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"Neighborhood effects" research, which maintains that poverty concentration generates a variety of social problems, has been questioned for concealing the role of powerful institutions. As an alternative, we focus on external institutions' practices in marginal neighborhoods and their impact on the emergence of social problems. Through a qualitative case-study of three neighborhoods in Santiago, we observed institutional practices and identified three distinct mechanisms. Through disinvestments, these neighborhoods have been turned into "Red Zones," because of public, private, and civil institutions' refusal to establish themselves and to deliver their services there. Through inaction and inefficacy, public intervention has been deeply intermittent, negligent, and uncoordinated. Finally, through territorial stigmatization, these neighborhoods have almost become no-go areas. Several material and symbolic consequences have resulted from these practices, including direct and indirect connections with social problems. These have implications for the debate on "neighborhood effects" and for social mix policies. [ABSTRACT FROM AUTHOR]

This study investigates the association between school-level achievement and the relative health of the social environment in which children are embedded, to gain a more comprehensive understanding of how behavioural, social, physical, and socio-emotional contexts may holistically impact learning. While research has recognised how specific aspects of a child’s environment can impact learning, what is less understood is how multiple facets of socioecological conditions may holistically contribute to learning advantages or disadvantages. To address this, we combine seven years and over 9,000 observations of school-level achievement scores from the U.S. state of Alabama with a comprehensive scale of “socioecological health” – a measure that includes multiple indicators such as nutrition access, housing quality, neighbourhood violence, social supports, income inequality, and mental health access. We then employ a three-level hierarchical linear modelling approach to assess the association between socioecological health and school achievement. Results suggest that (1) higher levels of socioecological health are associated with higher levels of school achievement; (2) effects are strongest for older students and rural students; and (3) healthy behaviours, social supports, and positive physical environment correspond with higher school achievement. These results highlight the breadth to which social and environmental determinants may influence learning opportunities and underscores the need for a more holistic and inclusive approach to educational leadership and social policy. [ABSTRACT FROM AUTHOR]

This paper proposes a framework to examine how neighborhood factors influence criminal justice (CJ) contact and contribute to disparities across multiple stages of the justice process. By conceptualizing the punishment process as a dynamic set of decision-making points, this study highlights the role of neighborhood context in shaping offenders' CJ trajectories and post-CJ residential inequality. Using Harris County, Texas, as a case study, this research considers individual-, neighborhood-, and event-level variables to understand the cumulative effects of neighborhood characteristics on CJ outcomes. This study underscores the critical need to investigate neighborhood mobility and its broader implications for community development and public policy. The findings can be supported by extensive data from the Federal Statistical Research Data Centers and the Criminal Justice Administrative Records System, offering a robust analysis of offenders' spatial patterns and economic transitions. [ABSTRACT FROM AUTHOR]

It is not entirely clear what attribute of neighborhoods' race/ethnicity affects crime rates over time. Drawing on a sample of block groups in Baltimore (MD) we therefore estimate negative binomial regression models to test the concentration of specific ethnic groups in neighborhoods (% Black, % White, % Latino, % Asian, and % other race) as well as the level of heterogeneity among these groups. The results show that ethnic heterogeneity is associated with higher rates of both violent and property crime years later, whereas the measures of nonwhite ethnic groups are not significant. We also determine that concentrated disadvantage moderates the effect of ethnic heterogeneity on property crime. The implications of these findings for criminology and urban sociology are discussed. [ABSTRACT FROM AUTHOR]

This study reexamines the relationship between the coexistence of distinct ethno-cultural groups and social connectedness. Although previous research suggests a negative association between neighborhood-level ethnic diversity or ethnic minority shares and individual integration, alternative theoretical perspectives propose that integration can occur equally well in neighborhoods with distinct ethnic groups but may require more time. Moreover, the causal nature of the observed negative relationship is unclear due to potential confounding biases related to neighborhood selection. To address these issues, this study presents a framework for estimating the longitudinal effects of neighborhood ethnic composition on social ties with neighbors. The objective is to estimate the differences in neighborly contacts between individuals in low- and high-minority share neighborhoods, under a counterfactual scenario where all households stay in their neighborhood for the same period. The findings challenge previous research by showing that the ethnic composition does not impact the quality of neighborly contacts. In addition, residing in a neighborhood for five years significantly enhances social connectivity, regardless of ethnic composition. These results suggest that reduced cohesion in areas with higher minority presence may be due to other factors such as socioeconomic disadvantage and housing instability.

