IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!)

Citations for "Selection of estimation window in the presence of breaks"

by Pesaran, M. Hashem & Timmermann, Allan

For a complete description of this item, click here. For a RSS feed for citations of this item, click here.
as
in new window

  1. Brandon J. Bates & Mikkel Plagborg-Møller & James H. Stock & Mark W. Watson, "undated". "Consistent factor estimation in dynamic factor models with structural instability," Working Paper 84631, Harvard University OpenScholar.
  2. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
  3. Carlo Altavilla & Matteo Ciccarelli, 2011. "Monetary Policy Analysis in Real-Time. Vintage Combination from a Real-Time Dataset," CESifo Working Paper Series 3372, CESifo Group Munich.
  4. Campa, Jose Manuel & Gavilan, Angel, 2011. "Current accounts in the euro area: An intertemporal approach," Journal of International Money and Finance, Elsevier, vol. 30(1), pages 205-228, February.
  5. Christophe Boucher & Bertrand Maillet, 2012. "Prévoir sans persistance," Post-Print hal-01386006, HAL.
  6. Agnieszka Markiewicz & Andreas Pick, 2013. "Adaptive Learning and Survey Data," CDMA Working Paper Series 201305, Centre for Dynamic Macroeconomic Analysis.
  7. Fabian Baetje & Lukas Menkhoff, 2016. "Equity Premium Prediction: Are Economic and Technical Indicators Unstable?," Discussion Papers of DIW Berlin 1552, DIW Berlin, German Institute for Economic Research.
  8. Ke Yang & Langnan Chen & Fengping Tian, 2015. "Realized Volatility Forecast of Stock Index Under Structural Breaks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(1), pages 57-82, 01.
  9. 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.
  10. Tian, Jing & Anderson, Heather M., 2014. "Forecast combinations under structural break uncertainty," International Journal of Forecasting, Elsevier, vol. 30(1), pages 161-175.
  11. Hansen, Bruce E., 2010. "Averaging estimators for autoregressions with a near unit root," Journal of Econometrics, Elsevier, vol. 158(1), pages 142-155, September.
  12. Do, Linh Phuong Catherine & Lin, Kuan-Heng & Molnár, Peter, 2016. "Electricity consumption modelling: A case of Germany," Economic Modelling, Elsevier, vol. 55(C), pages 92-101.
  13. M. Hashem Pesaran & Til Schuermann & L. Vanessa Smith, 2008. "Forecasting economic and financial variables with global VARs," Staff Reports 317, Federal Reserve Bank of New York.
  14. Jing Tian & Heather M. Anderson, 2011. "Forecasting Under Strucural Break Uncertainty," Monash Econometrics and Business Statistics Working Papers 8/11, Monash University, Department of Econometrics and Business Statistics.
  15. 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.
  16. Erhard Reschenhofer, 2010. "Forecasting volatility: double averaging and weighted medians," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 1(3/4), pages 317-326.
  17. John M. Maheu & Stephen Gordon, 2004. "Learning, Forecasting and Structural Breaks," Cahiers de recherche 0422, CIRPEE.
  18. repec:oxf:wpaper:2013-w04 is not listed on IDEAS
  19. Juraj Hucek & Alexander Karsay & Marian Vavra, 2015. "Short-term Forecasting of Real GDP Using Monthly Data," Working and Discussion Papers OP 1/2015, Research Department, National Bank of Slovakia.
  20. Tim Bollerslev & Andrew J. Patton & Wenjing Wang, 2016. "Daily House Price Indices: Construction, Modeling, and Longer‐run Predictions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(6), pages 1005-1025, 09.
  21. Wang, Cindy Shin-Huei & Bauwens, Luc & Hsiao, Cheng, 2013. "Forecasting a long memory process subject to structural breaks," Journal of Econometrics, Elsevier, vol. 177(2), pages 171-184.
  22. Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2012. "A Comprehensive Look at Financial Volatility Prediction by Economic Variables," BIS Working Papers 374, Bank for International Settlements.
  23. Jari Hännikäinen, 2016. "Selection of an Estimation Window in the Presence of Data Revisions and Recent Structural Breaks," Working Papers 1692, University of Tampere, School of Management, Economics.
  24. Morales-Arias, Leonardo & Moura, Guilherme V., 2013. "Adaptive forecasting of exchange rates with panel data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 493-509.
  25. Rodrigues, Bruno Dore & Stevenson, Maxwell J., 2013. "Takeover prediction using forecast combinations," International Journal of Forecasting, Elsevier, vol. 29(4), pages 628-641.
  26. M. Hashem Pesaran & Andreas Pick, 2009. "Forecasting Random Walks under Drift Instability," DNB Working Papers 207, Netherlands Central Bank, Research Department.
