Work

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

Year: 2025

Type: article

Abstract: 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.

Source: Journal of Radiation Research and Applied Sciences

DOI: 10.1016/j.jrras.2025.101582

Authors: Diaa S. Metwally, Mahmoud El-Morshedy, Hend S. Shahen, Abdallah Sayed Mossalem Ahmed Elshafei

Institutions: Imam Mohammad ibn Saud Islamic University, Prince Sattam Bin Abdulaziz University

Language: English

Topic: Fiscal Policies and Political Economy

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $1,400

Funders: Deanship of Scientific Research, Imam Mohammed Ibn Saud Islamic University, Al-Imam Muhammad Ibn Saud Islamic University