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Appendix

Stata do-file for probit regressions and descriptive statistics

*instal necessary packages for data analysis

ssc install outreg

ssc install estout

* find out the variable name, format+type, variable label of a the country (var)

describe country

* find out values(in the form of labels), frequencies, percent, cummulative % of country's representatives

tab country

*country variable: its type, label of the variable, examples of values+values' labels

codebook country

*getting rid of undefined genders

drop if gender ==-2|gender ==-1

*getting data on genders on the list, frequencies, percent, cum percent (+number of total obsvs)

tab gender

*getting data the number of male/female from each country

tab country gender

*seeing how country variable is coded in the dataset

codebook country

*getting information on GEMWORK GEMWORK3 GEMOCCU

describe GEMWORK GEMWORK3 GEMOCCU

label list GEMWORK GEMWORK3 GEMOCCU

*getting rid of missing observations

drop if GEMOCCU==-2

drop if GEMWORK3==-2

drop if GEMWORK==-2

*getting information on income GEMHHINC variable

describe GEMHHINC

tab GEMHHINC

*exluding missing values

drop if GEMHHINC ==-2

*getting information on education level (GEMEDUC)

describe GEMEDUC

label list GEMEDUC

Continued appendix 1

*getting rid of missing observations

drop if GEMEDUC==-2

*getting information about following variables: knowent, opport, suskill, fearfail, equalinc, nbgoodc, nbstatus, nbmedia, easystart, nbsocent, suacts, suown, suwage, suwageyr

describe knowent opport suskill fearfail equalinc nbgoodc nbstatus nbmedia easystart nbsocent suacts suown suwage suwageyr

*getting rid of missing variables

drop if knowent==-2

drop if knowent==-1

drop if opport==-2

drop if opport==-1

drop if suskill==-2

drop if suskill==-1

drop if fearfail==-2

drop if fearfail==-1

drop if equalinc==-2

drop if equalinc==-1

drop if nbgoodc==-2

drop if nbgoodc==-1

drop if nbstatus==-2

drop if nbstatus==-1

drop if nbstatus==-1

drop if nbmedia==-2

drop if nbmedia==-1

drop if easystart==-2

drop if easystart==-1

drop if nbsocent==-2

drop if nbsocent==-1

drop if age<0

*getting rid of other observations

drop if suacts<0

drop if suown<0

drop if suwage<0

drop if suwageyr<0

*occuself as the variable showing if a person is involved in entrepreneurship

tab occuself

drop if occuself<0

*recoding as 0 and 1 instead of 1 and 2 for Yes and No

label drop occuself

recode occuself (2=0)

Continued appendix 1

label define occuself 1 "Yes" 0 "No"

label list occuself

*generating new variable for age

generate corage=0

replace corage=ln(age)+ln(age)*ln(age)

drop if missing(age)

codebook corage

*household size

describe hhsize

*getting rid of missing data

drop if nbsocent==.

drop if knowent==.

drop if opport==.

drop if suskill==.

drop if fearfail==.

drop if equalinc==.

drop if nbgoodc==.

drop if nbstatus==.

drop if nbmedia==.

drop if easystart==.

drop if nbsocent==.

drop if missing(hhsize)

*descriptive statistics

*countries

codebook country

groups country, order(h) select(10) sep(0)

*age

summarize age, detail

histogram age, bin(60) frequency normal

histogram corage, bin(60) frequency normal

*average age is GEM 39.47714. One half is older than 38 years old, the rest are younger. The youngest is 18, oldest: 93, 95, 99.

*skewed to the right, light tailed distribution (kurtosis<3)

*gender of participants

tab gender

*there were 37,378 men and 34,163 female. 71,541 in total.In percent: 52.25 are male, 47.75 female.

*gender of participants

graph bar (count), over(gender, label)

*gender distribution by involvment in TEA, opportunity TEA, and necessity TEA

Continued appendix 1

graph bar (count), over(TEAyy, label) over(gender, label)

graph bar (count), over(TEAyyOPP, label) over(gender, label)

graph bar (count), over(TEAyyNEC, label) over(gender, label)

*to begin with, we can create a graph for the distribution of people in a household and age

histogram hhsize, bin(60) normal

histogram hhsize, bin(60) frequency normal

histogram corage, bin(60) normal

histogram age, bin(60) frequency normal

*graph for each gender showing if a person is involved in TEA or not

graph bar (count), over(TEAyy, label) over(gender, label)

*graph showing the reason for being involved in TEA

graph bar if TEAMOTIV>1, over(TEAMOTIV) over(gender) cw blabel(bar) legend(on)

*graph for each gender showing if a person is involved in TEAyyOPP or not (for TEA entrepreneurs only) in % from categories

graph bar if TEAyy==1, over(TEAyyOPP) over(gender) cw blabel(bar) legend(on)

*distribution of those who are and who are not involved in TEA

graph bar if TEAyy==1, over(GEMEDUC) cw blabel(bar) legend(on)

graph bar if TEAyy==0, over(GEMEDUC) cw blabel(bar) legend(on)

*how TEAyy and TEAyyOPP depends on opport, suskill, fearfail, equalinc, nbgoodc, nbstatus, nbmedia, hhsize, GEMHHINC, knowent

graph bar if TEAyy==1, over(knowent) cw blabel(bar) legend(on)

graph bar if TEAyy==0, over(knowent) cw blabel(bar) legend(on)

graph bar if TEAyy==1, over(opport) cw blabel(bar) legend(on)

graph bar if TEAyy==0, over(opport) cw blabel(bar) legend(on)

graph bar if TEAyy==1, over(suskill) cw blabel(bar) legend(on)

graph bar if TEAyy==0, over(suskill) cw blabel(bar) legend(on)

graph bar if TEAyy==1, over(fearfail) cw blabel(bar) legend(on)

graph bar if TEAyy==0, over(fearfail) cw blabel(bar) legend(on)

graph bar if TEAyy==1, over(equalinc) cw blabel(bar) legend(on)

graph bar if TEAyy==0, over(equalinc) cw blabel(bar) legend(on)

graph bar if TEAyy==1, over(nbgoodc) cw blabel(bar) legend(on)

graph bar if TEAyy==0, over(nbgoodc) cw blabel(bar) legend(on)

graph bar if TEAyy==1, over(nbstatus) cw blabel(bar) legend(on)

graph bar if TEAyy==0, over(nbstatus) cw blabel(bar) legend(on)

graph bar if TEAyy==1, over(nbmedia) cw blabel(bar) legend(on)

graph bar if TEAyy==0, over(nbmedia) cw blabel(bar) legend(on)

graph bar if TEAyy==1, over(hhsize) cw blabel(bar) legend(on)

graph bar if TEAyy==0, over(hhsize) cw blabel(bar) legend(on)

graph bar if TEAyy==1, over(GEMHHINC) cw blabel(bar) legend(on)

graph bar if TEAyy==0, over(GEMHHINC) cw blabel(bar) legend(on)

