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The purpose of this paper is to test whether the policies of China’s financial restraint have an inhibitory effect on the consumption of residents.

This study used the principal component analysis for constructing a financial restraint index and also used empirical methodology.

The authors found that financial restraint policies create rent opportunities for banking sector and production sector, which further creates the rent opportunities for the household sector. Such transfer of rent and redistribution will have an inhibitory effect on residents’ consumption. The financial restraint policies directly and indirectly inhibit the growth of residents’ income; and in theory, the purpose of financial restraint policy is to promote economic growth, thus promoting residents’ consumption. Thus, the financial restraint policies impacting the residents’ consumption are non-linear and test the threshold effect of financial restraints on the residents’ consumption of China.

This paper’s theoretical contribution includes: increasing the connotation of financial restraint in the policies of stock market and foreign exchange controls, and further developing the financial restraint theory; and exploring the inhibitory effect on the consumption of residents from the perspective of financial restraints to enrich the connotation of the consumption theory.

The findings in this study can help the financial authorities to gradually relax the financial restraint policies to encourage residents’ consumption.

The paper aims to examine the consumption behavior of Chinese residents during economic transition. It explores whether Western theories of consumption are applicable to the Chinese situation, and then tests the hypothesis based on Chinese traditional culture and dynamic nature of system change.

The paper opted for an empirical‐based approach. A regression model was used to analyze annual consumption data from 1986 to 2008 in China.

The paper provides empirical insights and suggests that under the influence of Chinese traditional culture and dynamic change of the Chinese economic system, Chinese urban residents exhibit a special consumption pattern of an intermittent and cyclical nature.

The paper concludes that in order to make the consumption stimulation policy in China more effective, it is necessary to establish a series of measures such as establishing a sound social welfare system as well as narrowing the gap between the rich and the poor, which will substantially increase the buying power of the less‐privileged groups and thus will increase the overall spending in the society. Although the econometric model used in this paper is adequate, a different approach like time series econometrics may give us additional insights. Researchers are encouraged to test the hypothesis further by employing other methodologies. Second, due to the lack of its own theories in the emerging market, this study remains exploratory.

This paper fulfils an identified need to study the special consumption behavior of Chinese urban residents during the economic transition.

The purpose of this study is to explain the rapid growth of urban residents' sugar consumption in China from the perspective of habit formation.

Using the provincial panel data of Chinese urban households from 1995 to 2012, this study uses the two-step System Generalized Moment Method (GMM) to test the habit formation effect on residents' sugar expenditure in urban China. We also use system GMM and the recursive estimated method to explore the changes of the habit formation coefficients in different years.

We find a significant habit formation effect on overall residents' sugar expenditure and different types of sugary foods expenditure. The habit formation effect on total residents' sugar expenditure and different types of sugary foods is decreasing over the years. The patterns of the changes of the habit formation effect on different types of sugar foods are slightly different.

Due to data limitations, we are not able to do household-level analysis and to examine the heterogeneity of the habit formation effect.

This is the first study that examines changes in the habit formation effect on residents' sugar expenditure in urban China. Our findings provide a reasonable explanation for the rapid growth of residents' sugar consumption in urban China. The result helps to formulate targeted policies for future interventions to control the growth of sugar consumption.

On the one hand, this paper is to further understand the residents' differentiated power consumption behaviors and tap the residential family characteristics labels from the perspective of electricity stability. On the other hand, this paper is to address the problem of lack of causal relationship in the existing research on the association analysis of residential electricity consumption behavior and basic information data.

First, the density-based spatial clustering of applications with noise method is used to extract the typical daily load curve of residents. Second, the degree of electricity consumption stability is described from three perspectives: daily minimum load rate, daily load rate and daily load fluctuation rate, and is evaluated comprehensively using the entropy weight method. Finally, residential customer labels are constructed from sociological characteristics, residential characteristics and energy use attitudes, and the enhanced FP-growth algorithm is employed to investigate any potential links between each factor and the stability of electricity consumption.

Compared with the original FP-growth algorithm, the improved algorithm can realize the excavation of rules containing specific attribute labels, which improves the excavation efficiency. In terms of factors influencing electricity stability, characteristics such as a large number of family members, being well employed, having children in the household and newer dwelling labels may all lead to poorer electricity stability, but residents' attitudes toward energy use and dwelling type are not significantly associated with electricity stability.

This paper aims to uncover household socioeconomic traits that influence the stability of home electricity use and to shed light on the intricate connections between them. Firstly, in this article, from the perspective of electricity stability, the characteristics of the power consumption of residents' users are refined. And the authors use the entropy weight method to comprehensively evaluate the stability of electricity usage. Secondly, the labels of residential users' household characteristics are screened and organized. Finally, the improved FP-growth algorithm is used to mine the residential household characteristic labels that are strongly associated with electricity consumption stability.

