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Citations for "Comparing Predictive Accuracy"

by Francis X. Diebold & Robert S. Mariano

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  1. Reimers, Hans-Eggert, 2002. "Analysing Divisia Aggregates for the Euro Area," Discussion Paper Series 1: Economic Studies 2002,13, Deutsche Bundesbank, Research Centre.
  2. Awartani, Basel M.A. & Corradi, Valentina, 2005. "Predicting the volatility of the S&P-500 stock index via GARCH models: the role of asymmetries," International Journal of Forecasting, Elsevier, vol. 21(1), pages 167-183.
  3. Lettau, Martin & Ludvigson, Sydney, 1999. "Consumption, Aggregate Wealth and Expected Stock Returns," CEPR Discussion Papers 2223, C.E.P.R. Discussion Papers.
  4. Pablo Pincheira, 2008. "Combining Tests of Predictive Ability Theory and Evidence for Chilean and Canadian Exchange Rates," Working Papers Central Bank of Chile 459, Central Bank of Chile.
  5. Chang, Kuang Liang & Chen, Nan Kuang & Leung, Charles Ka Yui, 2011. "The Dynamics of Housing Returns in Singapore: How Important are the International Transmission Mechanisms?," MPRA Paper 32255, University Library of Munich, Germany.
  6. Raviv, Eran & Bouwman, Kees E. & van Dijk, Dick, 2015. "Forecasting day-ahead electricity prices: Utilizing hourly prices," Energy Economics, Elsevier, vol. 50(C), pages 227-239.
  7. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2016. "Copula--based Specification of vector MEMs," Papers 1604.01338, arXiv.org.
  8. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2011. "Persistence and Cyclical Dependence in the Monthly Euribor Rate," Discussion Papers of DIW Berlin 1165, DIW Berlin, German Institute for Economic Research.
  9. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2010. "Evaluating Macroeconomic Forecasts: A Review of Some Recent Developments," Working Papers in Economics 10/09, University of Canterbury, Department of Economics and Finance.
  10. repec:ipg:wpaper:2014-471 is not listed on IDEAS
  11. Tsyplakov, Alexander, 2014. "Theoretical guidelines for a partially informed forecast examiner," MPRA Paper 55017, University Library of Munich, Germany.
  12. Aastveit, Knut Are & Trovik, Tørres, 2014. "Estimating the output gap in real time: A factor model approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 180-193.
  13. Mark E. Wohar & David E. Rapach, 2007. "Forecasting the recent behavior of US business fixed investment spending: an analysis of competing models This is a significantly revised version of our previous paper, 'Forecasting US Business Fixed ," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(1), pages 33-51.
  14. Chen, Cheng-Wei & Huang, Chin-Sheng & Lai, Hung-Wei, 2009. "The impact of data snooping on the testing of technical analysis: An empirical study of Asian stock markets," Journal of Asian Economics, Elsevier, vol. 20(5), pages 580-591, September.
  15. Rambaccussing, Dooruj, 2009. "Exploiting price misalignements," MPRA Paper 27147, University Library of Munich, Germany.
  16. Arvid Raknerud & Terje Skjerpen & Anders Rygh Swensen, 2003. "A linear demand system within a Seemingly Unrelated Time Series Equation framework," Discussion Papers 345, Statistics Norway, Research Department.
  17. Christensen, Bent Jesper & Raahauge, Peter, 2004. "Latent Utility Shocks in a Structural Empirical Asset Pricing Model," Working Papers 2004-7, Copenhagen Business School, Department of Finance.
  18. 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).
  19. Karen Cabos & Michael Funke & Nikolaus A. Siegfried, 2001. "Some Thoughts on Monetary Targeting vs. Inflation Targeting," German Economic Review, Verein für Socialpolitik, vol. 2(3), pages 219-238, 08.
  20. Sanders, Dwight R. & Manfredo, Mark R., 2003. "USDA Livestock Price Forecasts: A Comprehensive Evaluation," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 28(02), pages -, August.
