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Citations for "Tests of Conditional Predictive Ability"

by Raffaella Giacomini & Halbert White

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  1. repec:hal:journl:peer-00844809 is not listed on IDEAS
  2. Paye, Bradley S., 2012. "‘Déjà vol’: Predictive regressions for aggregate stock market volatility using macroeconomic variables," Journal of Financial Economics, Elsevier, vol. 106(3), pages 527-546.
  3. Banbura, Marta & Giannone, Domenico & Reichlin, Lucrezia, 2007. "Bayesian VARs with Large Panels," CEPR Discussion Papers 6326, C.E.P.R. Discussion Papers.
  4. Santiago Cajiao Raigosa & Luis Fernando Melo Velandia & Daniel Parra Amado, 2014. "Pronósticos para una economía menos volátil: el caso colombiano," COYUNTURA ECONÓMICA, FEDESARROLLO, December.
  5. Chudik, Alexander & Pesaran, Hashem, 2009. "Infinite-dimensional VARs and factor models," Working Paper Series 0998, European Central Bank.
  6. Chernov, Mikhail & Mueller, Philippe, 2008. "The Term Structure of Inflation Expectations," CEPR Discussion Papers 6809, C.E.P.R. Discussion Papers.
  7. Clark, Todd E. & West, Kenneth D., 2006. "Using out-of-sample mean squared prediction errors to test the martingale difference hypothesis," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 155-186.
  8. Marie Bessec, 2010. "Etalonnages du taux de croissance du PIB français sur la base des enquêtes de conjoncture," Economie & Prévision, La Documentation Française, vol. 0(2), pages 77-99.
  9. Michael P. Clements & Ana Beatriz Galvão, 2011. "Improving Real-time Estimates of Output Gaps and Inflation Trends with Multiple-vintage Models," Working Papers 678, Queen Mary University of London, School of Economics and Finance.
  10. Rombouts, Jeroen & Stentoft, Lars & Violante, Franceso, 2014. "The value of multivariate model sophistication: An application to pricing Dow Jones Industrial Average options," International Journal of Forecasting, Elsevier, vol. 30(1), pages 78-98.
  11. Tim Oliver Berg & Steffen Henzel, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," Ifo Working Paper Series Ifo Working Paper No. 155, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  12. Medel, Carlos A., 2015. "Forecasting Inflation with the Hybrid New Keynesian Phillips Curve: A Compact-Scale Global VAR Approach," MPRA Paper 67081, University Library of Munich, Germany.
  13. Neil Shephard & Kevin Sheppard, 2010. "Realising the future: forecasting with high-frequency-based volatility (HEAVY) models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 197-231.
  14. R Naraidoo & I Paya, 2010. "Forecasting Monetary Policy Rules in South Africa," Working Papers 611194, Lancaster University Management School, Economics Department.
  15. Hofmann, Boris, 2009. "Do monetary indicators lead euro area inflation?," Journal of International Money and Finance, Elsevier, vol. 28(7), pages 1165-1181, November.
  16. Fawcett, Nicholas & Kapetanios, George & Mitchell, James & Price, Simon, 2014. "Generalised density forecast combinations," Bank of England working papers 492, Bank of England.
  17. Garratt, Anthony & Lee, Kevin & Shields, Kalvinder, 2016. "Forecasting global recessions in a GVAR model of actual and expected output," International Journal of Forecasting, Elsevier, vol. 32(2), pages 374-390.
  18. Mariano, Roberto S. & Preve, Daniel, 2012. "Statistical tests for multiple forecast comparison," Journal of Econometrics, Elsevier, vol. 169(1), pages 123-130.
  19. Medel, Carlos & Camilleri, Gilmour & Hsu, Hsiang-Ling & Kania, Stefan & Touloumtzoglou, Miltiadis, 2015. "Robustness in Foreign Exchange Rate Forecasting Models: Economics-based Modelling After the Financial Crisis," MPRA Paper 65290, University Library of Munich, Germany.
  20. Teodosio Perez-Amaral & Giampiero M. Gallo & Halbert L. White, 2003. "A Flexible Tool for Model Building: the Relevant Transformation of the Inputs Network Approach (RETINA)," Econometrics Working Papers Archive wp2003_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
  21. Juan Carlos Pérez-Velasco Pavón, 2009. "Determinantes de la demanda por la denominación promedio de billete: el caso de México," Monetaria, Centro de Estudios Monetarios Latinoamericanos, vol. 0(4), pages 523-548, octubre-d.
  22. Jaqueson Galimberti & Michele Berardi, 2014. "A Note on the Representative Adaptive Learning Algorithm," KOF Working papers 14-356, KOF Swiss Economic Institute, ETH Zurich.
  23. Barnichon, Regis & Garda, Paula, 2016. "Forecasting unemployment across countries: The ins and outs," European Economic Review, Elsevier, vol. 84(C), pages 165-183.
