What Drives IT Salary? A Three-Stage Test of Human Capital Theory in Saudi Arabia

Workforce policy in the digital era depends on knowing which human capital attributes generate salary returns and through which channels they operate. Two limitations have constrained progress. First, IT-skills research routinely collapses individual competencies into composite indices, masking within-domain heterogeneity. Second, existing studies cannot distinguish whether human capital raises salary directly through within-role productivity or indirectly through access to higher-paying occupational categories. This study addresses both limitations through a sequenced three-stage analytical design applied to survey data from 2,167 IT professionals in Saudi Arabia, an emerging-economy IT labor market shaped by Vision 2030. Stage 1 estimates each predictor unconditional salary association. Stage 2 estimates the joint total effect of all four human capital predictors. Stage 3 adds job category as a structural control to approximate how those associations change after adjusting for occupational category. All three significant predictors: work experience, soft-skill proficiency, and educational attainment; retain roughly four-fifths of their salary association after adjusting for occupational category. The composite Technical Skills Score is silent because positive specializations (Information Security, Cloud Computing) and negative specializations (Network Administration, Technical Support) cancel within the index; disaggregation reveals the underlying heterogeneity. The study provides new empirical evidence separating HCT productivity–access channels at the predictor level and identifies seniority track as a dominant axis of Saudi IT salary stratification.