  21. Lahiani, A. & Scaillet, O., 2009. "Testing for threshold effect in ARFIMA models: Application to US unemployment rate data," International Journal of Forecasting, Elsevier, vol. 25(2), pages 418-428.
  22. Tseng, Tseng-Chan & Lee, Chien-Chiang & Chen, Mei-Ping, 2015. "Volatility forecast of country ETF: The sequential information arrival hypothesis," Economic Modelling, Elsevier, vol. 47(C), pages 228-234.
  23. Jonathan Hambur & Lynne Cockerell & Christopher Potter & Penelope Smith & Michelle Wright, 2015. "Modelling the Australian Dollar," RBA Research Discussion Papers rdp2015-12, Reserve Bank of Australia.
  24. Luis Ceballos S. & Mario González F., 2012. "Indicador de Condiciones Económicas," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 15(1), pages 105-117, April.
  25. Poncela, Pilar & Rodríguez, Julio & Sánchez-Mangas, Rocío & Senra, Eva, 2011. "Forecast combination through dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 27(2), pages 224-237.
  26. 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.
  27. Philip Rothman & Dick van Dijk & Philip Hans Franses, 1999. "A Multivariate STAR Analysis of the Relationship Between Money and Output," Working Papers 9913, East Carolina University, Department of Economics.
  28. Vadim Kufenko & Niels Geiger, 2016. "Business cycles in the economy and in economics: an econometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(1), pages 43-69, April.
  29. Gianluca Cubadda & Barbara Guardabascio & Alain Hecq, 2016. "A Vector Heterogeneous Autoregressive Index Model for Realized Volatily Measures," CEIS Research Paper 391, Tor Vergata University, CEIS, revised 23 Jul 2016.
  30. Carlo Altavilla & Raffaella Giacomini & Riccardo Costantini, 2014. "Bond Returns and Market Expectations," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 12(4), pages 708-729.
  31. Schorfheide, Frank & Sill, Keith & Kryshko, Maxym, 2010. "DSGE model-based forecasting of non-modelled variables," International Journal of Forecasting, Elsevier, vol. 26(2), pages 348-373, April.
  32. Daniel Buncic, 2012. "Understanding forecast failure of ESTAR models of real exchange rates," Empirical Economics, Springer, vol. 43(1), pages 399-426, August.
  33. Danilov, D.L. & Magnus, J.R., 2001. "On the Harm that Pretesting Does," Discussion Paper 2001-37, Tilburg University, Center for Economic Research.
  34. Granger, Clive W. J. & Swanson, Norman R., 1997. "An introduction to stochastic unit-root processes," Journal of Econometrics, Elsevier, vol. 80(1), pages 35-62, September.
  35. Gianluca Cubadda, 2007. "A Reduced Rank Regression Approach to Coincident and Leading Indexes Building," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(2), pages 271-292, 04.
  36. M. Hashem Pesaran & Andreas Pick, 2008. "Forecasting Random Walks Under Drift Instability," CESifo Working Paper Series 2293, CESifo Group Munich.
  37. Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2012. "The Out-of-Sample Forecasting Performance of Non-Linear Models of Regional Housing Prices in the US," Working Papers 15-27, Eastern Mediterranean University, Department of Economics.
  38. 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.
  39. Heij, C. & van Dijk, D.J.C. & Groenen, P.J.F., 2006. "Improved Construction of diffusion indexes for macroeconomic forecasting," Econometric Institute Research Papers EI 2006-03-REV, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  40. Junko Koeda, 2012. "How does yield curve predict GDP growth? A macro-finance approach revisited," Applied Economics Letters, Taylor & Francis Journals, vol. 19(10), pages 929-933, July.
  41. Clark, Todd E. & McCracken, Michael W., 2005. "The power of tests of predictive ability in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 124(1), pages 1-31, January.
  42. Hansson, Jesper & Jansson, Per & Lof, Marten, 2005. "Business survey data: Do they help in forecasting GDP growth?," International Journal of Forecasting, Elsevier, vol. 21(2), pages 377-389.
