scholarly journals IMPACT OF TRADE OPENNESS ON ENVIRONMENT IN CHINA

2020 ◽  
Vol 21 (4) ◽  
pp. 1185-1202 ◽  
Author(s):  
Wen Jun ◽  
Hamid Mahmood ◽  
Muhammad Zakaria
Keyword(s):  
Carbon Emission ◽  
Trade Openness ◽  
Wavelet Coherence ◽  
Coherence Analysis ◽  
Pollution Haven Hypothesis ◽  
Causality Test ◽  
Pollution Haven ◽  
Analysis Phase ◽  
The Impact ◽  
Wavelet Coherence Analysis

The study investigates the impact of trade openness on pollution in China by applying wavelet-coherence analysis, phase-difference technique and Breitung and Candelon (2006) causality test. The estimated results provide some dynamic association between trade openness and pollutant variables. The results indicate that trade openness has increased pollution in China especially after 2001 when China became member of WTO. It suggests that “pollution haven hypothesis” exists in China. These results imply that trade openness has increased exports which has increased domestic production by increasing the scale of industries, which in turn has increased pollution in the country. The findings of spectral domain causality test show that trade openness causes carbon emission both in short, medium and long runs. It indicates that trade openness forecast carbon emissions in China. The results suggest that China should take suitable measures while following trade openness policy to avoid pollution.

scholarly journals Effect of Structural Funds on Housing Market Sustainability Development—Correlation, Regression and Wavelet Coherence Analysis

Risks ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 182
Author(s):  
Łukasz Mach ◽  
Karina Bedrunka ◽  
Anna Kuczuk ◽  
Marzena Szewczuk-Stępień
Keyword(s):  
Positive Impact ◽  
Research Process ◽  
Global Scale ◽  
Real Estate Market ◽  
Wavelet Coherence ◽  
Time Variability ◽  
Coherence Analysis ◽  
Structural Funds ◽  
The Impact ◽  
Wavelet Coherence Analysis

Effective acquisition of funds, including European Union (EU) funds, designated for example, creating economic and social processes, may have a real impact on the elimination of the negative outcomes of the current position of the EU on the global scale. The aim of the research is to indicate the impact of spending funds from the Regional Operational Program of the Opolskie Voivodeship 2014–2020 (ROP OV) on a key macroeconomic area of the economy, i.e., the housing development sector in the region. The practical aim is to formulate recommendations and solutions that can offer guidelines for more effective spending of EU funds and their effect on the macroeconomic dimensions of the economy. The article proposes an innovative approach to linking EU payments in the region with the real estate market. The results of the research and the analyses made on this basis showed a positive impact of the payments made from the ROP OV on selected macroeconomic indicators, i.e., the number of permits issued for the construction of new apartments and the number of currently implemented housing investments. The obtained results should be used in the decision-making process at the level of regional and national authorities responsible for the payment of EU funds. In this article, prior to the research process, a literature review was made. It covered various aspects of the evolution and development of research in the area of regional development. The research process was based on innovative methods of time variability analysis, correlation between the investigated determinants and coherence analysis for the studied dimensions. Data on payments from the ROP OV concern the years 2015–2020.

scholarly journals An Analysis of the Impact of Clean and Non-clean Energy Consumption on Economic Growth and Carbon Emission: Evidence from PIMC Countries

2022 ◽  
Author(s):  
Arshad Ali ◽  
Magdalena Radulescu ◽  
Daniel Balsalobre Lorente ◽  
Viet-Ngu (Vincent) Hoang
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Environmental Kuznets Curve ◽  
Carbon Emission ◽  
Clean Energy ◽  
Kuznets Curve ◽  
Pollution Haven Hypothesis ◽  
Pollution Haven ◽  
The Impact

Abstract This study empirically estimates the impact of clean and non-clean energy consumption on economic growth and carbon dioxide emissions within the framework of the environmental Kuznets curve and pollution haven hypothesis in the case of PIMC countries from 1980 to 2019. The results of the panel cointegration test proposed by Westerlund (2007) show a long-term equilibrium relationship among the variables of each designated model. The long-term elasticities of economic growth and carbon emission estimated by AMG, CCEMG and MG estimators indicate that both clean and non-clean energy consumption have a significant impact on economic growth, while carbon emission hinders growth. The results also reveal that economic growth, non-clean energy consumption and interaction between trade openness and non-clean energy consumption have a driving effect on carbon dioxide emission, however, clean energy consumption is found to reduce carbon emission. In addition, the analysis confirms the existence of the inverted U-shaped environmental Kuznets curve and pollution haven hypothesis in the panel of PIMC economies. Finally, there is a one-way causality from non-clean energy consumption to economic growth, but no such causation exists between clean energy consumption and economic growth. The objective of sustained economic growth with a safe environment may be achieved by encouraging clean energy consumption in the PIMC economies.

