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Citations for "Tests of Conditional Predictive Ability"

by Giacomini, Raffaella & White, Halbert

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  1. Kirstin Hubrich, 2004. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," Computing in Economics and Finance 2004 230, Society for Computational Economics.
  2. Rocío Elizondo, 2013. "Forecasting the Term Structure of Interest Rates in Mexico Using an Affine Model," Working Papers 2013-03, Banco de México.
  3. Carlos Medel & Gilmour Camilleri & Hsiang-Ling Hsu & Stefan Kania & Miltiadis Touloumtzoglou, 2016. "Robustness in Foreign Exchange Rate Forecasting Models: Economics-Based Modelling After the Financial Crisis," Working Papers Central Bank of Chile 784, Central Bank of Chile.
  4. Massimo Guidolin & Allan Timmerman, 2007. "Forecasts of U.S. short-term interest rates: a flexible forecast combination approach," Working Papers 2005-059, Federal Reserve Bank of St. Louis.
  5. repec:uea:ueaeco:2016_05 is not listed on IDEAS
  6. Joan Jasiak & C. Gourieroux, 2006. "Dynamic Quantile Models," Working Papers 2006_4, York University, Department of Economics.
  7. Rangan Gupta & Alain Kabundi & Stephen M. Miller & Josine Uwilingiye, 2011. "Using Large Data Sets to Forecast Sectoral Employment," Working Papers 1106, University of Nevada, Las Vegas , Department of Economics.
  8. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
  9. N. Fawcett & G. Kapetanios & J. Mitchell & S. Price, 2014. "Generalised Density Forecast Combinations," CAMA Working Papers 2014-24, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  10. Buncic, Daniel, 2009. "Understanding forecast failure of ESTAR models of real exchange rates," MPRA Paper 16526, University Library of Munich, Germany.
  11. 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.
  12. Neil Shephard & Kevin Sheppard, 2009. "Realising the future: forecasting with high frequency based volatility (HEAVY) models," OFRC Working Papers Series 2009fe02, Oxford Financial Research Centre.
  13. Hännikäinen, Jari, 2014. "The mortgage spread as a predictor of real-time economic activity," MPRA Paper 58360, University Library of Munich, Germany.
  14. Issler, João Victor & Lima, Luiz Renato, 2009. "A panel data approach to economic forecasting: The bias-corrected average forecast," Journal of Econometrics, Elsevier, vol. 152(2), pages 153-164, October.
  15. Neil Shephard & Kevin Sheppard, 2009. "Nuisance parameters, composite likelihoods and a panel of GARCH models," Economics Series Working Papers 458, University of Oxford, Department of Economics.
  16. Sébastien Laurent & Jeroen V. K. Rombouts & Francesco Violante, 2012. "On the forecasting accuracy of multivariate GARCH models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 934-955, 09.
  17. Pablo Pincheira, 2012. "A Joint Test of Superior Predictive Ability for Chilean Inflation Forecasts," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 15(3), pages 04-39, December.
  18. Döpke, Jörg & Hartmann, Daniel & Pierdzioch, Christian, 2006. "Forecasting stock market volatility with macroeconomic variables in real time," Discussion Paper Series 2: Banking and Financial Studies 2006,01, Deutsche Bundesbank, Research Centre.
  19. Giovanni Calice & Christos Ioannidis & Julian Williams, 2011. "Credit Derivatives and the Default Risk of Large Complex Financial Institutions," CESifo Working Paper Series 3583, CESifo Group Munich.
  20. Hännikäinen, Jari, 2014. "Zero lower bound, unconventional monetary policy and indicator properties of interest rate spreads," MPRA Paper 56737, University Library of Munich, Germany.
  21. Marco Aiolfi & Marius Rodriguez & Allan Timmermann, 2010. "Understanding Analysts' Earnings Expectations: Biases, Nonlinearities, and Predictability," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 8(3), pages 305-334, Summer.
  22. Gianni Amisano & Raffaella Giacomini, 2005. "Comparing Density Forecsts via Weighted Likelihood Ratio Tests," Working Papers ubs0504, University of Brescia, Department of Economics.
  23. Conflitti, Cristina & De Mol, Christine & Giannone, Domenico, 2015. "Optimal combination of survey forecasts," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1096-1103.
  24. Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial conditions and density forecasts for US output and inflation," CReMFi Discussion Papers 1, CReMFi, School of Economics and Finance, QMUL.
  25. 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.
  26. Todd E. Clark & Michael W. McCracken, 2009. "Nested forecast model comparisons: a new approach to testing equal accuracy," Research Working Paper RWP 09-11, Federal Reserve Bank of Kansas City.
  27. Carriero, A. & Kapetanios, G. & Marcellino, M., 2009. "Forecasting exchange rates with a large Bayesian VAR," International Journal of Forecasting, Elsevier, vol. 25(2), pages 400-417.
  28. 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.
  29. 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, 03.
  30. 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.
  31. Hännikäinen, Jari, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," MPRA Paper 70489, University Library of Munich, Germany.
  32. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2008. "Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails," Discussion Papers 2008-10, School of Economics, The University of New South Wales.
  33. 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).
  34. Laurent, Sébastien & Rombouts, Jeroen V.K. & Violante, Francesco, 2013. "On loss functions and ranking forecasting performances of multivariate volatility models," Journal of Econometrics, Elsevier, vol. 173(1), pages 1-10.
  35. John Y. Campbell & Samuel B. Thompson, 2005. "Predicting the Equity Premium Out of Sample: Can Anything Beat the Historical Average?," NBER Working Papers 11468, National Bureau of Economic Research, Inc.
  36. Golinelli, Roberto & Parigi, Giuseppe, 2008. "Real-time squared: A real-time data set for real-time GDP forecasting," International Journal of Forecasting, Elsevier, vol. 24(3), pages 368-385.
  37. Rossi, Barbara & Sekhposyan, Tatevik, 2011. "Understanding models' forecasting performance," Journal of Econometrics, Elsevier, vol. 164(1), pages 158-172, September.