  24. Pagano Patrizio & Pisani Massimiliano, 2009. "Risk-Adjusted Forecasts of Oil Prices," The B.E. Journal of Macroeconomics, De Gruyter, vol. 9(1), pages 1-28, June.
  25. Baumeister, Christiane & Kilian, Lutz & Lee, Thomas K, 2015. "Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump," CEPR Discussion Papers 10362, C.E.P.R. Discussion Papers.
  26. Daniel Buncic, 2009. "Understanding forecast failure of ESTAR models of real exchange rates," EERI Research Paper Series EERI_RP_2009_18, Economics and Econometrics Research Institute (EERI), Brussels.
  27. Filip Zikes & Jozef Barunik & Nikhil Shenai, 2012. "Modeling and Forecasting Persistent Financial Durations," Papers 1208.3087, arXiv.org, revised Apr 2013.
  28. Marco Aiolfi & Carlo Ambrogio Favero, . "Model Uncertainty, Thick Modelling and the predictability of Stock Returns," Working Papers 221, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  29. Anthony Garratt & James Mitchell & Shaun P. Vahey, 2011. "Measuring Output Gap Nowcast Uncertainty," CAMA Working Papers 2011-16, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  30. Fernandes, Marcelo & Medeiros, Marcelo C. & Scharth, Marcel, 2013. "Modeling and predicting the CBOE market volatility index," Textos para discussão 342, Escola de Economia de São Paulo, Getulio Vargas Foundation (Brazil).
  31. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
  32. Sebastiano Manzan & Dawit Zerom, 2015. "Asymmetric Quantile Persistence and Predictability: the Case of US Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(2), pages 297-318, 04.
  33. Jari Hännikäinen, 2016. "The mortgage spread as a predictor of real-time economic activity," Applied Economics Letters, Taylor & Francis Journals, vol. 23(2), pages 112-116, February.
  34. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH Models," Economics Papers 2012-W01, Economics Group, Nuffield College, University of Oxford.
  35. repec:uea:ueaeco:2016_05 is not listed on IDEAS
  36. Galbraith, John W. & KI[#x1e63]Inbay, Turgut, 2005. "Content horizons for conditional variance forecasts," International Journal of Forecasting, Elsevier, vol. 21(2), pages 249-260.
  37. Boero, Gianna & Smith, Jeremy & Wallis, Kenneth F., 2011. "Scoring rules and survey density forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 379-393.
  38. Amendola, Alessandra & Candila, Vincenzo & Scognamillo, Antonio, 2015. "On the influence of the U.S. monetary policy on the crude oil price volatility," 2015 Fourth Congress, June 11-12, 2015, Ancona, Italy 207860, Italian Association of Agricultural and Applied Economics (AIEAA).
  39. Jonas Dovern & Christina Ziegler, 2008. "Predicting Growth Rates and Recessions. Assessing U.S. Leading Indicators Under Real-Time Conditions," Kiel Working Papers 1397, Kiel Institute for the World Economy.
  40. John Y. Campbell & Samuel B. Thompson, 2005. "Predicting the Equity Premium Out of Sample: Can Anything Beat the Historical Average?," Harvard Institute of Economic Research Working Papers 2084, Harvard - Institute of Economic Research.
  41. Giacomini, Raffaella & Komunjer, Ivana, 2005. "Evaluation and Combination of Conditional Quantile Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 416-431, October.
  42. Sébastien Laurent & Jeroen Rombouts & Francesco Violente, 2009. "On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models," CIRANO Working Papers 2009s-45, CIRANO.
  43. Barbara Rossi & Atsushi Inoue, 2012. "Out-of-Sample Forecast Tests Robust to the Choice of Window Size," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 432-453, April.
  44. Markku Lanne & Jani Luoto & Henri Nyberg, 2014. "Is the Quantity Theory of Money Useful in Forecasting U.S. Inflation?," CREATES Research Papers 2014-26, Department of Economics and Business Economics, Aarhus University.
  45. Cees Diks & Valentyn Panchenko & Dick Van Dijk, 2010. "Out-of-sample comparison of copula specifications in multivariate density forecasts," Post-Print hal-00732675, HAL.
  46. Travis J. Berge, 2014. "Forecasting Disconnected Exchange Rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 713-735, 08.
  47. Gary Koop & Simon M. Potter, 2003. "Forecasting in large macroeconomic panels using Bayesian Model Averaging," Staff Reports 163, Federal Reserve Bank of New York.
  48. 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.
  49. Ahmed, Shamim & Liu, Xiaoquan & Valente, Giorgio, 2016. "Can currency-based risk factors help forecast exchange rates?," International Journal of Forecasting, Elsevier, vol. 32(1), pages 75-97.
  50. Elena Andreou & Constantinos Kourouyiannis & Andros Kourtellos, 2012. "Volatility Forecast Combinations using Asymmetric Loss Functions," University of Cyprus Working Papers in Economics 07-2012, University of Cyprus Department of Economics.