Abstract This paper proposes a framework to examine how neighborhood factors influence criminal justice (CJ) contact and contribute to disparities across multiple stages of the justice process. By conceptualizing the punishment process as a dynamic set of decision-making points, this study highlights the role of neighborhood context in shaping offenders’ CJ trajectories and post-CJ residential inequality. Using Harris County, Texas, as a case study, this research considers individual-, neighborhood-, and event-level variables to understand the cumulative effects of neighborhood characteristics on CJ outcomes. This study underscores the critical need to investigate neighborhood mobility and its broader implications for community development and public policy. The findings can be supported by extensive data from the Federal Statistical Research Data Centers and the Criminal Justice Administrative Records System, offering a robust analysis of offenders’ spatial patterns and economic transitions.

While police officers must adapt behavior between places to effectively do their jobs, these decisions could result in some communities receiving different levels of exposure to the police. This study explores a new spatial measure of police contacts to observe these differences. We calculate neighborhood-specific Gini coefficients based upon the spatial distribution of 77,752 police-civilian stops at street segments and intersections nested within census tracts in Oakland, California. This coefficient presents a contrast between two divergent distributional patterns—the diffusion of police contacts to more places across neighborhoods and the concentration of contacts at fewer "hot spot" places within neighborhoods. The most consistent environmental explanation for these differences was the race/ethnicity of neighborhood residents, which was associated with the police stopping people across more places. Future research should continue to investigate this finding and examine the mechanisms that explain why spatial exposure to police contacts changes between places. [ABSTRACT FROM AUTHOR]

Insect pollinators frequently forage with conspecifics in nature, thus it is important to understand their behavioral responses to the presence of conspecifics on flowers. Plant-pollinator interactions can be influenced by neighboring flowers, and these neighborhood effects can have important implications for plant fitness. Research about neighborhood effects generally tests how plant traits or different plant communities affect plant-pollinator or plant-herbivore interactions. However, neighborhood effects can also be considered from the point of view of an insect pollinator and how the presence of their own conspecifics on plants alters their perceptions of plant quality. We used the Western honey bee, Apis mellifera, to test whether neighborhood effects affect honey bee foraging behavior. In this context, we refer to neighborhood effects as the relative number of bees on neighboring flowers compared to the number of bees on a focal flower. We found that in a floral neighborhood, the relative number of honey bees present on neighboring flowers has a weak effect, such that more bees on neighboring flowers increase the likelihood of visits to a focal flower. Our results suggest that high numbers of bees on neighboring flowers increase the attractiveness of the entire neighborhood and low numbers of bees on the neighboring flowers decrease the attractiveness of the neighborhood, highlighting that bee activity on neighboring flowers may have significant impacts on pollination services. [ABSTRACT FROM AUTHOR]

It is well established that living in a high‐poverty area often leads to lower levels of well‐being for residents. While these deleterious effects of place‐based poverty are well‐documented, the conceptual mechanisms linking poverty of place to negative outcomes remain debated, and the our understanding of the spatial patterning of poverty remains underdeveloped. In this paper, we problematize simple conceptualizations of the negative impacts of poverty exposure by illustrating the dynamic patterns poverty displays across cities on a daily basis. The vast majority of prior research on poverty of place has relied upon data anchored to place of residence. Thus, poverty rates broadly reflect poverty as it exists at night. This bias toward nighttime statistics leaves us with an incomplete understanding of spatial inequalities because daytime poverty rates can differ markedly from nighttime poverty rates due to work‐related commuting patterns. Here, we use novel data from the Census Transportation Planning Products to fully illustrate diurnal patterns in poverty at the census tract level in metropolitan America. Through a combination of descriptive, spatial, and statistical analyses, we show that the majority of census tracts experience changes in poverty throughout the day. Through a series of regression models, we also show that diurnal patterns in poverty are unevenly distributed along the lines of suburbanization, race, economic status, age composition, and industrial structure. Overall, our findings provide analytic insights into properly documenting poverty across space, while further problematizing lingering culture of poverty frameworks. [ABSTRACT FROM AUTHOR]

