conflict X Not Assigned Preference")
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order (choicebefore noconflict choicebeforenoconflict seeincentivecostly seequalitycostly professionalsfree incentiveB female age wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch )
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star(* 0.10 ** 0.05 *** 0.01) title("Belief Updating: Likelihood to Stick to the Prior Belief")
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drop(professionalsfree wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch)
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mlabels(none) label collabels(none) substitute(" 0.000 " " " " (.) " " ")
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posthead("`dv'" "`groups'") prehead("`panel'") nolines postfoot("\hline" "\end{tabular}%" "\captionsetup{width=\textwidth}" "\caption*{\footnotesize \textit{Notes:} This table displays the estimated coefficients from linear probability models on the advisor's likelihood to stick to the bin containing the prior belief (50\%) in the incentivized belief elicitation. Column (1) focuses on individuals who are assigned their preference, while column (2) focuses on individuals who are not assigned their preference. Columns (3) and (4) exclude individuals who chose a bin that is consistent with updating in the incorrect direction. Prefer to See Incentive First is an indicator of the advisor's preference, and Not Assigned Preference is an indicator for not receiving the preferred order. No Conflict is an indicator for the cases in which the signal of quality is not in conflict with the advisor's commission. Choice Free-Professionals, See Incentive First Costly and Assess Quality First Costly are indicator variables that take value 1 in the respective treatment, 0 otherwise. All regression models include controls for each wave of the experiment, whether incentives were probabilistic, the position of the products on the screen and the interaction between these two variables. Robust standard errors (HC3) in parentheses. * p$<$.10; ** p$<$.05; *** p$<$.01}" "\label{tab:beliefcorrect}" "\end{table}")
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reg recommendincentive i.treatment##i.getbefore incentiveB $covariates2
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if choicebefore==1 & conflict==1 & Highx10==0 & Highx100==0, vce(hc3)
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margins i.getbefore if treatment==0, atmeans
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reg recommendincentive i.treatment##i.getbefore incentiveB $covariates2
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if choicebefore==0 & conflict==1 & Highx10==0 & Highx100==0, vce(hc3)
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margins i.getbefore if treatment==0, atmeans
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di 0.45*.7115466 + 0.55*.8104721
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di 0.45*.5659195 + 0.55*.6759732
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est clear
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eststo:reg choicebefore $covariates2 Highx10 Highx100, vce(hc3)
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eststo:reg choicebefore $covariates2 Highx10 Highx100 stdalpha, vce(hc3)
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eststo:reg choicebefore $covariates2 Highx10 Highx100 stdalpha selfishseeincentivecostly selfishseequalitycostly, vce(hc3)
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local panel "\begin{table}[h!]" "\centering" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{10}{11}\selectfont" "\caption{Preference for Information Order: Including Incentives Treatments}" "\begin{tabular}{l*{3}{c}} \hline"
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local dv "$\ \ \ \ \ \ \ \ \ \ \ \ \ \ $ &\multicolumn{3}{c}{\textbf{Prefer to See Incentive First}} \\\hline & & & \\"
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esttab using "${appendix}Choice_Preferences_Including_Stakes.tex",
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se r2 replace lines cells(b(star fmt(2)) se(par fmt(2)))
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coeflabel (professionalsfree "Choice Free -- Professionals $ \ \ \ \ \ \ \ $" seeincentivecostly "See Incentive First Costly " seequalitycostly "Assess Quality First Costly" wave2 "Wave 2" wave3 "Wave 3"
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female "Female" age "Age" stdalpha "Selfishness" professionalscloudresearch "Professionals x Cloudresearch" selfishseeincentivecostly "See Incentive First Costly X Selfishness " selfishseequalitycostly "See Quality First Costly X Selfishness "
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incentiveshigh "Probabilistic Incentive Mturk" incentiveleft
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"Order" incentiveshigh_incentiveleft "Probabilistic Incentive X Order"
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Highx10 "High Stakes (10-fold incentives)"
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Highx100 "High Stakes (100-fold incentives)")
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order (seeincentivecostly seequalitycostly professionalsfree Highx10 Highx100 stdalpha selfishseeincentivecostly selfishseequalitycostly female age wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch )
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star(* 0.10 ** 0.05 *** 0.01) collabels(none)
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drop(wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch)
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nomtitle label substitute(" 0.000 " " " " (.) " " ")
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prehead("`panel'") posthead("`dv'") postfoot("\hline" "\end{tabular}%" "\captionsetup{width=0.75\textwidth}" "\caption*{\footnotesize \textit{Notes:} This table displays the estimated coefficients from linear probability models on the preference to see the incentive first. See Incentive First Costly and Assess Quality First Costly are indicator variables that take value 1 in the respective treatment, 0 otherwise. Selfishness was elicited at the end of the experiment, using a multiple price list (MPL) with 5 decisions. The variable is a standardized measure of the number of times the advisor chose to recommend the incentivized product in the MPL task. The regression models in columns (2) and (3) include individual controls for the advisor's gender and age, each wave of the experiment, whether incentives were probabilistic, the position of the products on the screen and the interaction between these two variables. Robust standard errors (HC3) in parentheses. * p$<$.10; ** p$<$.05; *** p$<$.01}" "\label{tab:demand_highincentives}" "\end{table}")
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foreach var in choicebefore choicebeforenoconflict noconflict
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notgetyourchoice choicebeforenotgetyourchoice notgetyourchoicenoconflict{
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g `var'x10=`var'*Highx10
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g `var'x100=`var'*Highx100
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}
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est clear
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eststo: reg recommendincentive choicebefore choicebeforenoconflict
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noconflict Highx10 Highx100
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choicebeforex10 choicebeforenoconflictx10 noconflictx10
