Search Results (30)

This paper analyzes the factors affecting the willingness to pay of urban households concerned with efficient waste management in Bangladesh. The multistage random sampling approach selected 1400 families from seven major cities in Bangladesh. This study addresses the socioeconomic and environmental factors that influence urban households’ willingness to pay for improved waste management services in Bangladesh. This study uniquely contributes to the literature by providing a large-scale empirical analysis of 1470 households using a logit model, revealing income, education, and environmental awareness as key predictors of WTP. Detailed survey data from respondents were then analyzed using a logit model based on the contingent valuation method. Indeed, the logit model showed that six variables (education, monthly income, value of the asset, knowledge of environment, and climate change) had a statistically significant effect on the WTP of the households. The results show that 63% of respondents were willing to pay BDT 250 or more per month. The most influential factors driving this willingness to pay were income (OR = 1.35), education level (OR = 1.45), and environmental awareness (OR = 3.56). These variables all contribute positively towards WTP. The idea is that families have some socioeconomic characteristics, regardless of which they are ready to pay for a higher level of waste collection. It is recommended that government interference be affected through various approaches, as listed below: support for public–private sector undertaking and disposal, an extensive cleaning campaign, decentralized management, cutting waste transport costs, and privatization of some waste management systems. These could be used to develop solutions to better waste management systems and improve public health. Full article

In the context of increasing digitization, integrating ICT technologies, artificial intelligence, and remote working is altering residential mobility patterns and housing preferences. This study examines the housing market’s impact, focusing on how residential affordability affects residential choices, using a case study of the Metropolitan City of Florence. The analysis employs a methodology centered on the Debt-to-Income Ratio (DTI), which cross-references real estate market values (source: Agenzia delle Entrate and leading real estate portals) with household income brackets to identify affordable areas. The results reveal a clear divide: households with incomes below EUR 26,000 per year (representing about 69% of the population) are excluded from the central urban property market. This evidence confirms regional and national trends, emphasizing a growing mismatch between housing costs and disposable incomes. The study concludes that affordability is a technical–financial parameter and a valuable tool for supporting inclusive urban planning. Its application facilitates the orientation of effective public policies and the identification of socially sustainable housing solutions. Full article

Access to clean drinking water is fundamental to human health, but a significant portion of China’s population lacks this essential resource due to low water quality. Point-of-use (POU) water filtering systems, offering ease of installation and maintenance, have emerged as a viable solution for providing clean drinking water in China. However, despite their advantages, the adoption rate remains below 20%. This study investigates whether and how price affordability affects the adoption of residential POU water filtering systems in China. In doing so, we conduct a quantitative analysis of the national POU water filtering systems sales and household income data from 2007 to 2022 in China. Our results show that the ratio of the initial purchase price to per capita disposable income and the adoption rate of POU systems in China are strongly positively correlated. Our findings shed light on potential pathways to facilitating their wider adoption, not only in China but also in other emerging countries. Full article

The Chinese food industry has opposed the mandatory inclusion of increased nutrients in the Nutrition Facts Table (NFT), thus impeding its improvement. This poses a challenge to the endeavors aiming to assist consumers in cultivating healthy dietary habits that incorporate reduced saturated fatty acids and added sugars while ensuring the adequate intake of essential micronutrients. This study conducted a choice experiment to investigate Chinese consumers’ preference for updated labeling schemes among 630 adults that were randomly selected from Central, North, East, South, Northwest, Southwest, and Northeast China. It revealed that respondents were willing to pay the highest premium for the most mandatory nutrients (22.575% of the food price per unit). Respondents preferred the NFT with the most mandatory nutrients if they met the following population characteristics: female; non-overweight or obese; without a college degree; possessed an annual household disposable income between 50,000 and 99,999 CNY; from North China; lived in rural areas and often cooked for family; cared about food nutrition. Two combinations of NFT information received the highest preference: (1) the NFT detailing the most mandatory nutrients and their content values and nutrient reference values (NRV%); (2) the NFT containing the most nutrients and the nutrients in 100 g/mL or a serving. The first and second combinations attracted a premium of 14.884% and 31.833% of the food price per unit, respectively. Full article

