Household Model Research Articles

How Employment Generates Social Integration: Trends Towards Disintegration and Over-Integration in the Hyper-Work Society

Using an analytical framework that further develops Jahoda’s ideas and distinguishes between two manifest and five latent mechanisms for the production of employment-based social integration, three research questions are examined: How does employment generate social integration in German welfare capitalism? How have these employment-based integration mechanisms changed in the Federal Republic of Germany (FRG) and the German Democratic Republic (GDR) since the Second World War? What dangers to social integration can be identified because of these changes? The manifest mechanisms establish socio-economic integration directly via employment or indirectly through de-commodifying welfare state interventions. The latent mechanisms ensure that social relationships can be formed by providing a time structure, extending social contacts, enabling participation in collective goals, offering collective identities and activating people. We analyse different social orders at the macro-level (labour and social legislation), meso-level (company structures, industrial relations, work environments) and micro-level (employment relationships, household models, action orientations, subjective identifications) of society to identify conditions that promote or endanger social integration. On the one hand, the danger of over-integration (reflected in the term “hyper-work society”), which arises from generalising employment-related performance and exploitation criteria, erects integration barriers for other forms of social integration beyond employment because alternative premises for organising one’s life are devalued by predominantly adopting capitalist criteria of social recognition. On the other hand, the binding power of employment and the integrative power of workplaces are weakened by disintegrative trends such as insecure employment, blurring organisational boundaries, as well as fragmentation of employment and social relations, jeopardising social integration through employment.

Renewable energy adoption and rural livelihoods in Ethiopia

AbstractThe introduction of new policies promoting decentralized energy technologies is likely to have profound effects across all the nexus activities, including agricultural production, input use, and labor allocations. Thus, this paper analyzes the potential synergies and trade‐offs created by the adoption of renewable energy technologies along the water–energy–food security nexus in Ethiopia. We use a mathematical programming‐based household model to compare the impacts of fossil‐based and renewable energy use on rural households’ livelihoods. Our findings show that only a 10% subsidy to the price of biogas digester considerably changes the energy mix of all types of households and increases the use of decentralized modern energy sources. Household crop production patterns are not changed substantially as a consequence of the biogas subsidy, despite the competition over resources between crop and energy production. Nonetheless, the subsidy policy can lead to family labor reallocation from collecting fuelwood to agricultural activities. Moreover, the biogas subsidy can improve household incomes. Specifically, the findings indicate that 10% biogas subsidy can lead to 0.93% and 3.44% increases in the net incomes of wealthier and poorer households, respectively, compared to the business‐as‐usual scenario, that is, also has a pro‐poor dimension. Sensitivity analyses are carried out and it appears among others that more subsidy of the price of biogas digester leads to an increase in the net income of the two household types. Overall, the benefits generated by the biogas subsidy in terms of increases in net household incomes outweigh the total costs of the subsidy program. The findings indicate the importance of the subsidy policy to improve rural households’ welfare.

Estimating the intrahousehold costs and benefits of innovations to enhance smallholder farmers’ resilience

This paper introduces a new framework to quantify costs and benefits for resilience-related outcomes of agricultural innovations targeting smallholder farmers. The framework employs a non-unitary household model with expected utility to quantify welfare benefits associated with non-monetary outcomes that are important from a development perspective, such as improved consumption smoothing, empowerment, and changes in time use. We demonstrate the application of the framework using a case study of climate information services (CIS) in Ghana. We develop a set of individual bargaining weights based on the women’s empowerment in agriculture index, to demonstrate how benefits from CIS are distributed among men and women within households. We find that for the average risk-averse farmer, using CIS is associated with a 37-percent increase in expected utility, but male household heads benefit more than women living in male-headed households. Cost–benefit analyses that do not consider the intrahousehold distribution of benefits associated with agricultural innovations will overestimate benefits accruing to women with low bargaining power.

Factors of Consumer Behavior of Ukrainian Households in the Pre-War and War Period: a Collective Approach to Definition and Evaluation

