The relationship between carbon dioxide emission and crop and livestock production indexes: a dynamic common correlated effects approach.

Rapid increase in carbon dioxide emission triggers climate change, while climate change poses a threat to food security. On the other hand, emission increase as a result of agricultural production continues. Considering this cycle, it is thought that examining the relationship between agricultural production and carbon dioxide emissions can help countries take emission-reducing measures and develop policies to ensure food safety. With this thought, a common correlated effect estimator was used in this study to explain the relationship between crop and livestock production index and carbon dioxide emission of 184 countries with the use of data for the period of 1998-2014. Countries were classified under four categories: low-income countries, lower middle-income countries, upper middle-income countries and high-income countries. According to DCCE test results, it was reported that a 1% increase in crop production index had effect on CO2 emission only in lower middle-income countries. A 1% increase in livestock production index, on the other hand, was reported to increase CO2 emission rates by 0.28, 0.49, and 0.39 in lower middle-income, upper middle-income, and high-income countries, respectively. When evaluated in general, it could be stated that livestock breeding has a higher effect on CO2 emission in agricultural production. The findings of the present study revealed that countries need to improve agricultural production methods in ways to minimize the positive association between vegetative and livestock production in accordance with their level of development, to adopt more environment-friendly agricultural technologies and to endorse international environmental policies.

Citation

Merve Ayyildiz, Gulistan Erdal. The relationship between carbon dioxide emission and crop and livestock production indexes: a dynamic common correlated effects approach. Environmental science and pollution research international. 2021 Jan;28(1):597-610

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PMID: 32815016

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