检索结果-内蒙古大学图书馆

The impact of democracy and income on CO2 emissions in MINT countries: evidence from quantile regression model

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2023年第18期30卷 52762-52783页

作者： Agbede, Esther Abdul Bani, Yasmin Naseem, Niaz Ahmad Mohd Azman-Saini, Wan Ngah Wan Univ Putra Malaysia UPM Sch Business & Econ Serdang 43400 Selangor Malaysia Fed Coll Educ Tech Sch Business Educ Potiskum Yobe Nigeria

This study analyses the relationship between democracy and environmental pollution in the MINT countries using a panel data spanning 1971-2016. It also investigates the interactive effect of income and democracy on CO2 emissions. We used various estimation techniques for the analysis, ranging from the quantile regression, OLS-fixed effect and GLS-random effect regressions with Driscoll-Kraay standard errors to control for cross-sectional dependence while a panel threshold regression is used for robustness check. The results showed existence of long-run relationship between CO2 emissions and the explanatory variables. The quantile regression results for interaction model indicate that economic growth, democracy and trade openness promote environmental pollution via their positive effects on CO2 emissions. Primary energy however reduces pollution across the lower and middle quantiles but enhances it in higher quantiles. The interaction effect is negative and statistically significant across all quantiles. This implies that democracy has a significant role in moderating the impact of income on CO2 emission in the MINT countries. It thus follows that if the MINT countries radically strengthen democracy and enhance income, it would be possible for them to achieve greater economic development and reduce CO2. In addition, a single threshold model is used to identify the asymmetry in response to CO2 emissions at lower and upper levels of democratic regimes. The results showed that once the degree of democracy is above the threshold level, an increase in income would reduce CO2 emissions but once it is below the threshold level, the effect of income becomes insignificant. Based on these results, the MINT countries need to strengthen democracy, enhance income level and relax trade barriers.

关键词： Democracy Income CO2 emissions quantile regression model

来源：评论

学校读者我要写书评

暂无评论

Examination on the setting of scheduled block time in China's aviation framework dependent on quantile regression model

引用

SOFT COMPUTING 2023年第6期27卷 3403-3410页

作者： Chen, Yunxiang Zhong, Sheng Yan, Zhenting Wuhan Univ Sch Elect Informat Wuhan 430072 Peoples R China Fudan Univ Sch Data Sci Shanghai 200433 Peoples R China

Based on nationwide aircraft performance and scheduling gathered from ***, the work evaluates how the identified factors, such as aircraft taxi-in and taxi-out time, airborne time, Origin-destination Pair Herfindahl-Hirschman Index (OD-Pair HHI), hub airport, and flight distance, coexisted in order to organize aviation scheduling more effectively and appropriately in the air transportation system. The result indicates that the variables of a hub airport, OD-Pair HHI and throughput have a more significant effect on SBT than the duration of each flight phase does (i.e., aircraft taxi-in and taxi-out time, airborne time, etc.). Fierce competition has prompted airlines to improve their on-time performance (OTP), instead of scheduling shorter block times. Moving forward, if the departure airport is a major one, the SBT will increase by 3.43 min, indicating that airport throughput is a primary determinant in adding or shortening SBT in China's aviation system.

关键词： Air transportation Flight schedule quantile regression model Scheduled block time Air traffic management

来源：评论

学校读者我要写书评

暂无评论

Application of machine learning technique for optimizing roadside design to decrease barrier crash costs, a quantile regression model approach

引用

JOURNAL OF SAFETY RESEARCH 2021年 78卷 19-27页

作者： Rezapour, Mahdi Ksaibati, Khaled Wyoming Technol Transfer Ctr 1000 E Univ AveDept 3295 Laramie WY 82071 USA

