https://orcid.org/0000-0001-8038-8241
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ABSTRACT
Countries have been faced with critical environmental problems and tried to take measures to prevent the negative effects on societies. In this context, countries, policymakers, and scholars have considered various factors. However, political stability (PS) has not been a fully recognized point. Therefore, the most recent studies have begun to include PS in empirically analyzing the environment. By considering the contemporary literature regarding factors affecting environmental quality, this research investigates the effect of PS on the environment in the Netherlands, which takes place among the countries that have a high level of PS. In doing this, the study focuses on the effect of PS by considering various controlling factors; utilizes data spanning from 1990/Q1 to 2019/Q4; employs Fourier-based ARDL and TY causality approaches as the base models; and performs the FMOLS approach for robustness. The findings present that (i) PS curbs environmental degradation; (ii) renewable energy declines environmental degradation; (iii) economic growth causes a stimulating in environmental degradation; (iv) globalization is not statistically significant on the environment; (iv) PS, renewable energy, and economic growth have a causal effect on the environmental degradation, whereas globalization does not have; (v) the results are robust based on the alternative approach. Thus, the study proves the highly effective role of PS on the environmental quality in the Netherlands. So, Netherlands policymakers should take PS into account in environmental plans so as not to miss being a carbon-neutral economy target due to the changes in the political environment. Accordingly, various policy options are discussed.
Graphical abstract
Highlights
Carbon dioxide (CO2) emissions in the Netherlands is investigated.
Long-run effect of political stability (PS) is examined.
Fourier-based ARDL and TY approaches are used for the period 1990/Q1-2019/Q4.
The PS has a significant and causal effect on CO2 emissions in the long-run.
The robustness of the Fourier ARDL approach is validated by the FMOLS approach.
Acronyms
| 3SLS | = | Three-Stage Least Squares |
| BCFDC | = | Breitung and Candelon Frequency-Domain Causality |
| CS-ARDL | = | Cross-Sectional ARDL |
| CV | = | Coefficient of Variation |
| DH | = | Dumitrescu Hurlin Causality |
| DOLS | = | Dynamic OLS |
| EF | = | Ecological Footprint |
| EQ | = | Environmental Quality |
| FE-OLS | = | Fixed Effect OLS |
| FADF | = | Fourier Augmented Dickey-Fuller |
| F-ADL | = | Fourier ADL Cointegration |
| F-ARDL | = | Fourier ARDL |
| FMOLSFTY | = | Fully Modified OLSFourier Toda Yamamoto Causality |
| GC | = | Granger Causality |
| GDP | = | Gross Domestic Product |
| MENA | = | Middle East and North Africa |
| MMQR | = | Methods of Moments Quantile Regression |
| NARDLPRSG | = | Nonlinear ARDLPolitical Risk Services Group |
| PRI | = | Political Risk Index |
| = | Quantile-on-Quantile Regression | |
| QRRCEC | = | Quantile RegressionRegional Comprehensive Economic Cooperation |
| RE-OLS | = | Random Effect OLS |
| TY | = | Toda Yamamoto Causality |
| UK | = | United Kingdom |
| WB | = | World Bank |
Disclosure statement
No potential conflict of interest was reported by the authors.
Authors’ contributions
The authors have contributed equally to this work. All authors read and approved the final manuscript.
Availability of data and materials
Data will be made available on request.
Consent for publication
The authors are willing to permit the Journal to publish the article.