Spatial Distribution Of Households Research Articles

Rational cuts? The local impact of closing undersized schools

The availability of public education services can influence residential choices. Therefore, policies aimed at ‘rationalising’ service provision by reducing the number of undersized nodes in the public school network can lead to population decline, especially in spatially isolated areas lacking valid alternatives to the removed services. This paper examines the demographic and income effects of primary school closures by exploiting an Italian education reform that resulted in the contraction of the school network. We assess whether school closures impact households’ residential choices, over and above preexisting negative population trends that motivate school closures. Our findings indicate that municipalities affected by school closures experience significant reductions in population and income. The effect is primarily driven by peripheral municipalities located far away from economic centres and distant from the next available primary school. This evidence indicates that school ‘rationalisation policies’, by fostering depopulation of peripheral areas, have an influence on the spatial distribution of households and income, thus affecting territorial disparities.

Spatial distribution and geographical heterogeneity factors associated with households' enrollment level in community-based health insurance.

Healthcare service utilization is unequal among different subpopulations in low-income countries. For healthcare access and utilization of healthcare services with partial or full support, households are recommended to be enrolled in a community-based health insurance system (CBHIS). However, many households in low-income countries incur catastrophic health expenditure. This study aimed to assess the spatial distribution and factors associated with households' enrollment level in CBHIS in Ethiopia. A cross-sectional study design with two-stage sampling techniques was used. The 2019 Ethiopian Mini Demographic and Health Survey (EMDHS) data were used. STATA 15 software and Microsoft Office Excel were used for data management. ArcMap 10.7 and SaTScan 9.5 software were used for geographically weighted regression analysis and mapping the results. A multilevel fixed-effect regression was used to assess the association of variables. A variable with a p < 0.05 was considered significant with a 95% confidence interval. Nearly three out of 10 (28.6%) households were enrolled in a CBHIS. The spatial distribution of households' enrollment in the health insurance system was not random, and households in the Amhara and Tigray regions had good enrollment in community-based health insurance. A total of 126 significant clusters were detected, and households in the primary clusters were more likely to be enrolled in CBHIS. Primary education (AOR: 1.21, 95% CI: 1.05, 1.31), age of the head of the household >35 years (AOR: 2.47, 95% CI: 2.04, 3.02), poor wealth status (AOR: 0.31, 95% CI: 0.21, 1.31), media exposure (AOR: 1.35, 95% CI: 1.02, 2.27), and residing in Afar (AOR: 0.01, 95% CI: 0.003, 0.03), Gambela (AOR: 0.03, 95% CI: 0.01, 0.08), Harari (AOR: 0.06, 95% CI: 0.02, 0.18), and Dire Dawa (AOR: 0.02, 95% CI: 0.01, 0.06) regions were significant factors for households' enrollment in CBHIS. The secondary education status of household heads, poor wealth status, and media exposure had stationary significant positive and negative effects on the enrollment of households in CBHIS across the geographical areas of the country. The majority of households did not enroll in the CBHIS. Effective CBHIS frameworks and packages are required to improve the households' enrollment level. Financial support and subsidizing the premiums are also critical to enhancing households' enrollment in CBHIS.

Two-worker Households, Decentralized Employment, and Residential Segregation

AbstractThe last century was marked by a remarkable improvement in the economic position of women, as reflected in higher labor force participation and wages. This paper extends the Hybrid Tiebout models of residential choice to allow for two-worker households. Our model incorporates both residential choice and labor market choices of households simultaneously and, thus, gives us a unique opportunity to study the impact of changes in the labor market conditions for workers on residential segregation. We develop a general equilibrium model of residential choice with decentralized workplaces in which households face a trade-off among accessibility, space and a public good (education). Education is financed through property taxes, which are determined by majority voting. The quality of education is determined by the spending and the peer group effects. The model is interesting in the sense that (i) households consider the work locations of both male and female working members of the household while making residential choice decisions; (ii) the presence of decentralized workplaces offers an alternative job location to workers; and (iii) the endogenous labor supply decisions for workers. We find that the increase in educational attainment for women and the changes in wages for men and women have had a substantial impact on the spatial distribution of households across metropolitan areas and hence, segregation by income.

