LIMITATIONS OF INCOME STABILIZATION INDEX METHODS IN LITHUANIAN GRAIN FARMS: THE CONTEXT OF RISK MANAGEMENT AND MUTUAL SUPPORT FUNDS

Abstract

Income stabilization tools (IST) and mutual risk-sharing funds have been promoted as innovative instruments to address increasing income volatility in European agriculture. Their effectiveness, however, depends critically on whether sector-level income indices accurately represent the income dynamics of individual farms. This study evaluates the limitations of index-based stabilization methods in the context of Lithuanian grain farms, drawing on Lithuanian FADN data (2006–2023) from farm-level gross margins, revenue structures, and long-term yield and price variability. Using correlation analysis, dispersion measures, and simulated income-trigger scenarios, we demonstrate that Lithuanian grain farms exhibit strong heterogeneity across regions, farm sizes, and production structures. As a result, aggregate or sector-level indices fail to track fluctuations in individual income, leading to significant basis risk. The empirical findings show that: (i) farm-level gross margin and revenue variability differ several-fold even within the same region; (ii) correlations between individual farms’ income series are insufficient for effective risk mutualization; (iii) yield and price shocks often co-move at the sector level, creating systemic risks that undermine collective fund solvency; and (iv) index-based triggers distort compensation outcomes, generating overcompensation for some farms and under compensation for others. These results are consistent with the theoretical literature on index insurance, basis risk, and mutual fund design, and highlight the structural constraints on implementing IST-type schemes in grain sectors exposed to spatially widespread, price-driven shocks. Policy implications emphasize the need for: (a) hybrid instruments combining farm-level revenue measures with reinsurance or state guarantees; (b) differentiated contributions based on risk profiles; (c) improved data systems enabling more granular index construction; and (d) cautious expectations regarding IST applicability in highly correlated crop sectors. The study concludes that sector-level index-based income-stabilization tools are unlikely to be effective for Lithuanian grain farms without substantial methodological and institutional adjustments.