Design and Use of the IPUMS-International Data Series

http://international.ipums.org

Matt SobekMinnesota Population Center

sobek@pop.umn.edu

Overview

Processing

Dissemination system

Strengths and limitations

Users

IPUMS-International

END

https://international.ipums.orghttps://international.ipums.org

Matt SobekMinnesota Population Center

sobek@pop.umn.edu

What is IPUMS-International?

Census data – 1960 to present

Samples – 1 to 10%, nationally representative

Microdata – individual-level

Extract system – select variables – pooled data

Downloadable – anonymized

Integrated – consistent codes across time and place

Map of IPUMS Partners

Dark green = disseminating dataLight green = partners, not yet disseminating

83 countries

Current Countries in IPUMS

44 countries130 samples279 million persons

EgyptGhanaGuineaKenyaRwandaSouth AfricaUganda

ArmeniaCambodiaChinaIndiaIraqIsraelJordanKyrgyz Rep.MalaysiaMongoliaPalestinePhilippinesVietnam

ArgentinaBoliviaBrazilCanadaChileColombiaCosta RicaEcuadorMexicoPanamaUnited StatesVenezuela

AustriaBelarusFranceGreeceHungaryItalyNetherlandsPortugalRomaniaSloveniaSpainUnited Kingdom

Africa Asia Americas Europe

Countries in IPUMS Archive

BangladeshBotswanaCubaCzech RepublicDominican Rep.El SalvadorEthiopiaFijiGermanyGuatemalaHaiti

Honduras

IndonesiaLiberiaMadagascarMalawiMaliMauritiusNepalNicaraguaPakistanParaguayPeru

Puerto RicoSenegalSaint LuciaSierra LeoneSudanSwitzerlandTanzaniaThailandTurkmenistanUruguayZambia

IPUMS MicrodataRelation to head

Marital status Literacy Occupation

Relationship to head 130 Religion 54

Age 130 Language 33

Sex 130 Ethnicity 41

Marital status 129 Race 20

Age at first marriage 16 School attendance 105

Children ever born 91 Literacy 91

Children surviving 59 Education attainment 119

Mother's mortality status 16 Years of schooling 72

Country of birth 81 Employment status 119

Place of birth 90 Class of worker 120

Citizenship 67 Occupation 116

Year of immigration 22 Industry 116

Migration, international 53 Hours worked weekly 38

Migration, internal 101 Total income 24

Disability 32 Earned income 26

Availability of Selected Person Variables

(Number of samples)

Urban-rural status 89 Electricity 81

Geography, 1st level 120 Water 95

Geography, 2nd level 86 Sewage 76

Home ownership 107 Toilet 86

Number of rooms 102 Cooking fuel 39

Floor material 46 Telephone 57

Wall material 40 Television 45

Roof material 27 Computer 16

Living Area 20 Automobiles 42

Availability of Selected Household Variables

(Number of samples)

536 Integrated variables

10,600 Unharmonized variables

User Access

Application

• Scholarly and educational purposes

• Key: it must not be redistributed

Once approved, access to all data

Free

Making the IPUMS

Pre-processing

Integration

Dissemination

Making the IPUMS

Pre-processing

Integration

• Language translation • Reformatting• Error correction• Sampling• Confidentiality

Making the IPUMS

Pre-processing

Integration

• Language translation • Reformatting• Error correction• Sampling• Confidentiality

• Metadata • Data harmonization• Constructed variables

Census Questionnaire (Mexico 2000)

Water

Access

5. Number of Rooms

How many rooms are used for sleeping without counting hallways? _____ Write the number

Without counting the hallways or bathrooms how many total rooms are in this dwelling? Count the kitchen

_____Write the number

6. Access to water

Read all of the options until you get an affirmative answer. Circle only one answer

1 Running water inside the dwelling 2 Running water outside the dwelling but on the land 3 Running water from a public faucet or hydrant 4 Running water that is carried from another dwelling 5 Tanked in by truck 6 Water from a well, river, lake, stream or other