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choicebeforex100 choicebeforenoconflictx100 noconflictx100
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incentiveB $covariates2 if getyourchoice==1, vce(hc3)
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eststo: reg recommendincentive choicebefore choicebeforenoconflict
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noconflict Highx10 Highx100
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choicebeforex10 choicebeforenoconflictx10 noconflictx10
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choicebeforex100 choicebeforenoconflictx100 noconflictx100
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incentiveB $covariates2 if getyourchoice==0, vce(hc3)
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eststo: reg recommendincentive choicebefore choicebeforenoconflict
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noconflict notgetyourchoice choicebeforenotgetyourchoice
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notgetyourchoicenoconflict Highx10 Highx100
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choicebeforex10 choicebeforenoconflictx10 noconflictx10
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choicebeforex100 choicebeforenoconflictx100 noconflictx100
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notgetyourchoicex10 choicebeforenotgetyourchoicex10
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notgetyourchoicenoconflictx10
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notgetyourchoicex100 choicebeforenotgetyourchoicex100
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notgetyourchoicenoconflictx100
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incentiveB $covariates2
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, vce(hc3)
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local panel "\begin{table}[h!]" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{10}{10}\selectfont" "\caption{Advisor Recommendations: Including Incentives Treatments}" "\begin{tabular}{l*{3}{c}} \hline"
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local dv "&\multicolumn{3}{c}{\textbf{Recommend incentivized product}} \\"
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local groups "\multicolumn{1}{r}{\textit{Assignment:}}&\multicolumn{1}{c}{Assigned Pref.}&\multicolumn{1}{c}{Not Assigned Pref.}&\multicolumn{1}{c}{Both} \\\hline & & & & \\ "
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local conflict "&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict}&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict}&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict} \\ \hline & & & & & & \\"
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esttab using "${appendix}Choice_Recommendations_IncludingStakes.tex", se r2 replace cells(b(star fmt(3)) se(par fmt(3)))
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coeflabel (noconflict "No Conflict" getbefore "Assigned to See Incentive First" getbeforenoconflict "Assigned to See Incentive First X No Conflict" professionalsfree "Choice Free--Professionals" seeincentivecostly "See Incentive First Costly" seequalitycostly "Assess Quality First Costly" wave2 "Wave 2" wave3 "Wave 3" notgetyourchoice "Not Assigned Preference"
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female "Female" age "Age" selfish "Selfish" professionalscloudresearch "Professionals x Cloudresearch" selfishseeincentivecostly "Selfish X See Incentive First Costly" selfishseequalitycostly "Selfish X See Quality First Costly"
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incentiveshigh "Probabilistic Incentive Mturk" incentiveleft "Order" incentiveshigh_incentiveleft "Probabilistic Incentive X Order"
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incentiveB "Incentive for B" choicebefore "Prefer to See Incentive First"
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choicebeforenoconflict "No Conflict X Prefer to See Incentive First"
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choicebeforenotgetyourchoice "Prefer to See Incentive First X Not Assigned Pref."
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Highx10 "High Stakes (10-fold incentives)"
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Highx100 "High Stakes (100-fold incentives)"
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notgetyourchoicenoconflict "No Conflict X Not Assigned Preference"
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selfishchoicebefore "Prefer to See Incentive First X Selfish"
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selfishnotgetyourchoice "Not Assigned Preference X Selfish"
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choicebeforex10 "Prefer to See Incentive First X High Stakes (10-fold)"
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choicebeforex100 "Prefer to See Incentive First X High Stakes (100-fold)")
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order (choicebefore notgetyourchoice choicebeforenotgetyourchoice noconflict choicebeforenoconflict notgetyourchoicenoconflict seeincentivecostly seequalitycostly professionalsfree incentiveB female age wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch )
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star(* 0.10 ** 0.05 *** 0.01) title("Advisor Recommendations")
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drop(professionalsfree wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch
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choicebeforenoconflictx10 noconflictx10
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choicebeforenoconflictx100 noconflictx100
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notgetyourchoicex10 choicebeforenotgetyourchoicex10
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notgetyourchoicenoconflictx10
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notgetyourchoicex100 choicebeforenotgetyourchoicex100
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notgetyourchoicenoconflictx100)
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mlabels(none) label collabels(none) substitute(" 0.000 " " " " (.) " " ")
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posthead("`dv'" "`groups'") prehead("`panel'") nolines postfoot("\hline" "\end{tabular}%" "\captionsetup{width=\textwidth}" "\caption*{\footnotesize \textit{Notes:} This table displays the estimated coefficients from linear probability models on the advisor's decision to recommend the incentivized option. Column (1) focuses on individuals who are assigned their preference, while column (2) focuses on individuals who are not assigned their preference. Both groups are merged in column (3). Prefer to See Incentive First is an indicator of the advisor's preference, and Not Assigned Preference is an indicator for not receiving the preferred order. No Conflict is an indicator for the cases in which the signal of quality is not in conflict with the advisor's commission. Choice Free-Professionals, See Incentive First Costly and Assess Quality First Costly are indicator variables that take value 1 in the respective treatment, 0 otherwise. All regression models include controls for each wave of the experiment, whether incentives were probabilistic, the position of the products on the screen and the interaction between these two variables. Robust standard errors (HC3) in parentheses. * p$<$.10; ** p$<$.05; *** p$<$.01}" "\label{tab:recommendations_highincentives}" "\end{table}")
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clear
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u "${data}choice_experiments.dta"
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drop if study!=1 & alphavaluefinal==.
