*S4 Text. STATA(TM) Regression Code

*use 4 rounds of DHS data
*declare survey design
gen sampleweight=v005/1000000
svyset yearvillage [pweight= sampleweight ], strata(v025)

*start with nutrition variables
svy: mean haz06  stunt stuntedsev  bornsmallsize mom_bmi lowbmi, over(year)


*haz clearly measured with error. we create two "flag" variables: +/-5 std approach, and 4 std. deviations from median approach
gen flaghaz=haz<-8 | haz>4


*now kernel densities for HAZ scores
twoway (kdensity haz if year==2001 & flag==0) (kdensity haz if year==2006 & flag==0), ytitle(Density) xtitle(HAZ score (children 0-59 months)) graphregion(fcolor(white))
twoway (kdensity haz if year==2006 & flag==0) (kdensity haz if year==2011 & flag==0), ytitle(Density) xtitle(HAZ score (children 0-59 months)) graphregion(fcolor(white))
twoway (kdensity haz if year==2001 & flag==0) (kdensity haz if year==2011 & flag==0), ytitle(Density) xtitle(HAZ score (children 0-59 months)) graphregion(fcolor(white))

*kernel for bmi
twoway (kdensity mom_bmi if year==2001) (kdensity mom_bmi if year==2011), ytitle(Density) xtitle(BMI score (mothers)) graphregion(fcolor(white))


*now Victora et al. type graphs

twoway (lpolyci haz06 chage if year==2001, clcolor(black) clpattern(solid) fcolor(white) blcolor(black) blpattern(dot)) (lpolyci haz06 chage if year==2006, clcolor(gs10) fcolor(none) blpattern(dash)), ytitle(Predicted HAZ scores) ytitle(, margin(medsmall)) xtitle(Child's age (months)) xtitle(,  margin(medsmall)) legend(on cols(2)) graphregion(fcolor(white)) plotregion(fcolor(white))

twoway (lpolyci haz06 chage if year==2006, clcolor(black) clpattern(solid) fcolor(white) blcolor(black) blpattern(dot)) (lpolyci haz06 chage if year==2011, clcolor(gs10) fcolor(none) blpattern(dash)), ytitle(Predicted HAZ scores) ytitle(, margin(medsmall)) xtitle(Child's age (months)) xtitle(,  margin(medsmall)) legend(on cols(2)) graphregion(fcolor(white)) plotregion(fcolor(white))

twoway (lpolyci haz06 chage if year==2001, clcolor(black) clpattern(solid)  blcolor(black) blpattern(dot)) (lpolyci haz06 chage if year==2011, clcolor(black)  clpattern(dash)), ytitle(Predicted HAZ scores) ytitle(, margin(medsmall)) xtitle(Child's age (months)) xtitle(,  margin(medsmall)) legend(on cols(2)) graphregion(fcolor(white)) plotregion(fcolor(white))


*now boys and girls
twoway (lpolyci haz06 chage if ch_male==0, clcolor(black) clpattern(solid)  blcolor(black) blpattern(dot)) (lpolyci haz06 chage if ch_male==1, clcolor(black) clpattern(dash)), ytitle(Predicted HAZ scores) ytitle(, margin(medsmall)) xtitle(Child's age (months)) xtitle(,  margin(medsmall)) legend(on cols(2)) 

*check distribution of age
twoway (kdensity chage if year==2001)  (kdensity chage if year==2011)






*CONSTRUCTING INDICATORS AND EXAMINING RELATIONSHIPS WITH HAZ SCORES
*SOME OF THE REUSLTS BELOW ARE REPORTED IN SUPPLEMENTS S1 TEXT AND S2 TEXT



*CONSTRUCTING ASSETS for Supplement S1. Text

tabstat electr radio tv bike better basic_floo, by(year)


*lack of data for 2001, so we construct a parsimonious wealth index and a richer one
*short list as follows for 2001, 2006 and 20

pca electr radio tv bike better basic_floo
predict wealth6comp, score
*now long list for 2006 and 2011 only
pca electr radio tv bike  better basic_floor fridge   mot_bike car
predict wealth9comp, score
*now very long list for 2011 only
pca electr radio tv bike better basic_floo fridge  mot_bike car table chair bed sofa cupboard computer clock fan dhiki
predict wealth18comp, score
*now 5 items without electricity
pca   radio tv bike better basic_floo
predict wealth5comp, score
*now 4 item index that includes 1996
pca electr radio tv bike
predict wealth4comp, score
summ wealth4comp
gen asset4ind10hat=(wealth4comp+1.25)
summ asset4ind10hat
gen asset4ind10= asset4ind10hat*10/4.33
summ asset4ind10

