<![CDATA[Econometrics, particularly Ordinary Least Squares (OLS) models, has long dominated development economics research, offering quantitative insights into growth, poverty, and institutional dynamics. However, its explanatory power is increasingly questioned in contexts characterized by weak institutions, informal economies, and complex socio-cultural dynamics. Grounded in institutional theory, political economy, and complexity perspectives, this study examines the contextual validity of econometrics in explaining development outcomes. Drawing on secondary sources including scholarly articles, books, and policy reports, the study employs content and thematic analysis to synthesize empirical and theoretical literature. Findings indicate that econometric models often fail due to unreliable data, omitted institutional variables, endogeneity caused by structural informality, and non-linear interactions among economic, political, and social factors. Moreover, existing literature has predominantly focused on technical issues such as heteroscedasticity and multicollinearity, leaving a gap in understanding the epistemic and contextual limitations of quantitative approaches and the potential for qualitative complementarity. The study argues that while econometrics is valuable for pattern detection and predictive inference, it is insufficient alone to capture the multidimensional and path-dependent nature of development. It advocates for methodological pluralism, integrating qualitative triangulation, institutional context analysis, and complexity-informed frameworks to enhance explanatory validity. By explicitly linking theory and context, this study contributes a critical and nuanced understanding of development processes, bridging the gap between statistical inference and socio-political realities. In doing so, it advances development economics by offering a theoretically integrated critique of econometric epistemology and proposing methodological pluralism as a more context-sensitive and explanatory framework for analysing development outcomes in heterogeneous institutional environments.]]>
