National Academies Press: OpenBook

Measuring Poverty: A New Approach (1995)

Chapter: Migration Effects

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Suggested Citation:"Migration Effects." National Research Council. 1995. Measuring Poverty: A New Approach. Washington, DC: The National Academies Press. doi: 10.17226/4759.
Page 346
Suggested Citation:"Migration Effects." National Research Council. 1995. Measuring Poverty: A New Approach. Washington, DC: The National Academies Press. doi: 10.17226/4759.
Page 347
Suggested Citation:"Migration Effects." National Research Council. 1995. Measuring Poverty: A New Approach. Washington, DC: The National Academies Press. doi: 10.17226/4759.
Page 348

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THE POVERTY MEASURE AND AFDC 346 reduction in work resulting from the disincentives embedded in assistance programs (see Danziger, Haveman, and Plotnick, 1981, and Moffitt, 1992, for extensive literature reviews on the subject). Although evidence shows that AFDC reduces the number of hours worked by single mothers, the estimates of those reductions vary among studies—from 1 to 10 hours per week. Moffitt (1992), in his review of the literature, concludes that "there is still considerable uncertainty regarding the magnitude of the effects." Moffitt (1992) points out that there is very little research on the effects of in-kind assistance on labor supply.8 He also notes the importance of exploring the effects of multiple assistance programs; however, these effects are difficult to model, and little work has been done in the area. Family Structure Decisions Much of the literature on family structure focuses on whether AFDC encourages the formation of single-parent families headed by women. Since benefits are targeted to mothers with children and no spouse present, they may provide incentives to delay marriage or remarriage, to obtain a divorce, or to have children outside of marriage. Early work looking at the effect of AFDC on the increase in female-headed families is extremely mixed (see the summary in Groeneveld, Hannan, and Tuma, 1983). Studies in the 1980s, however, show more consistent evidence of an effect (see Danziger et al., 1982; Ellwood and Bane, 1985; Hoffman and Duncan, 1988; Moffitt, 1992). There is also some evidence of an effect of AFDC benefit levels on the probability that a female head lives independently rather than in a larger family (see Ellwood and Bane, 1985; Hutchens, Jakubson, and Schwartz, 1989). Extensive research has been done on the effect of AFDC on illegitimacy. The work has studied whether the existence of public assistance increases the chances that babies will be born to unmarried women since a woman no longer needs a husband to help support a child. The work has also considered whether the existence of public assistance increases the likelihood that a woman will have a child in order to become eligible for benefits at all or have another child in order to receive additional benefits. The evidence on this issue in the literature is inconclusive: some studies find effects for some groups (e.g., white or black teenagers), and others find no effects for the same groups (see Duncan and Hoffman, 1990; Ellwood and Bane, 1985; An, Haveman, and Wolfe, 1991; Lundburg and Plotnick, 1990; Plotnick, 1990). Migration Effects The extent to which the wide variation in AFDC benefit levels across states influences patterns of interstate migration is of 8 See Fraker and Moffitt (1988) on the disincentive effects of the Food Stamp Program on the labor supply of female heads. Blank (1989), Moffitt and Wolfe (1990), and Winkler (1989) have analyzed the labor supply effects of the Medicaid program on the Medicaid- eligible population.

