Table 1.
Synopsis of studies
| S/N | Investigator (s) | Timeframe | Nation (s) | Technique(s) | Findings |
|---|---|---|---|---|---|
| 1 | Abbasi and Adedoyin (2021) | 1970–2018 | China | Dynamic simulated ARDL | EPU does not have any effect on CO2 emissions |
| 2 | Adedoyin et al. (2021) | 1996–2014 | Sub-Saharan Africa | Dynamic Panel System-GMM | EPU aggravates the level of emissions |
| 3 | Amin and Dogan (2021) | 1980–2016 | China | Dynamic simulated ARDL | EPU deteriorates environmental quality |
| 4 | Ahmed et al. (2021) | 1985–2017 | United States | NARDL | EPU improves environmental quality |
| 5 | Anser et al. 2021a | 1990–2015 | Top ten carbon emitter countries | PMG-ARDL | EPU increases carbon emissions |
| 6 | Atsu and Adams (2021) | 1984–2017 | BRICS | CS-ARDL, FMOLS | EPU accelerates environmental quality |
| 7 | Chu and Le (2022) | 1997–2015 | G7 countries | FMOLS, Fixed effect | EPU improves environmental quality |
| 8 | Gu et al. (2021a) | 2006–2016 | China | Spatial Econometric models | EPU decreases carbon emissions |
| 9 | Ivanovski and Marinucci (2021) | 1990–2015 | Global perspective | FMOLS, DOLS, ARDL-PMG, CCEMG, DCCEMG | EPU reduces carbon emissions |
| 10 | Khan et al. (2022) | 1997–2020 | East Asian economies | PMG | EPU deteriorates carbon emissions |
| 11 | Lei et al. (2022) | 1990–2019 | China | Nonlinear ARDL approach | EPU worsens the level of emissions |
| 12 | Liu and Zhang (2022) | 2003–2017 | China | Panel data analysis | EPU improves environmental quality |
| 13 | Nakhli et al. (2022) | 1985–2020 | USA | Bootstrap rolling approach | EPU increases carbon emissions |
| 14 | Shabir et al. (2022) | 2001–2019 | 24 developing, and developed countries | DSUR, VECM, DCCET, fixed-effect panel quantile regression | EPU intensifies carbon emissions |
| 15 | Syed et al. (2022) | 1990–2015 | BRICST countries | AMG, CCEMG, panel quantile regression | EPU worsens environmental quality |
| 16 | Ullah et al. (2022) | 1996–2019 | Low and high globalised OECD economies | AMG | EPU deteriorates environmental quality |
| 17 | Xin and Xin (2022) | 1976–2018 | 25 countries | Panel data analysis, fixed-effect | EPU improves environmental quality |
| 18 | Xue et al. (2022) | 1987–2019 | France | Augmented ARDL | EPU worsens environmental quality |
| 19 | Yu et al. (2021) | 2008–2011 | Chinese manufacturing firms | Panel data analysis, fixed-effect method | EPU deteriorates environmental quality |
| 20 | Zakari et al. (2021) | 1985–2017 | OECD countries | PMG-ARDL | EPU increases carbon emissions |
| 21 | Zeng and Yue (2022) | 1991–2019 | BRICS economies | NARDL-PMG | EPU decreases the level of emissions |
| 22 | Zhang et al. (2022) | 1995–2019 | USA, China | ARDL, non-linear ARDL | EPU does not have any effect on CO2 emissions |
| 23 | Zhao et al. (2022) | 1985–2018 | China | System dynamics, LEAP model, Monte Carlo simulation, mixed method | EPU deteriorates environmental quality |
| 24 | Chen et al. (2021) | 1997–2019 | 15 countries | Mixed panel data model | EPU lowers the level of emissions |
| 25 | Adams et al (2020) | 1996–2017 | Resource-rich countries | PMG-ARDL | EPU worsens environmental quality |
| 26 | Adedoyin and Zakari (2020) | 1985–2017 | UK | ARDL approach | EPU deteriorates environmental quality |
| 27 | Jiang et al. (2019) | 1985–2017 | USA | Granger causality in quantiles | EPU intensifies level of emissions |
| 28 | Pirgaip and Dinçergök (2020) | 1998–2018 | G7 countries | Bootstrap panel Granger causality test | EPU worsens environmental quality |
| 29 | Ulucak and Khan (2020) | 1985–2017 | USA | Dynamic ARDL model | EPU increases environmental degradation |
BICST: Brazil, India, China, South Africa, Turkey; ARDL: autoregressive distributed lag; DOLS: dynamic ordinary least squares; FMOLS: fully modified ordinary least squares; NARDL: nonlinear autoregressive distributed lag; NARDL-PMG: nonlinear autoregressive distributed lag—pooled mean group; ARDL-PMG: autoregressive distributed lag—pooled mean group; DSUR: dynamic seemingly unrelated regression; DCCET: dynamic common correlated effects technique; AMG: augmented mean group; PMG: pooled mean group; PMG-ARDL: pooled mean group-autoregressive distributed lag model; VECM: vector error correction model; CS-ARDL: cross-sectional augmented autoregressive distributed lag; CCEMG: common correlated effect mean group; DCCEMG: dynamic common correlated effect mean group