* This program reads the 1990 Philippines Census file *
* DATE: July 20, 1999.
* NAME: Yih-Jin Young
* PURPOSE:  THIS PROGRAM READS THE 1990 PHILIPPINES CENSUS FILE.
* DATA SOURCE: indo90.dat (SEE REFERENCE GUIDE FOR DETAILS).
* AND CREATES CONTEXTUAL FILES FOR THE 90 DATA.
* OUTPUT FILE: ICON90.POR.
* NUMBER OF VALID PROVINCE: ??.

set blanks=-9/undefined=nowarn/mxwarns=2000000.  
SET LENGTH=999999.
SET HEADER=OFF.

DATA LIST FILE= 'y:\philippines\data\census90\phil90.dat '/
 P1 1-2 P2 3-4 P3 5 P4 6-10 P5 11 P6 12-13 P7 14
 P8 15-16 P9 17-19 P10 20 P11 21 P12 22-23 P13 24-25
 P14 26 P15 27-28 P16 29-32 P17 33-36 P17A 33-34 P18 37-40
 P19 41-44 P19A 41-42 P20 45 P21 46 P22 47 P23 48-51 P23A 48-49 P24 52-55 
 P25 56-59 P25A 56 P26 60-62 P26A 60 P27 63 P28 64-67 P29 64
 P30 68-70 P30A 68 P31 71-74 P32 71-72 P33 73-74
 P34 75 P35 76 P36 77 P37 78-79 P38 80-81 P39 82 
 P40 83-84 P41 85-86 P42 92-96. 

RECODE P24 (5000 THRU 5999=5000)(6000 THRU 6999=6000).

VARIABLE LABELS
   P1	'Province'
   P2	'Municipality'	
   P3	'Urban/Rural'			
   P4	'Question Serial Number' 	
   P5	'Record Type' 
   P6	'LNO'			
   P7	'OV'				
   P8	'Relationship to Household'
   P9	'Age'		
  P10	'Sex'					
  P11	'Marital Status	'
  P12	'Religion'		
  P13	'Country'
  P14	'Disability'		
  P15	'Language/Dialect Spoken in Household'			  
  P16	'Mothers Usual Place of Residence at Persons Birth'
  P17	'Previous Residence'
  P17A  'Province of Previous Residence'  
  P18	'Date Moved to Current Residence'		
  P19	'Residence in 1985'
  P19A  'Province of Residence in 1985' 
  P20	'Ability to Speak Pilipino or Tagalog'	
  P21	'Literacy'	
  P22	'School Attendance'	
  P23	'Place of Schooling' 
  P23A  'Province of Schooling' 
  P24	'Highest Grade Completed'
  P25	'Usual Occupation'	
  P25A  'Usual Occupation, Major Category' 
  P26	'Industry Last Year'
  P26A  'Industry Last Year--Major Category' 
  P27	'Employment Status'		
  P28	'Occupation Last Week'
  P29	'Occupation Last Week--Major Category'	
  P30	'Industry Last Week'   	
  P30A	'Type of Industry Last Week'
  P31	'Place of Work'	
  P32	'Place of Work - Province'
  P33	'Place of Work, Mun'
  P34	'Available to Work'
  P35	'Look for Work'	
  P36   'Reason for Not Looking For Work'
  P37	'Number of Children Born Alive'	
  P38	'Number of Children Still Alive'
  P39	'Number of Children Born Alive with Last Year'
  P40	'Age at Marriage'	
  P41	'Dialect'		
  P42	'Weight for Individual'.

