Forecasting Energy Commodity Prices: A Large Global Dataset Sparse Approach
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- Ferrari, Davide & Ravazzolo, Francesco & Vespignani, Joaquin, 2021. "Forecasting energy commodity prices: A large global dataset sparse approach," Energy Economics, Elsevier, vol. 98(C).
- Ferrari, Davide & Ravazzolo, Francesco & Vespignani, Joaquin, 2019. "Forecasting energy commodity prices: a large global dataset sparse approach," Working Papers 2019-09, University of Tasmania, Tasmanian School of Business and Economics.
- Davide Ferrari & Francesco Ravazzolo & Joaquin Vespignani, 2019. "Forecasting Energy Commodity Prices: A Large Global Dataset Sparse Approach," Working Papers No 11/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Davide Ferrari & Francesco Ravazzolo & Joaquin L. Vespignani, 2019. "Forecasting Energy Commodity Prices: A Large Global Dataset Sparse Approach," Globalization Institute Working Papers 376, Federal Reserve Bank of Dallas.
- Davide Ferrari & Francesco Ravazzolo & Joaquin Vespignani, 2019. "Forecasting energy commodity prices: A large global dataset sparse approach," CAMA Working Papers 2019-90, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
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- Nguyen, BH & Zhang, Bo, 2022. "Forecasting oil Prices: can large BVARs help?," Working Papers 2022-04, University of Tasmania, Tasmanian School of Business and Economics.
- Silva, Rodolfo Rodrigues Barrionuevo & Martins, André Christóvão Pio & Soler, Edilaine Martins & Baptista, Edméa Cássia & Balbo, Antonio Roberto & Nepomuceno, Leonardo, 2022. "Two-stage stochastic energy procurement model for a large consumer in hydrothermal systems," Energy Economics, Elsevier, vol. 107(C).
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More about this item
Keywords
Energy Prices; Forecasting; Dynamic Factor model; Sparse Estimation; Penalized Maximum Likelihood.;All these keywords.
JEL classification:
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
- C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
- E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
- Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
NEP fields
This paper has been announced in the following NEP Reports:- NEP-BIG-2021-05-03 (Big Data)
- NEP-ENE-2021-05-03 (Energy Economics)
- NEP-FOR-2021-05-03 (Forecasting)
- NEP-MAC-2021-05-03 (Macroeconomics)
Statistics
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