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The Effect of Kinship Placement Laws on Foster Children’s Well-Being

  • Iryna Hayduk EMAIL logo
Veröffentlicht/Copyright: 10. Februar 2017
The B.E. Journal of Economic Analysis & Policy
Aus der Zeitschrift The B.E. Journal of Economic Analysis & Policy Band 17 Heft 1

Abstract

This paper examines whether placing foster children with relatives, instead of unfamiliar caregivers, institutions, or group homes, increases the effectiveness of foster care and consequently improves children’s well-being. As a source of exogenous variation in kinship placement, I use recent major reform of foster care – state policies that prefer kin placement over other types of foster care settings. Using individual-level panel dataset, the Adoption and Foster Care Analysis and Reporting System (AFCARS), and employing difference-in-differences identification strategy, I find that in the short-run children exposed to law benefit from higher stability of placement and shorter length of foster care episode, but do not experience significant changes in either mental or physical health. In the longer term, kinship foster homes are more efficient in terms of improving safety and providing permanent home through discharge from foster care with a relative. Thus, given the effectiveness of kinship care, policymakers should focus on developing and implementing policies that further facilitate relatives’ involvement in foster care.

Keywords: child welfare; foster care; kinship placement; kinship placement law

Appendix

Table 9:

Summary statistics by type of placement, AFCARS foster care files.

Ever placed with a relativeNever placed with a relative
MeanStd. Dev.ObsMeanStd. Dev.Obs
Length of foster care episode, days695.518674.31083,460616.568734.8611,541,536
Stability of placement0.3960.489683,4600.4370.4961,541,536
Living with a relative0.2100.407643,2840.0600.2381,441,041
Reunification0.4160.493643,2840.6030.4891,441,041
Adoption0.1890.391643,2840.1780.3821,441,041
Guardianship0.1280.334643,2840.0210.1451,441,041
Reentry0.0860.280594,4160.1210.3261,191,918
Reentry due to caretaker’s abuse0.0150.121594,4180.0190.1371,191,923
Any mental health problem0.0430.203612,4770.0840.2781,339,080
Any physical health problem0.0950.293612,4640.0950.2941,339,009
Age at removal6.2255.083683,4608.4336.0041,541,536
Hispanic0.1850.388683,4600.1790.3841,541,536
Black0.3220.467683,4600.2710.4451,541,536
Female0.5090.500683,4600.4800.5001,541,536
Table 10:

Impact of kinship placement laws on kinship placement.

Ever placed with a relative
Model without time trends

(1)		Model with time trends

(2)
Exposed to law0.047***0.035*
(0.016)(0.019)
Mean of dependent variable0.3010.301
Observations2,224,9962,224,996

Notes: The analysis uses AFCARS foster care data files. Each column reports the results of a separate model that also controls for child’s age, race and gender; removal reason, birth parent’s age and marital status, state and year fixed effects. Model in Column 2 also controls for linear state-specific time trends. Robust standard errors, clustered at the state level, are reported in parentheses.

  1. denote significance at the 10 %

  2. denote significance at the 5 %

  3. denote significance at the 1 % levels, respectively.

Table 11:

Effect of kinship placement laws on number and composition of cases.

Dependent variableCoefficientMean of dependent variableObs
Panel A: Number of cases
log(# of children entered foster care)0.0487.938528
(0.036)
Panel B: Composition of children
Removal reason child-related
Alcohol abuse−0.002*0.0122,224,996
(0.001)
Drug abuse0.0010.0272,224,996
(0.003)
Disability−0.0010.0252,224,996
(0.002)
Behavior problem−0.0040.1632,224,996
(0.009)
Removal reason parent-related
Physical abuse−0.023**0.172,224,996
(0.010)
Sexual abuse−0.0040.0562,224,996
(0.004)
Neglect0.0310.5352,224,996
(0.039)
Alcohol abuse−0.0260.0712,224,996
(0.016)
Drug abuse−0.0090.1982,224,996
(0.024)
Parent died−0.0000.0072,224,996
(0.001)
Parent in jail0.0010.0632,224,996
(0.004)
No cope−0.0240.1812,224,996
(0.018)
Abandonment−0.0260.0542,224,996
(0.020)
Relinquishment0.0010.0112,224,996
(0.001)
Housing−0.0220.0922,224,996
(0.016)
Panel C: Composition of foster caregivers
Receives subsidy−0.0416612,079,822
(0.029)
Receives subsidy, kin placement−0.110**0.591542,204
(0.054)
Receives subsidy, all other placements−0.0170.6851,537,618
(0.025)
Subsidy amount−7.1227101,861,004
(43.007)
Subsidy amount, kin placement−50.366***216489,330
(17.915)
Subsidy amount, all other placements10.8808851,371,674
(56.305)
Older foster parent0.0070.1251,403,192
(0.005)
Older foster parent, kin placement0.0100.142442,605
(0.007)
Older foster parent, all other placements0.004117960,587
(0.007)

