IDEAS home Printed from https://ideas.repec.org/r/eee/intfor/v19y2003i2p177-197.html

Exploiting information in vintages of time-series data

Citations

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


Cited by:

  1. Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2015. "Robust approaches to forecasting," International Journal of Forecasting, Elsevier, vol. 31(1), pages 99-112.
  2. Easaw Joshy & Golinelli Roberto, 2010. "Households Forming Inflation Expectations: Active and Passive Absorption Rates," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-32, November.
  3. Carlo Altavilla & Matteo Ciccarelli, 2011. "Monetary Policy Analysis in Real-Time. Vintage combination from a real-time dataset," CSEF Working Papers 274, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
  4. Hecq, Alain & Jacobs, Jan P.A.M. & Stamatogiannis, Michalis P., 2019. "Testing for news and noise in non-stationary time series subject to multiple historical revisions," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 396-407.
  5. Clements, Michael P. & Galvao, Ana Beatriz, "undated". "Macroeconomic Forecasting with Mixed Frequency Data: Forecasting US output growth and inflation," Economic Research Papers 269743, University of Warwick - Department of Economics.
  6. Carriero, Andrea & Clements, Michael P. & Galvão, Ana Beatriz, 2015. "Forecasting with Bayesian multivariate vintage-based VARs," International Journal of Forecasting, Elsevier, vol. 31(3), pages 757-768.
  7. Parigi, Giuseppe & Golinelli, Roberto, 2005. "Short-Run Italian GDP Forecasting and Real-Time Data," CEPR Discussion Papers 5302, C.E.P.R. Discussion Papers.
  8. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
  9. Clements, Michael P. & Beatriz Galvao, Ana, "undated". "Real-time Forecasting of Inflation and Output Growth in the Presence of Data Revisions," Economic Research Papers 270771, University of Warwick - Department of Economics.
  10. 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.
  11. Kosei Fukuda, 2007. "Forecasting real-time data allowing for data revisions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(6), pages 429-444.
  12. Jennifer Castle & David Hendry, 2012. "Forecasting by factors, by variables, or both?," Economics Series Working Papers 600, University of Oxford, Department of Economics.
  13. Clements, Michael P. & Galvão, Ana Beatriz, 2013. "Forecasting with vector autoregressive models of data vintages: US output growth and inflation," International Journal of Forecasting, Elsevier, vol. 29(4), pages 698-714.
  14. Michael P Clements & Ana Beatriz Galvao, 2017. "Data Revisions and Real-time Probabilistic Forecasting of Macroeconomic Variables," ICMA Centre Discussion Papers in Finance icma-dp2017-01, Henley Business School, University of Reading.
  15. Ciccarelli, Matteo & Altavilla, Carlo, 2007. "Information combination and forecast (st)ability evidence from vintages of time-series data," Working Paper Series 846, European Central Bank.
  16. Emilia Tomczyk, 2013. "End of sample vs. real time data: perspectives for analysis of expectations," Working Papers 68, Department of Applied Econometrics, Warsaw School of Economics.
  17. Bouwman, Kees E. & Jacobs, Jan P.A.M., 2011. "Forecasting with real-time macroeconomic data: The ragged-edge problem and revisions," Journal of Macroeconomics, Elsevier, vol. 33(4), pages 784-792.
  18. Hwa-Taek Lee & Gawon Yoon, 2013. "Does purchasing power parity hold sometimes? Regime switching in real exchange rates," Applied Economics, Taylor & Francis Journals, vol. 45(16), pages 2279-2294, June.
  19. Michael P. Clements, 2017. "Assessing Macro Uncertainty in Real-Time When Data Are Subject To Revision," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 420-433, July.
  20. Jan P.A.M. Jacobs & Samad Sarferaz & Simon van Norden & Jan-Egbert Sturm, 2013. "Modeling Multivariate Data Revisions," CIRANO Working Papers 2013s-44, CIRANO.
  21. Clements, Michael P., "undated". "Internal consistency of survey respondentsíforecasts: Evidence based on the Survey of Professional Forecasters," Economic Research Papers 269742, University of Warwick - Department of Economics.
  22. Thomas A. Knetsch & Hans‐Eggert Reimers, 2009. "Dealing with Benchmark Revisions in Real‐Time Data: The Case of German Production and Orders Statistics," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(2), pages 209-235, April.
  23. Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2013. "Forecasting by factors, by variables, by both or neither?," Journal of Econometrics, Elsevier, vol. 177(2), pages 305-319.
  24. Kevin Lee & Nilss Olekalns & Kalvinder Shields & Zheng Wang, 2012. "Australian Real-Time Database: An Overview and an Illustration of its Use in Business Cycle Analysis," The Economic Record, The Economic Society of Australia, vol. 88(283), pages 495-516, December.
  25. J. Easaw J. & R. Golinelli, 2009. "Households Forming Inflation Expectations: Who Are the 'Active' and 'Passive' Learners?," Working Papers 675, Dipartimento Scienze Economiche, Universita' di Bologna.
  26. David Hendry & Michael P. Clements, 2010. "Forecasting from Mis-specified Models in the Presence of Unanticipated Location Shifts," Economics Series Working Papers 484, University of Oxford, Department of Economics.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.