IDEAS home Printed from https://ideas.repec.org/a/zbw/espost/251280.html
   My bibliography  Save this article

Können intensive Beratungsprogramme soziale Ungleichheit beim Übergang in die Hochschule reduzieren? Ergebnisse eines Feldexperiments
[Do Intensive Guidance Programs Reduce Social Inequality in the Transition to Higher Education? Results of a Field Experiment]

Author

Listed:
  • Erdmann, Melinda
  • Pietrzyk, Irena
  • Helbig, Marcel
  • Jacob, Marita
  • Stuth, Stefan

Abstract

Im Beitrag wird die Wirkung eines intensiven Beratungsprogramms zur Förderung der Studienaufnahme von Hochschulzugangsberechtigten untersucht. Mittels Daten aus einer experimentellen Panelstudie werden der durchschnittliche Effekt auf die Studienaufnahme direkt nach dem Abitur und die Effektheterogenität nach Bildungsherkunft überprüft. Es zeigt sich keine positive Wirkung der Teilnahme. Diese Ergebnisse werden in Bezug auf die ungleichheitsreduzierenden Potentiale individueller Beratung in Deutschland diskutiert.

Suggested Citation

  • Erdmann, Melinda & Pietrzyk, Irena & Helbig, Marcel & Jacob, Marita & Stuth, Stefan, 2022. "Können intensive Beratungsprogramme soziale Ungleichheit beim Übergang in die Hochschule reduzieren? Ergebnisse eines Feldexperiments [Do Intensive Guidance Programs Reduce Social Inequality in the," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 48(1), pages 137-162.
    • Handle: RePEc:zbw:espost:251280
    DOI: 10.2478/sjs-2022-0007
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/251280/1/Full-text-article-Erdmann-et-al-Koennen-intensive-Beratungsprogramme.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.2478/sjs-2022-0007?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
    ---><---

    References listed on IDEAS

    as
    1. William G. Howell & Patrick J. Wolf & David E. Campbell & Paul E. Peterson, 2002. "School vouchers and academic performance: results from three randomized field trials," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 21(2), pages 191-217.
    2. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881.
    3. Eric P. Bettinger & Bridget Terry Long & Philip Oreopoulos & Lisa Sanbonmatsu, 2012. "The Role of Application Assistance and Information in College Decisions: Results from the H&R Block Fafsa Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(3), pages 1205-1242.
    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. Erdmann, Melinda & Pietrzyk, Irena Magdalena & Helbig, Marcel & Jacob, Marita & Stuth, Stefan, 2022. "Do intensive guidance programs reduce social inequality in the transition to higher education in Germany? Experimental evidence from the ZuBAb study 0.5 years after high school graduation," Discussion Papers, Presidential Department P 2022-001, WZB Berlin Social Science Center.
    2. Darolia, Rajeev, 2013. "Integrity versus access? The effect of federal financial aid availability on postsecondary enrollment," Journal of Public Economics, Elsevier, vol. 106(C), pages 101-114.
    3. Pugatch, Todd & Wilson, Nicholas, 2018. "Nudging study habits: A field experiment on peer tutoring in higher education," Economics of Education Review, Elsevier, vol. 62(C), pages 151-161.
    4. Sven Resnjanskij & Jens Ruhose & Simon Wiederhold & Ludger Wößmann, 2021. "Mentoring Improves the Labor-Market Prospects of Highly Disadvantaged Adolescents," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 74(02), pages 31-38, February.
    5. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-dimensional econometrics and regularized GMM," CeMMAP working papers CWP35/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Dimitris Bertsimas & Agni Orfanoudaki & Rory B. Weiner, 2020. "Personalized treatment for coronary artery disease patients: a machine learning approach," Health Care Management Science, Springer, vol. 23(4), pages 482-506, December.
    7. Clément de Chaisemartin & Jaime Ramirez-Cuellar, 2024. "At What Level Should One Cluster Standard Errors in Paired and Small-Strata Experiments?," American Economic Journal: Applied Economics, American Economic Association, vol. 16(1), pages 193-212, January.
    8. Clément de Chaisemartin & Luc Behaghel, 2020. "Estimating the Effect of Treatments Allocated by Randomized Waiting Lists," Econometrica, Econometric Society, vol. 88(4), pages 1453-1477, July.
    9. Bruno Ferman & Cristine Pinto & Vitor Possebom, 2020. "Cherry Picking with Synthetic Controls," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(2), pages 510-532, March.
    10. Bonesrønning, Hans & Finseraas, Henning & Hardoy, Ines & Iversen, Jon Marius Vaag & Nyhus, Ole Henning & Opheim, Vibeke & Salvanes, Kari Vea & Sandsør, Astrid Marie Jorde & Schøne, Pål, 2022. "Small-group instruction to improve student performance in mathematics in early grades: Results from a randomized field experiment," Journal of Public Economics, Elsevier, vol. 216(C).
    11. Peydró, José-Luis & Jiménez, Gabriel & Kenan, Huremovic & Moral-Benito, Enrique & Vega-Redondo, Fernando, 2020. "Production and financial networks in interplay: Crisis evidence from supplier-customer and credit registers," CEPR Discussion Papers 15277, C.E.P.R. Discussion Papers.
    12. Ruoxuan Xiong & Allison Koenecke & Michael Powell & Zhu Shen & Joshua T. Vogelstein & Susan Athey, 2021. "Federated Causal Inference in Heterogeneous Observational Data," Papers 2107.11732, arXiv.org, revised Apr 2023.
    13. Bo, Shiyu & Liu, Jing & Shiu, Ji-Liang & Song, Yan & Zhou, Sen, 2019. "Admission mechanisms and the mismatch between colleges and students: Evidence from a large administrative dataset from China," Economics of Education Review, Elsevier, vol. 68(C), pages 27-37.
    14. Marie Bjørneby & Annette Alstadsæter & Kjetil Telle, 2018. "Collusive tax evasion by employers and employees. Evidence from a randomized fi eld experiment in Norway," Discussion Papers 891, Statistics Norway, Research Department.
    15. Konrad Menzel, 2021. "Structural Sieves," Papers 2112.01377, arXiv.org, revised Apr 2022.
    16. Susan Athey & Guido W. Imbens & Stefan Wager, 2018. "Approximate residual balancing: debiased inference of average treatment effects in high dimensions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 80(4), pages 597-623, September.
    17. Damgaard, Mette Trier & Nielsen, Helena Skyt, 2018. "Nudging in education," Economics of Education Review, Elsevier, vol. 64(C), pages 313-342.
    18. Felipe Arteaga & Adam J Kapor & Christopher A Neilson & Seth D Zimmerman, 2022. "Smart Matching Platforms and Heterogeneous Beliefs in Centralized School Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 137(3), pages 1791-1848.
    19. Goodman, Joshua & Hurwitz, Michael & Smith, Jonathan & Fox, Julia, 2015. "The relationship between siblings’ college choices: Evidence from one million SAT-taking families," Economics of Education Review, Elsevier, vol. 48(C), pages 75-85.
    20. Alberto Abadie & Susan Athey & Guido W. Imbens & Jeffrey M. Wooldridge, 2020. "Sampling‐Based versus Design‐Based Uncertainty in Regression Analysis," Econometrica, Econometric Society, vol. 88(1), pages 265-296, January.

    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:zbw:espost:251280. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/zbwkide.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.