The development and implementation of an effective socio-economic policy requires various statistical data on the current economic performance. An important set of statistical data pertains to characteristics of the consumer behavior of households. Analysis and systematization of the factors and structural change in the consumer behavior of households, along with determining and evaluating their reactions on such crises, have become important considering the shocks experienced by Ukraine in the recent time. The research objective is to describe the changes in the pattern of household consumption, to determine, systematize and estimate the existing exogenous and endogenous factors in the context of geopolitical change. The research novelty consists in determining the vector of change in the consumer behavior of Ukrainian households in view of current events and crises in Ukraine and the world, especially ones related with the Russian-Ukrainian war and the pandemic of COVID-19, and in constructing the authors’ model for households’ behavior in time of war with account to the factor of time. The main features of the consumer behavior of Ukrainian households over longer than 20 latest years were identified. The consumer behavior of the Ukrainian population was analyzed during the crisis of COVID-19 at country level and by size and gender of a person in working age (18–59 years) who heads the household. It was concluded that consumer spending on essential goods increased in the first year of the pandemic and sharply decreased in the second year, with demonstrating that the consumer reaction on this crisis was quite similar to other ones. The current consumer behavior of Ukrainian households was analyzed, with identifying and estimating the influence of exogenous and endogenous factors on the vector of its change. The results of the study allow or a more detailed assessment of the consumer behavior of Ukrainian households in time of crises and a better understanding of its features in general.

Using Carbon Tax to Reach the U.S.’s 2050 NDCs Goals—A CGE Model of Firms, Government, and Households

Our study shows how the United States government can achieve its goal of Nationally Determined Contribution (NDC) in 2025, 2030, and 2050 by reducing energy consumption through a pure carbon tax. To achieve its emissions reduction goals, it is necessary for the U.S. to impose a long-term carbon tax that balances taxes on labour, capital, energy, and carbon. Therefore, in this study, through the two-layer CGE Cobb–Douglas model, the carbon tax rate is set while balancing the production and profit functions of government, businesses, and households. This study concludes that the carbon price will increase from USD 0.4391/kg CO2 in 2020 to USD 2.5671/kg CO2 in 2050, when the CO2 emissions reduction target is increased from 17% reduction in 2020 to 83% reduction in 2050 for the U.S.

정책모기지 이용자 만족도 영향 요인 연구

Policy mortgage is a policy financial product that enables long-term fixed interest rate, low interest rate, long-term loan period, and installment repayment for the residential stability of the common people and improvement of housing welfare. This study conducted an empirical analysis through a proportional odds logit model for households using Bogeumjari Loan, a policy mortgage for the housing vulnerable class, based on the Korea Housing Finance Corporation's '2021 Housing Finance and Demand Survey'. As a result of the analysis, the factors that affect Bogeumjari Loan user satisfaction are loan income requirements, loan maturity, increase in existing loan limit, educational level, type of product used, number of children, comparison with other products before joining, and finally single householder in order. In order to vitalize policy mortgage, it is considered that flexible operation considering the factors that most affect the satisfaction of policy mortgage users, such as housing price loan limit, income requirement, maturity, and repayment capacity, is necessary. As interest rates have risen sharply recently, the burden of repayment of interest on home mortgage loan users has been increasing, so the role of policy mortgage for the housing vulnerable class is expected to become more important. In addition, the results of this study can be used as policy data to improve housing welfare for homeless people or low-income consumers who want to buy their own home.

Optimal sizing of battery-less domestic rooftop PV systems in South Africa using a probabilistic electricity synthesiser

Solar Photovoltaic, or PV, systems are the topic of conversation that has transpired globally due to their benefits of decelerating the rapid depletion of fossil fuels, providing a sustainable and clean energy source, and powering communities that lack access to electricity. Despite the abundance of sunshine in South Africa, the adoption of domestic rooftop solar has remained limited. The uncertain cost/benefit of large-scale battery-less solar installations plays a significant role in this, especially with the disparate levels of affluence. To mitigate the uncertainty of large-scale solar deployment, PV system design may be predicted using simulation. This provides users with a better understanding of the power savings that PV system adoption can offer. We present a data-driven model and synthesiser for South African households and a case study to test the suitability of such a model for the design and sizing of fixed-axis rooftop PV systems. The case study findings revealed that PV systems sized using synthesised days were slightly under-designed in comparison to systems sized using measured days. Using a roundup strategy, however, would result in almost all of the systems tested having the correct number of PV modules. Furthermore, we determine the economic viability of the sized PV system in South Africa based on the chosen export tariff.

Investigation of individual motives and decision paths on residential energy supply systems

A better understanding of end users’ motives for choosing their energy supply system (heating and domestic hot water, cooling and electricity) can support the establishment of favorable conditions for the energy transition. In this research project, a survey was conducted in the Austrian residential sector to identify end users' interests and decisions for certain energy supply systems as well as motives for the choice. Based on 169 responses to the questionnaire, a statistical analysis was performed to evaluate the influence of gender aspects on interests and decisions. More than 90% of respondents required robust and efficient energy supply systems, which should have the highest technical standards. The environmental performance was also highly valued, whereas financial aspects, including investment costs were considered less important. 79% of men were mainly involved in the decision-making process, whereas only 59% of women were involved and, in most cases, made the decision together with their partner (52%). Identifying these motives and analyzing investment decisions enables the future integration of social and gender aspects into optimization models for individual households or energy communities.