Introduction: In-transport vehicles often leave the travel lane and encroach onto natural objects on the roadsides. These types of crashes are called run-off the road crashes (ROR). Such crashes accounts for a significant proportion of fatalities and severe crashes. Roadside barrier installation would be warranted if they could reduce the severity of these types of crashes. However, roadside barriers still account for a significant proportion of severe crashes in Wyoming. The impact of the crash severity would be higher if barriers are poorly designed, which could result in override or underride barrier crashes. Several studies have been conducted to identify optimum values of barrier height. However, limited studies have investigated the monetary benefit associated with adjusting the barrier heights to the optimal values. In addition, few studies have been conducted to model barrier crash cost. This is because the crash cost is a heavily skewed distribution, and well-known distributions such as linear or poison models are incapable of capturing the distribution. A semi-parametric distribution such as asymmetric Laplace distribution can be used to account for this type of sparse distribution. Method: Interaction between different predictors were considered in the analysis. Also, to account for exposure effects across various barriers, barrier lengths and traffic volumes were incorporated in the models. This study is conducted by using a novel machine-learning-based cost-benefit optimization to provide an efficient guideline for decision makers. This method was used for predicting barrier crash costs without barrier enhancement. Subsequently the benefit was obtained by optimizing traffic barrier height and recalculating the benefit and cost. The trained model was used for crash cost prediction on barriers with and without crashes. Results: The results of optimization clearly demonstrated the benefit of optimizing the heights of road barriers around the state. Practic

关键词： Machine learning quantile regression model Traffic barrier crash severity Optimization Benefit cost analysis

来源：评论

学校读者我要写书评

暂无评论

Solving the Time-Varying Cobb-Douglas Production Function Using a Varying-Coefficient quantile regression model

引用

JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS 2019年第5期23卷 831-837页

作者： Zhang, Shangfeng Zhu, Jiani Fang, Qi Liu, Yaoxin Xu, Siwa Tsai, Ming-Hsueh Zhejiang Gongshang Univ Res Inst Quantitat Econ 18 Xuezheng StXiasha Educ Pk Hangzhou 310018 Zhejiang Peoples R China Natl Acad Educ Res 2 Sanshu Rd New Taipei 23703 Taiwan

The output elasticity estimated by the traditional Cobb-Douglas production function is a fixed constant that describes developed countries with relative stable factor shares well. While the fixed constant fails to describe developing countries with changing factor shares during economic transitional periods, such as China. In this paper, we construct a time-varying elasticity production function model and extend the Cobb-Douglas production function to a time-varying elasticity Cobb-Douglas production function. The semi-parametric varying-coefficient quantile model, together with the local polynomial and the two-phase methods, is used for the estimation of the time-varying elasticity of the capital coefficient and the labor force. Empirical research on Chinese economic growth shows that the time-varying elasticity of capital is declining and the time-varying elasticity of the labor force is increasing gradually.

关键词： Cobb-Douglas production function semi-parametric varying-coefficient model quantile regression model local polynomial time-varying elasticity coefficient

来源：评论

学校读者我要写书评

暂无评论

Investigating the differences in CO₂ emissions in the transport sector across Chinese provinces: Evidence from a quantile regression model

引用

JOURNAL OF CLEANER PRODUCTION 2018年第Feb.20期175卷 109-122页

作者： Xu, Bin Lin, Boqiang Jiangxi Univ Finance & Econ Sch Stat Nanchang 330013 Jiangxi Peoples R China Jiangxi Univ Finance & Econ Res Ctr Appl Stat Nanchang 330013 Jiangxi Peoples R China Xiamen Univ Collaborat Innovat Ctr Energy Econ & Energy Policy Sch Management China Inst Studies Energy Policy Xiamen 361005 Fujian Peoples R China

Carbon dioxide (CO2) emission in China is currently the largest in the world. Considering that the transport sector, it is one of the major contributors, its CO2 emissions and their main driving factors have become the focus of many scholars. However, majority of the existing studies usually investigates CO2 emissions using the averaging method (i.e., ordinary least squares method). In fact, the data distribution of socioeconomic variables is often non-normal, with the tail having hidden important information. In order to overcome the shortcomings of existing research, this paper uses a quantile regression approach to explore the main driving forces of the difference in CO2 emissions under high, medium and low level of development. The results show that the effect of economic growth on CO2 emissions in the 25th-50th quantile provinces is higher than those in the other quantile provinces due to the differences in fixed-asset investment and motor vehicles. Energy intensity has a similar story owing to different R&D funding and R&D personnel investments. The influences of urbanization in the upper 90th and 75th-90th quantile provinces are higher than those in the other quantile provinces because of the differences in human capital accumulation and patented technology. Freight turnover produces the same effect, which is due to the differences in freight transportation and transport mode. However, the impacts of passenger turnover in the lower 10th and 10th-25th quantile provinces are the highest in all the quantile provinces. Therefore, in the process of emission reduction, the relevant departments should be concerned about the heterogeneous effects of these driving forces on the different quantile provinces, rather than adopting the "one-size-fits-all approach". (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Transport sector CO2 emissions Driving forces STIRPAT model quantile regression model