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global covariates "wave2 wave3 professionalscloudresearch incentiveshigh##incentiveleft age female"
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global covariates2 "professionalsfree seeincentivecostly seequalitycostly wave2 wave3 professionalscloudresearch incentiveshigh incentiveleft incentiveshigh_incentiveleft age female"
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tab alphavaluefinal if Highx10==0 | Highx100==0, m
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est clear
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eststo:reg choicebefore $covariates2 if Highx10==0 & Highx100==0 & alphavaluefinal!=., vce(hc3)
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eststo:reg choicebefore $covariates2 if Highx10==0 & Highx100==0, vce(hc3)
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local panel "\begin{table}[h!]" "\centering" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{10}{11}\selectfont" "\caption{Preference for Information Order---Including Inattentive}" "\begin{tabular}{l*{3}{c}} \hline"
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local dv "$\ \ \ \ \ \ \ \ \ \ \ \ \ \ $ &\multicolumn{3}{c}{\textbf{Prefer to See Incentive First}} \\\hline & & & \\"
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local pref "\multicolumn{1}{r}{\textit{Sample:}}&\multicolumn{1}{c}{Main Sample}&\multicolumn{1}{c}{Including Inattentive}\\ \hline & & & \\"
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esttab using "${appendix}Choice_Demand_withInattentive.tex",
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se r2 replace nolines cells(b(star fmt(3)) se(par fmt(3)))
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coeflabel (professionalsfree "Choice Free -- Professionals $ \ \ \ \ \ \ \ $" seeincentivecostly "See Incentive First Costly " seequalitycostly "Assess Quality First Costly" wave2 "Wave 2" wave3 "Wave 3"
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female "Female" age "Age" stdalpha "Selfishness" professionalscloudresearch "Professionals x Cloudresearch" selfishseeincentivecostly "See Incentive First Costly X Selfish " selfishseequalitycostly "See Quality First Costly X Selfish "
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incentiveshigh "Probabilistic Incentive Mturk" incentiveleft "Order" incentiveshigh_incentiveleft "Probabilistic Incentive X Order")
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order (seeincentivecostly seequalitycostly professionalsfree stdalpha selfishseeincentivecostly selfishseequalitycostly female age wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch )
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star(* 0.10 ** 0.05 *** 0.01) collabels(none)
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drop(wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch stdalpha selfishseeincentivecostly selfishseequalitycostly)
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nomtitle label substitute(" 0.000 " " " " (.) " " ")
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|
prehead("`panel'") posthead("`dv'") postfoot("\hline" "\end{tabular}%" "\captionsetup{width=0.75\textwidth}" "\caption*{\footnotesize Note: This table displays the estimated coefficients from linear probability models on the advisor's preference to see the incentive first. Column (1) focuses on individuals who are assigned their preference, while column (2) focuses on individuals who are not assigned their preference. Both groups are merged in column (3). Prefer to See Incentive First is an indicator of the advisor's preference, and Not Assigned Preference is an indicator for not receiving the preferred order. No Conflict is an indicator for the cases in which the signal of quality is not in conflict with the advisor's commission. See Incentive First Costly and Assess Quality First Costly are indicator variables that take value 1 in the respective treatment, 0 otherwise. All regression models include individual controls for the advisor's gender and age, each wave of the experiment, whether incentives were probabilistic, the position of the products on the screen and the interaction between these two variables. Robust standard errors (HC3) in parentheses. * p$<$.10; ** p$<$.05; *** p$<$.01}" "\label{tab:demand_inattentive}" "\end{table}")
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est clear
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eststo: reg recommendincentive choicebefore choicebeforenoconflict
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noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==1, vce(hc3)
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test choicebefore+choicebeforenoconflict==0
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eststo: reg recommendincentive choicebefore choicebeforenoconflict
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noconflict incentiveB $covariates2 if Highx10==0 & Highx100==0 & getyourchoice==0, vce(hc3)
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eststo: reg recommendincentive choicebefore choicebeforenoconflict
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noconflict notgetyourchoice choicebeforenotgetyourchoice notgetyourchoicenoconflict incentiveB $covariates2
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if Highx10==0 & Highx100==0, vce(hc3)
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test choicebefore+choicebeforenoconflict==0
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test choicebefore+notgetyourchoice+choicebeforenotgetyourchoice==0
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test notgetyourchoice+choicebeforenotgetyourchoice==0
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lincom notgetyourchoice+choicebeforenotgetyourchoice
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local panel "\begin{table}[h!]" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{10}{10}\selectfont" "\caption{Advisor Recommendations---Including Inattentive}" "\hspace{-0.5cm}" "\begin{tabular}{l*{3}{c}} \hline"
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local dv "&\multicolumn{3}{c}{\textbf{Recommend incentivized product}} \\"
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local groups "\multicolumn{1}{r}{\textit{Assignment:}}&\multicolumn{1}{c}{Assigned Pref.}&\multicolumn{1}{c}{Not Assigned Pref.}&\multicolumn{1}{c}{Both} \\\hline & & & \\ "
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local conflict "&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict}&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict}&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict} \\ \hline & & & & & & \\"
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esttab using "${appendix}Choice_Recommendations_WithInattentive.tex", se r2 replace cells(b(star fmt(3)) se(par fmt(3)))
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coeflabel (noconflict "No Conflict" getbefore "Assigned to See Incentive First" getbeforenoconflict "Assigned to See Incentive First X No Conflict" professionalsfree "Choice Free--Professionals" seeincentivecostly "See Incentive First Costly" seequalitycostly "Assess Quality First Costly" wave2 "Wave 2" wave3 "Wave 3" notgetyourchoice "Not Assigned Preference"
|
|
|
female "Female" age "Age" stdalpha "Selfishness" professionalscloudresearch "Professionals x Cloudresearch" selfishseeincentivecostly "Selfish X See Incentive First Costly" selfishseequalitycostly "Selfish X See Quality First Costly"
|
|
|
incentiveshigh "Probabilistic Incentive Mturk" incentiveleft "Order" incentiveshigh_incentiveleft "Probabilistic Incentive X Order"
|
|
|
incentiveB "Incentive for B" choicebefore "Prefer to See Incentive First"
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|
choicebeforenoconflict "No Conflict X Prefer to See Incentive First"