Answers 3, 4, 5, 6 continue with number 8

7. Water supply

How many days of the week is water available? Circle only one answer

1 Daily 2 Every third day 3 Twice a week 4 Once a week 5 Occasionally

Text of Census Questionnaire (Mexico 2000)

Water access

XML-Tagged Census Questionnaire (Mexico 2000)

Data Integration – Marital Status

MARST Marital Status

code label CN82A403 CO73A411 KN89A413 MX70A402 US90A425

100 SINGLE/NEVER MARRIED 1=never married 4=single 1=single 9=single 6=never married

200 MARRIED/IN UNION

210 Married (not specified) 2=married 2=married 3=monogamous 1=married

211 Civil 3=only civil

212 Religious 4=only religious

213 Civil and religious 2=civil and religious

214 Polygamous 3=polygamous

220 Consensual union 1=free union 5=free union

300 SEPARATED/DIVORCED 3=sep. or divorced

310 Separated 6=separated 8=separated 3=separated

321 Legally separated

322 De facto separated

330 Divorced 4=divorced 5=divorced 7=divorced 4=divorced

400 WIDOWED 3=widowed 5=widowed 4=widowed 6=widowed 5=widowed

999 UNKNOWN/MISSING 0=missing 6=unknown B=blank 1=unknown

China1982

Colombia1973

Kenya1989

Mexico1970

U.S.A.1990

Pernum Relate Age Sex Marst Chborn

1 head 46 male married n/a

2 spouse 44 female married 3

3 aunt 77 female widow 7

4 child 15 female single 0

5 child 13 female single n/a

6 child 11 male single n/a

Pernum Relate Age Sex Marst Chborn

1 head 46 male married n/a

2 spouse 44 female married 3

3 aunt 77 female widow 7

4 child 15 female single 0

5 child 13 female single n/a

6 child 11 male single n/a

Spouse’s

Mother’s Father’s

Family Interrelationship Variables

Location

 

 

 

 

 

 

2

1

0

0

0

0

Location

 

 

 

 

 

 

Location

 

 

 

 

 

 

0

0

0 0

0

0

2 1

1

1

2

2

(Simple household)

Pernum Relationship Age Sex Marst Chborn

1 head 53 female separated 6

2 child 28 male single n/a

3 child 22 male single n/a

4 child 21 male single n/a

5 child 25 female married 2

6 child-in-law 28 male married n/a

7 grandchild 3 male single n/a

8 grandchild 1 male single n/a

9 non-relative 32 female separated 2

10 non-relative 10 male single n/a

11 non-relative 5 female single n/a

Location

 

 

 

 

 

 

 

 

 

 

 

Location

 

 

 

 

 

 

 

 

 

 

 

Location

 

 

 

 

 

 

 

 

 

 

 

0

0

0

0

0

6

5

0

0

0

0

0

0

1

1

1

1

0

5

5

0

9

9

0

0

0

6

6

0

0

0

0

0

Spouse’s Father’sMother’s

IPUMS “Pointer” Variables(Complex household)

Family Interrelationship Pointers

13 censuses include data on location of parent or spouse

Agree Disagree

Spouse 99.5 0.5

Mother 98.7 1.3

Father 99.4 0.6

Mother 97.5 2.5

Father 98.7 1.3Under age 18

IPUMS Home Page

Variables Page

Variables Page

Variables Page

Sample Filtering

Variables Page

Unharmonized Variables

Variable Description(Marital status)

Comparability Discussion(Marital status)

Enumeration Text(Marital status)

Enumeration Text(Marital status, Cambodia)

Variable Codes(Marital status)

Variable Codes(Marital status)

Variable Codes(Marital status)

