Iqbal Alam
Iqbal Alam has a total of 8 co-authors. Here are the top co-authors by number of shared publications:
- Abdul Majeed
School of Insurance and Economics, University of International Business and Economics, Beijing 100029, China
2 shared publications - Andrew Adewale Alola
CREDS-Centre for Research on Digitalization and Sustainability, University of Inland Norway, Kongsvinger, Norway
2 shared publications - Lijuan Gao
YunNan Nuclear Industry Mining Group, Kunming, China
2 shared publications - Nicholas Apergis
Faculty of Economics, Prague University of Economics and Business, Prague, Czech Republic
2 shared publications - Qasim Raza Syed
National Tariff Commission, Islamabad, Pakistan
2 shared publications - Roni Bhowmik
School of Business, Guangdong University of Foreign Studies, China
2 shared publications
Latest Publications
- Open Access
- 29 December 2022
- Published by Springer Nature in Environmental Science and Pollution Research
- Vol. 30 (5) , 13863
Correction to: How FDI and technology innovation mitigate CO2 emissions in high-tech industries: evidence from province-level data of China
- 29 December 2022
- Published by Springer Nature in Environmental Science and Pollution Research
- Vol. 30 (5) , 13863
Open AccessCorrection to: How FDI and technology innovation mitigate CO2 emissions in high-tech industries: evidence from province-level data of China
- 8 October 2021
- Published by Springer Nature in Environmental Science and Pollution Research
- Vol. 29 (10) , 14914-14928
Applying a dynamic ARDL approach to the Environmental Phillips Curve (EPC) hypothesis amid monetary, fiscal, and trade policy uncertainty in the USA
It is well known that unemployment and environmental degradation are two critical issues across the globe. However, there is an extended dearth of literature that explores the nexus between unemployment and environmental degradation. Kashem and Rahman (Environ. Sci. Pollut. Res. 27(101): 31153–31170, 2020) put forward the Environmental Phillips Curve (EPC) hypothesis, which depicts a negative relationship between unemployment and environmental degradation. This study further explores the validity of the EPC hypothesis in the case of the USA. It also investigates the impact of monetary policy uncertainty (MU), fiscal policy uncertainty (FU), and trade policy uncertainty (TU) on carbon dioxide emissions. To this end, the analysis employs the novel methodology of the dynamic ARDL model. The results document that EPC does not hold in the short run, but it does in the long run. Furthermore, both in the short and long run, MU escalates CO2 emissions, while FU plunges emissions in both the short and long run. Finally, TU does not alter the level of CO2 emissions.
- 8 October 2021
- Published by Springer Nature in Environmental Science and Pollution Research
- Vol. 29 (10) , 14914-14928
Applying a dynamic ARDL approach to the Environmental Phillips Curve (EPC) hypothesis amid monetary, fiscal, and trade policy uncertainty in the USA
It is well known that unemployment and environmental degradation are two critical issues across the globe. However, there is an extended dearth of literature that explores the nexus between unemployment and environmental degradation. Kashem and Rahman (Environ. Sci. Pollut. Res. 27(101): 31153–31170, 2020) put forward the Environmental Phillips Curve (EPC) hypothesis, which depicts a negative relationship between unemployment and environmental degradation. This study further explores the validity of the EPC hypothesis in the case of the USA. It also investigates the impact of monetary policy uncertainty (MU), fiscal policy uncertainty (FU), and trade policy uncertainty (TU) on carbon dioxide emissions. To this end, the analysis employs the novel methodology of the dynamic ARDL model. The results document that EPC does not hold in the short run, but it does in the long run. Furthermore, both in the short and long run, MU escalates CO2 emissions, while FU plunges emissions in both the short and long run. Finally, TU does not alter the level of CO2 emissions.
- 19 August 2021
- Published by Springer Nature in Environmental Science and Pollution Research
- Vol. 29 (3) , 4641-4653
How FDI and technology innovation mitigate CO2 emissions in high-tech industries: evidence from province-level data of China
The high technology (high-tech) industry of China has gained a key strategic position in the Chinese economic goals. In this positioning, foreign direct investment (FDI) and technological innovation have emerged as strong pillars of the high-tech industry. However, there are growing concerns of carbon emission from this industry which is still debatable. In this context, this study measures the effect of FDI and technology innovation on carbon emissions in the high-tech industry from 28 provinces of China. The study uses the provincial data for China over the period 2000–2018. In addition to examining unit root properties, structural breaks, and cointegration, this study uses quantile regression for estimating long-run relationships among study variables. The findings reveal the negative impact of FDI on carbon emissions. Technology innovation positively impacts in the initial three quantiles, whereas negatively impacts in the next six quantiles. These results indicate that FDI and technology innovation have shaped the energy intensity in the high-tech industry, which causes fluctuation in carbon emissions over time. After controlling the effects of urbanization, energy intensity, and economic growth, this study recommends that policymakers should emphasize on the heterogeneous effects of FDI and technology-lead emissions at different quantiles during the process of CO2 emission reduction.
- 19 August 2021
- Published by Springer Nature in Environmental Science and Pollution Research
- Vol. 29 (3) , 4641-4653
How FDI and technology innovation mitigate CO2 emissions in high-tech industries: evidence from province-level data of China
The high technology (high-tech) industry of China has gained a key strategic position in the Chinese economic goals. In this positioning, foreign direct investment (FDI) and technological innovation have emerged as strong pillars of the high-tech industry. However, there are growing concerns of carbon emission from this industry which is still debatable. In this context, this study measures the effect of FDI and technology innovation on carbon emissions in the high-tech industry from 28 provinces of China. The study uses the provincial data for China over the period 2000–2018. In addition to examining unit root properties, structural breaks, and cointegration, this study uses quantile regression for estimating long-run relationships among study variables. The findings reveal the negative impact of FDI on carbon emissions. Technology innovation positively impacts in the initial three quantiles, whereas negatively impacts in the next six quantiles. These results indicate that FDI and technology innovation have shaped the energy intensity in the high-tech industry, which causes fluctuation in carbon emissions over time. After controlling the effects of urbanization, energy intensity, and economic growth, this study recommends that policymakers should emphasize on the heterogeneous effects of FDI and technology-lead emissions at different quantiles during the process of CO2 emission reduction.