Nowcasting gas demand based on timely available data sources

Natural gas consumption is a critical indicator in both economic analysis and environmental monitoring. Despite its significance for economic policy, energy security, and climate goals, official consumption data are typically published with a considerable time lag. In this work, we describe a method for nowcasting the monthly natural gas consumption of EU member states. Our approach is based on linear regression models and utilizes an external source of gas flow data. In addition, we propose a complementary modeling strategy for countries lacking sufficient flow data, by leveraging correlations across countries. The methodology has achieved promising results in the European Statistics Awards Energy Nowcasting Challenge – GAS.

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Publication Details

Journal
Statistical Journal of the IAOS
Published
2025-11-13
DOI
https://doi.org/10.1177/18747655251391280
Primary Topic
Energy, Environment, and Transportation Policies
Type
article
Field-Weighted Citation Impact
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article

Nowcasting gas demand based on timely available data sources

Martin Ofner, Daniel Strenger-Galvis
Statistical Journal of the IAOS
Energy, Environment, and Transportation Policies
article

Nowcasting gas demand based on timely available data sources

Martin Ofner, Daniel Strenger-Galvis
article en

Abstract

Natural gas consumption is a critical indicator in both economic analysis and environmental monitoring. Despite its significance for economic policy, energy security, and climate goals, official consumption data are typically published with a considerable time lag. In this work, we describe a method for nowcasting the monthly natural gas consumption of EU member states. Our approach is based on linear regression models and utilizes an external source of gas flow data. In addition, we propose a complementary modeling strategy for countries lacking sufficient flow data, by leveraging correlations across countries. The methodology has achieved promising results in the European Statistics Awards Energy Nowcasting Challenge – GAS.

Statistical Journal of the IAOSVol. 41(4)
Graz University of Technology (AT)
Openalex Percentile: Top 76%
Energy, Environment, and Transportation Policies
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