*associations between 2 indices

pwcorr haz wealth6comp wealth9comp wealth18comp wealth5comp elec
pwcorr haz electr radio tv bike  better basic_floor 
twoway (scatter wealth6comp wealth9comp)

twoway (lpolyci  wealth9comp wealth6comp), ytitle(Asset index scores - 9 variables) ytitle(, margin(medsmall)) /*
*/ xtitle(Asset index scores - 6 variables) xtitle(, margin(medsmall)) legend(off) graphregion(fcolor(white)) plotregion(fcolor(white))

twoway (lpolyci  wealth18comp wealth6comp), ytitle(Asset index scores - 18 variables) ytitle(, margin(medsmall)) /*
*/ xtitle(Asset index scores - 6 variables) xtitle(, margin(medsmall)) legend(off) graphregion(fcolor(white)) plotregion(fcolor(white))

twoway (lpolyci wealth6comp wealth9comp)
twoway (scatter wealth5comp wealth9comp)
twoway (lpolyci wealth5comp wealth9comp)


*trends
tabstat  wealth6comp wealth9comp wealth5comp elec, by(year)
tabstat electr radio tv bike better basic_floor, by(year)

*haz associations
twoway (lpolyci haz wealth5comp) (lpolyci haz wealth6comp)

twoway (lpolyci haz wealth6comp) (lpolyci haz wealth9comp)
twoway (lpoly haz wealth6comp) (lpoly haz wealth9comp)

twoway (lpoly haz assetind10 if year==2001) (lpoly haz assetind10 if year==2006) (lpoly haz assetind10 if year==2011)



*so more parsimonious 6-indicator index seems to perform quite well
*it doesn't seem powerful enough to pick up wealth differences among wealthier classes
*but performs reasonably well for the rest of the population
*only caveat may be electricity, which increased more quickly than other assets
*now re-scale to vary between 1 and 10
*called asset index
 
 twoway (lpolyci haz assetind10), ytitle(Predicted HAZ scores) ytitle(, margin(medsmall)) /*
*/ xtitle(Asset index (1-10)) xtitle(, margin(medsmall)) legend(off) graphregion(fcolor(white)) plotregion(fcolor(white))
 graph save Graph "D:\Users\dheadey\Documents\Economics\nutrition\LANSA & TRANSFORM\Nepal DHS study\stata regs\graphs\asset index and haz.gph"

 *now by rural and urban
 twoway (lpolyci haz assetind10 if urban==0) (lpolyci haz assetind10 if urban==1), ytitle(Predicted HAZ scores) ytitle(, margin(medsmall)) /*
*/ xtitle(Asset index (1-10)) xtitle(, margin(medsmall)) legend(off) graphregion(fcolor(white)) plotregion(fcolor(white))
 
 *let's look at electricity a bit more
 tabstat wealth5comp if year==2001, by(elec)
  tabstat wealth5comp if year==2006, by(elec)
 tabstat wealth5comp if year==2011, by(elec)

 
 
 
 
 
 
*EDUCATION
corr mom_yrschool hus_yrschool wealth6comp wealth9comp

twoway (lpolyci haz mom_yrschool) (lpolyci haz hus_yrschool)
twoway (lpoly haz mom_yrschool if year==2001)  (lpoly haz mom_yrschool if year==2006)  (lpoly haz mom_yrschool if year==2011)

twoway (lpolyci haz  mom_yrschool, clcolor(black) clpattern(solid) fcolor(white) blcolor(black) blpattern(dot)) (lpolyci haz hus_yrschool, clcolor(gs10) fcolor(none) blpattern(dash)), ytitle(Predicted HAZ scores) ytitle(, margin(medsmall)) xtitle(Parental education (years)) xtitle(,  margin(medsmall)) legend(on cols(2)) graphregion(fcolor(white)) plotregion(fcolor(white))

twoway (lpolyci haz  mom_yrschool), ytitle(Predicted HAZ scores) ytitle(, margin(medsmall)) xtitle(Maternal education (years)) xtitle(,  margin(medsmall)) legend(on cols(2)) graphregion(fcolor(white)) plotregion(fcolor(white))

twoway (lpolyci haz  mom_yrschool), ytitle(Predicted HAZ scores) ytitle(, margin(medsmall)) xtitle(Paternal education (years)) xtitle(,  margin(medsmall)) legend(on cols(2)) graphregion(fcolor(white)) plotregion(fcolor(white))




