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Tracking down the business cycle: A dynamic factor model for Germany 1820-1913

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  • Sarferaz, Samad
  • Uebele, Martin

Abstract

We use a Bayesian dynamic factor model in order to calculate an economic activity index for Germany prior to World War I. The procedure allows us to incorporate information from a vast number of time series, which are underutilized by historical national accounts. Therefore, our indicator provides an alternative measure for economic activity, based on a broader database. To investigate industrialization, we compare our aggregate measure of economic activity with sectoral activity indices. We find that the industrial transition was completed earlier than agricultural output and employment shares suggest, since the indicator for agriculture had already decoupled from the aggregate business cycle measure during the 1860s. Moreover, we find that stock prices are strongly correlated with our indicator, and lead it by 1-2 years.

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  • Sarferaz, Samad & Uebele, Martin, 2009. "Tracking down the business cycle: A dynamic factor model for Germany 1820-1913," Explorations in Economic History, Elsevier, vol. 46(3), pages 368-387, July.
    • Handle: RePEc:eee:exehis:v:46:y:2009:i:3:p:368-387
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    Cited by:

    1. Fredrik N G Andersson & Jason Lennard, 2019. "Irish GDP between the Famine and the First World War: estimates based on a dynamic factor model," European Review of Economic History, European Historical Economics Society, vol. 23(1), pages 50-71.
    2. Uebele, Martin & Pfister, Ulrich & Riedel, Jana, 2012. "Real wages and the origins of modern economic growth in Germany, 16th to 19th centuries," VfS Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62076, Verein für Socialpolitik / German Economic Association.
    3. Uebele, Martin & Ritschl, Albrecht, 2009. "Stock markets and business cycle comovement in Germany before World War I: Evidence from spectral analysis," Journal of Macroeconomics, Elsevier, vol. 31(1), pages 35-57, March.
    4. Rozite, Kristiana & Bezemer, Dirk J. & Jacobs, Jan P.A.M., 2019. "Towards a financial cycle for the U.S., 1973–2014," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    5. Albers, Thilo & Uebele, Martin, 2015. "The global impact of the great depression," LSE Research Online Documents on Economics 64491, London School of Economics and Political Science, LSE Library.
    6. Jansson, Walter, 2018. "Stock markets, banks and economic growth in the UK, 1850–1913," Financial History Review, Cambridge University Press, vol. 25(3), pages 263-296, December.
    7. Ritschl, Albrecht & Uebele, Martin & Sarferaz, Samad, 2008. "The U.S. Business Cycle, 1867-1995: A Dynamic Factor Approach," CEPR Discussion Papers 7069, C.E.P.R. Discussion Papers.
    8. Henning, Martin & Enflo, Kerstin & Andersson, Fredrik N.G., 2011. "Trends and cycles in regional economic growth," Explorations in Economic History, Elsevier, vol. 48(4), pages 538-555.
    9. Albers, Thilo Nils Hendrik, 2018. "The prelude and global impact of the Great Depression: Evidence from a new macroeconomic dataset," Explorations in Economic History, Elsevier, vol. 70(C), pages 150-163.
    10. George Chouliarakis & Tadeusz Gwiazdowski & Sophia Lazaretou, 2016. "The Effect of Fiscal Policy on Output in Times of Crisis and Prosperity: Historical Evidence From Greece ," Centre for Growth and Business Cycle Research Discussion Paper Series 230, Economics, The University of Manchester.
    11. Veenstra, Joost, 2015. "Output growth in German manufacturing, 1907–1936. A reinterpretation of time-series evidence," Explorations in Economic History, Elsevier, vol. 57(C), pages 38-49.

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    More about this item

    Keywords

    Business cycle chronology Imperial Germany Dynamic factor models Industrialization;

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • N13 - Economic History - - Macroeconomics and Monetary Economics; Industrial Structure; Growth; Fluctuations - - - Europe: Pre-1913

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