  51. Ziegler, Christina & Eickmeier, Sandra, 2006. "How good are dynamic factor models at forecasting output and inflation? A meta-analytic approach," Discussion Paper Series 1: Economic Studies 2006,42, Deutsche Bundesbank, Research Centre.
  52. De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2006. "Forecasting Using a Large Number of Predictors: Is Bayesian Regression a Valid Alternative to Principal Components?," CEPR Discussion Papers 5829, C.E.P.R. Discussion Papers.
  53. Manzan, Sebastiano & Zerom, Dawit, 2013. "Are macroeconomic variables useful for forecasting the distribution of U.S. inflation?," International Journal of Forecasting, Elsevier, vol. 29(3), pages 469-478.
  54. Aiolfi, Marco & Rodriguez, Marius & Timmermann, Allan G, 2010. "Understanding Analysts' Earnings Expectations: Biases, Nonlinearities and Predictability," CEPR Discussion Papers 7656, C.E.P.R. Discussion Papers.
  55. Monticini, Andrea & Ravazzolo, Francesco, 2014. "Forecasting the intraday market price of money," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 304-315.
  56. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, Elsevier.
  57. Gourieroux, C. & Jasiak, J., 2008. "Dynamic quantile models," Journal of Econometrics, Elsevier, vol. 147(1), pages 198-205, November.
  58. Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial indicators and density forecasts for US output and inflation," Temi di discussione (Economic working papers) 977, Bank of Italy, Economic Research and International Relations Area.
  59. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2014. "Improving Density Forecasts and Value-at-Risk Estimates by Combining Densities," Tinbergen Institute Discussion Papers 14-090/III, Tinbergen Institute.
  60. Ricardo Gimeno & José Manuel Marqués-Sevillano, 2009. "Incertidumbre y el precio del riesgo en un proceso de convergencia nominal," Monetaria, Centro de Estudios Monetarios Latinoamericanos, vol. 0(4), pages 451-489, octubre-d.
  61. El-Shagi, Makram & Giesen, Sebastian & Jung, Alexander, 2016. "Revisiting the relative forecast performances of Fed staff and private forecasters: A dynamic approach," International Journal of Forecasting, Elsevier, vol. 32(2), pages 313-323.
  62. Breitung, Jörg & Eickmeier, Sandra, 2005. "Dynamic factor models," Discussion Paper Series 1: Economic Studies 2005,38, Deutsche Bundesbank, Research Centre.
  63. José Julián Sidaoui & Carlos Capistrán & Daniel Chiquiar & Manuel Ramos Francia, 2009. "A Note on the Predictive Content of PPI over CPI Inflation: The Case of Mexico," Working Papers 2009-14, Banco de México.
  64. Piergiorgio Alessandri & Haroon Mumtaz, 2013. "Financial conditions and density forecasts for US Output and inflation," Joint Research Papers 4, Centre for Central Banking Studies, Bank of England.
  65. André A. P. Santos & Francisco J. Nogales & Esther Ruiz, 2013. "Comparing Univariate and Multivariate Models to Forecast Portfolio Value-at-Risk," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 11(2), pages 400-441, March.
  66. Gonzalo Calvo & Miguel Ricaurte, 2012. "Indicadores Sintéticos para la Proyección de Imacec en Chile," Working Papers Central Bank of Chile 656, Central Bank of Chile.
  67. Ghysels, Eric & Ozkan, Nazire, 2015. "Real-time forecasting of the US federal government budget: A simple mixed frequency data regression approach," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1009-1020.
  68. Le, Van & Zurbruegg, Ralf, 2014. "Forecasting option smile dynamics," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 32-45.
  69. Oscar Jorda & Massimiliano Marcellino, 2008. "Path Forecast Evaluation," Working Papers 85, University of California, Davis, Department of Economics.
  70. Carlos A. Medel Vera, 2011. "¿Akaike o Schwarz? ¿Cuál utilizar para predecir el PIB chileno?," Monetaria, Centro de Estudios Monetarios Latinoamericanos, vol. 0(4), pages 591-615, octubre-d.
  71. Medeiros, Marcelo C. & Vasconcelos, Gabriel F.R., 2016. "Forecasting macroeconomic variables in data-rich environments," Economics Letters, Elsevier, vol. 138(C), pages 50-52.
  72. Andrés Schneider, 2009. "Regímenes de flotación administrada: un enfoque de cartera," Monetaria, Centro de Estudios Monetarios Latinoamericanos, vol. 0(4), pages 549-584, octubre-d.
  73. Ard Reijer, 2013. "Forecasting Dutch GDP and inflation using alternative factor model specifications based on large and small datasets," Empirical Economics, Springer, vol. 44(2), pages 435-453, April.
  74. Rangan Gupta & Alain Kabundi & Stephen Miller & Josine Uwilingiye, 2014. "Using large data sets to forecast sectoral employment," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 229-264, June.
