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<p>India is the second-largest wheat producer in the world. However, the dynamics of per capita wheat production (PCPW) and its vulnerability to climatic stress remain poorly understood. Existing studies assume a linear relationship in the agro-climate nexus, but seldom assess how different temperature regimes and demographic factors affect PCPW. This study fills this gap by analysing the determinants of PCPW from 1951 to 2020 using the ARDL, Threshold Autoregression (TAR), and Granger causality approaches. The ARDL results indicate a long-run positive effect of maximum temperature (0.19%) and rainfall (0.08%) on PCPW, while per-capita land under wheat (PCLW), per-capita CO₂ emissions (PCO₂), and rural population share (SRP) remain statistically insignificant. Short-run estimates, however, reveal strong inertia and mixed thermal effects, where immediate warming increases PCPW by 4&#xa0;kg/person while lagged heat reduces it by 5&#xa0;kg/person. The TAR model identifies a significant temperature threshold at 30.73&#xa0;°C. Below this threshold, PCLW (1.96) and PCO₂ (0.06) have a positive influence on PCPW, reflecting legacy gains from irrigated, mechanized regions. Above the threshold, PCO₂ turns negative (-0.04), and SRP exerts a detrimental impact (-0.26), indicating compounded heat stress and reduced adaptive capacity in warmer zones. Granger causality confirms unidirectionality from rainfall to PCPW and a bidirectional link between temperature and PCPW. Overall, the findings highlight non-linear climatic vulnerabilities and the need for region-specific irrigation, climate-resilient varieties, timely sowing, and strengthened climate information systems to safeguard wheat availability in a warming India.</p>

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Climatic and demographic interactions: implications for wheat production dynamics

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月19日

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  • Keshav Soni,
  • V. Sivasankar,
  • Ramadas Sendhil

摘要

India is the second-largest wheat producer in the world. However, the dynamics of per capita wheat production (PCPW) and its vulnerability to climatic stress remain poorly understood. Existing studies assume a linear relationship in the agro-climate nexus, but seldom assess how different temperature regimes and demographic factors affect PCPW. This study fills this gap by analysing the determinants of PCPW from 1951 to 2020 using the ARDL, Threshold Autoregression (TAR), and Granger causality approaches. The ARDL results indicate a long-run positive effect of maximum temperature (0.19%) and rainfall (0.08%) on PCPW, while per-capita land under wheat (PCLW), per-capita CO₂ emissions (PCO₂), and rural population share (SRP) remain statistically insignificant. Short-run estimates, however, reveal strong inertia and mixed thermal effects, where immediate warming increases PCPW by 4 kg/person while lagged heat reduces it by 5 kg/person. The TAR model identifies a significant temperature threshold at 30.73 °C. Below this threshold, PCLW (1.96) and PCO₂ (0.06) have a positive influence on PCPW, reflecting legacy gains from irrigated, mechanized regions. Above the threshold, PCO₂ turns negative (-0.04), and SRP exerts a detrimental impact (-0.26), indicating compounded heat stress and reduced adaptive capacity in warmer zones. Granger causality confirms unidirectionality from rainfall to PCPW and a bidirectional link between temperature and PCPW. Overall, the findings highlight non-linear climatic vulnerabilities and the need for region-specific irrigation, climate-resilient varieties, timely sowing, and strengthened climate information systems to safeguard wheat availability in a warming India.