1. The stability of electricity consumption is important to the stable operation of the grid.

2. An improved FP-growth algorithm is employed to explore the influencing factors.

3. The improved algorithm enables the mining of rules containing specific attribute labels.

4. Residents' attitudes toward energy use are largely unrelated to the stability of electricity use.

The stability of electricity consumption is important to the stable operation of the grid.

An improved FP-growth algorithm is employed to explore the influencing factors.

The improved algorithm enables the mining of rules containing specific attribute labels.

Residents' attitudes toward energy use are largely unrelated to the stability of electricity use.

The Gaza Strip in Palestine is suffering from a shortage of water and energy. To manage the current situation and address future issues, practical approaches need to be adopted to enhance water and energy efficiency. The purpose of this paper is to elicit professionals’ perceptions of the drivers affecting water and related energy consumption in residential buildings in the Gaza Strip.

In total, 19 drivers were identified from previous research and modified according to the results of a pilot study. These drivers were ranked under a Relative Importance Index (RII). A questionnaire survey was then administered and non-random purposive sampling used. The population of this study comprised stakeholders, including the United Nation Refugee Work Agency, Gaza Strip Governorates Municipalities, and the Coastal Municipalities Water Utility.

The results of all drivers (i.e. RII=71.43 per cent, mean=3.57) indicated that the respondents agreed about which drivers were affecting water and energy consumption. The sign Test-value was a positive 4.55 and the p-value was 0.000 (i.e. smaller than the level of significance a=0.050). The means of these drivers differed significantly and were greater than the hypothesised value of 3. Accordingly, it was concluded that the drivers investigated significantly affected household residents’ consumption of water and energy in residential buildings. The study revealed that climate changes, knowledge of how to conserve water and energy and household size were the most important drivers affecting household residents’ consumption of water and related energy in residential buildings.

The study will assist the parties concerned about water and energy use to be aware and understand the drivers affecting water and related energy the consumption in order to provide household residents with the necessary knowledge to ensure conservation and sustainability. Although this study related to a narrow geographical area in Palestine, the findings could be useful to similar locations in the Middle East and Africa.

This research demonstrates the drivers affecting water and related energy the consumption in residential buildings in the Gaza Strip which is considered the first study in Palestine and in the region. The study provides a useful platform for the development of appropriate water and energy strategies in Palestine and other similar geographical locations in the Middle East.

This study estimates the income elasticities of calorie, macronutrients (carbohydrate, protein and fat) and key micronutrients including cholesterol, vitamin A, vitamin C, sodium, potassium, calcium, iron, zinc and insoluble fiber separately for urban and rural adults aged 18–60, using China Health and Nutrition Survey data set from 2004 to 2011.

A semiparametric model, a two-way fixed-effects model and a quantile regression approach are employed to estimate nutrient–income elasticities.

The income elasticities of calorie, protein, fat, cholesterol and calcium are in the range of 0.059–0.076, 0.059–0.076, 0.090–0.112, 0.134–0.230, 0.183–0.344 and 0.058–0.105, respectively. The income elasticity of each of the other nutrients is less than 0.1. The income elasticities of calorie and the majority of nutrients included are larger for rural residents than for urban residents and for low-income groups than for medium- and high-income groups. Overall, in spite of having a relatively small impact, income growth is shown to still have an impact on improving the nutritional status of Chinese adults.

This study estimates nutrient–income elasticities separately for urban and rural adults, expanding the scope of the study regarding the impact of income on the nutritional status in China. Moreover, this study uses a pooled sample generated from the personal food consumption records covering foods consumed at home and away from home during 2004–2011, which is thus likely to more comprehensively reveal the causal relationship between income growth and changes in the nutritional status in China.

As climate change impacts residential life, people typically use heating or cooling appliances to deal with varying outside temperatures, bringing extra electricity demand and living costs. Water is more cost-effective than electricity and could provide the same body utility, which may be an alternative choice to smooth electricity consumption fluctuation and provide living cost incentives. Therefore, this study aims to identify the substitute effect of water on the relationship between climate change and residential electricity consumption.

This study identifies the substitute effect of water and potential heterogeneity using panel data from 295 cities in China over the period 2004–2019. The quantile regression and the partially linear functional coefficient model in this study could reduce the risks of model misspecification and enable detailed identification of the substitution mechanism, which is in line with reality and precisely determines the heterogeneity at different consumption levels.

The results indicate that residential water consumption can weaken the impact of cooling demand on residential electricity consumption, especially in low-income regions. Moreover, residents exhibited adaptive asymmetric behaviors. As the electricity consumption level increased, the substitute effects gradually get strong. The substitute effects gradually strengthened when residential water consumption per capita exceeds 16.44 tons as the meeting of the basic life guarantee.

This study identifies the substitution role of water and heterogeneous behaviors in the residential sector in China. These findings augment the existing literature and could aid policymakers, investors and residents regarding climate issues, risk management and budget management.