VALUE LABELS 
  P1 P17A P19A P23A P32 
	1	'Abra'
	2	'Agusan del Norte'
	3	'Agusan del Sur'
	4	'Aklan'
	5	'Albay'
	6	'Antique'
	7	'Basilan'
	8	'Bataan'
	9	'Batanes'
	10	'Batangas'
	11	'Benguet'
	12	'Bohol'
	13	'Bukidnon'
	14	'Bulacan'
	15	'Cagayan'
	16	'Camarines Norte'
	17	'Camarines Sur'
	18	'Camiguin'
	19	'Capiz'
	20	'Catanduanes'
	21	'Cavite'
	22	'Cebu'
	23	'Davao'
	24	'Davao del Sur'
	25	'Davao Oriental'
	26	'Eastern Samar'
	27	'Ifugao'
	28	'Ilocos Norte'
	29	'Ilocos Sur'
	30	'Iloilo'
	31	'Isabela'
	32	'Kalinga-Apayao'
	33	'La Union'
	34	'Laguna'
	35	'Lanao del Norte'
	36	'Lanao del Sur'
	37	'Leyte'
	38	'Maguindanao'
	39	'Manila'
	40	'Marinduque'
	41	'Masbate'
	42	'Misamis Occidental'
	43	'Misamis Oriental'
	44	'Mt. Province'
	45	'Negros Occidental'
	46	'Negros Oriental'
	47	'North Cotabato'
	48	'Nort-hern Samar'
	49	'Nueva Ecija'
	50	'Nueva Vizcaya'
	51	'Occidental Mindoro'
	52	'Oriental Mindoro'
	53	'Palawan'
	54	'Pampanga'
	55	'Pangasinan'
	56	'Quezon'
	57	'Quirino'
	58	'Rizal'
	59	'Romblon'
	60	'Samar'
	61	'Siquijor'
	62	'Sorsogon'
	63	'South Cotabato'
	64	'Southern Leyte'
	65	'Sultan Kudarat'
	66	'Sulu'
	67	'Surigao del Norte'
	68	'Surigao del Sur'
	69	'Tarlac'
	70	'Tawi-Tawi'
	71	'Zambales'
	72	'Zamboanga del Norte'
	73	'Zamboanga del Sur'
	77	'Aurora'
	74	'Metro Manila I'
	75	'Metro Manila II'
	76	'Metro Manila III'/
  P3 
	1 	'Urban'
	2 	'Rural'/
  P5	
	1	'Person Record'
	6 	'Housing Record'/
  P8
	1 	'Head'
	2 	'Spouse'
	3 	'Son'
	4 	'Daughter'
	5 	'Step Son'
	6 	'Step Daughter'	
	7 	'Son-in-law'
	8 	'Daughter-in-law'
	9 	'Grandson'
	10 	'Granddaughter'
	11 	'Father'
	12 	'Mother'
	13 	'Brother'
	14 	'Sister'
	15 	'Uncle'
	16 	'Aunt'
	17 	'Nephew'
	18 	'Niece'
	19 	'Other relatives'
	00 	'Non-relative'/
	P9	
	00	'Less than 1 year'
	01	'1 Year'
	99	'99 Years'
	100	'100 Years'
	129	'129 Years'/
	P10
	1 'Male'
	2 'Female'/
	P11
	1 'Single'
	2 'Married'
	3 'Widow'
	4 'Separated/Divorced'
	5 'Others'
	6 'Unknown'/
	P12	
	01	'Roman-Catholic'	
	02	'Aglipay'
	03	'Islam'	
	04	'Iglesia-Nicristo'		
	05	'Uccp	'
	06	'Buddhist'	
	07	'Latter-Day-Saint'	
	08	'Jehovahs-Witness'	
	09	'Luthrnchurch-Phi'	
	10	'Phil-Benevo-Miss'	
	11	'Seventh-Day-Adve'	
	12	'Bornagain-Christ'	
	13	'Phil-Episcopal	'
	14	'Presbyterian	'
	21	'Baptist-Conferen'	
	22	'Bible-Baptist	'
	23	'Southern-Baptist'	
	29	'Other-Baptists	'
	31	'Iglesia-Evangeli'	
	32	'Lutheran-Church'	
	33	'United-Methodist'	
	34	'Wesleyan-Church'	
	35	'Other-Methodists'	
	41	'Bible-Christ-Com'	
