Journal of Business Cycle Research

, Volume 13, Issue 2, pp 165–187 | Cite as

Stylized Facts of the Business Cycle: Universal Phenomenon, or Institutionally Determined?

  • Vadim KufenkoEmail author
  • Niels Geiger
Research Paper


This paper empirically investigates and theoretically reflects on the generality of some “stylized facts” of business cycles. Using data for 1960–2016 and a sample of OECD countries, the duration of business cycles as well as three models capturing core macroeconomic relations are estimated: the Phillips curve (the inflation-unemployment nexus), Okun’s law (i.e. the relation between output growth and unemployment) and the inflation-output relation. Results are validated by relevant statistical tests. Observed durations vary from 4.2 to 7.4 years, and estimated coefficients differ in signs and magnitudes. An explanation of this heterogeneity is attempted by referring to proxies for various institutional variables. The findings suggest that core coefficients in the relations, such as the slope of the Phillips curve, show significant correlation with some of these variables, but no uniform results are obtained. In the detailed theoretical discussion and interpretation it is thus argued that the notable differences between countries call the universality of the “stylized facts” into question, but also that these variations cannot be explained exhaustively by the institutional proxy variables employed here.


Business cycles Empirical analysis Institutions Stylized facts 

JEL Classification

E02 E32 E39 F44 



The authors would like to express their gratitude to Harald Hagemann, Martyna Marczak, Klaus Prettner and Johannes Schwarzer for their support during the work on the given paper and beyond. In addition, the authors are thankful to Michael Graff and the anonymous referees for their suggestions and comments.