  43. Ahoniemi, Katja & Lanne, Markku, 2009. "Joint modeling of call and put implied volatility," International Journal of Forecasting, Elsevier, vol. 25(2), pages 239-258.
  44. Murat Midilic, 2016. "Estimation Of Star-Garch Models With Iteratively Weighted Least Squares," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 16/918, Ghent University, Faculty of Economics and Business Administration.
  45. Sarantis, Nicholas, 2006. "On the short-term predictability of exchange rates: A BVAR time-varying parameters approach," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2257-2279, August.
  46. Rangan Gupta & Mampho P. Modise & Josine Uwilingiye, 2011. "Out-of-Sample Equity Premium Predictability in South Africa: Evidence from a Large Number of Predictors," Working Papers 201122, University of Pretoria, Department of Economics.
  47. Trino-Manuel Niguez & Javier Perote, 2004. "Forecasting the density of asset returns," STICERD - Econometrics Paper Series 479, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  48. Peter F. Christoffersen & Francis X. Diebold, 1997. "Optimal prediction under asymmetric loss," Working Papers 97-11, Federal Reserve Bank of Philadelphia.
  49. Henrik Amilon, 2003. "A neural network versus Black-Scholes: a comparison of pricing and hedging performances," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(4), pages 317-335.
  50. Valentina Corradi & Norman Swanson, 2004. "Bootstrap Procedures for Recursive Estimation Schemes With Applications to Forecast Model Selection," Departmental Working Papers 200418, Rutgers University, Department of Economics.
  51. Barrera, Carlos R., 2010. "Redes neuronales para predecir el tipo de cambio diario," Working Papers 2010-001, Banco Central de Reserva del Perú.
  52. Smith Paul, 2016. "Nowcasting UK GDP during the depression," Working Papers 1606, University of Strathclyde Business School, Department of Economics.
  53. Ana Sequeira, 2013. "Predicting aggregate returns using valuation ratios out-of-sample," Economic Bulletin and Financial Stability Report Articles, Banco de Portugal, Economics and Research Department.
  54. Cerrato, Mario & Kim, Hyunsok & MacDonald, Ronald, 2010. "Microstructure Order Flow: Statistical and Economic Evaluation of Nonlinear Forecasts," SIRE Discussion Papers 2010-107, Scottish Institute for Research in Economics (SIRE).
  55. Hilde C. Bjørnland & Leif Brubakk & Anne Sofie Jore, 2006. "Forecasting inflation with an uncertain output gap," Working Paper 2006/02, Norges Bank.
  56. Carlos Fonseca Marinheiro, 2010. "Fiscal sustainability and the accuracy of macroeconomic forecasts: do supranational forecasts rather than government forecasts make a difference?," GEMF Working Papers 2010-07, GEMF - Faculdade de Economia, Universidade de Coimbra.
  57. Fernandes, Marcelo & Medeiros, Marcelo C. & Scharth, Marcel, 2014. "Modeling and predicting the CBOE market volatility index," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 1-10.
  58. Sasa Zikovic & Rafal Weron & Ivana Tomas Zikovic, 2014. "Evaluating the performance of VaR models in energy markets," HSC Research Reports HSC/14/12, Hugo Steinhaus Center, Wroclaw University of Technology.
  59. O. De Bandt & E. Michaux & C. Bruneau & A. Flageollet, 2007. "Forecasting inflation using economic indicators: the case of France," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(1), pages 1-22.
  60. Pierre L. Siklos, 2016. "Forecast Disagreement and the Inflation Outlook: New International Evidence," IMES Discussion Paper Series 16-E-03, Institute for Monetary and Economic Studies, Bank of Japan.
  61. Asai, M. & McAleer, M.J., 2015. "The Impact of Jumps and Leverage in Forecasting Co-Volatility," Econometric Institute Research Papers EI 2015-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  62. Leandro Maciel, 2012. "A Hybrid Fuzzy GJR-GARCH Modeling Approach for Stock Market Volatility Forecasting," Brazilian Review of Finance, Brazilian Society of Finance, vol. 10(3), pages 337-367.