*HEALTH & NUTRITION INTERVENTIONS (some of these reported in Supplement S2 Text)
tabstat  ant_visit n_antenat anc4plus  iron_supp tetanus bloodpres bloodwork urinetest postnatal birth_hosp asst_doctor asst_midwife allvaccin7plus vit_a gaveors zinc diarrhea p_fever p_cough, by(year)

*now check asset index associations with health outcomes over time


summ anc4plus birth_hosp allvaccin7plus if assetind10<0.5 & year==2001
summ anc4plus birth_hosp allvaccin7plus if assetind10>0.5 &  assetind10<2.2 & year==2001
summ anc4plus birth_hosp allvaccin7plus if assetind10>2.2 & assetind10<5 & year==2001
summ anc4plus birth_hosp allvaccin7plus if assetind10>5 & year==2001

summ anc4plus birth_hosp allvaccin7plus if assetind10<0.5 & year==2011
summ anc4plus birth_hosp allvaccin7plus if assetind10>0.5 &  assetind10<2.2 & year==2011
summ anc4plus birth_hosp allvaccin7plus if assetind10>2.2 & assetind10<5 & year==2011
summ anc4plus birth_hosp allvaccin7plus if assetind10>5 & year==2011

pwcorr   n_antenat postnatal allvaccin7plus birth_hosp asst_doctor asst_midwife iron_supp tetanus vit_a 

twoway (lpolyci haz n_antenat) 
*obviously declining returns to ANC visits, or more ANC visits sometimes associated with complications
*so we cap ANC visits at 8 visits (1 per month, essentially), and all it numanc

 twoway (lpolyci haz numanc), ytitle(Predicted HAZ scores) ytitle(, margin(medsmall)) /*
*/ xtitle(Number of antenatal visits) xtitle(, margin(medsmall)) legend(off) graphregion(fcolor(white)) plotregion(fcolor(white))
 graph save Graph "D:\Users\dheadey\Documents\Economics\nutrition\LANSA & TRANSFORM\Nepal DHS study\stata regs\graphs\antenatal visits and haz.gph", replace

 *gen vaccine variable that is interacted with child age
gen chage7mplus=chage>7
gen allvaccin7plus=allvaccin*chage7mplus
gen allvaccin7plusage=allvaccin7plus*chage
gen allvaccin7plusagesq=allvaccin7plus*chage_sq

*create anc=4
gen anc4plus=n_antenat>3

*experiment with health index
tabstat antenat_1st n_antenat iron_supp tetanus bloodpres bloodwork urinetest, by(year)

pca antenat_1st numanc iron_supp  bloodpres bloodwork urinetest

twoway (lpolyci haz chage if allvaccin==1) (lpolyci haz chage if allvaccin==0) 

*we decide to use antenatal and neonatal care/visits
*note that iron supplementation is highly correlated with ANC, so we omit it.
*vit A and tetanus not really expected to affect growthm but also correlated with ANC visits
tabstat iron_supp, by(numanc)
tabstat iron_supp vit_a tetanus, by(birth_hosp)






*DEMOGRAPHY
tabstat border pre_interval nchild_born, by(year)
hist border
hist pre_interval

corr border pre_birthintyrs  wealth6comp mom_yrschool hus_yrschool

twoway (lpolyci haz border if border<10) (lpolyci haz pre_interval if pre_interval<150) 
twoway (lpolyci haz pre_birthintyrs) 

corr haz pre_birthintyrs if  pre_birthintyrs>0
corr haz pre_birthintyrs if pre_birthintyrs<7 & pre_birthintyrs>0

*the non-linearity of pre-interval as well the problem of no obs for birthorder 1
*motivates us to construct a transformed variable: for firstborns value of this variable
*is set at 84. Also, all intervals longer than 84 months are also set at 84.
*84 months (8 years) chosen because of non-linear relationship observed in graph above
*variable is claled pre_birthintyr
gen border1=border==1
gen border1pre_birthintyrs=border1*pre_birthintyrs

twoway (lpolyci haz border if border<10), ytitle(Predicted HAZ scores) ytitle(, margin(medsmall)) /*
*/ xtitle(Birth order) xtitle(, margin(medsmall)) legend(off) graphregion(fcolor(white)) plotregion(fcolor(white))

gen bordersq=border^2


twoway (lpolyci haz pre_birthintyr), ytitle(Predicted HAZ scores) ytitle(, margin(medsmall)) /*
*/ xtitle(Preceding birth interval* (months)) xtitle(, margin(medsmall)) legend(off) graphregion(fcolor(white)) plotregion(fcolor(white))
 
twoway (lpolyci haz pre_birthintyr if year==2001) (lpolyci haz pre_birthintyr if year==2006) (lpolyci haz pre_birthintyr if year==2011)


