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The purpose of this paper is to present a nonparametric comparative study on the HCMS consumption of urban and rural households in China.

This paper applies the panel data for China's thirty provinces in 1991‐2007 as a sample and presents a local linear estimation to the nonparametric Working‐Leser panel data models on the HCMS consumption of the rural and urban households in China. The nonparametric Hausman test is applied to test the random effects specification against the fixed effects.

Both the parametric and nonparametric estimation of the Working‐Leser panel data models give us a similar result: that the HCMS commodity is quite elastic in both the rural and urban China. Nonparametric estimate also shows that the urban‐rural difference of the HCMS expenditure share in the total expenditure is mainly due to the large urban‐rural difference of total expenditure. Under the same total expenditure, the HCMS is more elastic in the urban than in the rural regions.

To decrease the urban‐rural difference in the HCMS consumption, the government should enhance the income or total expenditure level of the rural households, especially in the impoverished and remote areas in China. Urbanization plays a critical role in access to health care and can help make substantial changes in rural health care in China.

Compared to the parametric estimation, the nonparametric estimation gives us the added information that the expenditure elasticity of the HCMS consumption in China gradually declines as one moves up the per capita total expenditure distribution. The paper could make a contribution to the relatively thin literature on the Chinese medical and health consumption market.

Health is an important issue in our life. A person with good health will have peace of mind and will be able to contribute to nation-building. We cannot expect performance from an ill person with a low morale. In the present paper, the authors tried to understand the ground realities of health-care facilities provided in India and more specifically in Odisha, India.

This empirical paper used a non-experimental design to test a proposed model based on a review of relevant literature. In this paper, an initial pilot study was conducted by taking 44 various variables; however, after the study and taking the expert opinion, the variables were restricted to only 30. For the purpose of study, only state-sponsored hospitals were considered on a random sampling method.

The analysis of data is conducted on a simple percentage method with closed-end options. It is found that even after 67 years of independence, people do not have access to basic medical care facilities in the rural areas and to some extent in semi-urban areas also. The major stumbling block is inadequate infrastructure in these hospitals.

While this study offers some insight into the status of healthcare infrastructure in rural India, the sample was limited to respondents in state-sponsored hospitals, which may not represent the views about private hospitals.

It seems that in some interior areas of Odisha, people rely more on their fate than then these health-care services.

Various governments claim that they are spending millions of rupees on health-care service, but the benefits are not being felt by the masses. We are sure that our attempt to highlight the scenario of health-care services in the state of Odisha will be an eye opener and will compel the various stake holders to introspect their involvement in the health-care services provided in these areas.

A considerable amount of research has been done evaluating the status of healthcare in India, but this is the first empirical research study to date based on respondents from the rural parts of the state of Odisha in India. Some of these areas are not reachable to researchers due to the poor infrastructure. This contribution is also of special importance amid the recent criticism of the healthcare infrastructure in India by prominent management scholars.

Literature has shown that the intergenerational transmission of cognitive abilities is stronger for children raised in more advantaged environments. However, there has never been an empirical investigation of this pattern in China. This study examines differences in the intergenerational transmission of cognitive capabilities among mothers and young children in urban and rural subpopulations in China and investigates whether these differences are driven by differences in parental investment in the home environment.

Data collected from randomly selected 6- to 36-month-old babies and their mothers in a Northwestern province in China was used. Child capabilities were assessed by the Bayley Scales of Infant and Toddler Development (3rd edition). Maternal intelligence quotient (IQ) scores were assessed with the Raven’s Progressive Matrices test. The non-parametric regression methods were used to construct the factor scores of child capabilities. The ordinary least squares (OLS) models were employed to investigate the relations between child cognition, maternal IQ and parental investment.

In urban households, where most children are raised in a positive home environment, child cognitive scores are strongly correlated with maternal IQ. In rural households, where parental investments are lower and more variable, child cognitive scores are not significantly correlated with maternal IQ but are predicted by differences in parental investments in a cognitively stimulating home environment.

This study provides a unique contribution by utilizing rural–urban disparities in China as a unique natural experiment to investigate differences in the transmission of cognitive capabilities across socioeconomic status (SES). It also provides the first empirical evidence of SES differences in the intergenerational transmission of cognitive capabilities in a developing country. This study reveals that intergenerational mother–child cognition associations are disrupted by poor parental investment in rural households but not in urban households.