  75. Steven Trypsteen, . "The Importance of a Time-Varying Variance and Cross-Country Interactions in Forecast Models," Discussion Papers 2014/15, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
  76. Francesco Ravazzolo & Philip Rothman, 2010. "Oil and US GDP: A real-time out-of-sample examination," Working Paper 2010/18, Norges Bank.
  77. Wilmer Osvaldo Martínez-Rivera & Manuel Dario Hernández-Bejarano & Juan Manuel Julio-Román, 2014. "On Forecast Evaluation," BORRADORES DE ECONOMIA 011604, BANCO DE LA REPÚBLICA.
  78. Hajo Holzmann & Matthias Eulert, 2014. "The role of the information set for forecasting - with applications to risk management," Papers 1404.7653, arXiv.org.
  79. Rossi, Barbara & Sekhposyan, Tatevik, 2010. "Have economic models' forecasting performance for US output growth and inflation changed over time, and when?," International Journal of Forecasting, Elsevier, vol. 26(4), pages 808-835, October.
  80. Matteo Luciani, 2011. "Forecasting with Approximate Dynamic Factor Models: the Role of Non-Pervasive Shocks," Working Papers ECARES ECARES 2011‐022, ULB -- Universite Libre de Bruxelles.
  81. Drechsel, Katja & Scheufele, Rolf, 2012. "The performance of short-term forecasts of the German economy before and during the 2008/2009 recession," International Journal of Forecasting, Elsevier, vol. 28(2), pages 428-445.
  82. Boriss Siliverstovs & Konstantin A. Kholodilin, 2006. "On Selection of Components for a Diffusion Index Model: It's not the Size, It's How You Use It," Discussion Papers of DIW Berlin 598, DIW Berlin, German Institute for Economic Research.
  83. Carlos Medel, 2012. "How Informative are In–Sample Information Criteria to Forecasting? The Case of Chilean GDP," Working Papers Central Bank of Chile 657, Central Bank of Chile.
  84. 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.
  85. Jordà, Òscar & Taylor, Alan M., 2012. "The carry trade and fundamentals: Nothing to fear but FEER itself," Journal of International Economics, Elsevier, vol. 88(1), pages 74-90.
  86. Guillaume Chevillon & Sophocles Mavroeidis, 2013. "Learning generates Long Memory," Post-Print hal-00661012, HAL.
  87. Barrera, Carlos, 2013. "El sistema de predicción desagregada: Una evaluación de las proyecciones de inflación 2006-2011," Working Papers 2013-009, Banco Central de Reserva del Perú.
  88. Shinichiro Shirota & Takayuki Hizu & Yasuhiro Omori, 2012. "Realized stochastic volatility with leverage and long memory," CIRJE F-Series CIRJE-F-869, CIRJE, Faculty of Economics, University of Tokyo.
  89. Andrea Carriero & George Kapetanios & Massimiliano Marcellino, 2008. "Forecasting Exchange Rates with a Large Bayesian VAR," Working Papers 634, Queen Mary University of London, School of Economics and Finance.
  90. Ferraro, Domenico & Rogoff, Kenneth & Rossi, Barbara, 2011. "Can Oil Prices Forecast Exchange Rates?," CEPR Discussion Papers 8635, C.E.P.R. Discussion Papers.
  91. Todd E. Clark & Michael W. McCracken, 2008. "Tests of equal predictive ability with real-time data," Working Papers 2008-029, Federal Reserve Bank of St. Louis.
  92. Pincheira, Pablo, 2013. "A Bunch of Models, a Bunch of Nulls and Inference about Predictive Ability," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 26-43, October.
  93. Koo, Bonsoo & Seo, Myung Hwan, 2015. "Structural-break models under mis-specification: Implications for forecasting," Journal of Econometrics, Elsevier, vol. 188(1), pages 166-181.
  94. Isao Ishida, 2005. "Scanning Multivariate Conditional Densities with Probability Integral Transforms," CIRJE F-Series CIRJE-F-369, CIRJE, Faculty of Economics, University of Tokyo.
  95. Chudik, Alexander & Pesaran, M. Hashem, 2014. "Theory and practice of GVAR modeling," Globalization and Monetary Policy Institute Working Paper 180, Federal Reserve Bank of Dallas.
  96. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2010. "Should macroeconomic forecasters use daily financial data and how?," University of Cyprus Working Papers in Economics 09-2010, University of Cyprus Department of Economics.
  97. Roxana Halbleib & Valerie Voev, 2011. "Forecasting Covariance Matrices: A Mixed Frequency Approach," Working Papers ECARES ECARES 2011-002, ULB -- Universite Libre de Bruxelles.
  98. D'Agostino, Antonello & Domenico, Giannone & Surico, Paolo, 2006. "(Un)Predictability and Macroeconomic Stability," Research Technical Papers 5/RT/06, Central Bank of Ireland.
  99. Pablo M. Pincheira & Carlos A. Medel, 2015. "Forecasting Inflation with a Simple and Accurate Benchmark: The Case of the US and a Set of Inflation Targeting Countries," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(1), pages 2-29, January.
