Page 26 - Azerbaijan State University of Economics

THE JOURNAL OF ECONOMIC SCIENCES: THEORY AND PRACTICE, V.83, # 1, 2026, pp. 20-39

movement in energy sector influences financial performance and systemic risks (Qiu et
al., 2024) (Khaleel et al., 2024) (Jasmi & Hassan, 2024).

3. DATA, METHODOLOGY, AND EMPIRICAL RESULTS
3.1 Data and Variable Construction
The empirical research is conducted on six economies data Croatia, Greece, Slovenia,
India, South Africa, and Vietnam. These nations are a balanced portfolio of rising and
transitional economies with varying levels of energy reliance and the state of
renewable energy policies. It contains the set of financial, macroeconomic, and energy
market variables to be integrated into a set of financial and macroeconomic variables
in monthly reports, which is represented by the set of data collected between January
2010 and December 2024. This mix permits cross country comparison and at the same
time gives a picture of both structural variation and time variation in the energy-
finance relationship.

Variables
• Stock returns (STOCK_it): Monthly log returns of national benchmark
indices (CROBEX, ATHEX, SBITOP, BSE SENSEX, FTSE/JSE All Share,
VN Index).
• Exchange rate (FX_it): Monthly log change of the local currency per USD.
• Oil price (OIL_t): Brent crude monthly return (USD/barrel).
• Electricity price (ELEC_it): Wholesale or generation weighted electricity
price indices.
• Macroeconomic controls: Inflation (π_it) and industrial production growth
(ΔReal_it).
• Energy transition variables:
Dummy variables were added to take into consideration certain policies of energy.
o Renewables share (RENEW_it): the ratio of the total amount of
electricity generated by renewable sources.
o Feed-in tariff (FIT it) and phase-out of coal (CPO it) binary
variables that assume the value of 1 in the years where a particular
policy was implemented, and the value 0 in the other years.

• The oil shocks (ε 7 oil) and electricity shocks (ε 7 elec ) were structural
shocks that were determined using a SVAR ordering of Oil 7 Electricity 7
Exchange rate 7 Stock returns in accordance with the paradigm of Kilian
(2009) and Wang et al. (2013).

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