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Citations for "A Model Selection Approach To Real-Time Macroeconomic Forecasting Using Linear Models And Artificial Neural Networks"

by Norman R. Swanson & Halbert White

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  1. 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.
  2. Mototsugu Shintani, 2003. "Nonlinear Forecasting Analysis Using Diffusion Indexes: An Application to Japan," Vanderbilt University Department of Economics Working Papers 0322, Vanderbilt University Department of Economics, revised Apr 2004.
  3. Marcellino, Massimiliano, 2002. "Instability and Non-Linearity in the EMU," CEPR Discussion Papers 3312, C.E.P.R. Discussion Papers.
  4. Geetesh Bhardwaj & Norman Swanson, 2004. "An Empirical Investigation of the Usefulness of ARFIMA Models for Predicting Macroeconomic and Financial Time Series," Departmental Working Papers 200422, Rutgers University, Department of Economics.
  5. Michael H. Breitner & Christian Dunis & Hans-Jörg Mettenheim & Christopher Neely & Georgios Sermpinis & Georgios Sermpinis & Charalampos Stasinakis & Konstantinos Theofilatos & Andreas Karathanasopoul, 2014. "Inflation and Unemployment Forecasting with Genetic Support Vector Regression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(6), pages 471-487, 09.
  6. Malik, Farooq & Nasereddin, Mahdi, 2006. "Forecasting output using oil prices: A cascaded artificial neural network approach," Journal of Economics and Business, Elsevier, vol. 58(2), pages 168-180.
  7. Yang, Jian & Su, Xiaojing & Kolari, James W., 2008. "Do Euro exchange rates follow a martingale? Some out-of-sample evidence," Journal of Banking & Finance, Elsevier, vol. 32(5), pages 729-740, May.
  8. Ferland, Rene & Lalancette, Simon, 2006. "Dynamics of realized volatilities and correlations: An empirical study," Journal of Banking & Finance, Elsevier, vol. 30(7), pages 2109-2130, July.
  9. 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.
  10. Roberto Patuelli & Aura Reggiani & Peter Nijkamp & Uwe Blien, 2006. "New Neural Network Methods for Forecasting Regional Employment: An Analysis of German Labour Markets," Tinbergen Institute Discussion Papers 06-020/3, Tinbergen Institute.
  11. Khurshid M. KIANI & Terry L. KASTENS, 2006. "Using Macro-Financial Variables To Forecast Recessions. An Analysis Of Canada, 1957-2002," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 6(3).
  12. Zhou, Jian, 2016. "Hedging performance of REIT index futures: A comparison of alternative hedge ratio estimation methods," Economic Modelling, Elsevier, vol. 52(PB), pages 690-698.
  13. Wang, Tao & Yang, Jian, 2010. "Nonlinearity and intraday efficiency tests on energy futures markets," Energy Economics, Elsevier, vol. 32(2), pages 496-503, March.
  14. Yvon Fauvel & Alain Paquet & Christian Zimmermann, 1999. "A Survey on Interest Rate Forecasting," Cahiers de recherche CREFE / CREFE Working Papers 87, CREFE, Université du Québec à Montréal.
  15. Roberto Patuelli & Simonetta Longhi & Aura Reggiani & Peter Nijkamp, 2005. "Forecasting Regional Employment in Germany by Means of Neural Networks and Genetic Algorithms," Computational Economics 0511002, EconWPA.
  16. Medeiros, Marcelo C. & Teräsvirta, Timo & Rech, Gianluigi, 2002. "Building neural network models for time series: A statistical approach," SSE/EFI Working Paper Series in Economics and Finance 508, Stockholm School of Economics.
  17. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
  18. Koenig, Evan F. & Dolmas, Sheila & Piger, Jeremy M., 2000. "The use and abuse of "real-time" data in economic forecasting," Working Papers 0004, Federal Reserve Bank of Dallas.
  19. Khurshid Kiani & Terry Kastens, 2008. "Testing Forecast Accuracy of Foreign Exchange Rates: Predictions from Feed Forward and Various Recurrent Neural Network Architectures," Computational Economics, Springer;Society for Computational Economics, vol. 32(4), pages 383-406, November.
  20. Christoffersen, Peter & Ghysels, Eric & Swanson, Norman R., 2002. "Let's get "real" about using economic data," Journal of Empirical Finance, Elsevier, vol. 9(3), pages 343-360, August.
  21. Yang, Jian & Cabrera, Juan & Wang, Tao, 2010. "Nonlinearity, data-snooping, and stock index ETF return predictability," European Journal of Operational Research, Elsevier, vol. 200(2), pages 498-507, January.
  22. Marcellino, Massimliano, 2004. "Forecasting EMU macroeconomic variables," International Journal of Forecasting, Elsevier, vol. 20(2), pages 359-372.
  23. Ali Choudhary & Adnan Haider, 2008. "Neural Network Models for Inflation Forecasting: An Appraisal," School of Economics Discussion Papers 0808, School of Economics, University of Surrey.