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|
choicebeforenotgetyourchoice "Prefer to See Incentive First X Not Assigned Preference"
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notgetyourchoicenoconflict "No Conflict X Not Assigned Preference")
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|
order (choicebefore notgetyourchoice choicebeforenotgetyourchoice noconflict choicebeforenoconflict notgetyourchoicenoconflict professionalsfree seeincentivecostly seequalitycostly incentiveB selfish female age wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch )
|
|
|
star(* 0.10 ** 0.05 *** 0.01) title("Advisor Recommendations")
|
|
|
drop(selfish wave2 wave3 incentiveshigh incentiveleft incentiveshigh_incentiveleft professionalscloudresearch)
|
|
|
mlabels(none) label collabels(none) substitute(" 0.000 " " " " (.) " " ")
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|
|
posthead("`dv'" "`groups'") prehead("`panel'") nolines postfoot("\hline" "\end{tabular}%" "\captionsetup{width=1.1\textwidth}" "\caption*{\footnotesize Note: This table displays the estimated coefficients from linear probability models on the advisor's decision to recommend the incentivized option. Column (1) focuses on individuals who are assigned their preference, while column (2) focuses on individuals who are not assigned their preference. Both groups are merged in column (3). Prefer to See Incentive First is an indicator of the advisor's preference, and Not Assigned Preference is an indicator for not receiving the preferred order. No Conflict is an indicator for the cases in which the signal of quality is not in conflict with the advisor's commission. Choice Free-Professionals, See Incentive First Costly and Assess Quality First Costly are indicator variables that take value 1 in the respective treatment, 0 otherwise. All regression models include controls for each wave of the experiment, whether incentives were probabilistic, the position of the products on the screen and the interaction between these two variables. Robust standard errors (HC3) in parentheses. * p$<$.10; ** p$<$.05; *** p$<$.01}" "\label{tab:recommendations_inattentive}" "\end{table}")
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u "${data}stakes.dta", clear
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drop if alphavaluefinal==.
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global indiva "female age stdalpha"
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bys condition: egen meandemand=mean(choicebefore)
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bys condition: egen sddemand=sd(choicebefore)
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bys condition: egen ndemand=count(choicebefore)
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g lodemand=meandemand-1.96*(sqrt((meandemand*(1-meandemand))/ndemand))
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g hidemand=meandemand+1.96*(sqrt((meandemand*(1-meandemand))/ndemand))
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g meancommit =1
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twoway (bar meancommit conditionnum, fcolor(white) lcolor(gs10) barw(0.65))
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(bar meandemand conditionnum if conditionnum==1 , fcolor(gs10) lcolor(gs10) barw(0.65))
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(bar meandemand conditionnum if conditionnum==2 , fcolor(gs10) lcolor(gs10) barw(0.65))
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(bar meandemand conditionnum if conditionnum==3 , fcolor(gs10) lcolor(gs10) barw(0.65))
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(rcap lodemand hidemand conditionnum, lcolor(gs10))
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, ytitle("Advisor's preference") xtitle(" " "Treatment")
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graphr(c(white)) ylabel(0(0.2)1, gmax)
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xlabel(1 "Low Incentive" 2 "Intermediate Incentive" 3 "High Incentive")
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xscale(r(0.5 3.5))
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legend(order(2 1) lab(1 "Prefer to Assess Quality First")
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lab(2 "Prefer to See Incentive First") size(*0.9))
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text(0.05 1 "0.13") text(0.30 2 "0.41") text(0.3 3 "0.44")
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text(0.95 1 "0.87") text(0.95 2 "0.59") text(0.95 3 "0.56")
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graph export "${main}bar_stakes.pdf", replace
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tabstat choicebefore, by(condition) s(mean n)
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prtest choicebefore if conditionnum!=3, by(conditionnum)
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prtest choicebefore if conditionnum!=1, by(conditionnum)
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global covariates2 "commissionlow commissionhigh age female"
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est clear
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eststo:reg choicebefore $covariates2, vce(hc3)
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eststo:reg choicebefore $covariates2 stdalpha, vce(hc3)
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local panel "\begin{table}[h!]" "\centering" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{10}{11}\selectfont" "\caption{Preference for Information Order}" "\begin{tabular}{l*{2}{c}} \hline"
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local dv "$\ \ \ \ \ \ \ \ \ \ \ \ \ \ $ &\multicolumn{2}{c}{\textbf{Prefer to See Incentive First}} \\\hline & & & \\"
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esttab using "${appendix}Demand_ChoiceStakes.tex",
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se r2 replace nolines cells(b(star fmt(3)) se(par fmt(3)))
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coeflabel (commissionlow "Low Incentive $ \ \ \ \ \ \ \ $" commissionhigh "High Incentive $ \ \ \ \ \ \ \ $"
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female "Female" age "Age" stdalpha "Selfishness")
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order (commissionlow commissionhigh stdalpha female age )
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star(* 0.10 ** 0.05 *** 0.01) collabels(none)
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drop()
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nomtitle label substitute(" 0.000 " " " " (.) " " ")
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prehead("`panel'") posthead("`dv'") postfoot("\hline" "\end{tabular}%" "\captionsetup{width=0.7\textwidth}" "\caption*{\footnotesize \textit{Note:} This table displays the estimated coefficients from linear probability models on the preference to see the incentive first. Low Incentive and High Incentive are indicator variables that take value 1 in the respective treatment, 0 otherwise. Selfishness was elicited at the end of the experiment, using a multiple price list (MPL) with 5 decisions. The variable is a standardized measure of the number of times the advisor chose to recommend the incentivized product in the MPL task. Robust standard errors (HC3) in parentheses. * p$<$.10; ** p$<$.05; *** p$<$.01}" "\label{tab:demand_stakes}" "\end{table}")
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est clear
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eststo: reg recommendincentive choicebefore choicebeforenoconflict
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noconflict incentiveB $covariates2 commissionlowchoicebefore commissionhighchoicebefore if getyourchoice==1, vce(hc3)
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test choicebefore+choicebeforenoconflict==0