  63. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
  64. Campa, Jose Manuel & Chang, P. H. Kevin, 1998. "The forecasting ability of correlations implied in foreign exchange options," Journal of International Money and Finance, Elsevier, vol. 17(6), pages 855-880, December.
  65. Jari Hännikäinen, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," Working Papers 1603, University of Tampere, School of Management, Economics.
  66. Pablo Pincheira & Mauricio Calani, 2009. "Communicational Bias In Monetary Policy: Can Words Forecast Deeds?," Working Papers Central Bank of Chile 526, Central Bank of Chile.
  67. Ana Angulo & F. Trívez, 2010. "The impact of spatial elements on the forecasting of Spanish labour series," Journal of Geographical Systems, Springer, vol. 12(2), pages 155-174, June.
  68. Wang, Yudong & Zhang, Bing & Diao, Xundi & Wu, Chongfeng, 2015. "Commodity price changes and the predictability of economic policy uncertainty," Economics Letters, Elsevier, vol. 127(C), pages 39-42.
  69. 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.
  70. Goncalves, Silvia & McCracken, Michael W. & Perron, Benoit, 2015. "Tests of Equal Accuracy for Nested Models with Estimated Factors," Working Papers 2015-25, Federal Reserve Bank of St. Louis, revised 29 Aug 2016.
  71. Szabolcs Blazsek & Anna Downarowicz, 2013. "Forecasting hedge fund volatility: a Markov regime-switching approach," The European Journal of Finance, Taylor & Francis Journals, vol. 19(4), pages 243-275, April.
  72. Jozef Baruník, 2008. "How Do Neural Networks Enhance the Predictability of Central European Stock Returns?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 58(07-08), pages 358-376, Oktober.
  73. COSMA, Antonio & GALLI, Fausto, 2006. "A nonparametric ACD model," CORE Discussion Papers 2006067, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  74. Matheson, Troy D, 2006. "Factor Model Forecasts for New Zealand," MPRA Paper 807, University Library of Munich, Germany.
  75. Christian Huurman & Francesco Ravazzolo & Chen Zhou, 2007. "The Power of Weather: Some Empirical Evidence on Predicting Day-ahead Power Prices through Day-ahead Weather Forecasts," Tinbergen Institute Discussion Papers 07-036/4, Tinbergen Institute.
  76. Wang, Shuai & Yu, Lean & Tang, Ling & Wang, Shouyang, 2011. "A novel seasonal decomposition based least squares support vector regression ensemble learning approach for hydropower consumption forecasting in China," Energy, Elsevier, vol. 36(11), pages 6542-6554.
  77. Ruthira Naraidoo & Ivan Paya, 2010. "Forecasting Monetary Rules in South Africa," Working Papers 201007, University of Pretoria, Department of Economics.
  78. Zagaglia, Paolo, 2006. "Does the Yield Spread Predict the Output Gap in the U.S.?," Research Papers in Economics 2006:5, Stockholm University, Department of Economics.
  79. Steffen Henzel, 2008. "Learning Trend Inflation – Can Signal Extraction Explain Survey Forecasts?," Ifo Working Paper Series Ifo Working Paper No. 55, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  80. Liping Gao & Hyeongwoo Kim, 2015. "Testing the Predictability of Consumption Growth: Evidence from China," Auburn Economics Working Paper Series auwp2015-19, Department of Economics, Auburn University.
  81. Oscar Claveria & Enric Monte & Salvador Torra, 2016. "Modelling cross-dependencies between Spain’s regional tourism markets with an extension of the Gaussian process regression model," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 7(3), pages 341-357, August.
  82. Chalamandaris, Georgios & Rompolis, Leonidas S., 2012. "Exploring the role of the realized return distribution in the formation of the implied volatility smile," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1028-1044.
