MarvyGithub/ML-Model-For-Economic-Indicators-

Modeling Macroeconomic Indicators in Nigeria: A Comparison of Econometric and Machine Learning Approaches with Insights on Crude Oil and Economic Growth ***Modeling Nigeria's GDP with Econometrics and Machine Learning*** This project analyzes how key macroeconomic variables shape Nigeria's economic performance and compares traditional econometric modeling with modern machine learning for GDP prediction. Using annual Nigerian macroeconomic data from the 1970s through 2023, the analysis evaluates how oil price, oil production, foreign direct investment (FDI), and exchange rate dynamics relate to GDP. The workflow combines time series diagnostics, feature engineering, and predictive modeling to answer a practical question: When forecasting GDP in an oil-dependent economy like Nigeria, do machine learning models outperform conventional econometric approaches? The answer from this project is clear: yes. Among the models tested, XGBoost delivered the strongest predictive performance, followed by Random Forest, while ARDL provided a more interpretable but less accurate benchmark. **Why This Project Matters** Nigeria's economy is highly exposed to oil market conditions, exchange rate volatility, and external capital flows. That makes macroeconomic forecasting both important and difficult. **This project is valuable because it shows how to:** translate an economics research question into a reproducible machine learning workflow, combine domain-aware time series preprocessing with predictive modeling, compare interpretability-focused econometrics against accuracy-focused ML, extract insight from a relatively small macroeconomic dataset without ignoring temporal structure, **For recruiters and hiring managers, this project demonstrates practical strength in:** exploratory data analysis, time series reasoning\, feature engineering, model comparison and evaluation, communicating technical findings in an applied economic context, Research Objective, The goal of the analysis is to model and predict Nigeria's GDP using macroeconomic indicators that are especially relevant in an oil-based economy: Crude oil price, Crude …