IPUMS Home Page

Extract Step 1 – Login

Extract Step 2 – Select Samples

Extract Step 3 – Select Variables

Extract Step 4 – Variable Options

Extract Step 4 – Select Cases

Age of spouse

Employment status of father

Occupation of father

Extract Step 4 – Attach Characteristics

Extract Step 5 – Customize Sample Sizes

Extract Step 5 – Customize Sample Sizes

Extract Step 5 – Customize Sample Sizes

Extract Step 6 – Submit

Download or Revise Extract

Key Strengths of the Census Samples

• Internationally comparable

Pool data across countries – integrated variables

Enable study of relatively small populations

• Large

• Temporal depth

Provide historical perspective

Key Strengths of the Census Samples

• Microdata

All of a person’s characteristics – multivariate analysis

• Hierarchical

Characteristics of everyone a person resided with

Cohabitation and family interrelationships

Limitations Due to Confidentiality

• Geography

20,000 population or larger

• Sensitive variables, very small categories

• Samples

Too small to answer some questions

Other Issues and Limitations

• Cross-sectional dataNot longitudinal

• User burdenInformation overload; culturally specific knowledge

Variable labels are insufficient

Academic field (%)

47 Economics

21 Demography

10 Sociology

22 Other

IPUMS Users

54% Graduate students

2200 registered users

67% multiple samples

45% multiple countries

Samples Extracted

17% 5 or more countries

Decade of Extracted Sample

1960s 11

1970s 14

1980s 16

1990s 30

2000s 29

Decade Percent

Most Frequently Extracted Countries

1. Mexico

2. Brazil

3. United States

4. Colombia

5. France

6. Chile

7. Ecuador

8. Vietnam

9. Kenya

10. Argentina

Most Frequently Extracted Variables

Relation to headAgeSexMarital statusEducational attainmentYears of schoolingSchool attendanceLiteracyEmployment statusClass of workerOccupation recodeIndustry recodeOccupationIndustryUrban-rural status

Country of birthNativity statusMigration status, 5 yearsChildren ever bornChildren survivingReligionOwnership of dwellingWaterElectricitySewageNumber of roomsToiletEarned incomeTotal incomeSpouse’s location in household

Median Age by CountryItaly 42 Chile 29 Kyrgyz Republic 22

Greece 39 Argentina 27 Mongolia 21

Austria 38 Israel 27 Philippines 21

Hungary 38 Brazil 25 Bolivia 20

Portugal 38 China 25 Egypt 20

Canada 37 Colombia 25 Jordan 20

France 37 Costa Rica 24 Ghana 19

Netherlands 37 Mexico 24 Cambodia 17

Slovenia 37 Panama 24 Guinea 17

Spain 37 South Africa 24 Iraq 17

United Kingdom 37 Ecuador 23 Kenya 17

Belarus 36 Malaysia 23 Palestine 17

United States 36 Venezuela 23 Rwanda 17

Romania 35 Vietnam 23 Uganda 15

Armenia 31 India 22

(Calculated from the most recent sample from each country.)

10 8 6 4 2 0 2 4 6 8 10

10 8 6 4 2 0 2 4 6 8 10

10 8 6 4 2 0 2 4 6 8 10

Population Pyramids

Palestine

IraqEgypt

10 8 6 4 2 0 2 4 6 8 10 10 8 6 4 2 0 2 4 6 8 10

Population Pyramids

Young(Uganda 2002)

Medium(Philippines 2000)

Old(USA 2005)

10 8 6 4 2 0 2 4 6 8 10

10 8 6 4 2 0 2 4 6 8 1010 8 6 4 2 0 2 4 6 8 10

Belarus1998

Cambodia1998

China1990

Population Pyramids

10 8 6 4 2 0 2 4 6 8 10

10 8 6 4 2 0 2 4 6 8 10 10 8 6 4 2 0 2 4 6 8 10 10 8 6 4 2 0 2 4 6 8 10

Population Pyramids

Mexico

1960 1990 2005

0

5

10

15

20

25

30

35

40

45

50

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005

Pe

rce

nt

in L

ab

or

Fo

rce

MexicoCosta Rica

Ecuador

Chile

Venezuela

Colombia

Brazil

Married Female Labor Force Participation in Latin America(age 18 to 65)

0

10

20

30

40

50

60

70

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

Pe

rce

nt

in L

ab

or

Fo

rce

Latin America

United States

Married Female Labor Force Participation:Latin America and U.S. (age 18 to 65)

