The effects of time preferences on farmers’ energy-saving and emission-reducing behavior of agricultural machinery in a gain-loss dual context: Evidence from rural China

Amid climate change and agricultural modernization, farmers display heterogeneous preferences toward energy-saving and emission-reducing practices in agricultural machinery. However, the role of time preferences within a gain–loss framework remains underexplored. This study employed lottery-based experiments using the Double Multiple Price List and Convex Time Budget methods to measure farmers’ time preferences under dual gain–loss conditions. Boosted regression trees and partial dependency plots were applied to estimate the relative influence and nonlinear marginal effects of time preference parameters on energy-saving behaviors, supplemented by one-at-a-time sensitivity and subgroup analyses to assess model robustness and group heterogeneity. Results show that only 63.50 % of farmers exhibit desirable behaviors. In the gain context, farmers exhibit short-term present bias and a long-term preference for immediate gains, reflecting quasi-hyperbolic discounting; in the loss context, they also show present bias and are inclined to sacrifice present losses to future ones in the long term. Overall, both present bias and subjective discount rates exert significant, directionally consistent nonlinear effects. In the loss context, present bias and subjective discount rate positively influence behavior, contributing 9.54 % and 31.48 %, respectively. Conversely, the gain-context subjective discount rate shows a strong negative effect (−37.39 %), while gain-context present bias, though generally positive (21.59 %), follows a non-monotonic trajectory—first rising, then declining—due to distributional skewness and boundary effects. Heterogeneity analysis reveals distinct patterns across education, income, and household composition. These findings deepen understanding of time preference effects on energy-efficient decisions in rural areas and offer policy insights to enhance energy-saving outcomes in agricultural machinery use across similar global contexts.