This study provides a data-driven econometric analysis of the macroeconomic factors influencing national employment levels. To ensure methodological robustness, the research employs a two-tiered data strategy: an Ordinary Least Squares model with Fixed Effects (FE-OLS) evaluated on a global unbalanced panel of 161 countries (2010-2023), and a Two-step Difference Generalized Method of Moments (GMM) framework applied to a strictly balanced subset of 32 European countries (2015-2022). The analysis evaluates the level-log impact of nominal GDP, alongside tertiary education enrollment and inflation, on total employment. To address potential endogeneity and Nickel bias inherent in dynamic panels, the GMM specification applied a first-difference transformation with extended lagged instruments (t-2 and t-3). The findings reveal that economic output (nominal GDP) is the primary and highly significant driver of employment (β = 7.697, p < 0.001), validating the standard output-employment macroeconomic channel. Conversely, tertiary education enrollment and inflation did not demonstrate statistically significant effects within this 8-year window, likely due to the inherent lag between educational enrollment flows and human capital accumulation, as well as credible European inflation targeting. While these results offer crucial insights for policymakers aiming to foster sustainable socio-economic development, the findings are constrained to the developed European institutional context. Future research should integrate human capital stock metrics and expand the sample to emerging economies to capture broader global dynamics.