0

10

20

30

40

50

60

70

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

Pe

rce

nt

in L

ab

or

Fo

rce

United States

MexicoCosta Rica

EcuadorChile

Venezuela

Colombia

Brazil

Married Female Labor Force Participation:Latin America and U.S. (age 18 to 65)

Compare Latin America to U.S. 40 years earlier

Married Female Labor Force Participation:Mexican-born Women, 1970-2000

0

10

20

30

40

50

60

70

1970 1975 1980 1985 1990 1995 2000

Pe

rce

nt

in L

ab

or

Fo

rce

Mexican-born Women in United States

Women in Mexico

Working-Age Population in the Labor Force, by Sex

0

10

20

30

40

50

60

70

80

90

100B

razi

l 19

60

Bra

zil 1

97

0B

razi

l 19

80

Bra

zil 1

99

1B

razi

l 20

00

Ch

ile 1

96

0C

hile

19

70

Ch

ile 1

98

2C

hile

19

92

Ch

ile 2

00

2

Co

lom

bia

19

64

Co

lom

bia

19

73

Co

lom

bia

19

85

Co

lom

bia

19

93

Co

sta

Ric

a 1

96

3C

ost

a R

ica

19

73

Co

sta

Ric

a 1

98

4C

ost

a R

ica

20

00

Ecu

ad

or

19

62

Ecu

ad

or

19

74

Ecu

ad

or

19

82

Ecu

ad

or

19

90

Ecu

ad

or

20

01

Me

xico

19

70

Me

xico

19

90

Me

xico

20

00

Ve

ne

zue

la 1

97

1V

en

ezu

ela

19

81

Ve

ne

zue

la 1

99

0

Ch

ina

19

82

Vie

tna

m 1

98

9V

ietn

am

19

99

Ke

nya

19

89

Ke

nya

19

99

So

uth

Afr

ica

19

96

So

uth

Afr

ica

20

01

Fra

nce

19

62

Fra

nce

19

68

Fra

nce

19

75

Fra

nce

19

82

Fra

nce

19

90

Un

ited

Sta

tes

19

60

Un

ited

Sta

tes

19

70

Un

ited

Sta

tes

19

80

Un

ited

Sta

tes

19

90

Un

ited

Sta

tes

20

00

Pe

rce

nt

of

Wo

rkin

g-A

ge

Po

pu

lati

on

Males Females Persons age 16 to 65.

Population Residing with an Elderly Person

0

5

10

15

20

25

30

1960

1970

1980

1991

2000

1973

1985

1993

1970

1990

2000

1989

1999

1996

2001

1982

1989

1999

1962

1968

1975

1982

1990

1960

1970

1980

1990

2000

Per

cen

t o

f to

tal

po

pu

lati

on

Elderly persons (age 65+) Non-elderly residing with an elderly person

Brazil Mexico KenyaColombia VietnamChinaS Africa France United States

Percent of elders in elder-head intergenerational families

0

10

20

30

40

50

1970 1975 1980 1985 1990 1995 2000

Per

cent

Argentina

Brazil

Chile

Colombia

Costa Rica

Ecuador

Kenya

Mexico

Philippines

Romania

Rwanda

Vietnam

South Africa

Uganda

Venezuela

Percent of elders in younger-head families

0

10

20

30

40

50

1970 1975 1980 1985 1990 1995 2000

Per

cent

Argentina

Brazil

Chile

Colombia

Costa Rica

Ecuador

Kenya

Mexico

Philippines

Romania

Rwanda

Vietnam

South Africa

Uganda

Venezuela

Trends in Intergenerational Families

Intergenerational families headed by the older generation are becoming more common in most countries, with exceptions mainly in Africa.

Intergenerational families headed by the younger generation—the configuration that suggests old-age support—are much rarer, and they are on the decline in most countries.

Persons with Completed Secondary Education:National Populations Versus Migrants to the United States

0

10

20

30

40

50

60

70

80

90

100

Brazil Chile Costa Rica Ecuador Mexico Vietnam Kenya South Africa

Pe

rce

nt

In home country, ca. 2000 Migrants to U.S. 1995-2000