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Trends in African-American Marriage Patterns

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Title: Trends in African-American Marriage Patterns


1
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
2
We have three big questions
  1. Why was there no marriage boom among blacks?
  2. Why did black marriage age rise so rapidly after
    1970?
  3. Why did the traditional gender pattern of
    marriage age reverse among blacks after 1990?

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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 http//ipums.org
10
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

11
  • 1. Why was there no black marriage boom?

12
Marriage age distribution No marriage boom for
black men
13
Virtually no marriage boom for black women
14
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 doesnt 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

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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.
17
Note SMAM is even worse.
18
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
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  • Among white men, there was a marriage boom in
    every occupational group.

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  • Among black men, there was a marriage boom in
    every occupational group except for farming.

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  • 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.

25
  • 2. What caused the extraordinary rise of
  • black marriage age after 1970?

26
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.

27
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)

28
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)

29
Hypotheses-continued
  • Or, maybe it is cultural change
  • McLanahan 2004 the New Feminism

30
  • 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

31
Fitch and Ruggles Research Proposal
  • Use internal long-form data

32
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

33
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.

34
Cross-National HarmonizationNational 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)

35
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

36
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

37
Countries participating in IPUMS-International
Region Country
Africa Ghana, Kenya, Madagascar, Uganda
Americas Argentina, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Venezuela, USA
Asia China, Tajikistan, Turkmenistan, Vietnam, Mongolia
Europe Austria, Belarus, Bulgaria, Czech Republic, France, Germany, Greece, Hungary, Netherlands, Portugal, Romania, Russia, Slovenia, Spain, the United Kingdom
Middle East Israel, Palestinian Authority
38
Ipums-International Countries
39
IPUMS-Latin AmericaCensuses included in Round I
(1999-2004)

INEGI-Mexico 1960, 1970, 1990, 2000
DANE-Colombia 1964, 1972, 1985, 1993
IBGE-Brazil 1960, 1970, 1980, 1991, 2000
40
Censuses included in Round II (2003-2008)
Argentina 1960, 1970, 1980, 1991, 2001
Bolivia 1976, 1992, 2001
Chile 1960, 1970, 1982, 1992, 2002
Costa Rica 1963, 1973, 1984, 2000
Dominican Republic 1960, 1970, 1981, 1993, 2004
Ecuador 1962, 1974, 1982, 1990, 2001
El Salvador 1961, 1971, 1992, 2002
Guatemala 1964, 1973, 1981, 1994, 2002
Honduras 1961, 1974, 1988, 2001
Nicaragua 1971, 1995
Panama 1960, 1970, 1980, 1990, 2000
Paraguay 1962, 1972, 1982, 1992, 2002
Peru 1981, 1993, 2003
Puerto Rico 1960, 1970, 1980, 1990, 2000
Venezuela 1961, 1971, 1981, 1990, 2001
41
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.

42
Users must agree to
  • Maintain the confidentiality of persons,
    households, and other entities. Any attempt to
    ascertain the identity of persons or households
    from the microdata is prohibited. Alleging that
    a person or household has been identified is also
    prohibited.
  • Implement security measures to prevent
    unauthorized access to census microdata. Under
    IPUMS-International agreements with collaborating
    agencies, redistribution of the data to third
    parties is prohibited.
  • Use the microdata for the exclusive purposes of
    scholarly research and education. Researchers
    are not permitted to use the microdata for any
    commercial or income-generating venture.
  • Report all publications based on these data to
    IPUMS-International, which will in turn pass the
    information on to the relevant national
    statistical agencies.

43
Application procedures
  • Researchers must propose a research project that
    demonstrates a scientific need for access to the
    microdata.
  • Each application for access is individually
    evaluated by senior staff.
  • Once an application is approved, the license and
    user password is activated, allowing controlled
    access to data.
  • Penalties for violating the license include
    revocation of the license, recall of all
    microdata acquired, filing a motion of censure to
    the appropriate professional organizations, and
    civil prosecution under the relevant national or
    international statutes.

44
IPUMS-International statistical confidentiality
protections
  • Suppression of detailed geographic identifiers.
  • Swapping an undisclosed fraction of records from
    one administrative district to another to make
    positive identification of individuals
    impossible.
  • Randomizing the sequence of households within
    districts to disguise the order in which
    individuals were enumerated.
  • Combining codes that reveal sensitive
    characteristics or identify very small population
    subgroups (e.g., grouping together small ethnic
    categories).
  • Top coding, bottom coding, and rounding
    continuous variables to prevent identification.
  • Additional protections as requested by national
    authorities.

45
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

46
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

47
Easy access encourages use
Number of IPUMS-USA Registered Users since 1995
48
Additional information at http//ipums.org
Thank you.
  • Steven Ruggles
  • ruggles_at_pop.umn.edu
  • http//ipums.org
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