*potential multicollinearity problem for birth order
*create birth order dummies
gen border1=border==1
gen border2=border==2
gen border3=border==3
gen border4=border==4
gen border5=border==5
gen border6=border==6
gen border7=border==7
gen border8=border>7
drop border1-border8





*SANITATION AND WATER
tabstat nolatrine pr_nolatrine pipewater empower openwell tubewell safe_water, by(year)

pwcorr haz nolatrine pr_nolatrine pipewater empower openwell tubewell safe_water

*household and village level "no latrine" highly correlated - use village
*only tubewell and safe_water are significantly correlated with haz

twoway (lpolyci haz p_nolatrine), ytitle(Predicted HAZ scores) ytitle(, margin(medsmall)) /*
*/ xtitle(Open defecation prevalence at village level (%)) xtitle(, margin(medsmall)) legend(off) graphregion(fcolor(white)) plotregion(fcolor(white))
graph save Graph "D:\Users\dheadey\Documents\Economics\nutrition\LANSA & TRANSFORM\Nepal DHS study\stata regs\graphs\open defecation and haz full sample.gph"

*now separate for rural and urban areas
twoway (lpolyci haz p_nolatrine if urban==0, clcolor(black) clpattern(solid) fcolor(white) blcolor(black) blpattern(dot)) (lpolyci haz p_nolatrine if urban==1, clcolor(gs10) fcolor(none) blpattern(dash)), ytitle(Predicted HAZ scores) ytitle(, margin(medsmall)) xtitle(Open defecation prevalence at village level (%)) xtitle(,  margin(medsmall)) legend(on cols(2)) graphregion(fcolor(white)) plotregion(fcolor(white))

twoway (lpolyci mom_bmi pr_nolatrine), ytitle(Predicted maternal BMI) ytitle(, margin(medsmall)) /*
*/ xtitle(Open defecation prevalence at village level (%)) xtitle(, margin(medsmall)) legend(off) graphregion(fcolor(white)) plotregion(fcolor(white))

twoway (lpolyci mom_bmi pr_nolatrine)

gen sdistyear=sdist*year
by sdistyear, sort: egen distnolatrine=mean(nolatrine)
by sdistyear, sort: egen distmom_bmi=mean(mom_bmi)
by sdistyear, sort: egen distlowbmi=mean(lowbmi)

reg distlowbmi distnolatrine

twoway (lpolyci stunt p_nolatrine) (lpolyci lowbmi p_nolatrine), ytitle(Predicted stunting or low BMI) ytitle(, margin(medsmall))


*BMI
twoway (lpolyci lowbmi p_nolatrine if urban==0, clcolor(black) clpattern(solid) fcolor(white) blcolor(black) blpattern(dot)) (lpolyci lowbmi p_nolatrine if urban==1, clcolor(gs10) fcolor(none) blpattern(dash)), ytitle(Predicted low BMI prevalence) ytitle(, margin(medsmall)) xtitle(Open defecation prevalence at village level (%)) xtitle(,  margin(medsmall)) legend(on cols(2)) graphregion(fcolor(white)) plotregion(fcolor(white))



*MATERNAL EMPOWERMENT & MEDIA EXPOSURE
tabstat newspaper lis_radio watch_tv  health_care purchase visit_relat, by(year)
pwcorr haz newspaper lis_radio watch_tv  health_care purchase visit_relat

gen empowerind=0.333*health_care+0.333*purchase+0.333*visit_relat
summ empower
tabstat empower, by(year)
twoway (lpolyci haz empower) 

pwcorr health_care purchase visit_relat empower mom_yrschool asset

*so some improvement in empowerment but no storng link to HAZ scores

pwcorr newspaper lis_radio watch_tv mom_yrschool radio tv

gen radiotv=lis_radio==1 | watch_tv==1





*MATERNAL NUTRITION AND AGE

tabstat mom_height mom_bmi lowbmi, by(year)
hist mom_height
hist mom_bmi
hist mom_age


twoway (lpolyci haz mom_height if mom_height<175 & mom_height>130), ytitle(Predicted HAZ scores) ytitle(, margin(medsmall)) /*
*/ xtitle(Maternal height (cm)) xtitle(, margin(medsmall)) legend(off) graphregion(fcolor(white)) plotregion(fcolor(white))
graph save Graph "D:\Users\dheadey\Documents\Economics\nutrition\LANSA & TRANSFORM\Nepal DHS study\stata regs\graphs\matenral height and haz full sample.gph"

