This study examines the effect of environmental innovation on emission performance and the moderating role of board gender diversity among firms in the Middle East and North Africa (MENA) region. Using a panel dataset of 2319 firm-year observations from 13 countries between 2013 and 2024, the analysis applies fixed-effects regression and robustness checks using the Generalized Method of Moments (GMM). The findings show that environmental innovation significantly improves emissions performance, confirming its strategic role in achieving sustainability goals. Board gender diversity has a positive direct impact on emissions outcomes, suggesting that diverse boards enhance sustainability-oriented governance. However, the interaction term has a negative and significant effect, indicating that gender diversity, while beneficial overall, can weaken the link between environmental innovation and emission performance, possibly because of complex decision-making processes. This study contributes theoretically by extending the Resource-Based View and Porter Hypothesis to an under-researched context, while emphasizing the need for governance mechanisms that leverage diversity without slowing innovation implementation. Future research should incorporate qualitative insights and examine other governance factors to deepen our understanding of how board composition influences sustainability strategies.

Does mandatory sustainability disclosure improve the quality of corporate financial reporting immediately, gradually, or with delay? We address this question using Saudi Arabia’s January 2021 Tadawul ESG Disclosure Guidelines—the first comprehensive sustainability disclosure framework in the Gulf Cooperation Council and a uniform, accurately dated regulatory shock affecting all listed firms. Using a balanced panel of 135 non-financial firms over 2017–2024 (1080 firm-year observations), we estimate absolute discretionary accruals from the Modified Jones Model and employ event-time fixed-effects regressions with Driscoll–Kraay standard errors robust to heteroskedasticity, autocorrelation, and cross-sectional dependence. We document a temporal paradox: reporting quality did not change in the announcement year (2021), deteriorated significantly in 2022 (+28%) and 2023 (+38%) relative to the pre-reform baseline, and then improved significantly in 2024 (−17%). The pattern survives performance-matched discretionary accruals, exclusion of the 2020 COVID-19 year, a placebo test, sectoral disaggregation across nine Tadawul-aligned industry groups, and a battery of pre-reform firm characteristics. Heterogeneity analysis identifies the underlying mechanism: voluntary pre-2021 ESG disclosers and firms with stronger pre-reform governance exhibit amplified short-run deterioration, while larger firms with pre-existing reporting infrastructure show a substantially attenuated paradox. These patterns are jointly consistent with the adjustment-cost mechanism we develop: the reform redirected scarce reporting governance toward the new disclosure margin during a three-year compliance buildout, after which the constraining effect on accrual-based earnings management emerged. The findings carry direct implications for the design and evaluation of mandatory sustainability disclosure reforms currently advancing across emerging and developed markets.

Saudi Arabia’s Vision 2030 is a multifaceted endeavor seeking domestic energy price reforms, mobilization of green finance, and non-oil economic diversification, yet the interplay of these three pillars has not been empirically tested. This study examines the role and impact of calibrated energy price signals and novel financing instruments on non-oil GDP using quarterly data from 2010 to 2025. A sequential methodology integrates unit root tests, Johansen cointegration, the Vector Error Correction Model (VECM), ARDL, K-means clustering, and random forest. Findings indicate that all variables are I(1) except utilities GDP (I(0)), and the system is cointegrated with two cointegrating vectors. The ARDL long-run multipliers show that a 1% increase in oil GDP raises non-oil GDP by 0.37%, government spending by 0.70%, and investment by 0.25%, with the oil price deflator having a negligible long-run effect (0.012%). The VECM confirms partial decoupling, with non-oil GDP Granger-causing oil GDP in the short run. Clustering groups non-oil, utilities, and government sectors together, while isolating oil and investment. Random forest identifies lagged oil GDP and government spending as the top predictors of non-oil output. The study concludes that energy price reforms do not harm long-run non-oil growth, and fiscal policy remains the strongest lever of diversification. Policy recommendations include continuing subsidy reforms, reinvesting savings into productive government expenditure, scaling green bond-financed infrastructure, and monitoring sectoral sensitivities through the identified cluster structures.

This study analyzes the asymmetric effects of oil prices on Saudi Arabia’s trade balance from 1990 to 2024 using a nonlinear autoregressive distributed lag (NARDL) model. By decomposing oil price changes into positive and negative partial sums, this model estimates short- and long-run asymmetric responses and traces adjustment paths using dynamic multipliers. Our results indicate a stable cointegrating relationship and pronounced asymmetry: a $1 increase in oil prices raises the trade balance by approximately $1.56 billion in the long run, whereas a $1 decrease reduces it by about $1.85 billion. The dynamic multipliers show substantial immediate effects, approximately +$2.76 and −$2.88 at horizon 0, which gradually converge to their respective long-run levels, with negative shocks producing larger and more persistent adverse effects than positive shocks. These findings emphasize KSA’s external vulnerability to oil price declines and underscore the need for countercyclical fiscal rules, reserve buffers, and accelerated non-oil export growth to mitigate downside risks and effectively manage external trade in response to global oil market volatility.