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Financial Crises, Credit Booms, and External Imbalances: 140 Years of Lessons

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Abstract

Do external imbalances increase the risk of financial crises? This paper studies the experience of 14 developed countries over 140 years (1870–2008). It exploits the long-run data set in a number of different ways. First, the paper applies new statistical tools to describe the temporal and spatial patterns of crises and identifies five episodes of global financial instability in the past 140 years. Second, it studies the macroeconomic dynamics before crises and shows that credit growth tends to be elevated and short-term interest rates depressed relative to the “natural rate” in the run-up to global financial crises. Third, the paper shows that recessions associated with crises lead to deeper slumps and stronger turnarounds in imbalances than during normal recessions. Finally, the paper asks to what extent external imbalances help predict financial crises. The overall result is that credit growth emerges as the single best predictor of financial instability. External imbalances have played an additional role, but more so in the pre-WWII era of low financialization than today.

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Notes

  1. Also limits to liability and a short-term bonus culture have been cited as a reason for excessive risk taking (Alessandri and Haldane, 2009; Hume and Sentance, 2009). Others have pointed to political incentives for excessive risk taking as part of a mistaken social policy agenda.

  2. We thank: Antonio Tena Junguito (Spain); Gert den Bakker (the Kingdom of the Netherlands—Netherlands); and Tobias Straumann (Switzerland). Felix Mihram provided excellent research assistance.

  3. We wish to thank, without implicating, Daniel Waldenstroem (Stockholm), Pierre-Cyrille Hautcoeur and Angelo Riva (Paris), Jan Klovland (Oslo), Carl-Ludwig Holtfrerich (Berlin), Reinhard Spree (Munich), Margrit Grabas (Saarbrucken), Charles Tilly (Munster), Mari Oonuki (Tokyo), Tobias Straumann (Zurich), Joost Jonker (Utrecht), Michael Bordo (Rutgers), and Pablo Martin-Acenã (Alcalà). We asked these scholars whether they agreed that systemic banking crises took place in the given years and if any events were missing. In a few cases the question was not whether a significant crisis had occurred, but whether it should be called systemic. In such cases, we used some discretion to ensure comparability between countries. We generally coded crises if a significant part of the banking system was affected as measured by the number or the size of affected institutions.

  4. Customarily, TP(c), the true positive rate, is called sensitivity and TP(c), the true negative rate, is called specificity.

  5. Let u denote the values of ŷ for which S=1 and let v denote the values of ŷ for which S=0. Then, a simple, nonparametric estimate of the AUC is

    The AUC can be interpreted as P(v<u) (see Green and Swets, 1996) and if T P /T N → λ>0 as T → ∞, under standard regularity conditions Hsieh and Turnbull (1996) show that

    where the formula for σ2 can be found in Jordà and Taylor (2010). The asymptotic normality result makes this statistic particularly convenient since hypothesis tests can be constructed using the Wald principle.

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Authors

Additional information

Supplementary Information accompanies the paper on the IMF Economic Review website (www.palgrave-journals.com/imfer)

*Òscar Jordà is professor of Economics at the University of California, Davis. Moritz Schularick is professor of Economics and Economic History at the John-F.-Kennedy Institute of the Free University of Berlin, Germany. Alan M. Taylor is professor of Economics at the University of California, Davis; senior advisor at Morgan Stanley; research associate at the National Bureau of Economic Research; and research fellow at the Centre for Economic Policy Research. Taylor has been supported by the Center for the Evolution of the Global Economy at UC Davis and Jordà by DGCYT Grant (SEJ2007-63098-econ). Some work was completed while Taylor was a Houblon-Norman/George Fellow at the Bank of England, and later when he was a Senior Advisor at Morgan Stanley. All of this support is gratefully acknowledged. Felix Mihram provided excellent research assistance. The authors thank their discussant at the 2010 IMF ARC, Linda Tesar, the editors, and the referees for valuable comments. All errors are the authors’ own.

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Appendices

Appendix I

Data Sources

All data come from Schularick and Taylor (forthcoming), except for current accounts and equity prices. Historical equity prices come from the Global Financial Database, with the following exceptions:

U.S.A.: Shiller, Robert 2000, Irrational Exuberance (Princeton University Press). 2009 updates from www.econ.yale.edu/shiller/data.htm

Sweden: Waldenstroem, Daniel, “Swedish Stock Prices and Returns and Bond Yields, 1856–2006,” forthcoming in R. Edvinsson, T. Jacobsson, and D. Waldenstroem, Historical Monetary and Financial Statistics for Sweden, Vol. 2, Sveriges Riksbank.

Netherlands: Tweehonderd jaar statistiek in tijdreeksen, 1800–1999, University of Groningen and Centraal Bureau voor de Statistiek, Voorburg/Heerlrn 2001, Table 10. Data made available by Peter Koujdis (Barcelona).

France: new series made available by Pierre-Cyrille Hautcoeur, Paris.