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eststo: reg recommendincentive choicebefore choicebeforenoconflict
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noconflict incentiveB $covariates2 commissionlowchoicebefore commissionhighchoicebefore if getyourchoice==0, vce(hc3)
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eststo: reg recommendincentive choicebefore choicebeforenoconflict
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noconflict notgetyourchoice choicebeforenotgetyourchoice notgetyourchoicenoconflict incentiveB $covariates2
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commissionlowchoicebefore commissionhighchoicebefore , vce(hc3)
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test choicebefore+choicebeforenoconflict==0
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test choicebefore+notgetyourchoice+choicebeforenotgetyourchoice==0
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test notgetyourchoice+choicebeforenotgetyourchoice==0
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lincom notgetyourchoice+choicebeforenotgetyourchoice
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local panel "\begin{table}[h!]" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{10}{10}\selectfont" "\caption{Advisor Recommendations}" "\hspace{-0.5cm}" "\begin{tabular}{l*{3}{c}} \hline"
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local dv "&\multicolumn{3}{c}{\textbf{Recommend incentivized product}} \\"
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local groups "\multicolumn{1}{r}{\textit{Assignment:}}&\multicolumn{1}{c}{Assigned Pref.}&\multicolumn{1}{c}{Not Assigned Pref.}&\multicolumn{1}{c}{Both} \\\hline & & & \\ "
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local conflict "&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict}&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict}&\multicolumn{1}{c}{Conflict}&\multicolumn{1}{c}{No Conflict} \\ \hline & & & & & & \\"
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esttab using "${appendix}recommendations_pref_assign_stakes.tex", se r2 replace cells(b(star fmt(4)) se(par fmt(4)))
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coeflabel (noconflict "No Conflict" choicebefore "Prefer to See Incentive First" getbefore "Assigned to See Incentive First" getbeforenoconflict "Assigned to See Incentive First X No Conflict" notgetyourchoice "Not Assigned Preference"
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female "Female" age "Age" commissionlow "Low Incentive" commissionhigh "High Incentive" incentiveB "Incentive for B"
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choicebeforenoconflict "No Conflict X Prefer to See Incentive First"
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choicebeforenotgetyourchoice "Prefer to See Incentive First X Not Assigned Preference"
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notgetyourchoicenoconflict "No Conflict X Not Assigned Preference"
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commissionlowchoicebefore "Low Incentive X Prefer to See Incentive First"
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commissionhighchoicebefore "High Incentive X Prefer to See Incentive First" stdalpha "Selfishness")
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order (choicebefore notgetyourchoice choicebeforenotgetyourchoice noconflict choicebeforenoconflict notgetyourchoicenoconflict commissionlow commissionlowchoicebefore commissionhigh commissionhighchoicebefore incentiveB female age)
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star(* 0.10 ** 0.05 *** 0.01) title("Advisor Recommendations")
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drop()
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mlabels(none) label collabels(none) substitute(" 0.000 " " " " (.) " " ")
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posthead("`dv'" "`groups'") prehead("`panel'") nolines postfoot("\hline" "\end{tabular}%" "\captionsetup{width=1.1\textwidth}" "\caption*{\footnotesize \textit{Notes:} This table displays the estimated coefficients from linear probability models on the advisor's decision to recommend the incentivized option. Column (1) focuses on individuals who are assigned their preference, while column (2) focuses on individuals who are not assigned their preference. Both groups are merged in column (3). Prefer to See Incentive First is an indicator of the advisor's preference, and Not Assigned Preference is an indicator for not receiving the preferred order. No Conflict is an indicator for the cases in which the signal of quality is not in conflict with the advisor's commission. Low Incentive and High Incentive are indicator variables that take value 1 in the respective treatment, 0 otherwise. Robust standard errors (HC3) in parentheses. * p$<$.10; ** p$<$.05; *** p$<$.01}" "\label{tab:recommendations_stakes}" "\end{table}")
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clear
|
|
|
u "${data}InformationArchitect.dta"
|
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tab IAAdvisor if alphavaluefinal!=.
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prtest choicebefore if alphavaluefinal!=., by(IAAdvisor)
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est clear
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eststo: reg choicebefore IAAdvisor age female if alphavaluefinal!=., vce(hc3)
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eststo: reg choicebefore IAAdvisor age female , vce(hc3)
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local panel "\begin{table}[h!]" "\centering" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{9}{10}\selectfont" "\begin{tabular}{l*{3}{c}}\hline"
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|
|
local dv "&\multicolumn{2}{c}{\textbf{DM Choice to See Incentive First}} \\"
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|
local pref "\multicolumn{1}{r}{\textit{Sample:}}&\multicolumn{1}{c}{Main Sample}&\multicolumn{1}{c}{Including Inattentive}\\ \hline & & & \\"
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|
esttab using "${appendix}IA_Preferences.tex", se r2 replace nolines cells(b(star fmt(3)) se(par fmt(3)))
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|
|
coeflabel (IAAdvisor "IA-Advisor"
|
|
|
IAClient "IA-Client" )
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|
|
order (DMAdvisor)
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|
star(* 0.10 ** 0.05 *** 0.01)
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|
mlabels(none) label collabels(none)
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drop(age female)
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addnotes("Note: * p$<$.10; ** p$<$.05; *** p$<$.01") posthead("`dv'" "`pref'" ) prehead("`panel'")
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|
postfoot("\hline" "\end{tabular}%" "\captionsetup{width=0.55\textwidth}"
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|
|
"\caption*{\footnotesize \textit{Notes:} This table displays the coefficient estimates of OLS regressions on the Information Architect's preferences to have the advisor see the incentive first for the main sample (Column 1) and the sample that includes inattentive participants who switched multiple times in the selifishness measure. DM-Advisor is an indicator for whether advisors have an incentive to receive information about their incentive first. Robust standard errors in parentheses. \sym{*} \(p<0.10\), \sym{**} \(p<0.05\), \sym{***} \(p<0.01\).}" "\label{tab:dmdemand}" "\end{table}")
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clear
|
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|
u "${data}InformationArchitect.dta"
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|
append using "${data}choice_experiments.dta"
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|
drop if study!=1 & alphavaluefinal==.