Notes: The analysis uses AFCARS foster care data files. Each coefficient is from the separate regression. Model in panel A, with the number of children entered foster care as a dependent variable, controls for state and year fixed effects, and state-specific linear time trends. Specifications in panel B, with one of the removal reason as a dependent variable, control for child’s age, race and gender; birth parents age and marital status, state and year fixed effects, and linear state-specific time trends. Specifications in panel C, additionally to controls in panel B, also include dummies for removal reason. Variable Older foster parent is equal to one if foster caregiver is over age 60 and zero otherwise. Robust standard errors, clustered at the state level, are reported in parentheses.

  1. denote significance at the 10 %

  2. denote significance at the 5 %

  3. denote significance at the 1 % levels, respectively.

Table 12:

Test for policy impact on spell completion.

By 2011, has missing data on end date, entered before 2010

(1)		By 2011, has missing data on end date, entered before 2009

(2)
Exposed to law−0.001−0.003
(0.007)(0.007)
Mean of dependent variable0.1970.063
Observations2,224,9962,224,996

Notes: The analysis uses AFCARS foster care data files. Each column reports the results of a separate model that also controls for child’s age, race and gender; removal reason, birth parent’s age and marital status, state and year fixed effects, and linear state-specific time trends. Sample includes all children that entered foster care system during the time period 1998–2009. Robust standard errors, clustered at the state level, are reported in parentheses.

  1. denote significance at the 10 %

  2. denote significance at the 5 %

  3. denote significance at the 1 % levels, respectively.

Table 13:

Hazard model estimate of the effect of law exposure on the probability of being discharged from foster care.

Hazard Model
Exposed to law0.088***
(0.026)
Mean of dependent variable641
Observations2,224,996

Notes: The analysis uses AFCARS foster care data files. The coefficient presented in the table is from a parametric hazard model with a Weibull distribution. Model controls for child’s age, race and gender; removal reason, birth parent’s age and marital status, state and year fixed effects, and linear state-specific time trends. Sample includes all children that entered foster care system during the time period 1998–2009. Robust standard errors, clustered at the state level, are reported in parentheses.

  1. denote significance at the 10 %

  2. denote significance at the 5 %

  3. denote significance at the 1 % levels, respectively.

Table 14:

Impact of kinship placement laws on permanency outcomes.

Discharged to live with a relative (1)Reunification (2)Adoption (3)Guardianship (4)
Exposed to law0.013**0.008−0.002−0.003
(0.006)(0.017)(0.007)(0.007)
Female0.004**−0.017***0.009***0.002***
(0.002)(0.003)(0.001)(0.001)
Exposed to law*Female−0.0030.011**−0.0040.001
(0.003)(0.006)(0.003)(0.001)
Mean of dependent variable0.1060.5460.1810.054
Observations2,084,3252,084,3252,084,3252,084,325

Notes: The analysis uses AFCARS foster care data files. Each column within each panel reports the results of a separate model that also controls for child’s age, race and gender; removal reason; birth parent’s age and marital status; state and year fixed effects, and linear state-specific time trends. Robust standard errors, clustered at the state level, are reported in parentheses.

  1. denote significance at the 10 %

  2. denote significance at the 5 %

  3. denote significance at the 1 % levels, respectively.

Table 15:

Impact of kinship placement laws on health, by child age and gender.

All children (1)Age<7 (2)7 ≤ Age<13 (3)Age ≥ 13 (4)
A: Mental Health
Exposed to law−0.012−0.004−0.007−0.022
(0.010)(0.006)(0.015)(0.020)
Girl−0.023***−0.009***−0.040***−0.024***
(0.002)(0.001)(0.003)(0.005)
Exposed to law*Girl0.008*−0.002−0.0030.026**
(0.004)(0.002)(0.005)(0.012)
Effect [p value of effect] for:
Girl−0.004−0.006−0.0100.004
[0.725][0.276][0.548][0.871]
Mean of dependent variable0.0980.0460.1330.149
Observations2,053,045970,847477,900604,298
B: Physical Health
Exposed to law−0.0030.006−0.005−0.010
(0.013)(0.017)(0.009)(0.014)
Girl−0.015***−0.013***−0.022***−0.018***
(0.002)(0.001)(0.002)(0.004)
Exposed to law*Girl0.009**−0.0050.012***0.030*
(0.005)(0.003)(0.004)(0.015)
Effect [p value of effect] for:
Girl0.0060.0010.0070.020
[0.658][0.935][0.504][0.278]
Mean of dependent variable0.1120.1270.1070.088
Observations2,052,965970,866477,867604,232

Notes: The analysis uses AFCARS foster care data files. Each column within each panel reports the results of a separate model that also controls for child’s age, race and gender; removal reason; birth parent’s age and marital status; state and year fixed effects, and linear state-specific time trends. P-value reported in the brackets is associated with the null hypothesis that the effect is zero for girls. Robust standard errors, clustered at the state level, are reported in parentheses.

