Non-parametric direct multi-step estimation for forecasting economic processes

Citations

Cited by:

1. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2013. "Should Macroeconomic Forecasters Use Daily Financial Data and How?," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 240-251, April.
   • Elena Andreou & Eric Ghysels & Andros Kourtellos, 2010. "Should Macroeconomic Forecasters Use Daily Financial Data and How?," Working Paper series 42_10, Rimini Centre for Economic Analysis.
   • Eric Ghysels & Andros Kourtellos & Elena Andreou, 2012. "Should macroeconomic forecasters use daily financial data and how?," 2012 Meeting Papers 1196, Society for Economic Dynamics.
   • Elena Andreou & Eric Ghysels & Andros Kourtellos, 2010. "Should macroeconomic forecasters use daily financial data and how?," University of Cyprus Working Papers in Economics 09-2010, University of Cyprus Department of Economics.
2. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2006. "A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 499-526.
   • Massimiliano Marcellino & James Stock & Mark Watson, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," Working Papers 285, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
   • Stock, James & Watson, Mark & Marcellino, Massimiliano, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," CEPR Discussion Papers 4976, C.E.P.R. Discussion Papers.
3. Bauwens, Luc & Chevillon, Guillaume & Laurent, Sébastien, 2023. "We modeled long memory with just one lag!," Journal of Econometrics, Elsevier, vol. 236(1).
   • Bauwens, Luc & Chevillon, Guillaume & Laurent, Sébastien, 2022. "We modeled long memory with just one lag!," LIDAM Discussion Papers CORE 2022016, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
   • Luc Bauwens & Guillaume Chevillon & Sébastien Laurent, 2023. "We modeled long memory with just one lag!," Post-Print hal-04185755, HAL.
   • Bauwens, Luc & Chevillon, Guillaume & Laurent, Sébastien, 2023. "We modeled long memory with just one lag!," LIDAM Reprints CORE 3234, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
4. Edda Claus, 2011. "Seven Leading Indexes of New Zealand Employment," The Economic Record, The Economic Society of Australia, vol. 87(276), pages 76-89, March.
5. Guillaume Chevillon, 2004. "`Weak` trends for inference and forecasting in finite samples," Economics Series Working Papers 210, University of Oxford, Department of Economics.
   • Guillaume Chevillon, 2004. ""Weak" trends for inference and forecasting in finite samples," Documents de Travail de l'OFCE 2004-12, Observatoire Francais des Conjonctures Economiques (OFCE).
6. Alfred A. Haug & Christie Smith, 2012. "Local Linear Impulse Responses for a Small Open Economy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(3), pages 470-492, June.
   • Alfred A Haug & Christie Smith, 2007. "Local linear impulse responses for a small open economy," Reserve Bank of New Zealand Discussion Paper Series DP2007/09, Reserve Bank of New Zealand.
   • Alfred A. Haug & Christie Smith, 2007. "Local linear impulse responses for a small open economy," Working Papers 0707, University of Otago, Department of Economics, revised Apr 2007.
7. Jana Eklund & Sune Karlsson, 2007. "Forecast Combination and Model Averaging Using Predictive Measures," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 329-363.
   • Eklund, Jana & Karlsson, Sune, 2005. "Forecast Combination and Model Averaging using Predictive Measures," Working Paper Series 191, Sveriges Riksbank (Central Bank of Sweden).
   • Eklund, Jana & Karlsson, Sune, 2005. "Forecast Combination and Model Averaging Using Predictive Measures," CEPR Discussion Papers 5268, C.E.P.R. Discussion Papers.
8. Peng, Bo & Song, Haiyan & Crouch, Geoffrey I., 2014. "A meta-analysis of international tourism demand forecasting and implications for practice," Tourism Management, Elsevier, vol. 45(C), pages 181-193.
9. Jari Hännikäinen, 2014. "Multi-step forecasting in the presence of breaks," Working Papers 1494, Tampere University, Faculty of Management and Business, Economics.
   • Hännikäinen, Jari, 2014. "Multi-step forecasting in the presence of breaks," MPRA Paper 55816, University Library of Munich, Germany.
10. Marie Bessec & Othman Bouabdallah, 2015. "Forecasting GDP over the Business Cycle in a Multi-Frequency and Data-Rich Environment," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(3), pages 360-384, June.
    • Bessec, M. & Bouabdallah, O., 2012. "Forecasting GDP over the business cycle in a multi-frequency and data-rich environment," Working papers 384, Banque de France.
