IDEAS home Printed from https://ideas.repec.org/a/ksa/szemle/1875.html
   My bibliography  Save this article

A KRTK Adatbank Kapcsolt Államigazgatási Paneladatbázisa
[The panel of linked administrative data in the CERS databank]

Author

Listed:
  • Sebők, Anna

Abstract

A Közgazdaság- és Regionális Tudományi Kutatóközpont Adatbankjában létrejött a legújabb Kapcsolt Államigazgatási Paneladatbázis, az Admin3. A különböző államigazgatási nyilvántartások személyi szintű adatösszekötése - a korábbi hullámokhoz hasonlóan (Admin1 és Admin2) - lehetővé teszi a magyar lakosság 50 százalékos mintáján a népesség munkaerőpiaci, munkanélküliségi, oktatási és egészségügyi jellemzőinek tudományos vizsgálatát 2003 és 2017 között. Az egyéni és vállalati szintű, hosszú idősoros, ugyanakkor természetes azonosítókat nem tartalmazó paneladatbázis egyedülállóan szerteágazó tartalmú. Az Admin3 forrásregiszterei között szerepelnek a Nemzeti Egészségbiztosítási Alapkezelő, a Magyar Államkincstár, az Oktatási Hivatal, a Pénzügyminisztérium és a Nemzeti Adó- és Vámhivatal adatbázisai.* Journal of Economic Literature (JEL) kód: C8, C80, C81, C82, C89.

Suggested Citation

  • Sebők, Anna, 2019. "A KRTK Adatbank Kapcsolt Államigazgatási Paneladatbázisa [The panel of linked administrative data in the CERS databank]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(11), pages 1230-1236.
    • Handle: RePEc:ksa:szemle:1875
    DOI: 10.18414/KSZ.2019.11.1230
    as