THE POVERTY MEASURE AND AFDC 347 particular relevance to the issue of a nationwide minimum benefit standard. Hence, we considered it in some detail. Substantial cross-state differentials in AFDC benefits have existed since the inception of the AFDC program, but they have created greater policy concern since residency requirements were ruled unconstitutional in 1969. In particular, policy makers (particularly in high-benefit states) have worried that their states attract welfare recipients, thereby increasing the burden on taxpayers. A simple comparison of the expected income available to AFDC- eligible families in highand low-benefit states clearly indicates that such families can receive more income in a high-benefit state, which should create an incentive for them to relocate. Since the same states have generally remained high- or low-benefit states, if such migration occurs, it should have been steadily occurring in about the same regional patterns throughout the past 25 years. There are, however, at least three reasons why such an effect might be small or not exist at all. First, moving costs money. Not only are there actual transportation costs associated with moving, but families that migrate will often have to pay a security deposit for a new apartment, experience some transitional time during which they are neither working nor on AFDC, and bear the myriad of costs associated with relocation to a new city and residence. Low-income families may be least able to bear these moving costs. Second, families—and particularly low-income women—may lack information about their income opportunities in distant state locations. States do not generally advertise their AFDC benefit levels, and unless women have other sources of information (such as friends or relatives in another location), they may have only a hazy idea about alternative benefit levels. Third, relocation decisions are affected by many things other than income expectations. In particular, especially for low-income women with children, there may be substantial nonmonetary costs to moving. The presence of family and friends in their current location may provide many benefits: friends and family can provide free baby-sitting services, can be a source of shared resources in hard economic times, and can be an important source of psychological support. In addition, women with children might be quite risk- averse about relocating their children to an unknown low-income neighborhood, with concerns about school, crime, and gangs. For many women, these nonmonetary costs might be large enough that they completely swamp any differences in expected income levels. These arguments indicate that the expected effects of AFDC benefit levels on migration behavior among low-income women with children are probably small, at least in part because this is a population that one would expect to be less mobile than many others. On the margin, however, one may still expect that AFDC benefits would have a positive effect on migration probabilities. In order to measure the size of any welfare-induced migration, one ideally

THE POVERTY MEASURE AND AFDC 348 would have longitudinal data that track family location decisions. The data would also contain information on women's expectations and their economic opportunities in alternative locations, including not only what they know about alternative AFDC benefit levels in different locations, but also what they know about wage and employment opportunities. The need to have control variables available on non-AFDC economic opportunities is particularly important, since state AFDC benefit levels are positively correlated with state income and wage levels. (This is not surprising, given that only high-income states can afford to pay high AFDC benefits and that only states with high wage levels can pay high AFDC benefits without creating large work disincentives.) Finally, the data would contain information on whether women have friends, family, or any other source of support or contacts within alternative state locations. (For example, knowing if a woman or her parents have ever lived in another state would be one way of controlling for the nonmonetary costs of choosing a different location.) Unfortunately, a national data set with such information does not exist. The empirical research has been based on much more limited data, and, as a result, the quality of most the analyses is suspect (see Moffitt, 1992, for a review of the literature). Despite the problems, however, two conclusions are warranted: migration rates among AFDC recipients are quite low, and there is a small positive effect of AFDC benefits on the probability of migrating to (or not migrating out of) a high-benefit state (see, e.g., Blank, 1988; Clark, 1988, 1990, 1992; Gramlich and Laren, 1984; however, Peterson and Rom, 1989, find larger effects). The results are convincing not because any one of the studies is very well done, but because studies done in different ways with very different types of errors all point in the same direction. The research suggests that welfare-induced migration should be a second- order concern for policy makers. For states that have large populations very close to each other, large benefit differences may indeed induce a migration flow. However, on average, the effects of AFDC benefits on migration are small and movement among the AFDC population is infrequent. The fact that different states have had long-term AFDC benefit differentials that are very large and have been very large for many years is perhaps further evidence that migration effects are hard to discern in the data. Although states may talk about this problem, high-benefit states have not been concerned enough about it (with a few exceptions) to cut their benefits relative to other states. There is a lot that is not known about migration effects. There is little or no evidence on the propensity to use AFDC by recent migrants in comparison with natives in a state; on the comparative duration of their AFDC spells if they do become recipients; or on the effects of AFDC benefits on inducing families not currently eligible for AFDC to migrate to a state (i.e., whether people think about "potential safety net" issues). In addition, the growing

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Measuring Poverty: A New Approach Get This Book
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Each year's poverty figures are anxiously awaited by policymakers, analysts, and the media. Yet questions are increasing about the 30-year-old measure as social and economic conditions change.

In Measuring Poverty a distinguished panel provides policymakers with an up-to-date evaluation of:

  • Concepts and procedures for deriving the poverty threshold, including adjustments for different family circumstances.
  • Definitions of family resources.
  • Procedures for annual updates of poverty measures.

The volume explores specific issues underlying the poverty measure, analyzes the likely effects of any changes on poverty rates, and discusses the impact on eligibility for public benefits. In supporting its recommendations the panel provides insightful recognition of the political and social dimensions of this key economic indicator.

Measuring Poverty will be important to government officials, policy analysts, statisticians, economists, researchers, and others involved in virtually all poverty and social welfare issues.

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