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October 20, 1997

Economist says 'family cap' welfare policies may not work

Robert Fairlie


By Jennifer McNulty

A new study of welfare recipients across the country reveals that welfare mothers in states that offer larger benefit increases per additional child do not appear to be more likely to have another child than those in states with lower benefit increases per additional child. The study, which appears in the current issue of the Journal of Policy Analysis and Management (vol. 16, no. 4, fall 1997), suggests that recent efforts to hold down birthrates by capping welfare benefits may be misguided.

The study, entitled "The Effect of Incremental Benefit Levels on Births to AFDC Recipients," was coauthored by Robert Fairlie, an assistant professor of economics at UCSC, and Rebecca London, a visiting research associate at UCSC when the research was conducted and now a senior analyst with Berkeley Planning Associates in Oakland.

"There does not appear to be a relationship between the amount of the benefit increase and the birthrate among welfare recipients," said Fairlie.

The so-called "family cap" policy is one of the most hotly debated topics of welfare reform. Historically, all states provided increased monetary benefits to women who have additional children while receiving Aid to Families with Dependent Children (AFDC), the program recently replaced by Temporary Assistance to Needy Families (TANF). Many states have recently adopted "family caps," which eliminate those extra monetary benefits.

Fairlie and London's findings parallel a preliminary report by the state of New Jersey on its welfare reform efforts, which include a family cap that was implemented in 1992. Although the birth rate among women participating in a state-supported evaluation dropped from 11 percent in 1991 to 6 percent during the second year of the family cap, researchers concluded that "the significant drop in New Jersey's welfare birth rate could not be directly linked to the 'family cap.'" A similar decline in birthrates was evident among a control group of welfare recipients who continued to receive a grant increase with the birth of another child.

"Following on the heels of New Jersey's announcement, this study provides further evidence suggesting that it's quite likely that states that impose a family cap won't see a big drop in fertility," said Fairlie. "There doesn't seem to be a strong relationship between out-of-wedlock birthrates among welfare recipients and the additional monthly benefits they receive following the birth of each child."

Fairlie and London's study examined data from the U.S. Bureau of the Census gathered from 1990 to 1992. The data, part of the 1990 Panel of the Survey of Income and Program Participation (SIPP), provides detailed information on income levels and all forms of government assistance received by respondents. Fairlie and London did a state-by-state examination of benefits provided per number of children in search of a correlation between states that offer larger benefit increases and higher birthrates among welfare mothers.

"The only correlation we found was statistically insignificant," said Fairlie. "And the correlation disappeared once we included women with children who were not receiving welfare as a control group in our analysis." During the study, benefit increases for women who had a second child while receiving AFDC ranged from $24/month in Mississippi to $134/month in California.

Of about 15,000 women surveyed for more than two years during the SIPP data-collection process, about 1,000 were welfare recipients. "1990 was the first year that the Bureau of the Census deliberately focused on gathering information about female-headed households in the SIPP, so we had a relatively rich sample to pull from," said Fairlie, adding that he and London did numerous sensitivity checks to make sure their findings were holding up.

Results were similar among whites, African Americans, and never-married women, said Fairlie. Less consistent results were found among Hispanics and divorced or separated women, but the sample sizes among those groups were very small, said Fairlie.


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