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Forecasting macroeconomic time series: LASSO-based approaches and their forecast combinations with dynamic factor models

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Cited by:

  1. António Rua & Carlos Melo Gouveia & Nuno Lourenço, 2020. "Forecasting tourism with targeted predictors in a data-rich environment," Working Papers w202005, Banco de Portugal, Economics and Research Department.
  2. Olivier Darne & Amelie Charles, 2020. "Nowcasting GDP growth using data reduction methods: Evidence for the French economy," Economics Bulletin, AccessEcon, vol. 40(3), pages 2431-2439.
  3. Juntao Li & Tianxu Cui & Kaiwen Yang & Ruiping Yuan & Liyan He & Mengtao Li, 2021. "Demand Forecasting of E-Commerce Enterprises Based on Horizontal Federated Learning from the Perspective of Sustainable Development," Sustainability, MDPI, vol. 13(23), pages 1-29, November.
  4. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
  5. 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.
  6. Theodore Panagiotidis & Thanasis Stengos & Orestis Vravosinos, 2020. "A Principal Component-Guided Sparse Regression Approach for the Determination of Bitcoin Returns," JRFM, MDPI, vol. 13(2), pages 1-10, February.
  7. Amélie Charles & Olivier Darné, 2022. "Backcasting world trade growth using data reduction methods," The World Economy, Wiley Blackwell, vol. 45(10), pages 3169-3191, October.
  8. Zachary F. Fisher & Younghoon Kim & Barbara L. Fredrickson & Vladas Pipiras, 2022. "Penalized Estimation and Forecasting of Multiple Subject Intensive Longitudinal Data," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 1-29, June.
  9. Guo, Xiaozhu & Huang, Dengshi & Li, Xiafei & Liang, Chao, 2023. "Are categorical EPU indices predictable for carbon futures volatility? Evidence from the machine learning method," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 672-693.
  10. Maiorova, Ksenia & Fokin, Nikita, 2020. "Наукастинг Темпов Роста Стоимостных Объемов Экспорта И Импорта По Товарным Группам [Nowcasting the growth rates of the export and import by commodity groups]," MPRA Paper 109557, University Library of Munich, Germany.
  11. Oguzhan Cepni & I. Ethem Guney & Norman R. Swanson, 2020. "Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 18-36, January.
  12. Cepni, Oguzhan & Güney, I. Ethem & Swanson, Norman R., 2019. "Nowcasting and forecasting GDP in emerging markets using global financial and macroeconomic diffusion indexes," International Journal of Forecasting, Elsevier, vol. 35(2), pages 555-572.
  13. Alessi, Lucia & Balduzzi, Pierluigi & Savona, Roberto, 2019. "Anatomy of a Sovereign Debt Crisis: CDS Spreads and Real-Time Macroeconomic Data," JRC Working Papers in Economics and Finance 2019-03, Joint Research Centre, European Commission.
  14. Smeekes, Stephan & Wijler, Etienne, 2018. "Macroeconomic forecasting using penalized regression methods," International Journal of Forecasting, Elsevier, vol. 34(3), pages 408-430.
  15. Nicholson, William B. & Matteson, David S. & Bien, Jacob, 2017. "VARX-L: Structured regularization for large vector autoregressions with exogenous variables," International Journal of Forecasting, Elsevier, vol. 33(3), pages 627-651.
  16. Kyle E. Binder & Mohsen Pourahmadi & James W. Mjelde, 2020. "The role of temporal dependence in factor selection and forecasting oil prices," Empirical Economics, Springer, vol. 58(3), pages 1185-1223, March.
  17. Wilms, Ines & Rombouts, Jeroen & Croux, Christophe, 2021. "Multivariate volatility forecasts for stock market indices," International Journal of Forecasting, Elsevier, vol. 37(2), pages 484-499.
  18. Xu, Xu & McGrory, Clare Anne & Wang, You-Gan & Wu, Jinran, 2021. "Influential factors on Chinese airlines’ profitability and forecasting methods," Journal of Air Transport Management, Elsevier, vol. 91(C).
  19. Duangnate, Kannika & Mjelde, James W., 2017. "Comparison of data-rich and small-scale data time series models generating probabilistic forecasts: An application to U.S. natural gas gross withdrawals," Energy Economics, Elsevier, vol. 65(C), pages 411-423.
  20. Lourenço, Nuno & Gouveia, Carlos Melo & Rua, António, 2021. "Forecasting tourism with targeted predictors in a data-rich environment," Economic Modelling, Elsevier, vol. 96(C), pages 445-454.
  21. Mr. Jorge A Chan-Lau, 2017. "Lasso Regressions and Forecasting Models in Applied Stress Testing," IMF Working Papers 2017/108, International Monetary Fund.
