A Legal Web Crawling And Reverse Engineering Framework For Economic Data, Analysis, And Modeling: Application To Exchange Rate Depreciation And Stabilization In Madagascar

The collection of data constitutes a fundamental pillar of study, scientific research, and decision-making support mechanisms. In reality, this data collection remains a slow and complex process in the context of scientific study and research. These difficulties stem from the dispersion of sources, the heterogeneity of formats, and legal constraints related to data access. Furthermore, the increasing availability of economic information on the web represents a significant opportunity for analysis and knowledge production. This paper proposes a legal web crawling framework for collecting, analyzing and modeling economic data. The approach is based on reverse engineering, which aims to transform web interfaces into independent and usable data models. The framework combines the use of existing public APIs, such as those from the World Bank and other international institutions, with controlled and compliant crawling mechanisms. The collected data is then subjected to analysis and modelling steps to support decision-making. The results highlight the relevance of this approach for improving the accessibility, legality and reproducibility of economic analyses based on web data. This study adopts a multi-method approach that integrates legal web crawling for data collection, principal component analysis (PCA) supported by correlation analysis to identify the key determinants of currency stabilization, multiple linear regression to assess the marginal effect of each variable on the exchange rate, and an AutoRegressive Integrated Moving Average with eXogenous variables (ARIMAX) model to generate forward-looking exchange-rate projections. This study aims to identify the key determinants of currency stabilization and depreciation in Madagascar, and to propose strategic policy approaches that may support and strengthen monetary stability.