Exploring spatial patterns, and identifying factors associated with insufficient cash or food received from a productive safety net program among eligible households in Ethiopia: a spatial and multilevel analysis as an input for international food aid programmers

BackgroundIn low-income countries, households’ food insecurity and the undernutrition of children are the main health problems. Ethiopia is vulnerable to food insecurity and undernutrition among children because its agricultural production system is traditional. Hence, the productive safety net program (PSNP) is implemented as a social protection system to combat food insecurity and enhance agricultural productivity by providing cash or food assistance to eligible households. So, this study aimed to explore spatial patterns of households’ insufficient cash or food receiving from PSNP, and identify its associated factors in Ethiopia.MethodsThe 2019 Ethiopian Mini Demographic and Health Survey dataset was used. A total of 8595 households were included in this study. Data management and descriptive analysis were done using STATA version 15 software and Microsoft Office Excel. ArcMap version 10.7 software was used for spatial exploration and visualization. SaTScan version 9.5 software was used for spatial scan statistics reports. In the multilevel mixed effect logistic regression analysis, explanatory variables with a p-value of less than 0.05 were considered significant factors.ResultsOverall, 13.5% (95% CI: 12.81–14.27%) of the households’ level beneficiaries received cash or food from PSNP. The spatial distribution of households’ benficiaries received cash or food from PSNP was not random, and good access to cash or food from PSNP was detected in Addis Ababa, SNNPR, Amhara, and Oromia regions. Households’ heads aged 25–34 (AOR:1.43, 95% CI: 1.02, 2.00), 35–44 (AOR: 2.41, 95% CI: 1.72, 3.37), and > 34 (AOR: 2.54, 95% CI: 1.83, 3.51) years, being female (AOR: 1.51, 95% CI: 1.27,1.79), poor households (AOR: 1.91, 95% CI:1.52, 2.39), Amhara (AOR:.14, 95% CI: .06, .39) and Oromia (AOR:.36, 95% CI:.12, 0.91) regions, being rural residents (AOR:2.18, 95% CI: 1.21,3.94), and enrollment in CBHS (AOR: 3.34, 95% CI:2.69,4.16) are statistically significant factors.ConclusionsHouseholds have limited access to cash or food from the PSNP. Households in Addis Ababa, SNNPR, Amhara, and Oromia regions are more likely to receive benefits from PSNP. Encouraging poor and rural households to receive benefits from the PSNP and raise awareness among beneficiaries to use the benefits they received for productivity purposes. Stakeholders would ensure the eligibility criteria and pay close attention to the hotspot areas.

Spatial distribution and determinants of limited access to improved drinking water service among households in Ethiopia based on the 2019 Ethiopian Mini Demographic and Health Survey: spatial and multilevel analyses

IntroductionSafe and easily accessible drinking water service generates substantial benefits for public health and the economy. Approximately 10% of the global burden of disease worldwide could be prevented with improved access to drinking water. The death of ~ 30% of children younger than 5 years in developing countries is attributable to inadequate access to improved drinking water. Despite the presence of abundant water sources in Ethiopia, uneven distribution and waste pollution coupled with unprecedented population growth, rapid urbanization, and climate change are hindering the country's ability to maintain the balance between the demand and supply of accessible and improved drinking water services. The importance of up-to-date evidence for actions regarding the distribution of access to improved drinking water services is indicated by the Ethiopian Ministry of Water and Energy. Therefore, this study aimed to explore the spatial distribution and determinants of limited access to improved drinking water service among households in Ethiopia.MethodsThis study used the 2019 Ethiopian Mini Demographic and Health Survey (EMDHS). The data were weighted using sampling weight to restore the representativeness and to obtain valid statistical estimates. After excluding ineligible households, a total weighted sample of 5,760 households was included in the final analysis. The analysis was performed using STATA version 14.2, ArcGIS Pro, and SaTScan version 10.1 software. To find significant determinants with limited access to improved drinking water service, we used a multilevel logistic regression model. A P-value of &amp;lt;0.05 was used to declare statistical significance.ResultsThis study found that in Ethiopia, 16.1% (95% CI: 15.2, 17.1) of households have limited access to improved drinking water services. The spatial distribution of households with limited access was identified to be clustered across a few regions of the country (Moran's I = 0.17, p-value &amp;lt; 0.01). The most likely significant primary clusters with highly limited access were seen in the Somali region (RR = 4.16, LLR = 162.8), the border between Amhara and Afar region (RR = 4.74, LLR = 41.6), the border between Oromia and Afar region (RR = 5.21, LLR = 13.23), and the northeastern Tigray region (RR = 2.52, LLR = 9.87). The wealth index, the age of household head, residence, and region were significantly associated with limited access to improved drinking water service. A high rate of limited access to improved drinking water service is predicted in the southwestern part of Gambella, the northeastern part of Oromia, the southwestern part of South Nation Nationalities and Peoples' region, and part of the Oromia region that surrounds Addis Ababa.ConclusionLimited access to improved drinking water service in Ethiopia varies across regions, and inequality in the service provision exists in the country. Prioritization and extra level of efforts should be made by concerned government and non-government organizations as well as other stakeholders for those underprivileged areas and groups of the population as they are found in the study.