  27. Xiao, Liye & Shao, Wei & Liang, Tulu & Wang, Chen, 2016. "A combined model based on multiple seasonal patterns and modified firefly algorithm for electrical load forecasting," Applied Energy, Elsevier, vol. 167(C), pages 135-153.
  28. Todd E. Clark & Michael W. McCracken, 2010. "Averaging forecasts from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 5-29.
  29. Schrimpf, Andreas & Wang, Qingwei, 2010. "A reappraisal of the leading indicator properties of the yield curve under structural instability," International Journal of Forecasting, Elsevier, vol. 26(4), pages 836-857, October.
  30. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona Graduate School of Economics.
  31. Pesaran, M.H. & Assenmacher-Wesche, K., 2007. "Assessing forecast uncertainties in a VECX* model for Switzerland: an exercise in forecast combination across models and observation windows," Cambridge Working Papers in Economics 0746, Faculty of Economics, University of Cambridge.
  32. M. Mogliani & T. Ferrière, 2016. "Rationality of announcements, business cycle asymmetry, and predictability of revisions. The case of French GDP," Working papers 600, Banque de France.
  33. Jana Eklund & George Kapetanios & Simon Price, 2011. "Forecasting in the presence of recent structural change," CAMA Working Papers 2011-23, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  34. Cem Cakmakli & Dick van Dijk, 2010. "Getting the Most out of Macroeconomic Information for Predicting Stock Returns and Volatility," Tinbergen Institute Discussion Papers 10-115/4, Tinbergen Institute.
  35. John M Maheu & Thomas H McCurdy, 2007. "How useful are historical data for forecasting the long-run equity return distribution?," Working Papers tecipa-293, University of Toronto, Department of Economics.
  36. Campa, Jose M. & Gavilán, Angel, 2006. "Current accounts in the euro area: An intertemporal approach," IESE Research Papers D/651, IESE Business School.
  37. Giraitis, Liudas & Kapetanios, George & Price, Simon, 2014. "Adaptive forecasting in the presence of recent and ongoing structural change," Bank of England working papers 490, Bank of England.
  38. Joscha Beckmann & Rainer Schüssler, 2014. "Forecasting Exchange Rates under Model and Parameter Uncertainty," CQE Working Papers 3214, Center for Quantitative Economics (CQE), University of Muenster.
  39. Wei, Xiaoqiao & Yang, Yuhong, 2012. "Robust forecast combinations," Journal of Econometrics, Elsevier, vol. 166(2), pages 224-236.
  40. Anne Sofie Jore & James Mitchell & Shaun Vahey, 2008. "Combining Forecast Densities from VARs with Uncertain Instabilities," Reserve Bank of New Zealand Discussion Paper Series DP2008/18, Reserve Bank of New Zealand.
  41. Marco Aiolfi & Carlos Capistrán & Allan Timmermann, 2010. "Forecast Combinations," Working Papers 2010-04, Banco de México.
  42. Groen, Jan J.J. & Kapetanios, George & Price, Simon, 2009. "A real time evaluation of Bank of England forecasts of inflation and growth," International Journal of Forecasting, Elsevier, vol. 25(1), pages 74-80.
  43. repec:rdg:wpaper:em-dp2013-03 is not listed on IDEAS
  44. Davide De Gaetano, 2016. "Forecast Combinations For Realized Volatility In Presence Of Structural Breaks," Departmental Working Papers of Economics - University 'Roma Tre' 0208, Department of Economics - University Roma Tre.
  45. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2010. "Out-of-sample equity premium prediction: economic fundamentals vs. moving-average rules," Working Papers 2010-008, Federal Reserve Bank of St. Louis.
  46. Boonsoo Koo & Myung Hwan Seo, 2013. "Structural-break models under mis-specification: implications for forecasting," Monash Econometrics and Business Statistics Working Papers 11/13, Monash University, Department of Econometrics and Business Statistics.
  47. Barbara Rossi & Atsushi Inoue, 2011. "Out-of-sample forecast tests robust to the choice of window size," Working Papers 11-31, Federal Reserve Bank of Philadelphia.
  48. Terence Mills & Kerry Patterson, 2013. "Modelling the Trend: The Historical Origins of Some Modern Methods and Ideas," Economics & Management Discussion Papers em-dp2013-03, Henley Business School, Reading University.
  49. Raffaella Giacomini & Barbara Rossi, 2013. "Forecasting in macroeconomics," Chapters, in: Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 17, pages 381-408 Edward Elgar Publishing.
  50. 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.
  51. Jennifer Castle & David Hendry, 2012. "Forecasting by factors, by variables, or both?," Economics Series Working Papers 600, University of Oxford, Department of Economics.
  52. 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.