来源：评论

学校读者我要写书评

暂无评论

Moving Beyond the Linear regression model: Advantages of the quantile regression model

引用

JOURNAL OF MANAGEMENT 2015年第1期41卷 71-98页

作者： Li, Mingxiang Univ Wisconsin Madison WI 53706 USA

Heavy-tailed distributions occur often in empirical settings, making it difficult for management scholars to use linear regression models (LRMs) to investigate the nuanced relationships between dependent and predictor variables. Both frequentist and Bayesian quantile regression models (QRMs) are alternative techniques that can help management scholars overcome the hurdles associated with using LRMs. This study compares LRMs and QRMs and shows how the frequentist and Bayesian QRM can open up doors for management scholars to develop and test theory in novel and informative ways. In introducing Bayesian estimation, it also shows how Bayesian quantile regression can achieve what existing Bayesian LRM and frequentist QRM techniques cannot. Following this exploration, this paper explains how management researchers can systematically apply QRMs in two concrete empirical settings. The first example shows that organizational behavior and human resource scholars can apply QRMs to study questions related to gender inequality. The second example illustrates that QRMs enable strategy and organizational theory researchers to detect nuanced relations between environmental factors and firm performance. This paper demonstrates that the QRM is a comprehensive strategy capable of helping researchers obtain a complete regression picture for data with heavy-tailed distributions.

关键词： quantile regression model Bayesian quantile regression Bayesian estimation research methods

来源：评论

学校读者我要写书评

暂无评论

An empirical likelihood method for quantile regression models with censored data

引用

METRIKA 2021年第1期84卷 75-96页

作者： Gao, Qibing Zhou, Xiuqing Feng, Yanqin Du, Xiuli Liu, XiaoXiao Nanjing Normal Univ Sch Math Sci Nanjing 210023 Peoples R China Nanjing Normal Univ Inst Finance & Stat Nanjing 210023 Peoples R China Wuhan Univ Sch Math & Stat Wuhan 430072 Peoples R China

An estimation for censored quantile regression models, which is based on an inverse-censoring-probability weighting method, is studied in this paper, and asymptotic distribution of the parameter vector estimator is obtained. Based on the parameter estimation and asymptotic distribution of the estimator, an empirical likelihood inference method is proposed for censored quantile regression models and asymptotic property of empirical likelihood ratio is proved. Since the limiting distribution of the empirical likelihood ratio statistic is a mixture of chi-squared distributions, adjustment methods are also proposed to make the statistic converge to standard chi-squared distribution. The weighting scheme used in the parameter estimation is simple and the loss function is continuous and convex, and therefore, compared with empirical likelihood methods for quantile regression models with completely observed data, the methods proposed in this paper will not increase the computational complexity. This makes it especially useful for data with medium or high dimensional covariates. Simulation studies are developed to illustrate the performance of proposed methods.

关键词： quantile regression model Empirical likelihood method Censored data Asymptotic properties

来源：评论

学校读者我要写书评

暂无评论

Balancing the benefits and risks of China's national salt iodization policy over 30 years using disability-adjusted life years (DALYs): a systematic review and meta-analysis

引用

CRITICAL REVIEWS IN FOOD SCIENCE AND NUTRITION 2024年 1-11页

作者： Chen, Wenxiu Liu, Xinyi Zhang, Bin Sang, Chenhui Li, Hua Peng, Ying An, Wei Yang, Min Chinese Acad Sci Natl Engn Res Ctr Ind Wastewater Detoxicat & Resou Res Ctr Ecoenvironm Sci Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China UCL Stat Dept London England Beijing Ctr Dis Prevent & Control Beijing Key Lab Diagnost & Traceabil Technol Food Beijing Peoples R China Beijing Univ Agr Coll Plant Sci & Technol Beijing Key Lab Agr Applicat & New Tech Beijing Peoples R China Peking Univ Third Hosp Dept Gen Surg Beijing Peoples R China

