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A real-time data set for marcoeconomists: does the data vintage matter?

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Cited by:

  1. Pierdzioch, Christian & Döpke, Jörg & Hartmann, Daniel, 2008. "Forecasting stock market volatility with macroeconomic variables in real time," Journal of Economics and Business, Elsevier, vol. 60(3), pages 256-276.
  2. Valle e Azevedo, João & Pereira, Ana, 2013. "Approximating and forecasting macroeconomic signals in real-time," International Journal of Forecasting, Elsevier, vol. 29(3), pages 479-492.
  3. Adam J. Check & Anna K Nolan & Tyler C. Schipper, 2019. "Forecasting GDP Growth using Disaggregated GDP Revisions," Economics Bulletin, AccessEcon, vol. 39(4), pages 2580-2588.
  4. 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.
  5. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
  6. Stekler, H.O., 2007. "The future of macroeconomic forecasting: Understanding the forecasting process," International Journal of Forecasting, Elsevier, vol. 23(2), pages 237-248.
  7. Vivian, Andrew & Wohar, Mark E., 2013. "The output gap and stock returns: Do cyclical fluctuations predict portfolio returns?," International Review of Financial Analysis, Elsevier, vol. 26(C), pages 40-50.
  8. Croushore, Dean & Evans, Charles L., 2006. "Data revisions and the identification of monetary policy shocks," Journal of Monetary Economics, Elsevier, vol. 53(6), pages 1135-1160, September.
  9. Nicholas Taylor, 2014. "Economic forecast quality: information timeliness and data vintage effects," Empirical Economics, Springer, vol. 46(1), pages 145-174, February.
  10. Domenico Giannone & Lucrezia Reichlin & Luca Sala, 2005. "Monetary Policy in Real Time," NBER Chapters, in: NBER Macroeconomics Annual 2004, Volume 19, pages 161-224, National Bureau of Economic Research, Inc.
  11. Andrew C. Chang & Trace J. Levinson, 2023. "Raiders of the lost high‐frequency forecasts: New data and evidence on the efficiency of the Fed's forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(1), pages 88-104, January.
  12. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
  13. repec:wrk:wrkemf:31 is not listed on IDEAS
  14. Magnus Kvåle Helliesen & Håvard Hungnes & Terje Skjerpen, 2022. "Revisions in the Norwegian National Accounts: accuracy, unbiasedness and efficiency in preliminary figures," Empirical Economics, Springer, vol. 62(3), pages 1079-1121, March.
  15. Francesco Ravazzolo & Philip Rothman, 2013. "Oil and U.S. GDP: A Real-Time Out-of-Sample Examination," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(2-3), pages 449-463, March.
  16. Lise Pichette & Marie-Noëlle Robitaille, 2017. "Assessing the Business Outlook Survey Indicator Using Real-Time Data," Discussion Papers 17-5, Bank of Canada.
  17. de Carvalho, Miguel & Rua, António, 2017. "Real-time nowcasting the US output gap: Singular spectrum analysis at work," International Journal of Forecasting, Elsevier, vol. 33(1), pages 185-198.
  18. Andrew T. Levin & Alexei Onatski & John Williams & Noah M. Williams, 2006. "Monetary Policy under Uncertainty in Micro-Founded Macroeconometric Models," NBER Chapters, in: NBER Macroeconomics Annual 2005, Volume 20, pages 229-312, National Bureau of Economic Research, Inc.
  19. Ronald Indergand & Stefan Leist, 2014. "A Real-Time Data Set for Switzerland," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 150(IV), pages 331-352, December.
  20. Andreas Fischer & Marlene Amstad, 2004. "Sequential Information Flow and Real-Time Diagnosis of Swiss Inflation: Intra-Monthly DCF Estimates for a Low-Inflation Environment," Working Papers 04.06, Swiss National Bank, Study Center Gerzensee.
  21. Barbara Rossi, 2019. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," Working Papers 1162, Barcelona School of Economics.
  22. Alberto Caruso & Laura Coroneo, 2019. "Predicting interest rates in real-time," Discussion Papers 19/18, Department of Economics, University of York.
  23. Massimiliano Marcellino, 2008. "A linear benchmark for forecasting GDP growth and inflation?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(4), pages 305-340.
