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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 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

  • Sarferaz, Samad & Uebele, Martin, 2007. "Tracking down the business cycle: A dynamic factor model for Germany 1820-1913," SFB 649 Discussion Papers 2007-039, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    • Handle: RePEc:zbw:sfb649:sfb649dp2007-039
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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.
    2. Uhlig, H.F.H.V.S. & Ravn, M., 1997. "On Adjusting the H-P Filter for the Frequency of Observations," Discussion Paper 1997-50, Tilburg University, Center for Economic Research.
    3. Berger, Helge & Spoerer, Mark, 2001. "Economic Crises And The European Revolutions Of 1848," The Journal of Economic History, Cambridge University Press, vol. 61(2), pages 293-326, June.
    4. Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, May.
    5. Otrok, Christopher & Whiteman, Charles H, 1998. "Bayesian Leading Indicators: Measuring and Predicting Economic Conditions in Iowa," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 997-1014, November.
    6. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
    7. James H. Stock & Mark W. Watson, 1998. "Diffusion Indexes," NBER Working Papers 6702, National Bureau of Economic Research, Inc.
    8. Calomiris, Charles W. & Schweikart, Larry, 1991. "The Panic of 1857: Origins, Transmission, and Containment," The Journal of Economic History, Cambridge University Press, vol. 51(4), pages 807-834, December.
    9. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc.
    10. Chib, Siddhartha, 1993. "Bayes regression with autoregressive errors : A Gibbs sampling approach," Journal of Econometrics, Elsevier, vol. 58(3), pages 275-294, August.
    11. Ulrich Woitek, 1998. "A Note on the Baxter-King Filter," Working Papers 9813, Business School - Economics, University of Glasgow.
    12. Julian Hoppit, 1990. "Counting the industrial revolution," Economic History Review, Economic History Society, vol. 43(2), pages 173-193, May.
    13. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1.
    14. Walther G. Hoffmann, 1963. "The Take-Off in Germany," International Economic Association Series, in: W. W. Rostow (ed.), The Economics of Take-Off into Sustained Growth, chapter 0, pages 95-118, Palgrave Macmillan.
    15. Walther G. Hoffmann, 1963. "The Take-off in Germany," International Economic Association Series, in: W. W. Rostow (ed.), The Economics of Take-Off into Sustained Growth, chapter 0, pages 95-118, Palgrave Macmillan.
    16. Rajan, Raghuram G. & Zingales, Luigi, 2003. "The great reversals: the politics of financial development in the twentieth century," Journal of Financial Economics, Elsevier, vol. 69(1), pages 5-50, July.
    17. Thomas J. Sargent & Christopher A. Sims, 1977. "Business cycle modeling without pretending to have too much a priori economic theory," Working Papers 55, Federal Reserve Bank of Minneapolis.
    18. Helling Gertrud, 1965. "Berechnung eines Index der Agrarproduktion in Deutschland im 19. Jahrhundert," Jahrbuch für Wirtschaftsgeschichte / Economic History Yearbook, De Gruyter, vol. 6(4), pages 125-151, April.
    19. A'Hearn, Brian & Woitek, Ulrich, 2001. "More international evidence on the historical properties of business cycles," Journal of Monetary Economics, Elsevier, vol. 47(2), pages 321-346, April.
    20. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, April.
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    Cited by:

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    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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).
    7. 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.
    8. 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.
    9. Ritschl, Albrecht & Uebele, Martin, 2005. "Stock markets and business cvycle comovement in Germany before World War I: Evidence from spectral analysis," SFB 649 Discussion Papers 2005-056, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. 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.
    11. 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.
    12. 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.
    13. 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.

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    More about this item

    Keywords

    Business Cycle Chronology; Imperial Germany; Dynamic Factor Models; Industrialization;
    All these keywords.

    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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