Density dependence and habitat filtering have been proposed to aid in understanding community assembly and species coexistence. Phylogenetic relatedness between neighbors was used as a proxy for assessing the degree of ecological similarity among species. There are different conclusions regarding the neighborhood effect in previous studies with different phylogenetic indices or at different spatiotemporal scales. However, the effects of density dependence, neighbor phylogenetic relatedness, and habitat filtering on seedling survival with different phylogenetic indices or at different temporal and spatial scales are poorly understood. We monitored 916 seedlings representing 56 woody plant species within a 4‐ha forest dynamics plot for 4 years (from 2020 to 2023) in a subtropical mid‐mountain moist evergreen broad‐leaved forest in the Gaoligong Mountains, Southwestern China. Using generalized linear mixed models, we tested whether and how four phylogenetic indices: total phylogenetic distance (TOTPd), average phylogenetic distance (AVEPd), relative average phylogenetic distance (APd′), and relative nearest taxon phylogenetic distance (NTPd′), three temporals (1, 2, and 3 years), and spatial scales (1, 2, and 4 ha) affect the effect of density dependence, phylogenetic density dependence, and habitat filtering on seedling survival. We found evidence of the effect of phylogenetic density dependence in the 4‐ha forest dynamics plot. The effects of density dependence, phylogenetic density dependence, and habitat filtering on seedling survival were influenced by phylogenetic indices and temporal and spatial scales. The effects of phylogenetic density dependence and habitat filtering on seedling survival were more conspicuous only at 1‐year intervals, compared with those at 2‐ and 3‐year intervals. We did not detect any effects of neighborhood or habitat factors on seedling survival at small scales (1 and 2 ha), although these effects were more evident at the largest spatial scale (4 ha). These findings highlight that the effects of local neighborhoods and habitats on seedling survival are affected by phylogenetic indices as well as temporal and spatial scales. Our study suggested that phylogenetic index APd′, shortest time scale (1 year), and largest spatial scales (4 ha) were suitable for neighborhood studies in a mid‐mountain moist evergreen broad‐leaved forest in Gaoligong Mountains. Phylogenetic indices and spatiotemporal scales have important impacts on the results of the neighborhood studies. [ABSTRACT FROM AUTHOR]

Objectives : We test which neighborhood characteristics are associated with perceived control over victimization and how the neighborhood context explains differences between women's and men's perceived control. Methods: Drawing upon administrative data and a survey of 2,862 participants living in 80 neighborhoods in Victoria, Australia, we make a distinction between broader characteristics of the neighborhood, community processes, and gendered neighborhood dynamics. We run a series of multilevel mixed effects regression models to examine the relationship between individual-level perceptions of control over victimization and the neighborhood. Results: Results indicate that a concentration of low-income households in the neighborhood is associated with residents reporting less control over their victimization. Furthermore, the interaction revealed higher crime in the neighborhood lowered women's perceived control while heightening men's perceived control over victimization. Conclusions: Gender remained strongly associated with perceived control over victimization throughout the analysis despite extensive testing of general and gendered neighborhood conditions that may account for differences between women and men. The results found that overall crime rates were the only feature that assisted in explaining the differences between women and men. Future research must seek to better capture the environmental conditions that can account for the difference between women's and men's perceptions. [ABSTRACT FROM AUTHOR]

ABSTRACTUnderstanding the spatio-temporal evolution of urban expansion is essential for urban planning and sustainable development. Recently, cellular automata (CA)-based models have emerged as highly effective and widely utilized approaches for simulating urban expansion. However, they suffered from complex structural information inherent in neighborhood effects, including spatio-temporal dimension disjunction and neighborhood sensitivity. To address these issues, herein, we propose a spatial hierarchical learning module based cellular automata model (SH-CA). Specifically, to tackle the spatio-temporal dimension disjunction, we take spatial dependence and historical expansion trends into consideration. We redefine the neighborhood structure and introduce lightweight convolutional neural networks to capture the complex spatio-temporal interaction in neighborhood effects. For the neighborhood sensitivity, we develop a gate filter to aggregate multiscale neighborhood effects for ensuring the synthesis of diverse neighborhood effects disparities. The proposed SH-CA model was implemented to simulate urban expansion in three distinct main urban areas of Beijing, Guangzhou, and Chengdu in China during 2010–2015. The results showed that the proposed SH-CA greatly improves the figure of merit and simulates the most real land-use patterns compared with other four sophisticated CA models. Moreover, the hierarchical learning module effectively modeled spatio-temporal interaction in neighborhood effects, mitigated neighborhood sensitivity, and showed a strong scalability to existing popular CA-based models.

Urban growth has accelerated significantly in recent decades, categorized into two spatial patterns: adjacent and outlying growth. Traditional Cellular Automata (CA)-based models excel at simulating adjacent growth but exhibit limitations in modeling outlying growth, which can be summarized into two issues: 1) the overestimation of neighborhood effects caused by models’ excessive dependence on neighboring cell states; and 2) the ignorance of spatial heterogeneity in the relative importance of land suitability and neighborhood effects on urban growth. To address these problems, a novel CA model with Separate Extraction and Adaptive Fusion of land suitability and neighborhood effects (SEAF-CA) is proposed. In this model, a dual-path convolution structure is employed to extract spatial features from driving factors and cell states; geographical coordinates of each cell then input into a multilayer perceptron to derive spatially varying weights for feature fusion. Finally, the derived conversion probability is integrated with CA to simulate urban growth. Land use data collected from 2000 to 2020 in Wuhan are selected to evaluate the proposed model. Experimental results illustrate that SEAF-CA outperforms three typical CA models, achieving the closest outlying growth proportion to reality and the highest simulation accuracy. In addition, the source code of SEAF-CA is now available at GitHub (https://github.com/ohXu/SEAF-CA).

