Foreign Direct Investment, Economic Growth, and Environmental Sustainability in Pakistan: an Empirical Investigation of Dynamic Relationships
DOI:
https://doi.org/10.71317/jgst.2.10.2026.881Keywords:
Foreign Direct Investment, Economic Growth, Environmental Sustainability, CO₂ Emissions, ARDL Model, Time-Series Analysis, PakistanAbstract
This study examined the relationships among foreign direct investment (FDI), economic growth, and environmental sustainability in Pakistan using annual time-series data for 1990–2024. A quantitative longitudinal research design was employed, incorporating descriptive statistics, Pearson correlation analysis, Augmented Dickey–Fuller unit-root testing, autoregressive distributed lag (ARDL) estimation, bounds testing, and diagnostic procedures. FDI was measured as net inflows relative to GDP, economic growth was represented by annual real GDP growth, and environmental pressure was assessed using CO₂ emissions excluding land use, land-use change, and forestry per capita. The correlation analysis revealed statistically non-significant relationships between FDI and economic growth (r = 0.060, p = 0.732), FDI and CO₂ emissions (r = 0.121, p = 0.490), and economic growth and CO₂ emissions (r = −0.076, p = 0.664). The estimated ARDL model indicated substantial persistence in CO₂ emissions, whereas the individual FDI and economic-growth coefficients were statistically non-significant. The bounds-testing result (F = 1.7557) did not establish a long-run equilibrium relationship within the CO₂-dependent specification. Diagnostic testing identified heteroskedasticity, for which robust statistical inference was employed. The findings indicate that the hypothesized relationships were not statistically supported within the selected specifications and highlight the importance of considering economic structure, investment characteristics, and environmental conditions when evaluating sustainable development in Pakistan.
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Copyright (c) 2026 Agha Jan Hamraz, Syed Ahmed Shahab Tariq, Samar Ali (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.











