Time Series Forecasting with Many Predictors
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Michael W. McCracken & Serena Ng, 2016.
"FRED-MD: A Monthly Database for Macroeconomic Research,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 574-589, October.
- Michael W. McCracken & Serena Ng, 2015. "FRED-MD: A Monthly Database for Macroeconomic Research," Working Papers 2015-12, Federal Reserve Bank of St. Louis.
- Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015.
"Measuring Uncertainty,"
American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
- Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2013. "Measuring Uncertainty," NBER Working Papers 19456, National Bureau of Economic Research, Inc.
- Boivin, Jean & Ng, Serena, 2006.
"Are more data always better for factor analysis?,"
Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
- Jean Boivin & Serena Ng, 2003. "Are More Data Always Better for Factor Analysis?," NBER Working Papers 9829, National Bureau of Economic Research, Inc.
- Diebold, Francis X & Mariano, Roberto S, 2002.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.
- Francis X. Diebold & Roberto S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Bernanke, Ben S. & Boivin, Jean, 2003.
"Monetary policy in a data-rich environment,"
Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
- Ben S. Bernanke & Jean Boivin, 2001. "Monetary Policy in a Data-Rich Environment," NBER Working Papers 8379, National Bureau of Economic Research, Inc.
- Dashan Huang & Fuwei Jiang & Kunpeng Li & Guoshi Tong & Guofu Zhou, 2022.
"Scaled PCA: A New Approach to Dimension Reduction,"
Management Science, INFORMS, vol. 68(3), pages 1678-1695, March.
- Dashan Huang & Fuwei Jiang & Kunpeng Li & Guoshi Tong & Guofu Zhou, 2022. "Scaled PCA: A New Approach to Dimension Reduction," CEMA Working Papers 678, China Economics and Management Academy, Central University of Finance and Economics.
- Arkajyoti Saha & Sumanta Basu & Abhirup Datta, 2023. "Random Forests for Spatially Dependent Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 118(541), pages 665-683, January.
- Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005.
"Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach,"
The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(1), pages 387-422.
- Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2004. "Measuring the effects of monetary policy: a factor-augmented vector autoregressive (FAVAR) approach," Finance and Economics Discussion Series 2004-03, Board of Governors of the Federal Reserve System (U.S.).
- Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2004. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," NBER Working Papers 10220, National Bureau of Economic Research, Inc.
- 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.
- Huyn Hak Kim & Norman R. Swanson, 2011. "Forecasting Financial and Macroeconomic Variables Using Data Reduction Methods: New Empirical Evidence," Departmental Working Papers 201119, Rutgers University, Department of Economics.
- Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
- Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
- Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022.
"How is machine learning useful for macroeconomic forecasting?,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Working Papers 20-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Aug 2020.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Papers 2008.12477, arXiv.org.
- Michael W. McCracken & Serena Ng, 2016.
"FRED-MD: A Monthly Database for Macroeconomic Research,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 574-589, October.
- Michael W. McCracken & Serena Ng, 2015. "FRED-MD: A Monthly Database for Macroeconomic Research," Working Papers 2015-12, Federal Reserve Bank of St. Louis.
- Gilchrist, Simon & Yankov, Vladimir & Zakrajsek, Egon, 2009.
"Credit market shocks and economic fluctuations: Evidence from corporate bond and stock markets,"
Journal of Monetary Economics, Elsevier, vol. 56(4), pages 471-493, May.
- Simon Gilchrist & Vladimir Yankov & Egon Zakrajsek, 2009. "Credit Market Shocks and Economic Fluctuations: Evidence from Corporate Bond and Stock Markets," NBER Working Papers 14863, National Bureau of Economic Research, Inc.
- Vladimir Yankov & Egon Zakrajsek & Simon Gilchrist, 2009. "Credit Market Shocks and Economic Fluctuations: Evidence from Corporate Bond and Stock Markets," 2009 Meeting Papers 514, Society for Economic Dynamics.
- Vigo Pereira, Caio, 2021.
"Portfolio efficiency with high-dimensional data as conditioning information,"
International Review of Financial Analysis, Elsevier, vol. 77(C).
- Caio Vigo Pereira, 2020. "Portfolio Efficiency with High-Dimensional Data as Conditioning Information," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202015, University of Kansas, Department of Economics, revised Sep 2020.
- Kuusela, Annika & Hännikäinen, Jari, 2017. "What do the shadow rates tell us about future inflation?," MPRA Paper 80542, University Library of Munich, Germany.
- Olivier Fortin‐Gagnon & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022.
"A large Canadian database for macroeconomic analysis,"
Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(4), pages 1799-1833, November.
- Olivier Fortin-Gagnon & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2018. "A Large Canadian Database for Macroeconomic Analysis," CIRANO Working Papers 2018s-25, CIRANO.