The interdependent networked community resilience modeling environment (IN-CORE)

In 2015, the U.S National Institute of Standards and Technology (NIST) funded the Center of Excellence for Risk-Based Community Resilience Planning (CoE), a fourteen university-based consortium of almost 100 collaborators, including faculty, students, post-doctoral scholars, and NIST researchers. This paper highlights the scientific theory behind the state-of-the-art cloud platform being developed by the CoE - the Interdisciplinary Networked Community Resilience Modeling Environment (IN-CORE). IN-CORE enables communities, consultants, and researchers to set up complex interdependent models of an entire community consisting of people, businesses, social institutions, buildings, transportation networks, water networks, and electric power networks and to predict their performance and recovery to hazard scenario events, including uncertainty propagation through the chained models. The modeling environment includes a detailed building inventory, hazard scenario models, building and infrastructure damage (fragility) and recovery functions, social science data-driven household and business models, and computable general equilibrium (CGE) models of local economies. An important aspect of IN-CORE is the characterization of uncertainty and its propagation throughout the chained models of the platform.Three illustrative examples of community testbeds are presented that look at hazard impacts and recovery on population, economics, physical services, and social services. An overview of the IN-CORE technology and scientific implementation is described with a focus on four key community stability areas (CSA) that encompass an array of community resilience metrics (CRM) and support community resilience informed decision-making. Each testbed within IN-CORE has been developed by a team of engineers, social scientists, urban planners, and economists. Community models, begin with a community description, i.e., people, businesses, buildings, infrastructure, and progresses to the damage and loss of functions caused by a hazard scenario, i.e., a flood, tornado, hurricane, or earthquake. This process is accomplished through chaining of modular algorithms, as described. The baseline community characteristics and the hazard-induced damage sets are the initial conditions for the recovery models, which have been the least studied area of community resilience but arguably one of the most important. Communities can then test the effect of mitigation and/or policies and compare the effects of “what if” scenarios on physical, social, and economic metrics with the only requirement being that the change much be able to be numerically modeled in IN-CORE.

Genelleştirilmiş regresyon modelleri kullanılarak enerji talebi ve tüketimi için bir modelleme yaklaşımı

Energy management is an important process for maintaining available energy resources and meeting basic household energy needs. Many studies seek to optimize the household energy consumption patterns to manage the load demand and minimize energy costs. Adopting such optimizations in conflict-affected countries is more beneficial due to limited energy sources. This study identifies the optimal energy consumption model for households in northern Syria. The objective is to identify the most cost-efficient energy sources while considering the prices, average monthly household income, the main source of electricity, battery storage capacity, and energy demands for space heating, water heating and cooking. One hundred and thirty-six (136) standardized surveys of residential households are collected and used as a test case. Statistical analysis of the data was carried out using the R-Studio software, where Poisson regression and negative binomial regression were employed. Findings revealed that the Negative Binomial (NB) model used has high explanatory power. In addition, the energy sources used for space heating and water heating have a direct impact on monthly expenditures. The produced model showed that the most cost-effective energy sources are coal for space heating and natural gas and kerosene for water heating.

Household heterogeneity in macroeconomic models: A historical perspective

In this paper, we trace the rise of heterogeneous household models in mainstream macroeconomics from the turn of the 1980s to the early 2000s, when these models evolved into an identifiable and consistent literature. We show that different communities across the US and Europe considered heterogeneous agents for various reasons and developed models that differed in their theoretical and empirical strategies. Minnesota economists primarily focused on incorporating stochastic heterogeneity into general equilibrium models. Other researchers refined growth models or tried to find alternatives to the permanent income hypothesis, leading them to explore more structural heterogeneity. We also document the computational challenges that some of these communities faced, how they gradually became aware of each other's work, and how they faced criticisms from macro- and microeconomists, many of them trained in European countries and dissatisfied with the theoretical and empirical aggregation strategies underlying these models.

A Crossed Analysis of Participations in Labor and Grain Markets: Evidence from Malawi

Abstract This study contributes to the literature on the identification of factors shaping the decision to participate in the grain market in Africa. Unlike previous studies, we introduce labor market participation into the farm household model to highlight heterogeneities in decision making. Empirically, we rely on an extension of Heckman's approach and introduce control functions to mitigate endogeneity issues related to the adoption of agricultural technologies. We find that limited access to transportation infrastructure, by discouraging the supply of grain, constrains households to experience an excess of labor; price incentives may have a reverse effect on the choice of market regimes, even though the effect on production may be positive for households that are already participants. We also show that farmers' responses to grain prices are not sensitive to their labor market position. The use of agricultural technologies encourages cereal production and employment of external agricultural labor. This study thus provides a better targeting when designing policies promoting marketing and rural employment.