Communities of color and poor neighborhoods are disproportionately exposed to more air pollution-a pattern known as environmental injustices. Environmental injustices increase susceptibility to negative health outcomes among residents in affected communities. The structural mechanisms distributing environmental injustices in the USA are understudied. Bridging the literatures on the social determinants of health and environmental justice highlights the importance of the environmental conditions for health inequalities and sheds light on the institutional mechanisms driving environmental health inequalities. Employing a critical quantitative methods approach, we use data from an innovative state racism index to argue that systematic racialized inequalities in areas from housing to employment increase outdoor airborne environmental health risks in neighborhoods. Results of a multilevel analysis in over 65,000 census tracts demonstrate that tracts in states with higher levels of state-level Black-white gaps report greater environmental health risk exposure to outdoor air pollution. The state racism index explains four-to-ten percent of county- and state-level variation in carcinogenic risk and noncarcinogenic respiratory system risks from outdoor air toxics. The findings suggest that the disproportional exposure across communities is tied to systematic inequalities in environmental regulation and other structural elements such as housing and incarceration. Structural racism is an environmental justice issue.

Words with high orthographic relatedness are termed "word neighbors" (angle/angel; birch/birth). Activation-based models of word recognition assume that lateral inhibition occurs between words and their activated neighbors. However, studies of eye movements during reading have not found inhibitory effects in early measures assumed to reflect lexical access (e.g., gaze duration). Instead, inhibition in eye-movement studies has been found in later measures of processing (e.g., total time, regressions in). We conducted an eye-movement boundary change study (Rayner, Cognitive Psychology, 7(1), 65-81, 1975) that manipulated the parafoveal preview of the word following the neighbor word (word N+1). In this way, we explored whether the late inhibitory effects seen with transposed letter words and words with higher-frequency neighbors result from reduced parafoveal preview due to increased foveal load and/or interference during late stages of lexical processing (the L2 stage within the E-Z Reader framework). For word N+1, while there were clear preview effects, there was not an effect of the neighborhood status of word N, nor a significant interaction. This suggests that the late inhibitory effects of earlier eye-movement studies are driven by misidentification of neighbor words rather than being due to increased foveal load. [ABSTRACT FROM AUTHOR]

Competition among trees for limited resources (e.g., sunlight, water, and nutrients) impacts their growth differently. Crown plays a crucial role in resource access for trees. However, uncertainties persist regarding crown size differences, tree growth, and tree competition levels between coniferous and broadleaf trees in mixed-age forests. We conducted a study on 3008 live trees across 28 plots in Hunan Province to measure individual crown size and tree growth increment. Introducing a new metric, the Crown Size Competition Index (CSCI), we assessed competition pressure among coniferous and broadleaf species in mixed-age forests. We examined the correlation between competition indices and tree growth increment while also investigating the influence of neighboring species diversity on tree competition. Our results revealed a significant negative correlation between the tree growth of Cunninghamia lanceolata (Lamb.) Hook.(CL) and Phoebe bournei (Hemsl.) Yang (PB) and the competition index. Increased competitive pressure on the focal tree corresponded to a decline in the growth of focal tree volume, with a more pronounced impact observed in PB compared to CL. The diversity of neighboring species contributed to variations in competition for the focal tree, with broadleaved species (PB) exerting a greater influence on the focal tree than coniferous species (CL). These findings underscore the competitive potential of PB in mature coniferous stands and advocate for the restoration of stratified mixes in CL broadleaf forests. Furthermore, our findings support the management strategies for the valuable tree species PB. [ABSTRACT FROM AUTHOR]