  100. Todd E. Clark & Michael W. McCracken, 2011. "Advances in forecast evaluation," Working Paper 1120, Federal Reserve Bank of Cleveland.
  101. Amendola, Alessandra & Storti, Giuseppe, 2008. "A GMM procedure for combining volatility forecasts," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3047-3060, February.
  102. Roberto Golinelli & Giuseppe Parigi, 2013. "Tracking world trade and GDP in real time," Temi di discussione (Economic working papers) 920, Bank of Italy, Economic Research and International Relations Area.
  103. Tsiotas, Georgios, 2012. "On generalised asymmetric stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 151-172, January.
  104. Avdulaj, Krenar & Barunik, Jozef, 2015. "Are benefits from oil–stocks diversification gone? New evidence from a dynamic copula and high frequency data," Energy Economics, Elsevier, vol. 51(C), pages 31-44.
  105. Pesaran, M.H. & Pick, A. & Timmermann, A., 2009. "Variable Selection and Inference for Multi-period Forecasting Problems," Cambridge Working Papers in Economics 0901, Faculty of Economics, University of Cambridge.
  106. Milas, Costas & Rothman, Philip, 2008. "Out-of-sample forecasting of unemployment rates with pooled STVECM forecasts," International Journal of Forecasting, Elsevier, vol. 24(1), pages 101-121.
  107. Ana Beatriz Galvão & Michael Artis & Massimiliano Marcellino, 2007. "The transmission mechanism in a changing world," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 39-61.
  108. Marco Lombardi & Raphael A. Espinoza & Fabio Fornari, 2009. "The Role of Financial Variables in Predicting Economic Activity in the Euro Area," IMF Working Papers 09/241, International Monetary Fund.
  109. Boriss Siliverstovs, 2013. "Do business tendency surveys help in forecasting employment?: A real-time evidence for Switzerland," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing,Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 129-151.
  110. Hendry, David F & Hubrich, Kirstin, 2006. "Forecasting Economic Aggregates by Disaggregates," CEPR Discussion Papers 5485, C.E.P.R. Discussion Papers.
  111. Pablo Pincheira B. & Nicolás Fernández, 2011. "Jaque Mate a las Proyecciones de Consenso," Working Papers Central Bank of Chile 630, Central Bank of Chile.
  112. Ferrara, Laurent & Marcellino, Massimiliano & Mogliani, Matteo, 2013. "Macroeconomic forecasting during the Great Recession: The return of non-linearity?," CEPR Discussion Papers 9313, C.E.P.R. Discussion Papers.
  113. Avino, Davide & Nneji, Ogonna, 2012. "Are CDS spreads predictable? An analysis of linear and non-linear forecasting models," MPRA Paper 42848, University Library of Munich, Germany.
  114. A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.
  115. M. Hashem Pesaran & Andreas Pick & Allan Timmermann, 2010. "Variable Selection, Estimation and Inference for Multi-period Forecasting Problems," DNB Working Papers 250, Netherlands Central Bank, Research Department.
  116. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2012. "Was the Recent Downturn in US GDP Predictable?," Working Papers 1210, University of Nevada, Las Vegas , Department of Economics.
  117. Anatolyev, Stanislav & Gospodinov, Nikolay & Jamali, Ibrahim & Liu, Xiaochun, 2015. "Foreign exchange predictability during the financial crisis: implications for carry trade profitability," FRB Atlanta Working Paper 2015-6, Federal Reserve Bank of Atlanta.
  118. Dijk, D. van & Diks, C.G.H. & Panchenko, V., 2008. "Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails," CeNDEF Working Papers 08-03, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  119. Mansoor Maitah & Daniel Toth & Elena Kuzmenko & Karel Šrédl & Helena Rezbová & Petra Šánová, 2016. "Forecast of Employment in Switzerland: The Macroeconomic View," International Journal of Economics and Financial Issues, Econjournals, vol. 6(1), pages 132-138.
  120. Todd E. Clark & Kenneth D. West, 2005. "Using Out-of-Sample Mean Squared Prediction Errors to Test the Martingale Difference," NBER Technical Working Papers 0305, National Bureau of Economic Research, Inc.
  121. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2015. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Tinbergen Institute Discussion Papers 15-140/III, Tinbergen Institute.
  122. Stefania D'Amico, 2004. "Density Estimation and Combination under Model Ambiguity," Computing in Economics and Finance 2004 273, Society for Computational Economics.
  123. Makram El-Shagi & Sebastian Giesen & A. Jung, 2012. "Does Central Bank Staff Beat Private Forecasters?," IWH Discussion Papers 5, Halle Institute for Economic Research.
  124. repec:zbw:iwhdps:10-10 is not listed on IDEAS
  125. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
  126. Busetti, Fabio & Marcucci, Juri, 2013. "Comparing forecast accuracy: A Monte Carlo investigation," International Journal of Forecasting, Elsevier, vol. 29(1), pages 13-27.
