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A State-Space Model to Estimate Potential Growth in the Industrialized Countries

  • Thomas Brand
  • Gilles DufrénotEmail author
  • Antoine Mayerowitz
Chapter
  • 18 Downloads
Part of the Dynamic Modeling and Econometrics in Economics and Finance book series (DMEF, volume 27)

Abstract

This paper proposes new estimates of potential growth for 5 major industrialized countries. We use a state-space approach to obtain joint estimates of potential growth and the natural interest rates. The model is a reduced-form of a partial equilibrium model with a Phillips curve and an IS curve. In addition to the usual determinants of prices and business fluctuations, we consider financial variables as a determinant of the business cycle.

Keywords

Potential growth State-space models Long-memory Industrialized countries 

References

  1. Alichi, A. (2015). A new methodology for estimating the output gap in the United States (pp. 15–144). International Monetary Fund.Google Scholar
  2. Andrés, J., Lopez-Salido, J. D., & Nelson, E. (2005). Sticky-price models and the natural rate hypothesis. Journal of Monetary Economics, 52, 1025–1053.CrossRefGoogle Scholar
  3. Andrle, M. (2013). What is in your output gap? Unified framework & decomposition into observables (pp. 13–105). International Monetary Fund.Google Scholar
  4. Benati, L., & Vitale, G. (2007). Joint estimation of the natural rate of interest, the natural rate of unemployment, expected inflation, and potential output.Google Scholar
  5. Beneš, J., Clinton, K., García-Saltos, R., Johnson, M. P., Laxton, D., Manchev, P. B., & Matheson, T. (2010). Estimating potential output with a multivariate filter. In IMF Working Papers (pp. 1–37).Google Scholar
  6. Blagrave, P., Garcia-Saltos, M. R., Laxton, M. D., & Zhang, F. (2015). A simple multivariate filter for estimating potential output (pp. 15–79). International Monetary Fund.Google Scholar
  7. Borio, C. E., Disyatat, P., & Juselius, M. (2013). Rethinking potential output: Embedding information about the financial cycle.Google Scholar
  8. Borio, C. E., Disyatat, P., & Juselius, M. (2014). A parsimonious approach to incorporating economic information in measures of potential output.Google Scholar
  9. Cheremukhin, A. A., et al. (2013). Estimating the output gap in real time. Staff Papers.Google Scholar
  10. Claessens, S., Kose, M. A., & Terrones, M. E. (2012). How do business and financial cycles interact? Journal of International Economics, 87, 178–190.CrossRefGoogle Scholar
  11. Clancy, D. (2013). Output gap estimation uncertainty: extracting the TFP cycle using an aggregated PMI series. The Economic and Social Review, 44, 1–18.Google Scholar
  12. Drehmann, M., Borio, C. E., & Tsatsaronis, K. (2012). Characterising the financial cycle: Don’t lose sight of the medium term!.Google Scholar
  13. Edge, R. M., Kiley, M. T., & Laforte, J. P. (2008). Natural rate measures in an estimated DSGE model of the US economy. Journal of Economic Dynamics and control, 32, 2512–2535.CrossRefGoogle Scholar
  14. Epstein, N. P., & Macchiarelli, C. (2010). Estimating Poland’s potential output: A production function approach (pp. 10–15). International Monetary Fund.Google Scholar
  15. Keen, S. (2011). Debunking economics: The naked emperor dethroned? Zed Books Ltd.Google Scholar
  16. Laubach, T., & Williams, J. C. (2003). Measuring the natural rate of interest. The Review of Economics and Statistics, 85, 1063–1070.CrossRefGoogle Scholar
  17. Laubach, T., Williams, J. C., et al. (2015). Measuring the natural rate of interest redux. Federal Reserve Bank of San Francisco.Google Scholar
  18. McNelis, P. D., Bagsic, C. B., & Guinigundo, D. C. (2007). Output gap estimation for inflation forecasting: The case of the philippines. Center for Monetary and Financial Policy, BSP Working Paper Series.Google Scholar
  19. Minsky, H. P. (1992). The financial instability hypothesis. The Jerome Levy Economics Institute Working Paper.Google Scholar
  20. Okun, A. M. (1962). Potential gnp: its measurement and significance. In Proceedings of the Business and Economic Statistics Section of the American Statistical Association (pp. 89–104). Washington, DC.Google Scholar
  21. Proietti, T. (2009). Structural time series models for business cycle analysis. Palgrave handbook of econometrics (pp. 385–433). Springer.Google Scholar
  22. Schularick, M., & Taylor, A. (2012). Credit booms gone bust: Monetary policy, leverage cycles, and financial crises, 1870–2008. American Economic Review, 102, 1029–1061.CrossRefGoogle Scholar
  23. Vetlov, I., Hlédik, T., Jonsson, M., Henrik, K., & Pisani, M. (2011). Potential output in DSGE models.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2021

Authors and Affiliations

  • Thomas Brand
    • 1
  • Gilles Dufrénot
    • 2
    Email author
  • Antoine Mayerowitz
    • 3
  1. 1.CEPREMAPParisFrance
  2. 2.Aix-Marseille School of Economics and CEPIIMarseilleFrance
  3. 3.Paris School of EconomicsParisFrance

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