Effect of economic indicators, biomass energy on human development in China

2021 ◽  
pp. 0958305X2110220
Author(s):  
Ngo Thai Hung
Keyword(s):  
Human Development ◽  
Global Financial Crisis ◽  
Trade Openness ◽  
Biomass Energy ◽  
Wavelet Coherence ◽  
Causality Test ◽  
Frequency Domains ◽  
Bidirectional Relationship ◽  
The Global Financial Crisis

Previous studies ignored the distinction between short, medium, and long term by decomposing macroeconomic variables and human development index at different time scales. We re-visit the causal association between biomass energy (BIO), economic growth (GDP), trade openness (TRO), industrialization (IND), foreign direct investment (FDI), and human development (HDI) in China on a quarterly scale by scale basis for the period 1990 to 2019 using the tools of wavelet, i.e., wavelet correlation, wavelet coherence and scale by scale Granger causality test. The main findings uncover that IND, TRO, GDP, and BIO positively drive the HDI at low and medium frequencies, while FDI negatively impacts HDI during the sample period. Additionally, there is a bidirectional relationship between GDP and HDI at different time and frequency domains. Specifically, we discover that the positive co-movement is more robust in the aftermath of the global financial crisis, particularly for HDI, BIO, GDP, and TRO at medium frequencies throughout the period under research. Our empirical insights have significant implications for achieving human development sustainability in China.

Wavelet coherence analysis of prefrontal oxygenation signals in elderly subjects with hypertension

2014 ◽  
Vol 35 (5) ◽  
pp. 777-791 ◽  
Author(s):  
Zengyong Li ◽  
Ming Zhang ◽  
Ruofei Cui ◽  
Qing Xin ◽  
Lu Liqian ◽  
...  
Keyword(s):  
Wavelet Coherence ◽  
Elderly Subjects ◽  
Coherence Analysis ◽  
Wavelet Coherence Analysis

Role of forest fires in Holocene stand-scale dynamics in the unmanaged taiga forest of northwestern Russia

The Holocene ◽  
2014 ◽  
Vol 24 (11) ◽  
pp. 1503-1514 ◽  
Author(s):  
Niina Kuosmanen ◽  
Keyan Fang ◽  
Richard HW Bradshaw ◽  
Jennifer L Clear ◽  
Heikki Seppä
Keyword(s):  
Forest Fires ◽  
Siberian Larch ◽  
Wavelet Coherence ◽  
Individual Tree ◽  
Study Region ◽  
Taiga Forest ◽  
The Impact ◽  
Wavelet Coherence Analysis ◽  
Northwestern Russia

Fossil pollen, conifer stomata, and charcoal records for the last 10,000 years were studied from three small hollow sites (Larix Hollow, Mosquito Hollow, and Olga Hollow) located at the modern western range limit of Siberian larch ( Larix sibirica) in northwestern Russia to investigate the role of forest fires in stand-scale dynamics of taiga vegetation. Wavelet coherence analysis was utilized to reveal the significance of fire on the vegetation composition at different timescales by assessing the phase and strength of the relationship between forest fires and most common boreal tree taxa in a time–frequency window. Pollen and stomata data show that all of the modern-day common tree taxa, including Norway spruce ( Picea abies) and Siberian larch, have been present in the study region since the early Holocene. The absence of charcoal layers at Mosquito Hollow suggests that this site has acted as a fire-free refugium with continuous dominance of spruce throughout the Holocene. Meanwhile, the Larix Hollow record indicates frequent local fire events and as a consequence, a more variable tree species composition. The wavelet coherence results show that the impact of forest fires on vegetation varies from short-term (<200-year periods) changes in individual tree taxa to long-term (400–800 years) changes in forest composition, such as the expansion of spruce population after local high-intensity fires around 7500–7000 cal. yr BP and the increase in abundance of birch and alder during periods of high fire frequency. Our results suggest that Holocene fire histories can be markedly different within a small geographical area, demonstrating the importance of site-specific factors in the local fire regime in the unmanaged taiga forest.