This paper analyses the relationship between household debt and income inequality in South Africa for the period 1980–2021. We use two measures of inequality and estimate a vector error correction model (VECM) which includes household debt, inequality, and other macroeconomic variables. To test the robustness of our results, single equation models are used, which estimate household debt as a function of inequality and macroeconomic factors. We employ two measures of inequality, namely Gini coefficient and ratio of top and bottom income earners’ proportion of income. Furthermore, we use both household debt as a percentage of disposable income and household debt service costs as dependent variables in single equation regressions. The study finds a negative and significant relationship between household debt and income inequality in the long run, which contradicts the Rajan hypothesis in the South African case. Rather, we find that inequality in South Africa creates a bias in debt allocation towards high-income earners, whose incomes can easily absorb the extra debt (reduced ratio of debt to disposable income). There are therefore no socio-equity considerations in South African credit markets. We find growth in gross domestic product (GDP) per capita also has a moderating effect on the relationship between household debt and income inequality. High GDP per capita growth in the presence of high inequality reduces the impact of inequality on household debt and vice-versa. All other control variables take expected signs. These results are robust to changes in the inequality or household debt measures. Full article

Buildings are considered to have significant emission reduction potential. Residential building carbon emissions, as the most significant type of building-related carbon emissions, represent a crucial factor in achieving both carbon peak and carbon neutrality targets for China. Based on carbon emission data from Henan Province, a large province located in central China, between 2010 and 2020, this study employed the Kaya-LMDI decomposition method to analyze seven driving factors of carbon emission evolution, encompassing energy, population, and income, and assessed the historical reduction in CO₂ emissions from residential buildings. Then, by integrating Kaya identity static analysis with Monte Carlo dynamic simulation, various scenarios were established to infer the future evolution trend, peak time, and potential for carbon emission reduction in residential buildings. The analysis results are as follows: (1) The carbon emissions of residential buildings in Henan exhibited a rising trend from 2010 to 2020, albeit with a decelerating growth rate. (2) Per capita household disposable income is the main driving factor for the increase in carbon emissions, but the household housing purchase index inhibits most of the growth of carbon emissions for the residential buildings in Henan, with the total carbon emission reduction of residential buildings reaches 106.42 million tons of CO₂ during the research period. (3) During the period from 2020 to 2050, residential buildings in Henan Province will exhibit an “inverted U-shaped” trend in carbon emissions under the three static scenarios. The base scenario predicts that carbon emissions will reach their peak of 131.66 million tons in 2036, while the low-carbon scenario forecasts a peak of 998.8 million tons in 2030 and the high-carbon scenario projects a peak of 138.65 million tonnes in 2041. (4) Under the dynamic simulation scenario, it is anticipated that residential buildings in Henan Province will reach their carbon peak in 2036 ± 3 years, with a corresponding carbon emission of 155.34 million tons. This study can serve as a valuable reference for the future development of low-carbon pathways within the building sector. Full article

Food consumption is the vital connection between human beings and natural resources. Our research explores the characteristics and drivers of food consumption patterns within Mongolian grasslands with a vulnerable ecology and environment. Food consumption data were obtained via a household questionnaire survey, and the emergy method was applied to analyze the food consumption characteristics in different grassland areas. This led to the following results: (1) The total per capita food consumption in different banners showed greater consumption and higher percentage of animal-based food in regions farther north. (2) From south to north, the main meat consumption in different banners varied, the predominant meat type consumed in Taibus was pork, that in Zhenglan was mutton, and that in West Ujimqin was beef. The farther north, the more fruits and vegetables were consumed. (3) The characteristics of food consumption in different areas were influenced by a series of factors, including social, economic, and ecological ones. Local food supply and disposable income were the main factors that had important effects on food consumption structure, as these two factors provided accessibility to foods for consumption. Full article

The main purpose of this study is to explore the determinants of average household consumption spending in counties and cities from the two aspects of government fiscal expenditure and household characteristics. A spatial econometric model, the spatial Durbin model, was used to analyze Taiwan’s county-level and municipal panel data from 2000 to 2020. Global spatial autocorrelation and local spatial autocorrelation were applied to examine the overall degree of spatial agglomeration of average household consumption spending in Taiwan and the agglomeration status of specific counties and cities. The empirical results show that the average consumption spending per household of all counties and cities in Taiwan presents spatial autocorrelation, and the agglomeration of specific counties and cities is affected by different ruling parties of the central government. In terms of direct effects, the average consumption spending per household in local counties and cities is influenced by household characteristics, including average disposable income per household, average number of employees per household, and average living area per capita. In terms of the spatial spillover effect, the average consumption spending per household in local counties and cities is influenced by household characteristics of the neighboring counties and cities, including the average disposable income per household and the average living area per capita. Surprisingly, local economic development expenditure and local expenditure on education, science, and culture have no significant impact on the average consumption spending per household in counties and cities. The results of this study can be taken as a reference for government policymaking. Full article