  53. Kim, Hyun Hak & Swanson, Norman R., 2014. "Forecasting financial and macroeconomic variables using data reduction methods: New empirical evidence," Journal of Econometrics, Elsevier, vol. 178(P2), pages 352-367.
  54. Fantazziini, Dean, 2014. "Nowcasting and Forecasting the Monthly Food Stamps Data in the US using Online Search Data," MPRA Paper 59696, University Library of Munich, Germany.
  55. Chevillon, Guillaume, 2016. "Multistep forecasting in the presence of location shifts," International Journal of Forecasting, Elsevier, vol. 32(1), pages 121-137.
  56. Delle Monache, Davide & Petrella, Ivan, 2016. "Adaptive Models and Heavy Tails with an Application to Inflation Forecasting," EMF Research Papers 13, Economic Modelling and Forecasting Group.
  57. Pesaran, M. Hashem & Pick, Andreas & Pranovich, Mikhail, 2013. "Optimal forecasts in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 177(2), pages 134-152.
  58. repec:ctc:serie1:def10 is not listed on IDEAS
  59. Nicolau, Mihaela & Palomba, Giulio, 2015. "Dynamic relationships between spot and futures prices. The case of energy and gold commodities," Resources Policy, Elsevier, vol. 45(C), pages 130-143.
  60. Rossen, Anja, 2011. "On the predictive content of nonlinear transformations of lagged autoregression residuals and time series observations," HWWI Research Papers 113, Hamburg Institute of International Economics (HWWI).
  61. Hendry, David F. & Mizon, Grayham E., 2014. "Unpredictability in economic analysis, econometric modeling and forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 186-195.
  62. 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.
  63. Smith, Ron, 2009. "EMU and the Lucas Critique," Economic Modelling, Elsevier, vol. 26(4), pages 744-750, July.
  64. Sylvia Kaufmann, 2010. "Dating and forecasting turning points by Bayesian clustering with dynamic structure: a suggestion with an application to Austrian data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 309-344.
  65. Beckmann, Joscha & Schüssler, Rainer, 2016. "Forecasting exchange rates under parameter and model uncertainty," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 267-288.
  66. Joshua Gallin & Randal Verbrugge, 2007. "Improving the CPI’s Age-Bias Adjustment: Leverage, Disaggregation and Model Averaging," Working Papers 411, U.S. Bureau of Labor Statistics.
  67. Dorsey, Robert E. & Hu, Haixin & Mayer, Walter J. & Wang, Hui-chen, 2010. "Hedonic versus repeat-sales housing price indexes for measuring the recent boom-bust cycle," Journal of Housing Economics, Elsevier, vol. 19(2), pages 75-93, June.
  68. Timmermann, Allan, 2008. "Elusive return predictability," International Journal of Forecasting, Elsevier, vol. 24(1), pages 1-18.
  69. Pesaran, M.H. & Pick, A. & Pranovich, M., 2011. "Optimal Forecasts in the Presence of Structural Breaks (Updated 14 November 2011)," Cambridge Working Papers in Economics 1163, Faculty of Economics, University of Cambridge.
  70. Inoue, Atsushi & Jin, Lu & Rossi, Barbara, 2017. "Rolling window selection for out-of-sample forecasting with time-varying parameters," Journal of Econometrics, Elsevier, vol. 196(1), pages 55-67.
  71. Petrella, Ivan & Delle Monache, Davide, 2016. "Adaptive models and heavy tails," Bank of England working papers 577, Bank of England.
  72. Andrea Monticini & Francesco Ravazzolo, 2014. "Forecasting the intraday market price of money," DISCE - Working Papers del Dipartimento di Economia e Finanza def010, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
  73. Dandan Liu & Rui Li & Zijun Wang, 2011. "Testing for structural breaks in panel varying coefficient models: with an application to OECD health expenditure," Empirical Economics, Springer, vol. 40(1), pages 95-118, February.
  74. 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.
  75. Çakmaklı, Cem & van Dijk, Dick, 2016. "Getting the most out of macroeconomic information for predicting excess stock returns," International Journal of Forecasting, Elsevier, vol. 32(3), pages 650-668.
  76. Theodosiou, Marina, 2011. "Forecasting monthly and quarterly time series using STL decomposition," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1178-1195, October.
  77. Baltagi, Badi H., 2013. "Panel Data Forecasting," Handbook of Economic Forecasting, Elsevier.
  78. Michael P Clements & Ana Beatriz Galvao, 2017. "Data Revisions and Real-time Probabilistic Forecasting of Macroeconomic Variables," ICMA Centre Discussion Papers in Finance icma-dp2017-01, Henley Business School, Reading University.
  79. Mayr, Johannes, 2010. "Forecasting Macroeconomic Aggregates," Munich Dissertations in Economics 11140, University of Munich, Department of Economics.