  38. Travis J. Berge, 2013. "Predicting recessions with leading indicators: model averaging and selection over the business cycle," Research Working Paper RWP 13-05, Federal Reserve Bank of Kansas City.
  39. Pablo Pincheira Brown & Álvaro García Marín, 2009. "Forecasting Inflation in Chile With an Accurate Benchmark," Working Papers Central Bank of Chile 514, Central Bank of Chile.
  40. Götz Thomas B. & Hecq Alain & Urbain Jean-Pierre, 2012. "Real-Time Forecast Density Combinations (Forecasting US GDP Growth Using Mixed-Frequency Data)," Research Memorandum 021, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
  41. 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.
  42. 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.
  43. Pesaran, M Hashem & Pick, Andreas & Timmermann, Allan G, 2009. "Variable Selection and Inference for Multi-period Forecasting Problems," CEPR Discussion Papers 7139, C.E.P.R. Discussion Papers.
  44. Kees E. Bouwman & Elvira Sojli & Wing Wah Tham, 2012. "Aggregate Stock Market Illiquidity and Bond Risk Premia," Tinbergen Institute Discussion Papers 12-140/IV/DSF46, Tinbergen Institute.
  45. 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.
  46. 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.).
  47. Gary Koop & Simon Potter, 2003. "Forecasting in Large Macroeconomic Panels using Bayesian Model Averaging," Discussion Papers in Economics 04/16, Department of Economics, University of Leicester.
  48. 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.
  49. Joëts, Marc, 2015. "Heterogeneous beliefs, regret, and uncertainty: The role of speculation in energy price dynamics," European Journal of Operational Research, Elsevier, vol. 247(1), pages 204-215.
  50. Teodosio Perez-Amaral & Giampiero M. Gallo & Halbert White, 2003. "A Flexible Tool for Model Building: the Relevant Transformation of the Inputs Network Approach (RETINA)," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 821-838, December.
  51. Pablo Pincheira, 2010. "A Real Time Evaluation of the Central Bank of Chile GDP Growth Forecasts," Money Affairs, Centro de Estudios Monetarios Latinoamericanos, vol. 0(1), pages 37-73, January-J.
  52. 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.
  53. Eric Ghysels & Andros Kourtellos & Elena Andreou, 2012. "Should macroeconomic forecasters use daily financial data and how?," 2012 Meeting Papers 1196, Society for Economic Dynamics.
  54. Pirschel, Inske & Wolters, Maik H., 2014. "Forecasting German key macroeconomic variables using large dataset methods," Kiel Working Papers 1925, Kiel Institute for the World Economy (IfW).
  55. Cees Diks & Valentyn Panchenko & Oleg Sokolinskiy, & Dick van Dijk, 2013. "Comparing the Accuracy of Copula-Based Multivariate Density Forecasts in Selected Regions of Support," Tinbergen Institute Discussion Papers 13-061/III, Tinbergen Institute.
  56. Chen Xilong & Ghysels Eric & Wang Fangfang, 2011. "HYBRID GARCH Models and Intra-Daily Return Periodicity," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-28, February.
  57. 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).
  58. Michele Berardi & Jaqueson K. Galimberti, 2015. "Empirical Calibration of Adaptive Learning," KOF Working papers 15-392, KOF Swiss Economic Institute, ETH Zurich.
  59. Samuel W. Malone & Robert B. Gramacy & Enrique ter Horst, 2016. "Timing Foreign Exchange Markets," Econometrics, MDPI, Open Access Journal, vol. 4(1), pages 15, March.
  60. Bańbura, Marta & Giannone, Domenico & Reichlin, Lucrezia, 2008. "Large Bayesian VARs," Working Paper Series 0966, European Central Bank.
  61. Veiga, Helena & Bretó, Carles, 2011. "Forecasting volatility: does continuous time do better than discrete time?," DES - Working Papers. Statistics and Econometrics. WS ws112518, Universidad Carlos III de Madrid. Departamento de Estadística.
  62. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2016. "A quantile-boosting approach to forecasting gold returns," The North American Journal of Economics and Finance, Elsevier, vol. 35(C), pages 38-55.
  63. Andersen, Torben G. & Bollerslev, Tim & Huang, Xin, 2011. "A reduced form framework for modeling volatility of speculative prices based on realized variation measures," Journal of Econometrics, Elsevier, vol. 160(1), pages 176-189, January.
  64. Diks, C.G.H. & Dijk, D. van & Panchenko, V., 2008. "Out-of-sample comparison of copula specifications in multivariate density forecasts," CeNDEF Working Papers 08-10, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  65. Krenar Avdulaj & Jozef Barunik, 2013. "Can we still benefit from international diversification? The case of the Czech and German stock markets," Papers 1308.6120, arXiv.org, revised Sep 2013.
  66. 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.
  67. Hofmann, Boris, 2006. "Do monetary indicators (still) predict euro area inflation?," Discussion Paper Series 1: Economic Studies 2006,18, Deutsche Bundesbank, Research Centre.
  68. Todd E. Clark & Kenneth D. West, 2004. "Using out-of-sample mean squared prediction errors to test the Martingale difference hypothesis," Research Working Paper RWP 04-03, Federal Reserve Bank of Kansas City.
  69. Krueger, Fabian & Clark, Todd E. & Ravazzolo, Francesco, 2015. "Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts," Working Paper 1439, Federal Reserve Bank of Cleveland.
  70. Kirstin Hubrich & Kenneth D. West, 2010. "Forecast evaluation of small nested model sets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 574-594.
  71. Patrizio Pagano & Massimiliano Pisani, 2006. "Risk-Adjusted Forecasts of Oil Prices," Temi di discussione (Economic working papers) 585, Bank of Italy, Economic Research and International Relations Area.
  72. Todd E. Clark & Michael W. McCracken, 2004. "Improving forecast accuracy by combining recursive and rolling forecasts," Research Working Paper RWP 04-10, Federal Reserve Bank of Kansas City.