Differential impacts of autonomous and connected-autonomous vehicles on household residential location

High market penetration of autonomous vehicles (AVs) and connected-autonomous vehicles (CAVs) is expected to impact transportation network performance, which is an important determinant of residential location decisions, especially for households who commute to work by personal vehicle. This study examines and compares the impacts of privately owned AVs and CAVs on the location and commute characteristics as well as the spatial distribution of households within the Triangle Region in North Carolina. A Mixed Multinomial Logit model is developed using recent household survey data to capture household preferences. In addition, the region’s travel demand model, the Triangle Regional Model, is used to predict the network-level impacts of AV and CAV adoption, and cluster analysis is conducted to explore how network performance changes vary with transportation demand and supply zone characteristics at a local and regional level. Residential location patterns are predicted for a number of AV and CAV scenarios for the year 2045 using the outputs of the econometric analysis and the Triangle Regional Model. We find that extensive adoption of private CAVs improves network conditions and encourages households to live farther from work, leading up to a 5.6% increase in suburban and rural households that commute to work by personal vehicles. A high market share of AVs is associated with deteriorated transportation network performance and up to a 2.8% increase in urban households. Results vary by market penetration rate of each technology, mix of AVs, CAVs, and human driven vehicles in the traffic stream, and fuel type (conventional-fuel versus electric vehicles).

Using lidar and Bayesian inference to reconstruct archaeological populations in the Kingdom of Tonga

The islands of Polynesia are often seen as “natural laboratories” where population size and growth are core components of models which examine the development of Oceanic societies. As in many parts of the world, the population of Pacific Islands suffered severe declines after contact when Europeans introduced new pathogens. These rapid population declines and a historical record weighted heavily to later missionary accounts complicate estimates of population size and distribution. Here, we use lidar derived settlement data to estimate the population of the island of Tongatapu, the seat of power of the Tu‘i Tonga polity between the 13th and 19th centuries. We use a Bayesian approach to adapt the house count method and estimate population based on information from: the number and spatial distribution of households from lidar survey, archaeological transect data to determine structure function, and ethnographic records of household composition. Results indicate the population of Tongatapu was probably between 50,000 and 60,000 people, suggesting a total population living in the archipelago of between 100,000 to 120,000 people. Population estimates were compared to population retrodictions calculated with previously unanalysed historical sources to show the Tongan archipelago suffered a population decline at all island groups of approximately 70% to 86%. These results highlight the contribution lidar derived settlement data to our understanding of demography and social development.