  83. Maurício Yoshinori Une & Marcelo Savino Portugal, 2005. "Can fear beat hope? A story of GARCH-in-Mean-Level effects for Emerging Market Country Risks," Econometrics 0509006, EconWPA.
  84. Roberto Savona & Marika Vezzoli, 2012. "Fitting and Forecasting Sovereign Defaults Using Multiple Risk Signals," Working Papers 2012_26, Department of Economics, University of Venice "Ca' Foscari".
  85. Lorenzo, Fernando & Ruiz, Esther, 1996. "Which univariate time series model predicts quicker a crisis? The Iberia case," DES - Working Papers. Statistics and Econometrics. WS 4545, Universidad Carlos III de Madrid. Departamento de Estadística.
  86. Francisco Javier Eransus & Alfonso Novales Cinca, 2014. "Parameter Estimation Error in Tests of Predictive Performance under Discrete Loss Functions," Documentos de Trabajo del ICAE 2014-22, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  87. Cheng-Wen Lee & Bing-Yi Lin, 2016. "Application of Hybrid Quantum Tabu Search with Support Vector Regression (SVR) for Load Forecasting," Energies, MDPI, Open Access Journal, vol. 9(11), pages 873, October.
  88. Pedro N. Rodríguez, & Simón Sosvilla-Rivero, 2006. "Forecasting Stock Price Changes: Is it Possible?," Working Papers 2006-22, FEDEA.
  89. Lahiri, Kajal & Yang, Liu, 2016. "Asymptotic variance of Brier (skill) score in the presence of serial correlation," Economics Letters, Elsevier, vol. 141(C), pages 125-129.
  90. 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.
  91. Zhu, Xiaoneng & Rahman, Shahidur, 2015. "A regime-switching Nelson–Siegel term structure model of the macroeconomy," Journal of Macroeconomics, Elsevier, vol. 44(C), pages 1-17.
  92. Andre Lucas & Anne Opschoor, 2016. "Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns," Tinbergen Institute Discussion Papers 16-069/IV, Tinbergen Institute.
  93. Mizen, Paul & Tsoukas, Serafeim, 2011. "Forecasting US bond default ratings allowing for previous and initial state dependence in an ordered probit model," SIRE Discussion Papers 2011-69, Scottish Institute for Research in Economics (SIRE).
  94. Grégory Levieuge & Christophe Blot, 2008. "Are MCIs Good Indicators of Economic Activity ? Evidence from the G7 Countries," Sciences Po publications 2008-07, Sciences Po.
  95. Thomas Lux & Leonardo Morales-Arias, 2009. "Forecasting Volatility under Fractality, Regime-Switching, Long Memory and Student-t Innovations," Kiel Working Papers 1532, Kiel Institute for the World Economy.
  96. Avdulaj, Krenar & Barunik, Jozef, 2015. "Are benefits from oil-stocks diversification gone? New evidence from a dynamic copula and high frequency data," FinMaP-Working Papers 32, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
  97. Martyna Marczak & Tommaso Proietti, 2014. "Outlier Detection in Structural Time Series Models: the Indicator Saturation Approach," CEIS Research Paper 325, Tor Vergata University, CEIS, revised 08 Aug 2014.
  98. Taufiq Choudhry & Hao Wu, 2008. "Forecasting ability of GARCH vs Kalman filter method: evidence from daily UK time-varying beta," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 670-689.
  99. Caporin, Massimiliano & McAleer, Michael, 2014. "Robust ranking of multivariate GARCH models by problem dimension," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 172-185.
  100. Anthony Garratt & Gary Koop & Emi Mise & Shaun P Vahey, 2007. "Real-time Prediction with UK Monetary Aggregates in the Presence of Model Uncertainty," Birkbeck Working Papers in Economics and Finance 0714, Birkbeck, Department of Economics, Mathematics & Statistics.
  101. Yang, Zihui & Zhao, Yongliang, 2014. "Energy consumption, carbon emissions, and economic growth in India: Evidence from directed acyclic graphs," Economic Modelling, Elsevier, vol. 38(C), pages 533-540.