  73. Peter Reinhard Hansen & Allan Timmermann, 2012. "Equivalence Between Out-of-Sample Forecast Comparisons and Wald Statistics," Economics Working Papers ECO2012/24, European University Institute.
  74. 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.
  75. De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2006. "Forecasting using a large number of predictors: is Bayesian regression a valid alternative to principal components?," Discussion Paper Series 1: Economic Studies 2006,32, Deutsche Bundesbank, Research Centre.
  76. 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.
  77. Barnichon, Regis & Garda, Paula, 2016. "Forecasting unemployment across countries: The ins and outs," European Economic Review, Elsevier, vol. 84(C), pages 165-183.
  78. Allan Timmermann & M. Hashem Pesaran, 2003. "Small Sample Properties of Forecasts from Autoregressive Models under Structural Breaks," CESifo Working Paper Series 990, CESifo Group Munich.
  79. Alexander Chudik & M. Hashem Pesaran, 2016. "Theory And Practice Of Gvar Modelling," Journal of Economic Surveys, Wiley Blackwell, vol. 30(1), pages 165-197, 02.
  80. Alexander Chudik & M. Hashem Pesaran, 2007. "Infinite Dimensional VARs and Factor Models," CESifo Working Paper Series 2176, CESifo Group Munich.
  81. Carlos Medel, 2016. "Forecasting Inflation with the Hybrid New Keynesian Phillips Curve: A Compact-Scale Global VAR Approach," Working Papers Central Bank of Chile 785, Central Bank of Chile.
  82. Carlos Medel, 2015. "Inflation Dynamics and the Hybrid Neo Keynesian Phillips Curve: The Case of Chile," Working Papers Central Bank of Chile 769, Central Bank of Chile.
  83. Thomadakis, Apostolos, 2016. "Do Combination Forecasts Outperform the Historical Average? Economic and Statistical Evidence," MPRA Paper 71589, University Library of Munich, Germany.
  84. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
  85. Jeroen Rombouts & Lars Peter Stentoft & Francesco Violente, 2012. "The Value of Multivariate Model Sophistication: An Application to pricing Dow Jones Industrial Average Options," CIRANO Working Papers 2012s-05, CIRANO.
  86. El-Shagi, Makram & Giesen, Sebastian & Jung, Alexander, 2012. "Does Central Bank Staff Beat Private Forecasters?," IWH Discussion Papers 5/2012, Halle Institute for Economic Research (IWH).
  87. Travis Berge & Òscar Jordà & Alan M. Taylor, 2011. "Currency Carry Trades," NBER International Seminar on Macroeconomics, University of Chicago Press, vol. 7(1), pages 357 - 388.
    • Travis Berge & Òscar Jordà & Alan M. Taylor, 2010. "Currency Carry Trades," NBER Chapters, in: NBER International Seminar on Macroeconomics 2010, pages 357-387 National Bureau of Economic Research, Inc.
  88. 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.
  89. Anthony H. Tu & Cathy Yi-Hsuan Chen, 2016. "What Derives the Bond Portfolio Value-at-Risk: Information Roles of Macroeconomic and Financial Stress Factors," SFB 649 Discussion Papers SFB649DP2016-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  90. 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.
  91. Ferrara, L. & Marcellino, M. & Mogliani, M., 2012. "Macroeconomic forecasting during the Great Recession: The return of non-linearity?," Working papers 383, Banque de France.
  92. Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2016. "Volatility and quantile forecasts by realized stochastic volatility models with generalized hyperbolic distribution," International Journal of Forecasting, Elsevier, vol. 32(2), pages 437-457.
  93. Nicholas Taylor, 2015. "Realized volatility forecasting in an international context," Applied Economics Letters, Taylor & Francis Journals, vol. 22(6), pages 503-509, April.
  94. Juan Díaz Maureira & Gustavo Leyva Jiménez, 2009. "Proyección de la inflación chilena en tiempos difíciles," Monetaria, Centro de Estudios Monetarios Latinoamericanos, vol. 0(4), pages 491-522, octubre-d.
  95. 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.
  96. 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.
  97. Anthony Garratt & James Mitchell & Shaun P. Vahey, 2009. "Measuring Output Gap Uncertainty," Birkbeck Working Papers in Economics and Finance 0909, Birkbeck, Department of Economics, Mathematics & Statistics.
  98. Chevillon, Guillaume & Mavroeidis, Sophocles, 2011. "Learning generates Long Memory," ESSEC Working Papers WP1113, ESSEC Research Center, ESSEC Business School.
  99. Gubanova, Tatiana & Lohr, Luanne & Park, Timothy A., 2005. "Forecasting Organic Food Prices: Emerging Methods for Testing and Evaluating Conditional Predictive Ability," 2005 Conference, April 18-19, 2005, St. Louis, Missouri 19045, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
  100. Emanuel Kohlscheen & Fernando Avalos & Andreas Schrimpf, 2016. "When the walk is not random: commodity prices and exchange rates," BIS Working Papers 551, Bank for International Settlements.
  101. Ida Wolden Bache & James Mitchell & Francesco Ravazzolo & Shaun P. Vahey, 2009. "Macro modelling with many models," Working Paper 2009/15, Norges Bank.
  102. 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.
  103. Jörg Breitung & Sandra Eickmeier, 2006. "Dynamic factor models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 27-42, March.
  104. Santiago Cajiao Raigosa & Luis Fernando Melo Velandia & Daniel Parra Amado, 2014. "Pronósticos para una economía menos volátil: El caso colombiano," Borradores de Economia 821, Banco de la Republica de Colombia.
  105. Audrino, Francesco & Hu, Yujia, 2011. "Volatility Forecasting: Downside Risk, Jumps and Leverage Effect," Economics Working Paper Series 1138, University of St. Gallen, School of Economics and Political Science.
  106. Arbués, Ignacio, 2013. "Determining the MSE-optimal cross section to forecast," Journal of Econometrics, Elsevier, vol. 175(2), pages 61-70.