Continued appendix 1

*graph bar, over (TEAyy) over (knowent)

*variables for each coountry (the last country does not have its dummy it has all other dummies equal to 0)

gen country_name= ctryalp

tab country_name, generate (country_dummy)

ssc install margeff, replace

*ttest, mean, variance

ttest age, by(TEAyy)

summarize gender

prtest gender, by(TEAyy)

gen gendern = gender - 1

prtest gendern, by(TEAyy)

sum gendern, by (TEAyy)

sum gendern if TEAyy==1

sum gendern if TEAyy==0

ttest hhsize, by(TEAyy)

ttest GEMEDUC, by(TEAyy)

ttest GEMHHINC, by(TEAyy)

prtest knowent, by(TEAyy)

sum knowent if TEAyy==1

sum knowent if TEAyy==0

prtest opport, by(TEAyy)

sum opport if TEAyy==1

sum opport if TEAyy==0

prtest suskill, by(TEAyy)

sum suskill if TEAyy==1

sum suskill if TEAyy==0

prtest fearfail, by(TEAyy)

sum fearfail if TEAyy==0

sum fearfail if TEAyy==1

prtest equalinc , by(TEAyy)

sum equalinc if TEAyy==1

sum equalinc if TEAyy==0

prtest nbgoodc

sum nbgoodc if TEAyy==1

sum nbgoodc if TEAyy==0

prtest nbstatus

sum nbstatus if TEAyy==1

sum nbstatus if TEAyy==0

prtest nbmedia

Continued appendix 1

sum nbmedia if TEAyy==1

sum nbmedia if TEAyy==0

prtest nbmedia

sum easystart if TEAyy==1

sum easystart if TEAyy==0

*1 First model1: TEAyy is a dependent variable, both genders are included, model fit is assessed

cor TEAyy corage gender GEMEDUC GEMHHINC hhsize knowent opport suskill fearfail equalinc nbgoodc nbstatus nbmedia easystart

probit TEAyy corage i.gender i.GEMEDUC i.GEMHHINC hhsize i.knowent i.opport i.suskill i.fearfail i.equalinc i.nbgoodc i.nbstatus i.nbmedia i.easystart, vce(robust)

lroc

margins, dydx(*)

estat classification

*2 First model2: TEAyyOPP is a dependent variable, both genders are included, model fit is assessed

cor TEAyyOPP corage gender GEMEDUC GEMHHINC hhsize knowent opport suskill fearfail equalinc nbgoodc nbstatus nbmedia easystart

probit TEAyyOPP corage i.gender i.GEMEDUC i.GEMHHINC hhsize i.knowent i.opport i.suskill i.fearfail i.equalinc i.nbgoodc i.nbstatus i.nbmedia i.easystart, vce(robust)

lroc

margins, dydx(*)

estat classification

*3 First model3: TEAyyNEC is a dependent variable, both genders are included, model fit is assessed

cor TEAyyNEC corage gender GEMEDUC GEMHHINC hhsize knowent opport suskill fearfail equalinc nbgoodc nbstatus nbmedia easystart

probit TEAyyNEC corage i.gender i.GEMEDUC i.GEMHHINC hhsize i.knowent i.opport i.suskill i.fearfail i.equalinc i.nbgoodc i.nbstatus i.nbmedia i.easystart, vce(robust)

lroc

margins, dydx(*)

estat classification

*4 Second model1: TEAyy is a dependent variable, both genders are included, model fit is assessed, country dummies are included

cor TEAyy corage gender GEMEDUC GEMHHINC hhsize knowent opport suskill fearfail equalinc nbgoodc nbstatus nbmedia easystart country_dummy1 country_dummy2 country_dummy3 country_dummy4 country_dummy5 country_dummy6 country_dummy7 country_dummy8 country_dummy9 country_dummy10 country_dummy11 country_dummy12 country_dummy13 country_dummy14 country_dummy15 country_dummy16 country_dummy17 country_dummy18 country_dummy19 country_dummy20 country_dummy21 country_dummy22 country_dummy23 country_dummy24 country_dummy25 country_dummy26 country_dummy27 country_dummy28

country_dummy29 country_dummy30 country_dummy31 country_dummy32 country_dummy33 country_dummy34 country_dummy35 country_dummy36 country_dummy37 country_dummy38

Continued appendix 1

country_dummy39 country_dummy40 country_dummy41 country_dummy42 country_dummy43 country_dummy44

probit TEAyy corage i.gender i.GEMEDUC i.GEMHHINC hhsize i.knowent i.opport i.suskill i.fearfail i.equalinc i.nbgoodc i.nbstatus i.nbmedia i.easystart i.country_dummy1 i.country_dummy2 i.country_dummy3 i.country_dummy4 i.country_dummy5 i.country_dummy6 i.country_dummy7 i.country_dummy8 i.country_dummy9 i.country_dummy10 i.country_dummy11 i.country_dummy12 i.country_dummy13 i.country_dummy14 i.country_dummy15 i.country_dummy16 i.country_dummy17 i.country_dummy18 i.country_dummy19 i.country_dummy20 i.country_dummy21 i.country_dummy22 i.country_dummy23 i.country_dummy24 i.country_dummy25 i.country_dummy26 i.country_dummy27 i.country_dummy28 i.country_dummy29 i.country_dummy30 i.country_dummy31 i.country_dummy32 i.country_dummy33 i.country_dummy34 i.country_dummy35 i.country_dummy36 i.country_dummy37 i.country_dummy38 i.country_dummy39 i.country_dummy40 i.country_dummy41 i.country_dummy42 i.country_dummy43 i.country_dummy44, vce(robust)

lroc

margins, dydx(*)

estat classification

*5 Second model2: TEAyyOPP is a dependent variable, both genders are included, model fit is assessed, country dummies are included