  127. Teräsvirta, Timo, 2005. "Forecasting economic variables with nonlinear models," SSE/EFI Working Paper Series in Economics and Finance 598, Stockholm School of Economics, revised 29 Dec 2005.
  128. Gürkaynak, Refet S. & Kisacikoglu, Burçin & Rossi, Barbara, 2013. "Do DSGE Models Forecast More Accurately Out-of-Sample than VAR Models?," CEPR Discussion Papers 9576, C.E.P.R. Discussion Papers.
  129. Michele Berardi & Jaqueson K. Galimberti, 2015. "Empirical Calibration of Adaptive Learning," KOF Working papers 15-392, KOF Swiss Economic Institute, ETH Zurich.
  130. : Arie E. Gozluklu, 2012. "Inflation, Stock Market and Long-Term Investors: Real Effects of Changing Demographics," Working Papers wpn12-06, Warwick Business School, Finance Group.
  131. Noureldin, Diaa & Shephard, Neil & Sheppard, Kevin, 2014. "Multivariate rotated ARCH models," Journal of Econometrics, Elsevier, vol. 179(1), pages 16-30.
  132. Lee, Yun Shin & Scholtes, Stefan, 2014. "Empirical prediction intervals revisited," International Journal of Forecasting, Elsevier, vol. 30(2), pages 217-234.
  133. Barbara Rossi & Tatevik Sekhposyan, 2010. "Understanding Models' Forecasting Performance," Working Papers 10-56, Duke University, Department of Economics.
  134. Blaskowitz, Oliver & Herwartz, Helmut, 2014. "Testing the value of directional forecasts in the presence of serial correlation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 30-42.
  135. Garratt, Anthony & Mitchell, James & Vahey, Shaun, 2010. "Measuring Output Gap Uncertainty," CEPR Discussion Papers 7742, C.E.P.R. Discussion Papers.
  136. Raúl Ibarra-Ramírez, 2010. "Forecasting Inflation in Mexico Using Factor Models: Do Disaggregated CPI Data Improve Forecast Accuracy?," Working Papers 2010-01, Banco de México.
  137. Todd E. Clark & Michael W. Mccracken, 2014. "Tests Of Equal Forecast Accuracy For Overlapping Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 415-430, 04.
  138. Inske Pirschel & Maik Wolters, 2014. "Forecasting German Key Macroeconomic Variables Using Large Dataset Methods," Kiel Working Papers 1925, Kiel Institute for the World Economy.
  139. Bouwman, Kees E. & Jacobs, Jan P.A.M., 2005. "Forecasting with real-time macroeconomic data: the ragged-edge problem and revisions," CCSO Working Papers 200505, University of Groningen, CCSO Centre for Economic Research.
  140. Gianluca Cubadda & Barbara Guardabascio, 2010. "A Medium-N Approach to Macroeconomic Forecasting," CEIS Research Paper 176, Tor Vergata University, CEIS, revised 09 Dec 2010.
  141. Pablo Pincheira & Carlos A. Medel, 2012. "Forecasting Inflation with a Simple and Accurate Benchmark: a Cross-Country Analysis," Working Papers Central Bank of Chile 677, Central Bank of Chile.
  142. Kenneth D. West & Todd Clark, 2006. "Approximately Normal Tests for Equal Predictive Accuracy in Nested Models," NBER Technical Working Papers 0326, National Bureau of Economic Research, Inc.
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  285. Ouysse, Rachida, 2016. "Bayesian model averaging and principal component regression forecasts in a data rich environment," International Journal of Forecasting, Elsevier, vol. 32(3), pages 763-787.
  286. Rangan Gupta & Anandamayee Majumdar & Christian Pierdzioch & Mark Wohar, 2016. "Do Terror Attacks Predict Gold Returns? Evidence from a Quantile-Predictive-Regression Approach," Working Papers 201626, University of Pretoria, Department of Economics.
  287. Dr. James Mitchell, 2008. "Evaluating Density Forecasts: Forecast Combinations, Model Mixtures, Calibration and Sharpness," NIESR Discussion Papers 320, National Institute of Economic and Social Research.
  288. Maria Gonzalez-Perez & Alfonso Novales, 2011. "The information content in a volatility index for Spain," SERIEs- Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 2(2), pages 185-216, June.
  289. Idrovo Aguirre, Byron & Tejada, Mauricio, 2010. "Modelos de predicción para la inflación de Chile
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  290. Sepideh Dolatabadi & Paresh Kumar Narayan & Morten Ørregaard Nielsen & Ke Xu, 2016. "Economic significance of commodity return forecasts from the fractionally cointegrated VAR model," Working Papers 1337, Queen's University, Department of Economics.
  291. Oh, Dong Hwan & Patton, Andrew J., 2015. "High-Dimensional Copula-Based Distributions with Mixed Frequency Data," Finance and Economics Discussion Series 2015-50, Board of Governors of the Federal Reserve System (U.S.).