	42	'Assemblies-Ofgod'	
	43	'Christn-Missry	'
	44	'Four-Square-Gosp'	
	45	'Godworld-Mission'	
	46	'Nazarene-Church'	
	47	'Salvtn-Army-Phil'	
	49	'Othr-Evangelical'	
	50	'Othr-Protestants'	
	00	'None	'
	99	'Others'/
   P13
	0	'Filipino Not-Reported'
	1	'Chinese'
	2	'American'
	3	'Indonesian'
	4	'Indian'
	5	'Japanese'
	6	'Iranian'
	7	'Australian'
	8	'British'	
	9	'Afghan'	
	10	'Albanian'	
	11	'Algerian'
	12	'Angolan'
	13	'Antiguan'
	14	'Argentine'
	15	'Aruba'
	16	'Austrian'
	17	'Bahrain'
	18	'Bangladesh'
	19	'Belgian'
	20	'Bolivian'
	21	'Brazilian'
	22	'Bruneidarussalem' 
	23	'Bulgarian'
	24	'Burmese '
	25	'Canadian '
	26	'Cape-Verde' 
	27	'Chilean '
	28	'Colombian' 	
	29	'Costa-Rican' 
	30	'Cuban '
	31	'Czechoslovakian' 
	32	'Danes '
	33	'Dominican' 
	34	'Egyptian '
	35	'El-Salvador' 
	36	'Finn-Finnish' 
	37	'Fiji '
	38	'French' 
	39	'German '
	40	'Ghanian '	
	41	'Greek '	
	42	'Guam '
	43	'Guatemalan' 
	44	'Honduran '
	45	'Hongkong-Chinese'
	46	'Hungarian'
	47	'Icelander'
	48	'Irish'
	49	'Iraqi'
	50	'Israelite'
	51	'Italian'
	52	'Kampuchean'
	53	'Kenyan'
	54	'Korean'
	55	'Kuwaiti'
	56	'Jordanian'
	57	'Liberian'
	58	'Libyan'
	59	'Malayan'
	60	'Marshall-Islands' 
	61	'Mexican'
	62	'Monacan'
	63	'Moroccan'
	64	'Nepalese'
	65	'Dutch'
	66	'New-Zealander'
	67	'Nigerian'
	68	'Norwegian'
	69	'Pakistani'
	70	'Palau-Rep-Of'
	71	'Panamanian'
	72	'Papuan'
	73	'Paraguayan'
	74	'Peruvian'
	75	'Polish'
	76	'Portugeese' 
	77	'Timor-Portugeese' 
	78	'Puerto-Rican'
	79	'Romanian'
	80	'Arab'
	81	'Singapore'
	82	'Spanish'
	83	'Sri-Lankan'
	84	'Sudanese'
	85	'Swedish'
	86	'Swiss'
	87	'Syrian'
	88	'Taiwanese'
	89	'Thai'
	90	'Trust-Territory'
	91	'Tunisian'
	92	'Russian'
	93	'Uruguayan'
	94	'Venezuelan'
	95	'Vietnamese'
	96	'Zaire'
	97	'Zambian'
	98	'Rhodesian'
	99	'Others'/
  P14	1	'Blindness'
	2	'Deafness'	 
	3	'Muteness '
	4	'Deaf-Muteness' 
	5	'Speechimpairment' 
	6	'Mental-Illness' 
	7	'Mental-Retardation' 
	8	'Orthopedic-Handi' 
	9	'Multiple-Disabil '
	10	'Others'/
  P15 P41
	1	'Tagalog'
	2	'Cebuano'
	3	'Hiligaynon'
	4	'Ilocano'
	5	'Ibanag'
	6	'Pampanago'
	7	'Pangasinan'
	8	'Waray'
	9	'Bicol'
	10	'Maguindana'
	11	'Maranao'
	12	'Tausug'
	13	'Agta'
	14	'Agutaynon'
	15	'Aklanon'
	16	'Atta'
	17	'Badjao'
	18	'Bagobo'
	19	'Banuanon'
	20	'Batak'
	21	'Binisaya'
	22	'Binukid'
	23	'Bilaan'
	24	'Bolinao'
	25	'Bontoc'
	26	'Botolan'
	27	'Bukidnon'
	28	'Butuanon'
	29	'Cagayano'
	30	'Chavacano'
	31	'Cuyano'
	32	'Davaweno'
	33	'Dibabawon'
	34	'Dumagat'
