scholarly journals Spatiotemporal differentiation of urban-rural income disparity and its driving force in the Yangtze River Economic Belt during 2000-2017

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0245961
Author(s):  
Lingling Chen ◽  
Wei Shen
Keyword(s):  
Rural Areas ◽  
Spatial Differentiation ◽  
Economic Factors ◽  
Income Gap ◽  
Rural Income ◽  
Natural Factors ◽  
Urban Rural ◽  
Differentiation Pattern ◽  
Urban And Rural Areas ◽  
Socio Economic Factors

The income imbalance between urban and rural areas has seriously affected social fairness and justice and has become a key factor restricting the sustainable development of the economy and society. The analysis of the spatiotemporal laws and causes of urban-rural income disparity is of great significance to realizing the coordinated and integrated development of regional urban and rural areas. In this study, the coefficient of variation, Theil decomposition index, spatial autocorrelation method and GeoDetector model were used to analyze the spatiotemporal characteristics of the urban-rural income gap and its driving force in the Yangtze River Economic Belt from 2000 to 2017. The results show that the per capita disposable income of urban and rural residents in the study area shows a trend of rapid growth from 2000 to 2017. The urban-rural income gap in the study area showed an inverted "U"-shaped development process as a whole, and the relative difference showed an increasing trend. Regarding the spatial pattern, the study area showed a significant east-west differentiation pattern. The spatial distribution of the urban-rural income gap in the study area has an obvious positive spatial correlation, that is, the phenomena of high-value agglomeration and low-value agglomeration were significant. The economic development level, the industrial structure, the regional development policy, transportation, topographical conditions and resource endowments can strongly explain the spatial differentiation pattern of the urban-rural income gap in the study area. The spatial differentiation pattern of the urban-rural income gap is affected by both natural factors and socioeconomic factors. Among them, socioeconomic factors are the dominant factors, followed by natural factors. There is a significant interaction between natural factors and socio-economic factors, and the combination of socio-economic factors and adverse natural factors can significantly affect the regional urban-rural income gap.

scholarly journals Effect of the International Tourism Island Policy on Hainan Farmers’ Income and the Urban–Rural Income Gap: An Analysis Based on the GPCA and SCM Models

2021 ◽  
Vol 25 (5) ◽  
pp. 592-600
Author(s):  
He Xia ◽  
Shaoying Wu ◽  
◽  
Keyword(s):  
Rural Areas ◽  
Control Method ◽  
Principal Component ◽  
International Tourism ◽  
Kuznets Curve ◽  
Synthetic Control ◽  
Income Gap ◽  
Rural Income ◽  
Urban Rural ◽  
Urban And Rural Areas

The construction of Hainan International Tourism Island, one of the national strategies in China, implemented in January 2010. A common concern is whether the policy has managed to raise farmers’ income and reduce the income gap between urban and rural residents. Therefore, this study aims to make counterfactual causal inferences based on data from 2005 to 2018 on Hainan Province. This study applies both the generalized principal component analysis method and the synthetic control method. According to the model results, the policy did not increase farmers’ income in Hainan or narrow the income gap between urban and rural areas in the first five years. However, after 2014, the result reversed. The increasing farmers’ income and narrowing gap indicate that the tourism-related Kuznets curve hypothesis is valid for the policy. The results of a placebo test verify the robustness of this conclusion.

scholarly journals Does High-Speed Railway Influence Convergence of Urban-Rural Income Gap in China?

2020 ◽  
Vol 12 (10) ◽  
pp. 4236
Author(s):  
Weidong Li ◽  
Xuefang Wang ◽  
Olli-Pekka Hilmola
Keyword(s):  
Rural Areas ◽  
High Speed ◽  
Factor Model ◽  
High Speed Railway ◽  
Income Gap ◽  
Rural Income ◽  
Convergence Clubs ◽  
Convergence Club ◽  
Urban Rural ◽  
Urban And Rural Areas

Transportation is an important factor affecting the balance of regional economic pattern. The construction of high-speed railway enhances the mobility of population, capital, technology and information resources between urban and rural areas. Will it further affect the income gap between urban and rural areas? Based on the nonlinear time-varying factor model, this paper analyzes the convergence of urban-rural income gap with the angle of high-speed railway. After rejecting the assumption of overall convergence in the traditional four economic regions, three convergence clubs of urban-rural income gap were found. For these ordered logit regression model is used to explore the initial factors that may affect the formation of “convergence club”. Empirical results show that the construction of High-speed railway has effectively narrows the urban-rural income gap in China, but it is not the cause of the formation of the three convergence clubs. The convergence effect of High-speed railway on the urban-rural income gap in China is still relatively weak.