    • Marie Bessec & Othman Bouabdallah, 2015. "Forecasting GDP over the business cycle in a multi-frequency and data-rich environment," Post-Print hal-01275760, HAL.
11. Ericsson, Neil R., 2017. "Economic forecasting in theory and practice: An interview with David F. Hendry," International Journal of Forecasting, Elsevier, vol. 33(2), pages 523-542.
    • Neil R. Ericsson, 2016. "Economic Forecasting in Theory and Practice: An Interview with David F. Hendry," Working Papers 2016-012, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    • Neil R. Ericsson, 2016. "Economic Forecasting in Theory and Practice : An Interview with David F. Hendry," International Finance Discussion Papers 1184, Board of Governors of the Federal Reserve System (U.S.).
12. Jennifer Castle & David Hendry, 2012. "Forecasting by factors, by variables, or both?," Economics Series Working Papers 600, University of Oxford, Department of Economics.
13. Hendry, David F. & Pretis, Felix, 2023. "Analysing differences between scenarios," International Journal of Forecasting, Elsevier, vol. 39(2), pages 754-771.
    • David F. Hendry & Felix Pretis, 2020. "Analyzing Differences between Scenarios," Economics Papers 2020-W05, Economics Group, Nuffield College, University of Oxford.
14. Galvao Jr., Antonio F., 2011. "Quantile regression for dynamic panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 164(1), pages 142-157, September.
15. Jennifer Castle & David Hendry, 2007. "Forecasting UK Inflation: the Roles of Structural Breaks and Time Disaggregation," Economics Series Working Papers 309, University of Oxford, Department of Economics.
16. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
    • Buncic, Daniel & Gisler, Katja I. M., 2015. "Global Equity Market Volatility Spillovers: A Broader Role for the United States," Economics Working Paper Series 1508, University of St. Gallen, School of Economics and Political Science.
17. Vladimir Kuzin & Massimiliano Marcellino & Christian Schumacher, 2009. "Pooling versus Model Selection for Nowcasting with Many Predictors: An Application to German GDP," Economics Working Papers ECO2009/13, European University Institute.
    • Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "Pooling versus model selection for nowcasting with many predictors: an application to German GDP," Discussion Paper Series 1: Economic Studies 2009,03, Deutsche Bundesbank.
    • Schumacher, Christian & Marcellino, Massimiliano & Kuzin, Vladimir, 2009. "Pooling versus model selection for nowcasting with many predictors: An application to German GDP," CEPR Discussion Papers 7197, C.E.P.R. Discussion Papers.
18. Clements, Adam & Preve, Daniel P.A., 2021. "A Practical Guide to harnessing the HAR volatility model," Journal of Banking & Finance, Elsevier, vol. 133(C).
    • A Clements & D Preve, 2019. "A Practical Guide to Harnessing the HAR Volatility Model," NCER Working Paper Series 120, National Centre for Econometric Research.
19. Todd E. Clark & Michael W. McCracken, 2001. "Evaluating long-horizon forecasts," Research Working Paper RWP 01-14, Federal Reserve Bank of Kansas City.
20. Kuzin, Vladimir & Marcellino, Massimiliano & Schumacher, Christian, 2011. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the euro area," International Journal of Forecasting, Elsevier, vol. 27(2), pages 529-542.
    • Kuzin, Vladimir & Marcellino, Massimiliano & Schumacher, Christian, 2011. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the euro area," International Journal of Forecasting, Elsevier, vol. 27(2), pages 529-542, April.
    • Vladimir Kuzin & Massimiliano Marcellino & Christian Schumacher, 2009. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area," Economics Working Papers ECO2009/32, European University Institute.
    • Schumacher, Christian & Marcellino, Massimiliano & Kuzin, Vladimir, 2009. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area," CEPR Discussion Papers 7445, C.E.P.R. Discussion Papers.
21. Guillaume Chevillon, 2004. "A Comparison of Multi-step GDP Forecasts for South Africa," Documents de Travail de l'OFCE 2004-13, Observatoire Francais des Conjonctures Economiques (OFCE).
    • Guillaume Chevillon, 2004. "A Comparison of Multi-step GDP Forecasts for South Africa," Economics Series Working Papers 212, University of Oxford, Department of Economics.
22. Massimiliano Marcellino & Christian Schumacher, 2008. "Factor-MIDAS for Now- and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP1," Working Papers 333, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
23. Guillaume Chevillon, 2007. "Direct Multi‐Step Estimation And Forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 746-785, September.
