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Now-casting and the real-time data flow

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  • Banbura, Marta
  • Giannone, Domenico
  • Modugno, Michele
  • Reichlin, Lucrezia

Abstract

The term now-casting is a contraction for now and forecasting and has been used for a long-time in meteorology and recently also in economics In this paper we survey recent developments on economic now-casting with special focus on those models that formalize key features of how market participants and policy makers read macroeconomic data releases in real time, which involves: monitoring many data, forming expectations about them and revising the assessment on the state of the economy whenever realizations diverge sizeably from those expectations.

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Bibliographic Info

Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 9112.

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Date of creation: Sep 2012
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Handle: RePEc:cpr:ceprdp:9112

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Related research

Keywords: Dynamic factor model; High-Dimensional Data; Macroeconomic forecasting; Macroeconomic News; Mixed-Frequency; Real-Time Data; State-Space Models;

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References

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  1. 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.
  2. Martha Banbura & Domenico Giannone & Lucrezia Reichlin, 2008. "Large Bayesian VARs," Working Papers ECARES 2008_033, ULB -- Universite Libre de Bruxelles.
  3. Knut Are Aastveit & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud, 2011. "Nowcasting GDP in real-time: A density combination approach," Working Paper 2011/11, Norges Bank.
  4. Altissimo, Filippo & Bassanetti, Antonio & Cristadoro, Riccardo & Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia & Veronese, Giovanni, 2001. "EuroCOIN: A Real Time Coincident Indicator of the Euro Area Business Cycle," CEPR Discussion Papers 3108, C.E.P.R. Discussion Papers.
  5. Banbura, Marta & Rünstler, Gerhard, 2007. "A look into the factor model black box: publication lags and the role of hard and soft data in forecasting GDP," Working Paper Series 0751, European Central Bank.
  6. Angelini, Elena & Bańbura, Marta & Rünstler, Gerhard, 2008. "Estimating and forecasting the euro area monthly national accounts from a dynamic factor model," Working Paper Series 0953, European Central Bank.
  7. S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2007. "Real-time measurement of business conditions," International Finance Discussion Papers 901, Board of Governors of the Federal Reserve System (U.S.).
  8. Katerina Arnostova & David Havrlant & Lubos Ruzicka & Peter Toth, 2010. "Short-Term Forecasting of Czech Quarterly GDP Using Monthly Indicators," Working Papers 2010/12, Czech National Bank, Research Department.
  9. Bańbura, Marta & Modugno, Michele, 2010. "Maximum likelihood estimation of factor models on data sets with arbitrary pattern of missing data," Working Paper Series 1189, European Central Bank.
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Cited by:
  1. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Economics Working Papers ECO2013/02, European University Institute.
  2. Alessandro Beber & Michael W. Brandt & Maurizio Luisi, 2013. "Distilling the Macroeconomic News Flow," NBER Working Papers 19650, National Bureau of Economic Research, Inc.
  3. William Barnett & Marcelle Chauvetz & Danilo Leiva-Leonx, . "Real-Time Nowcasting Nominal GDP Under Structural Break," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201313, University of Kansas, Department of Economics.
  4. Keeney, Mary & Kennedy, Bernard & Liebermann, Joelle, 2012. "The value of hard and soft data for short-term forecasting of GDP," Economic Letters 11/EL/12, Central Bank of Ireland.
  5. Marek Rusnak, 2013. "Nowcasting Czech GDP in Real Time," Working Papers 2013/06, Czech National Bank, Research Department.
  6. Frédérique Bec & Matteo Mogliani, 2013. "Nowcasting French GDP in Real-Time from Survey Opinions : Information or Forecast Combinations ?," Working Papers 2013-21, Centre de Recherche en Economie et Statistique.
  7. Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2013. "Real-Time Nowcasting with a Bayesian Mixed Frequency Model with Stochastic Volatility," CEPR Discussion Papers 9312, C.E.P.R. Discussion Papers.
  8. Bell, Venetia & Co, Lai Wah & Stone, Sophie & Wallis, gavin`, 2014. "Nowcasting UK GDP growth," Bank of England Quarterly Bulletin, Bank of England, vol. 54(1), pages 58-68.
  9. Marczak, Martyna & Gómez, Victor, 2013. "Monthly US business cycle indicators: A new multivariate approach based on a band-pass filter," FZID Discussion Papers 64-2013, University of Hohenheim, Center for Research on Innovation and Services (FZID).

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