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|
tab study
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tab condition
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|
tab professionals
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gen DMAdvisor=0
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replace DMAdvisor=1 if condition=="IA-Advisor"
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drop if alphavaluefinal==.
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prtest choicebefore if professionals==0 & (condition=="ChoiceFree" & Highx10==0 & Highx100==0 )| condition=="IA-Advisor", by(condition)
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preserve
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|
u "${data}Clients_InfoArchitectsMain.dta", clear
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tab follow
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restore
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preserve
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|
u "${data}Clients_IAInfoArchitects_MPL.dta", clear
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tab follow
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restore
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preserve
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|
u "${data}Clients_IAAdvisors_MPL.dta", clear
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tab follow
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restore
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clear
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u "${data}NoChoiceSimoultaneous.dta"
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tab missingalpha
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append using "${data}nochoice.dta"
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|
save "${data}nochoice1_2_merged.dta", replace
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|
replace wave=1 if wave==.
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|
replace seeincentivefirst=1 if condition=="BeforeA" | condition=="BeforeB"
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|
replace seeincentivefirst=0 if condition=="AfterA" | condition=="AfterB"
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|
replace Together=0 if wave==1
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|
|
replace noconflict=1-conflict
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|
replace missingalpha=(alphavaluefinal==.)
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|
|
replace seeincentivefirst_noconflict= seeincentivefirst*noconflict
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|
|
gen together_noconflict= Together*noconflict
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|
|
gen wave2=(wave==2)
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|
|
drop stdalpha
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|
|
egen stdalpha=std(alphavaluefinal)
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|
est clear
|
|
|
eststo:reg recommendincentive seeincentivefirst noconflict seeincentivefirst_noconflict Together together_noconflict incentiveB female age wave2 if missingalpha==0, vce(hc3)
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|
|
eststo:reg recommendincentive seeincentivefirst noconflict seeincentivefirst_noconflict Together together_noconflict incentiveB female age stdalpha wave2 if missingalpha==0, vce(hc3)
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|
eststo:reg recommendincentive seeincentivefirst noconflict seeincentivefirst_noconflict Together together_noconflict incentiveB female age wave2 , vce(hc3)
|
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|
local panel "\begin{table}[h!]" "\centering" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{10}{11}\selectfont" "\caption{Advisor Recommendations - No Choice (Simultaneous)}" "\begin{tabular}{l*{3}{c}} \hline"
|
|
|
local dv "& & & \textbf{Including} \\" "$\ \ \ \ \ \ \ \ \ \ \ \ \ \ $ &\multicolumn{2}{c}{\textbf{Main Sample}} &\multicolumn{1}{c}{\textbf{Inattentive}} \\\hline & & & \\"
|
|
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|
|
|
esttab using "${appendix}Simultaneous.tex", se r2 replace lines cells(b(star fmt(3)) se(par fmt(3)))
|
|
|
coeflabel (seeincentivefirst "See Incentive First" noconflict "No Conflict" seeincentivefirst_noconflict "See Incentive First * No Conflict"
|
|
|
Together "Simultaneous" together_noconflict "Simultaneous X No Conflict" incentiveB "Incentive for B"
|
|
|
female "Female" age "Age" stdalpha "Selfishness" )
|
|
|
order ( seeincentivefirst noconflict seeincentivefirst_noconflict Together together_noconflict incentiveB female age stdalpha)
|
|
|
drop (wave2 female age)
|
|
|
star(* 0.10 ** 0.05 *** 0.01) collabels(none)
|
|
|
nomtitle label substitute(" 0.000 " " " " (.) " " ")
|
|
|
prehead("`panel'") posthead("`dv'") postfoot("\hline" "\end{tabular}%" "\captionsetup{width=0.75\textwidth}" "\caption*{\footnotesize Note: This table displays the estimated coefficients from linear probability models on the advisors' recommendations. See Incentive first is a binary indicator coded as 1 for participants who were randomly assigned to see the incentive first. Simultaneous is a binary indicator coded as 1 for participants who saw all infornation at the same time. Selfishness was elicited at the end of the experiment, using a multiple price list (MPL) with 5 decisions. The variable is a standardized measure of the number of times the advisor chose to recommend the incentivized product in the MPL task. The regression models in columns (1) and (2) restrict the analyses to participants who did not switch multiple times in the MPL. Column (3) includes all participants. The regression includes individual controls for the advisor's gender and age, and a binary indicator for the wave in which participants took part in the experiment. Robust standard errors (HC3) in parentheses}" "\label{tab:simultaneous}" "\end{table}")
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|
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|
|
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|
|
|
|
|
|
clear
|
|
|
u "${data}Clients_NoChoiceSimultaneousMain.dta"
|
|
|
tab follow
|
|
|
|
|
|
|
|
|
|
|
|
clear
|
|
|
u "${data}Clients_NoChoiceSimultaneousMPL.dta"
|
|
|
tab follow
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clear
|
|
|
u "${data}Choice_Deterministic.dta"
|
|
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|
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|
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|
tab alphavaluefinal, m
|
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|
tab condition if alphavaluefinal!=.