  1. Acemoglu, D., Johnson, S., & Robinson, J. A. (2005). Institutions as fundamental cause of long-run growth. In P. Aghion & S. N. Durlauf (Eds.), Handbook of economic growth (Vol. 1A, pp. 385–472). Amsterdam: Elsevier.Google Scholar
  2. Agresti, A.-M., & Mojon, B. (2001). Some stylised facts on the euro area business cycle. ECB working paper series, 95.Google Scholar
  3. Altug, S., & Canova, F. (2014). Do institutions and culture matter for business cycles? Open Economies Review, 25(1), 93–122.CrossRefGoogle Scholar
  4. Altug, S., Neyapti, B., & Emin, M. (2012). Institutions and business cycles. International Finance, 15(3), 347–366.CrossRefGoogle Scholar
  5. Andreano, M. S., & Savio, G. (2002). Further evidence on business cycle asymmetries in G7 countries. Applied Economics, 34(7), 895–904.CrossRefGoogle Scholar
  6. Arnone, M., Laurens, B. J., Segalotto, J.-F., & Sommer, M. (2007). Central bank autonomy: Lessons from global trends. IMF working papers 07/88, International Monetary Fund.Google Scholar
  7. Bassani, A., & Duval R. (2006). Employment patterns in OECD countries: Reassessing the role of policies and institutions. OECD social, employment and migration working paper no. 35.Google Scholar
  8. Baxter, M., & King, R. (1999). Measuring business cycles: Approximate band-pass filters for economic time series. The Review of Economics and Statistics, 81(4), 575–593.CrossRefGoogle Scholar
  9. Benczur, P., & Ratfai, A. (2014). Business cycles around the globe: Some key facts. Emerging Markets Finance and Trade, 50(2), 102–109.CrossRefGoogle Scholar
  10. Bergman, U. M., Bordo, M. D., & Jonung, L. (1998). Historical evidence on business cycles: The international experience. In J. C. Fuhrer & S. Schuh (Eds.), Beyond shocks: What causes business cycles?, volume 42 of conference series (pp. 65–113). Boston: Federal Reserve Bank of Boston.Google Scholar
  11. Breusch, T. S. (1978). Testing for autocorrelation in dynamic linear models*. Australian Economic Papers, 17(31), 334–355.CrossRefGoogle Scholar
  12. Breusch, T. S., & Pagan, A. R. (1979). A simple test for heteroscedasticity and random coefficient variation. Econometrica, 47(5), 1287–94.CrossRefGoogle Scholar
  13. Burns, A. F., & Mitchell, W. C. (1946). Measuring business cycles. NBER book series studies in business cycles. New York: NBER.Google Scholar
  14. Calmfors, L., Driffill, J., Honkapohja, S., & Giavazzi, F. (1988). Bargaining structure, corporatism and macroeconomic performance. Economic Policy, 3(6), 14–61.CrossRefGoogle Scholar
  15. Canova, F., Ciccarelli, M., & Ortega, E. (2012). Do institutional changes affect business cycles? Evidence from europe. Journal of Economic Dynamics and Control, 36(10), 1520–1533.CrossRefGoogle Scholar
  16. Cukierman, A., Webb, S. B., & Neyapti, B. (1992). Measuring the independence of central banks and its effect on policy outcomes. The World Bank Economic Review, 6(3), 353–398.CrossRefGoogle Scholar
  17. Fiorito, R., & Kollintzas, T. (1994). Stylized facts of business cycles in the g7 from a real business cycles perspective. European Economic Review, 38(2), 235–269.CrossRefGoogle Scholar
  18. Fonseca, R., Patureau, L., & Sopraseuth, T. (2009). Divergence in labor market institutions and international business cycles. Annals of Economics and Statistics, (95/96):279–314.Google Scholar
  19. Fonseca, R., Patureau, L., & Sopraseuth, T. (2010). Business cycle comovement and labor market institutions: An empirical investigation. Review of International Economics, 18(5), 865–881.CrossRefGoogle Scholar
  20. Glaeser, E. L., La Porta, R., Lopez-de Silanes, F., & Shleifer, A. (2004). Do institutions cause growth? Journal of Economic Growth, 9(3), 271–303.CrossRefGoogle Scholar
  21. Gnocchi, S., Lagerborg, A., & Pappa, E. (2015). Do labor market institutions matter for business cycles? Journal of Economic Dynamics and Control, 51, 299–317.CrossRefGoogle Scholar
  22. Godfrey, L. G. (1978). Testing against general autoregressive and moving average error models when the regressors include lagged dependent variables. Econometrica, 46(6), 1293–1301.CrossRefGoogle Scholar
  23. Haberler, G. (1946). Prosperity and depression. A theoretical analysis of cyclical movements (3rd ed.). New York: United Nations.Google Scholar
  24. Hodrick, R. J., & Prescott, E. C. (1997). Postwar U.S. business cycles: An empirical investigation. Journal of Money, Credit and Banking, 29(1), 1–16.CrossRefGoogle Scholar
  25. Huang, H.-C. R., & Yeh, C.-C. (2013). Okuns law in panels of countries and states. Applied Economics, 45(2), 191–199.CrossRefGoogle Scholar
  26. Johansen, S. (1995). Likelihood-based inference in cointegrated vector autoregressive models. Number 9780198774501 in OUP catalogue. Oxford: Oxford University Press.CrossRefGoogle Scholar
  27. Kaldor, N. (1957). A model of economic growth. The Economic Journal, 67(268), 591–624.CrossRefGoogle Scholar
