IDEAS home Printed from https://ideas.repec.org/p/hep/macppr/201406.html
   My bibliography  Save this paper

Real-time Macroeconomic Data and Uncertainty

Author

Listed:
  • Katharina Glass

    (Universität Hamburg (University of Hamburg))

  • Ulrich Fritsche

    (Universität Hamburg (University of Hamburg))

Abstract

Most macroeconomic data is continuously revised as additional information becomes avail- able. We suggest that revisions of data is an increasingly important source of uncertainty about the state of the economy and offer an alternative channel of uncertainty - data uncer- tainty. This paper adds on the uncertainty literature and focuses on data uncertainty, which originates in the revision structure of data. We find that apart from the general and eco- nomic policy uncertainty, the data uncertainty has been rising throughout the past decade in the US and Euro area. To the best of our knowledge, this is the first study of Euro area data uncertainty. Our analysis shows that there is a positive lagged effect of economic policy uncertainty on data uncertainty for both regions. Our finding corresponds to the recent lit- erature on increased macroeconomic and economic policy uncertainty during and after the "Great Recession”.

Suggested Citation

  • Katharina Glass & Ulrich Fritsche, 2015. "Real-time Macroeconomic Data and Uncertainty," Macroeconomics and Finance Series 201406, University of Hamburg, Department of Socioeconomics.
  • Handle: RePEc:hep:macppr:201406
    as

    Download full text from publisher

    File URL: https://www.wiso.uni-hamburg.de/repec/hepdoc/macppr_6_2014R.pdf
    File Function: First version, 2015-07
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zarnowitz, Victor, 1985. "Recent Work on Business Cycles in Historical Perspective: A Review of Theories and Evidence," Journal of Economic Literature, American Economic Association, vol. 23(2), pages 523-580, June.
    2. Jacob A. Mincer & Victor Zarnowitz, 1969. "The Evaluation of Economic Forecasts," NBER Chapters, in: Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance, pages 3-46, National Bureau of Economic Research, Inc.
    3. Marcellino, Massimiliano & Musso, Alberto, 2011. "The reliability of real-time estimates of the euro area output gap," Economic Modelling, Elsevier, vol. 28(4), pages 1842-1856, July.
    4. Nicholas Bloom & Max Floetotto & Nir Jaimovich & Itay Saporta†Eksten & Stephen J. Terry, 2018. "Really Uncertain Business Cycles," Econometrica, Econometric Society, vol. 86(3), pages 1031-1065, May.
    5. Baker, Scott R. & Bloom, Nicholas, 2013. "Does uncertainty reduce growth? Using disasters as natural experiments," LSE Research Online Documents on Economics 121906, London School of Economics and Political Science, LSE Library.
    6. Konstantin A. Kholodilin & Boriss Siliverstovs, 2009. "Do Forecasters Inform or Reassure? Evaluation of the German Real-Time Data," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 55(4), pages 269-294.
    7. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    8. James H. Stock & Mark W. Watson, 2003. "Has the Business Cycle Changed and Why?," NBER Chapters, in: NBER Macroeconomics Annual 2002, Volume 17, pages 159-230, National Bureau of Economic Research, Inc.
    9. Fred Joutz & Michael P. Clements & Herman O. Stekler, 2007. "An evaluation of the forecasts of the federal reserve: a pooled approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 121-136.
    10. Swanson, Norman R. & van Dijk, Dick, 2006. "Are Statistical Reporting Agencies Getting It Right? Data Rationality and Business Cycle Asymmetry," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 24-42, January.
    11. Serena Ng & Jonathan H. Wright, 2013. "Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1120-1154, December.
    12. Croushore, Dean, 2006. "Forecasting with Real-Time Macroeconomic Data," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 17, pages 961-982, Elsevier.
    13. Clements, Michael P., 2012. "Subjective and Ex Post Forecast Uncertainty: US Inflation and Output Growth," Economic Research Papers 270629, University of Warwick - Department of Economics.
    14. Croushore Dean, 2010. "An Evaluation of Inflation Forecasts from Surveys Using Real-Time Data," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-32, May.
    15. Nordhaus, William D, 1987. "Forecasting Efficiency: Concepts and Applications," The Review of Economics and Statistics, MIT Press, vol. 69(4), pages 667-674, November.
    16. Clements, Michael P., 2012. "Do professional forecasters pay attention to data releases?," International Journal of Forecasting, Elsevier, vol. 28(2), pages 297-308.
    17. Konstantin A. Kholodilin & Boriss Siliverstovs, 2009. "Do forecasters inform or reassure?," KOF Working papers 09-215, KOF Swiss Economic Institute, ETH Zurich.
    18. Messina, Jeffrey D. & Sinclair, Tara M. & Stekler, Herman, 2015. "What can we learn from revisions to the Greenbook forecasts?," Journal of Macroeconomics, Elsevier, vol. 45(C), pages 54-62.
    19. Gebhard Kirchgässner & Jürgen Wolters & Uwe Hassler, 2013. "Introduction to Modern Time Series Analysis," Springer Texts in Business and Economics, Springer, edition 2, number 978-3-642-33436-8, August.
    20. Andrea Terzi, 2010. "Keynes's uncertainty is not about white or black swans," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 32(4), pages 559-566, July.
    21. Joshua Abel & Robert Rich & Joseph Song & Joseph Tracy, 2016. "The Measurement and Behavior of Uncertainty: Evidence from the ECB Survey of Professional Forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 533-550, April.
    22. 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.
    23. Victor Zarnowitz, 1984. "Recent Work on Business Cycles in Historical Perspective: Review of Theories and Evidence," NBER Working Papers 1503, National Bureau of Economic Research, Inc.
    24. McNees, Stephen K., 1989. "Forecasts and actuals: The trade-off between timeliness and accuracy," International Journal of Forecasting, Elsevier, vol. 5(3), pages 409-416.
    25. Paul Davidson, 2010. "Black swans and Knight's epistemological uncertainty: are these concepts also underlying behavioral and post-Walrasian theory?," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 32(4), pages 567-570, July.
    26. Robert Rich & Joseph Tracy, 2010. "The Relationships among Expected Inflation, Disagreement, and Uncertainty: Evidence from Matched Point and Density Forecasts," The Review of Economics and Statistics, MIT Press, vol. 92(1), pages 200-207, February.
    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. Katharina Glass, 2018. "Predictability of Euro Area Revisions," Macroeconomics and Finance Series 201801, University of Hamburg, Department of Socioeconomics.
    2. Baetje, Fabian & Friedrici, Karola, 2016. "Does cross-sectional forecast dispersion proxy for macroeconomic uncertainty? New empirical evidence," Economics Letters, Elsevier, vol. 143(C), pages 38-43.
    3. Christian Glocker & Werner Hölzl, 2019. "Assessing the Economic Content of Direct and Indirect Business Uncertainty Measures," WIFO Working Papers 576, WIFO.
    4. de Mendonça, Helder Ferreira & Baca, Adriana Cabrera, 2022. "Fiscal opacity and reduction of income inequality through taxation: Effects on economic growth," The Quarterly Review of Economics and Finance, Elsevier, vol. 83(C), pages 69-82.
    5. Joshy Easaw & Christian Grimme, 2021. "The Impact of Aggregate Uncertainty on Firm-Level Uncertainty," CESifo Working Paper Series 8934, CESifo.

