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<p>Climate anomalies pose substantial threats to sustainable agriculture, primarily in emerging economies where agricultural systems are acutely vulnerable to temporal weather variabilities and operational inefficiencies. Against this backdrop, the current study integrates a Ricardian framework with farm-level Stochastic Frontier analysis to assess the economic impacts of climate dynamics while accounting for farmers’ technical inefficiencies in KP province, Pakistan. Using farm-level survey data from 762 agricultural households (2024 cropping season) across the five AEZs, we estimated the climate-revenue models under both the current and projected climate scenarios. Results indicate that a 1&#xa0;°C rise in summer temperature reduces revenue by $70, while moderate winter warming elevates the revenue by $47. Precipitation impacts followed a non-linear and spatially heterogenous trend, as summer rainfall posed partial benefits while winter precipitation led to diminishing returns. Future projections under CMIP6 climate models revealed potential revenue gains in mountainous areas while substantial losses in southern parts due to thermal stress and precipitation shortfalls. Inefficiency analysis indicated hidden economic losses, demonstrating that efficiency improvements can significantly buffer the climate induced revenue shocks. The study suggests evidence-based guidance for zone-specific climate-smart initiatives, institutional development and efficiency-driven investments as core strategies to safeguard farm livelihoods in climate-sensitive areas.</p> Graphical Abstract <p></p>

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Seasonal climate variability, production inefficiencies, and non-linear farm revenue responses: an SFA-Ricardian assessment across KP’s agro-ecological zones, Pakistan

  • 期刊论文

  • 发表日期：

    2026年1月30日

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  • Murtaza,
  • Jing Wang,
  • Waqas Ahmad,
  • Shehzad Muhammad

摘要

Climate anomalies pose substantial threats to sustainable agriculture, primarily in emerging economies where agricultural systems are acutely vulnerable to temporal weather variabilities and operational inefficiencies. Against this backdrop, the current study integrates a Ricardian framework with farm-level Stochastic Frontier analysis to assess the economic impacts of climate dynamics while accounting for farmers’ technical inefficiencies in KP province, Pakistan. Using farm-level survey data from 762 agricultural households (2024 cropping season) across the five AEZs, we estimated the climate-revenue models under both the current and projected climate scenarios. Results indicate that a 1 °C rise in summer temperature reduces revenue by $70, while moderate winter warming elevates the revenue by $47. Precipitation impacts followed a non-linear and spatially heterogenous trend, as summer rainfall posed partial benefits while winter precipitation led to diminishing returns. Future projections under CMIP6 climate models revealed potential revenue gains in mountainous areas while substantial losses in southern parts due to thermal stress and precipitation shortfalls. Inefficiency analysis indicated hidden economic losses, demonstrating that efficiency improvements can significantly buffer the climate induced revenue shocks. The study suggests evidence-based guidance for zone-specific climate-smart initiatives, institutional development and efficiency-driven investments as core strategies to safeguard farm livelihoods in climate-sensitive areas.

Graphical Abstract