**selecting variables to generate subset of data (immigrants only)

use "C:\Dropbox\Projects\Muslims\Data\Census\census2001.dta", clear

**Creating Variables

			**create the religion variable

				gen Religion = religrpa
				recode Religion 2/4=2 5=3 6=4 7=5 8/9=6 10/11=7 12=8 99=.
				label define Religion 1 "8.Catholic" 2 "7.Protestant" 3 "1.Muslim" 4 "4.Jewish" ///
				5 "2.Buddhist" 6 "3.Hindu/Sikh" 7 "5.Other" 8 "6.None", replace
				label values Religion Religion  
			
			**create the country of birth variable
			
				gen Birthplace = pobpa
				recode Birthplace 1/10=0 11=1 12/22=2 23=3 24/25=4 26/30=5 31/32=6 33=7 34=1 35/999=.
				**Arranging categories from high to low, then labelling them with numbers according to display order in R
				recode Birthplace 2=1 5=2 7=3 4=4 1=3 6=5 3=6 
				label define Birthplace 1 "6.Europe" 2 "4.East Asia" 3 "5.Americas +" ///
				4 "2.South Asia" 5 "3.Africa" 6 "1.Middle East", replace
				label values Birthplace Birthplace
			
			**create an immigration variable, plus a immigration percent variable
			
				gen Immigrant = Birthplace
				recode Immigrant 1/7=1
			
				bysort Religion: egen ImmigrantPer = mean(Immigrant)
				
			**create a different variable for the bar chart
			
				gen ImmigvNative = 0
				replace ImmigvNative = ImmigrantPer if Immigrant==1
				replace ImmigvNative = 1 - ImmigrantPer if Immigrant==0
				
				
			**create a variable for year of arrival
			
				gen YearArriveA = yrimmiga
				recode YearArriveA 98/99=.
				
			
			**create a variable for years in country
				gen YearsinCountry = yrimmiga
				recode YearsinCountry 98/99=.
				replace YearsinCountry = YearsinCountry*-1+37
			
			**create a variable for year of arrival in broader categories
				gen YearArriveB = yrimmig
				recode YearArriveB 8/9=.
				label define YearArriveB 1 "Pre 1961" 2 "1961-70" 3 "1971-80" ///
				4 "1981-90" 5 "1991-95" 6 "1996-2001", replace
				label variable YearArriveB YearArriveB
				
			**create a variable for gender
			
				gen Male = sexp
				recode Male 1=1 2=0
				label define Male 1 "Male" 0 "Female"
				
			
**Removing all variables that I do not need, to keep file sizes manageable for R

keep caseid agep Birthplace Religion YearArriveA YearArriveB YearsinCountry Male Immigrant ImmigrantPer ImmigvNative

**Remove all cases of missing values (very few) on remaining variables

keep if Religion !=.
keep if Immigrant !=.

save "C:\Dropbox\Projects\Muslims\Data\Census\census2001full.dta", replace
outsheet using C:\Dropbox\Projects\Muslims\Data\Census\census2001full.csv, comma replace 		
				
				
**Removing all cases of Canadian born responents

keep if Birthplace !=0
**Remove all cases of missing values (very few) on remaining variables

keep if Birthplace !=.
keep if Religion !=.
keep if YearArriveA !=.
keep if YearArriveB !=.
keep if Immigrant !=.



save "C:\Dropbox\Projects\Muslims\Data\Census\census2001immigsonly.dta", replace
outsheet using C:\Dropbox\Projects\Muslims\Data\Census\immigsonly.csv, comma replace 

**Subsetting Data

			**Catholics
			
			keep if Religion == 1
			
			save "C:\Dropbox\Projects\Muslims\Data\Census\Catholics.dta", replace
			outsheet using C:\Dropbox\Projects\Muslims\Data\Census\Catholics.csv, comma replace 
			