Abstract Density dependence and habitat filtering have been proposed to aid in understanding community assembly and species coexistence. Phylogenetic relatedness between neighbors was used as a proxy for assessing the degree of ecological similarity among species. There are different conclusions regarding the neighborhood effect in previous studies with different phylogenetic indices or at different spatiotemporal scales. However, the effects of density dependence, neighbor phylogenetic relatedness, and habitat filtering on seedling survival with different phylogenetic indices or at different temporal and spatial scales are poorly understood. We monitored 916 seedlings representing 56 woody plant species within a 4‐ha forest dynamics plot for 4 years (from 2020 to 2023) in a subtropical mid‐mountain moist evergreen broad‐leaved forest in the Gaoligong Mountains, Southwestern China. Using generalized linear mixed models, we tested whether and how four phylogenetic indices: total phylogenetic distance (TOTPd), average phylogenetic distance (AVEPd), relative average phylogenetic distance (APd′), and relative nearest taxon phylogenetic distance (NTPd′), three temporals (1, 2, and 3 years), and spatial scales (1, 2, and 4 ha) affect the effect of density dependence, phylogenetic density dependence, and habitat filtering on seedling survival. We found evidence of the effect of phylogenetic density dependence in the 4‐ha forest dynamics plot. The effects of density dependence, phylogenetic density dependence, and habitat filtering on seedling survival were influenced by phylogenetic indices and temporal and spatial scales. The effects of phylogenetic density dependence and habitat filtering on seedling survival were more conspicuous only at 1‐year intervals, compared with those at 2‐ and 3‐year intervals. We did not detect any effects of neighborhood or habitat factors on seedling survival at small scales (1 and 2 ha), although these effects were more evident at the largest spatial scale (4 ha). These findings highlight that the effects of local neighborhoods and habitats on seedling survival are affected by phylogenetic indices as well as temporal and spatial scales. Our study suggested that phylogenetic index APd′, shortest time scale (1 year), and largest spatial scales (4 ha) were suitable for neighborhood studies in a mid‐mountain moist evergreen broad‐leaved forest in Gaoligong Mountains. Phylogenetic indices and spatiotemporal scales have important impacts on the results of the neighborhood studies.

Understanding drivers of plant community assembly and individual survival in forest ecosystems is crucial for effective conservation and management. While macro-scale factors influencing vegetation patterns are well documented, the combined impact of microtopographic variations and neighborhood effects at neighborhood scales, particularly in subtropical forests, requires further study. To contribute to this area of research, we established a 9.6 ha dynamic plot in a subtropical evergreen broad-leaved forest to examine the interplay between microtopographic factors and neighborhood effects on individual plant survival across different life stages. We conducted a comprehensive analysis of microtopographic variables and neighborhood effects, with individual plant survival censused through repeated surveys at 5-year intervals. Mixed-effects models were employed to assess the combined influence of these factors across life stages. Our results reveal that both microtopographic factors and neighborhood effects significantly influence plant survival, with their impacts varying across life stages. Water availability, represented by flow direction, emerged as a consistently critical factor throughout all life stages. Elevation and the topographic position index showed significant positive effects on survival, particularly in later life stages, possibly reflecting adaptations to light acquisition and water drainage. The influence of topographic factors intensified with succession, while the impact of neighborhood effects, particularly asymmetric competition and conspecific negative density dependence, changed as plants matured. This study enhances our understanding of forest community assembly, emphasizing the importance of considering abiotic and biotic factors across multiple scales for effective forest conservation and management. It provides insights into mechanisms driving spatial variation in community composition, crucial for preserving biodiversity in heterogeneous forest landscapes.

Based on the perspective of combining informal and formal systems, this paper empirically explores the impact of neighborhood effects and policy interventions on the deviation of farmers' willingness and behavior of domestic waste separation (DWS) by using data from the China Land Economy Survey (CLES) and constructing a probit model. It should be explained that the neighborhood effect in this paper refers to the fact that the behavior of farmers is highly susceptible to the behavior of their neighbors in the process of production and living. The results of the study show that neighborhood effects and policy interventions have a significant negative impact on the deviation of farmers' willingness and behavior of DWS, respectively. Comparison of marginal effects shows that neighborhood effects > environmental advocacy > reward and punishment policies. From the interaction effects as a whole, neighborhood effects and policy interventions have complementary effects on the deviation of farmers' willingness and behavior of DWS, with the complementary effects of neighborhood effects and environmental advocacy being more significant. Heterogeneity analysis reveals that neighborhood effects completely replace the inhibitory effect of policy interventions on the deviation of high-income farmers' willingness and behavior of DWS, but have no effect on political elite farmers. The interaction between neighborhood effects and policy interventions has complementary effects on low-income farmers and ordinary farmers, with the complementary effects of neighborhood effects and environmental advocacy being more significant. [ABSTRACT FROM AUTHOR]

In August 2008, Beijing hosted the Summer Games of the XXIX Olympiad. On the fifteenth anniversary of that event, this article takes a multi-dimensional approach to analyzing the impact that the Games had on the neighborhoods surrounding the venues ("micro" effects), the city and country ("macro" effects), and China's international standing ("global" effects). The study is unique in including several years of direct observations made by one of the authors during the bid announcement period, the preparation period, and both the Games and post-Games periods. The study integrates the observational data with a review of relevant academic literature, an evaluation of Beijing's sustainability efforts, an assessment of domestic and international economic data, and an examination of the change in China's national power ranking to provide a holistic view of the Games' tangible and intangible legacies. The study compares data from a baseline period prior to the International Olympic Committee's 2001 announcement that Beijing would host the Games with data from the year following the announcement through 2015. The study finds that the Beijing Games accelerated urban renewal and sustainability efforts, strengthened national pride, and enhanced the country's global economic position and political influence. [ABSTRACT FROM AUTHOR]