  107. Stefania D'Amico, 2005. "Density selection and combination under model ambiguity: an application to stock returns," Finance and Economics Discussion Series 2005-09, Board of Governors of the Federal Reserve System (U.S.).
  108. 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.
  109. Gianluca Cubadda & Barbara Guardabascio, 2010. "A Medium-N Approach to Macroeconomic Forecasting," CEIS Research Paper 176, Tor Vergata University, CEIS, revised 09 Dec 2010.
  110. Zikes, Filip & Barunik, Jozef & Shenai, Nikhil, 2015. "Modeling and forecasting persistent financial durations," FinMaP-Working Papers 36, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
  111. 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.
  112. 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.
  113. Monticini, Andrea & Ravazzolo, Francesco, 2014. "Forecasting the intraday market price of money," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 304-315.
  114. 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.
  115. Òscar Jordà & Massimiliano Marcellino, 2010. "Path forecast evaluation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 635-662.
  116. Roxana Halbleib & Valerie Voev, 2011. "Forecasting Covariance Matrices: A Mixed Frequency Approach," Working Papers ECARES ECARES 2011-002, ULB -- Universite Libre de Bruxelles.
  117. Pablo Pincheira, 2011. "A Bunch of Models, a Bunch of Nulls and Inference About Predictive Ability," Working Papers Central Bank of Chile 607, Central Bank of Chile.
  118. 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.
  119. 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.
  120. repec:hal:journl:peer-00834423 is not listed on IDEAS
  121. 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.
  122. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2011. "Multivariate High-Frequency-Based Volatility (HEAVY) Models," Economics Series Working Papers 533, University of Oxford, Department of Economics.
  123. Xilong Chen & Eric Ghysels, 2011. "News--Good or Bad--and Its Impact on Volatility Predictions over Multiple Horizons," Review of Financial Studies, Society for Financial Studies, vol. 24(1), pages 46-81, October.
  124. 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.
  125. Wang, Jian & Wu, Jason J., 2008. "The Taylor rule and forecast intervals for exchange rates," Globalization and Monetary Policy Institute Working Paper 22, Federal Reserve Bank of Dallas.
  126. : Carlo A. Favero & : Arie E. Gozluklu & : Haoxi Yang, 2013. "Demographics and The Behavior of Interest Rates," Working Papers wpn13-10, Warwick Business School, Finance Group.
  127. Naraidoo, Ruthira & Paya, Ivan, 2012. "Forecasting monetary policy rules in South Africa," International Journal of Forecasting, Elsevier, vol. 28(2), pages 446-455.
  128. 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.
  129. Kei Kawakami, 2013. "Conditiona l Forecast Selection from Many Forecasts: An Application to the Yen/Dollar Exchange Rate," Department of Economics - Working Papers Series 1167, The University of Melbourne.
  130. Eran Raviv, 2013. "Prediction Bias Correction for Dynamic Term Structure Models," Tinbergen Institute Discussion Papers 13-041/III, Tinbergen Institute.
  131. Kei Kawakami, 2008. "Forecast Selection by Conditional Predictive Ability Tests: An Application to the Yen/Dollar Exchange Rate," Bank of Japan Working Paper Series 08-E-1, Bank of Japan.
  132. 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.
  133. repec:dau:papers:123456789/13532 is not listed on IDEAS
  134. Domenico Ferraro & Ken Rogoff & Barbara Rossi, 2011. "Can Oil Prices Forecast Exchange Rates?," Working Papers 11-05, Duke University, Department of Economics.
  135. Bec, Frédérique & Gollier, Christian, 2014. "Cyclicality and term structure of Value-at-Risk within a threshold autoregression setup," IDEI Working Papers 835, Institut d'Économie Industrielle (IDEI), Toulouse.
  136. 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.
  137. Tim Oliver Berg & Steffen Henzel, 2014. "Point and Density Forecasts for the Euro Area Using Bayesian VARs," CESifo Working Paper Series 4711, CESifo Group Munich.
  138. Florackis, Chris & Giorgioni, Gianluigi & Kostakis, Alexandros & Milas, Costas, 2014. "On stock market illiquidity and real-time GDP growth," Journal of International Money and Finance, Elsevier, vol. 44(C), pages 210-229.
  139. 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.
  140. 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.
  141. Berens, Tobias & Weiß, Gregor N.F. & Wied, Dominik, 2015. "Testing for structural breaks in correlations: Does it improve Value-at-Risk forecasting?," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 135-152.
  142. 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.
  143. 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.
  144. 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.
  145. Clements, Michael P. & Franses, Philip Hans & Swanson, Norman R., 2004. "Forecasting economic and financial time-series with non-linear models," International Journal of Forecasting, Elsevier, vol. 20(2), pages 169-183.
  146. Luciani, Matteo, 2014. "Forecasting with approximate dynamic factor models: The role of non-pervasive shocks," International Journal of Forecasting, Elsevier, vol. 30(1), pages 20-29.
  147. 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.
  148. Cees Diks & Valentyn Panchenko & Dick Van Dijk, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Post-Print hal-00834423, HAL.
  149. Hendry, David F & Hubrich, Kirstin, 2006. "Forecasting Economic Aggregates by Disaggregates," CEPR Discussion Papers 5485, C.E.P.R. Discussion Papers.
  150. 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.
  151. Chevillon, Guillaume, 2009. "Multi-step forecasting in emerging economies: An investigation of the South African GDP," International Journal of Forecasting, Elsevier, vol. 25(3), pages 602-628, July.
  152. Guillen, Osmani Teixeira Carvalho & Hecq, Alain & Issler, João Victor & Saraiva, Diogo Vinícius Menezes, 2015. "Forecasting multivariate time series under present-value-model short- and long-run co-movement restrictions," Economics Working Papers (Ensaios Economicos da EPGE) 763, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
  153. D'Agostino, Antonello & Giannone, Domenico & Surico, Paolo, 2007. "(Un)Predictability and Macroeconomic Stability," CEPR Discussion Papers 6594, C.E.P.R. Discussion Papers.
