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Measuring Predictability: Theory and Macroeconomic Applications

Citations

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Cited by:

  1. 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.
  2. Berkowitz, J. & Birgean, I. & Kilian, L., 1999. "On the Finite-Sample Accuracy of Nonparametric Resampling Algorithms for Economic Time Series," Papers 99-01, Michigan - Center for Research on Economic & Social Theory.
  3. Proietti, Tommaso & Lütkepohl, Helmut, 2013. "Does the Box–Cox transformation help in forecasting macroeconomic time series?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 88-99.
  4. Yang, Dazhi, 2022. "Correlogram, predictability error growth, and bounds of mean square error of solar irradiance forecasts," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
  5. 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.
  6. 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.
  7. John W. Galbraith, 1999. "Content Horizons for Forecasts of Economic Time Series," CIRANO Working Papers 99s-17, CIRANO.
  8. 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.
  9. Jamie L. Cross & Bao H. Nguyen & Trung Duc Tran, 2022. "The role of precautionary and speculative demand in the global market for crude oil," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 882-895, August.
  10. Hofer Helmut & Weyerstraß Klaus & Schmidt Torsten, 2011. "Practice and Prospects of Medium-term Economic Forecasting," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 153-171, February.
  11. Marc Brisson & Bryan Campbell & John W. Galbraith, 2001. "Forecasting Some Low-Predictability Time Series Using Diffusion Indices," CIRANO Working Papers 2001s-46, CIRANO.
  12. Kilian, Lutz & Zhou, Xiaoqing, 2018. "Modeling fluctuations in the global demand for commodities," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 54-78.
  13. Aruoba, S. Borağan & Diebold, Francis X. & Nalewaik, Jeremy & Schorfheide, Frank & Song, Dongho, 2016. "Improving GDP measurement: A measurement-error perspective," Journal of Econometrics, Elsevier, vol. 191(2), pages 384-397.
  14. 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.
  15. 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.
  16. Francis X. Diebold, 1998. "The Past, Present, and Future of Macroeconomic Forecasting," Journal of Economic Perspectives, American Economic Association, vol. 12(2), pages 175-192, Spring.
  17. 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.
  18. Oller, Lars-Erik & Teterukovsky, Alex, 2007. "Quantifying the quality of macroeconomic variables," International Journal of Forecasting, Elsevier, vol. 23(2), pages 205-217.
  19. Sridevi Narayanan & Chee Keong Choong & Lin Sea Lau, 2020. "An investigation on the role of good governance as a mediating factor in the FDI-Growth nexus: An ASEAN Perspective," Economics Bulletin, AccessEcon, vol. 40(4), pages 2769-2779.
  20. Fanelli, Luca & Paruolo, Paolo, 2010. "Speed of adjustment in cointegrated systems," Journal of Econometrics, Elsevier, vol. 158(1), pages 130-141, September.
  21. Konstantin A. Kholodilin & Boriss Siliverstovs, 2009. "Do forecasters inform or reassure?," KOF Working papers 09-215, KOF Swiss Economic Institute, ETH Zurich.
  22. Degenhardt, Thomas & Auer, Benjamin R., 2018. "The “Sell in May” effect: A review and new empirical evidence," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 169-205.
  23. 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.
  24. Yoshua Bengio & François Gingras & Claude Nadeau, 2002. "On Out-of-Sample Statistics for Time-Series," CIRANO Working Papers 2002s-51, CIRANO.
  25. 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.
  26. 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.
  27. Czudaj, Robert L., 2022. "Heterogeneity of beliefs and information rigidity in the crude oil market: Evidence from survey data," European Economic Review, Elsevier, vol. 143(C).
  28. Thomas A. Knetsch, 2007. "Forecasting the price of crude oil via convenience yield predictions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(7), pages 527-549.
  29. Barnett, Alina & Groen, Jan J J & Mumtaz, Haroon, 2010. "Time-varying inflation expectations and economic fluctuations in the United Kingdom: a structural VAR analysis," Bank of England working papers 392, Bank of England.
  30. Potì, Valerio & Siddique, Akhtar, 2013. "What drives currency predictability?," Journal of International Money and Finance, Elsevier, vol. 36(C), pages 86-106.
