The impact of financial stress on Saudi Arabia government spending: Using machine learning

The paper analyses the interplay between the Saudi government spending and the fiscal stress from the year 2001–2023, which is marked by the volatile prices of oil and ongoing economic difficulties. It untangles the adjustments of government expenses within the context of an oil dependent economy. The model incorporates time series data while using econometric frameworks such as cointegration, Error Correction Model (ECM), and integrating system with recurrent relations. The preliminary analysis indicates that government spending is highly responsive to the macroeconomic factors like -GDP, currency circulation, domestic inflation, oil market prices, and the ratio of unemployed people. Results of the (ECM, which a chooses by machine learning) confirm the importance of short-run and long-run interdependencies highlighting the feedback from oil revenues to government's expenditure and the scope for counter-cyclical fiscal policy. The simulation results are still corroborated by the diagnostics revealing soundness of the model. These reinforce the need to increase alternative sources of revenue in light of declining oil prices while underlining the constructiveness of Saudi fiscal and monetary strategy required to stabilize the economy.