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Impact of climate change on Indian agriculture: new evidence from the autoregressive distributed lag approach

By: Contributor(s): Material type: TextTextPublication details: Asia-Pacific Journal of Regional Science; 2024Description: 377-394ISSN:
  • 2509-7954
Subject(s): Online resources: Summary: Climate change constitutes one of the most critical challenges of the contemporary period and can affect various sectors of economies across the globe, the agricultural sector is not an exception. This study aimed to assess the impact of climate change on India's agricultural sector from 1990 to 2020. The autoregressive distributed lag (ARDL) approach was utilized to determine the short-run and long-run relationships between variables such as carbon dioxide emissions, temperature, energy utilization, and fertilizer consumption. The ARDL method and the Johansen and Juselius cointegration test both supported the existence of a significant and long relationship among the selected variables. The estimated short- and long-run findings showed that carbon dioxide emissions (CO2), temperature, and energy consumption affect agricultural yield positively and significantly. These findings have several implications for the Indian economy. With a large population dependent on agriculture, improved productivity can directly impact food security and rural income, consequently leading to the country's overall economic development. Enhanced agricultural output due to these factors may potentially lead to surplus production, allowing India to export more agricultural produce. This can positively impact the country's trade balance and generate revenue through exports.
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Article Index Article Index Dr VKRV Rao Library Vol. 8, No. 2 Not for loan AI497

Climate change constitutes one of the most critical challenges of the contemporary period and can affect various sectors of economies across the globe, the agricultural sector is not an exception. This study aimed to assess the impact of climate change on India's agricultural sector from 1990 to 2020. The autoregressive distributed lag (ARDL) approach was utilized to determine the short-run and long-run relationships between variables such as carbon dioxide emissions, temperature, energy utilization, and fertilizer consumption. The ARDL method and the Johansen and Juselius cointegration test both supported the existence of a significant and long relationship among the selected variables. The estimated short- and long-run findings showed that carbon dioxide emissions (CO2), temperature, and energy consumption affect agricultural yield positively and significantly. These findings have several implications for the Indian economy. With a large population dependent on agriculture, improved productivity can directly impact food security and rural income, consequently leading to the country's overall economic development. Enhanced agricultural output due to these factors may potentially lead to surplus production, allowing India to export more agricultural produce. This can positively impact the country's trade balance and generate revenue through exports.

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