- Olivier Fortin-Gagnon & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "A Large Canadian Database for Macroeconomic Analysis," Working Papers 20-07, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
- Demetrescu, Matei & Hacıoğlu Hoke, Sinem, 2019.
"Predictive regressions under asymmetric loss: Factor augmentation and model selection,"
International Journal of Forecasting, Elsevier, vol. 35(1), pages 80-99.
- Demetrescu, Matei & Hacioglu Hoke, Sinem, 2018. "Predictive regressions under asymmetric loss: factor augmentation and model selection," Bank of England working papers 723, Bank of England.
- Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019.
"Macroeconomic forecast accuracy in a data‐rich environment,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1050-1072, November.
- Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic Forecast Accuracy in data-rich environment," Post-Print hal-02435757, HAL.
- Paccagnini, Alessia, 2019. "Did financial factors matter during the Great Recession?," Economics Letters, Elsevier, vol. 174(C), pages 26-30.
- Varlam Kutateladze, 2021. "The Kernel Trick for Nonlinear Factor Modeling," Papers 2103.01266, arXiv.org.
- Smeekes, Stephan & Wijler, Etienne, 2018.
"Macroeconomic forecasting using penalized regression methods,"
International Journal of Forecasting, Elsevier, vol. 34(3), pages 408-430.
- Smeekes, Stephan & Wijler, Etiënne, 2016. "Macroeconomic Forecasting Using Penalized Regression Methods," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).
- Kutateladze, Varlam, 2022. "The kernel trick for nonlinear factor modeling," International Journal of Forecasting, Elsevier, vol. 38(1), pages 165-177.
- Kim, Hyun Hak & Swanson, Norman R., 2018. "Mining big data using parsimonious factor, machine learning, variable selection and shrinkage methods," International Journal of Forecasting, Elsevier, vol. 34(2), pages 339-354.
- Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
- Gupta, Rangan & Kabundi, Alain & Miller, Stephen M., 2011.
"Forecasting the US real house price index: Structural and non-structural models with and without fundamentals,"
Economic Modelling, Elsevier, vol. 28(4), pages 2013-2021, July.
- Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009. "Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals," Working Papers 200927, University of Pretoria, Department of Economics.
- Rangan Gupta & Alan Kabundi & Stephen M. Miller, 2010. "Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals," Working Papers 1001, University of Nevada, Las Vegas , Department of Economics.
- Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009. "Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals," Working papers 2009-42, University of Connecticut, Department of Economics.
- Mario Forni & Alessandro Giovannelli & Marco Lippi & Stefano Soccorsi, 2018.
"Dynamic factor model with infinite‐dimensional factor space: Forecasting,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(5), pages 625-642, August.
- Mario Forni & Alessandro Giovannelli & Marco Lippi & Stefano Soccorsi, 2016. "Dynamic Factor model with infinite dimensional factor space: forecasting," Center for Economic Research (RECent) 120, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
- Mario Forni & Alessandro Giovannelli & Marco Lippi & Stefano Soccorsi, 2016. "Dynamic Factor Model with Infinite Dimensional Factor Space: Forecasting," Working Papers ECARES ECARES 2016-16, ULB -- Universite Libre de Bruxelles.
- 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.
- Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2022.
"The global component of inflation volatility,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 700-721, June.
- Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2018. "The global component of inflation volatility," Temi di discussione (Economic working papers) 1170, Bank of Italy, Economic Research and International Relations Area.
- Marcellino, Massimiliano & Carriero, Andrea & Corsello, Francesco, 2019. "The Global Component of Inflation Volatility," CEPR Discussion Papers 13470, C.E.P.R. Discussion Papers.
- Caroline Jardet & Baptiste Meunier, 2022.
"Nowcasting world GDP growth with high‐frequency data,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1181-1200, September.
- Jardet Caroline & Meunier Baptiste, 2020. "Nowcasting World GDP Growth with High-Frequency Data," Working papers 788, Banque de France.
- Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Post-Print hal-03647097, HAL.
- Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05, Department of Economics, University of Birmingham.
- Antipa, Pamfili & Barhoumi, Karim & Brunhes-Lesage, Véronique & Darné, Olivier, 2012.
"Nowcasting German GDP: A comparison of bridge and factor models,"
Journal of Policy Modeling, Elsevier, vol. 34(6), pages 864-878.
- Antipa, P. & Barhoumi, K. & Brunhes-Lesage, V. & Darné, O., 2012. "Nowcasting German GDP: A comparison of bridge and factor models," Working papers 401, Banque de France.
More about this item
Keywords
supervised principal component analysis; diffusion index; Lasso; dynamic dependence; group orthogonal greedy algorithm;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:12:y:2024:i:15:p:2336-:d:1443454. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.