This paper examines the impact and mechanism of China's digital inclusive finance on rural consumption upgrade. First, the impact of the development of digital inclusive finance on the upgrading of rural household consumption structure is to be theoretically analyzed and empirically tested. Secondly, in terms of heterogeneity analysis, it pays attention to the age heterogeneity of users that digital inclusive finance influencing rural residents' developmental consumption upgrade, which is related to the issue of intergenerational “digital gap”. Thirdly, the mechanism of digital inclusive finance in promoting rural consumption upgrade is to be investigated. Finally, how to promote the role of digital inclusive finance in upgrading the structure of rural consumption to a developmental demand level will be showed.

From the perspective of the micro-household, this study is conducted by using the instrumental variable (IV) method, with 2SLS model and IV-Tobit model, based on the matched city-level data of Digital Inclusive Financial Index (DIFI) with the Chinese Household Financial Survey (CHFS). “The relief degree of land surface” is an ideal instrumental variable of digital inclusive finance, for including regional altitude difference and terrain factors of regional area, has theoretical influence on the development of digital inclusive finance, and is not affected by other economic variables.

The conclusions show that the digital inclusive finance plays a significant role in promoting the rural households' developmental consumption, but has no significant effect on the rural households' survival-type consumption and hedonistic consumption. Furthermore, this paper examines the impact and mechanism of China's digital inclusive finance on rural consumption upgrade. First, the impact of the development of digital inclusive finance on the upgrading of rural household consumption structure is to be theoretically analyzed and empirically tested. Secondly, it is discovered that digital inclusive finance is age heterogeneous in promoting the upgrade of consumption structure of rural household, and its effect on the elderly is weaker than that on the young for the intergenerational “digital gap”. Thirdly, these conclusions reveal that the digital inclusive finance does affect the consumption of rural residents through three mechanisms: increasing income and wealth, easing liquidity constraints and facilitating payment methods. Finally, how to promote the role of digital inclusive finance in upgrading the structure of rural consumption to a developmental demand level will be showed.

The current research on the relationship between digital inclusive finance and rural consumption only stays at the level of total rural consumption and has not stressed the structural problems of rural consumption. Can digital inclusive finance promote the upgrade of rural consumption structure? To what level can digital inclusive finance promote the upgrading of rural consumption structure? Therefore, it is of great theoretical value to study the upgrading of rural consumption structure from the micro level. Can the current digital inclusive finance benefit the elderly and help break the vulnerability of the elderly to enjoy finance? In this regard, evidence of heterogeneity remains to be provided.

Climate change will have a significant impact on China’s potential agricultural production and change the distribution of the population in various regions of China, thus producing population migration. This paper aims to analyze China’s population migration in response to climate change and its socio-economic impact.

In this paper, the Potential Agriculture Production Index is introduced as an analytical tool with which to estimate the scale of the population migration induced by climate change. Also, this paper constructs a multi-regional computable general equilibrium (CGE) model and analyzes the effect of change in the population distribution pattern on regional economies, regional disparity and resident welfare.

The key finding of this paper is that, as a result of changes in potential agricultural production induced by climate change, the Circum-Bohai-Sea region, the industrialized region and the industrializing region, which are the main destination regions of the migrating population, will face a severe labor shortage. In response to population migration, the economic growth rate of the immigrating population regions has accelerated. Correspondingly, the economic growth rate of the emigrating population regions has decreased. In addition, the larger the scale of population migration is, the larger the economic impact is. Migration increases inner-regional disparity and decreases inter-regional disparity. However, overall regional disparity is only somewhat decreased.

This paper introduces a Potential Agriculture Production Index to estimate the scale of the population migration and introduce a multi-regional CGE model to analyze the correlated social-economic impacts.

Seasonal fluctuation interference often affects the relational analysis of economic time series. The main purpose of this paper is to propose a new grey relational model for relational analysis of seasonal time series and apply it to identify and eliminate the influence of seasonal fluctuation of retail sales of consumer goods in China.

First, the whole quarterly time series is divided into four groups by data grouping method. Each group only contains the time series data in the same quarter. Then, the new series of four-quarters are used to establish the grey correlation model and calculate its correlation coefficient. Finally, the correlation degree of factors in each group of data was calculated and sorted to determine its importance.

The data grouping method can effectively reflect the correlation between time series in different quarters and eliminate the influence of seasonal fluctuation.

In this paper, the main factors influencing the quarterly fluctuations of retail sales of consumer goods in China are explored by using the grouped grey correlation model. The results show that the main factors are different from quarter to quarter: in the first quarter, the main factors are money supply, tax and per capita disposable income of rural residents. In the second quarter are money supply, fiscal expenditure and tax. In the third quarter are money supply, fiscal expenditure and per capita disposable income of rural residents. In the fourth quarter are money supply, fiscal expenditure and tax.

This paper successfully realizes the application of grey relational model in quarterly time series and extends the applicable scope of grey relational model.