cor TEAyyOPP corage gender GEMEDUC GEMHHINC hhsize knowent opport suskill fearfail equalinc nbgoodc nbstatus nbmedia easystart country_dummy1 country_dummy2 country_dummy3 country_dummy4 country_dummy5 country_dummy6 country_dummy7 country_dummy8 country_dummy9 country_dummy10 country_dummy11 country_dummy12 country_dummy13 country_dummy14 country_dummy15 country_dummy16 country_dummy17 country_dummy18 country_dummy19 country_dummy20 country_dummy21 country_dummy22 country_dummy23 country_dummy24 country_dummy25 country_dummy26 country_dummy27 country_dummy28 country_dummy29 country_dummy30 country_dummy31 country_dummy32 country_dummy33 country_dummy34 country_dummy35 country_dummy36 country_dummy37 country_dummy38 country_dummy39 country_dummy40 country_dummy41 country_dummy42 country_dummy43 country_dummy44

probit TEAyyOPP corage i.gender i.GEMEDUC i.GEMHHINC hhsize i.knowent i.opport i.suskill i.fearfail i.equalinc i.nbgoodc i.nbstatus i.nbmedia i.easystart i.country_dummy1 i.country_dummy2 i.country_dummy3 i.country_dummy4 i.country_dummy5 i.country_dummy6 i.country_dummy7 i.country_dummy8 i.country_dummy9 i.country_dummy10 i.country_dummy11 i.country_dummy12 i.country_dummy13 i.country_dummy14 i.country_dummy15 i.country_dummy16 i.country_dummy17 i.country_dummy18 i.country_dummy19 i.country_dummy20 i.country_dummy21 i.country_dummy22 i.country_dummy23 i.country_dummy24 i.country_dummy25 i.country_dummy26 i.country_dummy27i.country_dummy28 i.country_dummy29 i.country_dummy30

Continued appendix 1

i.country_dummy31 i.country_dummy32 i.country_dummy33 i.country_dummy34 i.country_dummy35

i.country_dummy36 i.country_dummy37 i.country_dummy38 i.country_dummy39 i.country_dummy40 i.country_dummy41 i.country_dummy42 i.country_dummy43 i.country_dummy44, vce(robust)

lroc

margins, dydx(*)

estat classification

*6 Second model3: TEAyyNEC is a dependent variable, both genders are included, model fit is assessed, country dummies are included

cor TEAyyNEC corage gender GEMEDUC GEMHHINC hhsize knowent opport suskill fearfail equalinc nbgoodc nbstatus nbmedia easystart country_dummy1 country_dummy2 country_dummy3 country_dummy4 country_dummy5 country_dummy6 country_dummy7 country_dummy8 country_dummy9 country_dummy10 country_dummy11 country_dummy12 country_dummy13 country_dummy14 country_dummy15 country_dummy16 country_dummy17 country_dummy18 country_dummy19 country_dummy20 country_dummy21 country_dummy22 country_dummy23 country_dummy24 country_dummy25 country_dummy26 country_dummy27 country_dummy28 country_dummy29 country_dummy30 country_dummy31 country_dummy32 country_dummy33 country_dummy34 country_dummy35 country_dummy36 country_dummy37 country_dummy38 country_dummy39 country_dummy40 country_dummy41 country_dummy42 country_dummy43 country_dummy44

probit TEAyyNEC corage i.gender i.GEMEDUC i.GEMHHINC hhsize i.knowent i.opport i.suskill i.fearfail i.equalinc i.nbgoodc i.nbstatus i.nbmedia i.easystart i.country_dummy1 i.country_dummy2 i.country_dummy3 i.country_dummy4 i.country_dummy5 i.country_dummy6 i.country_dummy7 i.country_dummy8 i.country_dummy9 i.country_dummy10 i.country_dummy11 i.country_dummy12 i.country_dummy13 i.country_dummy14 i.country_dummy15 i.country_dummy16 i.country_dummy17 i.country_dummy18 i.country_dummy19 i.country_dummy20 i.country_dummy21 i.country_dummy22 i.country_dummy23 i.country_dummy24 i.country_dummy25 i.country_dummy26 i.country_dummy27 i.country_dummy28 i.country_dummy29 i.country_dummy30 i.country_dummy31 i.country_dummy32 i.country_dummy33 i.country_dummy34 i.country_dummy35 i.country_dummy36 i.country_dummy37 i.country_dummy38 i.country_dummy39 i.country_dummy40 i.country_dummy41 i.country_dummy42 i.country_dummy43 i.country_dummy44, vce(robust)

lroc

margins, dydx(*)

estat classification

*7 Third model1: TEAyy is a dependent variable, only female gender is included, model fit is assessed

Continued appendix 1

cor TEAyy corage gender GEMEDUC GEMHHINC hhsize knowent opport suskill fearfail equalinc nbgoodc nbstatus nbmedia easystart

probit TEAyy corage i.gender i.GEMEDUC i.GEMHHINC hhsize i.knowent i.opport i.suskill i.fearfail i.equalinc i.nbgoodc i.nbstatus i.nbmedia i.easystart if gender==2, vce(robust)

lroc

margins, dydx(*)

estat classification

*8 Third model2: TEAyyOPP is a dependent variable, only female gender is included, model fit is assessed

cor TEAyyOPP corage gender GEMEDUC GEMHHINC hhsize knowent opport suskill fearfail equalinc nbgoodc nbstatus nbmedia easystart

probit TEAyyOPP corage i.gender i.GEMEDUC i.GEMHHINC hhsize i.knowent i.opport i.suskill i.fearfail i.equalinc i.nbgoodc i.nbstatus i.nbmedia i.easystart if gender==2, vce(robust)

lroc

margins, dydx(*)

estat classification

*9 Third model3: TEAyyNEC is a dependent variable, only female gender is included, model fit is assessed

cor TEAyyNEC corage gender GEMEDUC GEMHHINC hhsize knowent opport suskill fearfail equalinc nbgoodc nbstatus nbmedia easystart

probit TEAyyNEC corage i.gender i.GEMEDUC i.GEMHHINC hhsize i.knowent i.opport i.suskill i.fearfail i.equalinc i.nbgoodc i.nbstatus i.nbmedia i.easystart if gender==2, vce(robust)

lroc

margins, dydx(*)

estat classification

*10 Fourth model1: TEAyy is a dependent variable, only female gender is included, model fit is assessed, country dummies are included

cor TEAyy corage gender GEMEDUC GEMHHINC hhsize knowent opport suskill fearfail equalinc nbgoodc nbstatus nbmedia easystart country_dummy1 country_dummy2 country_dummy3 country_dummy4 country_dummy5 country_dummy6 country_dummy7 country_dummy8 country_dummy9 country_dummy10 country_dummy11 country_dummy12 country_dummy13 country_dummy14 country_dummy15 country_dummy16 country_dummy17 country_dummy18 country_dummy19 country_dummy20 country_dummy21 country_dummy22 country_dummy23 country_dummy24 country_dummy25 country_dummy26 country_dummy27 country_dummy28 country_dummy29 country_dummy30 country_dummy31 country_dummy32 country_dummy33 country_dummy34 country_dummy35 country_dummy36 country_dummy37 country_dummy38 country_dummy39 country_dummy40 country_dummy41 country_dummy42 country_dummy43 country_dummy44

probit TEAyy corage i.gender i.GEMEDUC i.GEMHHINC hhsize i.knowent i.opport i.suskill i.fearfail i.equalinc i.nbgoodc i.nbstatus i.nbmedia i.easystart i.country_dummy1 i.country_dummy2

