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Trends in African-American Marriage Patterns. Steven Ruggles and Catherine Fitch Minnesota Population Center. Funded by the National Science Foundation and the National Institutes of Health. We have three big questions:. Why was there no marriage boom among blacks?

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trends in african american marriage patterns
Trends in African-American Marriage Patterns

Steven Ruggles and Catherine Fitch

Minnesota Population Center

Funded by the National Science Foundation and the National Institutes of Health

we have three big questions
We have three big questions:
  • Why was there no marriage boom among blacks?
  • Why did black marriage age rise so rapidly after 1970?
  • Why did the traditional gender pattern of marriage age reverse among blacks after 1990?
data integrated public use microdata series ipums usa
Data: Integrated Public Use Microdata Series (IPUMS-USA)

Harmonized census microdata spanning the period from 1850 to 2000 with user-friendly access, integrated comprehensive hypertext documentation makes analysis of long run change easy

although we have three nice questions we have fewer answers
Although we have three nice questions, we have fewer answers.
  • Absence of a black marriage boom:

–we have that one covered.

  • Rise of black marriage age 1970-1990:

–I will briefly summarize our pending proposal

  • Reversal of traditional gender pattern

–some preliminary results


To investigate differentials, we must shift our measures from median marriage age and marriage age distribution to percent of young people never married.

  • The indirect median age at marriage is unreliable in periods of rapid change.
  • It also doesn’t allow us to look at differentials between most population subgroups, since people change their characteristics as they age.

Here is how the indirect median is calculated:


The indirect median has been the principal measure of marriage age in the U.S. for a century, but it is now unreliable.With the rapid change in marriage patterns we cannot predict how many people will eventually marry, so estimates are increasingly biased upwards.Also, indirect median is no good for studying differentials in characteristics that change over the life course, like socioeconomic status.So, forget about marriage age: we will focus on percent of young people never-married.


Trend in percent never married is closely similar to trend in marriage age, but there is a slight bump in marriage age for black men from 1950 to 1970

Among black men, there was a marriage boom in every occupational group except for farming.
Conclusion 1:
  • After the war, blacks were forced off southern farms by mechanization and consolidation of sharecropping farms.
  • This resulted in massive dislocation and a rise of young men with no occupation.
  • Without the shift from farming into no occupation, there would have been a marriage boom.
  • There was no marriage boom for blacks because there was no economic boom for blacks.
2. What caused the extraordinary rise of

black marriage age after 1970?

hypotheses 1 male opportunity
Hypotheses: 1. Male opportunity
  • Marriage boom resulted from rising prosperity, job security, optimism (Glick and Carter 1958); declining male opportunities in 1970s and 1980s, especially among blacks, reversed the trend (Wilson 1987 and many others)
  • Increasing economic uncertainty (Oppenheimer 1988) and inequality (Gould and Paserman 2003) compounded the problem.
hypotheses 2 rising female opportunity
Hypotheses 2. Rising female opportunity
  • Growing economic opportunities for women increased marriage age
    • Decreased dependence on a spouse, opened alternatives to marriage (Cherlin 1980)
    • Undermined sex-role specialization and reduced the value of marriage (Becker 1981)
hypotheses continued
Hypotheses, continued
  • These theories predict a positive association between male economic opportunity and early marriage, and an inverse association for female opportunity.
  • Historically, these relationships have been strong, but recent evidence that the relationship may have reversed for women (e.g. Oppenheimer and Lew 1995)
hypotheses continued1
  • Or, maybe it is cultural change
  • McLanahan 2004: the New Feminism
Past studies that attempted to assess relationship between economic opportunities for men and women at the local level on marriage formation ran into data limitations, especially for blacks
fitch and ruggles research proposal
Fitch and Ruggles Research Proposal:
  • Use internal long-form data
success of ipums usa
Success of IPUMS-USA

User friendly access, harmonized codes, and integrated comprehensive hypertext documentation led to flood of census-based research:

  • 12,000 users, 75,000 extractions
  • 1,000 publications and working papers
  • IPUMS-based research is concentrated in the top U.S. journals: the most common venues are Demography, American Economic Review, Journal of Political Economy, American Sociological Review, Social Forces, and Quarterly Review of Economics
  • Census microdata is now the most widely used source in U.S. demographic research
other public use census microdata
Other Public-Use Census Microdata
  • Canada
    • 1971, 1976, 1981, 1986, 1991, 1996: varying designs, densities
    • 1996: Data Liberation Initiative led to an explosion in of usage in research and teaching
  • United Kingdom
    • 1991: 2% individuals, 0.5% householdshundreds of publications, thousands of users
    • 2001: double the densities because confidentiality assessments were too conservative.
cross national harmonization national academy of science recommendations
Cross-National Harmonization:National Academy of Science recommendations
  • “National and international funding agencies should establish mechanisms that facilitate the harmonization of data collected in different countries.”
  • “Cross national studies conducted within a framework of comparable measurement can be a substantially more useful tool for policy analysis than studies of single countries.”
  • “The scientific community, broadly construed, should have widespread and unconstrained access to the data.”

Source: Preparing for an Aging World: The Case for Cross-National Research (National Academy, 2001)

international census microdata harmonization
International Census Microdata Harmonization
  • 1959-1976: Omuece (Latin America)
    • 19 countries, censuses from 1960s and 1970s
    • Goal was standardized tabulations, but microdata was a byproduct
    • Lowest common denominator approach
    • Preserved extraordinary body of data and documentation
  • 1992-2003: PAU (Europe and North America)
    • 24 countries, 1990s and 2000s
    • Focus on the aging population
    • Complex variables not harmonized
ipums international goals
IPUMS-International goals
  • Follow the model of IPUMS-USA to produce harmonized data and documentation for multiple countries over the 1960-2004 period
  • Learn from successes and limitations of OMUECE and PAU
  • Lose no information, except when necessary to ensure confidentiality
  • Harmonize complex variables using a composite coding system
  • Document comparability issues thoroughly
  • Provide user-friendly web-based data access tools
  • Ensure confidentially through non-disclosure agreements and statistical protections
confidentiality issues
Confidentiality Issues
  • The USA and Mexican census microdata are completely public, and may be freely downloaded from the web.

Even though these data are entirely public and the U.S. data have been available for forty years, there has not been a single instance of a breach of confidentiality

  • IPUMS-International is restricted microdata, requiring researchers to commit to a non-disclosure agreement.
  • IPUMS-International also incorporates statistical disclosure controls (swapping, blurring, top-coding, etc.) to minimize risk to confidentiality.
two major points
Two major points:
  • Disclosure controls work: no one has ever been identified in 40 years of experience
  • Reducing barriers to access leads to widespread use and quality research
statistical disclosure control is effective
Statistical disclosure control is effective

“For a user of an outside database, attempting this sort of match with no opportunity for verification would prove fruitless. In the first place, the small degree of expected overlap would be a considerable deterrent to an intruder. However, if a match between the two files was attempted the large number of apparent matches would be highly confusing as an intruder would have no way of checking correct identification.”

--Angela Dale and Mark Elliott, Journal of the Royal Statistical Society

easy access encourages use
Easy access encourages use

Number of IPUMS-USA Registered Users since 1995

additional information at http ipums org
Additional information at

Steven Ruggles

[email protected]

Thank you.