Dual Stressors in Engineering Education: Lagged Causal Effects of Academic Staff Strikes and Inflation on Dropout within the CAPIRE Framework

TL;DR

This paper empirically validates the dual-stressor hypothesis in engineering education, showing how academic staff strikes and inflation jointly influence student dropout through causal analysis and machine learning methods.

Contribution

It introduces a causal validation of the dual-stressor hypothesis using advanced machine learning techniques in a long-cycle engineering program.

Findings

Strikes two semesters earlier significantly impact dropout.

The interaction between strikes and inflation at entry is a robust predictor.

Macro shocks act as coupled stressors affecting dropout risk.

Abstract

This study provides a causal validation of the dual-stressor hypothesis in a long-cycle engineering programme in Argentina, testing whether academic staff strikes (proximal shocks) and inflation (distal shocks) jointly shape student dropout. Using a leak-aware longitudinal panel of 1,343 students and a manually implemented LinearDML estimator, we estimate lagged causal effects of strike exposure and its interaction with inflation at entry. The temporal profile is clear: only strikes occurring two semesters earlier have a significant impact on next-semester dropout in simple lagged logit models (ATE = 0.0323, p = 0.0173), while other lags are negligible. When we move to double machine learning and control flexibly for academic progression, curriculum friction and calendar effects, the main effect of strikes at lag 2 becomes small and statistically non-significant, but the interaction between strikes and inflation at entry remains positive and robust (estimate = 0.0625, p = 0.0033). A placebo model with a synthetic strike variable yields null effects, and a robustness audit (seed sensitivity, model comparisons, SHAP inspection) confirms the stability of the interaction across specifications. SHAP analysis also reveals that Strikes_Lag2 and Inflation_at_Entry jointly contribute strongly to predicted dropout risk. These findings align with the CAPIRE-MACRO agent-based simulations and support the view that macro shocks act as coupled stressors mediated by curriculum friction and financial resilience rather than isolated events.