Identifying the determinants of social mobility for children of non-Western immigrants is of vital concern as immigration pressures grow across the West. Prior studies have minimized the role of place as one such determinant but suffers from several unsupportable assumptions. We interrogate this issue by quantifying the relative contributions made by family and neighborhood characteristics in explaining the educational attainments of young adults, paying special attention to how effects differ by gender and parental immigrant status. Our statistical models provide plausibly causal estimates by controlling for geographic selection bias. We estimate model parameters using several cohorts of children raised in Oslo, Norway, for whom government registers provide exceptionally detailed information about cumulative exposures of children to family and neighborhood contexts. Our decomposition demonstrates that differences in childhood neighborhood have a substantial effect on male (but not female) immigrant-native gaps in the probabilities of completing secondary school and of enrolling in university, though these effects are smaller than those reflecting differences in family background. We discuss implications of our findings for people- and place-based social policies aimed at enhancing immigrant opportunities. [ABSTRACT FROM AUTHOR]

In this study, we examine whether students in violent neighborhoods actively avoid their local school as a form of social and physical protection. Specifically, we use 10 years of administrative data (2010–2020) from the high school choice open enrollment program in the Baltimore City Public School System to evaluate the interaction between neighborhood violence and geographic proximity when predicting choice behavior. We find that, adjusting for observed school characteristics and constant unobserved student characteristics, students from more violent neighborhoods are substantially less likely to choose their closest school than are students in safer neighborhoods; even when the closest school is listed, it is ranked lower for students from more violent neighborhoods than for students in safer ones. These findings have implications for how we think about the relationship between neighborhoods and educational opportunity in an era of choice. [ABSTRACT FROM AUTHOR]

The structure of plant communities at local scales depends on both the spatial heterogeneity of abiotic environmental factors and the biotic interactions within the community. However, although environmental filtering due to microtopographic heterogeneity and resource competition among plants caused by spatial variation in tree density and size are considered to be very important in explaining the mechanisms of community assembly, their effects on the processes of individual mortality and recruitment in natural forest regeneration, as well as their relative contributions, are still poorly understood. To address this, we established a 12-ha permanent plot in a subtropical evergreen broad-leaved forest area and measured microtopographic variables such as elevation, slope, aspect, and terrain position index (TPI) using a total station. We monitored the individual mortality and recruitment in forest natural regeneration through repeated surveys at 5-year intervals. We fitted spatial covariance models to jointly use multiple factors from three groups of variables (microtopographic effect, neighborhood density effects, neighborhood size effects) as explanatory variables to analyze their roles in driving the mortality and recruitment of all individual and 12 dominant species in forest natural regeneration at the neighborhood scale. Our results show that: (1) In the crucial early stages of secondary forest restoration, natural regeneration is influenced by a synergy of environmental filtering, due to microtopographic heterogeneity, and resource competition among plants. (2) For distinct species responses, evergreen dominant species' mortality is largely explained by neighborhood effects, while deciduous species are more affected by topographic factors. Furthermore, the adverse effects of larger conspecific trees on younger trees indicate a pattern of competitive pressure leading to mortality among regenerating trees, such pattern emphasis the influence of parent trees on natural regeneration. (3) As trees grow, their interaction with these stressors evolves, suggesting a shift in their resource acquisition strategies and response to neighborhood effects and environmental factors. Despite these changes, the relative importance of topographic factors in determining survival and recruitment success remains constant. This research highlights the importance of considering both environmental and neighborhood effects in forest management, particularly in early secondary forest restoration. [ABSTRACT FROM AUTHOR]

Sustainable agricultural development has been the policy priority for countries with limited natural resources. New farmers' emergence and growth have not only helped to address the labor crisis in agriculture to some extent, but they have also improved, integrated, and expanded the agricultural sectors. However, less attention has been paid to the performance of new farmers in adopting sustainable agricultural practices and the related spatial effects. Also, few studies have combined the composite adoption intensity of sustainable agricultural practices with the effects of various specific measures. Therefore, this study constructed the Tobit MLE spatial cross-section regression models to empirically study a sample of 174 farmers. We attempted to analyze the impact of the new farmers group on the diffusion of sustainable agricultural practices as well as farmers' influence on various sorts of sustainable agricultural practices. The results show that new farmers greatly enhanced the adoption of sustainable agricultural practices, as evidenced by the fact that their adoption level was 69.9% greater than that of traditional farmers. However, they had statistically significant negative spillover effects on their neighboring farmers. For the composite adoption intensity of sustainable agricultural practices, there were also statistically significant negative spillover effects. Additionally, there were notable disparities among the factors influencing farmers' decisions to adopt various types of sustainable agricultural practices and the spatial effects of those adoptions, particularly in the farm size, the number of plots, and the variety of marketing methods employed by farmers. Therefore, measures need to be proposed to address the barriers to the implementation and diffusion of various types of sustainable agricultural practices. This would increase farmers' willingness to adopt sustainable agricultural practices and the effectiveness of their motivation to neighboring farmers. [ABSTRACT FROM AUTHOR]