Continued appendix 1

i.country_dummy3 i.country_dummy4 i.country_dummy5 i.country_dummy6 i.country_dummy7 i.country_dummy8 i.country_dummy9 i.country_dummy10 i.country_dummy11 i.country_dummy12 i.country_dummy13 i.country_dummy14 i.country_dummy15 i.country_dummy16 i.country_dummy17 i.country_dummy18 i.country_dummy19 i.country_dummy20 i.country_dummy21 i.country_dummy22 i.country_dummy23

i.country_dummy24 i.country_dummy25 i.country_dummy26 i.country_dummy27 i.country_dummy28 i.country_dummy29 i.country_dummy30 i.country_dummy31 i.country_dummy32 i.country_dummy33 i.country_dummy34 i.country_dummy35 i.country_dummy36 i.country_dummy37 i.country_dummy38 i.country_dummy39 i.country_dummy40 i.country_dummy41 i.country_dummy42 i.country_dummy43 i.country_dummy44 if gender ==2, vce(robust)

lroc

margins, dydx(*)

estat classification

*11 Fourth model2: TEAyyOPP is a dependent variable, only female gender is included, model fit is assessed, country dummies are included

cor TEAyyOPP corage gender GEMEDUC GEMHHINC hhsize knowent opport suskill fearfail equalinc nbgoodc nbstatus nbmedia easystart country_dummy1 country_dummy2 country_dummy3 country_dummy4 country_dummy5 country_dummy6 country_dummy7 country_dummy8 country_dummy9 country_dummy10 country_dummy11 country_dummy12 country_dummy13 country_dummy14 country_dummy15 country_dummy16 country_dummy17 country_dummy18 country_dummy19 country_dummy20 country_dummy21 country_dummy22 country_dummy23 country_dummy24 country_dummy25 country_dummy26 country_dummy27 country_dummy28 country_dummy29 country_dummy30 country_dummy31 country_dummy32 country_dummy33 country_dummy34 country_dummy35 country_dummy36 country_dummy37 country_dummy38 country_dummy39 country_dummy40 country_dummy41 country_dummy42 country_dummy43 country_dummy44

probit TEAyyOPP corage i.gender i.GEMEDUC i.GEMHHINC hhsize i.knowent i.opport i.suskill i.fearfail i.equalinc i.nbgoodc i.nbstatus i.nbmedia i.easystart i.country_dummy1 i.country_dummy2 i.country_dummy3 i.country_dummy4 i.country_dummy5 i.country_dummy6 i.country_dummy7 i.country_dummy8 i.country_dummy9 i.country_dummy10 i.country_dummy11 i.country_dummy12 i.country_dummy13 i.country_dummy14 i.country_dummy15 i.country_dummy16 i.country_dummy17 i.country_dummy18 i.country_dummy19 i.country_dummy20 i.country_dummy21 i.country_dummy22 i.country_dummy23 i.country_dummy24 i.country_dummy25 i.country_dummy26 i.country_dummy27 i.country_dummy28 i.country_dummy29 i.country_dummy30 i.country_dummy31 i.country_dummy32 i.country_dummy33 i.country_dummy34 i.country_dummy35 i.country_dummy36 i.country_dummy37 i.country_dummy38 i.country_dummy39 i.country_dummy40 i.country_dummy41 i.country_dummy42 i.country_dummy43 i.country_dummy44 if gender ==2, vce(robust)

Continued appendix 1

lroc

margins, dydx(*)

estat classification

*12 Fourth model3: TEAyyNEC is a dependent variable, only female gender is included, model fit is assessed, country dummies are included

cor TEAyyNEC corage gender GEMEDUC GEMHHINC hhsize knowent opport suskill fearfail equalinc nbgoodc nbstatus nbmedia easystart country_dummy1 country_dummy2 country_dummy3 country_dummy4 country_dummy5 country_dummy6 country_dummy7 country_dummy8 country_dummy9 country_dummy10 country_dummy11 country_dummy12 country_dummy13 country_dummy14 country_dummy15 country_dummy16 country_dummy17 country_dummy18 country_dummy19 country_dummy20 country_dummy21 country_dummy22 country_dummy23 country_dummy24 country_dummy25 country_dummy26 country_dummy27 country_dummy28 country_dummy29 country_dummy30 country_dummy31 country_dummy32 country_dummy33 country_dummy34 country_dummy35 country_dummy36 country_dummy37 country_dummy38 country_dummy39 country_dummy40 country_dummy41 country_dummy42 country_dummy43 country_dummy44

probit TEAyyNEC corage i.gender i.GEMEDUC i.GEMHHINC hhsize i.knowent i.opport i.suskill i.fearfail i.equalinc i.nbgoodc i.nbstatus i.nbmedia i.easystart i.country_dummy1 i.country_dummy2 i.country_dummy3 i.country_dummy4 i.country_dummy5 i.country_dummy6 i.country_dummy7 i.country_dummy8 i.country_dummy9 i.country_dummy10 i.country_dummy11 i.country_dummy12 i.country_dummy13 i.country_dummy14 i.country_dummy15 i.country_dummy16 i.country_dummy17 i.country_dummy18 i.country_dummy19 i.country_dummy20 i.country_dummy21 i.country_dummy22 i.country_dummy23 i.country_dummy24 i.country_dummy25 i.country_dummy26 i.country_dummy27 i.country_dummy28 i.country_dummy29 i.country_dummy30 i.country_dummy31 i.country_dummy32 i.country_dummy33 i.country_dummy34 i.country_dummy35 i.country_dummy36 i.country_dummy37 i.country_dummy38 i.country_dummy39 i.country_dummy40 i.country_dummy41 i.country_dummy42 i.country_dummy43 i.country_dummy44 if gender ==2, vce(robust)

lroc

margins, dydx(*)

estat classification

*13 Fifth model1: TEAyy is a dependent variable, only male gender is included, model fit is assessed

cor TEAyy corage gender GEMEDUC GEMHHINC hhsize knowent opport suskill fearfail equalinc nbgoodc nbstatus nbmedia easystart

probit TEAyy corage i.gender i.GEMEDUC i.GEMHHINC hhsize i.knowent i.opport i.suskill i.fearfail i.equalinc i.nbgoodc i.nbstatus i.nbmedia i.easystart if gender==1, vce(robust)

lroc

margins, dydx(*)