Both insufficient and excessive iodine intake can lead to thyroid-related disorders. Although China has made progress in eliminating iodine deficiency over the past few decades, the incidence of thyroid cancer is increasing. Currently, there is a lack of relevant research on the tradeoff between the benefits and risks of salt iodization in China. In this study, we developed a method that combines the total probability algorithm and disease burden to evaluate the appropriate amount of salt iodization. Following the principle of minimizing the comprehensive disease burden and using the metabolic model of human iodine nutrition. Based on the average national iodine level in water, the optimal iodine content in Chinese salt is determined to be 17 mg/kg. However, iodine content in water is not evenly distributed in China. Approximately 3.23% of administrative villages have water iodine concentrations exceeding 80 ug/L, eliminating the need for iodine fortification in salt. Approximately 83.51% of administrative villages need to continue implementing the salt iodization policy, with the optimal iodine content in salt ranging from 15 to 18 mg/kg. In 13.16% of administrative villages, the iodine content in salt is determined based on the local water iodine concentration, ranging from 0 to 15 mg/kg. Our study cracks open a window of insight suggesting that the optimal iodine content for salt is lower than the existing benchmark dictated by the prevailing policy in China. Hence, there is an urgent need to refine and advance the iodine supplementation strategy in salt to pave the way for precision medicine and health-centric iodine supplementation strategies.

关键词： Disease burden iodine meta analysis mild mental retardation (MMR) quantile regression model thyroid disease

来源：评论

学校读者我要写书评

暂无评论

Assessment and comparison of bioenergy yield efficiency: A study of biohydrogen production from microalgae, macroalgae and competitive biomass feedstocks

引用

BIORESOURCE TECHNOLOGY REPORTS 2025年 29卷

作者： Lee, Duu-Hwa Natl Taiwan Ocean Univ Inst Appl Econ Keelung Taiwan 2 Beining Rd Keelung City 202301 Taiwan

This study utilizes data envelopment analysis (DEA) economic models to estimate the efficiency of biohydrogen yield (production) in economics, using experimental data from the literature on dark fermentation, and hybrid methods for microalgae, competitive biomass, and macroalgae. The available data from the literature is selected only with the same units in inputs (substrate concentration (SC), pH, and temperature) and output (hydrogen yield). Results reveal that a lower yield technology of a microalgae experiment could perform with a higher economic yield efficiency. The yield efficiency of pre-treatment procedures is higher than that of co-digestion procedures, and the economic yield efficiency generated by microalgae is lower than that of other representative biomass sources and macroalgae. pH is a more sensitive factor than SC and temperature. Some microalgae species perform as well as macroalgae. The results benefit decision-makers to choose competitive production technology in developing the sustainable biohydrogen industry.

关键词： Microalgae Biohydrogen Dark fermentation Macroalgae Data Envelopment model quantile regression model

来源：评论

学校读者我要写书评

暂无评论

Aggregated peak-load analysis and demand response potential of a residential building in Osaka, Japan

引用

ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY 2025年第3期27卷 6881-6898页

作者： Toosty, Nishat Tasnim Shimoda, Shota Hagishima, Aya Kyushu Univ Interdisciplinary Grad Sch Engn Sci Energy & Environm Engn Kasuga Fukuoka Japan Univ Dhaka Dept Stat Dhaka Bangladesh Kyushu Univ Fac Engn Sci Kasuga Fukuoka Japan

Global climate change has expedited the growth of renewable generation worldwide, particularly in Japan, which aims to attain carbon neutrality by 2050. Rapid increases in rooftop photovoltaic power and grid constraints in Japan have highlighted the need for efficient demand-management strategies for residential sectors. Under this background, identification of flexible consumers can be decisive for planning demand response (DR) programmes. This study analysed longitudinal data on electricity demand from 2013 to 2014 in a residential building of Osaka Prefecture, Japan. Score analyses quantified individual DR potentials of air-conditioning (AC) loads, a promising DR resource for domestic consumers. Next, the k-medoids clustering approach classified target households and quantile regression models identified household clusters with a high DR potential. Behavioural traits such as the frequency, peak-hour propensity, and grid adversity of AC use depicted the higher AC consumption, larger dwelling size, and daytime occupancy as influential characteristics to increase the potency of DR programmes. Thus, scrutinising the consumers' attributes and AC-usage patterns, this study revealed valuable implications for ramping up DR schemes and contributed to a sustainable energy future.

关键词： Demand response potential Score analysis Peak demand Grid adversity quantile regression model

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：