	35	'Gaddang'
	36	'Ilanum'
	37	'Ilongot'
	38	'Inibaloi'
	39	'Itawis'
	40	'Itbayaten'
	41	'Itneg'
	42	'Iraya'
	43	'Isinai'
	44	'Isneg'
	45	'Ifugao'
	46	'Ivatan'
	47	'Kalagan'
	48	'Kalamianon'
	49	'Kalibugan'
	50	'Kalinga'
	51	'Kallahan'
	52	'Kankanai'
	53	'Kapul'
	54	'Kene'
	55	'Kinamigin'
	56	'Kinaray-A'
	57	'Kulaman'
	58	'Kuyonon'
	59	'Malaweg'
	60	'Mamanwa'
	61	'Mandaya'
	62	'Mangyan'
	63	'Manobo'
	64	'Mansaka'
	65	'Masbateno'
	66	'Molbog'
	67	'Negrito'
	68	'Obian'
	69	'Planan'
	70	'Palaweno'
	71	'Parauan'
	72	'Pullon-Mapun'
	73	'Romblon'
	74	'Sama'
	75	'Samar-Leyte'
	76	'Sangil'
	77	'Subanon'
	78	'Susigaonon'
	79	'T-Boli'
	80	'Tagakaulo'
	81	'Tag-Baneva'
	82	'Tagbanua'
	83	'Yokad'
	84	'Zambal'
	85	'Belgian'
	86	'Chinese'
	87	'Dutch'
	88	'English'
	89	'French'
	90	'German'
	91	'Hindi'
	92	'Indonesian'
	93	'Italian'
	94	'Japanese'
	95	'Spanish'
	96	'Thai'
	97	'Oth-Foreign-Dialect'
	98	'Oth-Localdialect'
	99	'Not-Stated'/
  P16 P17 P19 P23 P31
	0007	'Foreign Country'
	0008	'Same-city-Municipality'
	0009	'Unknown'
	9999	'Not reported'/
  P20 P21 P22 P34 P35
	1 	'Yes'
	2 	'No'/
	P24	
	0000	'No grade completed'
	0100	'Pre-school'
	1100	'Grade 1'
	1200	'Grade 2'
	1300	'Grade 3'
	1400	'Grade 4'
	1500	'Grade 5'
	1600	'Grade 6 and 7'
	2100	'1st year high school'
	2200	'2nd year high school'
	2300	'3rd year high school'
	2400	'4th year high school'
	3000    'Postsec-undergraduate'
	3100	'1st year college'
	3200	'2nd year college'
	3300	'3rd year college'
	3400	'4th year college'
	3500	'5th year college and older'
	5000    'Postsec graduate'
	6000    'Degree Holder'/
	P25A P29 
	1	'Government Officials'
	2	'Professionals'
	3	'Technicians'
	4	'Clerical and Related Workers'
	5	'Sales and Service Workers'
	6	'Agricultural/Forestry Workers'
	7 	'Craft Related Workers'
	8 	'Machine Equipment Operators and Laborers'
	9 	'Elementary Occupation'
	0    	'Special Occupation'/
	P27
	1 	'Employed'
	2 	'Unemployed'/
  P26A	P30A
	1 	'Agricultural, Fishing and Forest'
	2	'Mining and Quarrying'
	3	'Manufacturing'
	4	'Electricity, Gas and Waterworks' 
	5	'Construction'
	6	'Wholesale, Retail Trade'
	7	'Transportation,Warehousing,Communication'
	8	'Finance, Insurance, Real Estate'
	9	'Services'/
	P36	
	1 	'No Work Available'
	2 	'Waiting for Results'
	3 	'Temporarily Illed'
	4 	'Bad Weather'
	5 	'Rehire-Waiting'
	6 	'Too Young to Work'
	7	'Housekeepers'
	8	'Students'
	9 	'Other-Specified'/
	P37 P38 P40
	99	'Not Stated'/
        P39
	09  	'Not Stated'.
		