  80. Mihaela NICOLAU & Giulio PALOMBA & Ilaria TRAINI, 2013. "Are Futures Prices Influenced by Spot;Prices or Vice-versa? An Analysis of Crude;Oil, Natural Gas and Gold Markets," Working Papers 394, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
  81. repec:cty:dpaper:12/02 is not listed on IDEAS
  82. Chrystalleni Aristidou & Kevin Lee & Kalvinder Shields, 2015. "Real-Time Data should be used in Forecasting Output Growth and Recessionary Events in the US," Discussion Papers 2015/13, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
  83. Leonardo Morales-Arias & Alexander Dross, 2010. "Adaptive Forecasting of Exchange Rates with Panel Data," Research Paper Series 285, Quantitative Finance Research Centre, University of Technology, Sydney.
  84. El-Shazly, Alaa, 2016. "Structural breaks and monetary dynamics: A time series analysis," Economic Modelling, Elsevier, vol. 53(C), pages 133-143.
  85. Xiao, Liye & Wang, Jianzhou & Hou, Ru & Wu, Jie, 2015. "A combined model based on data pre-analysis and weight coefficients optimization for electrical load forecasting," Energy, Elsevier, vol. 82(C), pages 524-549.
  86. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, Elsevier.
  87. Atak, Alev & Kapetanios, George, 2013. "A factor approach to realized volatility forecasting in the presence of finite jumps and cross-sectional correlation in pricing errors," Economics Letters, Elsevier, vol. 120(2), pages 224-228.
  88. Clements, Michael P., 2016. "Real-time factor model forecasting and the effects of instability," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 661-675.
  89. 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.
  90. Richard A. Ashley & Kwok Ping Tsang, 2014. "Credible Granger-Causality Inference with Modest Sample Lengths: A Cross-Sample Validation Approach," Econometrics, MDPI, Open Access Journal, vol. 2(1), pages 1-20, March.
  91. Xiu Xu & Andrija Mihoci & Wolfgang Karl Härdle, "undated". "lCARE – localizing Conditional AutoRegressive Expectiles," SFB 649 Discussion Papers SFB649DP2015-052, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  92. Ke Yang & Langnan Chen, 2014. "Realized Volatility Forecast: Structural Breaks, Long Memory, Asymmetry, and Day-of-the-Week Effect," International Review of Finance, International Review of Finance Ltd., vol. 14(3), pages 345-392, 09.
  93. WANG, Shin-Huei & BAUWENS, Luc & HSIAO, Cheng, 2012. "Forecasting long memory processes subject to structural breaks," CORE Discussion Papers 2012048, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  94. Ahumada, Hildegart A. & Garegnani, Maria Lorena, 2012. "Forecasting a monetary aggregate under instability: Argentina after 2001," International Journal of Forecasting, Elsevier, vol. 28(2), pages 412-427.
  95. repec:kie:kieliw:1987 is not listed on IDEAS
  96. Wang, Zijun, 2009. "Stock returns and the short-run predictability of health expenditure: Some empirical evidence," International Journal of Forecasting, Elsevier, vol. 25(3), pages 587-601, July.
  97. Hoornweg, V., 2013. "Some Tools for Robustifying Econometric Analyses," Econometric Institute Research Papers 50163, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  98. Aue, Alexander & Horváth, Lajos & Reimherr, Matthew L., 2009. "Delay times of sequential procedures for multiple time series regression models," Journal of Econometrics, Elsevier, vol. 149(2), pages 174-190, April.
  99. repec:wyi:journl:002213 is not listed on IDEAS
  100. Vasyl Golosnoy, 2007. "Sequential monitoring of minimum variance portfolio," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 91(1), pages 39-55, March.
  101. Biqing Cai & Jiti Gao, 2013. "Hermite Series Estimation in Nonlinear Cointegrating Models," Monash Econometrics and Business Statistics Working Papers 17/13, Monash University, Department of Econometrics and Business Statistics.
  102. Heather M Anderson & Farshid Vahid, 2010. "VARs, Cointegration and Common Cycle Restrictions," Monash Econometrics and Business Statistics Working Papers 14/10, Monash University, Department of Econometrics and Business Statistics.
  103. Elliott, Graham & Timmermann, Allan G, 2016. "Forecasting in Economics and Finance," CEPR Discussion Papers 11354, C.E.P.R. Discussion Papers.
  104. repec:onb:oenbwp:y::i:144:b:1 is not listed on IDEAS
  105. Christophe Boucher & Bertrand Maillet, 2012. "Prévoir sans persistance," Post-Print halshs-00662771, HAL.
  106. Jungmittag, Andre, 2014. "Combination of forecasts across estimation windows: An application to air travel demand," Working Paper Series: Business and Law 05, Frankfurt University of Applied Sciences, Faculty of Business and Law.
This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.