twoway (lpolyci haz mom_bmi if mom_bmi<35), ytitle(Predicted HAZ scores) ytitle(, margin(medsmall)) /*
*/ xtitle(Maternal BMI) xtitle(, margin(medsmall)) legend(off) graphregion(fcolor(white)) plotregion(fcolor(white))

twoway (lpolyci haz mom_age), ytitle(Predicted HAZ scores) ytitle(, margin(medsmall)) /*
*/ xtitle(Maternal age) xtitle(, margin(medsmall)) legend(off) graphregion(fcolor(white)) plotregion(fcolor(white))


gen agemom1519=mom_age<20
gen  agemom2=mom_age>19 & mom_age<25
gen  agemom3=mom_age>24 & mom_age<30
gen  agemom4=mom_age>29 & mom_age<35
gen  agemom5=mom_age>34 & mom_age<40
gen  agemom6=mom_age>39 & mom_age<45
gen  agemom7=mom_age>44

gen logmom_height=log(mom_height)
gen logmom_bmi=log(mom_bmi)
twoway (lpolyci haz logmom_height) 
twoway (lpolyci haz logmom_bmi) 






*CARE FACTORS
*feeding patterns for children 0-6 months
tabstat breastfeeding oth_milk oth_liquid solidfood if chage<6 & year>1996, by(year)
*feeding patterns 
tabstat  solidfood n_solidfood if chage>5 & chage<10 & year>1996, by(year)
tabstat  solidfood n_solidfood if chage<25, by(year)

twoway (lpolyci breastfeeding chage if year==2001 & chage<25) (lpolyci breastfeeding chage if year==2011 & chage<25)

twoway (lpolyci solidfood chage if year==2001 & chage<25) (lpolyci solidfood chage if year==2011 & chage<25)

twoway (lpolyci n_solidfood chage if year==2001 & chage<25) (lpolyci n_solidfood chage if year==2011 & chage<25)

twoway (lpolyci   n_solidfood chage if year==2001 & chage<24 & d_young==1, clcolor(black) clpattern(solid)  blcolor(black)) (lpolyci  n_solidfood chage if year==2011 & chage<24 & d_young==1, clcolor(gs10) ), ytitle(Times ate solid food yesterday) ytitle(, margin(medsmall)) xtitle(Child age (months)) xtitle(,  margin(medsmall)) legend(on cols(2)) graphregion(fcolor(white)) plotregion(fcolor(white))


twoway (lpolyci dietdiv1 chage if year==2001 & chage<25) (lpolyci dietdiv1 chage if year==2011 & chage<25)


pwcorr dietdiv1 dietdiv7 momdietdiv1
tabstat dietdiv1 solidfood n_solidfood if chage>6 & chage<24, by(year)

reg dietdiv1 assetind10 mom_yrschool hus_yrschool empower agemom1-agemom2 agemom4-agemom7 /*
*/ chhetri magar yadav tamang tharu  newar  buddhist  muslim year2006 year2011 /*
*/ urban eastern  western mid_west far_west mountain hill month1-month24 if chage<25

reg dietdiv1 assetind10 mom_yrschool hus_yrschool empower lis_radio watch_tv agemom1-agemom2 agemom4-agemom7 /*
*/ chhetri magar yadav tamang tharu  newar  buddhist  muslim year2006 year2011 /*
*/ urban eastern  western mid_west far_west mountain hill month1-month24 if chage<25



***************************************************************************************

*check age profile (at request of reviewer)
svy: mean haz06 chage, over(year)

svy: mean haz06 chage if chage<25, over(year)

svy: mean haz06 chage if chage>12 & chage<25, over(year)

*check how much difference adding age dummies makes to year2011 coefficient
eststo: reg haz06  year2006 year2011 if year>2000 
eststo: reg haz06 month* year2006 year2011 if year>2000 

eststo: reg stunt  year2006 year2011 if year>2000 
eststo: reg stunt month* year2006 year2011 if year>2000 

eststo: reg stuntedsev  year2006 year2011 if year>2000 
eststo: reg stuntedsev month* year2006 year2011 if year>2000 

eststo: dprobit stuntedsev  year2006 year2011 if year>2000 
eststo: dprobit stuntedsev month* year2006 year2011 if year>2000 


estout using "D:\Users\dheadey\Documents\Economics\nutrition\LANSA & TRANSFORM & SOC\Nepal DHS study\stata regs\reg table - age distribution check.xls", replace /*
*/ cells(b(star fmt(%9.3f)) se) stats(r2 N, fmt(%9.3f %9.0g) labels(R-squared)) /*
*/ starlevels(* 0.10 ** 0.05 *** 0.01) 
eststo clear


