Climate change and crop production nexus in Somalia: an empirical evidence from ARDL technique

Warsame, Abdimalik Ali; Sheik-Ali, Ibrahim Abdukadir; Ali, Abdullahi Osman; Sarkodıe, Samuel Asumadu

doi:10.1007/s11356-020-11739-3

Cited by 149 publications

(117 citation statements)

References 33 publications

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“…Following the previous comprehensive studies of , Pickson et al (2020), and Warsame et al (2021), this study explore the both short-term and long-term effects of climatic factors, such as carbon dioxide emission, average temperature, and average rainfall on agricultural output, cereal production and cereal yield in the case of India. In addition, this study also examine the impacts of non-climatic factors including land under cereal production, energy consumption, financial development, gross capital formation, and agricultural rural labour on agricultural output, cereal production and cereal yield.…”

Section: Model Specificationmentioning

confidence: 99%

Modeling the Impact of Climate and Non-Climatic Factors on Cereal Production: Evidence from Indian Agriculture

Chandio

Jiang

Amin

et al. 2021

Preprint

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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. 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-climatc 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.

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Section: Model Specificationmentioning

confidence: 99%

Modeling the Impact of Climate and Non-Climatic Factors on Cereal Production: Evidence from Indian Agriculture

Chandio

Jiang

Amin

et al. 2021

Preprint

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“…While Ahsan et al (2020) demonstrated that energy consumption, labour force, cultivated area and CO2 are the main determinants of agriculture productivity and CO2 positively impact agriculture productivity. Likewise, Warsame (2021) explained mean temperature and CO2 has negatively influenced agriculture productivity in Somalia.…”

Section: Introductionmentioning

confidence: 99%

“…The developing nations are more vulnerable than developed countries due to more extensive dependence on agriculture sector for livelihood, lack of technological advancement and lack of adaptation policies of climate change on agriculture production (Praveen & Sharma, 2020;Warsame, 2021). However, Chandio et al, (2021) stated that the increase in temperature and financial development, respectively has negative and positive impact on cereal production in Pakistan.…”

Section: Introductionmentioning

confidence: 99%

Does Climate Change Asymmetrically Affect Rice Productivity In India? New Insight From NARDL Cointegration Approach

Baig

Chandio

Salam

2021

Preprint

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This article attempt to answer the question "whether the dynamic relationship between climate change and rice productivity is symmetrical or asymmetrical" using data from 1990-2017 in India. First, we test the symmetrical and long-run dynamic relationship using the Autoregressive Distributed Lags (ARDL) model and test the asymmetrical and cointegration relationship based on Nonlinear Auto-Regressive Distributed Lag (NARDL) technique. The results of the ARDL model indicates that no symmetrical relationship between the variables in long-run. Whereas outcomes of the NARDL bound test reveal that there is long-run asymmetrical impact of climate change on rice productivity. The positive and negative shock of climate change has affected the rice productivity by different magnitude in India. The Wald statistics confirm asymmetric relationship between rice productivity and climate change in the long-run while only short-run asymmetrical relationships exist between rainfall and rice productivity in India.Furthermore, dynamic multipliers indicate that negative component of rainfall and temperature has a dominant effect over the positive component on rice productivity. To the best of the author's knowledge, no studies have been done to assess both symmetrical and asymmetrical dynamic relationships between climate change and rice productivity using ARDL and NARDL cointegration approaches in India's context. This study will help frame the environmental policies and strategy to cope with climate change in India's agriculture productivity.

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“…Moreover, environmental degradation-as a result of deforestation-releases carbon dioxide, leading to a rise in temperature and climate change (Magazzino, et al, 2021). It also poses a threat to agriculture production, livelihood systems, and food security (Warsame, Sheik-Ali, Ali, & Sarkodie, 2021 (Bölük & Mert, 2014;Farhani & Shahbaz, 2014;Shafiei & Salim, 2014;Jamel & Abdelkader, 2016;Ssali, Du, Mensah, & Hongo, 2019;Nathaniel & Iheonu, 2019).…”

Section: Introductionmentioning

confidence: 99%

Asymmetric Impact of Energy Utilization and Economic Development on Environmental Degradation in Somalia

Warsame¹,

Sarkodıe

2021

Preprint

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While there are enormous studies on climate change in stable countries, climate policy perspectives from conflict-prone regions including Somalia are limited. This study investigates the asymmetric impact of energy and economic growth on environmental degradation in Somalia—by employing nonlinear autoregressive distributed lag model (NARDL) and causal techniques from 1985 to 2017. We find asymmetric long-term cointegration among the variables, whereas energy consumption and economic growth asymmetrically affect environmental degradation. Besides, the causal inferences reveal unidirectional causality from environmental pollution to positive change in energy consumption. Additionally, we find unidirectional causality from negative shock in economic growth to positive shock in economic growth. Moreover, a bidirectional causality is observed between population growth and negative change in economic growth. A unidirectional causality is confirmed from positive shock in economic growth to population growth—from negative change in economic growth to negative shock in energy consumption—from positive change in economic growth to positive shock in energy consumption—and negative change in energy consumption to population growth. This calls for the implementation of clean energy investment policies, good farming methods, and improved grazing land policies. The adoption of these policies will improve both environmental quality and sustained economic development.

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Climate change and crop production nexus in Somalia: an empirical evidence from ARDL technique

Cited by 149 publications

References 33 publications

Modeling the Impact of Climate and Non-Climatic Factors on Cereal Production: Evidence from Indian Agriculture

Modeling the Impact of Climate and Non-Climatic Factors on Cereal Production: Evidence from Indian Agriculture

Does Climate Change Asymmetrically Affect Rice Productivity In India? New Insight From NARDL Cointegration Approach

Asymmetric Impact of Energy Utilization and Economic Development on Environmental Degradation in Somalia

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