Italy: Da Pozzo, M. and G. Felloni, La Borsa Valori di Genova nel secolo XIX, Torino, ILTE, 1963, Tab. LXVII, p. 499; and Parodi, S., Il mercato finanziario genovese dal 1895 al 1914, unpublished mater thesis (tesi di laurea), University of Genoa, 1966, Tab XLV, p. 238. Data made available by Angelo Riva (Paris).

Norway: Klovland, J.T., 2004, “Historical Stock Price Indices in Norway 1914–2001,” in Historical Monetary Statistics for Norway 1819–2003, Chapter 8, ed. by Ø. Eitrheim, J.T. Klovland, and J.F. Qvigstad, pp. 329-348, , Norges Bank Occasional Papers no. 35, Oslo, 2004.

Current account data, unless otherwise stated, come from the following three sources:

  1. i)

    J/O: Jones and Obstfeld data set (www.nber.org/databases/jones-obstfeld/).

  2. ii)

    Mitchell: Mitchell (2007a, 2007b, and 2007c).

  3. iii)

    IFS: International Financial Statistics (2010).

Australia:

  • 1870–1945 J/O

  • 1946–1959 Mitchell

  • 1960–2008 IFS

Canada:

  • 1870–1945 J/O

  • 1948–2009 IFS

Switzerland:

  • 1921–1939 Kellenberg, Eduard (1939–1942): Kapitalexport und Zahlungsbilanz; Bern: A. Francke; Bd. I: S. 155, 245, 307; Bd. II: S. 87, 244f, 364f.

  • 1948–1976 Mitchell

  • 1977–2009 IFS

Germany:

  • 1872–1938 J/O

  • 1948–1973 Mitchell

  • 1974–2009 IFS

Denmark:

  • 1874–1945 J/O

  • 1946–1974 Mitchell

  • 1975–2009 IFS

Spain:

France:

  • 1870–1945 J/O

  • 1948–1974 Mitchell

  • 1975–2009 IFS

Great Britain:

  • 1870–1945 J/O

  • 1946–1969 Mitchell

  • 1970–2009 IFS

Italy:

  • 1870–1945 J/O

  • 1946–1969 Mitchell

  • 1970–2009 IFS

Japan:

  • 1870–1944 J/O

  • 1948–1976 Mitchell

  • 1977–2009 IFS

Netherlands:

  • 1870–1913 Smits, Horlings, and van Zanden (2000)

  • 1921–1939 Statistics Netherlands, National accounts of the Netherlands (various issues), provided by Gert den Bakker (CBS Netherland)

  • 1948–1966 Mitchell

  • 1967–2009 IFS

Norway:

  • 1870–1939 J/O

  • 1946–1974 Mitchell

  • 1975–2009 IFS

Sweden:

  • 1870–1945 J/O

  • 1946–1969 Mitchell

  • 1970–2009 IFS

United States:

  • 1870–1945 J/O

  • 1946–1969 Mitchell

  • 1970–2009 IFS

Appendix II

Business Cycle Dating

We identify business cycle peaks using real GDP per capita. If output per capita growth was negative in any given year, we coded the preceding year as the business cycle peak. We then adjusted the resulting series for short-term rebounds within recessions. These are cases when output rebounded but failed to recover the prerecession level and fell again in the following year. We treated such short-term rebounds as part of the same recessionary episode and not as independent business cycles. Some minor adjustments were also made when country histories and other data sources suggested a slightly different chronology. For example, some differences may arise when accepted chronologies are built on higher-frequency (quarterly/monthly) data, in contrast to our annual data. In such cases, we moved the peak year by a maximum of one year to align our chronology with the accepted country histories.

  • D: Deleted peaks A: Added peaks

  • Australia: D: 1881, 1892, 1904, 1913, 1916, 1929, 1956, 1976 A: 1891

  • Canada D: 1874, 1882, 1920, 1931, 1947 A:1884

  • Switzerland D: 1878, 1881, 1902, 1951, 1994 A:1880

  • Germany D: 1875, 1931, 1928 A: 1874, 1929

  • Denmark D: 1870, 1917

  • Spain D: 1886, 1889, 1895, 1904, 1932

  • France D: 1872, 1875, 1878, 1885, 1916, 1933 A: 1874

  • U.K. D: 1871, 1878, 1892, 1902, 1938, 1946

  • Italy D: 1870, 1897, 1923, 1932

  • Japan D: 1883, 1904, 1922, 1933 A: 1992

  • Netherlands D: 1870, 1892, 1916, 1932, 1943

  • Norway D: 1881, 1893, 1923, 1942 A: 1941

  • Sweden D: 1883, 1886, 1904 A: 1885, 1888

  • U.S.A. D: 1916, 1919, 1932 A: 1918

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Jordà, Ò., Schularick, M. & Taylor, A. Financial Crises, Credit Booms, and External Imbalances: 140 Years of Lessons. IMF Econ Rev 59, 340–378 (2011). https://doi.org/10.1057/imfer.2011.8

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