*Table 2
svy: mean haz06 stunt stuntedsev asset4ind10 assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron birth_hosp allvaccin7plus border  pre_birthintyr /*
*/ pr_nolatrine tubewell pipewater empower  mom_height,over(year)


*young children: 0-24
svy: mean haz06 stunt stuntedsev asset4ind10 assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron birth_hosp allvaccin7plus border  pre_birthintyr /*
*/ pr_nolatrine tubewell pipewater empower  mom_height if chage<25 & year!=2006,over(year)

*younger children: 0-12
svy: mean haz06 stunt stuntedsev asset4ind10 assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron birth_hosp allvaccin7plus border  pre_birthintyr /*
*/ pr_nolatrine tubewell pipewater empower  mom_height if chage<13 & year!=2006,over(year)


*had to drop birth order - it suffered from multicollinearity (R-sq of 0.73), mainly due to birth interval

tabstat haz assetind10 mom_yrschool hus_yrschool /*
*/ numanc birth_hosp allvaccin7plus  pre_birthintyrs    /*
*/ pr_nolatrine  mom_height , by(year) stat(N)







*********************************************************

*PREFERED SET OF REGRESSIONS

centile mom_bmi, centile(25 50 75)

centile haz, centile(25 50 75)



*mean HAZ - OLS
eststo:  reg haz assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron birth_hosp allvaccin7plus   pre_birthintyrs   /*
*/ pr_nolatrine    tubewell pipewater empower   mom_height agemom1-agemom2 agemom4-agemom7 /*
*/ border1 border2 border3 border4 border5 border6 border7  /*
*/ chhetri magar yadav tamang tharu  newar  buddhist  muslim /*
*/ popdensity urban year2001 year2006 year2011 westernmountain westernhill easternmountain easternhill /*
*/ mid_westmountain mid_westhill mid_westhill far_westmountain far_westhill month1-month59 if zscore_flag==0, vce(cluster villageyear)

*stunting
eststo: quiet reg stunt assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron birth_hosp allvaccin7plus   pre_birthintyrs   /*
*/ pr_nolatrine    tubewell pipewater empower   mom_height agemom1-agemom2 agemom4-agemom7 /*
*/ border1 border2 border3 border4 border5 border6 border7  /*
*/ chhetri magar yadav tamang tharu  newar  buddhist  muslim /*
*/ popdensity urban year2001 year2006 year2011 westernmountain westernhill easternmountain easternhill /*
*/ mid_westmountain mid_westhill mid_westhill far_westmountain far_westhill month1-month59 if zscore_flag==0, vce(cluster villageyear)

*severe stunting
eststo: quiet reg stuntedsevere assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron birth_hosp allvaccin7plus   pre_birthintyrs   /*
*/ pr_nolatrine    tubewell pipewater empower   mom_height agemom1-agemom2 agemom4-agemom7 /*
*/ border1 border2 border3 border4 border5 border6 border7  /*
*/ chhetri magar yadav tamang tharu  newar  buddhist  muslim /*
*/ popdensity urban year2001 year2006 year2011 westernmountain westernhill easternmountain easternhill /*
*/ mid_westmountain mid_westhill mid_westhill far_westmountain far_westhill month1-month59 if zscore_flag==0, vce(cluster villageyear)


 



*now Oaxaca-Blinder decompositions
set matsize 5000
oaxaca haz assetind10 mom_yrschool hus_yrschool /*
*/ numanc birth_hosp allvaccin7plus   pre_birthintyrs   /*
*/ pr_nolatrine tubewell pipewater empower mom_height agemom1-agemom2 agemom4-agemom7 /*
*/ border1 border2 border3 border4 border5 border6 border7  /*
*/ chhetri magar yadav tamang tharu  newar  buddhist  muslim /*
*/ popdensity urban  westernhill easternmountain easternhill /*
*/ mid_westmountain mid_westhill  far_westmountain far_westhill month1-month59  /*
*/ if year==2001  | year==2011,  noisily by(year) detail

oaxaca  lowbmi assetind10 mom_yrschool hus_yrschool /*
*/ pr_nolatrine tubewell pipewater empower mom_height agemom1-agemom2 agemom4-agemom7 /*
*/ border1 border2 border3 border4 border5 border6 border7  /*
*/ chhetri magar yadav tamang tharu  newar  buddhist  muslim /*
*/ popdensity urban  westernhill easternmountain easternhill /*
*/ mid_westmountain mid_westhill  far_westmountain far_westhill month1-month59  /*
*/ if year==2001  | year==2011,  noisily by(year) detail