Since smartphones became ubiquitous, online grocery and food purchases through take-away delivery platforms have steadily increased in China. Nevertheless, whether the development of take-away delivery can ameliorate urban–rural wage inequality still requires further analysis. The purpose of this paper is to clarify whether this positive effect exists.

This paper makes estimations based on city and individual levels combining the Chinese Household Income Project (CHIP) 2008, CHIP 2013, CHIP2018 survey data and the take-away delivery site data. At the city level, the Oaxaca-Blinder (O-B) decomposition method is employed to construct wage inequality index of urban and rural labors. At the individual level, this paper analyzes urban–rural wage differentials with high or low formal education level.

The rapid establishment of take-away delivery sites has resulted in an increase of 52.425 yuan on average in the annual wage of rural labors with low formal education level. When the cumulative number of sites increases by 1 unit, the annual wage inequality index decreases by 0.007 on average. Labors with the characteristics of rural household registration and low education can enjoy more dividends. Through inter-/within-industry decomposition, this paper elaborates formal education, age and cross-industry transfer as the main factors for the improvement of urban–rural wage inequality. Narrowing effect of wage differences between different groups in multiple sample slices also contributes to the mechanism analyses.

To the best of the author’s knowledge, this paper is the first to analyze the impact of take-away delivery development on the urban–rural wage inequality from the perspective of the establishment of take-away delivery sites. This empirical study will enrich the existing theoretical perspectives on urban–rural divide under the emergence of new forms of employment. The results indicate that new forms of employment represented by take-away delivery can not only promote economic growth, but also eliminate urban–rural inequality.

This study aims to conduct a geographical analysis of the distribution and type of activities developed by social enterprises in rural and urban areas of Ireland.

The study analyses data of more than 4,000 social enterprises against a six-tier rural/urban typology, using descriptive statistics and non-parametric tests to test six hypotheses.

The study shows a geographical rural–urban pattern in the distribution of social enterprises in Ireland, with a positive association between the remoteness of an area and the ratio of social enterprises, and a lack of capital-city effect related to the density of social enterprises. The analysis also shows a statistically significant geographical rural–urban pattern for the types of activities developed by social enterprises. The authors observe a positive association between the remoteness of the areas and the presence of social enterprises operating in the community and local development sector whereas the association is not significant for social enterprises developing welfare services.

The paper shows the potential of using recently developed rural–urban typologies and tools such as geographical information systems for conducting geographical research on social enterprises. The findings also have implications for informing spatially sensitive policymaking on social enterprises.

The merging of a large national data set of social enterprises with geographical tools and data at subregional level contributes to the methodological advancement of the field of social enterprises, providing tools and frameworks for a nuanced and spatially sensitive analysis of these organisations.

This paper examines the impact of residents’ human capital investment inequality on the urban–rural income gap, using China’s provincial panel data from 1997 to 2013. The results show that, at the national level as well as at the regional level, residents’ overall human capital investment inequality has a positive significant impact on the urban–rural income gap. In addition, the impact of overall human capital investment inequality increased monotonically from the eastern region inward to the western region. In terms of the relative impact of each component of human capital investment inequality on the urban–rural income gap, migration investment inequality appears to have the greatest impact at the national level, whereas health investment inequality has the greatest impact on the urban–rural income gap in the eastern region, and education investment inequality exhibits the greatest impact in the central and western regions. We also investigate the impact of human capital investment inequality on the urban–rural income gap over different periods. The results show that residents’ overall human capital investment inequality had a positive impact on the urban–rural income gap in the period 1997–2008, but the impact rapidly shrunk in 2009–2013. Furthermore, the impact of residents’ health investment inequality on the urban–rural income gap shows a downward trend, and the impact of residents’ education investment inequality trended slightly upward from 1997 to 2008, and then rapidly shrunk in 2009–2013. Finally, the impact of residents’ migration investment inequality was only significant in 1997–2002.

