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We investigate the reasons why income inequality is so high in Spain in the EU context. We first show that the differential in inequality with Germany and other countries is driven by inequality among households who participate in the labor market. Then, we conduct an analysis of different household income aggregates. We also decompose the inter-country gap in inequality into characteristics and coefficients effects using regressions of the Recentered Influence Function for the Gini index. Our results show that the higher inequality observed in Spain is largely associated with lower employment rates, higher incidence of self-employment, lower attained education, as well as the recent increase in the immigration of economically active households. However, the prevalence of extended families in Spain contributes to reducing inequality by diversifying income sources, with retirement pensions playing an important role. Finally, by comparing the situations in 2008 and 2012, we separate the direct effects of the Great Recession on employment and unemployment benefits, from other more permanent factors (such as the weak redistributive effect of taxes and family or housing allowances, or the roles of education and the extended family).

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.

This paper aims to understand housing demand of urban Indian households in terms of housing and household-level characteristics. Because a house is a bundle of certain characteristics which vary across houses, each characteristic has an implicit price. Finding this implicit price for certain important characteristics is the first objective of this study. The second objective of the paper is to compute the income elasticity and price elasticity of housing demand for these cities.

To achieve comparable estimates, household-level data from India’s National Sample Survey Organisation housing surveys for the years 2002 and 2008-2009 have been used. A hedonic price function is estimated using ordinary least squares (OLS) and Box-Cox functional forms to estimate the implicit prices of housing characteristics. This exercise is attempted for owned and rented houses separately. Demand function required for computing the elasticities, uses the hedonic price index derived from the implicit prices and household characteristics.

The study finds housing demand to be income elastic and price inelastic for the six cities across both the time periods.

Firstly, this study includes housing characteristics such as individual access to drinking water, modern sanitation facility, separate kitchen, condition of the structure, existence of a road with street light and whether the house is in a slum or non-slum area in the hedonic price function. These variables were not used in any of the earlier studies pertaining to India. Secondly, it uses the Box-Cox non-linear form to derive the hedonic price function, a specification not used earlier. Thirdly, this is the first study analysing housing demand across the six largest Indian cities.

Although they are neighbouring Asian countries with many similarities, India and Indonesia have different levels of household expenditure inequality. During the end of 2000s, the Gini coefficient of Indonesia was 9.1 percentage points larger than the Gini coefficient of India. To understand the determinants of this difference, this study decomposes it into the contribution of price effects, demographic effects and labour market structure effects. Differences in expenditure structures (price effects) and demographic characteristics are found to be the greatest contributors to the inequality gap across the two countries. The difference in the education distribution of household heads also has a positive and significant impact on the inequality gap. Differences in the labour market structure, on the other hand, turn out to be less important.

The purpose of this paper uses household survey data to model the correlates of household consumption and poverty in Fiji. A multivariate empirical analysis is conducted to ascertain those household and community characteristics that correlate with household welfare and poverty. In particular, the results will show how a particular characteristic will affect household poverty conditional on the level of other characteristics that are also potential determinants of poverty.

The key approach in this paper is similar to Mukherjee and Benson and is based on ordinary least squares (OLS) modeling of the natural logarithm of total per capita consumption of households, which serves as the household welfare indicator, against a set of exogenous determinants such as household and community characteristics. For robustness checks, a probit regression is also estimated with the probability of a household being in poverty as the dependent variable and an identical set of independent variables used in the OLS regression.

The results show that higher levels of education, supporting agricultural growth policies in rural areas and reallocation of labour into the formal sector of the economy will prove effective in reducing poverty at the household level. These results can have important policy implications for design and implementation of poverty reduction policies.

Empirical studies on the determinants of household consumption and poverty are non‐existent in Fiji. This thus is the first study which attempts to model the determinants of poverty at the household level and is the major contribution of this paper.

The purpose of this paper is to investigate the relationship between maternal, household and socio-economic characteristics and household food security in Aceh Province, Indonesia.

The data used are cross-section, secondary data from the Economic Census of Indonesia in 2016 (BPS, 2016) from 23 districts/cities. The central message of the present empirical analysis is that relatively simple indicators perform well in locating food security.

The analysis proves that mother’s age has a significant effect on average calorie intake at the household level. This may be due to the fact that mother’s age plays an important role in the provision of proper food to her family. Higher-aged mothers can understand better about the food quality and requirement for the family as compared to low-aged mother. Environmental factors like access to safe water and better sanitation facilities within housing premises indirectly enhance the absorptive capacity of available food intake. Thus, environmental factors could play an important role in food security through calorie intake, irrespective of economic status of the household. This analysis further strengthens the earlier findings that higher food intake availability alone may not lead to improved health outcome, unless measures are taken to improve access to safe water and sanitation. The contribution of dependency ratio in per capita calorie intake also appeared to be significant in this study. This shows that high dependency ratio reduces the per capita calorie intake due to a larger share in food items among households.