    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. Katharina Glass, 2018. "Predictability of Euro Area Revisions," Macroeconomics and Finance Series 201801, University of Hamburg, Department of Socioeconomics.
    2. Andrade, P. & Ghysels, E. & Idier, J., 2012. "Tails of Inflation Forecasts and Tales of Monetary Policy," Working papers 407, Banque de France.
    3. N. Bloom, 2016. "Fluctuations in uncertainty," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 4.
    4. repec:zbw:bofrdp:037 is not listed on IDEAS
    5. Robert Rich & Joseph Tracy, 2021. "A Closer Look at the Behavior of Uncertainty and Disagreement: Micro Evidence from the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(1), pages 233-253, February.
    6. Berge, Travis J. & Chang, Andrew C. & Sinha, Nitish R., 2019. "Evaluating the conditionality of judgmental forecasts," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1627-1635.
    7. Tara M. Sinclair & H.O. Stekler, 2011. "Differences in Early GDP Component Estimates Between Recession and Expansion," Working Papers 2011-05, The George Washington University, Institute for International Economic Policy.
    8. Carlo Altavilla & Matteo Ciccarelli, 2011. "Monetary Policy Analysis in Real-Time. Vintage Combination from a Real-Time Dataset," CESifo Working Paper Series 3372, CESifo.
    9. Sinclair, Tara M. & Stekler, H.O., 2013. "Examining the quality of early GDP component estimates," International Journal of Forecasting, Elsevier, vol. 29(4), pages 736-750.
    10. Ambrocio, Gene, 2017. "The real effects of overconfidence and fundamental uncertainty shocks," Research Discussion Papers 37/2017, Bank of Finland.
    11. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    12. Strunz, Franziska & Gödl, Maximilian, 2023. "An Evaluation of Professional Forecasts for the German Economy," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277707, Verein für Socialpolitik / German Economic Association.
    13. Dovern, Jonas & Weisser, Johannes, 2011. "Accuracy, unbiasedness and efficiency of professional macroeconomic forecasts: An empirical comparison for the G7," International Journal of Forecasting, Elsevier, vol. 27(2), pages 452-465.
    14. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    15. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    16. repec:zbw:bofrdp:2017_037 is not listed on IDEAS
    17. Jacobs, Jan P.A.M. & van Norden, Simon, 2011. "Modeling data revisions: Measurement error and dynamics of "true" values," Journal of Econometrics, Elsevier, vol. 161(2), pages 101-109, April.
    18. Tunc, Ahmet & Kocoglu, Mustafa & Aslan, Alper, 2022. "Time-varying characteristics of the simultaneous interactions between economic uncertainty, international oil prices and GDP: A novel approach for Germany," Resources Policy, Elsevier, vol. 77(C).
    19. Robert W. Rich & Joseph Tracy, 2017. "The behavior of uncertainty and disagreement and their roles in economic prediction: a panel analysis," Staff Reports 808, Federal Reserve Bank of New York.
    20. Jacobs, Jan P.A.M. & van Norden, Simon, 2016. "Why are initial estimates of productivity growth so unreliable?," Journal of Macroeconomics, Elsevier, vol. 47(PB), pages 200-213.
    21. Lixiong Yang, 2020. "State-dependent biases and the quality of China’s preliminary GDP announcements," Empirical Economics, Springer, vol. 59(6), pages 2663-2687, December.
    22. Luca Rossi, 2020. "Indicators of uncertainty: a brief user’s guide," Questioni di Economia e Finanza (Occasional Papers) 564, Bank of Italy, Economic Research and International Relations Area.

    More about this item

    Keywords

    forecasting; information content; uncertainty; revisions; revision errors; entropy; signal-to-noise ratio; integrated signal-to-noise ratio; recession; EPU; VSTOXX; VIX;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

    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:hep:macppr:201406. 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: Ulrich Fritsche (email available below). General contact details of provider: https://edirc.repec.org/data/dwuhhde.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.