  1. denote significance at the 10 %

  2. denote significance at the 5 %

  3. denote significance at the 1 % levels, respectively.

Acknowledgments

I thank Aimee Chin, Chinhui Juhn, Andrew Zuppann, an anonymous referee, and participants at the Eastern Economic Association Conference, Fourteenth Annual Missouri Economics Conference, Midwest Economics Association Conference, the Ohio Association of Economists and Political Scientists 74th Annual Conference, Stata Texas Empirical Microeconomics Conference, the University of Houston graduate research workshop for helpful comments and suggestions. The data used in this paper were made available by the National Data Archive on Child Abuse and Neglect, Cornell University, Ithaca, NY, and have been used with permission. Data from the Adoption and Foster Care Analysis and Reporting System (AFCARS) were originally collected by the Children’s Bureau and funded by the Children’s Bureau, Administration on Children, Youth and Families, Administration for Children and Families, U.S. Department of Health and Human Services. The collector of the original data, the funder, the Archive, Cornell University and their agents or employees bear no responsibility for the analyses or interpretations presented here.

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Published Online: 2017-2-10

© 2017 Walter de Gruyter GmbH, Berlin/Boston

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  2. The Market Value of R&D in Emerging Economies: Evidence from India
  3. Are You What You Eat? Healthy Behaviour and Risk Preferences
  4. The Impacts of Rural Property Rights on Urban Unemployment, Wage Inequality, and Welfare in Developing Countries
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  6. Information Acquisition in Vertical Relations
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  8. Characteristics and Employment of Applicants for Social Security Disability Insurance over the Business Cycle
  9. Preferences Toward Leniency under Mandatory Criminal Sentencing Guidelines: Role-in-the-Offense Adjustments for Federal Drug Trafficking Defendants
  10. The Effect of Kinship Placement Laws on Foster Children’s Well-Being
  11. Are Immigrants in Favour of Immigration? Evidence from England and Wales
  12. Competition, Product Innovation and Licensing
  13. The Impact of Educational Mismatches on Wages: The Influence of Measurement Error and Unobserved Heterogeneity
  14. Education Outcomes of Children of Asian Intermarriages: Does Gender of the Immigrant Parent Matter?
  15. Letters
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https://doi.org/10.1515/bejeap-2016-0196
Schlagwörter für diesen Artikel
child welfare; foster care; kinship placement; kinship placement law

Artikel in diesem Heft

  1. Research Articles
  2. The Market Value of R&D in Emerging Economies: Evidence from India
  3. Are You What You Eat? Healthy Behaviour and Risk Preferences
  4. The Impacts of Rural Property Rights on Urban Unemployment, Wage Inequality, and Welfare in Developing Countries
  5. Lobbying as a Guard against Extremism
  6. Information Acquisition in Vertical Relations
  7. What Extent of Welfare Loss is Caused by the Disparity between Perceived and Scientific Risks? A Case Study of Food Irradiation
  8. Characteristics and Employment of Applicants for Social Security Disability Insurance over the Business Cycle
  9. Preferences Toward Leniency under Mandatory Criminal Sentencing Guidelines: Role-in-the-Offense Adjustments for Federal Drug Trafficking Defendants
  10. The Effect of Kinship Placement Laws on Foster Children’s Well-Being
  11. Are Immigrants in Favour of Immigration? Evidence from England and Wales
  12. Competition, Product Innovation and Licensing
  13. The Impact of Educational Mismatches on Wages: The Influence of Measurement Error and Unobserved Heterogeneity
  14. Education Outcomes of Children of Asian Intermarriages: Does Gender of the Immigrant Parent Matter?
  15. Letters
  16. Endogenous Leadership in Tax Competition: A Combination of the Effects of Market Power and Strategic Interaction
  17. Can Catastrophic Long-Term Care Insurance Policies Increase Private Insurance Coverage and Reduce Medicaid Expenditure?
  18. Getting Girls to Schools! – Assessing the Impacts of a Targeted Program on Enrollment and Academic Performance
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