In the United States, there is little difference in annual income inequality and income mobility between the rural and urban sectors of the economy. This forms a sharp contrast with China where income inequality is greater and income mobility lower among rural households than among urban households. When incomes are averaged over three years and when adjustments are made for the size and composition of households, income inequality among all households differs little between China and the United States in the 1990s. Moreover when pooling rural households and urban households and when measuring annual income inequality and income mobility of the pooled households, the mobility of incomes of households in the United States differs little from that in China. Social welfare functions are posited that allow for a trade-off between increases in income and increases in income inequality. These suggest strong increases in well-being for urban households in China. The corresponding changes in rural China and in the United States are smaller. Four sets of data on households are drawn on to document these findings.

The aim is to depict the effects of the rural-urban transformation visible in most western societies during the last few decades by examining the Swedish-speaking part of Finland, a geographically divided region kept together by a common language and culture. Everything from the remotely rural to the very central urban is represented here, as well as all possible types of outcomes of the post-industrial urbanization process: growing metropolitan centres, suburbs and commuting areas, declining smaller regional centres, counter-urbanization, and both viable and declining rural areas.

Population mobility may upset the formation (or preservation) of communities, and while these are vital for any sound and well-functioning society, we see a sense of community as especially crucial for the survival of minority populations. The empirical study consists of an overview of demographic trends during the time period from 1980 onwards to 2012, and in parallel, an overview of mobility patterns between urban and rural areas as well as of commuting.

The late modern trend of counter-urbanization is visible in our material, but still, while this does not extend outside the narrow commuting area, counter-urbanization may not be comprehended as a major trend in the Swedish-speaking regions. The main finding is the effect on communities of urbanization and counter-urbanization depicted by the ability to ‘live in Swedish’ in the different types of areas on the rural-urban scale. The study shows that while an area seemingly thrives, with evidence of population growth and in-migration, a high level of mobility may still hurt the prerequisites for community formation.

This chapter brings new knowledge on the effects of transformation in metropolitan and urban ruralities, as well as focus on social sustainability in these localities. The case study Sundom, Vaasa, Finland, highlights areas under pressure of transformation. ‘Metropolitan ruralities’ is used here as an umbrella concept, subdivided into metropolitan ruralities and smaller (non-metropolitan) urban ruralities. Qualitative and quantitative research methods are combined in a triangular study. An octagon figure (Fig. 4), including the main variables of the triangular study, is configured, to visualize different variables as a whole. The statistical material is more limited in urban ruralities – for example fewer property trades, less inhabitants and fewer voters – which make these case studies more vulnerable for the impact of extremes. The core of the chapter is to study how and if current global trends in metropolitan ruralities are visible in localities further down the urban scale. A stricter rural gentrification is expected in metropolitan ruralities than in urban ruralities, as the Sundom case exemplifies transformation with mild gentrification. Both metropolitan and urban ruralities are considered ‘breeding grounds’ for new rurban identities, with variations on an urban-rural scale. Metropolitan ruralities are expected to attract more exurbanite migrants, and urban ruralities attract more ‘exruralite’ migrants. This chapter also outlines some practical and social implications, argues for strengthening social sustainability in metropolitan ruralities and puts some much needed focus on transformation in metropolitan as well as non-metropolitan urban ruralities.

Urbanization is driving the growth of China’s carbon footprint. It’s important to investigate what factors, how and to what extent, affect carbon footprints embedded in various categories of rural and urban households’ consumption.

We employ an environmental extended input-output model to assess and compare the rural-urban household carbon footprints and perform a multivariant regression analysis to identify the varying relationships of the determinants on rural and urban household carbon footprints based on the panel data of Chinese households from 2012 to 2018.

The results show evidence of urbanity density effect on direct carbon footprints and countervailing effect on indirect carbon footprints. The old dependency ratio has no significant effect on rural family emissions but has a significantly negative effect on urban direct and indirect carbon footprints. A higher child dependency ratio is associated with less rural household carbon emissions while the opposite is true for urban households. Taking advantage of recycled fuel saves direct carbon emissions and this green lifestyle benefits urban households more by saving more carbon emissions. There is a positive relationship between consumption structure ratio and direct carbon footprints while a negative relationship with indirect carbon footprints and this impact is less significant for urban households. The higher the price level of water, electricity and fuel, the lower the rural household’s direct carbon footprints. Private car ownership consistently augments household carbon footprints across rural and urban areas.

This paper provides comprehensive findings to understand the relationships between an array of determinants and China’s rural-urban carbon emissions, empowering China’s contribution to the global effort on climate mitigation.