  24. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
  25. Mandler, Martin, 2007. "Decomposing Federal Funds Rate forecast uncertainty using real-time data," MPRA Paper 13498, University Library of Munich, Germany, revised Jan 2009.
  26. Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2023. "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(3), pages 355-387, July.
  27. Tierney, Heather L.R., 2011. "Forecasting and tracking real-time data revisions in inflation persistence," MPRA Paper 34439, University Library of Munich, Germany.
  28. Tierney, Heather L.R., 2011. "Real-time data revisions and the PCE measure of inflation," Economic Modelling, Elsevier, vol. 28(4), pages 1763-1773, July.
  29. Clements, Michael P. & Beatriz Galvao, Ana, 2010. "Real-time Forecasting of Inflation and Output Growth in the Presence of Data Revisions," Economic Research Papers 270771, University of Warwick - Department of Economics.
  30. van Os, Bram & van Dijk, Dick, 2024. "Accelerating peak dating in a dynamic factor Markov-switching model," International Journal of Forecasting, Elsevier, vol. 40(1), pages 313-323.
  31. John W. Galbraith & Simon van Norden, 2009. "Calibration and Resolution Diagnostics for Bank of England Density Forecasts," CIRANO Working Papers 2009s-36, CIRANO.
  32. Marcelle Chauvet & James D. Hamilton, 2006. "Dating Business Cycle Turning Points," Contributions to Economic Analysis, in: Nonlinear Time Series Analysis of Business Cycles, pages 1-54, Emerald Group Publishing Limited.
  33. Aslanidis, Nektarios & Cipollini, Andrea, 2010. "Leading indicator properties of US high-yield credit spreads," Journal of Macroeconomics, Elsevier, vol. 32(1), pages 145-156, March.
  34. Benoit Bellone & David Saint-Martin, 2004. "Detecting Turning Points with Many Predictors through Hidden Markov Models," Econometrics 0407001, University Library of Munich, Germany.
  35. 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.
  36. Clements, Michael P. & Galvao, Ana Beatriz, 2006. "Macroeconomic Forecasting with Mixed Frequency Data: Forecasting US output growth and inflation," Economic Research Papers 269743, University of Warwick - Department of Economics.
  37. Leonard I. Nakamura & Tom Stark, 2005. "Benchmark revisions and the U.S. personal saving rate," Working Papers 05-6, Federal Reserve Bank of Philadelphia.
  38. John W. Galbraith & Simon van Norden, 2008. "The Calibration of Probabilistic Economic Forecasts," CIRANO Working Papers 2008s-28, CIRANO.
  39. Alessandra Amendola & Vincenzo Candila & Antonio Scognamillo, 2017. "On the influence of US monetary policy on crude oil price volatility," Empirical Economics, Springer, vol. 52(1), pages 155-178, February.
  40. Garratt, Anthony & Koop, Gary & Mise, Emi & Vahey, Shaun P., 2009. "Real-Time Prediction With U.K. Monetary Aggregates in the Presence of Model Uncertainty," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 480-491.
  41. Graham Elliott & Allan Timmermann, 2016. "Economic Forecasting," Economics Books, Princeton University Press, edition 1, number 10740.
  42. Zijun Wang, 2010. "Directed graphs, information structure and forecast combinations: an empirical examination of US unemployment rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(4), pages 353-366.
  43. Benoit Bellone, 2004. "Une lecture probabiliste du cycle d’affaires américain," Econometrics 0407002, University Library of Munich, Germany, revised 28 Mar 2005.
  44. Michael Pedersen, 2013. "Extracting GDP signals from the monthly indicator of economic activity: Evidence from Chilean real-time data," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(1), pages 1-16.
  45. Andrew C. Chang & Phillip Li, 2018. "Measurement Error In Macroeconomic Data And Economics Research: Data Revisions, Gross Domestic Product, And Gross Domestic Income," Economic Inquiry, Western Economic Association International, vol. 56(3), pages 1846-1869, July.
  46. Zhang, Bo & Chan, Joshua C.C. & Cross, Jamie L., 2020. "Stochastic volatility models with ARMA innovations: An application to G7 inflation forecasts," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1318-1328.
  47. Michael P. Clements & Ana Beatriz Galvao, 2009. "Forecasting US output growth using leading indicators: an appraisal using MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(7), pages 1187-1206.
  48. Ales Bulir & Jaromir Hurnik & Katerina Smidkova, 2013. "Inflation Reports and Models: How Well Do Central Banks Really Write?," Working Papers 2013/03, Czech National Bank.
