PurposeThis research aims to examine the macro determinants that significantly affect financial development in the Middle East and North Africa (MENA) region, which could be used furtherly to play a major role in economic sustainability since one of the major driving forces for economic development is the financial development.Design/methodology/approachThe significant determinants of financial development should be efficiently used by the MENA region countries for creating huge financial sector development and innovation, stimulating economic development in turn and leading to the completion of the cycle of development and sustainability. To achieve this study's objective, the researcher employed a quantitative method to develop an econometric model.FindingsThis model consisted of two Panel EGLS Cross-Section Random Effects Models (REMs) in which Domestic credit to the private sector as a percentage of GDP (?PCGDP?_it) and stock market capitalization ratio (?SMC?_it) were taken as the dependent variables. In addition, the independent variables included the corruption perception index, financial freedom (FF), political stability (PS) and trade openness (TO). The researcher extracted the data for the analysis from different databases including the World Bank, the Organization for Economic Cooperation and Development and the International Monetary Fund. Throughout the first – Panel EGLS Cross-Section Random Effects Model, it turned out that, while FF, TO and corruption index had a positive relationship with ?PCGDP?_it, PS had an adverse effect on ?PCGDP?_it. The second – Panel EGLS Cross-Section Random Effects Model showed that, while PS and TO had a positive effect on stock market performance, the corruption index and FF had an adverse effect on stock market performance.Originality/valueThroughout the first – Panel EGLS Cross-Section Random Effects Model, it turned out that, while FF, TO and corruption index had a positive relationship with ?PCGDP?_it, PS had an adverse effect on ?PCGDP?_it. The second – Panel EGLS Cross-Section Random Effects Model showed that, while PS and TO had a positive effect on stock market performance, the corruption index and FF had an adverse effect on stock market performance.

By using time-series data in respect of the period from 1985 to 2019, this study aims to compare how the changes in Yearly Oil Prices (YOP) affect both Saudi Arabia's and Algeria's military expenditure. This study applies the Vector Error Correction Model (VECM) to measure the relationships between the variables. On the one hand, this study's findings indicate that changes in YOP have had a great causal impact on both countries' military expenditure, On the other hand, the link to Growth Fixed Capital (GFC) has had an insignificant effect on Saudi Arabia's military expenditure. However, in the case of Algeria, the causal effect has been significant but, nevertheless, at a particularly low level (α = 10%). In conclusion, the two countries should pay closer attention to the dominant YOP when formulating their policies to maintain their much-needed security systems and protection umbrellas.