  102. Norman R. Swanson & Valentina Corradi, 2011. "Predictive Density Construction and Accuracy Testing with Multiple Possibly Misspecified Diffusion Models," Departmental Working Papers 201112, Rutgers University, Department of Economics.
  103. Leo Krippner, 2006. "A Theoretically Consistent Version of the Nelson and Siegel Class of Yield Curve Models," Applied Mathematical Finance, Taylor & Francis Journals, vol. 13(1), pages 39-59.
  104. repec:onb:oenbwp:y::i:91:b:1 is not listed on IDEAS
  105. Norman Swanson & Nii Ayi Armah, 2006. "Predictive Inference Under Model Misspecification with an Application to Assessing the Marginal Predictive Content of Money for Output," Departmental Working Papers 200619, Rutgers University, Department of Economics.
  106. 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.
  107. Amstad, Marlene & Fischer, Andreas M, 2004. "Sequential Information Flow and Real-Time Diagnosis of Swiss Inflation: Intra-Monthly DCF Estimates for a Low-Inflation Environment," CEPR Discussion Papers 4627, C.E.P.R. Discussion Papers.
  108. Dr. Ibrahim Onour, . "The Global Financial Crisis and Equity Markets in Middle East Oil Exporting Countries," API-Working Paper Series 1009, Arab Planning Institute - Kuwait, Information Center.
  109. Gabriel E. Lade & C.Y. Cynthia Lin Lawell & Aaron Smith, 2016. "Policy Shocks and Market-Based Regulations: Evidence from the Renewable Fuel Standard," Center for Agricultural and Rural Development (CARD) Publications 16-wp565, Center for Agricultural and Rural Development (CARD) at Iowa State University.
  110. Gloria Gonzalez-Rivera & Javier Arroyo & Carlos Mate, 2011. "Forecasting with Interval and Histogram Data. Some Financial Applications," Working Papers 201438, University of California at Riverside, Department of Economics.
  111. Peter Fuleky & Carl S. Bonham, 2013. "Forecasting with Mixed Frequency Samples: The Case of Common Trends," Working Papers 201316, University of Hawaii at Manoa, Department of Economics.
  112. Jungjin Lee & Abdul d Abiad & Prakash Kannan, 2009. "Evaluating Historical CGER Assessments; How Well Have They Predicted Subsequent Exchange Rate Movements?," IMF Working Papers 09/32, International Monetary Fund.
  113. Nikolay Robinzonov & Gerhard Tutz & Torsten Hothorn, 2012. "Boosting techniques for nonlinear time series models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(1), pages 99-122, January.
  114. Götz Thomas & Hecq Alain & Urbain Jean-Pierre, 2012. "Forecasting Mixed Frequency Time Series with ECM-MIDAS Models," Research Memorandum 012, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
  115. Andrew Rennison, 2003. "Comparing Alternative Output-Gap Estimators: A Monte Carlo Approach," Staff Working Papers 03-8, Bank of Canada.
  116. Baumeister, Christiane & Kilian, Lutz, 2014. "A General Approach to Recovering Market Expectations from Futures Prices With an Application to Crude Oil," CEPR Discussion Papers 10162, C.E.P.R. Discussion Papers.
  117. Philip Hans Franses & Namwon Hyung, 2005. "Forecasting time series with long memory and level shifts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(1), pages 1-16.
  118. Preve, Daniel, 2015. "Linear programming-based estimators in nonnegative autoregression," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages S225-S234.
  119. Wong, Woon K. & Tu, Anthony H., 2009. "Market imperfections and the information content of implied and realized volatility," Pacific-Basin Finance Journal, Elsevier, vol. 17(1), pages 58-79, January.
  120. Marco Shinobu Matsumura & Ajax Reynaldo Bello Moreira & José Valentim Machado Vicente, 2010. "Forecasting the Yield Curve with Linear Factor Models," Working Papers Series 223, Central Bank of Brazil, Research Department.