  154. Caldeira, João F. & Moura, Guilherme V. & Santos, André A.P., 2016. "Predicting the yield curve using forecast combinations," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 79-98.
  155. Filipović, Damir & Gourier, Elise & Mancini, Loriano, 2016. "Quadratic variance swap models," Journal of Financial Economics, Elsevier, vol. 119(1), pages 44-68.
  156. Neil Shephard & Kevin Sheppard & Robert F. Engle, 2008. "Fitting vast dimensional time-varying covariance models," Economics Series Working Papers 403, University of Oxford, Department of Economics.
  157. Medeiros, Marcelo C. & Vasconcelos, Gabriel F.R., 2016. "Forecasting macroeconomic variables in data-rich environments," Economics Letters, Elsevier, vol. 138(C), pages 50-52.
  158. Guidolin, Massimo & Hyde, Stuart & McMillan, David & Ono, Sadayuki, 2009. "Non-linear predictability in stock and bond returns: When and where is it exploitable?," International Journal of Forecasting, Elsevier, vol. 25(2), pages 373-399.
  159. 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.
  160. Boriss Siliverstovs, 2015. "Dissecting Models’ Forecasting Performance," KOF Working papers 15-397, KOF Swiss Economic Institute, ETH Zurich.
  161. Sarno, Lucio & Schneider, Paul & Wagner, Christian, 2010. "Properties of Foreign Exchange Risk Premia," MPRA Paper 21302, University Library of Munich, Germany.
  162. 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.
  163. Irving Arturo De Lira Salvatierra & Andrew J. Patton, 2013. "Dynamic Copula Models and High Frequency Data," Working Papers 13-28, Duke University, Department of Economics.
  164. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH models," Economics Series Working Papers 594, University of Oxford, Department of Economics.
  165. 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.
  166. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2015. "A real-time quantile-regression approach to forecasting gold returns under asymmetric loss," Resources Policy, Elsevier, vol. 45(C), pages 299-306.
  167. Michael ARTIS & Ana Beatriz C. GALVÃO & Massimiliano MARCELLINO, 2003. "The transmission mechanism in a changing world," Economics Working Papers ECO2003/18, European University Institute.
  168. 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.
  169. Emilio Zanetti Chini, 2013. "Generalizing smooth transition autoregressions," CREATES Research Papers 2013-32, Department of Economics and Business Economics, Aarhus University.
  170. repec:uea:ueaeco:2016_07 is not listed on IDEAS
  171. Gabriel Rodríguez, 2016. " Modelando la volatilidad de los mercados bursátiles y cambiarios en América Latina: Aplicación empírica de un modelo de cambios de nivel aleatorios y larga memoria genuina," Documentos de Trabajo / Working Papers 2016-416, Departamento de Economía - Pontificia Universidad Católica del Perú.
  172. 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.
  173. Mihaela Bratu, 2011. "The Assessement Of Uncertainty In Predictions Determined By The Variables Aggregation," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 2(13), pages 31.
  174. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
  175. repec:zbw:iwhdps:5-12 is not listed on IDEAS
  176. Golinelli, Roberto & Parigi, Giuseppe, 2005. "Short-Run Italian GDP Forecasting and Real-Time Data," CEPR Discussion Papers 5302, C.E.P.R. Discussion Papers.
  177. Andrea Betancor & Pablo Pincheira, 2008. "Forecasting Inflation Forecast Errors," Working Papers Central Bank of Chile 477, Central Bank of Chile.
  178. Jaqueson Galimberti & Michele Berardi, 2014. "A Note on the Representative Adaptive Learning Algorithm," KOF Working papers 14-356, KOF Swiss Economic Institute, ETH Zurich.
  179. Paul D. McNelis & Salih N. Neftci, 2006. "Renminbi Revaluation, Euro Appreciation and Chinese Markets: What Can We Learn From Data?," Working Papers 012006, Hong Kong Institute for Monetary Research.
  180. 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.
  181. 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.
  182. 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.
  183. Kozhan, Roman & Salmon, Mark, 2012. "The information content of a limit order book: The case of an FX market," Journal of Financial Markets, Elsevier, vol. 15(1), pages 1-28.
  184. Pablo Pincheira B. & Nicolás Fernández, 2011. "Jaque Mate a las Proyecciones de Consenso," Working Papers Central Bank of Chile 630, Central Bank of Chile.
  185. Lucio Sarno & Paul Schneider & Christian Wagner, 2012. "Properties of Foreign Exchange Risk Premiums," Working Paper Series 10_12, The Rimini Centre for Economic Analysis.
  186. 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.
  187. Dreger, Christian & Wolters, Jürgen, 2014. "Money demand and the role of monetary indicators in forecasting euro area inflation," International Journal of Forecasting, Elsevier, vol. 30(2), pages 303-312.
  188. Andrea Carriero & Raffaella Giacomini, 2011. "How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?," Post-Print hal-00844809, HAL.
  189. Katja Drechsel & Rolf Scheufele, 2010. "Should We Trust in Leading Indicators? Evidence from the Recent Recession," IWH Discussion Papers 10, Halle Institute for Economic Research.
  190. Dotsey, Michael & Fujita, Shigeru & Stark, Tom, 2015. "Do Phillips curves conditionally help to forecast inflation?," Working Papers 15-16, Federal Reserve Bank of Philadelphia.
  191. Hansen, Peter Reinhard & Lunde, Asger, 2006. "Consistent ranking of volatility models," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 97-121.
  192. Golinelli, Roberto & Parigi, Giuseppe, 2014. "Tracking world trade and GDP in real time," International Journal of Forecasting, Elsevier, vol. 30(4), pages 847-862.
  193. 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.
  194. Gupta, Rangan & Steinbach, Rudi, 2013. "A DSGE-VAR model for forecasting key South African macroeconomic variables," Economic Modelling, Elsevier, vol. 33(C), pages 19-33.