scholarly journals Urbanization and the Urban–Rural Income Gap in China: A Continuous Wavelet Coherency Analysis

2020 ◽  
Vol 12 (19) ◽  
pp. 8261
Author(s):  
Yiguo Chen ◽  
Peng Luo ◽  
Tsangyao Chang
Keyword(s):  
Rural Areas ◽  
Local Governments ◽  
Coordinated Development ◽  
High Frequencies ◽  
Income Gap ◽  
Rural Income ◽  
Urban Rural ◽  
Urban And Rural Areas ◽  
Wavelet Coherency ◽  
The Relationship

This study applies wavelet analysis to examine the relationship between the urbanization and the urban–rural income gap in 31 provinces in China over the period 1978–2019. We find three patterns of causality between urbanization and the urban–rural income gap. Empirical results show that urbanization does Granger-cause an urban–rural income gap, the urban–rural income gap does Granger-cause urbanization, and there exists a two-way causality between the urban–rural income gap and urbanization. Furthermore, these relationships mainly exist at high frequencies (short term). The results obtained by considering the resident population are more significant than those by the registered population. These results could help local governments develop fair policies for urban and rural income distribution in the process of urbanization of different provinces, promoting the coordinated development between urban and rural areas.

Agriculture Biomaterial Industry in Romania

2021 ◽  
Vol 10 (1) ◽  
pp. 32-44
Author(s):  
Irina Bancescu
Keyword(s):  
Rural Development ◽  
Rural Areas ◽  
Urban Areas ◽  
Rural Poverty ◽  
Value Added ◽  
Poverty Rate ◽  
Economic Implications ◽  
Income Gap ◽  
Rural Income ◽  
Urban Rural

Rural areas in Romania are underdeveloped, with the main economic activity being agriculture. Urban-rural income gap and poverty levels are indicative of an underdeveloped rural area. Urban-rural absolute income gap for average monthly income increased from 352 RON in 2007 to 663 RON in 2017. Moreover, the work poverty rate is higher in rural areas than in urban areas. Economic rural development can be achieved by improvements of the labour market and introduction of new value-added products. Agricultural and non-agricultural activities are dependent on each other for a successful rural development leading to poverty alleviation. An industry that combines the two types of economic activities is agriculture biomaterial industry. In this paper, the authos investigates the factors influencing rural poverty and analyses the current stage of the bioplastics market in Romania and its economic implications. Bioplastics industry can reduce urban-rural income gaps and poverty in rural areas.

scholarly journals Rural - urban income gap and labour market in Romania

2021 ◽  
Vol 95 ◽  
pp. 01003
Author(s):  
Irina Băncescu
Keyword(s):  
Labour Market ◽  
Rural Areas ◽  
Reverse Flow ◽  
Income Effect ◽  
Gap Effect ◽  
Migration Flow ◽  
Income Gap ◽  
Rural Income ◽  
Urban Rural ◽  
Urban Income

Rural – urban income gap is an important social-economic development indicator for a society. A large rural - urban income gap within a society reveals a split of it into two distinct societies, one extremely poor compared to the other. In Romania, almost half of the resident population lives in rural areas (46.02% in 2019), while the urban-rural migration flow is higher than the traditional reverse flow since 1997. However, the country is characterized by regional economic disparities, Bucharest-Ilfov region being the most economically developed. Labour market in rural areas is underdeveloped, rural population being highly depended on subsistence agriculture. Furthermore, rural areas have a low level of income and living standards. In this paper, we analysis the rural-urban labour market dynamics and rural-urban income gap using a LMDI (logarithmic mean Divisia index) decomposition for 2005-2019 period. Factors such as income gap effect and structural rural income effect are considered. Results show that the total urban–rural income gap has decreased with 8.91%, while structural rural income effect contributed with an increase of only 0.63%, the income gap effect (of different employed population groups) being of -9.49%.