Continued appendix 1

estat classification

*14 Fifth model2: TEAyyOPP is a dependent variable, only male gender is included, model fit is assessed

cor TEAyyOPP corage gender GEMEDUC GEMHHINC hhsize knowent opport suskill fearfail equalinc nbgoodc nbstatus nbmedia easystart

probit TEAyyOPP corage i.gender i.GEMEDUC i.GEMHHINC hhsize i.knowent i.opport i.suskill i.fearfail i.equalinc i.nbgoodc i.nbstatus i.nbmedia i.easystart if gender==1, vce(robust)

lroc

margins, dydx(*)

estat classification

*15 Fifth model3: TEAyyNEC is a dependent variable, only male gender is included, model fit is assessed

cor TEAyyNEC corage gender GEMEDUC GEMHHINC hhsize knowent opport suskill fearfail equalinc nbgoodc nbstatus nbmedia easystart

probit TEAyyNEC corage i.gender i.GEMEDUC i.GEMHHINC hhsize i.knowent i.opport i.suskill i.fearfail i.equalinc i.nbgoodc i.nbstatus i.nbmedia i.easystart if gender==1, vce(robust)

lroc

margins, dydx(*)

estat classification

*16 Sixth model1: TEAyy is a dependent variable, only male gender is included, model fit is assessed, country dummies are included

cor TEAyy corage gender GEMEDUC GEMHHINC hhsize knowent opport suskill fearfail equalinc nbgoodc nbstatus nbmedia easystart country_dummy1 country_dummy2 country_dummy3 country_dummy4 country_dummy5 country_dummy6 country_dummy7 country_dummy8 country_dummy9 country_dummy10 country_dummy11 country_dummy12 country_dummy13 country_dummy14 country_dummy15 country_dummy16 country_dummy17 country_dummy18 country_dummy19 country_dummy20 country_dummy21 country_dummy22 country_dummy23 country_dummy24 country_dummy25 country_dummy26 country_dummy27 country_dummy28 country_dummy29 country_dummy30 country_dummy31 country_dummy32 country_dummy33 country_dummy34 country_dummy35 country_dummy36 country_dummy37 country_dummy38 country_dummy39 country_dummy40 country_dummy41 country_dummy42 country_dummy43 country_dummy44

probit TEAyy corage i.gender i.GEMEDUC i.GEMHHINC hhsize i.knowent i.opport i.suskill i.fearfail i.equalinc i.nbgoodc i.nbstatus i.nbmedia i.easystart i.country_dummy1 i.country_dummy2 i.country_dummy3 i.country_dummy4 i.country_dummy5 i.country_dummy6 i.country_dummy7 i.country_dummy8 i.country_dummy9 i.country_dummy10 i.country_dummy11 i.country_dummy12 i.country_dummy13 i.country_dummy14 i.country_dummy15 i.country_dummy16 i.country_dummy17 i.country_dummy18 i.country_dummy19 i.country_dummy20 i.country_dummy21 i.country_dummy22 i.country_dummy23 i.country_dummy24 i.country_dummy25 i.country_dummy26 i.country_dummy27

Continued appendix 1

i.country_dummy28 i.country_dummy29 i.country_dummy30 i.country_dummy31 i.country_dummy32 i.country_dummy33 i.country_dummy34 i.country_dummy35 i.country_dummy36 i.country_dummy37 i.country_dummy38 i.country_dummy39 i.country_dummy40 i.country_dummy41 i.country_dummy42 i.country_dummy43 i.country_dummy44 if gender ==1, vce(robust)

lroc

margins, dydx(*)

estat classification

*16 Sixth model2: TEAyyOPP is a dependent variable, only male gender is included, model fit is assessed, country dummies are included

cor TEAyyOPP corage gender GEMEDUC GEMHHINC hhsize knowent opport suskill fearfail equalinc nbgoodc nbstatus nbmedia easystart country_dummy1 country_dummy2 country_dummy3 country_dummy4 country_dummy5 country_dummy6 country_dummy7 country_dummy8 country_dummy9 country_dummy10 country_dummy11 country_dummy12 country_dummy13 country_dummy14 country_dummy15 country_dummy16 country_dummy17 country_dummy18 country_dummy19 country_dummy20 country_dummy21 country_dummy22 country_dummy23 country_dummy24 country_dummy25 country_dummy26 country_dummy27 country_dummy28 country_dummy29 country_dummy30 country_dummy31 country_dummy32 country_dummy33 country_dummy34 country_dummy35 country_dummy36 country_dummy37 country_dummy38 country_dummy39 country_dummy40 country_dummy41 country_dummy42 country_dummy43 country_dummy44

probit TEAyyOPP corage i.gender i.GEMEDUC i.GEMHHINC hhsize i.knowent i.opport i.suskill i.fearfail i.equalinc i.nbgoodc i.nbstatus i.nbmedia i.easystart i.country_dummy1 i.country_dummy2 i.country_dummy3 i.country_dummy4 i.country_dummy5 i.country_dummy6 i.country_dummy7 i.country_dummy8 i.country_dummy9 i.country_dummy10 i.country_dummy11 i.country_dummy12 i.country_dummy13 i.country_dummy14 i.country_dummy15 i.country_dummy16 i.country_dummy17 i.country_dummy18 i.country_dummy19 i.country_dummy20 i.country_dummy21 i.country_dummy22 i.country_dummy23 i.country_dummy24 i.country_dummy25 i.country_dummy26 i.country_dummy27 i.country_dummy28 i.country_dummy29 i.country_dummy30 i.country_dummy31 i.country_dummy32 i.country_dummy33 i.country_dummy34 i.country_dummy35 i.country_dummy36 i.country_dummy37 i.country_dummy38 i.country_dummy39 i.country_dummy40 i.country_dummy41 i.country_dummy42 i.country_dummy43 i.country_dummy44 if gender ==1, vce(robust)

lroc

margins, dydx(*)

estat classification

*17 Sixth model3: TEAyyNEC is a dependent variable, only male gender is included, model fit is assessed, country dummies are included

