The effects of infrastructure development and carbon emissions on economic growth

Sharif, Fatima; Tauqir, Aisha

doi:10.1007/s11356-021-12936-4

Cited by 16 publications

(10 citation statements)

References 26 publications

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“…Our research also demonstrates that a 1% increase in RTI corresponds to a 0.595% increase in EG, which is consistent with prior studies conducted by Shahbaz et al (2015) and Sharif and Tauqir (2021). When countries in the MENA region invest in expanding or enhancing their road transportation systems, it has a positive effect on their economic development.…”

Section: Source: Authors' Estimation Under Eviews 12supporting

confidence: 90%

Dynamic nexus between poverty and indicators for sustainable transportation in MENA countries: Evidence from panel PMG-ARDL approach

Ouni,

Abdallah

2024

Preprint

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Sustainable transportation indicators have attracted significant attention from policymakers, engineers, and academics. This heightened interest can be attributed to the transportation industry's impact on economic growth, poverty alleviation, and the environment. While numerous studies have explored the relationships between the transportation sector, poverty, economic growth, and environmental degradation on a global scale, there is a noticeable research gap concerning the Middle East and North Africa (MENA) region. This study addresses this gap by investigating the nexus between poverty, transportation-related CO2 emissions, economic growth, trade openness, urbanization, road infrastructure and transportation energy consumption in 14 MENA regions from 1983 to 2021. To achieve this objective, this investigation employs the panel pooled mean group-autoregressive distributed lag (PMG-ARDL) model to explore the long-term relationships among these variables. The findings, as revealed by the Dumitrescu-Hurlin panel causality, show a reciprocal relationship between poverty, transportation-related CO2 emissions and economic growth. Moreover, the study identifies a unidirectional relationship running from road infrastructure to poverty. Additionally, a unidirectional causality runs from both economic growth and poverty to transportation-related energy consumption. Furthermore, a bidirectional causality exists between trade openness and transport CO2 emissions, and a unidirectional causality running from trade openness to economic growth. These findings emphasize the importance of policymakers to adopt strategies that equally prioritize poverty alleviation, environmental sustainability, and economic development to attain sustainable transportation in MENA region.

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Section: Source: Authors' Estimation Under Eviews 12supporting

confidence: 90%

Dynamic nexus between poverty and indicators for sustainable transportation in MENA countries: Evidence from panel PMG-ARDL approach

Ouni,

Abdallah

2024

Preprint

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“…Therefore, the region is experiencing both an increase in HDI and a rise in environmental pollution. Sharif and Tauqir (2021) investigated the relationship between infrastructure development and carbon emissions in Pakistan for the period 1972-2017. They used ordinary least squares (OLS) and fully modified OLS methods for analysis.…”

Section: Literature Reviewmentioning

confidence: 99%

Infrastructure development, human development index, and CO2 emissions in China: A quantile regression approach

Liu

Poulová²,

Pražák³

et al. 2023

Front. Environ. Sci.

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This study investigates the relationships between infrastructure development, human development index (HDI), and CO2 emissions in China. Infrastructure has played an essential role in achieving social and economic developmental goals in China, but environmental pollution has significantly increased in the country in the last two decades. Our analysis uses time series data from 1990 to 2021 and quantile regressions, and we find that infrastructure has positive and statistically significant relationships with HDI, CO2 emissions, and GDP in all quantiles. Recent infrastructure upgrades improve living standards and increase HDI but damage the environment, and infrastructure is the main source of CO2 emissions in the country. Therefore, the government should invest in sustainable infrastructure to mitigate CO2 emissions. The government may consider infrastructure options such as low carbon transportation, including railway infrastructure, urban metros, and light rail.

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“…Pavement roughness is a significant factor for vehicle travel, which has a direct impact on both vehicle smoothness and occupant comfort, as well as the quality and service life of the road [ 1 , 2 ]. In order to use vehicles better and ensure road traffic safety, pavement roughness recognition has theoretical research value and practical application significance [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Pavement Roughness Grade Recognition Based on One-dimensional Residual Convolutional Neural Network

2023

Sensors

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A pavement’s roughness seriously affects its service life and driving comfort. Considering the complexity and low accuracy of the current recognition algorithms for the roughness grade of pavements, this paper proposes a real-time pavement roughness recognition method with a lightweight residual convolutional network and time-series acceleration. Firstly, a random input pavement model is established by the white noise method, and the pavement roughness of a 1/4 vehicle vibration model is simulated to obtain the vehicle vibration response data. Then, the residual convolutional network is used to learn the deep-level information of the sample signal. The residual convolutional neural network recognizes the pavement roughness grade quickly and accurately. The experimental results show that the residual convolutional neural network has a robust feature-capturing ability for vehicle vibration signals, and the classification features can be obtained quickly. The accuracy of pavement roughness classification is as high as 98.7%, which significantly improves the accuracy and reduces the computational effort of the recognition algorithm, and is suitable for pavement roughness grade classification.

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The effects of infrastructure development and carbon emissions on economic growth

Cited by 16 publications

References 26 publications

Dynamic nexus between poverty and indicators for sustainable transportation in MENA countries: Evidence from panel PMG-ARDL approach

Dynamic nexus between poverty and indicators for sustainable transportation in MENA countries: Evidence from panel PMG-ARDL approach

Infrastructure development, human development index, and CO2 emissions in China: A quantile regression approach

Pavement Roughness Grade Recognition Based on One-dimensional Residual Convolutional Neural Network

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