Drivers of climate change in selected emerging countries: the ecological effects of monetary restrictions and expansions

Abstract

Drivers of environmental quality have recently been identified in a large body of literature. However, the ecological effects of both regimes of monetary policy remain under-explored so far. Moreover, previous studies use limited samples and econometric approaches. Climate change from the empirical perspective of the country’s monetary policy has recently become a promising avenue to investigate. Motivated by the aforementioned research gaps and increasing attention from energy researchers and policy-makers, this research aims to test the monetary restrictions and expansion on climate change represented by CO₂ emissions, after controlling other significant drivers. We use a dataset from 1998 to 2018 for a sample of 14 selected emerging economies and quantitatively advanced techniques for panel data analysis, such as Ordinary Least Squares (OLS), Dynamic OLS, Fully-Modified OLS, and Panel Quantile Regression. We also use a two-step system generalized method of moments to avoid concerns about endogeneity and heteroskedasticity issues. We find strong evidence that contractionary and expansionary monetary policy both eliminate and escalate the environmental degradation through an increase in CO₂ emissions, respectively. Moreover, these ecological effects of monetary policy interestingly appear in the middle and large quantiles of CO₂ levels. Based on these findings, the research offers some key implications for policymakers looking to initiate green monetary policy for carbon abatement.

Keywords:

• Monetary policy
• climate change
• emerging countries
• dynamic OLS
• fully-modified OLS
• panel quantile regression

JEL classification:

• F14
• F15
• F43
• E31
• Q41
• Q43

PUBLIC INTEREST STATEMENT

This research contributes to the very limited empirical studies on the ecological impacts of monetary policy with an extensive sample of 14 emerging economies. In addition, none of the prior research looks at how both regimes of monetary policy and other climate change predictors could differ across the quantile levels of CO₂ emissions.

Policy practitioners should be aware that loosening monetary policy, considered as a new and significant driver of the environmental degradation caused by an increase in CO₂ emissions, could hinder the sound transition of policy towards a sustainable low-carbon economy. This gives rise to the establishment of a “green lending program” shaped by commercial banks, which is identified as a critical conduit of monetary policy transmission via the policy interest rate of central banks.

Our research highlights

• Conventional Panel Ordinary Least Squares (OLS), Dynamic OLS, Fully-Modified OLS, Panel Quantile Regression, and two-step system GMM are applied to a sample of 14 selected emerging countries covering the period of 1998-2018.

• Both regimes of monetary policy are captured in the identity function.

• Contractionary and expansionary monetary policy both eliminate and escalate the environmental degradation through the increase in CO₂ emissions, respectively.

• The ecological effects of monetary policy are most visible in the middle-large quantile levels of CO2.

Acknowledgements

This research is funded by University of Economics Ho Chi Minh City (UEH). The first author is also greatful to the financial support from Van Lang University (VLU). This paper captures a part of the thesis conducted by Thanh Phuc Nguyen, Ph.D. Candidate of UEH, under the supervision of Tho Ngoc Tran. We also appreciate the valuable comments and suggestions from Le Van, Ho Hoang Gia Bao, Ha Van Dinh, Tri Minh Nguyen, Bao Cong Nguyen To and Luu Van Anh Dung that greatly improved the quality of this research. We are also very grateful to four anonymous referees for their constructive comments and suggestions. We are responsible for any remaining errors.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Notes

1. To be readable, we display the word abbreviations and its interpretation in Table A1 of the Appendix. We thank one anonymous reviewer for this suggestion.

2. https://www.msci.com/our-solutions/indexes/market-classification.

3. Author’s calculation is based on the World Bank database in 2019.

4. We truly appreciate this suggestion from one anonymous reviewer.

Additional information

Funding

This work was funded by the University of Economics Ho Chi Minh City (UEH). The first author is also grateful to the financial support from Van Lang University (VLU);

Notes on contributors

Thanh Phuc Nguyen

His research interests revolve around banking & finance, risk management, and financial management. He has currently served as an anonymous reviewer for Journal of Asian Business and Economic Studies (UEH).

His current research interests include banking & finance, risk management, and financial markets. Currently, he serves as a member of the National Financial and Monetary Policy Advisory Council.

She is currently a senior lecturer and the Dean of the School of Finance (University of Economics Ho Chi Minh City). Her current research interests include banking & finance, risk management, and financial markets.

He is a Ph.D. student at the University of Economics Ho Chi Minh City (UEH). He is also a lecturer at Vietnam’s Ho Chi Minh City University of Technology (HUTECH). His research interests include behavioural finance and markets, as well as empirical asset pricing.

She is a Ph.D. Candidate in the School of International Business Marketing from University of Economics Ho Chi Minh City, Vietnam (UEH). Her current research interests include sustainable marketing management and strategy, public relations, and minimalism.