  24. Ülengin, Füsun & Kabak, Özgür & Önsel, Sule & Aktas, Emel & Parker, Barnett R., 2011. "The competitiveness of nations and implications for human development," Socio-Economic Planning Sciences, Elsevier, vol. 45(1), pages 16-27, March.
  25. Eric Ghysels & Norman R. Swanson & Myles Callan, 2002. "Monetary Policy Rules with Model and Data Uncertainty," Southern Economic Journal, Southern Economic Association, vol. 69(2), pages 239-265, October.
  26. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, Elsevier.
  27. Todd E. Clark & Michael McCracken, 1999. "Tests of Equal Forecast Accuracy and Encompassing for Nested Models," Computing in Economics and Finance 1999 1241, Society for Computational Economics.
  28. Qin, Ting & Enders, Walter, 2008. "In-sample and out-of-sample properties of linear and nonlinear Taylor rules," Journal of Macroeconomics, Elsevier, vol. 30(1), pages 428-443, March.
  29. Laura Brown & Saeed Moshiri, 2004. "Unemployment variation over the business cycles: a comparison of forecasting models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(7), pages 497-511.
  30. Anders Bredahl Kock & Timo Teräsvirta, 2010. "Forecasting with nonlinear time series models," CREATES Research Papers 2010-01, Department of Economics and Business Economics, Aarhus University.
  31. Low, Rand Kwong Yew & Alcock, Jamie & Faff, Robert & Brailsford, Timothy, 2013. "Canonical vine copulas in the context of modern portfolio management: Are they worth it?," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3085-3099.
  32. Golinelli, Roberto & Parigi, Giuseppe, 2014. "Tracking world trade and GDP in real time," International Journal of Forecasting, Elsevier, vol. 30(4), pages 847-862.
  33. Kiani, Khurshid M., 2016. "On business cycle fluctuations in USA macroeconomic time series," Economic Modelling, Elsevier, vol. 53(C), pages 179-186.
  34. Thomas Flavin & Ekaterini Panopoulou & Theologos Pantelidis, 2009. "Forecasting growth and inflation in an enlarged euro area," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(5), pages 405-425.
  35. Marcos Álvarez-Díaz & Rangan Gupta, 2015. "Forecasting the US CPI: Does Nonlinearity Matter?," Working Papers 201512, University of Pretoria, Department of Economics.
  36. Dean Croushore, 2008. "Frontiers of real-time data analysis," Working Papers 08-4, Federal Reserve Bank of Philadelphia.
  37. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415, Junio.
  38. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
  39. Farzan Aminian & E. Suarez & Mehran Aminian & Daniel Walz, 2006. "Forecasting Economic Data with Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 28(1), pages 71-88, August.
  40. Kajal Lahiri & Liu Yang, 2012. "Forecasting Binary Outcomes," Discussion Papers 12-09, University at Albany, SUNY, Department of Economics.
  41. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2010. "Forecasting Nevada Gross Gaming Revenue and Taxable Sales Using Coincident and Leading Employment Indexes," Working Papers 201018, University of Pretoria, Department of Economics.
  42. Andrew J. Patton, 2004. "On the Out-of-Sample Importance of Skewness and Asymmetric Dependence for Asset Allocation," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(1), pages 130-168.
  43. Zhang, Mingzhu & He, Changzheng & Gu, Xin & Liatsis, Panos & Zhu, Bing, 2013. "D-GMDH: A novel inductive modelling approach in the forecasting of the industrial economy," Economic Modelling, Elsevier, vol. 30(C), pages 514-520.
  44. Michael Cooper & Huseyin Gulen, 2006. "Is Time-Series-Based Predictability Evident in Real Time?," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1263-1292, May.
  45. Saman, Corina, 2011. "Scenarios of the Romanian GDP Evolution With Neural Models," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 129-140, December.
  46. James H. Stock & Mark W. Watson, 1998. "A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series," NBER Working Papers 6607, National Bureau of Economic Research, Inc.
  47. Chung-Ming Kuan, 2006. "Artificial Neural Networks," IEAS Working Paper : academic research 06-A010, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  48. Chen Zhuo & Yang Yuhong, 2007. "Time Series Models for Forecasting: Testing or Combining?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 11(1), pages 56-90, March.
  49. Norman Swanson & Valentina Corradi, 2006. "Nonparametric Bootstrap Procedures for Predictive Inference Based on Recursive Estimation Schemes," Departmental Working Papers 200618, Rutgers University, Department of Economics.
  50. Juan Reboredo & José Matías & Raquel Garcia-Rubio, 2012. "Nonlinearity in Forecasting of High-Frequency Stock Returns," Computational Economics, Springer;Society for Computational Economics, vol. 40(3), pages 245-264, October.
  51. María Clara Aristizábal Restrepo, . "Evaluación asimétrica de una red neuronal artificial:Aplicación al caso de la inflación en Colombia," Borradores de Economia 377, Banco de la Republica de Colombia.