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|
tab condition choicebefore if alphavaluefinal!=., row
|
|
|
tab condition choicebefore if alphavaluefinal!=., chi2
|
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|
tab condition choicebefore , row
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|
|
tab condition choicebefore , chi2
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|
bys condition: egen recbefore_before=mean(recommendincentive) if choicebefore==1 & getbefore==1 & conflict==1
|
|
|
bys condition: egen recbefore_after=mean(recommendincentive) if choicebefore==1 & getbefore==0 & conflict==1
|
|
|
bys condition: egen recafter_before=mean(recommendincentive) if choicebefore==0 & getbefore==1 & conflict==1
|
|
|
bys condition: egen recafter_after=mean(recommendincentive) if choicebefore==0 & getbefore==0 & conflict==1
|
|
|
|
|
|
|
|
|
bys condition: egen sdrecbefore_before=sd(recommendincentive) if choicebefore==1 & getbefore==1 & conflict==1
|
|
|
bys condition: egen sdrecbefore_after=sd(recommendincentive) if choicebefore==1 & getbefore==0 & conflict==1
|
|
|
bys condition: egen sdrecafter_after=sd(recommendincentive) if choicebefore==0 & getbefore==0 & conflict==1
|
|
|
bys condition: egen sdrecafter_before=sd(recommendincentive) if choicebefore==0 & getbefore==1 & conflict==1
|
|
|
bys condition: egen nrecbefore_before=count(recommendincentive) if choicebefore==1 & getbefore==1 & conflict==1
|
|
|
bys condition: egen nrecbefore_after=count(recommendincentive) if choicebefore==1 & getbefore==0 & conflict==1
|
|
|
bys condition: egen nrecafter_after=count(recommendincentive) if choicebefore==0 & getbefore==0 & conflict==1
|
|
|
bys condition: egen nrecafter_before=count(recommendincentive) if choicebefore==0 & getbefore==1 & conflict==1
|
|
|
|
|
|
|
|
|
g lobefore_before=recbefore_before-1.96*((sdrecbefore_before)/sqrt(nrecbefore_before))
|
|
|
g hibefore_before=recbefore_before+1.96*((sdrecbefore_before)/sqrt(nrecbefore_before))
|
|
|
g lobefore_after=recbefore_after-1.96*((sdrecbefore_after)/sqrt(nrecbefore_after))
|
|
|
g hibefore_after=recbefore_after+1.96*((sdrecbefore_after)/sqrt(nrecbefore_after))
|
|
|
|
|
|
|
|
|
g loafter_after=recafter_after-1.96*((sdrecafter_after)/sqrt(nrecafter_after))
|
|
|
g loafter_before=recafter_before-1.96*((sdrecafter_before)/sqrt(nrecafter_before))
|
|
|
g hiafter_after=recafter_after+1.96*((sdrecafter_after)/sqrt(nrecafter_after))
|
|
|
g hiafter_before=recafter_before+1.96*((sdrecafter_before)/sqrt(nrecafter_before))
|
|
|
|
|
|
|
|
|
g treatnumgraph2=1 if choicebefore==1 & getbefore==1 & condition=="ChoiceFree_Probabilistic"
|
|
|
replace treatnumgraph2=1.1 if choicebefore==1 & getbefore==0 & condition=="ChoiceFree_Probabilistic"
|
|
|
replace treatnumgraph2=1.2 if choicebefore==0 & getbefore==1 & condition=="ChoiceFree_Probabilistic"
|
|
|
replace treatnumgraph2=1.3 if choicebefore==0 & getbefore==0 & condition=="ChoiceFree_Probabilistic"
|
|
|
|
|
|
replace treatnumgraph2=1.8 if choicebefore==1 & getbefore==1 & condition=="ChoiceFree_Deterministic"
|
|
|
replace treatnumgraph2=2.1 if choicebefore==0 & getbefore==0 & condition=="ChoiceFree_Deterministic"
|
|
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|
|
|
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|
|
twoway (scatteri 1 0.8 1 1.6, bcolor(gs15) recast(area))
|
|
|
(rcap lobefore_before hibefore_before treatnumgraph2, lcolor(red ) lwidth(thin))
|
|
|
(rcap loafter_after hiafter_after treatnumgraph2, lcolor( black) lwidth(thin))
|
|
|
(rcap lobefore_after hibefore_after treatnumgraph2, lcolor( red*0.3 ) lwidth(thin))
|
|
|
(rcap loafter_before hiafter_before treatnumgraph2, lcolor( black*0.3) lwidth(thin))
|
|
|
(scatter recbefore_before treatnumgraph2 if
|
|
|
condition=="ChoiceFree_Probabilistic", mcolor(red) msize(*0.8) ms(T))
|
|
|
(scatter recbefore_after treatnumgraph2 if
|
|
|
condition=="ChoiceFree_Probabilistic", mfcolor(white) msize(*0.8) mlcolor(red%50) ms(T))
|
|
|
(scatter recafter_after treatnumgraph2 if
|
|
|
condition=="ChoiceFree_Probabilistic", mcolor(black) mlcolor(black) msize(*0.8) ms(S))
|
|
|
(scatter recafter_before treatnumgraph2 if
|
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condition=="ChoiceFree_Probabilistic" , mfcolor(white) mlcolor(black%50) msize(*0.8) ms(S))
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(scatter recbefore_before treatnumgraph2 if
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condition=="ChoiceFree_Deterministic" , mcolor(red) msize(*0.8) ms(T))
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(scatter recafter_after treatnumgraph2 if
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condition=="ChoiceFree_Deterministic", mcolor(black) msize(*0.8) mlcolor(black) ms(S))
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, graphr(c(white)) plotr(c(white))
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ylabel(0(0.1)1) yscale(r(0.2 1))
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xtitle(" " "Treatment")
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xlabel(none)
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xscale(r(0.8 2.3))
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legend(order( - "{bf:Advisor Prefers to}" "{bf:See Incentive First}"
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6 7 - "{bf:Advisor Prefers to}" "{bf:Assess Quality First}" 9 8)
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lab(6 " Assigned to See Incentive First")
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lab(8 " Assigned to Assess Quality First")
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lab(7 " Assigned to Assess Quality First")
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lab(9 " Assigned to See Incentive First")
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rows(3) colfirst size(*0.9))
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text(0.15 1.15 "{bf: Choice Free}", color(black) size(*0.9))
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text(0.07 1.15 "{bf: Probabilistic}", color(black) size(*0.9))
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text(0.15 2 "{bf: Choice Free}", color(black) size(*0.9))
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text(0.07 2 "{bf: Deterministic}", color(black) size(*0.9))
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ytitle("{bf:Incentivized product recommendation}" " " )
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graph export "${appendix}Deterministic_Recommendations.png", replace
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clear
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u "${data}Choice_Deterministic.dta"
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tab condition recommendincentive if choicebefore==1 & getbefore==1 & conflict==1, row
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tab condition recommendincentive if choicebefore==1 & getbefore==0 & conflict==1, row
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tab condition recommendincentive if choicebefore==1 & getbefore==1 & conflict==0, row
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tab condition recommendincentive if choicebefore==1 & getbefore==0 & conflict==0, row
