Another Look into the Relationship between Economic Growth, Carbon Emissions, Agriculture and Urbanization in Thailand: A Frequency Domain Analysis

Energies

Rjoub Husam¹  Dervis Kirikkaleli²  Seun Damola Oladipupo³  Mehmet Altuntaş⁴  Mário Nuno Mata⁵  Joaquim António Ferrão⁵  Rui Miguel Dantas⁵  Jéssica Nunes Martins⁶  António Morão Lourenço⁷ 

[1] Department of Accounting and Finance, Faculty of Economics and Administrative Sciences, Cyprus International University, Mersin 10, Haspolat 99040, Turkey;Department of Banking and Finance, Faculty of Economics and Administrative Sciences, European University of Lefke, Northern Cyprus, TR-10, Mersin 99010, Turkey;Department of Earth Science, Faculty of Science, Olabisi Onabanjo University, Ago-Iwoye 110262, Ogun State, Nigeria;Department of Economics, Administrative and Social Sciences, Faculty of Economics, Nisantasi University, Istanbul 34398, Turkey;ISCAL-Instituto Superior de Contabilidade e Administração de Lisboa, Instituto Politécnico de Lisboa, Avenida Miguel Bombarda 20, 1069-035 Lisbon, Portugal;NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, 1099-085 Lisbon, Portugal;Polytechnic Institute of Santarém, School of Management and Technology (ESGTS-IPS), 2001-904 Santarém, Portugal;

关键词: agriculture;    urbanization;    economic growth;    CO₂ emissions;    energy use;    Thailand;   

DOI  :  10.3390/en14165132

来源: DOAJ

【 摘 要 】

This empirical study assesses the effect of CO₂ emissions, urbanization, energy consumption, and agriculture on Thailand’s economic growth using a dataset between 1970 and 2018. The ARDL and the frequency domain causality (FDC) approaches were applied to assess these interconnections. The outcome of the bounds test suggested a long-term association among the variables of investigation. The ARDL outcomes reveal that urbanization, agriculture, energy consumption, and CO₂ emissions positively trigger Thailand’s economic growth. Additionally, the frequency domain causality test was used to detect a causal connection between the series. The main benefit of this technique is that it can detect a causal connection between series at different frequencies. To the understanding of the authors, this is the first study in the case of Thailand that will apply the FDC approach to capture the causal linkage between GDP and the regressors. The outcomes of the causality test suggested that CO₂ emissions, urbanization, energy consumption, and agriculture can predict Thailand’s economic growth in the long term. These outcomes have far-reaching implications for economic performance and Thailand’s macroeconomic indicators.

【 授权许可】

Unknown