Early Academic Capital as the Causal Origin of Dropout in Constrained Educational Systems -- Evidence from Longitudinal Data and Structural Causal Models
Hugo Roger Paz

TL;DR
This study uses longitudinal data and causal models to show that low early academic progress significantly increases dropout risk, emphasizing early trajectory issues over isolated academic failures.
Contribution
It introduces a causal computational approach to identify early academic capital as the primary cause of dropout in constrained educational systems.
Findings
Low early academic capital increases dropout probability by over 25 percentage points.
The effect of early academic capital is roughly twice as large as that of later academic failures.
Early trajectory misalignment is a key factor in dropout, shifting intervention focus to early stages.
Abstract
Dropout in higher education is commonly analysed through observable academic events such as course failure or repetition. However, these event-based perspectives may obscure the underlying structural dynamics that shape student trajectories. In this study, we adopt a causal computational social science approach to identify the origins of dropout in a constrained engineering curriculum. Using longitudinal administrative data from 16,868 students who survived to their second active term, and a leakage-free panel design, we estimate the causal effect of early academic capital accumulation on three-year dropout. Treatment is defined as low early progress (passing at most 1 subject by the end of the second term). We employ G-estimation of structural nested mean models, complemented by marginal structural models with inverse probability weighting. We find a large and robust causal effect: low…
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