Agricultural Involution in Indonesia: A Generalized Structured Component Analysis (GSCA) Approach with Land and Labor Interaction Effects

Abstract

Indonesian agriculture faces an economic paradox where the sector remains a primary employer despite low wages and stagnant GDP contributions compared to industry. This study aims to analyze and quantify the phenomenon of agricultural involution in Indonesia from 2017 to 2023 by simultaneously examining the effects of land, labor, productivity, and land–labor interaction on agricultural output across 34 provinces. Generalized Structured Component Analysis (GSCA) with an Alternating Least Squares (ALS) approach is employed because of its ability to handle mixed formative–reflective measurement models and accommodate latent variable interaction effects —  capabilities unavailable in conventional covariance-based SEM or linear regression. The results indicate that land capacity is the dominant determinant of agricultural output with a path coefficient of 0.958, signaling that growth remains extensive rather than intensive. Crucially, labor intensity is found to have a significant negative effect on productivity and total output, confirming the law of diminishing marginal returns and the presence of labor surpluses that exceed optimal points. Furthermore, the interaction between land and labor yields a significant negative coefficient (-0.109), proving that demographic pressure on limited land exacerbates inefficiency and output destruction. Spatial post-hoc analysis indicates that agricultural involution is no longer confined to Java but has evolved into a national phenomenon, as demonstrated by the absence of significant disparities in labor-to-land ratios and productivity between Java and other regions. These findings suggest that sustainable transformation requires integrated policies for land protection, labor restructuring toward non-agricultural sectors, and technological modernization to break the cycle of involution.