			**Protstants and Other Christian
			
			use "C:\Dropbox\Projects\Muslims\Data\Census\census2001immigsonly.dta"
			
			keep if Religion == 2
			
			save "C:\Dropbox\Projects\Muslims\Data\Census\Protestants.dta", replace
						outsheet using C:\Dropbox\Projects\Muslims\Data\Census\Protestants.csv, comma replace 
			**Muslims
			
			use "C:\Dropbox\Projects\Muslims\Data\Census\census2001immigsonly.dta"
			
			keep if Religion == 3
			
			save "C:\Dropbox\Projects\Muslims\Data\Census\Muslims.dta", replace
			outsheet using C:\Dropbox\Projects\Muslims\Data\Census\Muslims.csv, comma replace 
			
			** Jews
			
			use "C:\Dropbox\Projects\Muslims\Data\Census\census2001immigsonly.dta", replace
			
			keep if Religion == 4
			
			save "C:\Dropbox\Projects\Muslims\Data\Census\Jews.dta", replace
			outsheet using C:\Dropbox\Projects\Muslims\Data\Census\Jews.csv, comma replace 
			
			**Buddhist
			
			use "C:\Dropbox\Projects\Muslims\Data\Census\census2001immigsonly.dta", replace
			keep if Religion == 5
			
			save "C:\Dropbox\Projects\Muslims\Data\Census\Buddhist.dta", replace
			outsheet using C:\Dropbox\Projects\Muslims\Data\Census\Buddhist.csv, comma replace 
			
			
			**Hindu/Sikhs
			
			use "C:\Dropbox\Projects\Muslims\Data\Census\census2001immigsonly.dta", replace
			
			keep if Religion == 6
			
			save "C:\Dropbox\Projects\Muslims\Data\Census\HinduSikh.dta", replace
			outsheet using C:\Dropbox\Projects\Muslims\Data\Census\HinduSikh.csv, comma replace 
			
			**Other (Non-Christian)
			
			use "C:\Dropbox\Projects\Muslims\Data\Census\census2001immigsonly.dta", replace
			
			keep if Religion == 7
			
			save "C:\Dropbox\Projects\Muslims\Data\Census\Other.dta", replace
			outsheet using C:\Dropbox\Projects\Muslims\Data\Census\Other.csv, comma replace 
			
			**No Religion
			
			use "C:\Dropbox\Projects\Muslims\Data\Census\census2001immigsonly.dta", replace
			
			keep if Religion == 8
			
			save "C:\Dropbox\Projects\Muslims\Data\Census\None.dta", replace
			outsheet using C:\Dropbox\Projects\Muslims\Data\Census\None.csv, comma replace 
	
*****IPSOS Data
	
	clear all
	
	set mem 500m
	

	use "C:\Dropbox\Projects\Muslims\Data\Ipsos\ipsos2006.dta", clear
	

	gen Year = 2006
	
	gen Male = pmgender
	recode Male 2=0
	
	gen Vismin = .
	
	gen Religion = q27
	recode Religion 5/6=5 7=6 8=7 9=.
	*1 "Catholic" 2 "Protestant" 3 "Muslim" 4 "Jewish" 5 "Hindu/Sikh" 6 "Other" 7 "None"
	
	gen ReligImp = .
	
	gen ChurchAtt = q26
	recode ChurchAtt 8=. 5/7=0 3/4=1 2=2 1=3
	*0 "Less than once a month" 1 "Less than once a week" 2 "Once a week" 3 "More than Once a week"
	
	gen GodPrayers = .

	
	gen HolyBook = .
	
	gen GayMarriage = q19
	recode GayMarriage 1=1 2=2 3=3 4=.
		
	gen Education = pmed
	recode Education 1/2=0 3=1 4=2 5=3 6=4 7=5 8=6 9=.
	*Education 0 <HS, 1 HS, 2 Some College, 3 College, 4 Some Univ, 5 Univ, 6 Grad/Prof Degree
	
	gen Immigrant = q23
	recode Immigrant 2=1 1=0
	
	gen YearsinCountry = .
	recode YearsinCountry 1=50 2=50 3=50 4=40 5=30 6=20 7=10 8/19=1
	**These are approximate, recoded to reduce very small n for very recent immigs
	**Given the recoding, the categories should be read as:
	**60 "60 or More" 50 "At least 50" 40 "At least 40" and so on...
	
