Nonlinear ARDL analysis of economic growth, nuclear energy, and innovation's asymmetric effects on Finland's load capacity factor

Irina Georgescu and Jani Kinnunen ()
Additional contact information
Jani Kinnunen: Åbo Akademi University

SN Business & Economics, 2025, vol. 5, issue 4, 1-26

Abstract: Abstract Finland's energy system relies heavily on nuclear power, achieving one of the highest load capacity factors (LCF) globally. This study examines the long- and short-run dynamics between Finland's LCF and the economic variables—gross domestic product (GDP), nuclear power generation (NUK), and patent applications (PA)—using a nonlinear autoregressive distributed lag (NARDL) model for the period 1990–2022. The results indicate that positive changes in GDP significantly reduce LCF in the long run, while negative GDP changes have no substantial effect. Nuclear power generation shows strong asymmetric effects, with positive changes increasing LCF and negative changes causing substantial reductions. Patent applications exhibit nuanced impacts, with positive changes decreasing LCF and negative changes showing marginal positive effects. In the short run, GDP and NUK exhibit mixed asymmetric effects, while patent applications initially reduce LCF before contributing to delayed improvements. These findings emphasize the critical role of nuclear energy in maintaining operational efficiency.

Keywords: NARDL; Nuclear energy; Patent applications; Load capacity factor (search for similar items in EconPapers)
JEL-codes: C23 O13 O44 (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s43546-025-00808-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:snbeco:v:5:y:2025:i:4:d:10.1007_s43546-025-00808-9

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/43546

DOI: 10.1007/s43546-025-00808-9

Access Statistics for this article

SN Business & Economics is currently edited by Gino D'Oca

More articles in SN Business & Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().