Abstract

This study assesses the relationship between economic performance and environmental sustainability by taking into account the role of energy consumption, urbanization, and trade openness in Brazil by using data spanning from 1965 to 2019. The study is distinct from previously documented studies in literature in terms of scope for Brazil, where few entries have been recorded. The major objectives are to address the questions: (a) Is there a long-run connection between the variables under consideration? (b) Can CO2 emissions, trade openness, and energy consumption predict economic performance of Brazil? (c) What is the connection between economic growth and the independent variables at different frequencies and time-period? Furthermore, the study utilized dynamic ordinary least square (DOLS), fully modified ordinary least square (FMOLS), Maki Cointegration, and autoregressive distributed lag (ARDL) to capture the long-run association between the variables of interest. Also, we used the Wavelet coherence and Gradual-shift causality tests to capture the causal linkage between economic growth and the regressors. The advantage of the wavelet coherence test is that it can capture causal linkage between series at different frequencies and periods. The outcome of both Maki cointegration and ARDL bounds testing to cointegration affirms the presence of long-run interaction among the parameters of interest. Furthermore, the outcomes of the DOLS and FMOLS revealed that energy consumption, CO2 emissions, and urbanization exert positive impacts on economic growth in Brazil while there is no significant connection between trade openness and economic growth. Moreover, Gradual shift causality test outcomes disclosed that urbanization, trade openness, CO2 emissions and energy usage can predict the economic performance of Brazil. The outcomes of the wavelet coherence test give credence to the FMOLS, DOLS, and Gradual shift causality tests.

Highlights

  • Both industrialized and emerging economies share the aim of achieving economic growth and sustainable development

  • The present research tends to close this gap in the literature by exploring CO2 emissions (CO2 ) and real growth (GDP) in Brazil, while accounting for the role of urbanization (URB), trade openness (TR), and energy usage (EC) utilizing data stretching between 1965 and 2019

  • The Causality results confirm that energy consumption causes GDP in Brazil, validating that energy usage is a key contributing factor of GDP. This result resonates with the outcomes of Ali et al [53] for the case of Nigeria and Shahbaz et al [90] in Pakistan

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Summary

Introduction

Both industrialized and emerging economies share the aim of achieving economic growth and sustainable development. Argued challenge to achieving the required degree of sustainable development, the assoEnvironmental deterioration is growing as a consequence of global warming and cliciation between environmental degradation and economic growth is complex [1]. The country’s NDC is targeted at reducing 37% of its 2005 emitted GHG level by 2025 In both theoretical and empirical studies, the effect of trade on GDP remains an area of continuous debate. Given the rapid pace of population development, substantial attempts have been made to mitigate the negative effects of global warming while maintaining GDP growth This is what inspired the investigators to delve at the variables examined in this study, with the intention of utilizing the results to provide policy suggestions to various policymakers. The organization of the study is as follows: Section 2 presents synopsis of prior studies; Data and methodology are presented in Section 3; Section 4 presents empirical analyses and discussion; Section 5 depicts conclusion and policy recommendation

Economic Growth and CO2 Emission Relationship
Economic Growth and Energy Consumption Relationship
Economic Growth and Trade Openness Relationship
Economic Growth and Urbanization Relationship
Theoretical Framework
Data and Methodology
Unit Root Test
Maki Co-Integration Test
ARDL Approach
Wavelet Approach
Gradual Shift Causality
Findings and Discussion
Conclusions
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