IPUMS MicrodataRelation to head

Marital status Literacy Occupation

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

• Reformatting• Error correction• Sampling• Confidentiality

Making the IPUMS

Pre-processing

Integration

• Reformatting• Error correction• Sampling• Confidentiality

• Metadata • Data harmonization• Constructed variables

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

ChinaChina19821982

ColombiaColombia19731973

KenyaKenya19891989

MexicoMexico19701970

U.S.A.U.S.A.19901990

IPUMS Home 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

2000 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

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

MexicoMexicoCosta RicaCosta Rica

EcuadorEcuador

ChileChile

VenezuelaVenezuela

ColombiaColombia

BrazilBrazil

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 Latin AmericaAmerica

United United StatesStates

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 United StatesStates

MexicoMexicoCosta RicaCosta Rica

EcuadorEcuadorChileChile

VenezuelaVenezuela

ColombiaColombia

BrazilBrazil

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

Compare Latin Compare Latin America to U.S. America to U.S. 40 years earlier40 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 Mexican-born Women in United Statesin United States

Women in Women in MexicoMexico

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 intergenerational families

0

10

20

30

40

50

60

70

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 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