Households with unimproved water sources in Ethiopia: spatial variation and point-of-use treatment based on 2016 Demographic and Health Survey

BackgroundImproved water sources are not equally available in all geographical regions. Populations dependent on unsafe water sources are recommended to treat their water at point-of-use using adequate methods to reduce associated health problems. In Ethiopia, the spatial distribution of households using unimproved water sources have been incomplete or ignored in most of the studies. Moreover, evidence on the point-of-use water treatment practice of households dependent on such water sources is scarce. Therefore, the current study is intended to analyze the spatial distribution of unimproved water sources by wealth quintiles at country level and point-of-use treatment (POU) practices using nationally representative data.MethodThe data of 2016 Ethiopian Demographic and Health Survey (EDHS) conducted on 16650 households from 643 clusters were used for the analysis. For spatial analysis, the raw and spatially smoothed coverage data was joined to the geographic coordinates based on EDHS cluster identification code. Global spatial autocorrelation was performed to analyze whether the pattern of unimproved water coverage is clustered, dispersed, or random across the study areas. Once a positive global autocorrelation was confirmed, a local spatial autocorrelation analysis was applied to detect local clusters. The POU water treatment is analyzed based on reported use of either boiling, chlorine (bleach), filtration, or solar disinfection (SODIS).ResultsThere were 5005 households using unimproved water sources for drinking purposes. Spatial variation of unimproved water coverage was observed with high coverage observed at Amhara, Afar, Southern Nations Nationalities and People and Somalia regions. Disparity in unimproved water coverage between wealth quintiles was also observed. The reported point-of-use water treatment practice among these households is only 6.24%. The odds of POU water treatment among household heads with higher education status is 2.5 times higher (95% CI = 1.43-4.36) compared to those who did not attend education.ConclusionAn apparent clustering trend with high unimproved water coverage was observed between regions and among wealth quintiles hence indicates priority areas for future resource allocation and the need for regional and national policies to address the issue. Promoting households to treat water prior to drinking is essential to reduce health problems.

Modeling household housing and car ownership decisions: a group decision-based time allocation approach

ABSTRACT Multitudes of household long-term decisions and daily activity-travel decisions are interdependent and bound together in some ways. This paper develops an integrated model that links long-term decisions like housing, vehicle ownership and short-term activity-travel decisions like time allocation to activity participation, so as to examine the interactions between long-terms decisions (in terms of expenditure tradeoff), as well as investigate household housing and car ownership decisions from the perspective of time allocation. A group decision approach is adopted to differentiate household members’ relative influence on consensual decision-making and capture intra-household interactions. The proposed model is applied to an empirical case study in Beijing to calibrate the parameters, demonstrate its applicability and analyze household members’ interactive decision-making on housing, car ownership and time use over in-home and out-of-home activities. This study will be helpful for gaining a deep understanding of spatial distribution of households, household car ownership levels and individuals’ activity-travel patterns.

Spatial-temporal economic analysis of modern sustainable sanitation in rural China: Resource-oriented system

Sustainable sanitation is developed in order to create an efficient and ecological use of water, energy and nutrients, the basic elements important for living beings. However, the sustainable sanitation is still doubted by authority and there is no large-scale implementation when wastewater treatment campaign significantly carries out in rural China. The lack of economic feasibility assessment is a major barrier to break through the current wastewater treatment paradigm. This study aims to evaluate the economic performance and feasibility of resource-oriented system, an innovative sustainable sanitation, based on vacuum pipelines technology and source separation. For this purpose, life cycle cost analysis for conventional wastewater treatment and resource-oriented system in different population sizes was studied. Considering the spatial distribution of households, an important and remarkable factor in rural China, the paper innovatively instigated the balance between the economies of scale and decentralization. Results show that resource-separated system with positive environment and social effects outperforms current system in terms of lifetime cost because of its lower energy consumption and sewer cost. Based on the discussion, the optimum collection scale is not fixed and decided by local market situation. Commonly speaking, village-group model is preferred for conventional wastewater treatment system in rural China. Considering the factors of biogas utilization, pipe airtightness and financial pressure, both centralized and decentralized model can be chosen in resource-oriented system.