Continued appendix 1

cor TEAyyNEC corage gender GEMEDUC GEMHHINC hhsize knowent opport suskill fearfail equalinc nbgoodc nbstatus nbmedia easystart country_dummy1 country_dummy2 country_dummy3 country_dummy4 country_dummy5 country_dummy6 country_dummy7 country_dummy8 country_dummy9 country_dummy10 country_dummy11 country_dummy12 country_dummy13 country_dummy14 country_dummy15 country_dummy16 country_dummy17 country_dummy18 country_dummy19 country_dummy20 country_dummy21 country_dummy22 country_dummy23 country_dummy24 country_dummy25 country_dummy26 country_dummy27 country_dummy28 country_dummy29 country_dummy30 country_dummy31 country_dummy32 country_dummy33

country_dummy34 country_dummy35 country_dummy36 country_dummy37 country_dummy38 country_dummy39 country_dummy40 country_dummy41 country_dummy42 country_dummy43 country_dummy44

probit TEAyyNEC corage i.gender i.GEMEDUC i.GEMHHINC hhsize i.knowent i.opport i.suskill i.fearfail i.equalinc i.nbgoodc i.nbstatus i.nbmedia i.easystart i.country_dummy1 i.country_dummy2 i.country_dummy3 i.country_dummy4 i.country_dummy5 i.country_dummy6 i.country_dummy7 i.country_dummy8 i.country_dummy9 i.country_dummy10 i.country_dummy11 i.country_dummy12 i.country_dummy13 i.country_dummy14 i.country_dummy15 i.country_dummy16 i.country_dummy17 i.country_dummy18 i.country_dummy19 i.country_dummy20 i.country_dummy21 i.country_dummy22 i.country_dummy23 i.country_dummy24 i.country_dummy25 i.country_dummy26 i.country_dummy27 i.country_dummy28 i.country_dummy29 i.country_dummy30 i.country_dummy31 i.country_dummy32 i.country_dummy33 i.country_dummy34 i.country_dummy35 i.country_dummy36 i.country_dummy37 i.country_dummy38 i.country_dummy39 i.country_dummy40 i.country_dummy41 i.country_dummy42 i.country_dummy43 i.country_dummy44 if gender ==1, vce(robust)

predict pr

lroc

margins, dydx(*)

estat classification

Correlation matrix of selected variables

Table 1. Correlation matrix of selected variables and TEAyy, both genders, ignoring the country

Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)	(14)	(15)
(1) TEAyy	1.000
(2) Current age (ln)	-0.071	1.000
(3) Gender	-0.044	-0.001	1.000
(4) Education	0.003	-0.135	-0.039	1.000
(5) Household Income	0.069	0.002	-0.073	0.206	1.000
(6) number of household members	0.056	-0.122	0.011	-0.137	0.058	1.000
(7) Personal knowledge of early-stage entrepreneurs	0.190	-0.070	-0.058	0.062	0.108	0.059	1.000
(8) Good opportunity for starting a business where they live	0.187	-0.070	-0.031	0.025	0.077	0.051	0.226	1.000
(9) Having the required knowledge and skills to start a business	0.253	-0.006	-0.104	0.068	0.094	0.042	0.239	0.216	1.000
(10) Fear of failure as a preventing factor	-0.090	0.010	0.070	0.001	-0.040	-0.037	-0.025	-0.079	-0.132	1.000
(11) Preference for similar standards of living in the country	-0.003	0.024	0.006	-0.045	-0.038	0.001	0.005	0.027	0.025	0.074	1.000
(12) People consider starting a business a desirable career choice	0.048	-0.037	-0.002	-0.070	-0.025	0.054	0.049	0.128	0.085	0.033	0.160	1.000
(13) Those successful at starting a business have a high level of status and respect	0.043	-0.021	0.000	-0.040	-0.017	0.045	0.056	0.114	0.068	0.060	0.118	0.240	1.000
(14) Frequent stories in the public media about successful new businesses	0.057	-0.003	0.008	-0.006	0.010	0.036	0.080	0.155	0.095	0.011	0.095	0.169	0.196	1.000
(15) Easy to start a business in a country	0.077	0.018	-0.018	-0.027	0.022	0.029	0.081	0.210	0.120	-0.045	0.061	0.116	0.092	0.166	1.000

Continued appendix 2

Table 2. Correlation matrix of selected variables and TEAyyOPP, both genders, ignoring the country

Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)	(14)	(15)
(1) TEAyyOPP	1.000
(2) Current age (ln)	-0.068	1.000
(3) Gender	-0.052	-0.001	1.000
(4) Education	0.031	-0.135	-0.039	1.000
(5) Household income	0.094	0.002	-0.073	0.206	1.000
(6) Number of household members	0.045	-0.122	0.011	-0.137	0.058	1.000
(7) Personal knowledge of early-stage entrepreneurs	0.172	-0.070	-0.058	0.062	0.108	0.059	1.000
(8) Good opportunity for starting a business where they live	0.173	-0.070	-0.031	0.025	0.077	0.051	0.226	1.000
(9) Having the required knowledge and skills to start a business	0.218	-0.006	-0.104	0.068	0.094	0.042	0.239	0.216	1.000
(10) Fear of failure as a preventing factor	-0.086	0.010	0.070	0.001	-0.040	-0.037	-0.025	-0.079	-0.132	1.000
(11) Preference for similar standards of living in the country	-0.006	0.024	0.006	-0.045	-0.038	0.001	0.005	0.027	0.025	0.074	1.000
(12) People consider starting a business a desirable career choice	0.033	-0.037	-0.002	-0.070	-0.025	0.054	0.049	0.128	0.085	0.033	0.160	1.000
(13) Those successful at starting a business have a high level of status and respect	0.037	-0.021	0.000	-0.040	-0.017	0.045	0.056	0.114	0.068	0.060	0.118	0.240	1.000
(14) Frequent stories in the public media about successful new businesses	0.050	-0.003	0.008	-0.006	0.010	0.036	0.080	0.155	0.095	0.011	0.095	0.169	0.196	1.000
(15) Easy to start a business in a country	0.074	0.018	-0.018	-0.027	0.022	0.029	0.081	0.210	0.120	-0.045	0.061	0.116	0.092	0.166	1.000