  292. Kevin Sheppard & Lily Liu & Andrew J. Patton, 2013. "Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes," Economics Series Working Papers 645, University of Oxford, Department of Economics.
  293. Carlos Medel, 2012. "¿Akaike o Schwarz? ¿Cuál elegir para Predecir el PIB Chileno?," Working Papers Central Bank of Chile 658, Central Bank of Chile.
  294. Diks, Cees & Panchenko, Valentyn & Sokolinskiy, Oleg & van Dijk, Dick, 2014. "Comparing the accuracy of multivariate density forecasts in selected regions of the copula support," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 79-94.
  295. Michael P. Clements & David F. Hendry, 2005. "Guest Editors' Introduction: Information in Economic Forecasting," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 713-753, December.
  296. Mike Buckle & Jing Chen & Julian Williams, 2014. "How Predictable Are Equity Covariance Matrices? Evidence from High‐Frequency Data for Four Markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(7), pages 542-557, November.
  297. repec:gam:jecnmx:v:4:y:2016:i:1:p:15:d:65565 is not listed on IDEAS
  298. Giacomini, Raffaella, 2014. "Economic theory and forecasting: lessons from the literature," CEPR Discussion Papers 10201, C.E.P.R. Discussion Papers.
  299. repec:gam:jecnmx:v:4:y:2016:i:1:p:8:d:64253 is not listed on IDEAS
  300. Ruthira Naraidoo & Kasai Ndahiriwe, 2010. "Financial asset prices, linear and nonlinear policy rules. An In-sample assessment of the reaction function of the South African Reserve Bank," Working Papers 201006, University of Pretoria, Department of Economics.
  301. Dotsey, Michael & Fujita, Shigeru & Stark, Tom, 2015. "Do Phillips curves conditionally help to forecast inflation?," Working Papers 15-16, Federal Reserve Bank of Philadelphia.
  302. Javier Contreras-Reyes & Wilfredo Palma, 2013. "Statistical analysis of autoregressive fractionally integrated moving average models in R," Computational Statistics, Springer, vol. 28(5), pages 2309-2331, October.
  303. Haroon Mumtaz & Nitin Kumar, 2012. "An application of data-rich environment for policy analysis of the Indian economy," Joint Research Papers 2, Centre for Central Banking Studies, Bank of England.
  304. El-Shagi, Makram & Giesen, Sebastian & Jung, Alexander, 2014. "Does the federal reserve staff still beat private forecasters?," Working Paper Series 1635, European Central Bank.
  305. Chu, Ba, 2011. "Recovering copulas from limited information and an application to asset allocation," Journal of Banking & Finance, Elsevier, vol. 35(7), pages 1824-1842, July.
  306. Georgios Tsiotas, 2009. "On the use of non-linear transformations in Stochastic Volatility models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(4), pages 555-583, November.
  307. Niels S. Hansen & Asger Lunde, 2013. "Analyzing Oil Futures with a Dynamic Nelson-Siegel Model," CREATES Research Papers 2013-36, Department of Economics and Business Economics, Aarhus University.
  308. Hansen, Peter Reinhard & Lunde, Asger, 2006. "Consistent ranking of volatility models," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 97-121.
  309. Cecilia Frale, . "Do Surveys Help in Macroeconomic Variables Disaggregation and Estimation?," Working Papers wp2008-2, Department of the Treasury, Ministry of the Economy and of Finance.
  310. Manuel Landajo & Javier de Andrés & Pedro Lorca, 2008. "Measuring firm performance by using linear and non-parametric quantile regressions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(2), pages 227-250.
  311. Ghent, Andra C., 2009. "Comparing DSGE-VAR forecasting models: How big are the differences?," Journal of Economic Dynamics and Control, Elsevier, vol. 33(4), pages 864-882, April.
  312. David E. Rapach & Jack K. Strauss, 2008. "Structural breaks and GARCH models of exchange rate volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 65-90.
  313. Sarno, Lucio & Schneider, Paul & Wagner, Christian, 2010. "Properties of Foreign Exchange Risk Premia," MPRA Paper 21302, University Library of Munich, Germany.
  314. João Caldeira & Guilherme Moura & André Santos, 2015. "Measuring Risk in Fixed Income Portfolios using Yield Curve Models," Computational Economics, Society for Computational Economics, vol. 46(1), pages 65-82, June.
  315. Hännikäinen, Jari, 2014. "Multi-step forecasting in the presence of breaks," MPRA Paper 55816, University Library of Munich, Germany.
  316. Altug, Sumru G. & Cakmakli, Cem, 2015. "Forecasting Inflation using Survey Expectations and Target Inflation: Evidence for Brazil and Turkey," CEPR Discussion Papers 10419, C.E.P.R. Discussion Papers.
  317. Todd E. Clark & Michael W. McCracken, 2006. "Forecasting of small macroeconomic VARs in the presence of instabilities," Research Working Paper RWP 06-09, Federal Reserve Bank of Kansas City.
