Carbon emissions, logistics volume and GDP in China: empirical analysis based on panel data model

Guo, Xiaopeng; Ren, Dongfang; Shi, Jiaxing

doi:10.1007/s11356-016-7615-z

Cited by 33 publications

(18 citation statements)

References 32 publications

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“…Furthermore, the application of the panel data models avoided information loss of the data. Compared with the cross-sectional data, the panel data might reflect the optimal validity of data by arranging the crosssectional data and time-series data together [22,27].…”

Section: Discussionmentioning

confidence: 99%

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Maternal health services utilization and maternal mortality in China: a longitudinal study from 2009 to 2016

Zhao

Han

You

et al. 2020

BMC Pregnancy Childbirth

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Background: The Chinese government introduced the maternal health services as part of the Basic Public Health Service (BPHS) project in 2009. While China has made progress in reducing maternal mortality, the longitudinal association between the utilization rate of the maternal health services of the BPHS project and such reduction was rarely evaluated with robust methods. Methods: We conducted a longitudinal study on the maternal health service utilization rates of the BPHS project and the maternal mortality ratios (MMR) in mainland China and its 31 provincial regions. The data were extracted from the National Health Statistic Yearbooks (2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016). Panel data models were used to evaluate the association between the utilization rate and the MMR after adjusting for available covariates on healthcare resources. Stepwise regression models were used to gauge the direction and magnitude of omitted variable bias. Results: It was found that the service utilization rate increased from 79.24% in 2009 to 91.67% in 2016, while MMR decreased from 30.90 to 17.88 per 100,000 livebirths at the national level. The results of the fixed effects panel data model revealed that the utilization rate was associated with MMR deduction continuously. With every 1% increase in utilization rate, the maternal death would decrease by 0.35 per 100,000 livebirths after having the health resources variables adjusted. Conclusions: The utilization of maternal health services increased continuously after the introduction of BPHS project in 2009 and MMR went downward from then on. The utilization of maternal health services did have significant association with MMR and could reduce MMR effectively. Such improvement could be attributed to the fact that this program was designed to serve the targeted population throughout the continuum of maternal care and the government's rigorous efforts in stressing equality and standard care in program implementation.

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Section: Discussionmentioning

confidence: 99%

“…As for the panel data models, pooled effects model, fixed effects model and random effects model were all applied in this study. Comparing to linear models, these panel data models were more effective in controlling confounding factors [27]. The F test and the Hausman-type test would be used for model selection [28].…”

Section: Statistics Analysesmentioning

confidence: 99%

Maternal health services utilization and maternal mortality in China: a longitudinal study from 2009 to 2016

Zhao

Han

You

et al. 2020

BMC Pregnancy Childbirth

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“…The superiority of the panel data model is that it can increase the estimator precision by increasing the number of observations and obtain more dynamic information than a single cross sectional data [28], which can reflect the optimal validity of data [27]. Furthermore, the fixed effects model can eliminate the influence of individual-variant but time-invariant unobserved confounders in the study [31].…”

Section: Methodsmentioning

confidence: 99%

“…Compared with the traditional statistical analysis, the panel data model can control both observed and unobserved confounding factors within individuals [24,25] and is more suitable for the longitudinal data analysis by connecting individual experience and behaviors at different time points [25,26,27,28]. In this study, we aim to reconsider sleep duration and sleep problems in infants and their association with body weight by using the panel data model analysis based on a retrospective longitudinal cohort of Chinese infants.…”

Section: Introductionmentioning

confidence: 99%

Association between Sleep and Body Weight: A Panel Data Model Based on a Retrospective Longitudinal Cohort of Chinese Infants

Sha

Gao

Xiang

et al. 2017

IJERPH

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The focus of this article is on sleep duration and sleep problems in infants and their association with body weight. A retrospective birth cohort of 519 infants was enrolled in a community-based study conducted in Changsha, China. Infant weight and other health-related information were collected during regular standard checkups at the Community Health Service Centers when infants were 1, 3, 6, 8, and 12 months old. The sleep duration and sleep problems of infants were assessed by maternal self-reports. Panel data model was used to evaluate the association of sleep duration and sleep problems with infant body weight. Significant relevance between self-reported sleep duration and weight of infants has been reported in the literature tested by the fixed effects model (p < 0.01). However, this study indicated that sleep problems of infants had no effect on their weight (p = 0.151), after adjusting feeding patterns and socioeconomic factors of their families. This paper argues that, as a potentially modifiable risk factor, infant sleep duration deserves more attention from their parents and families in order to prevent and control overweight or obesity in infants as well as reducing the incidence of obesity in adults.

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“…Lakew et al used panel data to analyze air cargo costs in the United States, airport traffic and airport delays in the aviation industry [31]. Guo et al studied the relationship among carbon emissions, GDP, and logistics by using a panel data model and a combination of statistics and econometrics theory [32]. Considering data as a panel, not just a cross-sectional or time series data, has multiple advantages.…”

Section: The Cargo Handling Capacity Data Released By the Statistics mentioning

confidence: 99%

Estimation of Cargo Handling Capacity of Coastal Ports in China Based on Panel Model and DMSP-OLS Nighttime Light Data

Liu

Wei

et al. 2019

Remote Sensing

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The cargo handling capacity of a port is the most basic and important indicator of port size. Based on the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) nighttime light data and panel model, this study attempts to estimate the cargo handling capacity of 28 coastal ports in China using satellite remote sensing. The study confirmed that there is a very close correlation between DMSP-OLS nighttime light data and the cargo handling capacity of the ports. Based on this correlation, the panel data model was established for remote sensing-based estimation of cargo handling capacity at the port and port group scales. The test results confirm that the nighttime light data can be used to accurately estimate the cargo handling capacity of Chinese ports, especially for the Yangtze River Delta Port Group, Pearl River Delta Port Group, Southeast Coastal Port Group, and Southwest Coastal Port Group that possess huge cargo handling capacities. The high accuracy of the model reveals that the remote sensing analysis method can make up for the lack of statistical data to a certain extent, which helps to scientifically analyze the spatiotemporal dynamic changes of coastal ports, provides a strong basis for decision-making regarding port development, and more importantly provides a convenient estimation method for areas that have long lacked statistical data on cargo handling capacity.

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Carbon emissions, logistics volume and GDP in China: empirical analysis based on panel data model

Cited by 33 publications

References 32 publications

Maternal health services utilization and maternal mortality in China: a longitudinal study from 2009 to 2016

Maternal health services utilization and maternal mortality in China: a longitudinal study from 2009 to 2016

Association between Sleep and Body Weight: A Panel Data Model Based on a Retrospective Longitudinal Cohort of Chinese Infants

Estimation of Cargo Handling Capacity of Coastal Ports in China Based on Panel Model and DMSP-OLS Nighttime Light Data

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