IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/7831.html
   My bibliography  Save this paper

Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools

Author

Listed:
  • Joseph G. Altonji
  • Todd E. Elder
  • Christopher R. Taber

Abstract

We develop estimation methods that use the amount of selection on the observables in a model as a guide to the amount of selection on the unobservables. We show that if the observed variables are a random subset of a large number of factors that influence the endogenous variable and the outcome of interest, then the relationship between the index of observables that determines the endogenous variable and the index that determines the outcome will be the same as the relationship between the indices of unobservables that determine the two variables. In some circumstances this fact may be used to identify the effect of the endogenous variable. We also propose an informal way to assess selectivity bias based on measuring the ratio of selection on unobservables to selection on observables that would be required if one is to attribute the entire effect of the endogenous variable to selection bias. We use our methods to estimate the effect of attending a Catholic high school on a variety of outcomes. Our main conclusion is that Catholic high schools substantially increase the probability of graduating from high school and, more tentatively, college attendance. We do not find much evidence for an effect on test scores.

Suggested Citation

  • Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2000. "Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools," NBER Working Papers 7831, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:7831
    Note: CH PE
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w7831.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Sims,Christopher A. (ed.), 1994. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521444606, September.
    2. Kevin M. Murphy & Robert H. Topel, 1990. "Efficiency Wages Reconsidered: Theory and Evidence," Palgrave Macmillan Books, in: Yoram Weiss & Gideon Fishelson (ed.), Advances in the Theory and Measurement of Unemployment, chapter 8, pages 204-240, Palgrave Macmillan.
    3. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2002. "An Evaluation of Instrumental Variable Strategies for Estimating the Effects of Catholic Schools," NBER Working Papers 9358, National Bureau of Economic Research, Inc.
    4. William N. Evans & Robert M. Schwab, 1995. "Finishing High School and Starting College: Do Catholic Schools Make a Difference?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(4), pages 941-974.
    5. Christopher Jepsen, 2003. "The Effectiveness of Catholic Primary Schooling," Journal of Human Resources, University of Wisconsin Press, vol. 38(4).
    6. repec:eme:rlepps:v:18:y:1999:i:1999:p:115-140 is not listed on IDEAS
    7. Sims,Christopher A. (ed.), 1994. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521444590, September.
    8. Richard J. Murnane, 1984. "A Review Essay-Comparisons of Public and Private Schools: Lessons from the Uproar," Journal of Human Resources, University of Wisconsin Press, vol. 19(2), pages 263-277.
    9. Stephen V. Cameron & James J. Heckman, 1998. "Life Cycle Schooling and Dynamic Selection Bias: Models and Evidence for Five Cohorts of American Males," Journal of Political Economy, University of Chicago Press, vol. 106(2), pages 262-333, April.
    10. Currie, Janet & Thomas, Duncan, 1995. "Does Head Start Make a Difference?," American Economic Review, American Economic Association, vol. 85(3), pages 341-364, June.
    11. Witte, John F., 1992. "Private school versus public school achievement: Are there findings that should affect the educational choice debate?," Economics of Education Review, Elsevier, vol. 11(4), pages 371-394, December.
    12. Eric M. Engen & William G. Gale & John Karl Scholz, 1996. "The Illusory Effects of Saving Incentives on Saving," Journal of Economic Perspectives, American Economic Association, vol. 10(4), pages 113-138, Fall.
    13. Angrist, Joshua D & Evans, William N, 1998. "Children and Their Parents' Labor Supply: Evidence from Exogenous Variation in Family Size," American Economic Review, American Economic Association, vol. 88(3), pages 450-477, June.
    14. Charles F. Manski, 1989. "Anatomy of the Selection Problem," Journal of Human Resources, University of Wisconsin Press, vol. 24(3), pages 343-360.
    15. Derek Neal, 1998. "What have we learned about the benefits of private schooling?," Economic Policy Review, Federal Reserve Bank of New York, vol. 4(Mar), pages 79-86.
    16. Stephen V. Cameron & Christopher Taber, 2004. "Estimation of Educational Borrowing Constraints Using Returns to Schooling," Journal of Political Economy, University of Chicago Press, vol. 112(1), pages 132-182, February.
    17. Poterba, James M & Venti, Steven F & Wise, David A, 1994. "Targeted Retirement Saving and the Net Worth of Elderly Americans," American Economic Review, American Economic Association, vol. 84(2), pages 180-185, May.
