Asymmetric Effects of Energy Inflation, Agri-inflation and CPI on Agricultural Output: Evidence from NARDL and SVAR Models for the UK

Soliman, Alaa M.; Lau, Chi Keung; Cai, Yifei; Sarker, Provash Kumer; Dastgir, Shabbir

doi:10.1016/j.eneco.2023.106920

Cited by 13 publications

(6 citation statements)

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“…The results under the PP test reveal that EDU and Internet series are I (0) stationary, while DCO 2 , HT, and FD series are I (1) stationary. The results of unit root tests fulfill the prerequisite of the ARDL and NARDL approaches [53][54][55][56][57][58][59][60][61][62][63][64][65][66][67], which states that the variable series must meet the modeling requirements of the first order and below without unit roots (stationary or first-order stationary). Table 4 lists the results of the Brock-Dechert-Scheinkman (BDS) test.…”

Section: Resultsmentioning

confidence: 73%

“…As previously stated, Equation (2) assumes that the effects of variable changes on CO 2 emissions are symmetric; thus, this paper uses the non-linear autoregressive distributed lag (NARDL) model developed by Shin and Yu [33]. The NARDL model is an advanced method based on an ARDL approach, which allows the nonlinear asymmetry and cointegration relationship of small samples to be discussed in a single equation, in order to identify the effect of decomposition of explanatory variables into positive and negative changes on the explained variables [54][55][56][57][58]. In the extant literature, the NARDL model is widely used in the analysis of environmental problems [59][60][61][62][63][64][65][66][67].…”

Section: The Non-linear Autoregressive Distributed Lag (Nardl) Modelmentioning

confidence: 99%

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Green Household Technology and Its Impacts on Environmental Sustainability in China

Meng,

Zhang,

Wang

et al. 2023

Sustainability

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China has made a commitment to achieve carbon neutrality by 2060, and promoting a green lifestyle is an essential means to this end. The primary aim of this study is to investigate the asymmetric impact of green household technology on environmental sustainability in China. To that end, we have employed linear and non-linear auto-regressive distributed lag models to identify this complicated effect. The empirical results suggest that green household technology’s positive change exerts significant and negative effect on carbon emission in the short and long terms. And the impacts of green household technology’s negative change on carbon emission are significantly negative but smaller than its positive change in the long run, while insignificant in the short term. The estimates endorse the asymmetric impact of green household technology on carbon emissions both in the short and long term. This finding suggests that the improvement of green household technology can reduce carbon emissions, while a decline in it causes carbon emissions to rise, and technological retrogression plays a less influential role than its development. This research is a groundbreaking point in discussing the way towards environmental sustainability from a green household technology perspective, which considers the asymmetric effect and provides meaningful insights for China to achieve sustainable development.

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Section: Resultsmentioning

confidence: 73%

Section: The Non-linear Autoregressive Distributed Lag (Nardl) Modelmentioning

confidence: 99%

Green Household Technology and Its Impacts on Environmental Sustainability in China

Meng,

Zhang,

Wang

et al. 2023

Sustainability

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“…Here, then, we have an obvious link between energy prices and fundamental macroeconomic categories (growth, inflation, unemployment, the exchange rate and the fiscal position of states). In turn, agflation itself should also be implicitly linked to such general phenomena as globalisation, international trade and geopolitical risk [11]. Of course, the links between agflation and agricultural production should not be lost from sight.…”

Section: Review Of Literature and Context Analysismentioning

confidence: 99%

Cost of Energy Consumption and Return of Excise Tax on Motor Fuels vs. the Durability of Operations and Financial Sustainability in Polish Agriculture