*now quantile regs of robustness for Supplement S3 Text

*qreg median
eststo: quiet qreg haz assetind10 mom_yrschool hus_yrschool /*
*/ numanc iron birth_hosp allvaccin7plus   pre_birthintyrs   /*
*/ pr_nolatrine    tubewell pipewater empower   mom_height agemom1-agemom2 agemom4-agemom7 /*
*/ border1 border2 border3 border4 border5 border6 border7  /*
*/ chhetri magar yadav tamang tharu  newar  buddhist  muslim /*
*/ popdensity urban year2001 year2006 year2011 westernmountain westernhill easternmountain easternhill /*
*/ mid_westmountain mid_westhill mid_westhill far_westmountain far_westhill month1-month59 if zscore_flag==0

*qreg 25th percentile
eststo: quiet qreg haz assetind10 mom_yrschool hus_yrschool /*
*/ numanc iron birth_hosp allvaccin7plus   pre_birthintyrs   /*
*/ pr_nolatrine    tubewell pipewater empower   mom_height agemom1-agemom2 agemom4-agemom7 /*
*/ border1 border2 border3 border4 border5 border6 border7  /*
*/ chhetri magar yadav tamang tharu  newar  buddhist  muslim /*
*/ popdensity urban year2001 year2006 year2011 westernmountain westernhill easternmountain easternhill /*
*/ mid_westmountain mid_westhill mid_westhill far_westmountain far_westhill month1-month59 if zscore_flag==0, q(0.25)


estout using "D:\Users\dheadey\Documents\Economics\nutrition\LANSA & TRANSFORM\Nepal DHS study\stata regs\reg table 15 - preferred set.xls", replace /*
*/ cells(b(star fmt(%9.3f)) se) stats(r2 N, fmt(%9.3f %9.0g) labels(R-squared)) /*
*/ starlevels(* 0.10 ** 0.05 *** 0.01) 
eststo clear


*now district fixed effects for Supplement S3 Text

eststo ch_haz_1: quietly reg haz assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron birth_hosp allvaccin7plus  pre_birthintyrs    /*
*/ pr_nolatrine tubewell pipewater empower   mom_height agemom1-agemom2 agemom4-agemom7 /*
*/ feb_mar mar_apr apr_may may_jun jun_jul jul_aug aug_sep sep_oct oct_nov nov_dec dec_jan /*
*/ chhetri magar yadav tamang tharu  newar  buddhist  muslim /*
*/ urban year2001 year2006 year2011 urban2001 urban2006 urban2011 month1-month59  sdist2-sdist75 if zscore_flag==0, vce(cluster villageyear)

eststo ch_haz_2: quietly reg stunt assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron birth_hosp allvaccin7plus  pre_birthintyrs    /*
*/ pr_nolatrine tubewell pipewater empower   mom_height agemom1-agemom2 agemom4-agemom7 /*
*/ feb_mar mar_apr apr_may may_jun jun_jul jul_aug aug_sep sep_oct oct_nov nov_dec dec_jan /*
*/ chhetri magar yadav tamang tharu  newar  buddhist  muslim /*
*/ urban year2001 year2006 year2011 urban2001 urban2006 urban2011 month1-month59  sdist2-sdist75 if zscore_flag==0, vce(cluster villageyear)

eststo ch_haz_3: quietly reg stuntedsev assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron birth_hosp allvaccin7plus  pre_birthintyrs    /*
*/ pr_nolatrine tubewell pipewater empower   mom_height agemom1-agemom2 agemom4-agemom7 /*
*/ feb_mar mar_apr apr_may may_jun jun_jul jul_aug aug_sep sep_oct oct_nov nov_dec dec_jan /*
*/ chhetri magar yadav tamang tharu  newar  buddhist  muslim /*
*/ urban year2001 year2006 year2011 urban2001 urban2006 urban2011 month1-month59  sdist2-sdist75 if zscore_flag==0, vce(cluster villageyear)

eststo ch_haz_4: quietly reg bornsmallsize assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron birth_hosp   pre_birthintyrs    /*
*/ pr_nolatrine tubewell pipewater empower   mom_height agemom1-agemom2 agemom4-agemom7 /*
*/ feb_mar mar_apr apr_may may_jun jun_jul jul_aug aug_sep sep_oct oct_nov nov_dec dec_jan /*
*/ chhetri magar yadav tamang tharu  newar  buddhist  muslim /*
*/ urban year2001 year2006 year2011 urban2001 urban2006 urban2011 month1-month59  sdist2-sdist75 if zscore_flag==0, vce(cluster villageyear)


