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Citations for "Measuring Predictability: Theory and Macroeconomic Applications"

by Francis X. Diebold & Lutz Kilian

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  1. Carlos Capistrán & Gabriel López-Moctezuma, 2010. "Forecast Revisions of Mexican Inflation and GDP Growth," Working Papers 2010-11, Banco de México.
  2. 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.
  3. Hendry, David F & Hubrich, Kirstin, 2006. "Forecasting Economic Aggregates by Disaggregates," CEPR Discussion Papers 5485, C.E.P.R. Discussion Papers.
  4. Dovern, Jonas, 2006. "Predicting GDP components : do leading indicators increase predictability?," Kiel Advanced Studies Working Papers 436, Kiel Institute for the World Economy (IfW).
  5. Dufour, Jean-Marie & Taamouti, Abderrahim, 2010. "Short and long run causality measures: Theory and inference," Journal of Econometrics, Elsevier, vol. 154(1), pages 42-58, January.
  6. Lucey, Brian M & Zhao, Shelly, 2008. "Halloween or January? Yet another puzzle," International Review of Financial Analysis, Elsevier, vol. 17(5), pages 1055-1069, December.
  7. Monica Jain, 2013. "Perceived Inflation Persistence," Staff Working Papers 13-43, Bank of Canada.
  8. Kirstin Hubrich & David F. Hendry, 2005. "Forecasting Aggregates by Disaggregates," Computing in Economics and Finance 2005 270, Society for Computational Economics.
  9. Osmani Teixeira de Carvalho Guillén & João Victor Issler & George Athanasopoulos, 2006. "Forecasting Accuracy and Estimation Uncertainty using VAR Models with Short- and Long-Term Economic Restrictions: A Monte-Carlo Study," IBMEC RJ Economics Discussion Papers 2006-01, Economics Research Group, IBMEC Business School - Rio de Janeiro.
  10. S. Boragan Aruoba & Francis X. Diebold & Jeremy J. Nalewaik & Frank Schorfheide & Dongho Song, 2013. "Improving GDP measurement: a measurement-error perspective," Working Papers 13-16, Federal Reserve Bank of Philadelphia.
  11. Helmut Hofer & Torsten Schmidt & Klaus Weyerstrass, 2010. "Practice and prospects of medium-term economic forecasting," NRN working papers 2010-12, The Austrian Center for Labor Economics and the Analysis of the Welfare State, Johannes Kepler University Linz, Austria.
  12. John W. Galbraith, 1999. "Content Horizons For Forecasts Of Economic Time Series," Departmental Working Papers 1999-01, McGill University, Department of Economics.
  13. repec:zbw:rwirep:0177 is not listed on IDEAS
  14. Tommaso, Proietti & Helmut, Luetkepohl, 2011. "Does the Box-Cox transformation help in forecasting macroeconomic time series?," MPRA Paper 32294, University Library of Munich, Germany.
  15. Nicoletti-Altimari, Sergio, 2001. "Does money lead inflation in the euro area?," Working Paper Series 0063, European Central Bank.
  16. Timothy Cogley & Giorgio E. Primiceri & Thomas J. Sargent, 2010. "Inflation-Gap Persistence in the US," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(1), pages 43-69, January.
  17. Luati, Alessandra & Proietti, Tommaso & Reale, Marco, 2011. "The Variance Profile," MPRA Paper 30378, University Library of Munich, Germany.
  18. Potì, Valerio & Siddique, Akhtar, 2013. "What drives currency predictability?," Journal of International Money and Finance, Elsevier, vol. 36(C), pages 86-106.
  19. John G. Galbraith & Greg Tkacz, 2006. "How Far Can We Forecast? Forecast Content Horizons For Some Important Macroeconomic Time Series," Departmental Working Papers 2006-13, McGill University, Department of Economics.
  20. Capistrán, Carlos & López-Moctezuma, Gabriel, 2014. "Forecast revisions of Mexican inflation and GDP growth," International Journal of Forecasting, Elsevier, vol. 30(2), pages 177-191.