Wales is one of the world leaders in household waste recycling with a steady recent recycling rate of ~65%. The Welsh Assembly Government (WAG) set a statutory target of achieving a 70% recycling rate by 2024/25. We reviewed historical trends in waste management in Wales from 2006 to 2020, with a focus on recycling. Authoritative, official data were obtained from WasteDataFlow, an Internet system for municipal waste data reporting by UK local authorities to government. Data are collected quarterly allowing the generation of time series plots, trendlines and like-for-like comparisons between groupings of various characteristics, such as number of separate kerbside collections, income, political preference, and impact of policy changes. Results showed that the approach taken by the WAG to politically prioritise and encourage participation in household recycling has achieved impressive results that contrast starkly with the recycling performance of other UK countries. In Wales, household waste disposed annually per person via landfill decreased from ~410 kg to <50 kg and household waste recycled increased from to ~150 kg to ~310 kg, with a recent increase in incineration with energy recovery to ~135 kg as infrastructure has come online. Recycling rates show a seasonal variation due to increases in garden waste sent for composting in the summer. There are variations in local authority performance across Wales, mainly caused by variations in the number of separate collections. Co-mingled collections tend to lead to higher contamination of recyclates that are then not able to be sold for recycling. Deprivation, as indicated by differences in income, also influences total waste arisings and recycling rates. A plateau of ~65% recycling rate was reached in 2020, with incineration reaching a rate of >25%. The recycling rate plateaus at exactly the same time as incineration comes on stream. Evidence demonstrates that improvements to recycling rates can become more difficult when incineration becomes available. Whilst further reductions and improvements to recycling in Wales will be more challenging, the WAG’s track record of focused proactive political and policy support shows what can be achieved when there is suitable political will. The WAG has demonstrated that it tends to deliver on its waste-related plans, and it clearly has the best chance of any of the UK’s four countries of achieving its aims. Full article

Since the beginning of the new century, China’s carbon emissions have increased significantly, and the country has become the world’s largest carbon emitter. Therefore, determining the influencing factors of carbon emissions is an important issue for policymakers. Based on the panel data of 30 provinces and cities across the country from 2000 to 2018, this study empirically tested how per capita disposable income, industrial structure, urbanization level, average family size, and technological innovation level impacts carbon emissions at different quantile levels by using the panel quantile STIRPAT model. The results showed that per capita disposable income and industrial structure had significant promoting effects on carbon emissions, while urbanization level, average family size, and technological innovation level had significant inhibitory effects on carbon emissions. The main thing is that the emission distributions of the 10th and 90th quantiles of the independent variables were quite different, which shows that the influence of each factor on carbon emissions has obvious heterogeneity at different levels. Specifically, the impact of per capita disposable income and technological innovation level on carbon emissions in low carbon emission areas were higher than that in high carbon emission areas, and the impact of industrial structure, urbanization level, and average household size on carbon emissions in high carbon emission areas was higher. Finally, specific policy implications are provided based on these results. Full article

At present, abandoned cropland has become a common phenomenon spreading to countries around the world. China has seen widespread abandoned cropland in recent years. However, there are extremely few empirical studies of cropland abandonment and influencing factors nationwide. In this study, survey data from 8071 farmer households in 14 Chinese provinces were used to analyze the degree of cropland abandonment in China and its spatial distribution. A multi-level model was constructed to quantitatively explore the socioeconomic factors affecting the degree of cropland abandonment, at both the farmer and district/county levels. The results show that: (1) the proportion of farmers and the spatial distribution of abandoned cropland are consistent. (2) Chongqing City, Guangdong Province, and Shanxi Province are high-value areas of abandoned cropland, while Shandong, Liaoning, Henan and Jiangsu provinces are low-value areas. (3) Among the differences in cropland abandonment, 68.5% and 31.5% can be explained at the farmer and district/county level, respectively. (4) At the farmer level, all labor and cropland transfer indicators, including land labor quantity per unit area, male agricultural labor ratio, farmers mainly of middle-aged labor, cropland transfer area and cropland subcontract amount, have significant negative effects on the degree of abandoned cropland. There is a significant negative correlation between the value of agricultural operating fixed assets in the agricultural input indicators and the degree of abandoned cropland, but participation in professional, cooperative, economic, agricultural organizations has no significant impact on the degree of abandoned cropland. The per capita disposable income, which represents the quality of life indicator, has a significant positive impact on the degree of abandoned cropland. (5) At the district/county level, the proportion of the total co-working labor force and the transfer rate of cropland are negatively related to the degree of cropland abandonment, and the proportion of the co-working labor force outside the district/county is positively related to the degree of cropland abandonment. In addition, we briefly analyzed the mechanism and process of cropland abandonment from the perspective of farmers’ decision-making. Finally, the policy suggestions to alleviate the abandonment of cropland were put forward from the district/county and farmer level, respectively. Full article

