IDEAS home Printed from https://ideas.repec.org/p/iab/iabfme/201510(en).html
   My bibliography  Save this paper

Generalised partially linear regression with misclassied data and an application to labour market transitions

Author

Listed:
  • Dlugosz, Stephan

    (ZEW Mannheim)

  • Mammen, Enno

    (Institute for Applied Mathematics, Heidelberg)

  • Wilke, Ralf A.

    (Copenhagen Business School)

Abstract

"We consider the semiparametric generalised linear regression model which has mainstream empirical models such as the (partially) linear mean regression, logistic and multinomial regression as special cases. As an extension to related literature we allow a misclassified covariate to be interacted with a nonparametric function of a continuous covariate. This model is tailor- made to address known data quality issues of administrative labour market data. Using a sample of 20m observations from Germany we estimate the determinants of labour market transitions and illustrate the role of considerable misclassification in the educational status on estimated transition probabilities and marginal effects." (Author's abstract, IAB-Doku) ((en))

Suggested Citation

  • Dlugosz, Stephan & Mammen, Enno & Wilke, Ralf A., 2015. "Generalised partially linear regression with misclassied data and an application to labour market transitions," FDZ-Methodenreport 201510 (en), Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  • Handle: RePEc:iab:iabfme:201510(en)
    as

    Download full text from publisher

    File URL: https://doku.iab.de/fdz/reporte/2015/MR_10-15_EN.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Hernandez, Monica & Pudney, Stephen, 2007. "Measurement error in models of welfare participation," Journal of Public Economics, Elsevier, vol. 91(1-2), pages 327-341, February.
    2. Bergemann, Annette & Mertens, Antje, 2000. "Job stability trends, layoffs and quits: An empirical analysis for West Germany," SFB 373 Discussion Papers 2001,102, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    3. Manfred Antoni & Stefan Seth, 2012. "ALWA-ADIAB – Linked Individual Survey and Administrative Data for Substantive and Methodological Research," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 132(1), pages 141-146.
    4. Nina Westerheide & Goran Kauermann, 2014. "Unemployed in Germany: Factors Influencing the Risk of Losing the Job," Research in World Economy, Research in World Economy, Sciedu Press, vol. 5(2), pages 43-55, September.
    5. Manfred Antoni & Stefan Seth, 2012. "ALWA-ADIAB – Linked Individual Survey and Administrative Data for Substantive and Methodological Research," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 132(1), pages 141-146.
    6. Bernd Fitzenberger & Aderonke Osikominu & Robert Völter, 2006. "Imputation Rules to Improve the Education Variable in the IAB Employment Subsample," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 126(3), pages 405-436.
    7. Thierry Magnac & Michael Visser, 1999. "Transition Models With Measurement Errors," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 466-474, August.
    8. Manuel Arellano & Costas Meghir, 1992. "Female Labour Supply and On-the-Job Search: An Empirical Model Estimated Using Complementary Data Sets," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 59(3), pages 537-559.
    9. Maddala, G S, 1971. "The Likelihood Approach to Pooling Cross-Section and Time-Series Data," Econometrica, Econometric Society, vol. 39(6), pages 939-953, November.
    10. Xiaohong Chen & Han Hong & Elie Tamer, 2005. "Measurement Error Models with Auxiliary Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(2), pages 343-366.
    11. Chen, Xiaohong & Hu, Yingyao & Lewbel, Arthur, 2008. "Nonparametric identification of regression models containing a misclassified dichotomous regressor without instruments," Economics Letters, Elsevier, vol. 100(3), pages 381-384, September.
    12. repec:iab:iabfme:201112(en is not listed on IDEAS
    13. Laura Wichert & Ralf A. Wilke, 2012. "Which factors safeguard employment?: an analysis with misclassified German register data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 175(1), pages 135-151, January.
    14. Kruppe, Thomas & Matthes, Britta & Unger, Stefanie, 2014. "Effectiveness of data correction rules in process-produced data : the case of educational attainment," IAB-Discussion Paper 201415, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    15. Dlugosz, Stephan, 2011. "Give missings a chance: Combined stochastic and rule-based approach to improve regression models with mismeasured monotonic covariates without side information," ZEW Discussion Papers 11-013, ZEW - Leibniz Centre for European Economic Research.
    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. Dlugosz, Stephan & Mammen, Enno & Wilke, Ralf A., 2015. "Generalised partially linear regression with misclassified data and an application to labour market transitions," ZEW Discussion Papers 15-043, ZEW - Leibniz Centre for European Economic Research.