    • Guillaume Chevillon, 2005. "Direct multi-step estimation and forecasting," Documents de Travail de l'OFCE 2005-10, Observatoire Francais des Conjonctures Economiques (OFCE).
24. Nikolay Robinzonov & Klaus Wohlrabe, 2010. "Freedom of Choice in Macroeconomic Forecasting ," CESifo Economic Studies, CESifo Group, vol. 56(2), pages 192-220, June.
    • Nikolay Robinzonov & Klaus Wohlrabe, 2008. "Freedom of Choice in Macroeconomic Forecasting: An Illustration with German Industrial Production and Linear Models," ifo Working Paper Series 57, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
25. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
26. Gür Ali, Özden & Gürlek, Ragıp, 2020. "Automatic Interpretable Retail forecasting with promotional scenarios," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1389-1406.
27. Buncic, Daniel & Piras, Gion Donat, 2016. "Heterogeneous agents, the financial crisis and exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 313-359.
    • Buncic, Daniel & Piras, Gion Donat, 2014. "Heterogeneous Agents, the Financial Crisis and Exchange Rate Predictability," Economics Working Paper Series 1436, University of St. Gallen, School of Economics and Political Science, revised Oct 2015.
28. 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.
29. Marcellino, Massimiliano & Schumacher, Christian, 2007. "Factor-MIDAS for now- and forecasting with ragged-edge data: a model comparison for German GDP," Discussion Paper Series 1: Economic Studies 2007,34, Deutsche Bundesbank.
    • Massimiliano Marcellino & Christian Schumacher, 2008. "Factor-MIDAS for Now- and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP," Economics Working Papers ECO2008/16, European University Institute.
    • Schumacher, Christian & Marcellino, Massimiliano, 2008. "Factor-MIDAS for now- and forecasting with ragged-edge data: A model comparison for German GDP," CEPR Discussion Papers 6708, C.E.P.R. Discussion Papers.
30. Schumacher, Christian, 2016. "A comparison of MIDAS and bridge equations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 257-270.
31. Buncic, Daniel & Moretto, Carlo, 2015. "Forecasting copper prices with dynamic averaging and selection models," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 1-38.
    • Buncic, Daniel & Moretto, Carlo, 2014. "Forecasting Copper Prices with Dynamic Averaging and Selection Models," Economics Working Paper Series 1430, University of St. Gallen, School of Economics and Political Science.
32. Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "MIDAS versus mixed-frequency VAR: nowcasting GDP in the euro area," Discussion Paper Series 1: Economic Studies 2009,07, Deutsche Bundesbank.
33. Eliana González Molano & Luis Fernando Melo Velnadia & Anderson Grajales Olarte, 2007. "Pronósticos directos de la inflación colombiana," Borradores de Economia 4247, Banco de la Republica.
    • Eliana González Molano & Luis Fernando Melo Velnadia & Anderson Grajales Olarte, 2007. "Pronósticos directos de la inflación colombiana," Borradores de Economia 4246, Banco de la Republica.
    • Eliana González Molano & Luis Fernando Melo Velandia & Anderson Grajales Olarte, 2007. "Pronósticos directos de la inflación colombiana," Borradores de Economia 458, Banco de la Republica de Colombia.
34. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    • Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
35. Souhaib Ben Taieb & Rob J Hyndman, 2012. "Recursive and direct multi-step forecasting: the best of both worlds," Monash Econometrics and Business Statistics Working Papers 19/12, Monash University, Department of Econometrics and Business Statistics.
36. Jalal Shiri & Shahaboddin Shamshirband & Ozgur Kisi & Sepideh Karimi & Seyyed M Bateni & Seyed Hossein Hosseini Nezhad & Arsalan Hashemi, 2016. "Prediction of Water-Level in the Urmia Lake Using the Extreme Learning Machine Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5217-5229, November.
37. 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.
38. Kisi, Ozgur & Shiri, Jalal & Karimi, Sepideh & Shamshirband, Shahaboddin & Motamedi, Shervin & Petković, Dalibor & Hashim, Roslan, 2015. "A survey of water level fluctuation predicting in Urmia Lake using support vector machine with firefly algorithm," Applied Mathematics and Computation, Elsevier, vol. 270(C), pages 731-743.
39. Hendry, David & Hubrich, Kirstin, 2006. "Forecasting Economic Aggregates by Disaggregates," CEPR Discussion Papers 5485, C.E.P.R. Discussion Papers.
