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Embedding Liquidity Information in Estimating Potential Output

Author

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  • Stefano Scalone

    (Department of Economics (University of Verona))

Abstract

This paper analyzes and extends the original study by Borio (2013), which includes proxies for the financial cycle in the process for estimating potential output. We extend the estimation to more countries (USA, UK, Spain, Italy, France, Austria, Netherlands and Switzerland) to check the robustness of the original method, and propose short-term debt as a new proxy for liquidity. We confirm that "finance neutral" measures of potential output are more reliable even though the original proxies are not particularly robust across countries, and that including liquidity information in the estimation process (whose analysis is conducted for United States, Australia and Canada) leads to better estimates, that are significant in all of the countries we analyze.

Suggested Citation

  • Stefano Scalone, 2014. "Embedding Liquidity Information in Estimating Potential Output," Working Papers 20/2014, University of Verona, Department of Economics.
    • Handle: RePEc:ver:wpaper:20/2014
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    References listed on IDEAS

    as
    1. Christophe Cahn & Arthur Saint-Guilhem, 2010. "Potential output growth in several industrialised countries a comparison," Empirical Economics, Springer, vol. 39(1), pages 139-165, August.
    2. Claudio BorioBy & Piti Disyatat & Mikael Juselius, 2017. "Rethinking potential output: embedding information about the financial cycle," Oxford Economic Papers, Oxford University Press, vol. 69(3), pages 655-677.
    3. Markus Brunnermeier & Gary Gorton & Arvind Krishnamurthy, 2013. "Liquidity Mismatch Measurement," NBER Chapters, in: Risk Topography: Systemic Risk and Macro Modeling, pages 99-112, National Bureau of Economic Research, Inc.
    4. Efraim Benmelech & Eyal Dvir, 2010. "Does short-term debt increase vulnerability to crisis? Evidence from the East Asian financial crisis," Proceedings, Federal Reserve Bank of San Francisco, issue Oct.
    5. Frédéric Boissay & Fabrice Collard & Frank Smets, 2016. "Booms and Banking Crises," Journal of Political Economy, University of Chicago Press, vol. 124(2), pages 489-538.
    6. Claudio Borio & Mathias Drehmann, 2011. "Toward an Operational Framework for Financial Stability: “Fuzzy” Measurement and Its Consequences," Central Banking, Analysis, and Economic Policies Book Series, in: Rodrigo Alfaro (ed.),Financial Stability, Monetary Policy, and Central Banking, edition 1, volume 15, chapter 4, pages 063-123, Central Bank of Chile.
    7. Lourdes Acedo Montoya & Björn Döhring, 2011. "The improbable renaissance of the Phillips curve: The crisis and euro area inflation dynamics," European Economy - Economic Papers 2008 - 2015 446, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    8. Orphanides, Athanasios & van Norden, Simon, 2005. "The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 583-601, June.
    9. Benmelech, Efraim & Dvir, Eyal, 2013. "Does Short-Term Debt Increase Vulnerability to Crisis? Evidence from the East Asian Financial Crisis," Journal of International Economics, Elsevier, vol. 89(2), pages 485-494.
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    JEL classification:

    • 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
    • E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General
    • E60 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General

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