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Tracking Down the Business Cycle: A Dynamic Factor Model For Germany 1820-1913

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  • Samad Sarferaz
  • Martin Uebele

Abstract

We use a Bayesian dynamic factor model to measure Germany’s pre World War I economic activity. The procedure makes better use of existing time series data than historical national accounting. To investigate industrialization we propose to look at comovement between sectors. We find that Germany’s industrial sector developed earlier than stated in the literature, since after the 1860s agricultural time series do not comove with the business cycle anymore. Also, the bulk of comovement between 1820 and 1913 can be traced back to five out of 18 series representing industrial production, investment and demand for industrial inputs. Our factor is impressingly confirmed by a stock price index, leading the factor by 1-2 years. We also find evidence for early market integration in the 1820s and 1830s. Our business cycle dating aims to resolve the debate on German business cycle history. Given the often unsatisfactory quality of national accounting data for the 19th century we show the advantage of dynamic factor models in making efficient use of rare historical time series.

Suggested Citation

  • Samad Sarferaz & Martin Uebele, 2007. "Tracking Down the Business Cycle: A Dynamic Factor Model For Germany 1820-1913," SFB 649 Discussion Papers SFB649DP2007-039, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  • Handle: RePEc:hum:wpaper:sfb649dp2007-039
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. Andersson, Fredrik N. G. & Lennard, Jason, 2016. "Irish GDP between the Famine and the First World War: Estimates Based on a Dynamic Factor Model," Working Papers 2016:13, Lund University, Department of Economics, revised 16 Jan 2018.
    2. 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.
    3. Ulrich Pfister & Jana Riedel & Martin Uebele, 2012. "Real Wages and the Origins of Modern Economic Growth in Germany, 16th to 19th Centuries," Working Papers 0017, European Historical Economics Society (EHES).
    4. Ritschl, Albrecht & Sarferaz, Samad & Uebele, Martin, 2008. "The U.S. Business Cycle, 1867-1995: A Dynamic Factor Approach," CEPR Discussion Papers 7069, C.E.P.R. Discussion Papers.
    5. 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.
    6. 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.
    7. 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.
    8. 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 Univeristy of Manchester.

    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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