  28. Kendall, M. G. (1938). A new measure of rank correlation. Biometrika, 30(1/2), 81–93.CrossRefGoogle Scholar
  29. Kollintzas, T., Konstantakopoulou, I., & Tsionas, E. (2011). Stylized facts of money and credit over the business cycles. Applied Financial Economics, 21(23), 1735–1755.CrossRefGoogle Scholar
  30. Kromphardt, J. (1993). Wachstum und Konjunktur. Grundlagen der Erklärung und Steuerung des Wachstumsprozesses, volume 26 of Grundriss der Sozialwissenschaft (3rd ed.). Göttingen: Vandenhoeck & Ruprecht.Google Scholar
  31. Kydland, F. E., & Prescott, E. C. (1990). Business cycles: Real facts and a monetary myth. Federal Reserve Bank of Minneapolis Quarterly Review, 14(Spring), 3–18.Google Scholar
  32. Lucas, R. E. (1977). Understanding business cycles. In K. Brunner & A. Meltzer (Eds.), Stabilization of the domestic and international economy (pp. 7–29). Amsterdam: North-Holland.Google Scholar
  33. Maußner, A. (1994). Konjunkturtheorie. Berlin: Springer.CrossRefGoogle Scholar
  34. Milanovic, B. (2014). All the Ginis database [ATG]. Accessed on August 30, 2017.Google Scholar
  35. Mitchell, W. C. (1951). What happens during business cycles: A progress report. NBER book series studies in business cycles. New York: NBER.Google Scholar
  36. Moosa, I. A. (1997). A cross-country comparison of Okun’s coefficient. Journal of Comparative Economics, 24(3), 335–356.CrossRefGoogle Scholar
  37. Newey, W. K., & West, K. D. (1987). A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55(3), 703–08.CrossRefGoogle Scholar
  38. Nickell, W. (2006). The CEP-OECD institutions data set (1960–2004). CEP discussion paper no. 759.Google Scholar
  39. North, D. C. (1991). Institutions. The Journal of Economic Perspectives, 5(1), 97–112.CrossRefGoogle Scholar
  40. Ochel, W. (2001). Collective bargaining coverage in the OECD from the 1960s to the 1990s. CESifo Forum, 2(4), 62–65.Google Scholar
  41. Okun, A. M. (1962). Potential GNP: Its measurement and significance. In American Statistical Association (ed.), Proceedings of the business and economic statistics section.Google Scholar
  42. Perman, R., & Tavera, C. (2005). A cross-country analysis of the Okun’s law coefficient convergence in Europe. Applied Economics, 37(21), 2501–2513.CrossRefGoogle Scholar
  43. Pisarenko, V. F. (1973). The retrieval of harmonics from a covariance function. Geophysical Journal of the Royal Astronomical Society, 33(3), 347–366.CrossRefGoogle Scholar
  44. Ravn, M. O., & Uhlig, H. (2002). On adjusting the Hodrick–Prescott filter for the frequency of observations. The Review of Economics and Statistics, 84(2), 371–375.CrossRefGoogle Scholar
  45. Rodrik, D. (2000). Institutions for high-quality growth: What they are and how to acquire them. Studies in Comparative International Development, 35(3), 3–31.CrossRefGoogle Scholar
  46. Romer, C. D. (2008). Business cycles. In D. R. Henderson (Ed.), The concise encyclopedia of economics (2nd ed.). Indianopolis: Library of Economics and Liberty.Google Scholar
  47. Rumler, F. & Scharler, J. (2009). Labor market institutions and macroeconomic volatility in a panel of OECD countries. ECB working paper series, 1005.Google Scholar
  48. Ryan, C. (2002). Business cycles: Stylized facts. In B. Snowdon & H. R. Vane (Eds.), An encyclopedia of macroeconomics (pp. 97–104). Cheltenham: Edward Elgar.Google Scholar
  49. Schmidt, R. O. (1986). Multiple emitter location and signal parameter estimation. IEEE Transactions on Antennas and Propagation, 34, 276–280.CrossRefGoogle Scholar
  50. Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3/4), 591–611.CrossRefGoogle Scholar
  51. Spearman, C. (1987). The proof and measurement of association between two things. By C. Spearman, 1904. The American Journal of Psychology, 100(3–4), 441–471.CrossRefGoogle Scholar
  52. Stock, J. H., & Watson, M. W. (2016). Dynamic factor models, factor-augmented vector autoregressions, and structural vector autoregressions in macroeconomics. In J. B. Taylor & H. Uhlig (Eds.), Handbook of macroeconomics (Vol. 2, pp. 415–525). Amsterdam: Elsevier.Google Scholar
  53. The Conference Board. (2017). Total economy database. Accessed on August 30, 2017.Google Scholar
  54. The World Bank. (2017). World development indicators, trade (% of GDP) [NE.TRD.GNFS.ZS]. Accessed on September 25, 2017.Google Scholar
  55. White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–38.CrossRefGoogle Scholar
  56. Woitek, U. (1997). Business cycles. An international comparison of stylized facts in a historical perspective. Heidelberg: Physica.Google Scholar
  57. Zarnowitz, V. (1992). Business cycles: Theory, history, indicators, and forecasting. NBER book series studies in business cycle. Chicagos: University of Chicago Press.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Institute of Economics (520H), Faculty of Business, Economics and Social SciencesUniversity of HohenheimStuttgartGermany

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