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Evaluating the Impact of Oil Price Volatility and Renewable Energy Adoption on Pakistan's Economic Growth: A Time-Series Analysis Cover

Evaluating the Impact of Oil Price Volatility and Renewable Energy Adoption on Pakistan's Economic Growth: A Time-Series Analysis

By:   
Open Access
|Nov 2025

Figures & Tables

Table 1

Variables, Measurement Units, and Data Sources for the ARDL Model

Variable NameCategoryAbbreviationUnit of MeasurementData Source
Gross Domestic Product GrowthDependentGDPGrowthAnnual %World Development Indicators (WDI)
Oil Price Volatility IndexIndependentOVXIndex ValueInvesting.com
Renewable Energy ConsumptionRES% of Total Final Energy ConsumptionWorld Development Indicators (WDI)
Official Exchange RateControlEXRLocal Currency per USD (Period Average)World Development Indicators (WDI)
Lending Interest RateIR%World Development Indicators (WDI)
Manufacturing Value AddedIPI% of GDPWorld Development Indicators (WDI)
Table 2

ADF Stationarity Tests for Variables Used in the ARDL Model

VariableADF Test at LevelADF Test at First DifferenceADF Test at Second Difference
GDP Growth (GDPGrowth)-3.089 (p = 0.0274)--Level (I(0))
Oil Price Volatility (OVX)-2.680 (p = 0.0775)-3.089 (p = 0.0274)-First Difference (I(1))
Renewable Energy Share (RES)-1.401 (p = 0.5816)-4.453 (p = 0.0002)-First Difference (I(1))
Exchange Rate (EXR)2.371 (p = 0.9990)-0.788 (p = 0.8226)-5.579 (p = 0.0000)Second Difference (I(2))
Interest Rate (IR)-1.502 (p = 0.5326)-2.101 (p = 0.2439)-3.983 (p = 0.0015)Second Difference (I(2))
Industrial Production Index (IPI)-1.731 (p = 0.4153)-2.850 (p = 0.0515)-First Difference (I(1))
Table 3

Diagnostic Tests for ARDL Model Validity and Assumptions

Test NameResultsStatus
Variance Inflation Factor (VIF) TestMean VIF = 3.04
(No multicollinearity issue)
Passed
Breusch-Pagan Heteroskedasticity Testp = 0.6708
(No heteroscedasticity detected)
Passed
Shapiro-Wilk Normality Testp = 0.87437
(Residuals follow normal distribution)
Passed
Durbin-Watson Test for AutocorrelationDurbin-Watson = 2.157 (No severe autocorrelation)Passed
Breusch-Godfrey LM Test for Serial Correlationp = 0.1108
(No serial correlation detected)
Passed
Ramsey RESET Test for Model Specificationp = 0.6088
(No omitted variable bias)
Passed

1 Note: Breusch-Pagan tests for heteroskedasticity, Shapiro-Wilk for normality of residuals, Durbin-Watson and Breusch-Godfrey for autocorrelation, and Ramsey RESET for functional form.

Table 4

ARDL Estimation Results: Short-Run and Long-Run Effects on GDP Growth

VariableCoefficientStd.Errort-StatisticP-Value95% Conf. Interval
GDPGrowth (L1)-0.5875490.0710509-8.270.001(-0.7848179, - 0.39028)
D_OVX0.01238630.0092571.340.252(-0.0133154, 0.0380879)
D_OVX (L1)-0.04999210.0096537-5.180.007(-0.0767952, - 0.0231891)
D_RES0.64942550.10613996.120.004(0.3547338, 0.9441172)
D2_EXR0.11324940.01500397.550.002(0.0715918, 0.1549069)
D2_IR0.03090560.10394350.30.781(-0.2576879, 0.319499)
D_IPI-1.474790.2516851-5.860.004(-2.173579, - 0.7759998)
D_IPI (L1)-3.6751860.1960487-18.750(-4.219504, - 3.130867)
Constant5.8903090.268623721.930(5.14449, 6.636128)

1 Note: This table presents the estimated coefficients from the ARDL model assessing GDP growth as the outcome variable. GDP growth (annual percentage change) serves as the dependent variable. The primary explanatory variables analyzed in the model include oil price volatility (OVX) and renewable energy share (RES), while macroeconomic factors such as exchange rate (EXR), interest rate (IR), and industrial production index (IPI) have been incorporated as control variables to account for broader economic influences.

DOI: https://doi.org/10.2478/acpro-2025-0001 | Journal eISSN: 3044-7259 (formerly 1691-6077) | Journal ISSN: 1691-6077
Language: English
Page range: 4 - 18
Published on: Nov 10, 2025
Published by: Turiba University Ltd
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2025 Usman Bashir, published by Turiba University Ltd
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.