  121. Jean-Philippe Cayen & Simon van Norden, 2002. "La fiabilité des estimations de l'écart de production au Canada," Staff Working Papers 02-10, Bank of Canada.
  122. Eleni Constantinou & Robert Georgiades & Avo Kazandjian & George Kouretas, 2005. "Regime Switching and Artificial Neural Network Forecasting," Working Papers 0502, University of Crete, Department of Economics.
  123. Hindrayanto, Irma & Koopman, Siem Jan & Ooms, Marius, 2010. "Exact maximum likelihood estimation for non-stationary periodic time series models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2641-2654, November.
  124. Swanson, N.R. & White, H., 1995. "A Models Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks," Papers 04-95-12, Pennsylvania State - Department of Economics.
  125. Fabio Rumler & Maria Teresa Valderrama, 2008. "Comparing the New Keynesian Phillips Curve with Time Series Models to Forecast Inflation," Working Papers 148, Oesterreichische Nationalbank (Austrian Central Bank).
  126. Sébastien Laurent & Jeroen V.K. Rombouts & Francesco Violante, 2010. "On the Forecasting Accuracy of Multivariate GARCH Models," Cahiers de recherche 1021, CIRPEE.
  127. repec:dau:papers:123456789/13532 is not listed on IDEAS
  128. esposito, francesco paolo & cummins, mark, 2015. "Multiple hypothesis testing of market risk forecasting models," MPRA Paper 64986, University Library of Munich, Germany.
  129. Lv, Xiaodong & Shan, Xian, 2013. "Modeling natural gas market volatility using GARCH with different distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5685-5699.
  130. Erik Snowberg & Justin Wolfers & Eric Zitzewitz, 2012. "Prediction Markets for Economic Forecasting," CAMA Working Papers 2012-33, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  131. Forni, Mario & Giovannelli, Alessandro & Lippi, Marco & Soccorsi, Stefano, 2016. "Dynamic Factor model with infinite dimensional factor space: forecasting," CEPR Discussion Papers 11161, C.E.P.R. Discussion Papers.
  132. Argyropoulos Efthymios & Tzavalis Elias, 2015. "Term spread regressions of the rational expectations hypothesis of the term structure allowing for risk premium effects," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(1), pages 49-70, February.
  133. Francis X. Diebold, 2012. "Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests," PIER Working Paper Archive 12-035, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  134. Kilian, Lutz & Taylor, Mark P., 2003. "Why is it so difficult to beat the random walk forecast of exchange rates?," Journal of International Economics, Elsevier, vol. 60(1), pages 85-107, May.
  135. Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2014. "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers 9848, C.E.P.R. Discussion Papers.
  136. Hilde C. Bjørnland & Karsten Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2012. "Does Forecast Combination Improve Norges Bank Inflation Forecasts?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(2), pages 163-179, 04.
  137. 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.
  138. Jean-Stéphane MESONNIER, 2007. "The predictive content of the real interest rate gap for macroeconomic variables in the euro area," Money Macro and Finance (MMF) Research Group Conference 2006 102, Money Macro and Finance Research Group.
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  1375. Lehmann, Robert & Weyh, Antje, 2015. "Forecasting employment in Europe: Are survey results helpful?," IAB Discussion Paper 201530, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  1376. 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.
  1377. Lees, Kirdan & Matheson, Troy & Smith, Christie, 2011. "Open economy forecasting with a DSGE-VAR: Head to head with the RBNZ published forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 512-528, April.
  1378. Moreno, David & Olmeda, Ignacio, 2007. "Is the predictability of emerging and developed stock markets really exploitable?," European Journal of Operational Research, Elsevier, vol. 182(1), pages 436-454, October.
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  1380. Norman R. Swanson, 2000. "An Out of Sample Test for Granger Causality," Econometric Society World Congress 2000 Contributed Papers 0362, Econometric Society.
  1381. Angelos Kanas & Yue Ma, 2004. "Intrinsic bubbles revisited: evidence from nonlinear cointegration and forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(4), pages 237-250.
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