  22. Paolo Andreini & Donato Ceci, 2019. "A Horse Race in High Dimensional Space," CEIS Research Paper 452, Tor Vergata University, CEIS, revised 14 Feb 2019.
  23. Yuntong Liu & Yu Wei & Yi Liu & Wenjuan Li, 2020. "Forecasting Oil Price by Hierarchical Shrinkage in Dynamic Parameter Models," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-12, December.
  24. Li, W. & Fok, D. & Franses, Ph.H.B.F., 2019. "Forecasting own brand sales: Does incorporating competition help?," Econometric Institute Research Papers EI2019-35, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  25. Mr. Jorge A Chan-Lau, 2017. "Variance Decomposition Networks: Potential Pitfalls and a Simple Solution," IMF Working Papers 2017/107, International Monetary Fund.
  26. Nikita Fokin & Andrey Polbin, 2019. "Forecasting Russia's Key Macroeconomic Indicators with the VAR-LASSO Model," Russian Journal of Money and Finance, Bank of Russia, vol. 78(2), pages 67-93, June.
  27. Ayush Jain & Smit Marvaniya & Shantanu Godbole & Vitobha Munigala, 2020. "A Framework for Crop Price Forecasting in Emerging Economies by Analyzing the Quality of Time-series Data," Papers 2009.04171, arXiv.org.
  28. Nikodinoska, Dragana & Käso, Mathias & Müsgens, Felix, 2022. "Solar and wind power generation forecasts using elastic net in time-varying forecast combinations," Applied Energy, Elsevier, vol. 306(PA).
  29. Mikhail Gareev, 2020. "Use of Machine Learning Methods to Forecast Investment in Russia," Russian Journal of Money and Finance, Bank of Russia, vol. 79(1), pages 35-56, March.
  30. Alonso-Alvarez, Irma & Molina, Luis, 2023. "How to foresee crises? A new synthetic index of vulnerabilities for emerging economies," Economic Modelling, Elsevier, vol. 125(C).
  31. Stolyarov, Dmitriy & Tesar, Linda L., 2021. "Interest rate trends in a global context," Economic Modelling, Elsevier, vol. 101(C).
  32. Liu, Guangqiang & Guo, Xiaozhu, 2022. "Forecasting stock market volatility using commodity futures volatility information," Resources Policy, Elsevier, vol. 75(C).
  33. Sagaert, Yves R. & Aghezzaf, El-Houssaine & Kourentzes, Nikolaos & Desmet, Bram, 2018. "Tactical sales forecasting using a very large set of macroeconomic indicators," European Journal of Operational Research, Elsevier, vol. 264(2), pages 558-569.
  34. Kapetanios, George & Zikes, Filip, 2018. "Time-varying Lasso," Economics Letters, Elsevier, vol. 169(C), pages 1-6.
  35. Zhentao Shi & Liangjun Su & Tian Xie, 2020. "L2-Relaxation: With Applications to Forecast Combination and Portfolio Analysis," Papers 2010.09477, arXiv.org, revised Aug 2022.
  36. repec:hal:journl:hal-04675599 is not listed on IDEAS
  37. Ateeb Akhter Shah Syed & Hassan Raza & Mohsin Waheed, 2023. "Easydata-MD: A Monthly Dataset for Macroeconomic Research on Pakistan," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 28(1), pages 63-88, Jan-June.
  38. Chao Liang & Yi Zhang & Yaojie Zhang, 2022. "Forecasting the volatility of the German stock market: New evidence," Applied Economics, Taylor & Francis Journals, vol. 54(9), pages 1055-1070, February.
  39. Kim, Jang Ho & Han, Jiwoon & Kang, Taehyeon & Fabozzi, Frank J., 2023. "A machine learning approach for comparing the largest firm effect," Emerging Markets Review, Elsevier, vol. 54(C).
  40. Yoshiki Nakajima & Naoya Sueishi, 2022. "Forecasting the Japanese macroeconomy using high-dimensional data," The Japanese Economic Review, Springer, vol. 73(2), pages 299-324, April.
  41. Ding, Yi & Kambouroudis, Dimos & McMillan, David G., 2021. "Forecasting realised volatility: Does the LASSO approach outperform HAR?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
  42. Clément Cariou & Amélie Charles & Olivier Darné, 2024. "Are national or regional surveys useful for nowcasting regional jobseekers? The case of the French region of Pays‐de‐la‐Loire," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2341-2357, September.
  43. Sakemoto, Ryuta, 2021. "Economic Evaluation of Cryptocurrency Investment," MPRA Paper 108283, University Library of Munich, Germany.
  44. António Rua & Nuno Lourenço & Francisco Dias, 2018. "Forecasting exports with targeted predictors," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
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