IDEAS home Printed from https://ideas.repec.org/a/sae/jedbes/v33y2008i1p111-130.html
   My bibliography  Save this article

Nonparametric Bounds on the Causal Effect of University Studies on Job Opportunities Using Principal Stratification

Author

Listed:
  • Leonardo Grilli
  • Fabrizia Mealli

Abstract

The authors propose a methodology based on the principal strata approach to causal inference for assessing the relative effectiveness of two degree programs with respect to the employment status of their graduates. An innovative use of nonparametric bounds in the principal strata framework is shown, examining the role of some assumptions in reducing uncertainty about the causal effects and proposing a strategy to use the covariates in the construction of the bounds. In the application, the nonparametric bounds turn out to be quite informative on the average causal effect for the latent group of students who are potentially able to graduate from both degree programs. There is some evidence that the effect is positive for economics with respect to political science, at least for some values of the covariates.

Suggested Citation

  • Leonardo Grilli & Fabrizia Mealli, 2008. "Nonparametric Bounds on the Causal Effect of University Studies on Job Opportunities Using Principal Stratification," Journal of Educational and Behavioral Statistics, , vol. 33(1), pages 111-130, March.
    • Handle: RePEc:sae:jedbes:v:33:y:2008:i:1:p:111-130
    DOI: 10.3102/1076998607302627
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.3102/1076998607302627
    Download Restriction: no
    File URL: https://libkey.io/10.3102/1076998607302627?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cavalletti, Barbara & Corsi, Matteo & Persico, Luca & di Bella, Enrico, 2021. "Public university orientation for high-school students. A quasi-experimental assessment of the efficiency gains from nudging better career choices," Socio-Economic Planning Sciences, Elsevier, vol. 73(C).
    2. Martin Huber & Giovanni Mellace, 2015. "Sharp Bounds on Causal Effects under Sample Selection," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(1), pages 129-151, February.
    3. Kaitlin Anderson & Gema Zamarro & Jennifer Steele & Trey Miller, 2021. "Comparing Performance of Methods to Deal With Differential Attrition in Randomized Experimental Evaluations," Evaluation Review, , vol. 45(1-2), pages 70-104, February.
    4. Fabrizia Mealli & Barbara Pacini & Elena Stanghellini, 2016. "Identification of Principal Causal Effects Using Additional Outcomes in Concentration Graphs," Journal of Educational and Behavioral Statistics, , vol. 41(5), pages 463-480, October.
    5. Shanshan Luo & Wei Li & Yangbo He, 2023. "Causal inference with outcomes truncated by death in multiarm studies," Biometrics, The International Biometric Society, vol. 79(1), pages 502-513, March.
    6. Jiannan Lu & Peng Ding & Tirthankar Dasgupta, 2018. "Treatment Effects on Ordinal Outcomes: Causal Estimands and Sharp Bounds," Journal of Educational and Behavioral Statistics, , vol. 43(5), pages 540-567, October.
    7. Dustin M. Long & Michael G. Hudgens, 2013. "Sharpening Bounds on Principal Effects with Covariates," Biometrics, The International Biometric Society, vol. 69(4), pages 812-819, December.
    8. Sandra De Iaco & Sabrina Maggio & Donato Posa, 2019. "A Multilevel Multinomial Model for the Dynamics of Graduates Employment in Italy," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 149-168, November.
    9. Avi Feller & Fabrizia Mealli & Luke Miratrix, 2017. "Principal Score Methods: Assumptions, Extensions, and Practical Considerations," Journal of Educational and Behavioral Statistics, , vol. 42(6), pages 726-758, December.
    10. Jiannan Lu & Yunshu Zhang & Peng Ding, 2020. "Sharp bounds on the relative treatment effect for ordinal outcomes," Biometrics, The International Biometric Society, vol. 76(2), pages 664-669, June.
    11. Montserrat Hernández-LÓPEZ & José Juan Cáceres-HERNÁNDEZ, 2016. "Forecasting The Composition Of Demand For Higher Education Degrees By Genetic Algorithms," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(3), pages 153-172.
    12. Andrea Mercatanti & Fan Li, 2017. "Do debit cards decrease cash demand?: causal inference and sensitivity analysis using principal stratification," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(4), pages 759-776, August.
    13. Kédagni, Désiré, 2023. "Identifying treatment effects in the presence of confounded types," Journal of Econometrics, Elsevier, vol. 234(2), pages 479-511.

    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:sae:jedbes:v:33:y:2008:i:1:p:111-130. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: SAGE Publications (email available below). General contact details of provider: .

    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.