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Googlemetrie und Arbeitsmarkt in der Wirtschaftskrise

Author

Listed:
  • Askitas, Nikos

    (IZA)

  • Zimmermann, Klaus F.

    (University of Bonn)

Abstract

Die große Wirtschaftskrise hat bisher nur verhaltene Spuren am Arbeitsmarkt hinterlassen. Angesichts der unsicheren weiteren konjunkturellen Entwicklung, der schlechten Auslastung der Arbeitskräfte in den Unternehmen und der hohen Kurzarbeit erwarten viele Beobachter zum Herbst einen dramatischen Anstieg der Arbeitslosigkeit mit einer baldigen Überschreitung der Vier-Millionen-Grenze. Nach Prognosen unter Verwendung von Google-Internetzugriffsstatistiken bleibt es aber im Vorfeld der Bundestagswahlen in den Sommermonaten August und September aller Voraussicht nach völlig ruhig. Saisonal bedingt geht die Arbeitslosigkeit sogar zurück. Damit verringert sich die Gefahr, dass eine Arbeitslosenzahl von vier Millionen noch in diesem Jahr erreicht werden wird.

Suggested Citation

  • Askitas, Nikos & Zimmermann, Klaus F., 2009. "Googlemetrie und Arbeitsmarkt in der Wirtschaftskrise," IZA Standpunkte 17, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izasps:sp17
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    References listed on IDEAS

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    1. Zimmermann, Klaus F., 2009. "Prognosekrise: Warum weniger manchmal mehr ist," IZA Standpunkte 4, Institute of Labor Economics (IZA).
    2. Amelie Constant & Klaus F. Zimmermann, 2008. "Im Angesicht der Krise: US-Präsidentschaftswahlen in transnationaler Sicht," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 75(44), pages 688-701.
    3. Nikolaos Askitas & Klaus F. Zimmermann, 2009. "Google Econometrics and Unemployment Forecasting," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 55(2), pages 107-120.
    4. Nikos Askitas & Klaus F. Zimmermann, 2009. "Prognosen aus dem Internet: weitere Erholung am Arbeitsmarkt erwartet," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 76(25), pages 402-408.
    5. Nikos Askitas & Klaus Zimmermann, 2009. "Googlemetrie und Arbeitsmarkt," Wirtschaftsdienst, Springer;ZBW - Leibniz Information Centre for Economics, vol. 89(7), pages 489-496, July.
    6. Jeremy Ginsberg & Matthew H. Mohebbi & Rajan S. Patel & Lynnette Brammer & Mark S. Smolinski & Larry Brilliant, 2009. "Detecting influenza epidemics using search engine query data," Nature, Nature, vol. 457(7232), pages 1012-1014, February.
    7. Christian Dreger & Patricia Alvarez-Plata & Kerstin Bernoth & Karl Brenke & Stefan Kooths & Vladimir Kuzin & Jörg Weber & Sebastian Weber & Florian Zinsmeister, 2009. "Tendenzen der Wirtschaftsentwicklung 2009/2010," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 76(31), pages 490-529.
    8. Konstantin A. Kholodilin & Boriss Siliverstovs, 2009. "Geben Konjunkturprognosen eine gute Orientierung?," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 76(13), pages 207-213.
    9. Karl Brenke & Christian Dreger & Stefan Kooths & Vladimir Kuzin & Sebastian Weber & Florian Zinsmeister, 2009. "Grundlinien der Wirtschaftsentwicklung 2009/2010," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 76(1/2), pages 2-35.
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    Cited by:

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    2. Jan Goebel & Christian Krekel & Tim Tiefenbach & Nicholas R. Ziebarth, 2014. "Natural Disaster, Environmental Concerns, Well-Being and Policy Action," CINCH Working Paper Series 1405, Universitaet Duisburg-Essen, Competent in Competition and Health.
    3. Simionescu, Mihaela & Raišienė, Agota Giedrė, 2021. "A bridge between sentiment indicators: What does Google Trends tell us about COVID-19 pandemic and employment expectations in the EU new member states?," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    4. Mihaela, Simionescu, 2020. "Improving unemployment rate forecasts at regional level in Romania using Google Trends," Technological Forecasting and Social Change, Elsevier, vol. 155(C).

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    More about this item

    Keywords

    Evaluation; Prognosen; Arbeitslosigkeit; Schlüsselworte; Suchmaschinen; Internet; Google;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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