    18. Heckman, James J, 1990. "Varieties of Selection Bias," American Economic Review, American Economic Association, vol. 80(2), pages 313-318, May.
    19. Bronars, Stephen G & Grogger, Jeff, 1994. "The Economic Consequences of Unwed Motherhood: Using Twin Births as a Natural Experiment," American Economic Review, American Economic Association, vol. 84(5), pages 1141-1156, December.
    20. Stephen V. Cameron & James J. Heckman, 1998. "Life Cycle Schooling and Dynamic Selection Bias: Models and Evidence for Five Cohorts," NBER Working Papers 6385, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2002. "An Evaluation of Instrumental Variable Strategies for Estimating the Effects of Catholic Schools," NBER Working Papers 9358, National Bureau of Economic Research, Inc.
    2. Lewbel, Arthur, 2007. "Endogenous selection or treatment model estimation," Journal of Econometrics, Elsevier, vol. 141(2), pages 777-806, December.
    3. James J. Heckman, 2005. "Micro Data, Heterogeneity and the Evaluation of Public Policy Part 2," The American Economist, Sage Publications, vol. 49(1), pages 16-44, March.
    4. Joseph G. Altonji & Ching-I Huang & Christopher R. Taber, 2015. "Estimating the Cream Skimming Effect of School Choice," Journal of Political Economy, University of Chicago Press, vol. 123(2), pages 266-324.
    5. Clint Harris, 2022. "Interpreting Instrumental Variable Estimands with Unobserved Treatment Heterogeneity: The Effects of College Education," Papers 2211.13132, arXiv.org.
    6. Heckman, James J. & Lochner, Lance J. & Todd, Petra E., 2006. "Earnings Functions, Rates of Return and Treatment Effects: The Mincer Equation and Beyond," Handbook of the Economics of Education, in: Erik Hanushek & F. Welch (ed.), Handbook of the Economics of Education, edition 1, volume 1, chapter 7, pages 307-458, Elsevier.
    7. Ho, Kate & Rosen, Adam M., 2015. "Partial Identification in Applied Research: Benefits and Challenges," CEPR Discussion Papers 10883, C.E.P.R. Discussion Papers.
    8. James Heckman & Flavio Cunha, 2007. "The Technology of Skill Formation," American Economic Review, American Economic Association, vol. 97(2), pages 31-47, May.
    9. James J. Heckman, 2001. "Micro Data, Heterogeneity, and the Evaluation of Public Policy: Nobel Lecture," Journal of Political Economy, University of Chicago Press, vol. 109(4), pages 673-748, August.
    10. Akabayashi, Hideo & Ruberg, Tim & Shikishima, Chizuru & Yamashita, Jun, 2023. "Education-oriented and care-oriented preschools: Implications on child development," Labour Economics, Elsevier, vol. 84(C).
    11. Hiroyuki Kasahara & Katsumi Shimotsu, 2006. "Nonparametric Identification And Estimation Of Finite Mixture Models Of Dynamic Discrete Choices," Working Paper 1092, Economics Department, Queen's University.
    12. Vazquez-Alvarez, R. & Melenberg, B. & van Soest, A.H.O., 1999. "Nonparametric Modeling of the Anchoring Effect in an Unfolding Bracket Design," Discussion Paper 1999-115, Tilburg University, Center for Economic Research.
    13. Martin Huber, 2014. "Treatment Evaluation in the Presence of Sample Selection," Econometric Reviews, Taylor & Francis Journals, vol. 33(8), pages 869-905, November.
    14. James J. Heckman & Edward J. Vytlacil, 2000. "Instrumental Variables, Selection Models, and Tight Bounds on the Average Treatment Effect," NBER Technical Working Papers 0259, National Bureau of Economic Research, Inc.
    15. Vazquez-Alvarez, R. & Melenberg, B. & van Soest, A.H.O., 1999. "Nonparametric Bounds on the Income Distribution in the Presence of Item Nonresponse," Other publications TiSEM d37fb6a5-2075-42b2-b0b4-5, Tilburg University, School of Economics and Management.
    16. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2005. "An Evaluation of Instrumental Variable Strategies for Estimating the Effects of Catholic Schooling," Journal of Human Resources, University of Wisconsin Press, vol. 40(4), pages 791-821.
    17. Arnaud Chevalier & Colm Harmon & Vincent O’ Sullivan & Ian Walker, 2013. "The impact of parental income and education on the schooling of their children," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 2(1), pages 1-22, December.
    18. Elizabeth M. Caucutt & Lance Lochner & Youngmin Park, 2017. "Correlation, Consumption, Confusion, or Constraints: Why Do Poor Children Perform so Poorly?," Scandinavian Journal of Economics, Wiley Blackwell, vol. 119(1), pages 102-147, January.
    19. Manuel Arellano & Stéphane Bonhomme, 2017. "Quantile Selection Models With an Application to Understanding Changes in Wage Inequality," Econometrica, Econometric Society, vol. 85, pages 1-28, January.
    20. Anjana Susarla & Anitesh Barua, 2011. "Contracting Efficiency and New Firm Survival in Markets Enabled by Information Technology," Information Systems Research, INFORMS, vol. 22(2), pages 306-324, June.

    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • I2 - Health, Education, and Welfare - - Education

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:7831. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.