No previous study has comprehensively studied the relationship between maternal, household, and socio-economic characteristics and household food security, especially in Aceh, Indonesia.

This study aims to assess housing affordability and estimate demand using a hedonic regression model in the context of Lucknow city, India. This study assesses housing affordability by considering various housing and household-related variables. This study focuses on the impoverished urban population, as they experience the most severe housing scarcity. This study’s primary objective is to understand the demand dynamics within the market comprehensively. An understanding of housing demand can be achieved through an examination of its characteristics and components. Individuals consider the implicit values associated with various components when deciding to purchase or rent a home. The components and characteristics have been obtained from variables relating to housing and households.

A socioeconomic survey was conducted for 450 households from slums in Lucknow city. Two-stage regression models were developed for this research paper. A hedonic price index was prepared for the first model to understand the relationship between housing expenditure and various housing characteristics. The housing characteristics considered for the hedonic model are dwelling unit size, typology, condition, amenities and infrastructure. In the second stage, a regression model is created between household characteristics. The household characteristics considered for the demand estimation model are household size, age, education, social category, income, nonhousing expenditure, migration and overcrowding.

Based on the findings of regression model results, it is evident that the hedonic model is an effective tool for the estimation of housing affordability and housing demand for urban poor. Various housing and household-related variables affect housing expenditure positively or negatively. The two-stage hedonic regression model can define willingness to pay for a particular set of housing with various attributes of a particular household. The results show the significance of dwelling unit size, quality and amenities (R² > 0.9, p < 0.05) for rent/imputed rent. The demand function shows that income has a direct effect, whereas other variables have mixed effects.

This study is case-specific and uses a data set generated from a primary survey. Although household surveys for a large sample size are resource-intensive exercises, they provide an opportunity to exploit microdata for a better understanding of the complex housing situation in slums.

All the stakeholders can use the findings to create an effective housing policy. The variables that are statistically significant and have a positive relationship with housing costs should be deliberated upon to provide the basic standard of living for the urban poor. The formulation of policies should duly include the housing preferences of the economically disadvantaged population residing in slum areas.

This paper uses primary survey data (collected by the authors) to assess housing affordability for the urban poor of Lucknow city. It makes the results of the study credible and useful for further applications.

The purpose of this paper is to analyse the determinants of the saving behaviour of Vietnamese households and to explore the possible heterogeneity of household saving propensities.

The authors estimate the effects of household characteristics on Vietnamese household saving rates by means of a quantile regression approach using the Vietnam Household Living Standard Survey 2010 data set.

The results suggest that the way household characteristics influence saving rates is different for each quantile of the household saving rate distribution. Household characteristics tend to have stronger effects at lower quantiles. Particularly, the marginal propensity to save of households at low quantiles is higher than those at high quantiles. Analysing rural and urban households separately, the authors find evidence that household and household head characteristics have stronger significant effects for rural than for urban households. Children and elderly members should be treated as part of the household labour force, instead of household dependency, since both of them increase household saving rates.

This research contributes to the literature on Vietnamese household saving behaviours, especially for households living in urban areas.

The purpose of this paper is to investigate antecedents of households' local demand for domestic tourism in Jordan.

A sample of 600 households is surveyed and a two‐stage demand model is estimated. Stage 1 identifies the antecedents of the probability of entering the domestic tourism market. Stage 2 identifies the antecedents of households' expenditures on domestic tourism. The Heckit method is used to estimate the first stage and the OLS is used to estimate the second stage.

Certain socio‐economic factors (household characteristics, individual characteristics and ability variables) impact the local demand for domestic tourism, as do price and income variables.

The generalizability of results to other countries is limited.

Identification of antecedents of local demand for domestic tourism helps governments to formulate and modify future tourism strategies.

This paper contributes to the literature by including socio‐economic variables in the domestic tourism demand model. Further, there is a dearth of studies in Jordan in general and regarding domestic tourism in particular.

This paper investigates the effect of household size, and in particular of the number of children of different age groups, on poverty, defined as being in a situation of low income. We apply various static and dynamic probit models to control for the endogeneity of the variables of interest and to account for unobserved heterogeneity, state dependence, and serially correlated error components. Using Luxembourg longitudinal data, we show that the number of children of different age groups significantly affects the probability of being poor. However, the magnitude of the effect varies across different specifications. In addition, we find strong evidence of true poverty persistency due to past experience, spurious poverty persistency due to individual heterogeneity, and transitory random shocks.