    2. Dlugosz, Stephan & Mammen, Enno & Wilke, Ralf A., 2017. "Generalized partially linear regression with misclassified data and an application to labour market transitions," Computational Statistics & Data Analysis, Elsevier, vol. 110(C), pages 145-159.
    3. repec:iab:iabfme:201510(en is not listed on IDEAS
    4. Kohlbrecher, Britta & Merkl, Christian & Nordmeier, Daniela, 2016. "Revisiting the matching function," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 350-374.
    5. DiTraglia, Francis J. & García-Jimeno, Camilo, 2019. "Identifying the effect of a mis-classified, binary, endogenous regressor," Journal of Econometrics, Elsevier, vol. 209(2), pages 376-390.
    6. Boockmann, Bernhard & Steffes, Susanne, 2005. "Individual and Plant-level Determinants of Job Durations in Germany," ZEW Discussion Papers 05-89, ZEW - Leibniz Centre for European Economic Research.
    7. Francis J. DiTraglia & Camilo García-Jimeno, 2017. "Mis-classified, Binary, Endogenous Regressors: Identification and Inference," NBER Working Papers 23814, National Bureau of Economic Research, Inc.
    8. Korbmacher, Julie M. & Schröder, Mathis, 2013. "Consent when Linking Survey Data with Administrative Records: The Role of the Interviewer," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 7(2), pages 115-131.
    9. Antoni, Manfred & Heineck, Guido, 2012. "Do literacy and numeracy pay off? : on the relationship between basic skills and earnings," IAB-Discussion Paper 201221, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    10. Nicole Gürtzgen & André Nolte, 2017. "Imputation rules for the implementation of the pre-unification education variable in the BASiD Data Set [Imputationsregeln für die Generierung der Bildungsvariable in den BASiD-Daten vor der Wieder," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 50(1), pages 45-65, August.
    11. Stüber, Heiko & Seth, Stefan & Stegmaier, Jens, 2020. "The Administrative Wage and Labor Market Flow Panel Extension for the IAB Establishment Panel 1993 - 2014," FDZ Datenreport. Documentation on Labour Market Data 202007_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    12. Berlingieri, Francesco & Gathmann, Christina & Quinckhardt, Matthias, 2022. "College Openings and Local Economic Development," CEPR Discussion Papers 17374, C.E.P.R. Discussion Papers.
    13. Paul Sullivan, 2009. "Estimation of an Occupational Choice Model when Occupations are Misclassified," Journal of Human Resources, University of Wisconsin Press, vol. 44(2).
    14. repec:iab:iabfda:202007(en is not listed on IDEAS
    15. Bachbauer, Nadine & Wolf, Clara, 2020. "NEPS-SC6 survey data linked to administrative data of the IAB (NEPS-SC6-ADIAB)," FDZ Datenreport. Documentation on Labour Market Data 202004_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    16. Stüber, Heiko & Seth, Stefan & Lochner, Benjamin, 2020. "The Administrative Wage and Labor Market Flow Panel Extension for the IAB Job Vacancy Survey 2010 - 2014," FDZ Datenreport. Documentation on Labour Market Data 202008_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    17. repec:iab:iabfda:202004(de is not listed on IDEAS
    18. repec:iab:iabfda:201603(de is not listed on IDEAS
    19. Hartmut Egger & Elke J. Jahn & Udo Kreickemeier, 2018. "Distance and the Multinational Wage Premium," CESifo Working Paper Series 7347, CESifo.
    20. Eberle, Johanna & Schmucker, Alexandra, 2017. "The establishment History Panel : Redesign and update 2016," FDZ Methodenreport 201703_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    21. Buchinsky, Moshe & Li, Fanghua & Liao, Zhipeng, 2022. "Estimation and inference of semiparametric models using data from several sources," Journal of Econometrics, Elsevier, vol. 226(1), pages 80-103.
    22. Neumann, M., 2017. "Earnings responses to social security contributions," Labour Economics, Elsevier, vol. 49(C), pages 55-73.
    23. Francis DiTraglia & Camilo Garcia-Jimeno, 2015. "On Mis-measured Binary Regressors: New Results And Some Comments on the Literature, Second Version," PIER Working Paper Archive 15-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 11 Nov 2015.
    24. Francis DiTraglia & Camilo Garcia-Jimeno, 2015. "On Mis-measured Binary Regressors: New Results And Some Comments on the Literature, Third Version," PIER Working Paper Archive 15-040, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 24 Nov 2015.

    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:iab:iabfme:201510(en). 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: IAB, Geschäftsbereich Wissenschaftliche Fachinformation und Bibliothek (email available below). General contact details of provider: https://edirc.repec.org/data/iabfzde.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.