Characteristics of Residential Locations and Demographic Structural Trends of the Shiraho Rural Settlement on Ishigaki Island

This study clarifies three things about the housing environment that should be considered when planning future community vitalizations through collaborations among people on remote island regions with different origins and immigration motives. First, it identifies the factors that influenced the residential composition of Shiraho. Second, it classifies residents by origin. Third, it identifies the characteristics of residential locations according to the residents′ origins and immigration timing. The results show that the residential composition of Shiraho changed in four stages. Regarding the spatial distribution of households in the residential areas of Shiraho, similar Shuriners and similar Taramanians resided in respective clusters, which were spatially separate from Shirahonians. Recent immigration of outsiders changed the distribution of the old residential area, but in some cases they came to reside in newly opened areas that other residents avoided for various reasons.

Spatial attraction in migrants' settlement patterns in the city of Catania

(ProQuest: ... denotes formulae omitted.)1. IntroductionResidential location influences individuals' proximity to important resources (such as schools, hospitals, child care facilities, labor markets, and employment opportunities) and to potential risks, including environmental threats and social hazards (such as exposure to crime and violence) (Reardon 2006). Furthermore, it impacts access to social networks and other forms of social capital; overall, it shapes human interaction and the demographic processes that originate from it, such as mortality, fertility and mobility (Almquist and Butts 2012).A minority ethnic group is spatially clustered when the spatial arrangement of minority households departs from expectations based upon a random spatial allocation (Freeman, Pilger, and Alexander 1971).In broad terms, and apart from ethnic discriminatory rules enforced by law or traditions in some places and at some times, we may distinguish between two sources of spatial clustering. One source is spatial inhomogeneity or apparent contagion. Typically, the different parts of a city exhibit large variations in the price of residential property, in the accessibility of low cost public infrastructures, and in the availability of certain types of jobs; these inhomogeneities may lead to a mostly economically induced segregation. As Schelling (1971) observes, ethnicity is often correlated with income, and income with residence; so even if residential choices were unconstrained by ethnic discrimination, the different ethnic groups would not be randomly distributed among residences.The second source is spatial attraction or true contagion. Survey data on the ideal neighborhood composition for different ethnic groups in the USA, reported in Clark and Fossett (2008), show that all groups prefer living in areas where their group is a majority or near-majority. These preferences have complex origins and may reflect attachment to group identity and culture (e.g., language, religion, customs, etc.). Newly arrived minority migrants may benefit from positive spillovers in settling close to their compatriots, in terms of reciprocal acceptance, common language, and support. Transnational social networks play an important role in channeling arriving migrants into specific neighborhoods and also into particular occupations (Gelderblom and Adams 2006).However, regardless of what the basis of the individual preferences for coethnic contact is, they produce identical patterns of residential segregation (Clark and Fossett 2008). The Schelling (1971) model provides an analysis of the implications of individual preferences and shows that when a household enters a neighborhood, that neighborhood becomes more attractive to members of the household's own group and less attractive to members of other groups. In other words, the presence of a household in a given area increases the probability of others of the same group to locating nearby.It is relevant in social research to be able to distinguish between these two sources of clustering. Whereas economic induced segregation might explain some initial degree of segregation and raises questions of social equity, the Schelling model highlights the importance of individually motivated segregation and posits that even mild preferences for living with similar neighbors carry the potential of being strong determinants for residential segregation (Clark and Fossett 2008). The spatial distribution of households may be represented by a point pattern, i.e.,a set of points in a map. Ripley's K-function (Ripley 1981) is widely used to detect clustering in point processes. The inhomogeneous K-function is a version of Ripley's K-function conceived for assessing the effects of spatial attraction (or inhibition), while adjusting for the effects of spatial inhomogeneity. In other words, this approach allows us to distinguish between the two sources of clustering, by assessing clustering above and beyond that due to apparent contagion. …

The Diurnal Cycle of Regional Commuter Systems: North Wales, 1991

Places of household residence and places of commuter destination are considered in a contiguous system of subareas constituting a region. An intrahousehold distribution of household members, by subarea of their commuting destination, is considered for each subarea of residence. A household composition matrix is constructed in reference to the average number of commuters to subareas of destination, per household at a subarea of residence, across all subareas. The matrix is a linear transformation from the spatial distribution of households onto the spatial distribution of daytime population, over all subareas of the region. Diurnal population change throughout the region is rendered by this transformation. A linear optimization model extending this transformation formalizes general conditions that relate the diurnal population system to household choice of residence and work. Further, the division of the region into subareas is assumed to be such that the average household in each subarea contains at least one person who remains in the subarea during day and night. Under these conditions, the diurnal system is shown to be analogous to the Leontief input-output model. An example of eleven counties of North Wales, along with an exogenous area of northwestern England, drawn from the 1991 census of the United Kingdom, illustrates the formal relationships.