  21. Rudebusch, Glenn D., 2002. "Term structure evidence on interest rate smoothing and monetary policy inertia," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1161-1187, September.
  22. Isiklar, Gultekin & Lahiri, Kajal, 2007. "How far ahead can we forecast? Evidence from cross-country surveys," International Journal of Forecasting, Elsevier, vol. 23(2), pages 167-187.
  23. John W. Galbraith & Greg Tkacz, 2007. "Forecast content and content horizons for some important macroeconomic time series," Canadian Journal of Economics, Canadian Economics Association, vol. 40(3), pages 935-953, August.
  24. Torsten Schmidt & Helmut Hofer & Klaus Weyerstrass, 2010. "Practice and Prospects of Medium-term Economic Forecasting," Ruhr Economic Papers 0177, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
  25. Lahiri, Kajal & Sheng, Xuguang, 2010. "Learning and heterogeneity in GDP and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 26(2), pages 265-292, April.
  26. Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.
  27. Francis X. Diebold, 1997. "The Past, Present, and Future of Macroeconomic Forecasting," NBER Working Papers 6290, National Bureau of Economic Research, Inc.
  28. Vardhan, Harsh & Sinha, Pankaj, 2015. "Influence of Macroeconomic Variable on Indian Stock Movement: Cointegration Approach," MPRA Paper 64369, University Library of Munich, Germany, revised 10 May 2015.
  29. Oller, Lars-Erik & Teterukovsky, Alex, 2007. "Quantifying the quality of macroeconomic variables," International Journal of Forecasting, Elsevier, vol. 23(2), pages 205-217.
  30. Fanelli, Luca & Paruolo, Paolo, 2010. "Speed of adjustment in cointegrated systems," Journal of Econometrics, Elsevier, vol. 158(1), pages 130-141, September.
  31. Rosa, Carlo & Verga, Giovanni, 2007. "On the consistency and effectiveness of central bank communication: Evidence from the ECB," European Journal of Political Economy, Elsevier, vol. 23(1), pages 146-175, March.
  32. Yoshua Bengio & François Gingras & Claude Nadeau, 2002. "On Out-of-Sample Statistics for Time-Series," CIRANO Working Papers 2002s-51, CIRANO.
  33. Chen, Qiwei & Costantini, Mauro & Deschamps, Bruno, 2016. "How accurate are professional forecasts in Asia? Evidence from ten countries," International Journal of Forecasting, Elsevier, vol. 32(1), pages 154-167.
  34. Kilian, L. & Bergean, I., 1999. "Data-Driven Nonparametric Spectral Density Estimators for Economic Time Series: A Monte Carlo Study," Papers 99-04, Michigan - Center for Research on Economic & Social Theory.
  35. António Brandão Moniz, 2008. "Assessing scenarios on the future of work," Enterprise and Work Innovation Studies, Universidade Nova de Lisboa, IET/CICS.NOVA-Interdisciplinary Centre on Social Sciences, Faculty of Science and Technology, vol. 4(4), pages 91-106, November.
  36. Jonas Dovern, 2006. "Predicting GDP Components. Do Leading Indicators Increase Predictability?," Kiel Advanced Studies Working Papers 436, Kiel Institute for the World Economy.
  37. Jeremy Berkowitz & Ionel Biegean & Lutz Kilian, 1999. "On the finite-sample accuracy of nonparametric resampling algorithms for economic time series," Finance and Economics Discussion Series 1999-04, Board of Governors of the Federal Reserve System (U.S.).
  38. David McMillan & Isabel Ruiz & Alan Speight, 2010. "Correlations and spillovers among three euro rates: evidence using realised variance," The European Journal of Finance, Taylor & Francis Journals, vol. 16(8), pages 753-767.
  39. Marc Brisson & Bryan Campbell & John Galbraith, 2001. "Forecasting Some Low-Predictability Time Series Using Diffusion Indices," CIRANO Working Papers 2001s-46, CIRANO.
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