Determinants of crop insurance demand in Türkiye: a PLS-SEM analysis integrating economic and ecological factors

Introduction Agricultural production in Türkiye is increasingly exposed to risks stemming from climate change, environmental degradation, and economic volatility. Effective insurance mechanisms are crucial for building resilience in this sector. Methods This study analyzes agricultural insurance demand in Türkiye from 2006 to 2023 using Partial Least Squares Structural Equation Modeling (PLS-SEM). Three latent constructs are examined: Agricultural Economy (agricultural GDP, agricultural area, insured area), Insurance Economy (government subsidized premium, total premiums, insured values), and Ecological-Meteorological Risks (Load Capacity Factor and meteorological disasters count). Results The agricultural economy is identified as the strongest predictor of insurance demand, followed by the insurance economy and ecological-meteorological risks. The inclusion of Load Capacity Factor introduces a novel ecological dimension, revealing that insurance demand increases as ecological thresholds are approached. Discussion The study proposes that structural modeling outputs can be utilized in designing index-based insurance premiums. It recommends policy interventions such as ecological risk zoning, vulnerability-based premium subsidies, and adaptive insurance schemes. Integrating ecological indicators into insurance modeling offers a future-oriented approach to sustainable agricultural risk management.

Abstract licence: CC BY

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