Volume 14 , Issue 2 , PP: 60–71, 2026 | Cite this article as | XML | Html | PDF | Full Length Article
Heba Moselhy 1 * , Noura Metawa 2
Doi: https://doi.org/10.54216/AJBOR.140206
This article provides a data analysis framework to study asymmetric macro-financial relationships in an emerging market economy with significant energy dependence. Using annual observations for Egypt over 1990–2024, we estimate a nonlinear autoregressive distributed lag (NARDL) error-correction model in which changes in Brent crude prices are algorithmically decomposed into positive and negative cumulative partial-sum series. A composite financial development index, constructed from banking-sector depth indicators, enters the model both as a direct regressor and as an interaction term with each shock component. The results show that positive oil-price shocks carry a substantially larger long-run penalty on real GDP growth than negative shocks of equal magnitude—consistent with the cost-side exposure of a net oil-importing economy. Financial deepening conditions the transmission of these shocks but does not neutralise them; the allocation of credit toward productive private-sector activity, rather than the aggregate volume of intermediation, determines the direction of the moderating effect. Rolling-window and dynamic multiplier analyses confirm structural instability in the oil–growth relationship across sub-periods, validating the nonlinear modelling approach over standard linear alternatives. Unit root tests with structural breaks, NARDL bounds tests, and a battery of diagnostic checks support the robustness of the estimated long-run relationships. The findings carry direct implications for energy-risk management, financial-sector reform, and growth-stability policy in emerging market settings.
Data analysis , Nonlinear time series , Oil price asymmetry , Financial development , NARDL , Intelligent business analytics , Emerging markets
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