Out-of-pocket (OOP) payments are perceived as the most regressive means of health financing. Using the panel-data approach and region-aggregated data from Statistics Poland, this research investigated associations between socio-economic factors and OOP health spending in 16 Polish regions for the period 1999–2019. The dependent variable was real (inflation-adjusted) monthly OOP health expenditure per person in Polish households. Potential independent variables included economic, labour, demographic, educational, health, environmental, and lifestyle measures based on previous research. A set of panel-data estimators was used in regression models. The factors that were positively associated with OOP health spending were disposable income, the proportions of children (aged 0–9) and elderly (70+ years) in the population, healthcare supply (proxied by physicians’ density), air pollution, and tobacco and alcohol expenditure. On the other hand, the increased unemployment rate, life expectancy at age 65, mortality rate, and higher sports participation were all related to lower OOP health spending. The results may guide national strategies to improve health-care allocations and offer additional financial protection for vulnerable groups, such as households with children and elderly members. Full article

Promoted by rapid industrialization and urbanization, the structure and spatial pattern of farming in China has changed greatly, and nongrain farming (NGF) has become more common. However, excessive NGF in some areas is not conducive to sustainable agricultural development and threatens China’s food security. In this study, we briefly analyze the stage characteristics of NGF in China and investigate the spatial agglomeration of NGF and its influencing factors from the perspective of spatial econometrics. The results showed that the average annual growth rate of NGF in China from 1985 to 2019 was 0.64%, and there was a growing positive spatial correlation between NGF in each province. Spatial Durbin model (SDM) estimation showed that both the per capita disposable income of local rural residents and the local urbanization rate promoted the development of NGF, while local per capita farmland, road density, and the functional orientation of the main grain-producing areas had a negative impact on NGF. The per capita disposable income of rural households and urbanization rate in neighboring areas had a promoting effect on the development of NGF, while road density in neighboring areas was negatively correlated with NGF. Ultimately, some targeted measures are proposed to promote China’s agricultural development in the new era. Full article

As a result of the increase in city populations, and the high energy consumption and emissions of buildings, cities in general, and buildings in particular, are the focus of attention for public organizations and utilities. Heating is among the largest consumers of energy in buildings. This study examined the influence of the income of inhabitants on the consumption of energy for heating and the CO₂ emissions in city buildings. The study was carried out using equivalized disposable income as the basis for the analysis and considered the economies of scale of households. The results are shown per inhabitant and household, by independently considering each city. Furthermore, to more clearly identify the influence of the population income, the study was also carried out without considering the influence of the climate. The method was implemented in the case of Spain. For this purpose, Spanish cities with more than 50,000 inhabitants were analyzed. The results show that, both per inhabitant and per household, the higher the income of the inhabitants, the greater the consumption of energy for heating and the greater the emissions in the city. This research aimed to help energy utilities and policy makers make appropriate decisions, namely, planning for the development of facilities that do not produce greenhouse gases, and enacting laws to achieve sustainable economies, respectively. The overall aim is to achieve the objective of mitigating the impact of emissions and the scarcity of energy resources. Full article

A large population size and rapid economic growth have resulted in a huge amount of housing consumption in China. Therefore, it is critical to identify the determinants of housing carbon footprint (CF) and prepare appropriate carbon mitigation measures. By employing the IPCC accounting method, input-output analysis and the stochastic impacts by regression on population, affluence, and technology (STIRPAT) model, this study aims to study the spatio-temporal patterns and identify the driving factors of housing CF. The results show that regional disparities and urban-rural differences existed during the period 2012–2017. The results of the extended STIRPAT model show that population scale and energy consumption per unit building area are the two dominant contributors to the housing CF increments in all areas. While, family size only shows significant negative impact in eastern and western regions, the per capita disposable income only induces higher housing CF in rural areas, and energy structure had a remarkable positive impact in urban area of western region and all rural areas. Policy recommendations are proposed to mitigate the overall housing CF, including; controlling population growth and promoting urbanization benefits; encouraging green consumption; optimizing household energy consumption structure, and; enhancing residential building energy management. Full article