IDEAS home Printed from https://ideas.repec.org/p/wiw/wiwwuw/wuwp223.html
   My bibliography  Save this paper

A Representative Matched Cross-section Survey for Austria - Measuring Worker Flow Dynamics with the Austrian Labour Force Survey

Author

Listed:
  • Schoiswohl Florian

    (Department of Economics, Vienna University of Economics and Business)

  • Wüger Michael

    (Department of Economics, Vienna University of Economics and Business)

Abstract

While worker flow analysis has grown in importance in many countries, Austria still lacks a specific longitudinal dataset as a prerequisite to perform similar analyses. For this reason, this article provides a coherent procedure to construct a longitudinal dataset based on the rotational panel structure of the Austrian quarterly LFS from 2004 to 2014. The procedure, which is available for researcher, is grounded on the discussion of several related and important issues inherent in constructing this sort of longitudinal data: First, it deals with the construction of the quarterly-matched dataset and the quality-of-measurement of several labour market variables. Second, the paper analyses non-response as a sample selection process, and shows that the selected (quarterly-matched) dataset causes biased estimates of worker flows. Third, the article proposes an iterative raking procedure to obtain survey weights as a bias-correcting device for any future analysis. Based on these adjustments, we present unbiased time-series of worker flows and transition rates, and conclude that the employment-unemployment margin is highly sensitive to economic shocks and that the Austrian labour market is additionally shaped by large movements within the participation margin.

Suggested Citation

  • Schoiswohl Florian & Wüger Michael, 2016. "A Representative Matched Cross-section Survey for Austria - Measuring Worker Flow Dynamics with the Austrian Labour Force Survey," Department of Economics Working Papers wuwp223, Vienna University of Economics and Business, Department of Economics.
    • Handle: RePEc:wiw:wiwwuw:wuwp223
    Note: PDF Document
    as

    Download full text from publisher

    File URL: https://epub.wu.ac.at/4935/1/wp223.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ronald Bachmann & Peggy Bechara & Anica Kramer & Sylvi Rzepka, 2015. "Labour market dynamics and worker heterogeneity during the Great Recession – Evidence from Europe," IZA Journal of European Labor Studies, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 4(1), pages 1-29, December.
    2. Gomes, Pedro, 2012. "Labour market flows: Facts from the United Kingdom," Labour Economics, Elsevier, vol. 19(2), pages 165-175.
    3. Sergi Jiménez-Martín & Franco Peracchi, 2002. "Sample attrition and labor force dynamics: Evidence from the Spanish labor force survey," Spanish Economic Review, Springer;Spanish Economic Association, vol. 4(2), pages 79-102.
    4. Van den Berg, G J & Lindeboom, M & Ridder, G, 1994. "Attrition in Longitudinal Panel Data and the Empirical Analysis of Dynamic Labour Market Behaviour," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(4), pages 421-435, Oct.-Dec..
    5. Christopher A. Pissarides & Barbara Petrongolo, 2001. "Looking into the Black Box: A Survey of the Matching Function," Journal of Economic Literature, American Economic Association, vol. 39(2), pages 390-431, June.
    6. Alfred Stiglbauer & Florian Stahl & Rudolf Winter-Ebmer & Josef Zweimüller, 2003. "Job Creation and Job Destruction in a Regulated Labor Market: The Case of Austria," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 30(2), pages 127-148, June.
    7. Vladislav Flek & Martina Mysíková, 2015. "Uneployment Dynamics in Central Europe: A Labour Flow Approach," Prague Economic Papers, Prague University of Economics and Business, vol. 2015(1), pages 73-87.
    8. Peracchi, Franco & Welch, Finis, 1995. "How representative are matched cross-sections? Evidence from the Current Population Survey," Journal of Econometrics, Elsevier, vol. 68(1), pages 153-179, July.
    9. Pietro Garibaldi & Etienne Wasmer, 2005. "Equilibrium Search Unemployment, Endogenous Participation, And Labor Market Flows," Journal of the European Economic Association, MIT Press, vol. 3(4), pages 851-882, June.
    10. repec:hal:spmain:info:hdl:2441/8921 is not listed on IDEAS
    11. repec:hal:wpspec:info:hdl:2441/8921 is not listed on IDEAS
    12. Hausman, Jerry A & Wise, David A, 1979. "Attrition Bias in Experimental and Panel Data: The Gary Income Maintenance Experiment," Econometrica, Econometric Society, vol. 47(2), pages 455-473, March.
    13. Nordmeier, Daniela, 2012. "Worker flows in Germany: Inspecting the time aggregation bias," IAB-Discussion Paper 201212, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    14. repec:zbw:rwirep:0499 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Michael Christl, 2020. "A Beveridge curve decomposition for Austria: did the liberalisation of the Austrian labour market shift the Beveridge curve?," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 54(1), pages 1-15, December.

