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Relationships between agricultural growth and energy consumption in China: Toda–Yamamoto tests

This article analyzed the causal link between the growth in agricultural output value and total primary energy consumption for both the 1953 to 2020 and 1980 to 2020 periods. The main method applied is the Toda–Yamamoto Wald-χ2test. Empirical results show that from 1953 to 2020, feedback existed between the growth in agricultural output and energy use. From 1980 to 2020, unidirectional Granger causality existed from energy consumption to the aggregate economy and agriculture. Thus, the study suggests the growth hypothesis in energy economics. In the short-run, agricultural growth will not increase energy consumption. However, strict energy-saving measures in the agricultural sector may curb its growth. During the period after 1980, agricultural energy use efficiency improved. Energy consumption was a short-run determinant of agricultural growth.
- University of Hong Kong China (People's Republic of)
- University of Hong Kong China (People's Republic of)
- Chengdu University China (People's Republic of)
Energy consumption, Value added, Granger causality, Agricultural growth, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Energy consumption, Value added, Granger causality, Agricultural growth, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).1 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