  318. Euler Pereira G. de Mello & Francisco Marcos R. Figueiredo, 2014. "Assessing the Short-term Forecasting Power of Confidence Indices," Working Papers Series 371, Central Bank of Brazil, Research Department.
  319. Kyungchul Song, 2009. "Testing Predictive Ability and Power Robustification," PIER Working Paper Archive 09-035, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  320. Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
  321. Şener, Emrah & Baronyan, Sayad & Ali Mengütürk, Levent, 2012. "Ranking the predictive performances of value-at-risk estimation methods," International Journal of Forecasting, Elsevier, vol. 28(4), pages 849-873.
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  323. repec:zbw:iwhdps:5-12 is not listed on IDEAS
  324. Ruiz, Esther & Hotta, Luiz & Almeida, Daniel De, 2015. "MGARCH models: tradeoff between feasibility and flexibility," DES - Working Papers. Statistics and Econometrics. WS ws1516, Universidad Carlos III de Madrid. Departamento de Estadística.
  325. Ando, Tomohiro & Tsay, Ruey, 2010. "Predictive likelihood for Bayesian model selection and averaging," International Journal of Forecasting, Elsevier, vol. 26(4), pages 744-763, October.
  326. Audrino, Francesco, 2014. "Forecasting correlations during the late-2000s financial crisis: The short-run component, the long-run component, and structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 43-60.
  327. Serena Ng & Jonathan H. Wright, 2013. "Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling," NBER Working Papers 19469, National Bureau of Economic Research, Inc.
  328. Francesco Ravazzolo & Shaun P Vahey, 2010. "Measuring Core Inflation in Australia with Disaggregate Ensembles," RBA Annual Conference Volume, in: Renée Fry & Callum Jones & Christopher Kent (ed.), Inflation in an Era of Relative Price Shocks Reserve Bank of Australia.
  329. Mihaylov, George & Cheong, Chee Seng & Zurbruegg, Ralf, 2015. "Can security analyst forecasts predict gold returns?," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 237-246.
  330. Kaminska, Iryna & Roberts-Sklar, Matt, 2015. "A global factor in variance risk premia and local bond pricing," Bank of England working papers 576, Bank of England.
  331. Calista Cheung & Frédérick Demers, 2007. "Evaluating Forecasts from Factor Models for Canadian GDP Growth and Core Inflation," Staff Working Papers 07-8, Bank of Canada.
  332. Todd E. Clark & Michael W. McCracken, 2009. "Nested forecast model comparisons: a new approach to testing equal accuracy," Working Papers 2009-050, Federal Reserve Bank of St. Louis.
  333. Roque Montero & Javier García-Cicco, 2012. "Modelo y Pronóstico del Precio del Cobre: Un Enfoque de Cambio de Regímenes," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 15(2), pages 099-116, August.
  334. Siem Jan Koopman & Rutger Lit, 2012. "A Dynamic Bivariate Poisson Model for Analysing and Forecasting Match Results in the English Premier League," Tinbergen Institute Discussion Papers 12-099/III, Tinbergen Institute.
  335. Park, Timothy A. & Gubanova, Tatiana & Lohr, Luanne & Escalante, Cesar L., 2005. "Forecasting Organic Food Prices: Testing and Evaluating Conditional Predictive Ability," 2005 Annual meeting, July 24-27, Providence, RI 19412, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  336. Byun, Sung Je, 2016. "The usefulness of cross-sectional dispersion for forecasting aggregate stock price volatility," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 162-180.
  337. Javier García - Cicco & Roque Montero, 2011. "Modeling Copper Price: A Regime-Switching Approach," Working Papers Central Bank of Chile 613, Central Bank of Chile.
  338. Ibarra, Raul, 2012. "Do disaggregated CPI data improve the accuracy of inflation forecasts?," Economic Modelling, Elsevier, vol. 29(4), pages 1305-1313.
  339. Eran Raviv, 2013. "Prediction Bias Correction for Dynamic Term Structure Models," Tinbergen Institute Discussion Papers 13-041/III, Tinbergen Institute.
  340. Pablo Pincheira B., 2008. "Predictibilidad Encubierta en Economía: El Caso del Tipo de Cambio Nominal Chileno," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 11(1), pages 137-142, April.
  341. Ferraro, Domenico & Rogoff, Kenneth & Rossi, Barbara, 2015. "Can oil prices forecast exchange rates? An empirical analysis of the relationship between commodity prices and exchange rates," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 116-141.
  342. Liu, Xiaochun, 2015. "Modeling time-varying skewness via decomposition for out-of-sample forecast," International Journal of Forecasting, Elsevier, vol. 31(2), pages 296-311.
  343. Anders Bredahl Kock & Timo Teräsvirta, 2011. "Forecasting Macroeconomic Variables using Neural Network Models and Three Automated Model Selection Techniques," CREATES Research Papers 2011-27, Department of Economics and Business Economics, Aarhus University.
This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.