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Business Cycle Dating and Forecasting with Real-time Swiss GDP Data

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  • Christian Glocker

    (WIFO)

  • Philipp Wegmüller

Abstract

We develop a small-scale dynamic factor model for the Swiss economy based on an appropriately selected set of indicators. The resulting business cycle factor is in striking accordance with historical Swiss business cycle fluctuations. Our proposed model demonstrates a remarkable performance in short-term and medium-term forecasting. Using real-time GDP data since 2004, the model successfully anticipates the downturn of 2008-09 and responds in a timely manner to the recent sudden drop following the removal of the Swiss Franc lower bound. In a Markov-switching extension, we propose that our model could be used for Swiss recession dating. Our model does not indicate a regime-switch following the removal of the Swiss Franc lower bound.

Suggested Citation

  • Christian Glocker & Philipp Wegmüller, 2017. "Business Cycle Dating and Forecasting with Real-time Swiss GDP Data," WIFO Working Papers 542, WIFO.
    • Handle: RePEc:wfo:wpaper:y:2017:i:542
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    1. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
    2. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    3. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
    4. Adrian, Tobias & Shin, Hyun Song, 2010. "Liquidity and leverage," Journal of Financial Intermediation, Elsevier, vol. 19(3), pages 418-437, July.
    5. Duprey, Thibaut & Klaus, Benjamin & Peltonen, Tuomas, 2017. "Dating systemic financial stress episodes in the EU countries," Journal of Financial Stability, Elsevier, vol. 32(C), pages 30-56.
    6. Maximo Camacho & Gabriel Perez-Quiros, 2010. "Introducing the euro-sting: Short-term indicator of euro area growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 663-694.
    7. Christian Glocker & Serguei Kaniovski, 2014. "A financial market stress indicator for Austria," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 41(3), pages 481-504, August.
    8. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
    9. Camacho, Maximo & Perez-Quiros, Gabriel & Poncela, Pilar, 2018. "Markov-switching dynamic factor models in real time," International Journal of Forecasting, Elsevier, vol. 34(4), pages 598-611.
    10. S. Borağan Aruoba, 2008. "Data Revisions Are Not Well Behaved," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2‐3), pages 319-340, March.
    11. Marco Riguzzi & Philipp Wegmueller, 2017. "Economic Openness and Fiscal Multipliers," International Economic Journal, Taylor & Francis Journals, vol. 31(1), pages 1-35, January.
    12. Tommaso Proietti & Filippo Moauro, 2006. "Dynamic factor analysis with non‐linear temporal aggregation constraints," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(2), pages 281-300, April.
    13. G. Rünstler & K. Barhoumi & S. Benk & R. Cristadoro & A. Den Reijer & A. Jakaitiene & P. Jelonek & A. Rua & K. Ruth & C. Van Nieuwenhuyze, 2009. "Short-term forecasting of GDP using large datasets: a pseudo real-time forecast evaluation exercise," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(7), pages 595-611.
    14. Alain Galli, 2018. "Which Indicators Matter? Analyzing the Swiss Business Cycle Using a Large-Scale Mixed-Frequency Dynamic Factor Model," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(2), pages 179-218, November.
    15. Banbura, Marta & Rünstler, Gerhard, 2011. "A look into the factor model black box: Publication lags and the role of hard and soft data in forecasting GDP," International Journal of Forecasting, Elsevier, vol. 27(2), pages 333-346, April.
    16. Stark, Tom & Croushore, Dean, 2002. "Reply to the comments on 'Forecasting with a real-time data set for macroeconomists'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 563-567, December.
    17. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
    18. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2010. "Are disaggregate data useful for factor analysis in forecasting French GDP?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 132-144.
    19. N. Gregory Mankiw & Matthew D. Shapiro, 1986. "News or Noise? An Analysis of GNP Revisions," NBER Working Papers 1939, National Bureau of Economic Research, Inc.
    20. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
    21. Tony Chernis & Rodrigo Sekkel, 2017. "A dynamic factor model for nowcasting Canadian GDP growth," Empirical Economics, Springer, vol. 53(1), pages 217-234, August.
    22. Knut Aastveit & Tørres Trovik, 2012. "Nowcasting norwegian GDP: the role of asset prices in a small open economy," Empirical Economics, Springer, vol. 42(1), pages 95-119, February.
    23. Christian Glocker & Werner Hölzl, 2019. "Assessing the Economic Content of Direct and Indirect Business Uncertainty Measures," WIFO Working Papers 576, WIFO.
    24. Gerhard Fenz & Martin Spitzer, 2006. "An Unobserved Components Model to Forecast Austrian GDP," Working Papers 119, Oesterreichische Nationalbank (Austrian Central Bank).
    25. Antonello D'Agostino & Kieran McQuinn & Derry O’Brien, 2012. "Nowcasting Irish GDP," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2012(2), pages 21-31.