  195. 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.
  196. 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.
  197. Benavides, Guillermo & Capistrán, Carlos, 2012. "Forecasting exchange rate volatility: The superior performance of conditional combinations of time series and option implied forecasts," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 627-639.
  198. Maria Dolores Gadea Rivas & Gabriel Perez-Quiros, 2012. "The failure to predict the Great Recession. The failure of academic economics? A view focusing on the role of credit," Working Papers 1240, Banco de España;Working Papers Homepage.
  199. El-Shagi, Makram & Giesen, Sebastian & Jung, Alexander, 2014. "Does the federal reserve staff still beat private forecasters?," Working Paper Series 1635, European Central Bank.
  200. Neri, Marcelo Cortes, 2014. "Brazil's middle classes," Economics Working Papers (Ensaios Economicos da EPGE) 759, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
  201. Knüppel, Malte & Schultefrankenfeld, Guido, 2013. "The Empirical (Ir)Relevance of the Interest Rate Assumption for Central Bank Forecasts," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 80042, Verein für Socialpolitik / German Economic Association.
  202. Kopoin, Alexandre & Moran, Kevin & Paré, Jean-Pierre, 2013. "Forecasting regional GDP with factor models: How useful are national and international data?," Economics Letters, Elsevier, vol. 121(2), pages 267-270.
  203. Calhoun, Gray, 2014. "Out-Of-Sample Comparisons of Overfit Models," Staff General Research Papers 32462, Iowa State University, Department of Economics.
  204. 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).
  205. Nikolsko-Rzhevskyy, Alex & Prodan, Ruxandra, 2012. "Markov switching and exchange rate predictability," International Journal of Forecasting, Elsevier, vol. 28(2), pages 353-365.
  206. Chernov, Mikhail & Mueller, Philippe, 2012. "The term structure of inflation expectations," Journal of Financial Economics, Elsevier, vol. 106(2), pages 367-394.
  207. Todd E. Clark & Michael W. McCracken, 2011. "Advances in forecast evaluation," Working Papers 2011-025, Federal Reserve Bank of St. Louis.
  208. Niels Haldrup & Oskar Knapik & Tommaso Proietti, 2016. "A generalized exponential time series regression model for electricity prices," CREATES Research Papers 2016-08, Department of Economics and Business Economics, Aarhus University.
  209. Ruiz, Esther & Nogales, Francisco J. & Santos, André A. P., 2009. "Comparing univariate and multivariate models to forecast portfolio value-at-risk," DES - Working Papers. Statistics and Econometrics. WS ws097222, Universidad Carlos III de Madrid. Departamento de Estadística.
  210. Javier García - Cicco & Roque Montero, 2011. "Modeling Copper Price: A Regime-Switching Approach," Working Papers Central Bank of Chile 613, Central Bank of Chile.
  211. Brave, Scott & Butters, R. Andrew & Justiniano, Alejandro, 2016. "Forecasting Economic Activity with Mixed Frequency Bayesian VARs," Working Paper Series WP-2016-5, Federal Reserve Bank of Chicago.
  212. Marie Bessec & Julien Fouquau & Sophie Meritet, 2016. "Forecasting electricity spot prices using time-series models with a double temporal segmentation," Applied Economics, Taylor & Francis Journals, vol. 48(5), pages 361-378, January.
  213. Osmani Teixeira de Carvalho Guillén & Alain Hecq & João Victor Issler & Diogo Saraiva, 2013. "Time Series under Present-Value-Model Short- and Long-run Co-movement Restrictions," Working Papers Series 330, Central Bank of Brazil, Research Department.
  214. Elliott, Graham & Timmermann, Allan G, 2016. "Forecasting in Economics and Finance," CEPR Discussion Papers 11354, C.E.P.R. Discussion Papers.
  215. Claus, Edda & Lucey, Brian M., 2012. "Equity market integration in the Asia Pacific region: Evidence from discount factors," Research in International Business and Finance, Elsevier, vol. 26(2), pages 137-163.
  216. 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.
  217. 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.
  218. 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.
  219. Jennifer Castle & David Hendry, 2012. "Forecasting by factors, by variables, or both?," Economics Series Working Papers 600, University of Oxford, Department of Economics.
  220. Giacomini, Raffaella & Ragusa, Giuseppe, 2011. "Incorporating theoretical restrictions into forecasting by projection methods," CEPR Discussion Papers 8604, C.E.P.R. Discussion Papers.
  221. Carlos Capistrán, 2007. "Optimality Tests for Multi-Horizon Forecasts," Working Papers 2007-14, Banco de México.
  222. Hajo Holzmann & Matthias Eulert, 2014. "The role of the information set for forecasting - with applications to risk management," Papers 1404.7653, arXiv.org.
  223. Hua, Jian & Manzan, Sebastiano, 2013. "Forecasting the return distribution using high-frequency volatility measures," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4381-4403.
  224. 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.
  225. 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.
  226. Yelland, Phillip M., 2010. "Bayesian forecasting of parts demand," International Journal of Forecasting, Elsevier, vol. 26(2), pages 374-396, April.
  227. Robinson Durán & Evelyn Garrido & Carolina Godoy & Juan de Dios Tena, 2012. "Predicción de la inflación en México con modelos desagregados por componente," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 27(1), pages 133-167.
  228. 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.
  229. 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.
  230. Patton, Andrew J., 2011. "Data-based ranking of realised volatility estimators," Journal of Econometrics, Elsevier, vol. 161(2), pages 284-303, April.
  231. : 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.
  232. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, Elsevier.
  233. Sergii Pypko, 2015. "Volatility Forecast in Crises and Expansions," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 8(3), pages 311, August.
  234. Lee, Yun Shin & Scholtes, Stefan, 2014. "Empirical prediction intervals revisited," International Journal of Forecasting, Elsevier, vol. 30(2), pages 217-234.