Table 3. Correlation matrix of selected variables and TEAyyNEC, both genders, ignoring the country

Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)	(14)	(15)
(1) TEAyyNEC	1.000
(2) Current age (ln)	-0.018	1.000
(3) Gender	0.003	-0.001	1.000
(4) Education	-0.047	-0.135	-0.039	1.000
(5) Household income	-0.023	0.002	-0.073	0.206	1.000
(6) Number of household members	0.032	-0.122	0.011	-0.137	0.058	1.000
(7) Personal knowledge of early-stage entrepreneurs	0.070	-0.070	-0.058	0.062	0.108	0.059	1.000
(8) Good opportunity for starting a business where they live	0.066	-0.070	-0.031	0.025	0.077	0.051	0.226	1.000
(9) Having the required knowledge and skills to start a business	0.110	-0.006	-0.104	0.068	0.094	0.042	0.239	0.216	1.000
(10) Fear of failure as a preventing factor	-0.025	0.010	0.070	0.001	-0.040	-0.037	-0.025	-0.079	-0.132	1.000
(11) Preference for similar standards of living in the country	0.006	0.024	0.006	-0.045	-0.038	0.001	0.005	0.027	0.025	0.074	1.000
(12) People consider starting a business a desirable career choice	0.036	-0.037	-0.002	-0.070	-0.025	0.054	0.049	0.128	0.085	0.033	0.160	1.000
(13) Those successful at starting a business have a high level of status and respect	0.021	-0.021	0.000	-0.040	-0.017	0.045	0.056	0.114	0.068	0.060	0.118	0.240	1.000
(14) Frequent stories in the public media about successful new businesses	0.025	-0.003	0.008	-0.006	0.010	0.036	0.080	0.155	0.095	0.011	0.095	0.169	0.196	1.000
(15) Easy to start a business in a country	0.021	0.018	-0.018	-0.027	0.022	0.029	0.081	0.210	0.120	-0.045	0.061	0.116	0.092	0.166	1.000

The marginal effects of the motivating factors to be involved into entrepreneurial activities

	1	2	3	4	5	6	7	8	9
	TEAyy	TEAyyOPP	TEAyyNEC	TEAyy	TEAyyOPP	TEAyyNEC	TEAyy	TEAyyOPP	TEAyyNEC
Current age (ln)	-0.007	-0.006	-0.001	-0.005	-0.005	-0.000	-0.006	-0.005	-0.001
	(0.000)**	(0.000)**	(0.000)**	(0.000)**	(0.000)**	(0.000)	(0.001)**	(0.000)**	(0.000)**
Gender	-0.008	-0.013	0.004	-0.013	-0.016	0.003	0.000	0.000	0.000
	(0.002)**	(0.002)**	(0.001)**	(0.002)**	(0.002)**	(0.001)	(0.000)	(0.000)	(0.000)
Level of education (Some Secondary)	-0.021	0.002	-0.020	0.001	0.013	-0.009	-0.015	0.002	-0.012
	(0.005)**	(0.004)	(0.003)**	(0.005)	(0.004)**	(0.003)**	(0.006)*	(0.005)	(0.003)**
Level of education (Secondary degree)	-0.037	-0.008	-0.026	-0.003	0.013	-0.012	-0.033	-0.007	-0.021
	(0.005)**	(0.004)*	(0.003)**	(0.004)	(0.004)**	(0.003)**	(0.005)**	(0.005)	(0.003)**
Level of education (Post-Secondary)	-0.038	-0.001	-0.035	0.002	0.025	-0.020	-0.044	-0.007	-0.035
	(0.005)**	(0.004)	(0.003)**	(0.005)	(0.004)**	(0.003)**	(0.006)**	(0.005)	(0.004)**
Level of education (Graduated experience)	-0.016	0.021	-0.036	0.021	0.043	-0.020	-0.019	0.015	-0.037
	(0.008)*	(0.007)**	(0.004)**	(0.008)**	(0.007)**	(0.004)**	(0.010)*	(0.008)	(0.007)**
Level of household income (Middle)	0.016	0.023	-0.006	0.016	0.021	-0.005	0.015	0.023	-0.007
	(0.003)**	(0.003)**	(0.002)**	(0.003)**	(0.003)**	(0.002)*	(0.004)**	(0.004)**	(0.002)**
Level of household income (High)	0.032	0.045	-0.013	0.032	0.045	-0.013	0.028	0.039	-0.013
	(0.003)**	(0.003)**	(0.002)**	(0.003)**	(0.003)**	(0.002)**	(0.004)**	(0.004)**	(0.003)**
The number of household members	0.003	0.002	0.001	0.001	0.000	0.000	0.002	0.002	0.001
	(0.000)**	(0.000)**	(0.000)**	(0.001)	(0.000)	(0.000)	(0.001)**	(0.001)**	(0.000)
Personal knowledge of early-stage entrepreneurs	0.073	0.055	0.017	0.069	0.052	0.016	0.066	0.050	0.016
	(0.003)**	(0.002)**	(0.002)**	(0.003)**	(0.002)**	(0.002)**	(0.003)**	(0.003)**	(0.002)**
Good opportunity for starting a business where they live	0.068	0.055	0.012	0.060	0.049	0.011	0.060	0.047	0.014
	(0.003)**	(0.002)**	(0.002)**	(0.003)**	(0.002)**	(0.002)**	(0.004)**	(0.003)**	(0.002)**
Having the required knowledge and skills to start a business	0.138	0.099	0.038	0.127	0.093	0.034	0.137	0.095	0.047
	(0.003)**	(0.002)**	(0.001)**	(0.003)**	(0.002)**	(0.001)**	(0.004)**	(0.003)**	(0.003)**
Fear of failure as a preventing factor	-0.032	-0.029	-0.003	-0.026	-0.025	-0.001	-0.027	-0.022	-0.004
	(0.003)**	(0.002)**	(0.001)*	(0.003)**	(0.002)**	(0.001)	(0.004)**	(0.003)**	(0.002)
Preference for similar standards of living in the country	-0.007	-0.005	-0.001	-0.003	-0.003	-0.000	-0.002	0.000	-0.002
	(0.003)**	(0.002)*	(0.002)	(0.003)	(0.002)	(0.002)	(0.004)	(0.003)	(0.002)
People consider starting a business a desirable career choice	0.006	0.000	0.006	0.002	-0.001	0.003	0.008	0.004	0.005
	(0.003)*	(0.002)	(0.002)**	(0.003)	(0.002)	(0.002)*	(0.004)*	(0.003)	(0.002)*
Those successful at starting a business have a high level of status and respect	0.005	0.005	0.000	-0.002	0.001	-0.003	0.003	0.003	-0.000
	(0.003)	(0.002)*	(0.002)	(0.003)	(0.002)	(0.002)	(0.004)	(0.003)	(0.002)
Frequent stories in the public media about successful new businesses	0.007	0.006	0.001	-0.001	0.002	-0.002	0.003	0.005	-0.001
	(0.003)*	(0.002)*	(0.002)	(0.003)	(0.002)	(0.002)	(0.004)	(0.003)	(0.002)
Easy to start a business in a country	0.014	0.015	-0.002	0.013	0.013	-0.000	0.017	0.018	-0.001
	(0.003)**	(0.002)**	(0.001)	(0.003)**	(0.002)**	(0.002)	(0.004)**	(0.003)**	(0.002)
Country				NO	NO	NO
N	71,541	71,541	71,541	71,541	71,541	71,541	34,163	34,163	34,163

