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Are Bayesian Fan Charts Useful? The Effect of Zero Lower Bound and Evaluation of Financial Stability Stress Tests

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  • Michal Franta

    (International Monetary Fund)

  • Jozef Baruník

    (Institute of Economic Studies, Charles University, Prague, and UTIA, Czech Academy of Sciences)

  • Roman Horváth

    (Institute of Economic Studies, Charles University, Prague)

  • Katerina Smídková

    (Czech National Bank, and Institute of Economic Studies, Charles University, Prague)

Abstract

We show how fan charts generated from Bayesian vector autoregression models can be useful for assessing (i) the effect of the zero-lower-bound constraint on forecasting uncertainty and (ii) the credibility of stress tests conducted to evaluate financial stability. To illustrate these issues, we use a data set for the Czech Republic and macroeconomic scenarios that are used by the Czech National Bank (CNB) in stress tests of the banking sector. Our results demonstrate how different modeling approaches to the zero lower bound affect the resulting fan charts. The pros and cons of the considered methods are discussed; ignoring the zero-lower-bound constraint represents the worst approach. Next, using our fan charts, we propose a method for evaluating whether the assumptions that are employed in the bank’s stress tests regarding the macroeconomic outlook are sufficiently adverse and consistent with past cross-correlations observed in the data. We find that CNB stress tests are sufficiently conservative in this respect.

Suggested Citation

  • Michal Franta & Jozef Baruník & Roman Horváth & Katerina Smídková, 2014. "Are Bayesian Fan Charts Useful? The Effect of Zero Lower Bound and Evaluation of Financial Stability Stress Tests," International Journal of Central Banking, International Journal of Central Banking, vol. 10(1), pages 159-188, March.
  • Handle: RePEc:ijc:ijcjou:y:2014:q:1:a:5
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    as
    1. Maximiano Pinheiro & Paulo Esteves, 2012. "On the uncertainty and risks of macroeconomic forecasts: combining judgements with sample and model information," Empirical Economics, Springer, vol. 42(3), pages 639-665, June.
    2. Roman Horvath & Dan Vaško, 2012. "Central Bank Transparency and Financial Stability: Measurement, Determinants and Effects," Working Papers IES 2012/25, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2012.
    3. Nergiz Dincer & Barry Eichengreen, 2009. "Central Bank Transparency: Causes, Consequences and Updates," NBER Working Papers 14791, National Bureau of Economic Research, Inc.
    4. Daniel F. Waggoner & Tao Zha, 1999. "Conditional Forecasts In Dynamic Multivariate Models," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 639-651, November.
    5. James Mitchell & Stephen G. Hall, 2005. "Evaluating, Comparing and Combining Density Forecasts Using the KLIC with an Application to the Bank of England and NIESR ‘Fan’ Charts of Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 995-1033, December.
    6. Gill Hammond, 2012. "State of the art of inflation targeting," Handbooks, Centre for Central Banking Studies, Bank of England, edition 4, number 29, April.
    7. Tilmann Gneiting & Roopesh Ranjan, 2011. "Comparing Density Forecasts Using Threshold- and Quantile-Weighted Scoring Rules," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(3), pages 411-422, July.
