TY - JOUR
T1 - Modeling the impact of climatic and non-climatic factors on cereal production
T2 - evidence from Indian agricultural sector
AU - Chandio, Abbas Ali
AU - Jiang, Yuansheg
AU - Amin, Asad
AU - Akram, Waqar
AU - Ozturk, Ilhan
AU - Sinha, Avik
AU - Ahmad, Fayyaz
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2022/2
Y1 - 2022/2
N2 - The underpinned study examines the effects of climatic and non-climatic factors on Indian agriculture, cereal production, and yield using the country-level time series data of 1965–2015. With the autoregressive distributed lag (ARDL) bounds testing approach, the long-term equilibrium association among the variables has been explored. The results reveal that climatic factors like CO2 emissions and temperature adversely affect agricultural output, while rainfall positively affects it. Likewise, non-climatic factors, including energy used, financial development, and labor force, affect agricultural production positively in the long run. The estimated long-run results further demonstrate that CO2 emissions and rainfall positively affect both cereal production and yield, while temperature adversely affects them. The results exhibit that the cereal cropped area, energy used, financial development, and labor force significantly and positively impact the long-run cereal production and yield. Finally, pairwise Granger causality test confirmed that both climatic and non-climatic factors are significantly influencing agriculture and cereal production in India. Based on these results, policymakers and governmental institutions should formulate coherent adaptation measures and mitigation policies to tackle the adverse climate change effects on agriculture and its production of cereals.
AB - The underpinned study examines the effects of climatic and non-climatic factors on Indian agriculture, cereal production, and yield using the country-level time series data of 1965–2015. With the autoregressive distributed lag (ARDL) bounds testing approach, the long-term equilibrium association among the variables has been explored. The results reveal that climatic factors like CO2 emissions and temperature adversely affect agricultural output, while rainfall positively affects it. Likewise, non-climatic factors, including energy used, financial development, and labor force, affect agricultural production positively in the long run. The estimated long-run results further demonstrate that CO2 emissions and rainfall positively affect both cereal production and yield, while temperature adversely affects them. The results exhibit that the cereal cropped area, energy used, financial development, and labor force significantly and positively impact the long-run cereal production and yield. Finally, pairwise Granger causality test confirmed that both climatic and non-climatic factors are significantly influencing agriculture and cereal production in India. Based on these results, policymakers and governmental institutions should formulate coherent adaptation measures and mitigation policies to tackle the adverse climate change effects on agriculture and its production of cereals.
KW - ARDL method
KW - Agricultural output
KW - Cereal production
KW - Climate change
KW - India
UR - http://www.scopus.com/inward/record.url?scp=85116423170&partnerID=8YFLogxK
U2 - 10.1007/s11356-021-16751-9
DO - 10.1007/s11356-021-16751-9
M3 - Article
C2 - 34617217
AN - SCOPUS:85116423170
SN - 0944-1344
VL - 29
SP - 14634
EP - 14653
JO - Environmental Science and Pollution Research
JF - Environmental Science and Pollution Research
IS - 10
ER -