  49. Kizys, Renatas & Pierdzioch, Christian, 2011. "The changing sensitivity of realized portfolio betas to U.S. output growth: An analysis based on real-time data," Journal of Economics and Business, Elsevier, vol. 63(3), pages 168-186, May.
  50. 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.
  51. Yunus Aksoy & Kurmas Akdogan, 2006. "Exchange Rates and Fundamentals: Is there a Role for Nonlinearities in Real Time?," Computing in Economics and Finance 2006 12, Society for Computational Economics.
  52. Gazzani, Andrea & Venditti, Fabrizio & Veronese, Giovanni, 2024. "Oil price shocks in real time," Journal of Monetary Economics, Elsevier, vol. 144(C).
  53. Tatiana Cesaroni & Stefano Iezzi, 2017. "The Predictive Content of Business Survey Indicators: Evidence from SIGE," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 13(1), pages 75-104, May.
  54. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
  55. Andrew C. Chang & Trace J. Levinson, 2020. "Raiders of the Lost High-Frequency Forecasts: New Data and Evidence on the Efficiency of the Fed's Forecasting," Finance and Economics Discussion Series 2020-090, Board of Governors of the Federal Reserve System (U.S.).
  56. Raffaella Giacomini & Barbara Rossi, 2013. "Forecasting in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 17, pages 381-408, Edward Elgar Publishing.
  57. Bernanke, Ben S. & Boivin, Jean, 2003. "Monetary policy in a data-rich environment," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
  58. 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.
  59. 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.
  60. Steve Cook, 2008. "Cross‐data‐vintage Encompassing," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 849-865, December.
  61. Andrew C. Chang & Phillip Li, 2015. "Is Economics Research Replicable? Sixty Published Papers from Thirteen Journals Say \"Usually Not\"," Finance and Economics Discussion Series 2015-83, Board of Governors of the Federal Reserve System (U.S.).
  62. Mazzi Gian Luigi & Mitchell James & Carausu Florabela, 2021. "Measuring and Communicating the Uncertainty in Official Economic Statistics," Journal of Official Statistics, Sciendo, vol. 37(2), pages 289-316, June.
  63. Tony Chernis & Rodrigo Sekkel, 2018. "Nowcasting Canadian Economic Activity in an Uncertain Environment," Discussion Papers 18-9, Bank of Canada.
  64. Branch, William A., 2007. "Sticky information and model uncertainty in survey data on inflation expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 31(1), pages 245-276, January.
  65. Alexandre Bonnet R. Costa & Pedro Cavalcanti G. Ferreira & Wagner Piazza Gaglianone & Osmani Teixeira C. Guillén & João Victor Issler & Artur Brasil Fialho Rodrigues, 2023. "Predicting Recessions in (almost) Real Time in a Big-data Setting," Working Papers Series 587, Central Bank of Brazil, Research Department.
  66. S Cook, 2011. "An historical perspective on the forecasting performance of the Treasury Model: Forecasting the growth in UK consumers' expenditure," Post-Print hal-00665455, HAL.
  67. Benjamin Beckers, 2015. "The Real-Time Predictive Content of Asset Price Bubbles for Macro Forecasts," Discussion Papers of DIW Berlin 1496, DIW Berlin, German Institute for Economic Research.
  68. Clements, Michael P. & Beatriz Galvão, Ana, 2010. "First announcements and real economic activity," European Economic Review, Elsevier, vol. 54(6), pages 803-817, August.
  69. Jiang, Lei, 2014. "Stock liquidity and the Taylor rule," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 202-214.
  70. João Valle e Azevedo, 2011. "Rational vs. professional forecasts," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
  71. Tom Stark, 2000. "Does current-quarter information improve quarterly forecasts for the U.S. economy?," Working Papers 00-2, Federal Reserve Bank of Philadelphia.
  72. Clark, Todd E. & McCracken, Michael W., 2009. "Tests of Equal Predictive Ability With Real-Time Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 441-454.
  73. Boriss Siliverstovs, 2020. "Assessing nowcast accuracy of US GDP growth in real time: the role of booms and busts," Empirical Economics, Springer, vol. 58(1), pages 7-27, January.
  74. 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.
  75. 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.