The Environmental Audit Screening Evaluation: Establishing Reliability and Validity of an Evidence-Based Design Tool.

Current assessment tools for long-term care environments have limited generalizability or ability to be linked to specific quality outcomes. To discriminate between different care models, tools are needed to assess important elements of the environmental design. The goal of this project was to systematically evaluate the reliability and validity of the Environmental Audit Screening Evaluation (EASE) tool to better enable the identification of best models in long-term care design to maintain quality of life for persons with dementia and their caregivers. Twenty-eight living areas (LAs) were selected from 13 sites similar in organizational/operational commitment to person-centered care but with very different LA designs. LAs were stratified into 3 categories (traditional, hybrid, and household) based primarily on architectural/interior features. Three evaluators rated each LA using the Therapeutic Environment Screening Scale (TESS-NH), Professional Environmental Assessment Protocol (PEAP), Environmental Audit Tool (EAT-HC), and EASE. One of each type of LA was reassessed approximately 1 month after the original assessment. EASE scores were compared against the scores of 3 existing tools to evaluate its construct validity. The EAT-HC was most closely related to the EASE (r = 0.88). The PEAP and the TESS-NH were less correlated to the EASE (r = 0.82 and 0.71, respectively). Analysis of variance indicated that the EASE distinguished between traditional and home-like settings (0.016), but not hybrid LAs. Interrater and inter-occasion reliability and agreement of the EASE were consistently high. Neither of the 2 U.S.-based existing environmental assessment tools (PEAP and TESS-NH) discriminated between the 3 models of environments. The EAT-HC was most closely aligned with the EASE and performed similarly in differentiating between the traditional and household models, but the dichotomous scoring of the EAT-HC fails to capture environmental nuances. The EASE tool is comprehensive and accounts for nuanced design differences across settings.

In Search of a Risk‐Free Asset: Search Costs and Sticky Deposit Rates

AbstractI examine the role of costly consumer search for the pricing of deposits. Estimates of a model of heterogeneous search cost households reveal a large fraction of high‐search‐cost depositors composed of elderly and less financially sophisticated households. Those households grant banks significant monopoly power that results in low and asymmetric interest rate pass‐through. The predictions of the estimated model are consistent with responses in the Survey of Consumer Finances to questions related to financial sophistication, search for investment return, and deposit allocations across multiple bank accounts. The estimated model also reveals a nonmonotone relationship between bank entry, deposit rates, and consumer surplus.

A health risk model for rural households based on the distribution of multi pollutants.

Rapid consumerism and improper waste disposal create widespread environmental degradation through the air, water sources and landfills in India's rural areas. This work develops a health risk prediction model to score villages based on quantitative and qualitative factors. Quantitative observations regarding pollutant levels and qualitative responses are collected from various households. that are risk labelled against WHO standards. The health risk model is designed to correlate the qualitative factors. A total of 2,370 rural households spread across three districts of Karnataka were selected. The study found that the health risk score predicted by the model has a higher significant correlation (0.8) to various existing pollutant factors. The study found that source of drinking water (0.87), quality of drinking water (0.81), drainage canal availability (0.72), type of drainage (0.73), stagnant water (0.71), toilet availability (0.83), maintenance frequency (0.83), cooking fuel type (0.77), cigarette use (0.71), garbage piles up (0.73) and the percentage composition of wastes (0.74) was found to have a higher positive correlation to the health of rural households. The villages with higher health risks can be identified, and suitable mitigation plans can be designed to mitigate the health risk by state authorities.

Estimation of sharing rule: an application of intra-household collective model on Indian data

