scholarly journals Policy Uncertainty, Economic Activity And Carbon Emissions: A Nonlinear Autoregressive Distributed Lag Approach

Author(s):  
Malihe Ashena ◽  
Ghazal Shahpari

Abstract Over the last few years, economic uncertainty has become a global concern. Not only has its impact on economic activities, but there are pieces of evidence that show uncertainty can be the reason for CO2 emissions. It is also expected that the economic policy uncertainty may decrease or delay economic production, which may lead to a reduction in carbon emissions. Furthermore, uncertainty may decrease friendly environment policies and budgets, which cause increase in carbon emissions. Thus, there may be an asymmetric relationship between economic uncertainty and the amount of CO2 emissions. This study investigates the effects of economic policy uncertainty and economic activity on carbon emission applying a Nonlinear Autoregressive Distributive Lag (NARDL) cointegration approach in Iran between 1971 and 2018. Findings show that both policy uncertainty and economic growth contribute to CO2 emissions. The negative and positive shocks of GDP and uncertainty index on CO2 emissions in both the short-run and long-run are significant. It can be concluded that there is an asymmetric effect of economic production on CO2 emissions in Iran. The results of analyzing asymmetric effects of economic uncertainty show a symmetric relationship between uncertainty index and CO2 emissions. In a way that a shock in uncertainty index lowers carbon emission. To sum up, since uncertainty may affect the analysis of carbon emissions incorrectly, some environmental policies such as allocating a budget for R&D on clean energy, and environmental taxes must be implemented.

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Ruwei Zhao

This paper investigates the long-term dynamic cross-correlation evolution between US economic policy uncertainty index (USEPU) and Guangdong carbon emission trading price (GDCP) from the multifractal detrended cross-correlation analysis (MF-DCCA) perspective. With the calculation of correlation statistics and fluctuation function, the beginning procedures of MF-DCCA, we find that the cross-correlation between USEPU and GDCP is significant and presents power law property. Also, with the Hurst exponent, we find that the long-horizon correlations between series are persistent. Moreover, we perform Rényi exponent and spectrum singularity check. The empirical findings reveal that the all the correlations are of multifractality and the correlation of GDCP holds the highest degree.


2017 ◽  
Vol 8 (2) ◽  
pp. 563-575 ◽  
Author(s):  
Mirjana Čižmešija ◽  
◽  
Ivana Lolić ◽  
Petar Sorić ◽  
◽  
...  

2019 ◽  
Vol 12 (1) ◽  
pp. 5 ◽  
Author(s):  
Jun Gao ◽  
Sheng Zhu ◽  
Niall O’Sullivan ◽  
Meadhbh Sherman

We investigated the role of domestic and international economic uncertainty in the cross-sectional pricing of UK stocks. We considered a broad range of financial market variables in measuring financial conditions to obtain a better estimate of macroeconomic uncertainty compared to previous literature. In contrast to many earlier studies using conventional principal component analysis to estimate economic uncertainty, we constructed new economic activity and inflation uncertainty indices for the UK using a time-varying parameter factor-augmented vector autoregressive (TVP-FAVAR) model. We then estimated stock sensitivity to a range of macroeconomic uncertainty indices and economic policy uncertainty indices. The evidence suggests that economic activity uncertainty and UK economic policy uncertainty have power in explaining the cross-section of UK stock returns, while UK inflation, EU economic policy and US economic policy uncertainty factors are not priced in stock returns for the UK.


2018 ◽  
Vol 34 (2) ◽  
pp. 355-365 ◽  
Author(s):  
Ellen Tobback ◽  
Hans Naudts ◽  
Walter Daelemans ◽  
Enric Junqué de Fortuny ◽  
David Martens

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