IDEAS home Printed from https://ideas.repec.org/p/imk/report/103-2015.html
   My bibliography  Save this paper

Erwerbstätigkeit in Deutschland im europäischen Vergleich

Author

Listed:
  • Sven Schreiber

    (Macroeconomic Policy Institute (IMK))

Abstract

Im vorliegenden Report werden die Erwerbstätigenquoten europäischer Länder untersucht, um Teilzeiteffekte bereinigt und nach Geschlechtern aufgeschlüsselt. Die positive Entwicklung des deutschen Arbeitsmarkts seit 2005 bestätigt sich und ist (beinahe) unabhängig von Teilzeiteffekten. Jedoch täuscht das nominell hohe Niveau der Erwerbstätigkeit durch den vergleichsweise hohen Teilzeitanteil und den geringen Stundenumfang der Teilzeitstellen in Deutschland. Dementsprechend liegt bei den korrigierten Erwerbstätigenquoten (in Vollzeitäquivalenten) Deutschland in Europa derzeit auf Platz 11 statt wie bei den nominellen Quoten auf Platz 5. Die Länder, bei denen die teilzeitbedingte Korrektur groß ist, weisen tendenziell eine geringere korrigierte Erwerbstätigenquote von Frauen im Vergleich zu Männern auf. Eine alternative Erwerbstätigenquote unter Berücksichtigung der Erwerbsneigung führt zu keiner grundlegend veränderten Beurteilung.

Suggested Citation

  • Sven Schreiber, 2015. "Erwerbstätigkeit in Deutschland im europäischen Vergleich," IMK Report 103-2015, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    • Handle: RePEc:imk:report:103-2015
    as

    Download full text from publisher

    File URL: http://www.boeckler.de/pdf/p_imk_report_103_2015.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bai, Jushan & Ng, Serena, 2013. "Principal components estimation and identification of static factors," Journal of Econometrics, Elsevier, vol. 176(1), pages 18-29.
    2. Bai, Jushan, 2004. "Estimating cross-section common stochastic trends in nonstationary panel data," Journal of Econometrics, Elsevier, vol. 122(1), pages 137-183, September.
    3. Böhm, Kathrin, 2011. "Schätzung der Stillen Reserve mit dem Mikrozensuspanel 2001-2004 : eine Machbarkeitsstudie," IAB-Forschungsbericht 201102, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    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. Raddatz, Guido, 2015. "Mehr Arbeit wagen," Argumente zur Marktwirtschaft und Politik 129, Stiftung Marktwirtschaft / The Market Economy Foundation, Berlin.
    2. Florian Blank & Camille Logeay & Erik Türk & Josef Wöss & Rudolf Zwiener, 2018. "Den demografischen Wandel bewältigen: Die Schlüsselrolle des Arbeitsmarktes," IMK Report 137-2018, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    3. Lara Minkus, 2019. "Labor Market Closure and the Stalling of the Gender Pay Gap," SOEPpapers on Multidisciplinary Panel Data Research 1049, DIW Berlin, The German Socio-Economic Panel (SOEP).

    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. Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
    2. İshak Demi̇r & Burak A. Eroğlu & Seçi̇l Yildirim‐Karaman, 2022. "Heterogeneous Effects of Unconventional Monetary Policy on the Bond Yields across the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(5), pages 1425-1457, August.
    3. Claudio Morana, 2014. "New insights on the US OIS spreads term structure during the recent financial turmoil," Applied Financial Economics, Taylor & Francis Journals, vol. 24(5), pages 291-317, March.
    4. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    5. Francisco Corona & Pilar Poncela & Esther Ruiz, 2017. "Determining the number of factors after stationary univariate transformations," Empirical Economics, Springer, vol. 53(1), pages 351-372, August.
    6. Francisco Corona & Pilar Poncela & Esther Ruiz, 2020. "Estimating Non-stationary Common Factors: Implications for Risk Sharing," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 37-60, January.
    7. Francisco Corona & Graciela Gonz'alez-Far'ias & Jes'us L'opez-P'erez, 2021. "A nowcasting approach to generate timely estimates of Mexican economic activity: An application to the period of COVID-19," Papers 2101.10383, arXiv.org.
    8. Zhaoxing Gao & Ruey S. Tsay, 2021. "Divide-and-Conquer: A Distributed Hierarchical Factor Approach to Modeling Large-Scale Time Series Data," Papers 2103.14626, arXiv.org.
    9. Javier Maldonado & Esther Ruiz, 2021. "Accurate Confidence Regions for Principal Components Factors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(6), pages 1432-1453, December.
    10. Claudio Morana, 2010. "Heteroskedastic Factor Vector Autoregressive Estimation of Persistent and Non Persistent Processes Subject to Structural Breaks," ICER Working Papers - Applied Mathematics Series 36-2010, ICER - International Centre for Economic Research.
    11. Marc Burri & Daniel Kaufmann, 2020. "A daily fever curve for the Swiss economy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-11, December.
    12. Mario Forni & Luca Gambetti & Luca Sala, 2014. "No News in Business Cycles," Economic Journal, Royal Economic Society, vol. 124(581), pages 1168-1191, December.
    13. Rangan Gupta & Alain Kabundi & Stephen Miller & Josine Uwilingiye, 2014. "Using large data sets to forecast sectoral employment," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 229-264, June.
    14. Luke Hartigan & James Morley, 2020. "A Factor Model Analysis of the Australian Economy and the Effects of Inflation Targeting," The Economic Record, The Economic Society of Australia, vol. 96(314), pages 271-293, September.
    15. Yi‐Chiuan Wang & Jyh‐Lin Wu, 2015. "Fundamentals and Exchange Rate Prediction Revisited," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(8), pages 1651-1671, December.
    16. Jushan Bai & Serena Ng, 2020. "Simpler Proofs for Approximate Factor Models of Large Dimensions," Papers 2008.00254, arXiv.org.
    17. Chiara Casoli & Riccardo (Jack) Lucchetti, 2022. "Permanent-Transitory decomposition of cointegrated time series via dynamic factor models, with an application to commodity prices [Commodity-price comovement and global economic activity]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 494-514.
    18. Thomas Despois & Catherine Doz, 2022. "Identifying and interpreting the factors in factor models via sparsity : Different approaches," Working Papers halshs-03626503, HAL.
    19. Mark J. Holmes & Arthur Grimes, 2005. "Is there long-run convergence of regional house prices in the UK?," Working Papers 05_11, Motu Economic and Public Policy Research.
    20. Leif Anders Thorsrud, 2016. "Nowcasting using news topics Big Data versus big bank," Working Papers No 6/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.

    More about this item

    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:imk:report:103-2015. 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: Sabine Nemitz (email available below). General contact details of provider: https://edirc.repec.org/data/imkhbde.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.