Would Urban–Rural Income Gap Affect Carbon Dioxide Emissions? Empirical Research Based on the Extended IPAT Model

2016 ◽  
Vol 04 (02) ◽  
pp. 1650014 ◽  
Author(s):  
Lei HU
Keyword(s):  
Carbon Dioxide ◽  
Energy Efficiency ◽  
Energy Conservation ◽  
Rural Areas ◽  
Carbon Dioxide Emissions ◽  
Emission Reduction ◽  
Empirical Test ◽  
Income Gap ◽  
Rural Income ◽  
Urban Rural

At present, there’s no agreement on how income gap affects carbon dioxide emissions. In this study, the author takes an empirical test of the relationship between income gap and carbon dioxide emissions based on the extended IPAT model, using China’s provincial panel data of from 2000 to 2012. The conclusion supports Boyce’s point of view that excessive income gap between urban and rural areas leads to environmental degradation. Meanwhile, the study introduces the cross terms of urban–rural income gap ratio and energy efficiency, and finds that excessive income gap would be an obstacle for China to achieve energy conservation and emission reduction by improving energy efficiency. Therefore, while promoting actions to climate change, energy conservation and emission reduction, governments should also narrow urban–rural income gap besides relying on the restrictions of relevant laws and regulations.

Rural credit input, labor transfer and urban–rural income gap: evidence from China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Guohua Yu ◽  
Zheng Lu
Keyword(s):  
Rural Areas ◽  
Industrial Structure ◽  
Content Type ◽  
Rural Credit ◽  
Income Gap ◽  
Rural Income ◽  
Urban Rural ◽  
Labor Transfer ◽  
Theoretical Mechanism ◽  
Agricultural Industries

PurposeThe purpose of this study is to elaborate the theoretical mechanism of rural credit input affecting the urban–rural income gap from the perspective of labor transfer, and use a dynamic panel mediation model to test the transmission mechanism of rural credit input affecting the urban–rural income gap through labor transfer, so as to provide an empirical basis for narrowing the urban–rural income gap in China.Design/methodology/approachThis paper constructs a mechanism analysis framework for rural credit input affecting the urban–rural income gap. From the perspective of resource allocation and labor transfer, the authors expound the transmission path of rural credit input to the urban–rural income gap and analyze the theoretical mechanism of rural credit input that affects the urban–rural income gap through labor transfer. Based on this, this paper uses the dynamic panel mediation model to test the effect relationship between rural credit input, labor transfer and urban–rural income gap in 31 provinces of China from 2009 to 2018.FindingsIn theory, increasing rural credit input can ease the financial constraints on the development of “agriculture, rural areas and farmers” and provide capital accumulation for the development of rural non-agricultural industries. The development of rural non-agricultural industries can provide more jobs for rural surplus labor, thereby increasing the labor rate of return in rural areas, and ultimately conducive to narrowing the urban–rural income gap. Further, increasing rural credit input can improve the development level of rural non-agricultural industries, thereby promoting the transfer of agricultural labor. At the same time, rural credit input based on the intermediary variable of labor transfer has a significant inhibitory effect on the urban–rural income gap.Research limitations/implicationsThis study mainly focuses on the relationship between rural credit input, labor transfer and urban–rural income gap, so it is impossible to use micro-level data to further verify the impact of rural credit input on labor transfer. At the same time, the collection of indicators of rural credit investment in the China Financial Yearbook only started in 2009, which limited the number of samples to a certain extent.Practical implicationsThis paper assumes that the economy is mainly composed of urban and rural economic sectors. Therefore, labor can flow freely between urban and rural areas. However, in the near future, China's rural secondary and tertiary industries may develop rapidly, especially with the in-depth implementation of rural revitalization strategy, it is very important to pay attention to the current situation of rural industrial structure and incorporate the factors such as rural industrial structure into the existing model.Social implicationsThis study attempts to provide a new perspective and inspiration for rural credit input, the optimal allocation of labor force and narrowing the urban–rural income gap under China's rural revitalization strategy.Originality/valueBased on the analysis framework of neoclassical economic theory, this paper uses the constant elasticity of substitution production function to establish an urban–rural two-sector nested model that includes credit supply variables and analyzes the mechanism of rural credit input affecting the urban–rural income gap through labor transfer.

scholarly journals Financial Deepening, Spatial Spillover, and Urban–Rural Income Disparity: Evidence from China

2020 ◽  
Vol 12 (4) ◽  
pp. 1450 ◽  
Author(s):  
Maosheng Ran ◽  
Liang Chen ◽  
Wanli Li
Keyword(s):  
Financial Development ◽  
Rural Areas ◽  
Proximity Effect ◽  
Local Effect ◽  
Income Disparity ◽  
Financial Deepening ◽  
Rural Income ◽  
Central Regions ◽  
Urban Rural ◽  
Urban And Rural Areas