  235. Theodore M. Crone & N. Neil K. Khettry & Loretta J. Mester & Jason A. Novak, 2011. "Core measures of inflation as predictors of total inflation," Working Papers 11-24, Federal Reserve Bank of Philadelphia.
  236. Pablo Pincheira & Roberto Álvarez, 2012. "Evaluation of Short Run Inflation Forecasts in Chile," Working Papers Central Bank of Chile 674, Central Bank of Chile.
  237. Tamara Burdisso & Eduardo Ariel Corso, 2011. "Incertidumbre y dolarización de cartera: el caso argentino en el último medio siglo," Monetaria, Centro de Estudios Monetarios Latinoamericanos, vol. 0(4), pages 461-515, octubre-d.
  238. 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.
  239. 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.
  240. 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.
  241. Le, Van & Zurbruegg, Ralf, 2014. "Forecasting option smile dynamics," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 32-45.
  242. Jonas Dovern & Christina Ziegler, 2008. "Predicting Growth Rates and Recessions. Assessing U.S. Leading Indicators under Real-Time Condition," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 54(4), pages 293-318.
  243. 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.
  244. Hong, Yongmiao & Li, Haitao & Zhao, Feng, 2007. "Can the random walk model be beaten in out-of-sample density forecasts? Evidence from intraday foreign exchange rates," Journal of Econometrics, Elsevier, vol. 141(2), pages 736-776, December.
  245. 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.
  246. Amendola, Alessandra & Storti, Giuseppe, 2008. "A GMM procedure for combining volatility forecasts," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3047-3060, February.
  247. 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.
  248. 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.
  249. 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.
  250. 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.
  251. Fawcett, Nicholas & Koerber, Lena & Masolo, Riccardo & Waldron, Matthew, 2015. "Evaluating UK point and density forecasts from an estimated DSGE model: the role of off-model information over the financial crisis," Bank of England working papers 538, Bank of England.
  252. 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).
  253. Alain Hecq & Sébastien Laurent & Franz C. Palm, 2011. "Common Intraday Periodicity," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 10(2), pages 325-353, 2012 20 1.
  254. Robinson Kruse & Christian Leschinski & Michael Will, 2016. "Comparing Predictive Accuracy under Long Memory - With an Application to Volatility Forecasting," CREATES Research Papers 2016-17, Department of Economics and Business Economics, Aarhus University.
  255. 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.
  256. McMillan, David G., 2014. "Stock return, dividend growth and consumption growth predictability across markets and time: Implications for stock price movement," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 90-101.
  257. Timmermann, Allan, 2008. "Elusive return predictability," International Journal of Forecasting, Elsevier, vol. 24(1), pages 1-18.
  258. Raffaella Giacomini & Barbara Rossi, 2010. "Forecast comparisons in unstable environments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 595-620.
  259. 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.
  260. 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.
  261. repec:gam:jecnmx:v:4:y:2016:i:1:p:15:d:65565 is not listed on IDEAS
  262. 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.
  263. 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.
  264. Travis J. Berge, 2014. "Forecasting Disconnected Exchange Rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 713-735, 08.
  265. 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.
  266. Ghent, Andra, 2006. "Comparing Models of Macroeconomic Fluctuations: How Big Are the Differences?," MPRA Paper 180, University Library of Munich, Germany.
  267. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2014. "Does the Macroeconomy Predict UK Asset Returns in a Nonlinear Fashion? Comprehensive Out-of-Sample Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(4), pages 510-535, 08.
  268. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, Elsevier.
  269. Javier Contreras-Reyes & Byron Idrovo, 2011. "En busca de un modelo Benchmark univariado para predecir la tasa de desempleo," REVISTA CUADERNOS DE ECONOMÍA, UN - RCE - CID, December.
  270. 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.
  271. Jennifer Castle & David Hendry, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
  272. Mauro Bernardi & Leopoldo Catania, 2016. "Comparison of Value-at-Risk models using the MCS approach," Computational Statistics, Springer, vol. 31(2), pages 579-608, June.
  273. 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.
  274. 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.
  275. Makram El-Shagi & Sebastian Giesen & A. Jung, 2012. "Does Central Bank Staff Beat Private Forecasters?," IWH Discussion Papers 5, Halle Institute for Economic Research.
  276. Javier Pereda, 2011. "Estimación de la tasa natural de interés para Perú: un enfoque financiero," Monetaria, Centro de Estudios Monetarios Latinoamericanos, vol. 0(4), pages 429-459, octubre-d.
  277. 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.
  278. 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.
  279. repec:zbw:iwhdps:10-10 is not listed on IDEAS
  280. Carlos Medel, 2012. "¿Akaike o Schwarz? ¿Cuál elegir para Predecir el PIB Chileno?," Working Papers Central Bank of Chile 658, Central Bank of Chile.
  281. 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.
  282. 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.
  283. Fabio Busetti & Juri Marcucci & Giovanni Veronese, 2009. "Comparing forecast accuracy: A Monte Carlo investigation," Temi di discussione (Economic working papers) 723, Bank of Italy, Economic Research and International Relations Area.
  284. 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.
  285. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
  286. 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.
  287. repec:hal:journl:peer-00844809 is not listed on IDEAS
  288. Seiler, Christian & Heumann, Christian, 2012. "Microdata imputations and macrodata implications: evidence from the Ifo Business Survey," MPRA Paper 37045, University Library of Munich, Germany.
  289. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2013. "Predicting Covariance Matrices with Financial Conditions Indexes," Tinbergen Institute Discussion Papers 13-113/III, Tinbergen Institute.
  290. Gael M. Martin & Andrew Reidy & Jill Wright, 2009. "Does the option market produce superior forecasts of noise-corrected volatility measures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 77-104.
  291. 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.
  292. Noureldin, Diaa & Shephard, Neil & Sheppard, Kevin, 2014. "Multivariate rotated ARCH models," Journal of Econometrics, Elsevier, vol. 179(1), pages 16-30.
  293. 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.
