[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/19650.html
   My bibliography  Save this paper

Distilling the Macroeconomic News Flow

Author

Listed:
  • Alessandro Beber
  • Michael W. Brandt
  • Maurizio Luisi
Abstract
We propose a simple cross-sectional technique to extract daily factors from economic news released at different times and frequencies. Our approach can effectively handle the large number of different announcements that are relevant for tracking current economic conditions. We apply the technique to extract real-time measures of inflation, output, employment, and macroeconomic sentiment, as well as corresponding measures of disagreement among economists about these indices. We find that our procedure provides more timely and accurate forecasts of future changes in economic conditions than other real-time forecasting approaches.

Suggested Citation

  • Alessandro Beber & Michael W. Brandt & Maurizio Luisi, 2013. "Distilling the Macroeconomic News Flow," NBER Working Papers 19650, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:19650
    Note: AP
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w19650.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2003. "The Use and Abuse of Real-Time Data in Economic Forecasting," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 618-628, August.
    2. 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.
    3. Martin D. D. Evans, 2005. "Where Are We Now? Real-Time Estimates of the Macroeconomy," International Journal of Central Banking, International Journal of Central Banking, vol. 1(2), September.
    4. Bańbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2013. "Now-Casting and the Real-Time Data Flow," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 195-237, Elsevier.
    5. Alessandro Beber & Michael W. Brandt & Kenneth A. Kavajecz, 2011. "What Does Equity Sector Orderflow Tell Us About the Economy?," The Review of Financial Studies, Society for Financial Studies, vol. 24(11), pages 3688-3730.
    6. Yacine Aït-Sahalia, 2005. "How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise," The Review of Financial Studies, Society for Financial Studies, vol. 18(2), pages 351-416.
    7. repec:bla:jfinan:v:44:y:1989:i:5:p:1115-53 is not listed on IDEAS
    8. Reichlin, Lucrezia & Giannone, Domenico & Small, David, 2005. "Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases," CEPR Discussion Papers 5178, C.E.P.R. Discussion Papers.
    9. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Clara Vega, 2003. "Micro Effects of Macro Announcements: Real-Time Price Discovery in Foreign Exchange," American Economic Review, American Economic Association, vol. 93(1), pages 38-62, March.
    10. Liebermann, Joelle, 2010. "Real-time nowcasting of GDP: Factor model versus professional forecasters," MPRA Paper 28819, University Library of Munich, Germany.
    11. Aruoba, S. BoraÄŸan & Diebold, Francis X. & Scotti, Chiara, 2009. "Real-Time Measurement of Business Conditions," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 417-427.
    12. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    13. Eric Ghysels & Casidhe Horan & Emanuel Moench, 2018. "Forecasting through the Rearview Mirror: Data Revisions and Bond Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 31(2), pages 678-714.
    14. Stambaugh, Robert F., 1997. "Analyzing investments whose histories differ in length," Journal of Financial Economics, Elsevier, vol. 45(3), pages 285-331, September.
    15. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc.
    16. Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
    17. Joelle Liebermann, 2014. "Real-Time Nowcasting of GDP: A Factor Model vs. Professional Forecasters," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(6), pages 783-811, December.
    18. 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.
    19. Anon, 2002. "The Economy of Influence," Environment and Planning A, , vol. 34(8), pages 1331-1332, August.
    20. Mark J. Flannery & Aris A. Protopapadakis, 2002. "Macroeconomic Factors Do Influence Aggregate Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 15(3), pages 751-782.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Min Jeong Kim & Dohyoung Kwon, 2023. "Dynamic asset allocation strategy: an economic regime approach," Journal of Asset Management, Palgrave Macmillan, vol. 24(2), pages 136-147, March.
    2. Jean-Charles Bricongne & Baptiste Meunier & Raquel Caldeira, 2024. "Should Central Banks Care About Text Mining? A Literature Review," Working papers 950, Banque de France.
    3. Beber, Alessandro & Brandt, Michael & Luisi, Maurizio, 2013. "Eurozone Sovereign Yield Spreads and Diverging Economic Fundamentals," CEPR Discussion Papers 9538, C.E.P.R. Discussion Papers.
    4. Alessi, Lucia & Balduzzi, Pierluigi & Savona, Roberto, 2019. "Anatomy of a Sovereign Debt Crisis: CDS Spreads and Real-Time Macroeconomic Data," JRC Working Papers in Economics and Finance 2019-03, Joint Research Centre, European Commission.