    26. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    27. Massimiliano Marcellino & Christian Schumacher, 2010. "Factor MIDAS for Nowcasting and Forecasting with Ragged‐Edge Data: A Model Comparison for German GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(4), pages 518-550, August.
    28. David C. Wheelock & Mark E. Wohar, 2009. "Can the term spread predict output growth and recessions? a survey of the literature," Review, Federal Reserve Bank of St. Louis, vol. 91(Sep), pages 419-440.
    29. Boivin, Jean & Ng, Serena, 2006. "Are more data always better for factor analysis?," Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
    30. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    31. Ang, Andrew & Piazzesi, Monika & Wei, Min, 2006. "What does the yield curve tell us about GDP growth?," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 359-403.
    32. Massimiliano Marcellino & Mario Porqueddu & Fabrizio Venditti, 2016. "Short-Term GDP Forecasting With a Mixed-Frequency Dynamic Factor Model With Stochastic Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 118-127, January.
    33. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
    34. Diebold, Francis X & Rudebusch, Glenn D, 1996. "Measuring Business Cycles: A Modern Perspective," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 67-77, February.
    35. David N. DeJong & Roman Liesenfeld & Jean-François Richard, 2005. "A Nonlinear Forecasting Model of GDP Growth," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 697-708, November.
    36. Matteo Luciani & Lorenzo Ricci, 2014. "Nowcasting Norway," International Journal of Central Banking, International Journal of Central Banking, vol. 10(4), pages 215-248, December.
    37. Bai, Jushan & Ng, Serena, 2008. "Forecasting economic time series using targeted predictors," Journal of Econometrics, Elsevier, vol. 146(2), pages 304-317, October.
    38. Heinrich, Markus & Carstensen, Kai & Reif, Magnus & Wolters, Maik, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168206, Verein für Socialpolitik / German Economic Association.
    39. William A. Barnett & Marcelle Chauvet & Danilo Leiva-Leon, 2014. "Real-Time Nowcasting of Nominal GDP Under Structural Breaks," Staff Working Papers 14-39, Bank of Canada.
    40. Alain Galli & Christian Hepenstrick & Rolf Scheufele, 2019. "Mixed-Frequency Models for Tracking Short-Term Economic Developments in Switzerland," International Journal of Central Banking, International Journal of Central Banking, vol. 15(2), pages 151-178, June.
    41. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    42. G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.
    43. Maximo Camacho & Agustin Garcia‐Serrador, 2014. "The Euro‐Sting Revisited: The Usefulness of Financial Indicators to Obtain Euro Area GDP Forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(3), pages 186-197, April.
    44. Chernis, Tony & Cheung, Calista & Velasco, Gabriella, 2020. "A three-frequency dynamic factor model for nowcasting Canadian provincial GDP growth," International Journal of Forecasting, Elsevier, vol. 36(3), pages 851-872.
    45. Domenico Giannone & Lucrezia Reichlin & David Small, 2008. "Nowcasting: the real time informational content of macroeconomic data releases," ULB Institutional Repository 2013/6409, ULB -- Universite Libre de Bruxelles.
    46. G. Bruno & L. Crosilla & P. Margani, 2019. "Inspecting the Relationship Between Business Confidence and Industrial Production: Evidence on Italian Survey Data," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 15(1), pages 1-24, April.
    47. Wolfgang Nierhaus & Klaus Abberger, 2015. "ifo Konjunkturampel revisited," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 68(05), pages 27-32, March.
    48. Maximo Camacho & Gabriel Perez Quiros, 2011. "Spain‐Sting: Spain Short‐Term Indicator Of Growth," Manchester School, University of Manchester, vol. 79(s1), pages 594-616, June.
    49. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    50. Domenico Giannone & Lucrezia Reichlin & David H. Small, 2005. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Finance and Economics Discussion Series 2005-42, Board of Governors of the Federal Reserve System (U.S.).
    51. Christian Glocker, 2012. "Unemployment compensation and aggregate fluctuations," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 59(1), pages 21-39, March.
    52. Chauvet, Marcelle, 1998. "An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 969-996, November.
    53. Camacho, Maximo & Dal Bianco, Marcos & Martinez-Martin, Jaime, 2015. "Toward a more reliable picture of the economic activity: An application to Argentina," Economics Letters, Elsevier, vol. 132(C), pages 129-132.
    54. repec:ulb:ulbeco:2013/13388 is not listed on IDEAS
    55. Barnett, William A. & Chauvet, Marcelle & Leiva-Leon, Danilo, 2014. "Real-Time Nowcasting Nominal GDP Under Structural Break," MPRA Paper 53699, University Library of Munich, Germany.
    56. Ronald Indergand & Stefan Leist, 2014. "A Real-Time Data Set for Switzerland," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 150(IV), pages 331-352, December.
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    Cited by:

    1. Magnus Kvåle Helliesen & Håvard Hungnes & Terje Skjerpen, 2022. "Revisions in the Norwegian National Accounts: accuracy, unbiasedness and efficiency in preliminary figures," Empirical Economics, Springer, vol. 62(3), pages 1079-1121, March.
    2. Glocker, Christian & Kaniovski, Serguei, 2020. "Structural modeling and forecasting using a cluster of dynamic factor models," MPRA Paper 101874, University Library of Munich, Germany.
    3. Erhan Uluceviz & Kamil Yilmaz, 2020. "Real-financial connectedness in the Swiss economy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-20, December.
    4. Christian Glocker & Serguei Kaniovski, 2022. "Macroeconometric forecasting using a cluster of dynamic factor models," Empirical Economics, Springer, vol. 63(1), pages 43-91, July.
    5. Andreas Brunhart, 2019. "Der neue Konjunkturindex „KonSens“: Ein gleichlaufender, vierteljährlicher Sammelindikator für Liechtenstein," Arbeitspapiere 62, Liechtenstein-Institut.
    6. Klaus Friesenbichler & Christian Glocker & Werner Hölzl & Philipp Wegmüller, 2018. "Ein neues Modell für die kurzfristige Prognose der Herstellung von Waren und der Ausrüstungsinvestitionen," WIFO Monatsberichte (monthly reports), WIFO, vol. 91(9), pages 651-661, September.
    7. Marcus Scheiblecker & Christian Glocker & Serguei Kaniovski & Atanas Pekanov, 2018. "Der Beitrag der Finanzmarktinterventionen des Bundes über die HETA Abwicklungsgesellschaft zur Stabilisierung des österreichischen Finanzmarktes," WIFO Studies, WIFO, number 60979.
    8. Wegmüller, Philipp & Glocker, Christian & Guggia, Valentino, 2023. "Weekly economic activity: Measurement and informational content," International Journal of Forecasting, Elsevier, vol. 39(1), pages 228-243.

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    More about this item

    Keywords

    Dynamic Factor Model; Markov-Switching KP_Berichte_Analysen; Nowcasting; Real-Time Data;
    All these keywords.

    JEL classification:

    • 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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