	gen Birthplace = .
	recode Birthplace 1=5 2=6 3=6 4=6 5=6 6=3 7=3 8=4 9=1 10=2 11/15=5 16=.
	**Ipsos uses slightly different categories than StatsCan, referring to 
	**what Stats Can calls "South Asia" (i.e., India, Pakistan etc.) as "Central Asia."
	**The Categories are recoded to overlap with the Stats Can categories; that is:
	**1 "1.Middle East" 2 "2.South Asia" 3 "3.Africa" 4 "4.East Asia" 5 "5.Americas+" 6 "6.Europe"
	
	gen Age = .
	
	gen Income = .
	recode Income 31=.
	
	
	gen Employed = pmemp
	recode Employed 1/3=1 4=0 5=1 6=0 7=0 8=. 9=.
	**Variable for employed outside the home or not
	
	keep Year Male Vismin Religion ReligImp ChurchAtt GodPrayers HolyBook GayMarriage Education Immigrant YearsinCountry Birthplace Age Income Employed

	
	
	save "C:\Dropbox\Projects\Muslims\Data\Ipsos\ipsos2006ltd.dta", replace
	
	
	
	use "C:\Dropbox\Projects\Muslims\Data\Ipsos\ipsos2011.dta", clear
	
	gen Year = 2011
	
	gen Male = gender
	recode Male 2=0
	
	gen Vismin = d7
	recode Vismin 2=0

	gen Religion = d12
	recode Religion 5/6=5 7=6 8=7 9=.
	*1 "Catholic" 2 "Protestant" 3 "Muslim" 4 "Jewish" 5 "Hindu/Sikh" 6 "Other" 7 "None"
	
	gen ReligImp = d11
	recode ReligImp 1=3 2=2 3=1 4=0 5=.
	*0 "Not important at all" 1 "Not very important" 2 "Somewhat important" 3 "Very important"
	
	gen ChurchAtt = d14
	recode ChurchAtt 4=0 3=1 2=2 1=4 5=.
	*0 "Less than once a month" 1 "Less than once a week" 2 "Once a week" 3 "More than Once a week"
	
	gen GodPrayers = d15
	recode GodPrayers 1=1 2=0 3=.
	*0 "No does not answer prayers" 1 "Yes, Answers Prayers"
	
	gen HolyBook = d16
	recode HolyBook 1=1 2=0
	*0 "Holy Book is not revealed word of God" 1 "Holy Book is revealed word of God"
	
	gen GayMarriage = q26
	recode GayMarriage 1=1 2=2 3=3 4/5=.
		
	gen Education = educ
	recode Education 1/2=0 3=1 4=2 5=3 6=4 7=5 8=6 9=.
	*Education 0 <HS, 1 HS, 2 Some College, 3 College, 4 Some Univ, 5 Univ, 6 Grad/Prof Degree
	
	gen Immigrant = c1
	recode Immigrant 2=1 1=0
	
	gen YearsinCountry = c2
	recode YearsinCountry 1=50 2=50 3=50 4=40 5=30 6=20 7=10 8/19=0
	recode YearsinCountry .=99 if Immigrant==0
	

	**These are approximate, recoded to reduce very small n for very recent immigs
	**Given the recoding, the categories should be read as:
	**50 "At least 50" 40 "At least 40" and so on...to less than 10 = 0, and Cdn Born = 99
	
	gen Birthplace = c3
	recode Birthplace 1=5 2=6 3=6 4=6 5=6 6=3 7=3 8=4 9=1 10=2 11/15=5 16=.
	recode Birthplace .=0 if Immigrant ==0 & Year==2011
	**Ipsos uses slightly different categories than StatsCan, referring to 
	**what Stats Can calls "South Asia" (i.e., India, Pakistan etc.) as "Central Asia."
	**The Categories are recoded to overlap with the Stats Can categories; that is:
	label define Birthplace 0 "0.Canada" 1 "1.Middle East" 2 "2.South Asia" 3 "3.Africa" 4 "4.East Asia" 5 "5.Americas+" 6 "6.Europe", replace
	
	
	gen Age = age_val
	
	gen Income = hhincome
	recode Income 31=.
	