eststo ch_haz_5: quietly reg lowbmi stuntedsev assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron birth_hosp pre_birthintyrs pr_nolatrine tubewell pipewater empower mom_height agemom1-agemom2 agemom4-agemom7 /*
*/ feb_mar mar_apr apr_may may_jun jun_jul jul_aug aug_sep sep_oct oct_nov nov_dec dec_jan /*
*/ chhetri magar yadav tamang tharu  newar  buddhist  muslim /*
*/ urban year2001 year2006 year2011 urban2001 urban2006 urban2011 month1-month59  sdist2-sdist75 if zscore_flag==0, vce(cluster villageyear)


estout using "D:\Users\dheadey\Documents\Economics\nutrition\LANSA & TRANSFORM\Nepal DHS study\stata regs\reg table 1.xls", replace /*
*/ cells(b(star fmt(%9.3f)) se) stats(r2 N, fmt(%9.3f %9.0g) labels(R-squared)) /*
*/ starlevels(* 0.10 ** 0.05 *** 0.01) 
eststo clear



*now under 24m and under 12m for Supplement S3 Text.
eststo:  reg haz assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron birth_hosp allvaccin7plus   pre_birthintyrs   /*
*/ pr_nolatrine    tubewell pipewater empower   mom_height agemom1-agemom2 agemom4-agemom7 /*
*/ border1 border2 border3 border4 border5 border6 border7  /*
*/ chhetri magar yadav tamang tharu  newar  buddhist  muslim /*
*/ popdensity urban year2001 year2006 year2011 westernmountain westernhill easternmountain easternhill /*
*/ mid_westmountain mid_westhill mid_westhill far_westmountain far_westhill month1-month59 if zscore_flag==0 & chage<25, vce(cluster villageyear)

eststo:  reg haz assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron birth_hosp allvaccin7plus   pre_birthintyrs   /*
*/ pr_nolatrine    tubewell pipewater empower   mom_height agemom1-agemom2 agemom4-agemom7 /*
*/ border1 border2 border3 border4 border5 border6 border7  /*
*/ chhetri magar yadav tamang tharu  newar  buddhist  muslim /*
*/ popdensity urban year2001 year2006 year2011 westernmountain westernhill easternmountain easternhill /*
*/ mid_westmountain mid_westhill mid_westhill far_westmountain far_westhill month1-month59 if zscore_flag==0 & chage<13, vce(cluster villageyear)

estout using "D:\Users\dheadey\Documents\Economics\nutrition\LANSA & TRANSFORM & SOC\Nepal DHS study\stata regs\reg table 17 - preferred set.xls", replace /*
*/ cells(b(star fmt(%9.3f)) se) stats(r2 N, fmt(%9.3f %9.0g) labels(R-squared)) /*
*/ starlevels(* 0.10 ** 0.05 *** 0.01) 
eststo clear


****************************************************

*look at correlations by round to check stability of relationships

pwcorr haz assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron  birth_hosp allvaccin7plus  border pre_birthintyr /*
*/ pr_nolatrine tubewell pipewater empower empower mom_height if year==2001 &  zscore_flag==0

pwcorr haz assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron   birth_hosp allvaccin7plus  border pre_birthintyr /*
*/ pr_nolatrine tubewell pipewater empower empower mom_height if year==2006 &  zscore_flag==0

pwcorr haz assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron   birth_hosp allvaccin7plus  border pre_birthintyr /*
*/ pr_nolatrine tubewell pipewater empower empower mom_height if year==2011 &  zscore_flag==0

pwcorr haz assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron   birth_hosp allvaccin7plus  border pre_birthintyr /*
*/ pr_nolatrine tubewell pipewater empower empower mom_height if year>1998 &  zscore_flag==0


pwcorr lowbmi assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron  birth_hosp allvaccin7plus  border pre_birthintyr /*
*/ pr_nolatrine tubewell pipewater empower empower mom_height if year==2001 &  zscore_flag==0

pwcorr lowbmi assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron   birth_hosp allvaccin7plus  border pre_birthintyr /*
*/ pr_nolatrine tubewell pipewater empower empower mom_height if year==2006 &  zscore_flag==0

pwcorr lowbmi assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron   birth_hosp allvaccin7plus  border pre_birthintyr /*
*/ pr_nolatrine tubewell pipewater empower empower mom_height if year==2011 &  zscore_flag==0

pwcorr lowbmi assetind10 mom_yrschool hus_yrschool /*
*/ anc4plus iron   birth_hosp allvaccin7plus  border pre_birthintyr /*
*/ pr_nolatrine tubewell pipewater empower empower mom_height if year>1998 &  zscore_flag==0