* p<0.05; ** p<0.01

	10	11	12	13	14	15	16	17	18
	TEAyy	TEAyyOPP	TEAyyNEC	TEAyy	TEAyyOPP	TEAyyNEC	TEAyy	TEAyyOPP	TEAyyNEC
Current age (ln)	-0.003	-0.004	0.000	-0.009	-0.008	-0.001	-0.006	-0.006	-0.000
	(0.001)**	(0.001)**	(0.000)	(0.001)**	(0.001)**	(0.000)**	(0.001)**	(0.001)**	(0.000)
Gender	0.000	0.000	0.000
	(0.000)	(0.000)	(0.000)
Level of education (Some Secondary)	0.003	0.009	-0.002	-0.023	0.003	-0.019	-0.000	0.018	-0.012
	(0.006)	(0.006)	(0.004)	(0.007)**	(0.006)	(0.003)**	(0.007)	(0.007)**	(0.003)**
Level of education (Secondary degree)	-0.003	0.011	-0.010	-0.037	-0.009	-0.021	-0.003	0.017	-0.013
	(0.006)	(0.005)*	(0.003)**	(0.006)**	(0.006)	(0.003)**	(0.007)	(0.006)**	(0.003)**
Level of education (Post-Secondary)	-0.005	0.017	-0.019	-0.029	0.004	-0.030	0.011	0.035	-0.019
	(0.006)	(0.006)**	(0.004)**	(0.007)**	(0.006)	(0.003)**	(0.007)	(0.007)**	(0.004)**
Level of education (Graduated experience)	0.027	0.042	-0.016	-0.009	0.024	-0.030	0.018	0.045	-0.021
	(0.010)**	(0.009)**	(0.007)*	(0.010)	(0.009)**	(0.006)**	(0.011)	(0.009)**	(0.006)**
Level of household income (Middle)	0.016	0.021	-0.005	0.018	0.025	-0.004	0.017	0.024	-0.003
	(0.004)**	(0.004)**	(0.003)	(0.005)**	(0.004)**	(0.002)	(0.005)**	(0.004)**	(0.002)
Level of household income (High)	0.030	0.039	-0.010	0.036	0.050	-0.014	0.034	0.050	-0.015
	(0.004)**	(0.004)**	(0.003)**	(0.005)**	(0.004)**	(0.003)**	(0.005)**	(0.004)**	(0.003)**
The number of household members	-0.001	-0.000	-0.000	0.003	0.002	0.001	0.001	0.001	0.001
	(0.001)	(0.001)	(0.000)	(0.001)**	(0.001)**	(0.000)**	(0.001)*	(0.001)	(0.000)*
Personal knowledge of early-stage entrepreneurs	0.060	0.046	0.014	0.076	0.058	0.018	0.074	0.056	0.018
	(0.004)**	(0.003)**	(0.002)**	(0.004)**	(0.003)**	(0.002)**	(0.004)**	(0.003)**	(0.002)**
Good opportunity for starting a business where they live	0.053	0.042	0.012	0.071	0.060	0.011	0.062	0.054	0.010
	(0.004)**	(0.003)**	(0.002)**	(0.004)**	(0.003)**	(0.002)**	(0.004)**	(0.003)**	(0.002)**
Having the required knowledge and skills to start a business	0.123	0.086	0.041	0.155	0.122	0.037	0.143	0.113	0.034
	(0.004)**	(0.003)**	(0.003)**	(0.004)**	(0.004)**	(0.003)**	(0.004)**	(0.004)**	(0.003)**
Fear of failure as a preventing factor	-0.022	-0.020	-0.002	-0.038	-0.036	-0.002	-0.031	-0.032	0.000
	(0.003)**	(0.003)**	(0.002)	(0.004)**	(0.003)**	(0.002)	(0.004)**	(0.003)**	(0.002)
Preference for similar standards of living in the country	0.002	0.003	-0.001	-0.012	-0.011	-0.001	-0.007	-0.008	0.001
	(0.004)	(0.003)	(0.002)	(0.004)**	(0.003)**	(0.002)	(0.004)	(0.003)*	(0.002)
People consider starting a business a desirable career choice	0.006	0.004	0.001	0.003	-0.003	0.008	-0.001	-0.005	0.005
	(0.004)	(0.003)	(0.002)	(0.004)	(0.003)	(0.002)**	(0.004)	(0.004)	(0.002)*
Those successful at starting a business have a high level of status and respect	-0.001	0.002	-0.002	0.007	0.006	0.000	-0.003	-0.001	-0.003
	(0.004)	(0.003)	(0.002)	(0.004)	(0.004)	(0.002)	(0.004)	(0.004)	(0.002)
Frequent stories in the public media about successful new businesses	-0.006	-0.001	-0.005	0.010	0.006	0.003	0.004	0.004	-0.000
	(0.004)	(0.003)	(0.002)*	(0.004)*	(0.003)	(0.002)	(0.004)	(0.003)	(0.002)
Easy to start a business in a country	0.014	0.014	-0.000	0.010	0.012	-0.003	0.011	0.011	-0.000
	(0.004)**	(0.003)**	(0.002)	(0.004)**	(0.003)**	(0.002)	(0.004)**	(0.003)**	(0.002)
Country	NO	NO	NO				NO	NO	NO
N	34,163	34,163	34,163	37,378	37,378	37,378	37,378	37,378	37,378

* p<0.05; ** p<0.01

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