Using COGARCH-Filtered Volatility in Modelling Within ARDL Framework

Arı, Yakup

doi:10.1007/978-3-030-54108-8_13

Cited by 1 publication

(1 citation statement)

References 23 publications

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“…In econometrics, the study of cointegration dynamics between a dependent variable and independent variables is often based on two well-established techniques: The Autoregressive Distributed Lag (ARDL) model and the Nonlinear Autoregressive Distributed Lag (NARDL) model. While both approaches have the advantage of capturing the lagged effects of the independent variables on the dependent variable, they offer different advantages in elucidating the nature of the relationship between the variables (Arı 2021;Turhan and Arı 2021). The ARDL model is characterized by its ability to identify long-run equilibrium relationships between variables even if they have different orders of integration, with the exception of I(2) stationarity (Menegaki 2019;Arı 2022).…”

Section: Ardl and Nardl Modelsmentioning

confidence: 99%

The Nexus of Agricultural Efficiency, Renewable Energy Consumption, and Climate Change in Turkey

Çam

2024

Alanya Akademik Bakış

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Agricultural practices and renewable energy consumption have a major impact on the intensity and absorption of heat-trapping greenhouse gases and are closely linked to climate change. The impact of agriculture on climate change is due to the GHGs such as methane, nitrous oxide and carbon dioxide into the atmosphere during the agricultural practices. Therefore, to avoid undesirable effects of agriculture on climate change, it is important to understand the relationship between agricultural activities and greenhouse gases. In this study, we analyze the long-term effects of agricultural efficiency, fertilizer use, and renewable energy consumption on total carbon emissions in Turkey using ARDL/NARDL and CCE methods. The CCE method is used to evaluate the values of agricultural efficiency for Turkey, while ARDL and NARDL models are used to estimate the long-term effects of variables including agricultural efficiency, fertilizer use, renewable energy consumption, GDP, and population on carbon emissions. The results show that improving agricultural efficiency and increasing the share of renewable energy would reduce carbon emissions, while fertilizer use, GDP, and population have negative long-term effects on carbon emissions. In addition, the results of the Wald test indicate asymmetric long-term effects of renewable energy, agricultural efficiency, and fertilizer use on climate change.

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Section: Ardl and Nardl Modelsmentioning

confidence: 99%

The Nexus of Agricultural Efficiency, Renewable Energy Consumption, and Climate Change in Turkey

Çam

2024

Alanya Akademik Bakış

View full text Add to dashboard Cite

show abstract

Using COGARCH-Filtered Volatility in Modelling Within ARDL Framework

Cited by 1 publication

References 23 publications

The Nexus of Agricultural Efficiency, Renewable Energy Consumption, and Climate Change in Turkey

The Nexus of Agricultural Efficiency, Renewable Energy Consumption, and Climate Change in Turkey

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