scholarly journals Exploring the Impact of Climate Variability on Malaria Transmission Using a Dynamic Mosquito-Human Malaria Model

2018 ◽  
Vol 10 (1) ◽  
pp. 88-100 ◽  
Author(s):  
Gbenga J. Abiodun ◽  
Peter J. Witbooi ◽  
Kazeem O. Okosun ◽  
Rajendra Maharaj
Keyword(s):  
Climate Variability ◽  
Malaria Transmission ◽  
Malaria Incidence ◽  
Principal Component ◽  
Wavelet Coherence ◽  
Human Malaria ◽  
Kwazulu Natal ◽  
The Impact ◽  
Wavelet Coherence Analysis ◽  
Malaria Model

Introduction: The reasons for malaria resurgence mostly in Africa are yet to be well understood. Although the causes are often linked to regional climate change, it is important to understand the impact of climate variability on the dynamics of the disease. However, this is almost impossible without adequate long-term malaria data over the study areas. Methods: In this study, we develop a climate-based mosquito-human malaria model to study malaria dynamics in the human population over KwaZulu-Natal, one of the epidemic provinces in South Africa, from 1970-2005. We compare the model output with available observed monthly malaria cases over the province from September 1999 to December 2003. We further use the model outputs to explore the relationship between the climate variables (rainfall and temperature) and malaria incidence over the province using principal component analysis, wavelet power spectrum and wavelet coherence analysis. The model produces a reasonable fit with the observed data and in particular, it captures all the spikes in malaria prevalence. Results: Our results highlight the importance of climate factors on malaria transmission and show the seasonality of malaria epidemics over the province. Results from the principal component analyses further suggest that, there are two principal factors associated with climates variables and the model outputs. One of the factors indicate high loadings on Susceptible, Exposed and Infected human, while the other is more correlated with Susceptible and Recovered humans. However, both factors reveal the inverse correlation between Susceptible-Infected and Susceptible-Recovered humans respectively. Through the spectrum analysis, we notice a strong annual cycle of malaria incidence over the province and ascertain a dominant of one year periodicity. Consequently, our findings indicate that an average of 0 to 120-day lag is generally noted over the study period, but the 120-day lag is more associated with temperature than rainfall. This is consistence with other results obtained from our analyses that malaria transmission is more tightly coupled with temperature than with rainfall in KwaZulu-Natal province.

scholarly journals Multi-scale investigation on streamflow temporal variability and its connection to global climate indices for unregulated rivers in India

2021 ◽  
Author(s):  
Pavan Kumar Yeditha ◽  
Tarun Pant ◽  
Maheswaran Rathinasamy ◽  
Ankit Agarwal
Keyword(s):  
Wavelet Transform ◽  
Temporal Variability ◽  
Global Climate ◽  
Phase Relationship ◽  
Wavelet Coherence ◽  
Climate Indices ◽  
Coherence Analysis ◽  
Cross Wavelet Transform ◽  
Wavelet Coherence Analysis ◽  
Cross Wavelet

Abstract With the increasing stress on water resources for a developing country like India, it is pertinent to understand the dominant streamflow patterns for effective planning and management activities. This study investigates the spatiotemporal characterization of streamflow of six unregulated catchments in India. Firstly, Mann Kendall (MK) and Changepoint analysis were carried out to detect the presence of trends and any abrupt changes in hydroclimatic variables in the chosen streamflows. To unravel the relationships between the temporal variability of streamflow and its association with precipitation and global climate indices, namely, Niño 3.4, IOD, PDO, and NAO, continuous wavelet transform is used. Cross-wavelet transform and wavelet coherence analysis was also used to capture the coherent and phase relationships between streamflow and climate indices. The continuous wavelet transforms of streamflow data revealed that intra-annual (0.5 years), annual (1 year), and inter-annual (2–4 year) oscillations are statistically significant. Furthermore, a better understanding of the in-phase relationship between the streamflow and precipitation at intra-annual and annual time scales were well-captured using wavelet coherence analysis compared to cross wavelet transform. Furthermore, our analysis also revealed that streamflow observed an in-phase relationship with IOD and NAO, whereas a lag correlation with Niño 3.4 and PDO indices at intra-annual, annual and interannual time scales.

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