M M Abd El-Raouf
Biographic Data
| ID | 6943799 |
|---|---|
| NAME | M M Abd El-Raouf |
| GIVEN NAMES | M M Abd |
| FAMILY NAME | El-Raouf |
| SIGNATURE | EL-RAOUF M M A |
| AFFILIATIONS | Arab Academy for Science, Technology, and Maritime Transport |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
A Nonlinear Statistical Analysis of Demand Shocks and Public Debt Dynamics in Egypt
This study uses non-linear econometrics to analyze Egypt’s public debt from 1970-2022 and finds three key results: (1) a 89.7% debt/GDP threshold (95% CI: 87.2-92.4%) beyond which fiscal multipliers decline by 40% and interest-growth differentials become 2.5× more volatile, (2) regime asymmetries where crisis periods have 50% slower debt adjustment (α=-0.11 vs -0.32 in stable regimes) and 8.7-year persistence, and (3) institutional mediation wher…
The Optimal Orchestration of Military Expenditure for Economic Growth in Africa
This study presents an extensive empirical investigation into the non-linear relationship between military spending and economic growth, backed by data from 45 African countries for the period of 1990-2023. We relied on an extended Solow growth model and a multi-method econometric approach consisting of System GMM, Panel ARDL, and Panel Threshold Regression; to deal with the problems of endogeneity, dynamic panel bias, and heterogeneity. The resu…
Forecasting Sovereign Debt Distress in Egypt Using a Machine Learning-Based Early Warning System
In the era of rising global sovereign risk, this study designs and validates A Machine Learning-Based Early Warning System for sovereign debt distress specific to Egypt. Going beyond conventional econometric models, we advance machine learning techniques suited to the idiosyncratic nature of the Egyptian economy. Upon rigorous analysis of a comprehensive dataset (1990–2023), the XGBoost algorithm (an implementation of Gradient Boosting showed exc…
No prominent works on this page.
A Nonlinear Statistical Analysis of Demand Shocks and Public Debt Dynamics in Egypt
This study uses non-linear econometrics to analyze Egypt’s public debt from 1970-2022 and finds three key results: (1) a 89.7% debt/GDP threshold (95% CI: 87.2-92.4%) beyond which fiscal multipliers decline by 40% and interest-growth differentials become 2.5× more volatile, (2) regime asymmetries where crisis periods have 50% slower debt adjustment (α=-0.11 vs -0.32 in stable regimes) and 8.7-year persistence, and (3) institutional mediation wher…
The Optimal Orchestration of Military Expenditure for Economic Growth in Africa
This study presents an extensive empirical investigation into the non-linear relationship between military spending and economic growth, backed by data from 45 African countries for the period of 1990-2023. We relied on an extended Solow growth model and a multi-method econometric approach consisting of System GMM, Panel ARDL, and Panel Threshold Regression; to deal with the problems of endogeneity, dynamic panel bias, and heterogeneity. The resu…
Forecasting Sovereign Debt Distress in Egypt Using a Machine Learning-Based Early Warning System
In the era of rising global sovereign risk, this study designs and validates A Machine Learning-Based Early Warning System for sovereign debt distress specific to Egypt. Going beyond conventional econometric models, we advance machine learning techniques suited to the idiosyncratic nature of the Egyptian economy. Upon rigorous analysis of a comprehensive dataset (1990–2023), the XGBoost algorithm (an implementation of Gradient Boosting showed exc…
Corporate governance (2 works) · Debt (2 works) · Fiscal Policies and Political Economy (2 works) · Global Financial Crisis and Policies (2 works) · Bad debt (1 work) · Boosting (machine learning (1 work) · Business cycle (1 work) · Constraint (computer-aided design (1 work) · Credit risk (1 work) · Credit Risk and Financial Regulations (1 work)