    8. Dr. James Mitchell, 2005. "Evaluating, comparing and combining density forecasts using the KLIC with an application to the Bank of England and NIESR ÔfanÕ charts of inflation," National Institute of Economic and Social Research (NIESR) Discussion Papers 253, National Institute of Economic and Social Research.
    9. Cogley, Timothy & Morozov, Sergei & Sargent, Thomas J., 2005. "Bayesian fan charts for U.K. inflation: Forecasting and sources of uncertainty in an evolving monetary system," Journal of Economic Dynamics and Control, Elsevier, vol. 29(11), pages 1893-1925, November.
    10. Renee Fry & Adrian Pagan, 2005. "Some Issues In Using Vars For Macroeconometric Research," CAMA Working Papers 2005-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    11. Michael P. Clements, 2004. "Evaluating the Bank of England Density Forecasts of Inflation," Economic Journal, Royal Economic Society, vol. 114(498), pages 844-866, October.
    12. Dr. James Mitchell, 2005. "Evaluating, comparing and combining density forecasts using the KLIC with an application to the Bank of England and NIESR ÔfanÕ charts of inflation," National Institute of Economic and Social Research (NIESR) Discussion Papers 253, National Institute of Economic and Social Research.
    13. Giannone, Domenico & Lenza, Michele & Momferatou, Daphne & Onorante, Luca, 2014. "Short-term inflation projections: A Bayesian vector autoregressive approach," International Journal of Forecasting, Elsevier, vol. 30(3), pages 635-644.
    14. Thomas Breuer & Martin Jandacka & Klaus Rheinberger & Martin Summer, 2009. "How to Find Plausible, Severe and Useful Stress Scenarios," International Journal of Central Banking, International Journal of Central Banking, vol. 5(3), pages 205-224, September.
    15. Jan Babecky & Ales Bulir & Katerina Smidkova, 2012. "Sustainable Real Exchange Rates in the New EU Member States: What Did the Great Recession Change?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 62(3), pages 226-251, July.
    16. Rodrigo Alfaro & Mathias Drehmann, 2009. "Macro stress tests and crises: what can we learn?," BIS Quarterly Review, Bank for International Settlements, December.
    17. Par Osterholm, 2008. "A structural Bayesian VAR for model-based fan charts," Applied Economics, Taylor & Francis Journals, vol. 40(12), pages 1557-1569.
    18. Stephen Murchison & Andrew Rennison, 2006. "ToTEM: The Bank of Canada's New Quarterly Projection Model," Technical Reports 97, Bank of Canada.
    19. Kadiyala, K Rao & Karlsson, Sune, 1997. "Numerical Methods for Estimation and Inference in Bayesian VAR-Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 99-132, March-Apr.
    20. Goodhart, C.A.E., 2006. "A framework for assessing financial stability?," Journal of Banking & Finance, Elsevier, vol. 30(12), pages 3415-3422, December.
    21. Gneiting, Tilmann & Ranjan, Roopesh, 2011. "Comparing Density Forecasts Using Threshold- and Quantile-Weighted Scoring Rules," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(3), pages 411-422.
    22. Breuer, Thomas & Jandačka, Martin & Mencía, Javier & Summer, Martin, 2012. "A systematic approach to multi-period stress testing of portfolio credit risk," Journal of Banking & Finance, Elsevier, vol. 36(2), pages 332-340.
    23. Mr. Prakash Kannan & Mr. Selim A Elekdag, 2009. "Incorporating Market Information into the Construction of the Fan Chart," IMF Working Papers 2009/178, International Monetary Fund.
    24. Litterman, Robert, 1986. "Forecasting with Bayesian vector autoregressions -- Five years of experience : Robert B. Litterman, Journal of Business and Economic Statistics 4 (1986) 25-38," International Journal of Forecasting, Elsevier, vol. 2(4), pages 497-498.
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    Cited by:

    1. McDonald, Christopher & Thamotheram, Craig & Vahey, Shaun P. & Wakerly, Elizabeth C., 2015. "Assessing the Economic Value of Probabilistic Forecasts in the Presence of an Inflation Target," EMF Research Papers 09, Economic Modelling and Forecasting Group.
    2. Knüppel, Malte & Krüger, Fabian, 2017. "Forecast Uncertainty, Disagreement, and Linear Pools of Density Forecasts," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168294, Verein für Socialpolitik / German Economic Association.
    3. Milan Szabo, 2020. "Growth-at-Risk: Bayesian Approach," Working Papers 2020/3, Czech National Bank.
    4. Ahmad Razi & Po Ling Loke, 2017. "Fan Chart: The art and science of communicating uncertainty," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Statistical implications of the new financial landscape, volume 43, Bank for International Settlements.
    5. Oxana Babecka Kucharcukova & Alexis Derviz & Vaclav Hausenblas & Michal Hlavacek & Mark Joy & Narcisa Kadlcakova & Lubos Komarek & Zlatuse Komarkova & Tomas Konecny & Ivana Kubicova & Jitka Lesanovska, 2014. "Macroprudential Research: Selected Issues," Occasional Publications - Edited Volumes, Czech National Bank, edition 2, volume 12, number rb12/2 edited by Jan Babecky & Borek Vasicek, January.
    6. Franta, Michal, 2017. "Rare shocks vs. non-linearities: What drives extreme events in the economy? Some empirical evidence," Journal of Economic Dynamics and Control, Elsevier, vol. 75(C), pages 136-157.
    7. Milan Szabo & Zlatuse Komarkova & Martin Casta, 2020. "Vulnerable growth: Bayesian GDP-at-Risk," Occasional Publications - Chapters in Edited Volumes,, Czech National Bank.
    8. Michal Franta, 2016. "The Effect of Nonlinearity between Credit Conditions and Economic Activity on Density Forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 147-166, March.
    9. Irving Fisher Committee, 2017. "Statistical implications of the new financial landscape," IFC Bulletins, Bank for International Settlements, number 43.
    10. Lubomír Lízal & Jirí Schwarz, 2013. "Foreign exchange interventions as an (un)conventional monetary policy tool," BIS Papers chapters, in: Bank for International Settlements (ed.), Sovereign risk: a world without risk-free assets?, volume 73, pages 127-143, Bank for International Settlements.
    11. Damian Stelmasiak & Grzegorz Szafrański, 2016. "Forecasting the Polish Inflation Using Bayesian VAR Models with Seasonality," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 21-42, March.
    12. Andrew Binning & Junior Maih, 2016. "Forecast uncertainty in the neighborhood of the effective lower bound: How much asymmetry should we expect?," Working Paper 2016/13, Norges Bank.
    13. Farooq Akram & Andrew Binning & Junior Maih, 2016. "Joint Prediction Bands for Macroeconomic Risk Management," Working Papers No 5/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    14. Frantisek Brazdik & Jan Bruha & Michal Franta & David Havrlant & Tibor Hledik & Tomas Holub & Zuzana Humplova & Frantisek Kopriva & Jiri Polansky & Marek Rusnak & Jaromir Tonner, 2015. "Forecasting," Occasional Publications - Edited Volumes, Czech National Bank, edition 1, volume 13, number rb13/1 edited by Jan Babecky & Kamil Galuscak, January.
    15. Michal Andrle & Oxana Babecka Kucharcukova & Jaromir Baxa & Jan Bruha & Peter Claeys & Jan Filacek & Jakub Mateju & Miroslav Plasil & Serhat Solmaz & Borek Vasicek, 2015. "Monetary Policy Challenges in a Low-Inflation Environment," Occasional Publications - Edited Volumes, Czech National Bank, edition 2, volume 13, number rb13/2 edited by Jan Babecky & Michal Franta, January.
    16. Jan Bruha & Jiri Polansky & Jaromir Tonner & Stanislav Tvrz & Osvald Vasicek & Jan Babecky & Kamil Galuscak & Lubomir Lizal & Diana Zigraiova, 2016. "Topics in Labour Markets," Occasional Publications - Edited Volumes, Czech National Bank, edition 1, volume 14, number rb14/1 edited by Jan Babecky, January.
    17. Ohnsorge,Franziska Lieselotte & Stocker,Marc & Some,Modeste Y., 2016. "Quantifying uncertainties in global growth forecasts," Policy Research Working Paper Series 7770, The World Bank.
    18. Miroslav Plasil & Jakub Seidler & Petr Hlavac & Volha Audzei & Jakub Mateju & Michal Kejak & Simona Malovana & Jan Frait, 2016. "Financial Cycles and Macroprudential and Monetary Policies," Occasional Publications - Edited Volumes, Czech National Bank, edition 2, volume 14, number rb14/2 edited by Jan Babecky & Michal Hlavacek, January.
    19. Malte Knüppel & Fabian Krüger, 2022. "Forecast uncertainty, disagreement, and the linear pool," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 23-41, January.
    20. Hamid Baghestani & Liliana Danila, 2014. "Interest Rate and Exchange Rate Forecasting in the Czech Republic: Do Analysts Know Better than a Random Walk?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(4), pages 282-295, September.
    21. Kamil Galuscak & Adam Gersl & Marcela Gronychova & Petr Hlavac & Petr Jakubik & Lubos Komarek & Zlatuse Komarkova & Tomas Konecny & Jakub Seidler, 2014. "Stress-Testing Analyses of the Czech Financial System," Occasional Publications - Edited Volumes, Czech National Bank, edition 1, volume 12, number rb12/1 edited by Jan Babecky & Roman Horvath, January.
    22. Michal Franta & Tomas Holub & Petr Kral & Ivana Kubicova & Katerina Smidkova & Borek Vasicek, 2014. "The Exchange Rate as an Instrument at Zero Interest Rates: The Case of the Czech Republic," Research and Policy Notes 2014/03, Czech National Bank.
    23. Jackson, Emerson Abraham & Tamuke, Edmund, 2021. "The Science and Art of Communicating Fan Chart Uncertainty: The case of Inflation Outcome in Sierra Leone," MPRA Paper 105892, University Library of Munich, Germany, revised 05 Jan 2021.

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    JEL classification:

    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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