    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. Carrillo-Tudela, Carlos & Launov, Andrey & Robin, Jean-Marc, 2021. "The fall in german unemployment: A flow analysis," European Economic Review, Elsevier, vol. 132(C).
    2. Matthias S. Hertweck & Oliver Sigrist, 2012. "The Aggregate Effects of the Hartz Reforms in Germany," Working Paper Series of the Department of Economics, University of Konstanz 2012-38, Department of Economics, University of Konstanz.
    3. Mathan Satchi & Jonathan Temple, 2006. "Growth and labour markets in developing countries," Bristol Economics Discussion Papers 06/581, School of Economics, University of Bristol, UK.
    4. Mark L Bryan & Nigel Rice & Jennifer Roberts & Cristina Sechel, 2022. "Mental Health and Employment: A Bounding Approach Using Panel Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(5), pages 1018-1051, October.
    5. Naval, Joaquín & Silva, José I. & Vázquez-Grenno, Javier, 2020. "Employment effects of on-the-job human capital acquisition," Labour Economics, Elsevier, vol. 67(C).
    6. Alon Binyamini & Tali Larom, 2012. "Encouraging Participation in a Labor Market with Search and Matching Frictions," Bank of Israel Working Papers 2012.11, Bank of Israel.
    7. John Fitzgerald & Peter Gottschalk & Robert Moffitt, 1998. "An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of Income Dynamics," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 251-299.
    8. Moon, Weh-Sol, 2011. "Endogenous labor force participation and firing costs," Labour Economics, Elsevier, vol. 18(5), pages 607-623, October.
    9. Christoffel, Kai & Costain, James & de Walque, Gregory & Kuester, Keith & Linzert, Tobias & Millard, Stephen & Pierrard, Olivier, 2009. "Inflation dynamics with labour market matching: assessing alternative specifications," Bank of England working papers 375, Bank of England.
    10. Otsu, Yuki & Yuen, C.Y. Kelvin, 2022. "Health, crime, and the labor market: Theory and policy analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    11. Kohlbrecher, Britta & Merkl, Christian & Nordmeier, Daniela, 2016. "Revisiting the matching function," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 350-374.
    12. Joohun Han & Chanjin Chung, 2021. "Impact of Aging and Underemployment on Income Disparity between Agricultural and Non-Agricultural Households," Sustainability, MDPI, vol. 13(21), pages 1-15, October.
    13. Sabrina Di Addario, 2005. "Job Search in Thick Markets: Evidence from Italy," Development Working Papers 198, Centro Studi Luca d'Agliano, University of Milano.
    14. Silva, José I. & Vázquez-Grenno, Javier, 2013. "The ins and outs of unemployment in a two-tier labor market," Labour Economics, Elsevier, vol. 24(C), pages 161-169.
    15. Francesco D'Amuri & Marta De Philippis & Elisa Guglielminetti & Salvatore Lo Bello, 2021. "Natural unemployment and activity rates: flow-based determinants and implications for price dynamics," Questioni di Economia e Finanza (Occasional Papers) 599, Bank of Italy, Economic Research and International Relations Area.
    16. Ronald Bachmann & Peggy Bechara & Anica Kramer & Sylvi Rzepka, 2015. "Labour market dynamics and worker heterogeneity during the Great Recession – Evidence from Europe," IZA Journal of European Labor Studies, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 4(1), pages 1-29, December.
    17. D’Amuri, Francesco & De Philippis, Marta & Guglielminetti, Elisa & Lo Bello, Salvatore, 2022. "Slack and prices during Covid-19: Accounting for labor market participation," Labour Economics, Elsevier, vol. 75(C).
    18. Fontaine, François, 2008. "Why are similar workers paid differently? the role of social networks," Journal of Economic Dynamics and Control, Elsevier, vol. 32(12), pages 3960-3977, December.
    19. Noritaka Kudoh & Hiroaki Miyamoto, 2021. "Robots and Unemployment," Working Papers SDES-2021-5, Kochi University of Technology, School of Economics and Management, revised May 2021.
    20. Andrew M. Jones & Xander Koolman & Nigel Rice, 2006. "Health‐related non‐response in the British Household Panel Survey and European Community Household Panel: using inverse‐probability‐weighted estimators in non‐linear models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 543-569, July.

    More about this item

    Keywords

    Matched cross-sections; Sample selection; Worker flows; Unemployment dynamics; Austrian labour market;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J63 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Turnover; Vacancies; Layoffs

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:wiw:wiwwuw:wuwp223. 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: Department of Economics (email available below). General contact details of provider: http://www.wu.ac.at/economics/en .

    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.