Design and Use of the IPUMS-International Data Serieshttp://international.ipums.org Matt Sobek Minnesota Population Center

Overview Processing Dissemination system Strengths and limitations Users Summation IPUMS-International

END Matt Sobek Minnesota Population Center

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 data Light green = partners, not yet disseminating 83 countries

Current Countries in IPUMS 35 countries 111 samples 263 million persons Egypt Ghana Kenya Rwanda South Africa Uganda Cambodia China Iraq Israel Malaysia Palestine Philippines Vietnam Argentina Brazil Canada Chile Colombia Costa Rica Ecuador Mexico Panama United States Venezuela Austria Belarus France Greece Hungary Netherlands Portugal Romania Spain United Kingdom Most countries have multiple samples Africa Asia Americas Europe

IPUMS Microdata Relation 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) Water Access

Editable Census Questionnaire

Water access XML-Tagged Census Questionnaire

Data Integration – Marital Status China1982Colombia1973Kenya1989Mexico1970U.S.A.1990

PernumRelateAgeSexMarstChborn 1head46malemarriedn/a 2spouse44femalemarried3 3aunt77femalewidow7 4child15femalesingle0 5child13femalesinglen/a 6child11malesinglen/a PernumRelateAgeSexMarstChborn 1head46malemarriedn/a 2spouse44femalemarried3 3aunt77femalewidow7 4child15femalesingle0 5child13femalesinglen/a 6child11malesinglen/a Spouse’s Mother’sFather’s Family Interrelationship Variables Location (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

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 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 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 data Not longitudinal User burden Information overload; culturally specific knowledge Variable labels are insufficient Very large data

Academic field (%) 47Economics 21Demography 10Sociology 22Other 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 s s s s 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

Percent in Labor Force Mexico Costa Rica Ecuador Chile Venezuela Colombia Brazil Married Female Labor Force Participation in Latin America (age 18 to 65)

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

Percent in Labor Force United States Mexico Costa Rica Ecuador Chile 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, Percent in Labor Force Mexican-born Women in United States Women in Mexico

Percent of elders in intergenerational families

Percent in elder-head intergenerational families

Percent in younger-head families