	
	gen Employed = d1
	recode Employed 1/3=1 4=0 5=1 6=0 7=0 8=. 9=.
	**Variable for employed outside the home or not
	
	keep Year Male Vismin Religion ReligImp ChurchAtt GodPrayers HolyBook GayMarriage Education Immigrant YearsinCountry ///
	Birthplace Age Income Employed
	
	
	gen GayMarriage01 = GayMarriage
	recode GayMarriage01 1/2=0 3=1
	
	save "C:\Dropbox\Projects\Muslims\Data\Ipsos\ipsos2011ltd.dta", replace
	
	

	append using C:\Dropbox\Projects\Muslims\Data\Ipsos\ipsos2006ltd.dta
	
	outsheet using C:\Dropbox\Projects\Muslims\Data\Ipsos\Merged0611.csv, comma replace 
	
	 save "C:\Dropbox\Projects\Muslims\Data\Ipsos\Merged0611.dta", replace
	
	**Analysis
	
	keep if Year==2011
	
	tab Religion, gen(Relig)
	rename Relig1 Catholic
	rename Relig2 Protestant
	rename Relig3 Muslim
	rename Relig4 Jewish
	rename Relig5 HinduSikh
	rename Relig6 Other
	rename Relig7 None

	factor ChurchAtt GodPrayers HolyBook ReligImp
	
	egen zChurchAtt = std(ChurchAtt)
	egen zGodPrayers = std(GodPrayers)
	egen zHolyBook = std(HolyBook)
	egen zReligImp = std(ReligImp)
	
	gen Religiosity_3i_84a = zGodPrayers *.7570 + zHolyBook *.7771 + zReligImp *.7582
	
	egen zReligiosity = std(Religiosity_3i_84a)
	egen Min = min(zReligiosity)
	replace zReligiosity = zReligiosity + Min*-1
	drop Min
	
	****Patterns of Missing Data?
	
	gen GayMarMiss = GayMarriage01
	recode GayMarMiss .=1 0/1=0
	
	logit  GayMarMiss Protestant Muslim Jewish HinduSikh Other None Education  Male Income Age
	
	**Answer: YES, not much, but not completely MCAR.  Socio Dems are measured without missing values, as a component of the 
	**standing web panel.
	
	**Ommitting missing values
	
	keep if Religion !=.
	keep if GayMarriage !=.
	keep if Religiosity !=.
	
	gen COUNTRIES_OF_BIRTH = 0
	
	recode Birthplace .=0 if Immigrant==0
	
	tab Birthplace, gen(Origin)
	rename Origin1 Canada
	rename Origin2 MiddleEast
	rename Origin3 SouthAsia
	rename Origin4 Africa
	rename Origin5 EastAsia
	rename Origin6 Americas
	rename Origin7 Europe
	
	label variable Canada "Canada"
	label variable MiddleEast "Middle East"
	label variable SouthAsia "South Asia"
	label variable Africa "Africa"
	label variable Europe "Europe"
	label variable EastAsia "East Asia"
	label variable Americas "Americas +"
	
	
	tab YearsinCountry, gen(YearsHere)
	rename YearsHere1 LessThan10
	rename YearsHere2 TentoTwenty
	rename YearsHere3 TwentytoThirty
	rename YearsHere4 ThirtytoForty
	rename YearsHere5 FortytoFifty
	rename YearsHere6 MorethanFifty
	rename YearsHere7 NativeBorn
	
	**interaction terms
	

	gen ReligCath = zReligiosity * Catholic
	gen ReligProt = zReligiosity * Protestant
	gen ReligMus = zReligiosity * Muslim
	gen ReligJew = zReligiosity * Jewish
	gen ReligHinduSikh = zReligiosity * HinduSikh
	gen ReligOther = zReligiosity * Other
	gen ReligNone = zReligiosity * None
	
	gen MusImmigrant = Muslim * Immigrant
	gen MusLessThan10 = Muslim * LessThan10
	gen MusTentoTwenty = Muslim * TentoTwenty
	gen MusTwentytoThirty = Muslim * TwentytoThirty
	gen MusThirtytoForty = Muslim * ThirtytoForty
	gen MusFortytoFifty = Muslim * FortytoFifty
	gen MusMorethanFifty = Muslim * MorethanFifty
	gen MusNativeBorn = Muslim * NativeBorn
	