  76. Lahura, Erick, 2017. "Monetary Aggregates and Monetary Policy in Peru," Working Papers 2017-003, Banco Central de Reserva del Perú.
  77. Roger D. Congleton & Youngshin Kim & Alexander Marsella, 2020. "On the stability of U.S. politics: post-sample forecasts and refinements of the Congleton–Shughart models of Social Security and Medicare benefit levels," Public Choice, Springer, vol. 183(1), pages 101-132, April.
  78. repec:dgr:rugsom:12009-eef is not listed on IDEAS
  79. Raul Ibarra, 2016. "How important is the credit channel in the transmission of monetary policy in Mexico?," Applied Economics, Taylor & Francis Journals, vol. 48(36), pages 3462-3484, August.
  80. Hui Feng, 2005. "Real-Time or Current Vintage: Does the Type of Data Matter for Forecasting and Model Selection?," Econometrics Working Papers 0515, Department of Economics, University of Victoria.
  81. Rad, Hossein & Low, Rand Kwong Yew & Miffre, Joëlle & Faff, Robert, 2023. "The commodity risk premium and neural networks," Journal of Empirical Finance, Elsevier, vol. 74(C).
  82. Döpke, Jörg & Hartmann, Daniel & Pierdzioch, Christian, 2008. "Real-time macroeconomic data and ex ante stock return predictability," International Review of Financial Analysis, Elsevier, vol. 17(2), pages 274-290.
  83. Parigi, Giuseppe & Golinelli, Roberto, 2005. "Short-Run Italian GDP Forecasting and Real-Time Data," CEPR Discussion Papers 5302, C.E.P.R. Discussion Papers.
  84. Boysen-Hogrefe, Jens & Neuwirth, Stefan, 2012. "The impact of seasonal and price adjustments on the predictability of German GDP revisions," Kiel Working Papers 1753, Kiel Institute for the World Economy (IfW Kiel).
  85. Alexander Herzog-Stein & Camille Logeay, 2019. "Short-Term macroeconomic evaluation of the German minimum wage with a VAR/VECM," IMK Working Paper 197-2019, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
  86. Tony Chernis & Taylor Webley, 2022. "Nowcasting Canadian GDP with Density Combinations," Discussion Papers 2022-12, Bank of Canada.
  87. Gregory E. Givens, 2017. "Do Data Revisions Matter for DSGE Estimation?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(6), pages 1385-1407, September.
  88. Benhima, Kenza & Poilly, Céline, 2021. "Does demand noise matter? Identification and implications," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 278-295.
  89. Döpke, Jörg, 2004. "Real-time data and business cycle analysis in Germany," Discussion Paper Series 1: Economic Studies 2004,11, Deutsche Bundesbank.
  90. Domenico Giannone & Jérôme Henry & Magdalena Lalik & Michele Modugno, 2012. "An Area-Wide Real-Time Database for the Euro Area," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1000-1013, November.
  91. 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.
  92. Hamilton, James D., 2011. "Calling recessions in real time," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1006-1026, October.
  93. Clements, Michael P, 2006. "Internal consistency of survey respondents.forecasts : Evidence based on the Survey of Professional Forecasters," The Warwick Economics Research Paper Series (TWERPS) 772, University of Warwick, Department of Economics.
  94. Nicolas Reigl, 2023. "Noise shocks and business cycle fluctuations in three major European Economies," Empirical Economics, Springer, vol. 64(2), pages 603-657, February.
  95. Biswas, Anindya, 2014. "The output gap and expected security returns," Review of Financial Economics, Elsevier, vol. 23(3), pages 131-140.
  96. 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.
  97. Chrystalleni Aristidou & Kevin Lee & Kalvinder Shields, 2015. "Real-Time Data should be used in Forecasting Output Growth and Recessionary Events in the US," Discussion Papers 2015/13, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
  98. Paredes, Joan & Pedregal, Diego J. & Pérez, Javier J., 2009. "A quarterly fiscal database for the euro area based on intra-annual fiscal information," Working Paper Series 1132, European Central Bank.
  99. Ahsan ul Haq Satti & Wasim Shahid Malik, 2017. "The Unreliability of Output-Gap Estimates in Real Time," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 56(3), pages 193-219.
