Design and Use of the IPUMS-International Data Series

http://international.ipums.orghttp://international.ipums.org

Matt SobekMinnesota Population Center

sobek@pop.umn.edu

Overview

Processing

Dissemination system

Strengths and limitations

Users

Summation

IPUMS-International

END

Matt SobekMinnesota Population Center

sobek@pop.umn.edu

Census data samples

What is IPUMS-International?

Integrated

Public Use

Microdata

Series

– consistent codes and labels

– anonymized – users download

– individual-level

– 1960 to present – pooled data

IPUMS 1992 – Steve Ruggles

Bob McCaa

IPUMS-International 1999

Latin America, Europe, Extension

Background

Map of IPUMS Partners

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

83 countries

Current Countries in IPUMS

35 countries111 samples263 million persons

EgyptGhanaKenyaRwandaSouth AfricaUganda

CambodiaChinaIraqIsraelMalaysiaPalestinePhilippinesVietnam

ArgentinaBrazilCanadaChileColombiaCosta RicaEcuadorMexicoPanamaUnited StatesVenezuela

AustriaBelarusFranceGreeceHungaryNetherlandsPortugalRomaniaSpainUnited Kingdom

Most countries havemultiple samples

Africa Asia Americas Europe

IPUMS MicrodataRelation to head

Marital status Literacy Occupation

Selected Variable Topics

Basic demographics

Marriage

Family structure

Fertility and mortality

Migration

Ethnicity, language, religion

Education

Work

Income

Housing characteristics

475 Integrated variables

9052 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

Dissemination

• 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

Dissemination

Census Questionnaire (Mexico 2000)

WaterAccess

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

Editable Census Questionnaire

Water access

XML-Tagged Census Questionnaire

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

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)

Attached Characteristics

Spouse’s age

Mother’s location

Employment status

Mother’s Employment

status

Spouse’s location Age

IPUMS Home Page

Variables Page

Variable browsing

Variables Page

Variables Page

Sample Filtering

Variables Page

Unharmonized Variables

Variables Page

Variable Description

(Marital status)

Comparability Discussion

(Marital status)

Variable Description

(Marital status)

Enumeration Text(Marital status)

Enumeration Text(Marital status, Cambodia)

Variable Description(Marital status)

Variable Codes(Marital status)

Variable Codes(Marital status)

Variable Description(Marital status)

Unharmonized Input Variables(Marital status)

IPUMS Home Page

Extract Step 1 – Login

Extract Step 2 – Select Samples

Extract Step 3 – Select Variables

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

• Varying census years

• Cross-sectional dataNot longitudinal

• User burdenInformation overload; culturally specific knowledge

Variable labels are insufficient

• Very large data

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

Summation

• Living project

Democratized access

World’s largest collection of census data

200 samples in another 5 years

Ongoing nature of project limits us in some respects

Allows us to correct errors and improve

Most data are not otherwise accessible

• New opportunities for comparative research

Entire system is designed to encourage comparisons

We welcome your feedback

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

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 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 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

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

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