* PERSON *.
SELECT IF P5=1.

COMPUTE REGION=P1.
RECODE REGION
	(1=1)(2=10)(3=10)(4=6)(5=5)(6=6)(7=9)(8=3)
	(9=2)(10=4)(11=1)(12=7)(13=10)(14=3)(15=2)
	(16=5)(17=5)(18=10)(19=6)(20=5)(21=4)(22=7)
	(23=11)(24=11)(25=11)(26=8)(27=2)(28=1)
	(29=1)(30=6)(31=2)(32=2)(33=1)(34=4)(35=12)
	(36=12)(37=8)(38=12)(39=15)(40=4)(41=5)(42=10)
	(43=10)(44=1)(45=6)(46=7)(47=12)(48=8)(49=3)
	(50=2)(51=4)(52=4)(53=4)(54=3)(55=1)(56=4)
	(57=2)(58=4)(59=4)(60=8)(61=7)(62=5)(63=11)
	(64=8)(65=12)(66=9)(67=10)(68=11)(69=3)(70=9)
	(71=3)(72=9)(73=9)(77=6)(74=20)(75=20)(76=20).

VALUE LABELS REGION
  	1 'Ilocos Region'       7  'Central Visayas'  
 	2 'Cagayan Valley'	8  'Eastern Visayas'  
  	3 'Central Luzon'	9  'Western Mindanao'
  	4 'Southern Tagalog'	10 'Northern Mindanao'
  	5 'Bicol'     	        11 'Southern Mindanao'
  	6 'Western Visayas'	12 'Central Mindanao' 
 	15 'Manila'		20 'Metro Mania'.

missing values p1 to p42 (-9).   

***** CONVERTING PROV CODES TO EQUAL TO THE 70-80 MATCHED FILE*.
COMPUTE PROV=P1.
RECODE PROV (1=11)(2=12)(3=83)(4=13)(5=14)(6=15)(7=82)(8=16)
 (9=17)(10=18)(11=19)(12=21)(13=22)(14=23)(15=24)(16=25)(17=26)
 (18=27)(19=28)(20=29)(21=31)(22=32)(23=35)(24=36)(25=37)
 (26=71)(27=38)(28=39)(29=41)(30=42)(31=43)(32=44)(33=45)
 (34=46)(35=47)(36=48)(37=49)
 (38=33)(39=10)(40=52)(41=53)(42=54)(43=55)(44=56)(45=57)(46=58)
 (47=33)(48=72)(49=59)(50=61)(51=62)(52=63)(53=64)(54=65)(55=66)
 (56=67)(57=99)(58=68)(59=69)(60=73)
 (61=99)(62=74)(63=34)(64=51)(65=33)(66=75)
 (67=76)(68=77)(69=78)(70=75)(71=79)(72=82)(73=82)(74 THRU 76=10).

*CONSTRUCT CONTEXTUAL VARIABLES *.  
 
SELECT IF (PROV LT 99).
 
COMPUTE PROVINCE=PROV.
COMPUTE EDU490=0.

IF (P24 GE 2100 AND P24 LT 9999) EDU490=1.
 
 
COMPUTE MARRY190=0.
IF (P11=1) MARRY190=1.
 
 
COMPUTE CWORK=0.
IF (P27=1) CWORK=1.


compute wt=p42*(6013913)/(60559106).
weight by wt.

 
* PROP. OF WOMEN 15-34 GT PRIMARY EDUCATION *.
TEMPORARY.
SELECT IF (P9 GE 15 AND P9 LE 34 AND P10=2).
AGGREGATE OUTFILE='y:\philippines\data\contextuals\e490.sav'
 /BREAK=PROVINCE
 /E490 = MEAN (EDU490).
 
* proportion of women 15-24 who are single 15-24.
TEMPORARY.
SELECT IF (P9 GE 15 AND P9 LE 24 AND P10=2).
AGGREGATE OUTFILE='y:\philippines\data\contextuals\mar190.sav'
 /BREAK=PROVINCE
 /MAR190 = MEAN (MARRY190).
 
* PROPORTION OF CHILDREN IN LABOR FORCE 15-18 YEARS OLD *.
TEMPORARY.
SELECT IF (P9 GE 15 AND P9 LE 18).
AGGREGATE OUTFILE='y:\philippines\data\contextuals\chwk190.sav'
 /BREAK=PROVINCE
 /CHWK190 = MEAN (CWORK).


GET FILE='y:\philippines\data\contextuals\mar190.sav'.
EXECUTE.
SORT CASES BY PROVINCE.
SAVE OUTFILE= 'y:\philippines\data\contextuals\mar190.sav'.


GET FILE='y:\philippines\data\contextuals\e490.sav'.
EXECUTE.
SORT CASES BY PROVINCE.
SAVE OUTFILE= 'y:\philippines\data\contextuals\e490.sav'.


GET FILE='y:\philippines\data\contextuals\chwk190.sav'.
EXECUTE.
SORT CASES BY PROVINCE.
SAVE OUTFILE= 'y:\philippines\data\contextuals\chwk190.sav'.

GET FILE='y:\philippines\data\contextuals\mar190.sav'.
EXECUTE.

MATCH FILES /FILE=*
 /FILE='Y:\philippines\DATA\contextuals\chwk190.sav'
 /RENAME (province = d0)
 /DROP= d0.
EXECUTE.

MATCH FILES /FILE=*
 /FILE='Y:\philippines\DATA\contextuals\e490.sav'
 /RENAME (province = d0)
 /DROP= d0.
EXECUTE.

EXPORT OUTFILE='y:\philippines\data\contextuals\pcon90721.por'.

des var all.