Forecasting natural gas consumption using Bagging and modified regularization techniques

Erick Meira, Fernando Luiz Cyrino Oliveira and Lilian M. de Menezes

Energy Economics, 2022, vol. 106, issue C

Abstract: This paper develops a new approach to forecast natural gas consumption via ensembles. It combines Bootstrap Aggregation (Bagging), univariate time series forecasting methods and modified regularization routines. A new variant of Bagging is introduced, which uses Maximum Entropy Bootstrap (MEB) and a modified regularization routine that ensures that the data generating process is kept in the ensemble. Monthly natural gas consumption time series from 18 European countries are considered. A comparative, out-of-sample evaluation is conducted up to 12 steps (a year) ahead, using a comprehensive set of competing forecasting approaches. These range from statistical benchmarks to machine learning methods and state-of-the-art ensembles. Several performance (accuracy) metrics are used, and a sensitivity analysis is undertaken. Overall, the new variant of Bagging is flexible, reliable, and outperforms well-established approaches. Consequently, it is suitable to support decision making in the energy and other sectors.

Keywords: Forecasting; Natural gas demand; Ensembles; Bagging; Regularization (search for similar items in EconPapers)
JEL-codes: C22 C51 C52 C53 Q41 Q47 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0140988321006034
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:106:y:2022:i:c:s0140988321006034

DOI: 10.1016/j.eneco.2021.105760

Access Statistics for this article

Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant

More articles in Energy Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().