  31. Clements, Michael P., 2018. "Are macroeconomic density forecasts informative?," International Journal of Forecasting, Elsevier, vol. 34(2), pages 181-198.
  32. Ionel Birgean & Lutz Kilian, 2002. "Data-Driven Nonparametric Spectral Density Estimators For Economic Time Series: A Monte Carlo Study," Econometric Reviews, Taylor & Francis Journals, vol. 21(4), pages 449-476.
  33. Athanasopoulos, George & Issler, João Victor & Guillen, Osmani Teixeira Carvalho, 2005. "Forecasting accuracy and estimation uncertainty using VAR models with short- and long-term economic restrictions: a Monte-Carlo study," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 589, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
  34. Jörg Breitung & Malte Knüppel, 2021. "How far can we forecast? Statistical tests of the predictive content," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(4), pages 369-392, June.
  35. 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.
  36. Zhang, Gang & Yang, Dazhi & Galanis, George & Androulakis, Emmanouil, 2022. "Solar forecasting with hourly updated numerical weather prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
  37. Dovern, Jonas, 2006. "Predicting GDP components: do leading indicators increase predictability?," Kiel Advanced Studies Working Papers 436, Kiel Institute for the World Economy (IfW Kiel).
  38. 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.
  39. Nicoletti-Altimari, Sergio, 2001. "Does money lead inflation in the euro area?," Working Paper Series 0063, European Central Bank.
  40. 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.
  41. Hendry, David & Hubrich, Kirstin, 2006. "Forecasting Economic Aggregates by Disaggregates," CEPR Discussion Papers 5485, C.E.P.R. Discussion Papers.
  42. Monica Jain, 2019. "Perceived Inflation Persistence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(1), pages 110-120, January.
  43. Marc-Oliver Pohle, 2020. "The Murphy Decomposition and the Calibration-Resolution Principle: A New Perspective on Forecast Evaluation," Papers 2005.01835, arXiv.org.
  44. Dovern, Jonas, 2024. "Eliciting expectation uncertainty from private households," International Journal of Forecasting, Elsevier, vol. 40(1), pages 113-123.
  45. Romeo-Catalin CRETU & Irina-Daniela CISMASU & Adrian ANICA-POPA & Petrica STEFAN, 2021. "Education In Digital Era Between Analysis Of Predictability And Consolidation Of Resiliance," Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 15(1), pages 274-289, November.
  46. Ruan, Xinfeng & Zhang, Jin E., 2018. "Risk-neutral moments in the crude oil market," Energy Economics, Elsevier, vol. 72(C), pages 583-600.
  47. Edoardo Otrano & Umberto Triacca, 2007. "Testing for Equal Predictability of Stationary ARMA Processes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(9), pages 1091-1108.
  48. Dovern, Jonas, 2023. "Eliciting expectation uncertainty from private households," Working Papers 38, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
  49. Yang, Dazhi & Wang, Wenting & Gueymard, Christian A. & Hong, Tao & Kleissl, Jan & Huang, Jing & Perez, Marc J. & Perez, Richard & Bright, Jamie M. & Xia, Xiang’ao & van der Meer, Dennis & Peters, Ian , 2022. "A review of solar forecasting, its dependence on atmospheric sciences and implications for grid integration: Towards carbon neutrality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
  50. Alessandra Luati & Tommaso Proietti & Marco Reale, 2012. "The Variance Profile," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(498), pages 607-621, June.
  51. 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.
  52. Kieran Mc Morrow & Werner Roeger & Valerie Vandermeulen, 2017. "Evaluating Medium Term Forecasting Methods and their Implications for EU Output Gap Calculations," European Economy - Discussion Papers 070, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
  53. Kirstin Hubrich & David F. Hendry, 2005. "Forecasting Aggregates by Disaggregates," Computing in Economics and Finance 2005 270, Society for Computational Economics.
  54. repec:zbw:rwirep:0177 is not listed on IDEAS
  55. Liu, Bai & Yang, Dazhi & Mayer, Martin János & Coimbra, Carlos F.M. & Kleissl, Jan & Kay, Merlinde & Wang, Wenting & Bright, Jamie M. & Xia, Xiang’ao & Lv, Xin & Srinivasan, Dipti & Wu, Yan & Beyer, H, 2023. "Predictability and forecast skill of solar irradiance over the contiguous United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
  56. 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.
  57. 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.
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