It is well known that the racial composition of a neighborhood influences who chooses to live there. Less established is whether the political party mix of the neighborhood influences neighborhood choice. In this paper, we study racial and political neighborhood sorting, their interaction, and how they are changing over time. Our methodology involves the estimation of a conditional logit model with data on hundreds of thousands of homebuyers whose race and political affiliation are known. The neighborhood choices of homeowners categorized by race and party are explained by a typology that defines neighborhoods by their dominance of a particular party and race/ethnicity. We find that both Democrats and Republicans prefer living in a neighborhood that matches their race and political party, but both show an increased willingness to live in a non-matched neighborhood over the past decade. Our results are encouraging, suggesting that both political and racial/ethnicity neighborhood segregation may subside in the future. [ABSTRACT FROM AUTHOR]

Abstract Background Presently, global aging has become increasingly serious, whereas the health concerns brought by aging have become a public issue that warrants an urgent solution from all countries across the world. Therefore, this research paper discusses the influence of neighborhood health on elderly individuals’ health, and extending a realistic basis for the other economies to improve the neighborhood environment and promote the health of the elderly. Methods Based on the data of CHARLS2018, this research paper adopts the samples that fulfill the study requirements (N = 7326). we constructed a comprehensive research framework integrating oprobit regression model, heterogeneity analysis, conditional mixed process(CMP)robustness testing, Furthermore, the KHB decomposition method is implemented to ascertain the influential mechanism of NMH and NPH on the mental- and physical health of elderly persons. Results The oprobit regression model analysis indicates that NMH 0.434 and NPH 0.550 exert positive influences on the elderly’s mental- and physical health. Meanwhile, the effects of conditional mixed process on NMH and NPH stand at 0.381 and4.372, which are different from the oprobit regression results; thereby, indicating the existence of endogeneity. Afterward, KHB mediating effect confirms that Internet use, gift reciprocity, and charity activity contribute 30.21% and 16.83% to mental- and physical health, respectively. Conclusions Firstly, the NMH and NPH demonstrate a positive influence on the mental- and physical health of the elder population. However, there exist heterogeneous differences. Secondly, the conditional mixed process deals with the endogeneity of NMH and NPH. Thirdly, social integration, social interaction, and social engagement serve as significant transmission mechanisms for the influences of NMH and NPH on the health of elderly persons.

Abstract In mountainous rural settlements facing the threat of geohazards, local adaptation is a self-organizing process influenced by individual and group behaviors. Encouraging a wide range of local populations to embrace geohazard adaptation strategies emerges as a potent means of mitigating disaster risks. The purpose of this study was to investigate whether neighbors influence individuals’ adaptation decisions, as well as to unravel the mechanisms through which neighborhood effects exert their influence. We employed a spatial Durbin model and a series of robustness checks to confirm the results. The dataset used in this research came from a face-to-face survey involving 516 respondents residing in 32 rural settlements highly susceptible to geohazards. Our empirical results reveal that neighborhood effects are an important determinant of adaptation to geohazards. That is, a farmer’s adaptation decision is influenced by the adaptation choices of his/her neighbors. Furthermore, when neighbors adopt adaptation strategies, the focal individuals may also want to adapt, both because they learn from their neighbors’ choices (social learning) and because they tend to abide by the majority’s choice (social norms). Incorporating neighborhood effects into geohazard adaptation studies offers a new perspective for promoting disaster risk reduction decision making.

Background: Presently, global aging has become increasingly serious, whereas the health concerns brought by aging have become a public issue that warrants an urgent solution from all countries across the world. Therefore, this research paper discusses the influence of neighborhood health on elderly individuals' health, and extending a realistic basis for the other economies to improve the neighborhood environment and promote the health of the elderly. Methods: Based on the data of CHARLS2018, this research paper adopts the samples that fulfill the study requirements (N = 7326). we constructed a comprehensive research framework integrating oprobit regression model, heterogeneity analysis, conditional mixed process(CMP)robustness testing, Furthermore, the KHB decomposition method is implemented to ascertain the influential mechanism of NMH and NPH on the mental- and physical health of elderly persons. Results: The oprobit regression model analysis indicates that NMH 0.434 and NPH 0.550 exert positive influences on the elderly's mental- and physical health. Meanwhile, the effects of conditional mixed process on NMH and NPH stand at 0.381 and4.372, which are different from the oprobit regression results; thereby, indicating the existence of endogeneity. Afterward, KHB mediating effect confirms that Internet use, gift reciprocity, and charity activity contribute 30.21% and 16.83% to mental- and physical health, respectively. Conclusions: Firstly, the NMH and NPH demonstrate a positive influence on the mental- and physical health of the elder population. However, there exist heterogeneous differences. Secondly, the conditional mixed process deals with the endogeneity of NMH and NPH. Thirdly, social integration, social interaction, and social engagement serve as significant transmission mechanisms for the influences of NMH and NPH on the health of elderly persons. [ABSTRACT FROM AUTHOR]