Financial development is one of the main sources of economic growth, whether financial deepening can lower the income inequality between urban and rural areas has been the focus of policy makers and researchers. Using data from 31 provinces in China, from 2002 to 2013, this paper examines the impact of financial deepening on income inequality between urban and rural areas. These empirical results show that financial deepening is significantly negatively associated with urban–rural income disparity, that is, for every 1% increase in financial deepening urban–rural income disparity can be reduced by about 0.5%. Further research has investigated that the influence of financial deepening on income disparity has a selective effect. From the decomposition effect of financial deepening, we also find that the proximity effect of the Eastern and Central regions is higher than that of the local effect, while the local effect of the Western region is higher than that of the Eastern and Central regions, but the proximity effect is not significant. The conclusion of this paper is of great significance to further deepen financial reform, improve the quality of financial development, and achieve sustainable development of economy.

scholarly journals Comparative Study of E-Learning Readiness and Socio-Economic Factors during Covid-19 Pandemic: Evidence from High School Students in Urban and Rural Areas of Indonesia

2021 ◽  
Author(s):  
Moch. Bambang Sulistio ◽  
Keyword(s):  
High School Students ◽  
Rural Areas ◽  
Urban Areas ◽  
Online Survey ◽  
Economic Factors ◽  
School Students ◽  
Learning Readiness ◽  
E Learning ◽  
Urban And Rural Areas ◽  
Socio Economic Factors

As the global pandemic of COVID-19 spreads enormously, educational institutions were forced to close down in most countries, affecting 91% of pupils and causing massive disruption to the education sector. In Indonesia, 62, 5 million students from pre-primary to higher education are forced to shift from conventional learning to a complete move into e-Learning. This study sought to explore students' readiness to cope with online learning both in urban and rural areas of Indonesia and to find the relation whether socio-economic factors during pandemic affect their e-learning readiness. The theory underpinning the study was the e-Learning Readiness theory which measures eight dimensions: human resource, financial, technological, equipment, content, psychological, sociological, and environmental readiness. An online survey was conducted, and a total of 1.260 million students in urban and 846 students in rural areas participated in the study. The data were analyzed using multiple regression and confirmatory factor analysis (CFA). This study reveals that students in urban areas are categorized as ready, but they need improvements in several aspects with the readiness index 3, 47. In contrast, students are not ready in rural areas and need several improvements with index 3,01. The study also highlights that basic IT skills competencies are critical for the preparedness of e-learning and should be taught to students. Future studies could analyze whether ICT training will significantly impact their perceives and acceptance of students' e-learning readiness, especially in rural areas, after training has been conducted.

scholarly journals Trends in overweight by socio-economic status in Vietnam: 1992 to 2002

2007 ◽  
Vol 10 (2) ◽  
pp. 115-121 ◽  
Author(s):  
Minh Duc Nguyen ◽  
Shirley AA Beresford ◽  
Adam Drewnowski
Keyword(s):  
Rural Areas ◽  
Economic Status ◽  
Age Groups ◽  
National Health Survey ◽  
Living Standard ◽  
Economic Factors ◽  
Socio Economic Status ◽  
Food Expenditures ◽  
Urban And Rural Areas ◽  
Socio Economic Factors

AbstractObjectiveTo explore socio-economic factors associated with rising rates of overweight among Vietnamese adults.DesignThe study was based on three national surveys of socio-economic factors and health conducted over a 10-year period. The studies were: the Vietnamese Living Standard Survey 1992–1993 (11 982 participants); the Vietnamese Living Standard Survey 1997–1998 (15 975 participants); and the Vietnamese National Health Survey 2001–2002 (94 656 participants).SubjectsMale and female adults >18 years old were stratified by gender, age group, area of residence, occupation, education and relative food expenditures. Overweight was defined using body mass index (BMI) ≥ 25 kg m− 2.ResultsOverweight rates in Vietnam more than doubled between 1992 and 2002 (from 2.0 to 5.7%). Significant increases were observed for men and women, in urban and rural areas, and for all age groups. In univariate analyses, both age and higher socio-economic status were associated with higher rates of overweight. Using the most recent survey, urban populations were more likely to be overweight than rural ones (odds ratio (OR) = 1.79), white-collar workers were more likely to be overweight than manual labourers (OR = 1.95) and persons in the top level of food expenditures were more likely to be overweight than persons in the bottom level (OR = 4.96) after adjustment for other factors. Education was inversely associated with overweight after adjusting for covariates.ConclusionEconomic growth and improved standard of living are associated with higher rates of overweight in nations in early stages of economic development. In Vietnam, higher rates of overweight were observed among the higher income and occupation groups.

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