Population research has a distinguished history of empirical work on a wide variety of important topics related to population growth, the components of demographic trends, estimation of vital rates, life table construction, investigation into causes of historical population developments, and many others. However, one branch of population research that has seen increasing interest has been in the area of social demography, where the determinants of individual behavior regarding fertility, marriage, and related areas has been studied. It is in that branch that issues of causal inference have arisen, and with which this essay is concerned.
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References
Angrist, J. and W. Evans (1998). Children and Their Parents’ Labor Supply: Evidence from Exogenous Variation in Family Size. American Economic Review 88 (June): 450–477.
Angrist, J. and G. Imbens (1995). Two-Stage Least Squares Estimation of Average Causal Effects in Models with Variable Treatment Intensity. Journal of the American Statistical Society 90 (June): 431–442.
Angrist, J., G. Imbens and D. Rubin (1996). Identification of Causal Effects Using Instrumental Variables. Journal of the American Statistical Association 91 (June): 444–472.
Angrist, J. and A. Krueger (1991). Does Compulsory School Attendance Affect Schooling and Earnings? Quarterly Journal of Economics 106 (November): 979–1014.
Angrist, J. and A. Krueger (1999). Empirical Strategies in Labor Economics. In: Handbook of Labor Economics, Vol. 3A, eds. O. Ashenfelter and D. Card. Amsterdam: North-Holland.
Angrist, J. and A. Krueger (2001). Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments. Journal of Economic Perspectives 15 (Fall): 69–85.
Barnow, B., G. Cain and A. Goldberger (1980). Issues in the Analysis of Selectivity Bias. In: Evaluation Review Studies Annual, eds. E. Stromsdorfer and G. Farkas. Beverly Hills: Sage.
Björklund, A. and R. Moffitt (1987). The Estimation of Wage and Welfare Gains in Self-Selection Models. Review of Economics and Statistics 69: 42–49.
Bound, J. and G. Solon (1999). Double Trouble: On the Value of Twins-Based Estimation of the Return to Schooling. Economics of Education Review 18 (April): 169–182.
Cameron, A.C. and P. Trivedi (2005). Microeconometrics: Methods and Applications. Cambridge: Cambridge University Press.
Card, D. (2001). Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems. Econometrica 69 (September): 1127–1160.
Carneiro, P.J., J. Heckman and E. Vytlacil (2006). Estimating Marginal and Average Returns to Education. New York: Mimeo.
Chevalier, A. and T. Viitanen (2003). The Long-Run Labour Market Consequences of Teenage Motherhood in Britain. Journal of Population Economics 16: 323–343.
Currie, J. and J. Gruber (1996). Health Insurance Eligibility, Utilization of Medical Care, and Child Health. Quarterly Journal of Economics 111 (May): 431–466.
Geronimus, A. and S. Korenman (1992). The Socioeconomic Consequences of Teen Childbearing Reconsidered. Quarterly Journal of Economics 107 (November): 1187–1214.
Heckman, J. (1978). Dummy Endogenous Variables in a Simultaneous Equation System. Econometrica 46: 931–960.
Heckman, J. and R. Robb (1985). Alternative Methods for Evaluating the Impact of Interventions. In: Longitudinal Analysis of Labor Market Data, eds. J. Heckman and B. Singer. Cambridge: Cambridge University Press.
Heckman, J., S. Urzua and E. Vytlacil (2006). Understanding Instrumental Variables in Models with Essential Heterogeneity. Review of Economics and Statistics 88 (August): 389–432.
Heckman, J. and E. Vytlacil (1999). Local Instrumental Variables and Latent Variable Models for Identifying and Bounding Treatment Effects. Proceedings of the National Academy of Sciences 96 (April): 4730–4734.
Heckman, J. and E. Vytlacil (2001). Policy-Relevant Treatment Effects. American Economic Review 91 (May): 107–111.
Heckman, J. and E. Vytlacil (2005). Structural Equations, Treatment Effects, and Econometric Policy Evaluation. Econometrica 73 (May): 669–738.