Kulawik,

Soliwoda,

Kurdyś-Kujawska

et al. 2023

Energies

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For the European Union, the course of the Community’s energy and climate policy as well as changes in the objectives and priorities of the Common Agricultural Policy, as reflected, among others, in rural development programs subject to ex ante, environmental and ex post evaluation, should be considered. Individual EU countries are still implementing their own programs focused on improving energy efficiency, energy modernisation and supporting renewable energy, and they also intervene in the energy market on an ad hoc basis, as was the case after the outbreak of the war in Ukraine. This article fits into such a broadly understood research perspective, and its primary goal is to identify the impact of the costs of energy consumption and the reimbursement of excise tax on motor fuels on the operational durability and financial sustainability of 103 farms belonging to the Polish FADN network, which in 2017–2021 implemented modernisation projects under the rural development program. Logistic and linear multivariate regression were used to estimate the strength, direction and significance of correlation relationships. It was found that relative energy costs were significantly negatively correlated with financial sustainability only in the linear model, while the impact of excise tax return was positive but not significant. Thus, an empirical proof of the advisability of a possible public intervention aimed at making farmers’ access to energy cheaper was obtained. All public interventions in agricultural energy use should be subject to careful and systematic ex ante, mid-term and ex post assessments based on sound program theory. It is necessary to identify the cause-and-effect chains, in which the regression proposed in the article may be helpful.

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“…On the one hand, pork is an important part of residents' daily consumption. Changes in pork prices will significantly affect the consumer price index (CPI) in China [1,2]. More seriously, the rise in pork prices may lead to an overall and sustained increase in prices, which in turn will cause inflation [3].…”

Section: Introductionmentioning

confidence: 99%

“…(1) This paper first uses the latest optimization algorithm, SSA (Sparrow Search Algorithm), to optimize the MinLeafSize of the decision tree, reduce the overfitting risk of the model, overcome the limitations of single model prediction, and explore a new path to solve the problem of the easy overfitting of the decision tree. (2) In this paper, the correlation coefficients between various variables are measured using the Pearson correlation coefficient and visually expressed via thermal maps. (3) Different from the traditional method of optimizing hyperparameters on the training set, this study divided the dataset into three categories and updated the search strategy by calculating the MAE values of the validation set and the training set.…”

Section: Introductionmentioning

confidence: 99%

A Pork Price Prediction Model Based on a Combined Sparrow Search Algorithm and Classification and Regression Trees Model

Qin,

Yang,

Zhang

2023

Applied Sciences

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The frequent fluctuation of pork prices has seriously affected the sustainable development of the pork industry. The accurate prediction of pork prices can not only help pork practitioners make scientific decisions but also help them to avoid market risks, which is the only way to promote the healthy development of the pork industry. Therefore, to improve the prediction accuracy of pork prices, this paper first combines the Sparrow Search Algorithm (SSA) and traditional machine learning model, Classification and Regression Trees (CART), to establish an SSA-CART optimization model for predicting pork prices. Secondly, based on the Sichuan pork price data during the 12th Five-Year Plan period, the linear correlation between piglet, corn, fattening pig feed, and pork price was measured using the Pearson correlation coefficient. Thirdly, the MAE fitness value was calculated by combining the validation set and training set, and the hyperparameter “MinLeafSize” was optimized via the SSA. Finally, a comparative analysis of the prediction performance of the White Shark Optimizer (WSO)-CART model, CART model, and Simulated Annealing (SA)-CART model demonstrated that the SSA-CART model has the best prediction of pork price (compared with a single decision tree, R2 increased by 9.236%), which is conducive to providing support for pork price prediction. The accurate prediction of pork prices with an optimized machine learning model is of great practical significance for stabilizing pig production, ensuring the sustainable growth of farmers’ income, and promoting sound economic development.

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Asymmetric Effects of Energy Inflation, Agri-inflation and CPI on Agricultural Output: Evidence from NARDL and SVAR Models for the UK

Cited by 13 publications

References 46 publications

Green Household Technology and Its Impacts on Environmental Sustainability in China

Green Household Technology and Its Impacts on Environmental Sustainability in China

Cost of Energy Consumption and Return of Excise Tax on Motor Fuels vs. the Durability of Operations and Financial Sustainability in Polish Agriculture

A Pork Price Prediction Model Based on a Combined Sparrow Search Algorithm and Classification and Regression Trees Model

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