Uncovering nonlinear interplays: how rainfall, mechanization and temperature uniquely impact maize yields in Bangladesh? Evidence from NARDL and MTNARDL

PurposeThis study aims to investigate the complex, nonlinear relationships between climatic and non-climatic factors and their influence on maize productivity in Bangladesh. The research objectives are to assess the short- and long-term effects of rainfall, mechanization and temperature on maize yields, examine their interactive dynamics and provide policy insights to enhance agricultural resilience.Design/methodology/approachEmploying a nonlinear autoregressive distributed lag (NARDL) model and a multiple threshold NARDL (MTNARDL) approach, the study analyzes annual data from 1980 to 2020. This methodological framework allows for the examination of asymmetric and threshold-dependent effects of the key variables on maize supply.FindingsThe findings reveal significant nonlinearities in the impacts of rainfall, mechanization, and temperature on maize yields. Positive rainfall shocks substantially boost long-term productivity, while negative deviations have negligible effects. Mechanization exhibits complex dynamics, with short-term benefits offset by adjustment costs but long-term positive impacts across regimes. Temperature, on the other hand, imposes uniformly negative effects, with major shocks causing greater immediate harm and persistent yield reductions. Population growth and carbon emissions further exacerbate maize supply challenges. Diagnostic tests confirmed the statistical model was robust.Originality/valueThis study provides novel insights into the nonlinear, regime-specific interplays between climatic and non-climatic factors and their implications for maize production in Bangladesh. The results challenge the predominant focus on linear relationships in the literature and offer actionable policy recommendations to enhance the resilience of maize-based food systems in the face of climate change.