    5. Guceri, Irem & Albinowski, Maciej, 2021. "Investment responses to tax policy under uncertainty," Journal of Financial Economics, Elsevier, vol. 141(3), pages 1147-1170.
    6. Beber, Alessandro & Brandt, Michael & Luisi, Maurizio, 2013. "Economic Cycles and Expected Stock Returns," CEPR Discussion Papers 9528, C.E.P.R. Discussion Papers.
    7. Garcí­a, Juan Angel & Werner, Sebastian E. V., 2016. "Bond risk premia, macroeconomic factors and financial crisis in the euro area," Working Paper Series 1938, European Central Bank.
    8. Zheng, Hannan & Schwenkler, Gustavo, 2020. "The network of firms implied by the news," ESRB Working Paper Series 108, European Systemic Risk Board.
    9. Dahlquist, Magnus & Hasseltoft, Henrik, 2020. "Economic momentum and currency returns," Journal of Financial Economics, Elsevier, vol. 136(1), pages 152-167.
    10. van Binsbergen, Jules H. & Koijen, Ralph S.J., 2017. "The term structure of returns: Facts and theory," Journal of Financial Economics, Elsevier, vol. 124(1), pages 1-21.
    11. Audrino, Francesco & Tetereva, Anastasija, 2019. "Sentiment spillover effects for US and European companies," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 542-567.
    12. Félix, Luiz & Kräussl, Roman & Stork, Philip, 2018. "Predictable biases in macroeconomic forecasts and their impact across asset classes," CFS Working Paper Series 596, Center for Financial Studies (CFS).
    13. Akhtar, Shumi & Akhtar, Farida & Jahromi, Maria & John, Kose, 2017. "Impact of interest rate surprises on Islamic and conventional stocks and bonds," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 218-231.
    14. Luiz Félix & Roman Kräussl & Philip Stork, 2021. "Strategic bias and popularity effect in the prediction of economic surprises," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1095-1117, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Beber, Alessandro & Brandt, Michael & Luisi, Maurizio, 2013. "Economic Cycles and Expected Stock Returns," CEPR Discussion Papers 9528, C.E.P.R. Discussion Papers.
    2. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Working Paper 2013/06, Norges Bank.
    3. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    4. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    5. Thomas Gilbert & Chiara Scotti & Georg Strasser & Clara Vega, 2015. "Is the Intrinsic Value of Macroeconomic News Announcements Related to their Asset Price Impact?," Finance and Economics Discussion Series 2015-46, Board of Governors of the Federal Reserve System (U.S.).
    6. William A. Barnett & Marcelle Chauvetz & Danilo Leiva-Leonx, 2014. "Real-Time Nowcasting Nominal GDP Under Structural Break," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201313, University of Kansas, Department of Economics, revised Feb 2014.
    7. 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.
    8. 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.
    9. Bragoli, Daniela & Modugno, Michele, 2017. "A now-casting model for Canada: Do U.S. variables matter?," International Journal of Forecasting, Elsevier, vol. 33(4), pages 786-800.
    10. William A. Barnett & Biyan Tang, 2016. "Chinese Divisia Monetary Index and GDP Nowcasting," Open Economies Review, Springer, vol. 27(5), pages 825-849, November.
    11. Juan Antolin-Diaz & Thomas Drechsel & Ivan Petrella, 2017. "Tracking the Slowdown in Long-Run GDP Growth," The Review of Economics and Statistics, MIT Press, vol. 99(2), pages 343-356, May.
    12. Bańbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2013. "Now-Casting and the Real-Time Data Flow," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 195-237, Elsevier.
    13. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
    14. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.
    15. Barnett, William A. & Chauvet, Marcelle & Leiva-Leon, Danilo, 2016. "Real-time nowcasting of nominal GDP with structural breaks," Journal of Econometrics, Elsevier, vol. 191(2), pages 312-324.
    16. Aastveit, Knut Are & Trovik, Tørres, 2014. "Estimating the output gap in real time: A factor model approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 180-193.
    17. Raïsa Basselier & David Antonio Liedo & Geert Langenus, 2018. "Nowcasting Real Economic Activity in the Euro Area: Assessing the Impact of Qualitative Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 1-46, April.
    18. Martha Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Nowcasting," Working Papers ECARES ECARES 2010-021, ULB -- Universite Libre de Bruxelles.
    19. Juan Tenorio & Wilder Perez, 2024. "Monthly GDP nowcasting with Machine Learning and Unstructured Data," Papers 2402.04165, arXiv.org.
    20. Scotti, Chiara, 2016. "Surprise and uncertainty indexes: Real-time aggregation of real-activity macro-surprises," Journal of Monetary Economics, Elsevier, vol. 82(C), pages 1-19.

    More about this item

    JEL classification:

    • E0 - Macroeconomics and Monetary Economics - - General
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G0 - Financial Economics - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:19650. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.