Hoffman, S., E.M. Foster and F. Furstenberg (1993). Re-evaluating the Costs of Teenage Childbearing. Demography 30 (February): 1–13.
Hotz, V.J., S. McElroy and S. Sanders (1997a). The Impacts of Teenage Childbearing on the Mothers and the Consequences of those Impacts for the Government. In: Kids Having Kids: Economic Costs and Social Consequences of Teen Pregnancy, ed. R. Maynard. Washington: Urban Institute Press.
Hotz, V.J., C. Mullin and S. Sanders (1997b). Bounding Causal Effects Using Data from a Contaminated Natural Experiment: Analysing the Effect of Teenage Childbearing. Review of Economic Studies 64 (October): 575–603.
Imbens, G. (2004). Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review. Review of Economics and Statistics 86 (February): 4–29.
Imbens, G. and J. Angrist (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica 62: 467–76.
Imbens, G. and T. Lemieux (2008). Regression Continuity Designs: A Guide for Practice. Journal of Econometrics 142 (February): 615–35.
Klepinger, D., S. Lundberg and R. Plotnick (1999). How Does Adolescent Fertility Affect the Human Capital and Wages of Young Women? Journal of Human Resources 34 (Summer): 421–448.
Lee, L.F. (1979). Identification and Estimation in Binary Choice Models with Limited (Censored) Dependent Variables. Econometrica 47: 977–996.
Manski, C. (1995). Identification Problems in the Social Sciences. Cambridge: Harvard University Press.
Moffitt, R. (2003). Causal Analysis in Population Research: An Economist’s Perspective. Population and Development Review 29 (September): 448–458.
Moffitt, R. (2005). Remarks on the Analysis of Causal Relationships in Population Research. Demography 42 (February): 91–108.
Moffitt, R. (Forthcoming). Estimating Marginal Treatment Effects in Heterogeneous Populations. Annales d’Economie et de Statistique.
Moffitt, R. and M. Ver Ploeg (eds.) (2001). Evaluating Welfare Reform in an Era of Transition. Washington: National Research Council.
Reinhold, S. (2007). Essays in Demographic Economics. Unpublished Ph.D. dissertation, Johns Hopkins University.
Ribar, D. (1994). Teenage Fertility and High School Completion. Review of Economics and Statistics 76 (August): 413–424.
Ribar, D. (1999). The Socioeconomic Consequences of Young Women’s Childbearing: Reconciling Disparate Evidence. Journal of Population Economics 12 (November): 547–565.
Robins, J., A. Rotnitzky and D. Scharfstein (2000). Sensitivity Analysis for Selection Bias and Unmeasured Confounding in Missing Data and Causal Inference Models. In: Statistical Models in Epidemiology, the Environment, and Clinical Trials, eds. E.M. Halloran and D. Berry. New York: Springer-Verlag.
Rosenzweig, M. and K. Wolpin (2000). Natural ‘Natural Experiments’ in Economics. Journal of Economic Literature 38 (December): 827–874.
Rubin, D. (1974). Estimating Causal Effects of Treatments in Randomized and Non-randomized Studies. Journal of Educational Psychology 66: 688–701.
Stock, J., J. Wright and M. Yogo (2002). A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments. Journal of Business and Economic Statistics 20 (October): 518–529.
Stock, J. and M. Yogo (2005). Testing for Weak Instruments in Linear IV Regression. In: Identification and Inference for Econometric Models: Essays in Honor of Thomas Rothenberg, eds. D. Andrews and J. Stock. New York: Cambridge University Press.
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Moffitt, R.A. (2009). Issues in the Estimation of Causal Effects in Population Research, with an Application to the Effects of Teenage Childbearing. In: Engelhardt, H., Kohler, HP., Fürnkranz-Prskawetz, A. (eds) Causal Analysis in Population Studies. The Springer Series on Demographic Methods and Population Analysis, vol 23. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-9967-0_2
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