Another Look into the Relationship between Economic Growth, Carbon Emissions, Agriculture and Urbanization in Thailand: A Frequency Domain Analysis
Mário Nuno Mata,
Seun Damola Oladipupo,
Rjoub Husam,
Joaquim António Ferrão,
Mehmet Altuntaş,
Jéssica Nunes Martins,
Dervis Kirikkaleli,
Rui Miguel Dantas,
António Morão Lourenço
Affiliations
Mário Nuno Mata
ISCAL-Instituto Superior de Contabilidade e Administração de Lisboa, Instituto Politécnico de Lisboa, Avenida Miguel Bombarda 20, 1069-035 Lisbon, Portugal
Seun Damola Oladipupo
Department of Earth Science, Faculty of Science, Olabisi Onabanjo University, Ago-Iwoye 110262, Ogun State, Nigeria
Rjoub Husam
Department of Accounting and Finance, Faculty of Economics and Administrative Sciences, Cyprus International University, Mersin 10, Haspolat 99040, Turkey
Joaquim António Ferrão
ISCAL-Instituto Superior de Contabilidade e Administração de Lisboa, Instituto Politécnico de Lisboa, Avenida Miguel Bombarda 20, 1069-035 Lisbon, Portugal
Mehmet Altuntaş
Department of Economics, Administrative and Social Sciences, Faculty of Economics, Nisantasi University, Istanbul 34398, Turkey
Jéssica Nunes Martins
NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, 1099-085 Lisbon, Portugal
Dervis Kirikkaleli
Department of Banking and Finance, Faculty of Economics and Administrative Sciences, European University of Lefke, Northern Cyprus, TR-10, Mersin 99010, Turkey
Rui Miguel Dantas
ISCAL-Instituto Superior de Contabilidade e Administração de Lisboa, Instituto Politécnico de Lisboa, Avenida Miguel Bombarda 20, 1069-035 Lisbon, Portugal
António Morão Lourenço
Polytechnic Institute of Santarém, School of Management and Technology (ESGTS-IPS), 2001-904 Santarém, Portugal
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.