PurposeMany aspects of well-being depend critically on individual-level expenditure and consumption. The Millennium Development Goals include the promotion of gender equality and the empowerment of women, which partly have to do with women’s access to resources within households. Many important questions in labour, public and development economics also hinge on the intra-household distribution of resources. This paper aims to estimate the resource shares within a household in the rural and urban sectors of West Bengal through a collective household model, where each household member has a specific utility function. The sharing rule parameters, that determine the apportionment of resources between members within a household, are estimated in an intra-household collective framework. The analysis is based on a system of log-quadratic Engel curves estimated using the 68th round (2011–2012) household-level consumption expenditure data of the Indian National Sample Survey Office (NSSO) for rural and urban sectors separately for the state of West Bengal.Design/methodology/approachThe sharing rule parameters (that determine the apportionment of resources between members) within a household are estimated in an intra-household collective framework as suggested by Dunbar et al. (2013). The analysis is based on a Quadratic Almost Ideal Demand System (QUAIDS) estimated using the 68th round (2011–2012) household-level consumption expenditure data of the Indian NSSO.FindingsIn this paper, the authors estimate the sharing rule of total household expenditure between couples in a household in the state of West Bengal. They use a modified version of the QUAIDS and the 68th round (2011–2012) household-level consumer expenditure data provided by the NSSO. From the exercise, it emerges that on an average, the resource shares between husband and wife in a household is about 66:34% in the rural sector and about 60:40% in the urban sector. Based on a classification of households by the distribution of resource shares, where higher resource share for the husband is classified as “Husband dominated” and the reverse as “Wife dominated”, the percentage of “Husband dominated” households is much more in both sectors. This unequal distribution of resources may have far-reaching consequences on allocation of expenditure on the children of the household. The authors leave this exercise as a future project.Originality/valueThis paper is an attempt to estimate the sharing rule for households using NSSO consumption expenditure data. This paper also highlights the intra household unequal resource allocation through the sharing rule. They use a modified version of the QUAIDS and the 68th round (2011–2012) household-level consumer expenditure data provided by the NSSO. From the exercise, it emerges that on an average, the resource shares between husband and wife in a household is about 66:34% in the rural sector and about 60:40% in the urban sector. Based on a classification of households by the distribution of resource shares, where higher resource share for the husband is classified as “Husband dominated” and the reverse as “Wife dominated”, the percentage of “Husband dominated” households is much more in both sectors. This unequal distribution of resources may have far-reaching consequences on allocation of expenditure on the children of the household. The authors leave this exercise as a future project.

Peer-to-Peer Energy Trading for Residential Prosumers With Photovoltaic and Battery Storage Systems

The popularization of solar generation enables residential households to supply their loads and trade the surplus energy through residential peer-to-peer (P2P) energy trading market. Facing the increasing complexity of the market structure and decision-making strategies, this article proposes a P2P energy trading model for residential households, and the objective is to help the centralized market coordinator optimize the benefit of participants under such a P2P market. To this end, a new mathematical model, including the rules for buying and selling energy, is presented. In this model, a supply function bidding mechanism is formulated to match the power supply imbalance and calculate the market-clearing price. An optimization problem is formulated to identify the optimal strategies for energy buying and selling, which consists of two parts: the first part is to maximize the social welfare; the second part is to minimize the unfair benefit distribution that participants can gain through P2P energy trading. The case study based on the real data for four different household categories has revealed that households can achieve 26.38% net cost reduction, and the proposed fair benefit distribution function also can fairly allocate the benefit by enforcing households' benefit variance indexes at a low level.

A model of household shared parking decisions incorporating equity-seeking household dynamics and leadership personality traits

A model of household shared parking decisions incorporating equity-seeking household dynamics and leadership personality traits

Discourse and Intercourse

In this article, I consider three narratives, Genesis 38, 2 Samuel 13, and Judges 19, in which biblical authors deploy women’s speech at moments of crisis in the plot. These moments are caused by women’s precarious location in the bêt ʾāb, which I theorize using the framework of the Patrimonial Household Model (PHM). I assess the women characters’ speech through the lens of Laura Mary Elizabeth Hare’s sociolinguistic analysis of gendered speech in biblical narrative. While Tamar in Gen 38 uses manipulation and “masculine” speech to successfully re-insert herself into the bêt ʾāb, Tamar in 2 Sam 13 is the victim of men’s manipulation and her “feminine” speech fails to protect her. The secondary wife in Judges 19 has no verbal speech, only speech-acts, which leaves her almost but not entirely at the mercy of men’s discourse. I argue that the biblical authors understood women characters as able to exercise some amount of agency through their leveraging of normatively masculine speech, but only for the purpose of re-establishing the social order of the PHM.

Analysis of network disruption evolution of Chinese fresh cold chain under COVID-19.

The spread of the global COVID-19 epidemic, home quarantine, and blockade of infected areas are essential measures to prevent the spread of the epidemic, but efforts to prevent and control the outbreak lead to the disruption of fresh and cold chain agricultural products in the region. Based on the multi-layer management model of non-scale agricultural households in China, we applied the complex network theory to construct an evolutionary model of the Chinese fresh cold chain network with adaptation degree priority connection, dual local world considering transport distance connection relationship, and superiority and inferiority mechanism. Based on this model, we studied the evolution of fresh cold chain disruption, and puts forward the optimal design of fresh cold chain network disruption and reconnection from the perspective of practicality and economy.