  100. Dungey, Mardi & Jacobs, Jan & Tian, Jing & Norden, Simon van, 2012. "On trend-cycle decomposition and data revision," Research Report 12009-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
  101. Martin Slanicay & Jan Čapek & Miroslav Hloušek, 2016. "Some Notes On Problematic Issues In Dsge Models," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 61(210), pages 79-100, July - Se.
  102. Clements Michael P., 2012. "Forecasting U.S. Output Growth with Non-Linear Models in the Presence of Data Uncertainty," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(1), pages 1-27, January.
  103. Paolo Pasquariello & Clara Vega, 2007. "Informed and Strategic Order Flow in the Bond Markets," The Review of Financial Studies, Society for Financial Studies, vol. 20(6), pages 1975-2019, November.
  104. 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.
  105. Denis Shibitov & Mariam Mamedli, 2021. "Forecasting Russian Cpi With Data Vintages And Machine Learning Techniques," Bank of Russia Working Paper Series wps70, Bank of Russia.
  106. Genre, Véronique & Kenny, Geoff & Meyler, Aidan & Timmermann, Allan, 2013. "Combining expert forecasts: Can anything beat the simple average?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 108-121.
  107. Dean Croushore, 2019. "Revisions to PCE Inflation Measures: Implications for Monetary Policy," International Journal of Central Banking, International Journal of Central Banking, vol. 15(4), pages 241-265, October.
  108. Yi Zheng & James Rossiter, 2006. "Using Monthly Indicators to Predict Quarterly GDP," Staff Working Papers 06-26, Bank of Canada.
  109. Asimakopoulos, Stylianos & Lalik, Magdalena & Paredes, Joan & Salvado García, José, 2023. "GDP revisions are not cool: the impact of statistical agencies’ trade-off," Working Paper Series 2857, European Central Bank.
  110. Semieniuk, Gregor, 2024. "Inconsistent definitions of GDP: Implications for estimates of decoupling," Ecological Economics, Elsevier, vol. 215(C).
  111. S. Borağan Aruoba, 2008. "Data Revisions Are Not Well Behaved," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2‐3), pages 319-340, March.
  112. 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.
  113. Capek Jan, 2015. "Estimating DSGE model parameters in a small open economy: Do real-time data matter?," Review of Economic Perspectives, Sciendo, vol. 15(1), pages 89-114, March.
  114. Kizys, Renatas & Pierdzioch, Christian, 2010. "The business cycle and the equity risk premium in real time," International Review of Economics & Finance, Elsevier, vol. 19(4), pages 711-722, October.
  115. Benoît Bellone, 2006. "Une lecture probabiliste du cycle d’affaires américain," Économie et Prévision, Programme National Persée, vol. 172(1), pages 63-81.
  116. D'Elia, Enrico, 2012. "A case study: the revisions and forecasts of Euro Area quarterly GDP," MPRA Paper 40264, University Library of Munich, Germany.
  117. Leonard I. Nakamura & Tom Stark, 2007. "Mismeasured personal saving and the permanent income hypothesis," Working Papers 07-8, Federal Reserve Bank of Philadelphia.
  118. Cath Sleeman, 2006. "Analysis of revisions to quarterly GDP - a real-time database," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 69, pages 1-44., March.
  119. Heather L. R. Tierney, 2019. "Forecasting with the Nonparametric Exclusion-from-Core Inflation Persistence Model Using Real-Time Data," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 25(1), pages 39-63, February.
  120. Dean Croushore & Tom Stark, 2000. "A real-time data set for macroeconomists: does data vintage matter for forecasting?," Working Papers 00-6, Federal Reserve Bank of Philadelphia.
  121. S. Boragan Aruoba, 2004. "Data Uncertainty in General Equilibrium," Computing in Economics and Finance 2004 131, Society for Computational Economics.
  122. Bo Zhang, 2019. "Real‐time inflation forecast combination for time‐varying coefficient models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(3), pages 175-191, April.
  123. Dean Croushore & Tom Stark, 1999. "Does data vintage matter for forecasting?," Working Papers 99-15, Federal Reserve Bank of Philadelphia.
  124. Mandler, Martin, 2012. "Decomposing Federal Funds Rate forecast uncertainty using time-varying Taylor rules and real-time data," The North American Journal of Economics and Finance, Elsevier, vol. 23(2), pages 228-245.
  125. Jens Hogrefe, 2008. "Forecasting data revisions of GDP: a mixed frequency approach," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(3), pages 271-296, August.
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