    Download full text from publisher

    File URL: http://www.kszemle.hu/tartalom/letoltes.php?id=1875
    Download Restriction: Registration and subscription. 3-month embargo period to non-subscribers.
    File URL: https://libkey.io/10.18414/KSZ.2019.11.1230?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Márton Csillag, 2019. "The Incentive Effects of Sickness Absence Compensation – Analysis of a Natural Experiment in Eastern Europe☆," Research in Labor Economics, in: Health and Labor Markets, volume 47, pages 195-225, Emerald Group Publishing Limited.
    2. Stefano DellaVigna & Attila Lindner & Balázs Reizer & Johannes F. Schmieder, 2017. "Reference-Dependent Job Search: Evidence from Hungary," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(4), pages 1969-2018.
    3. Bence Czafit & János Köllő, 2015. "Employment and wages before and after incarceration – evidence from Hungary," IZA Journal of European Labor Studies, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 4(1), pages 1-21, December.
    4. Anikó Bíró & Péter Elek, 2018. "How does retirement affect healthcare expenditures? Evidence from a change in the retirement age," Health Economics, John Wiley & Sons, Ltd., vol. 27(5), pages 803-818, May.
    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. David S. Lee & Pauline Leung & Christopher J. O’Leary & Zhuan Pei & Simon Quach, 2021. "Are Sufficient Statistics Necessary? Nonparametric Measurement of Deadweight Loss from Unemployment Insurance," Journal of Labor Economics, University of Chicago Press, vol. 39(S2), pages 455-506.
    2. Koenig, Felix & Manning, Alan & Petrongolo, Barbara, 2014. "Reservation wages and the wage flexibility puzzle," LSE Research Online Documents on Economics 60613, London School of Economics and Political Science, LSE Library.
    3. François Gerard & Joana Naritomi, 2021. "Job Displacement Insurance and (the Lack of) Consumption-Smoothing," American Economic Review, American Economic Association, vol. 111(3), pages 899-942, March.
    4. Sascha Drahs & Luke Haywood & Amelie Schiprowski, 2018. "Job Search with Subjective Wage Expectations," Discussion Papers of DIW Berlin 1725, DIW Berlin, German Institute for Economic Research.
    5. Belot, Michele & Kircher, Philipp & Muller, Paul, 2021. "Eliciting time preferences when income and consumption vary: Theory, validation & application to job search," LIDAM Discussion Papers CORE 2021035, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Chen Lian & Yueran Ma & Carmen Wang, 2019. "Low Interest Rates and Risk-Taking: Evidence from Individual Investment Decisions," The Review of Financial Studies, Society for Financial Studies, vol. 32(6), pages 2107-2148.
    7. Bíró, Anikó & Elek, Péter, 2020. "Job loss, disability insurance and health expenditure," Labour Economics, Elsevier, vol. 65(C).
    8. Edika Quispe-Torreblanca & David Hume & John Gathergood & George Loewenstein & Neil Stewart, 2023. "At the Top of the Mind: Peak Prices and the Disposition Effect," Discussion Papers 2023-09, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
    9. Hai Long Duong & Junhong Chu & Dai Yao, 2023. "Taxi Drivers’ Response to Cancellations and No-Shows: New Evidence for Reference-Dependent Preferences," Management Science, INFORMS, vol. 69(1), pages 179-199, January.
    10. Eibich, Peter & Goldzahl, Léontine, 2021. "Does retirement affect secondary preventive care use? Evidence from breast cancer screening," Economics & Human Biology, Elsevier, vol. 43(C).
    11. Jin, Miao & Liu, Yu-Jane & Meng, Juanjuan, 2019. "Fat-finger event and risk-taking behavior," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 126-143.
    12. Barschkett, Mara & Geyer, Johannes & Haan, Peter & Hammerschmid, Anna, 2022. "The effects of an increase in the retirement age on health — Evidence from administrative data," The Journal of the Economics of Ageing, Elsevier, vol. 23(C).
    13. Stefano Della & Jörg Heining & Johannes F Schmieder & Simon Trenkle, 2023. "Evidence on Job Search Models from a Survey of Unemployed Workers in Germany," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 137(2), pages 1181-1232.
    14. Backes-Gellner, Uschi & Herz, Holger & Kosfeld, Michael & Oswald, Yvonne, 2021. "Do preferences and biases predict life outcomes? Evidence from education and labor market entry decisions," European Economic Review, Elsevier, vol. 134(C).
    15. Heutel, Garth, 2019. "Prospect theory and energy efficiency," Journal of Environmental Economics and Management, Elsevier, vol. 96(C), pages 236-254.
    16. Altmann, Steffen & Falk, Armin & Jäger, Simon & Zimmermann, Florian, 2018. "Learning about job search: A field experiment with job seekers in Germany," Journal of Public Economics, Elsevier, vol. 164(C), pages 33-49.
    17. Nafziger, Julia & Kaiser, Jonas P. & Koch, Alexander K, 2021. "Self-Set Goals Are Effective Self-Regulation Tools -- Despite Goal Revision," CEPR Discussion Papers 15716, C.E.P.R. Discussion Papers.
    18. Andrea Guido & Alejandro Martinez-Marquina & Ryan Rholes, 2022. "Reference Dependence and the Role of Information Frictions," GREDEG Working Papers 2022-17, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    19. Andreas I. Mueller & Johannes Spinnewijn & Giorgio Topa, 2021. "Job Seekers' Perceptions and Employment Prospects: Heterogeneity, Duration Dependence, and Bias," American Economic Review, American Economic Association, vol. 111(1), pages 324-363, January.
    20. Alberto Alesina & Francesco Passarelli, 2019. "Loss Aversion in Politics," American Journal of Political Science, John Wiley & Sons, vol. 63(4), pages 936-947, October.

    More about this item

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other

    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:ksa:szemle:1875. 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: Odon Sok (email available below). General contact details of provider: http://www.kszemle.hu .

    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.