The urban household pattern of daytime population change.

"A matrix representation of places of residence and places of commuting destination in a metropolis, is coupled with evidence regarding spatio-temporal change in average household size. This approach allows the average number of persons per household who commute to be hierarchically ordered in a square matrix which shows attributes associated with a well-known class of matrices. Based on these attributes it is shown that any given spatial distribution of households implies a bounded range of vectors representing the spatial distribution of commuters.... The proposed methodology is applied to thirty four subareas throughout the city of Saskatoon, Saskatchewan."

THE ECONOMICS OF COMMUTING AND THE URBAN LABOUR MARKET

ABSTRACT. The spatial distribution of households and firms, or urban spatial structure, is a core element of the study of urban economics and the crucial determinant of commuting patterns. This paper examines developments in the analysis of urban spatial structure and commuting are related to the urban labour market—that is the analysis of labour supply and labour demand in a spatial context. These developments have been overlooked in the traditional approach to urban structure and commuting where most attention has been devoted to the markets for land and housing rather than the market for labour. Yet a little reflection suggests that the labour market might have a great deal to do with the location decisions of households and firms, and hence with commuting patterns. We argue that much criticism of the economic analysis of urban structure and commuting can be addressed by explicit incorporation of the labour market into the conventional model of urban location. This criticism includes findings that the theory cannot explain the tendency for richer households to live farther from the central business district and commute farther to work (Wheaton, 1977) and findings of substantial unexplained or ‘wasteful’ commuting according to conventional theory (Hamilton, 1982). The paper begins by outlining the basic model of residential location and commuting (Section 2). We then consider extensions that involve the introduction of labour supply decisions and which determine the value of commuting time (Section 3). More recent extensions involve the introduction of decentralized workplaces (Section 4) and, logically, the issues of job search and migration (Section 5). We conclude with a summary of the progress in incorporating labour market behaviour into the analysis of urban structure and commuting and our suggestions for further research in this area.

Segregation by Racial and Demographic Group: Evidence from the San Francisco Bay Area

This paper considers residential segregation by race and by type of household in 1970 and 1980. The paper presents entropy indices of segregation for the San Francisco Bay Area and its five metropolitan areas. The methodology permits an investigation of the effects of group definition upon segregation measures, and an analysis of the degree of independence in the segregation of households by race and demographic group. The results indicate that the levels of segregation by race and by household type have declined modestly during the 1970s, at least in this region. More importantly, however, the results indicate a remarkable independence in the spatial distribution of households by race and demographic group. Only a very small fraction of the observed levels of segregation by race could be 'explained' by the prior partitioning of households by demographic group. The principal results of the analysis are invariant to changes in the definition of racial or household groups.

Spatial Competition with a Land Market: Hotelling and Von Thunen Unified

We introduce into the standard spatial competition model the consumption of land by households, and study the spatial competition under the influence of a land market. In contrast to the standard assumption of a fixed, given distribution of households, we introduce the possibility of households' relocation in reaction to firms' location decisions. Thus, the spatial distribution of households is treated as endogenous, and a land market is introduced on which households compete for land-use. Households consume simultaneously land and firms' output. Accordingly, the demand of each household becomes in turn endogenous as it depends on the income left after the land rent is paid. Not surprisingly, the results obtained within this more general framework prove to be very different from the standard results. For example, in the 2- and 3-firm cases, the optimal configuration of firms is a Nash equilibrium when transport costs are high enough or the amount of vacant land is large enough. The existence property is restored in the 3-firm case when the transport costs are high enough. The introduction of vacant land causes a discontinuous change in the set of equilibrium configurations.

On the Spatial Distribution of Households According to Income

On the Spatial Distribution of Households According to Income