    • Hendry, David F. & Hubrich, Kirstin, 2006. "Forecasting economic aggregates by disaggregates," Working Paper Series 589, European Central Bank.
40. Schumacher Christian, 2011. "Forecasting with Factor Models Estimated on Large Datasets: A Review of the Recent Literature and Evidence for German GDP," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 28-49, February.
41. Bjørn Eraker & Ching Wai (Jeremy) Chiu & Andrew T. Foerster & Tae Bong Kim & Hernán D. Seoane, 2015. "Bayesian Mixed Frequency VARs," Journal of Financial Econometrics, Oxford University Press, vol. 13(3), pages 698-721.
    • Ching Wai Chiu & Bjorn Eraker & Andrew T. Foerster & Tae Bong Kim & Hernan D. Seoane, 2011. "Estimating VAR's sampled at mixed or irregular spaced frequencies : a Bayesian approach," Research Working Paper RWP 11-11, Federal Reserve Bank of Kansas City.
42. Chevillon, Guillaume, 2016. "Multistep forecasting in the presence of location shifts," International Journal of Forecasting, Elsevier, vol. 32(1), pages 121-137.
43. Christian Schumacher, 2007. "Forecasting German GDP using alternative factor models based on large datasets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(4), pages 271-302.
    • Schumacher, Christian, 2005. "Forecasting German GDP using alternative factor models based on large datasets," Discussion Paper Series 1: Economic Studies 2005,24, Deutsche Bundesbank.
44. Taewoon Kong & Dongguen Choi & Geonseok Lee & Kichun Lee, 2021. "Air Pollution Prediction Using an Ensemble of Dynamic Transfer Models for Multivariate Time Series," Sustainability, MDPI, vol. 13(3), pages 1-17, January.
45. Gur Ali, Ozden & Pinar, Efe, 2016. "Multi-period-ahead forecasting with residual extrapolation and information sharing — Utilizing a multitude of retail series," International Journal of Forecasting, Elsevier, vol. 32(2), pages 502-517.
46. Chevillon, Guillaume, 2017. "Robustness of Multistep Forecasts and Predictive Regressions at Intermediate and Long Horizons," ESSEC Working Papers WP1710, ESSEC Research Center, ESSEC Business School.
47. 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.
48. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2015. "Markov-switching mixed-frequency VAR models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 692-711.
    • Marcellino, Massimiliano & Foroni, Claudia, 2014. "Markov-Switching Mixed-Frequency VAR Models," CEPR Discussion Papers 9815, C.E.P.R. Discussion Papers.
49. Johannes Mayr & Dirk Ulbricht, 2007. "VAR Model Averaging for Multi-Step Forecasting," ifo Working Paper Series 48, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
50. Schumacher, Christian & Breitung, Jörg, 2008. "Real-time forecasting of German GDP based on a large factor model with monthly and quarterly data," International Journal of Forecasting, Elsevier, vol. 24(3), pages 386-398.
51. Protić, Milan & Shamshirband, Shahaboddin & Petković, Dalibor & Abbasi, Almas & Mat Kiah, Miss Laiha & Unar, Jawed Akhtar & Živković, Ljiljana & Raos, Miomir, 2015. "Forecasting of consumers heat load in district heating systems using the support vector machine with a discrete wavelet transform algorithm," Energy, Elsevier, vol. 87(C), pages 343-351.
52. 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.
53. Pierre Guérin & Massimiliano Marcellino, 2013. "Markov-Switching MIDAS Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 45-56, January.
    • Marcellino, Massimiliano, 2011. "Markov-switching MIDAS models," CEPR Discussion Papers 8234, C.E.P.R. Discussion Papers.
54. Hendry, David F., 2006. "Robustifying forecasts from equilibrium-correction systems," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 399-426.
55. Massimiliano Marcellino & Christian Schumacher, 2010. "Factor MIDAS for Nowcasting and Forecasting with Ragged‐Edge Data: A Model Comparison for German GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(4), pages 518-550, August.
56. Kirstin Hubrich & David F. Hendry, 2005. "Forecasting Aggregates by Disaggregates," Computing in Economics and Finance 2005 270, Society for Computational Economics.
57. John Haywood & Granville Tunnicliffe Wilson, 2009. "A test for improved multi‐step forecasting," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(6), pages 682-707, November.
58. Meenakshi Narayan & Ann Majewicz Fey, 2020. "Developing a novel force forecasting technique for early prediction of critical events in robotics," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-34, May.