  52. John C. Robertson & Ellis W. Tallman, 1998. "Data vintages and measuring forecast model performance," Economic Review, Federal Reserve Bank of Atlanta, issue Q 4, pages 4-20.
  53. Zhou, Jian, 2014. "Modeling conditional covariance for mixed-asset portfolios," Economic Modelling, Elsevier, vol. 40(C), pages 242-249.
  54. repec:dgr:uvatin:20060020 is not listed on IDEAS
  55. Dean Croushore & Tom Stark, 2000. "A real-time data set for macroeconomists: does data vintage matter for forecasting?," Working Papers 00-6, Federal Reserve Bank of Philadelphia.
  56. Valentina Corradi & Norman Swanson, 2003. "The Block Bootstrap for Parameter Estimation Error In Recursive Estimation Schemes, With Applications to Predictive Evaluation," Departmental Working Papers 200313, Rutgers University, Department of Economics.
  57. Hui Feng, 2005. "Real-Time or Current Vintage: Does the Type of Data Matter for Forecasting and Model Selection?," Econometrics Working Papers 0515, Department of Economics, University of Victoria.
  58. Kock, Anders Bredahl & Teräsvirta, Timo, 2014. "Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009," International Journal of Forecasting, Elsevier, vol. 30(3), pages 616-631.
  59. Lance J. Bachmeier & Norman R. Swanson, 2005. "Predicting Inflation: Does The Quantity Theory Help?," Economic Inquiry, Western Economic Association International, vol. 43(3), pages 570-585, July.
  60. Longhi, Simonetta & Nijkamp, Peter, 2006. "Forecasting regional labor market developments under spatial heterogeneity and spatial correlation," Serie Research Memoranda 0015, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
  61. Tom Stark & Dean Croushore, 2001. "Forecasting with a real-time data set for macroeconomists," Working Papers 01-10, Federal Reserve Bank of Philadelphia.
  62. Kala Krishna & Ataman Ozyildirim & Norman R. Swanson, 1998. "Trade, Investment, and Growth: Nexus, Analysis, and Prognosis," NBER Working Papers 6861, National Bureau of Economic Research, Inc.
  63. Bildirici, Melike & Alp, Aykaç, 2008. "The Relationship Between Wages and Productivity: TAR Unit Root and TAR Cointegration Approach," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 5(1), pages 93-110.
  64. 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.
  65. Hassani, Hossein & Heravi, Saeed & Zhigljavsky, Anatoly, 2009. "Forecasting European industrial production with singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 25(1), pages 103-118.
  66. Landajo, Manuel & de Andres, Javier & Lorca, Pedro, 2007. "Robust neural modeling for the cross-sectional analysis of accounting information," European Journal of Operational Research, Elsevier, vol. 177(2), pages 1232-1252, March.
  67. Andreas Karatahansopoulos & Georgios Sermpinis & Jason Laws & Christian Dunis, 2014. "Modelling and Trading the Greek Stock Market with Gene Expression and Genetic Programing Algorithms," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(8), pages 596-610, December.
  68. Kiani, K.M., 2009. "Neural Networks to Detect Nonlinearities in Time Series: Analysis of Business Cycle in France and the United Kingdom," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 9(1).
  69. 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.
  70. Oliver Blaskowitz & Helmut Herwartz, 2009. "Adaptive forecasting of the EURIBOR swap term structure," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(7), pages 575-594.
  71. Massimiliano Marcellino, 2008. "A linear benchmark for forecasting GDP growth and inflation?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(4), pages 305-340.
  72. Tkacz, Greg & Hu, Sarah, 1999. "Forecasting GDP Growth Using Artificial Neural Networks," Staff Working Papers 99-3, Bank of Canada.
  73. Qi, Min & Zhang, Guoqiang Peter, 2001. "An investigation of model selection criteria for neural network time series forecasting," European Journal of Operational Research, Elsevier, vol. 132(3), pages 666-680, August.
  74. Massimiliano Marcellino, . "Forecast pooling for short time series of macroeconomic variables," Working Papers 212, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  75. Heravi, Saeed & Osborn, Denise R. & Birchenhall, C. R., 2004. "Linear versus neural network forecasts for European industrial production series," International Journal of Forecasting, Elsevier, vol. 20(3), pages 435-446.
  76. Gustavo A. Marrero, 2007. "Traditional versus unobserved components methods to forecast quarterly national account aggregates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(2), pages 129-153.
  77. Simonetta Longhi & Peter Nijkamp, 2005. "Forecasting Regional Labour Market Developments Under Spatial Heterogeneity and Spatial Autocorrelation," Tinbergen Institute Discussion Papers 05-041/3, Tinbergen Institute.
  78. Oliver Blaskowitz & Helmut Herwartz, 2008. "Testing directional forecast value in the presence of serial correlation," SFB 649 Discussion Papers SFB649DP2008-073, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  79. Golinelli, Roberto & Parigi, Giuseppe, 2005. "Short-Run Italian GDP Forecasting and Real-Time Data," CEPR Discussion Papers 5302, C.E.P.R. Discussion Papers.
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