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The Dynamic Relationship between Low Birthweight and Induced Abortion in New York City: An Aggregate Time-Series Analysis

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  • Theodore Joyce
  • Michael Grossman

Abstract

We use a vector autoregression to examine the dynamic relationship between the race-specific percentage of pregnancies terminated by induced abortion and the race-specific percentage of low-birthweight births in New York City. With monthly data beginning in 1972, we find that induced abortion explains low birthweight for blacks, but not for whites. There is no evidence of feedback from low birthweight to induced abortion. Simulations based on the model reveal that an unanticipated decrease in the percentage of pregnancies terminated by induced abortion results in an increase in the rate of low-birthweight births among blacks. The findings suggest that restrictions on legalized abortion in New York City would worsen birth outcomes among blacks.

Suggested Citation

  • Theodore Joyce & Michael Grossman, 1989. "The Dynamic Relationship between Low Birthweight and Induced Abortion in New York City: An Aggregate Time-Series Analysis," NBER Working Papers 3211, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:3211
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    References listed on IDEAS

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    1. Godfrey, Leslie G, 1978. "Testing for Higher Order Serial Correlation in Regression Equations When the Regressors Include Lagged Dependent Variables," Econometrica, Econometric Society, vol. 46(6), pages 1303-1310, November.
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    3. Michael Grossman & Steven Jacobowitz, 1981. "Variations in Infant Mortality Rates among Counties in the United States: The Roles of Social Policies and Programs," NBER Working Papers 0615, National Bureau of Economic Research, Inc.
    4. Backus, David, 1986. "The Canadian-U.S. Exchange Rate: Evidence from a Vector Autoregression," The Review of Economics and Statistics, MIT Press, vol. 68(4), pages 628-637, November.
    5. Grossman, Michael & Joyce, Theodore J, 1990. "Unobservables, Pregnancy Resolutions, and Birth Weight Production Functions in New York City," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 983-1007, October.
    6. Cooley, Thomas F. & Leroy, Stephen F., 1985. "Atheoretical macroeconometrics: A critique," Journal of Monetary Economics, Elsevier, vol. 16(3), pages 283-308, November.
    7. Leamer, Edward E., 1985. "Vector autoregressions for causal inference?," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 22(1), pages 255-304, January.
    8. Theodore Joyce & Michael Grossman, 1990. "Pregnancy wantedness and the early initiation of prenatal care," Demography, Springer;Population Association of America (PAA), vol. 27(1), pages 1-17, February.
    9. Lutkepohl, Helmut, 1982. "Non-causality due to omitted variables," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 367-378, August.
    10. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
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    Cited by:

    1. Reichman, Nancy E. & Florio, Maryanne J., 1996. "The effects of enriched prenatal care services on Medicaid birth outcomes in New Jersey," Journal of Health Economics, Elsevier, vol. 15(4), pages 455-476, August.
    2. Hope Corman & Dhaval M. Dave & Nancy E. Reichman, 2017. "Evolution of the Infant Health Production Function," NBER Working Papers 24131, National Bureau of Economic Research, Inc.
    3. O'Neill June E & O'Neill Dave M, 2008. "Health Status, Health Care and Inequality: Canada vs. the U.S," Forum for Health Economics & Policy, De Gruyter, vol. 10(1), pages 1-45, April.

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