  294. Manzan, Sebastiano & Zerom, Dawit, 2009. "Are Macroeconomic Variables Useful for Forecasting the Distribution of U.S. Inflation?," MPRA Paper 14387, University Library of Munich, Germany.
  295. Hännikäinen, Jari, 2015. "Selection of an estimation window in the presence of data revisions and recent structural breaks," MPRA Paper 66759, University Library of Munich, Germany.
  296. Guido Bulligan & Roberto Golinelli & Giuseppe Parigi, 2010. "Forecasting monthly industrial production in real-time: from single equations to factor-based models," Empirical Economics, Springer, vol. 39(2), pages 303-336, October.
  297. Meyer, Brent & Venkatu, Guhan, 2014. "Trimmed-Mean Inflation Statistics: Just Hit the One in the Middle," FRB Atlanta Working Paper 2014-3, Federal Reserve Bank of Atlanta.
  298. Abdymomunov, Azamat, 2013. "Predicting output using the entire yield curve," Journal of Macroeconomics, Elsevier, vol. 37(C), pages 333-344.
  299. Krenar Avdulaj & Jozef Barunik, 2013. "Are benefits from oil - stocks diversification gone? New evidence from a dynamic copula and high frequency data," Papers 1307.5981, arXiv.org, revised Feb 2015.
  300. Costas Milas & Phil Rothman, 2005. "Multivariate STAR Unemployment Rate Forecasts," Econometrics 0502010, EconWPA.
  301. 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.
  302. Hofmann, Boris, 2009. "Do monetary indicators lead euro area inflation?," Journal of International Money and Finance, Elsevier, vol. 28(7), pages 1165-1181, November.
  303. Pesaran, M. Hashem & Pick, Andreas & Timmermann, Allan, 2011. "Variable selection, estimation and inference for multi-period forecasting problems," Journal of Econometrics, Elsevier, vol. 164(1), pages 173-187, September.
  304. Isao Ishida, 2005. "Scanning Multivariate Conditional Densities with Probability Integral Transforms," CIRJE F-Series CIRJE-F-369, CIRJE, Faculty of Economics, University of Tokyo.
  305. 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.
  306. 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.
  307. Meyer, Brent & Tasci, Murat, 2015. "Lessons for forecasting unemployment in the United States: use flow rates, mind the trend," FRB Atlanta Working Paper 2015-1, Federal Reserve Bank of Atlanta.
  308. Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2014. "Causality and predictability in distribution: The ethanol–food price relation revisited," Energy Economics, Elsevier, vol. 42(C), pages 152-160.
  309. 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.
  310. 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.
  311. Lorenzo Boldrini & Eric Hillebrand, 2015. "Supervision in Factor Models Using a Large Number of Predictors," CREATES Research Papers 2015-38, Department of Economics and Business Economics, Aarhus University.
  312. Hännikäinen, Jari, 2014. "Multi-step forecasting in the presence of breaks," MPRA Paper 55816, University Library of Munich, Germany.
  313. Daniel Fernández, 2011. "Suficiencia del capital y previsiones de la banca uruguaya por su exposición al sector industrial," Monetaria, Centro de Estudios Monetarios Latinoamericanos, vol. 0(4), pages 517-589, octubre-d.
  314. Tsiotas, Georgios, 2012. "On generalised asymmetric stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 151-172, January.
  315. 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.
  316. 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.
  317. 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.
  318. 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.
  319. Wilmer Osvaldo Martínez-Rivera & Manuel Dario Hernández-Bejarano & Juan Manuel Julio-Román, 2014. "On Forecast Evaluation," Borradores de Economia 825, Banco de la Republica de Colombia.
  320. 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.
  321. Stefania D'Amico, 2004. "Density Estimation and Combination under Model Ambiguity," Computing in Economics and Finance 2004 273, Society for Computational Economics.
  322. Gloria González-Rivera & Tae-Hwy Lee, 2007. "Nonlinear Time Series in Financial Forecasting," Working Papers 200803, University of California at Riverside, Department of Economics, revised Feb 2008.
  323. 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.
  324. 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.
  325. 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.
  326. Mariano, Roberto S. & Preve, Daniel, 2012. "Statistical tests for multiple forecast comparison," Journal of Econometrics, Elsevier, vol. 169(1), pages 123-130.
  327. 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.
  328. Brunhes-Lesage, Véronique & Darné, Olivier, 2012. "Nowcasting the French index of industrial production: A comparison from bridge and factor models," Economic Modelling, Elsevier, vol. 29(6), pages 2174-2182.
  329. Lorenzo Boldrini & Eric Hillebrand, 2015. "The Forecasting Power of the Yield Curve, a Supervised Factor Model Approach," CREATES Research Papers 2015-39, Department of Economics and Business Economics, Aarhus University.
  330. 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.
  331. 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.
  332. 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.
  333. repec:ctc:serie1:def10 is not listed on IDEAS
  334. repec:gam:jecnmx:v:4:y:2016:i:1:p:8:d:64253 is not listed on IDEAS
  335. Ibarra, Raul, 2012. "Do disaggregated CPI data improve the accuracy of inflation forecasts?," Economic Modelling, Elsevier, vol. 29(4), pages 1305-1313.
  336. 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.
  337. 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.
  338. Giacomini, Raffaella, 2014. "Economic theory and forecasting: lessons from the literature," CEPR Discussion Papers 10201, C.E.P.R. Discussion Papers.
  339. Veiga, Helena & Ruiz, Esther & Mao, Xiuping, 2013. "One for all : nesting asymmetric stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS ws131110, Universidad Carlos III de Madrid. Departamento de Estadística.
  340. In Choi, 2013. "Model Selection for Factor Analysis: Some New Criteria and Performance Comparisons," Working Papers 1209, Research Institute for Market Economy, Sogang University.
  341. Idrovo Aguirre, Byron & Tejada, Mauricio, 2010. "Modelos de predicción para la inflación de Chile
    [Inflation forecast models for Chile]
    ," MPRA Paper 31586, University Library of Munich, Germany, revised 26 Mar 2010.
  342. 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.
This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.