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tab condition recommendincentive if choicebefore==0 & getbefore==1 & conflict==1, row
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tab condition recommendincentive if choicebefore==0 & getbefore==0 & conflict==1, row
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tab condition recommendincentive if choicebefore==0 & getbefore==1 & conflict==0 , row
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tab condition recommendincentive if choicebefore==0 & getbefore==0 & conflict==0 , row
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est clear
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eststo:reg recommendincentive choicebefore noconflict choicebefore_noconflict Deterministic Deterministic_noconflict choicebefore_Deterministic Deterministic_choicebeforeNocon incentiveB female age if getyourchoice==1 & alphavaluefinal!=., vce(hc3)
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eststo:reg recommendincentive choicebefore noconflict choicebefore_noconflict Deterministic Deterministic_noconflict choicebefore_Deterministic Deterministic_choicebeforeNocon incentiveB female age stdalpha if getyourchoice==1 & alphavaluefinal!=., vce(hc3)
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eststo:reg recommendincentive choicebefore noconflict choicebefore_noconflict Deterministic Deterministic_noconflict choicebefore_Deterministic Deterministic_choicebeforeNocon incentiveB female age if getyourchoice==1, vce(hc3)
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local panel "\begin{table}[h!]" "\centering" "\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}" "\fontsize{10}{11}\selectfont" "\caption{Recommendations: Assigned Preferences}" "\begin{tabular}{l*{3}{c}} \hline"
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local dv " & & & \textbf{Including} \\ $\ \ \ \ \ \ \ \ \ \ \ \ \ \ $ &\multicolumn{2}{c}{\textbf{Main Sample}} &\multicolumn{1}{c}{\textbf{ Inattentve}} \\\hline & & & \\"
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esttab using "${appendix}Deterministic_Recommendations.tex",
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se r2 replace nolines cells(b(star fmt(3)) se(par fmt(3)))
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coeflabel(choicebefore "Prefer to See Incentive First" noconflict "No Conflict"
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choicebefore_noconflict "Prefer to See Incentive First * No Conflict"
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Deterministic "Deterministic" Deterministic_noconflict "Deterministic X No Conflict" choicebefore_Deterministic "Deterministic X Prefer to See Incentive First" Deterministic_choicebeforeNocon "Deterministic X Prefer to See Incentive First x No Conflict"
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female "Female" age "Age" stdalpha "Selfishness"
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incentiveB "Incentive for B")
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order (choicebefore noconflict choicebefore_noconflict Deterministic Deterministic_noconflict choicebefore_Deterministic Deterministic_choicebeforeNocon incentiveB female age stdalpha)
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star(* 0.10 ** 0.05 *** 0.01) collabels(none)
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nomtitle label substitute(" 0.000 " " " " (.) " " ")
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prehead("`panel'") posthead("`dv'") postfoot("\hline" "\end{tabular}%" "\captionsetup{width=1\textwidth}" "\caption*{\footnotesize Note: This table displays the estimated coefficients from linear probability models on the advisors' recommendations. Deterministic is a binary indicator coded as 1 for participants in the Deterministic treatment. Selfishness was elicited at the end of the experiment, using a multiple price list (MPL) with 5 decisions. The variable is a standardized measure of the number of times the advisor chose to recommend the incentivized product in the MPL task. The regression model in column (3) extends the analyses to included advisors who switched multiple times in the multiple price list eliciting selfishness. The regression includes individual controls for the advisor's gender and age. Robust standard errors (HC3) in parentheses}" "\label{tab:rec_deterministic}" "\end{table}")
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preserve
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u "${data}Clients_ChoiceDeterministic_Main.dta"
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tab follow
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restore
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preserve
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u "${data}Clients_ChoiceDeterministic_MPL.dta"
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tab follow
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restore
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clear
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u "${data}predictionsstudy.dta"
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tabstat gap if attentivenum==1, s(mean n)
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preserve
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u "${data}choice_experiments.dta"
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drop if study!=1 & alphavaluefinal==.
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tabstat recommendincentive if choicebefore==1 & conflict==1 & wave=="AMT-1" & condition=="PayBefore" & alphavaluefinal!=., by(getbefore) stats(mean sd)
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di 0.0515133*sqrt(393)
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di sqrt(0.4702^2+0.4084^2)
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di (sqrt(0.4702^2+0.4084^2))/sqrt(393)
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restore
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g meanbeh=.7894737-.6759259
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g sebeh=(sqrt(0.4702^2+0.4084^2))/sqrt(393)
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g nbeh=393
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g red=(gapred!=.)
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ttest gap, by(red)
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ttest gap=0
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cdfplot gap, opt1(lcolor(ebblue)) xlabel(-0.75(.25)0.75) graphr(c(white))
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xline(.1135478, lcolor(black)) xline(.0621875, lcolor(red))
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xtitle("Forecasted Effect of Seeing Incentive First")
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text(0.95 -0.1 "Mean forecast" "(0.06)", color(red))
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text(0.05 0.31 "Mean actual effect" "(0.11)", color(black))
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graph export "${appendix}/predictionscdf.png", replace
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ttesti 393 .1135478 .622799 288 .0621875 .2213746
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tab predictcorrect
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