	**Religiosity Models
	ologit GayMarriage Age Male  Protestant Muslim Jewish HinduSikh Other None
	estimates store ReligOnly
	
	ologit GayMarriage Age Male  Protestant Muslim Jewish HinduSikh Other None  zReligiosity
	estimates store Religiosity
	
	ologit GayMarriage Age Male  Protestant Muslim Jewish HinduSikh Other None  zReligiosity  ///
	ReligProt ReligMus ReligJew ReligHinduSikh ReligOther ReligNone
	estimates store FullRelig
	
	esttab ReligOnly Religiosity FullRelig using test.tex, replace b(3) ///
nogaps title(The Correlates of Muslim Opinion About Same-Sex Marriage, Abortion, and Government Intervention) ///
mtitles("Bloc 1" "Bloc 2"  "Bloc 3") nonumbers coeflabels(Age "Age" Male "Male" ///
Protestant "Protestant" Muslim "Muslim" Jewish "Jewish" HinduSikh "Hindu/Sikh" Other "Other Religion" None "No Religion" zReligiosity "Religiosity" ///
ReligProt "Protestant * Religiosity" ReligMus "Muslim * Religiosity" ReligJew "Jewish * Religiosity" ReligHinduSikh "Hindu/Sikh * Religiosity"  ///
ReligOther "Other * Religiosity" ReligNone "No Religion * Religiosity")  ///
pr2 se nodepvars  se(3) addnote("Source: Ipsos 2011") star(* 0.05)
	
	
	ologit GayMarriage Male Age  Protestant Muslim Jewish HinduSikh Other None  zReligiosity  MiddleEast SouthAsia Africa EastAsia Americas Europe
	estimates store CountryofOrigin
	
		esttab ReligOnly Religiosity CountryofOrigin using test.tex, replace b(3) ///
nogaps title(The Correlates of Muslim Opinion About Same-Sex Marriage, Abortion, and Government Intervention) ///
mtitles("Bloc 1" "Bloc 2"  "Bloc 3") nonumbers coeflabels(Age "Age" Male "Male" ///
Protestant "Protestant" Muslim "Muslim" Jewish "Jewish" HinduSikh "Hindu/Sikh" Other "Other Religion" None "No Religion" zReligiosity "Religiosity" ///
MiddleEast "Middle East" SouthAsia "South Asia" Africa "Africa" EastAsia "East Asia"  ///
Americas "Americas +" Europe "Europe")  ///
pr2 se nodepvars  se(3) addnote("Source: Ipsos 2011") star(* 0.05)
	
	
	gen MusYearsinCountry = Muslim * YearsinCountry
	
	gen EducMus = Education * Muslim
	gen ImmigMus = Birthplace * Muslim
	gen ImmigEduc = Immigrant * Education
	gen ImmigEducMus = Immigrant * Education * Muslim
	
	
	
	
		gen CdaEduc = Canada * Education
	gen MidEastEduc = MiddleEast * Education
	gen SouthAsiaEduc = SouthAsia * Education
	gen AfricaEduc = Africa * Education
	gen EastAsiaEduc = EastAsia * Education
	gen AmericasEduc = Americas * Education
	gen EuropeEduc = Europe * Education
	
	gen ForBornEduc = 0
	replace ForBornEduc = Education if Canada~=1
	gen NatBornEduc 
	
	gen EducCath = Education * Catholic
	gen EducProt = Education * Protestant
	gen EducMus = Education * Muslim
	gen EducJew = Education * Jew
	gen EducHinduSikh = Education * HinduSikh
	gen EducOther = Education * Other
	gen EducNone = Education * None