In mountainous rural settlements facing the threat of geohazards, local adaptation is a self-organizing process influenced by individual and group behaviors. Encouraging a wide range of local populations to embrace geohazard adaptation strategies emerges as a potent means of mitigating disaster risks. The purpose of this study was to investigate whether neighbors influence individuals' adaptation decisions, as well as to unravel the mechanisms through which neighborhood effects exert their influence. We employed a spatial Durbin model and a series of robustness checks to confirm the results. The dataset used in this research came from a face-to-face survey involving 516 respondents residing in 32 rural settlements highly susceptible to geohazards. Our empirical results reveal that neighborhood effects are an important determinant of adaptation to geohazards. That is, a farmer's adaptation decision is influenced by the adaptation choices of his/her neighbors. Furthermore, when neighbors adopt adaptation strategies, the focal individuals may also want to adapt, both because they learn from their neighbors' choices (social learning) and because they tend to abide by the majority's choice (social norms). Incorporating neighborhood effects into geohazard adaptation studies offers a new perspective for promoting disaster risk reduction decision making. [ABSTRACT FROM AUTHOR]

In this paper, I applied criminological theory to the epidemiological understanding of health-related deviant behavior such as problematic drug use. To that end, I built and subsequently tested an epidemiological model informed by macro-level criminological theory that helped explain the spatial distribution of accidental drug deaths across neighborhoods in a heavily suburban area (i.e. unincorporated Miami-Dade County, FL), analyzing toxicology reports from the Miami-Dade County Medical Examiner Department. Estimating a negative binomial analysis of drug abuse that predicted drug-related death rates from 2013 through 2017, I drew insights from the following place-based control theories or perspectives in macro criminology: social disorganization, relative deprivation, immigration revitalization, social institutions, and drug enforcement. I found support for social disorganization theory and the immigration revitalization and social institutions perspectives. Since drug abuse is deviant behavior that is both criminal and health-related, criminology and epidemiology appear to overlap with one another. Epidemiology, the study of disease distribution among populations, would profit by integrating insights from social control theories of criminology. Researchers interested in the social context of neighborhoods and the clustering of drug deaths can apply macrocriminological theory to social epidemiology, which concerns itself with the social determinants of health. [ABSTRACT FROM AUTHOR]

As evidence of the relationship between place and health mounts, more epidemiologists and clinical science researchers are becoming interested in incorporating place-based measures and analyses into their examination of population health and health inequities. Given the extensive literature on place and health, it can be challenging for researchers new to this area to develop neighborhood-effects research questions and apply the appropriate measures and methods. This paper provides a road map for guiding health researchers through the conceptual and methodological stages of incorporating various dimensions of place into their quantitative health research. Synthesizing across reviews, commentaries, and empirical investigations, the road map consists of 4 broad stages for considering place and health: 1) why? : articulating the motivation for assessing place and health and grounding the motivation in theory; 2) what? : identifying the relevant place-based characteristics and specifying their link to health to build a conceptual framework; 3) how? : determining how to operationalize the conceptual framework by defining, measuring, and assessing place-based characteristics and quantifying their effect on health; and 4) now what? : discussing the implications of neighborhood research findings for future research, policy, and practice. This road map supports efforts to develop conceptually and analytically rigorous neighborhood research projects. [ABSTRACT FROM AUTHOR]

Immigrants tend to live in areas with higher co-ethnic density, and the effect of neighborhood ethnic composition could be particularly salient for health. This study explored associations between neighborhood ethnic composition and self-rated health among Asian immigrants. We analyzed data collected at baseline from 670 Chinese and Vietnamese immigrants enrolled in a lifestyle intervention trial. Residential addresses were geocoded and combined with neighborhood socio-demographic profiles based on census data. We used generalized estimating equations to examine neighborhood ethnic composition and self-rated health. Independent of individual-level factors, living in neighborhoods more densely populated by whites was associated with poor/fair self-rated health. Neighborhood household income and density of participants' own ethnic group were not associated with poor/fair self-rated health. More research is warranted to disentangle reasons why Chinese and Vietnamese immigrants living in white-concentrated neighborhoods reported poorer self-rated health, including investigating effects of discrimination, relative deprivation, and availability of social resources.

We revisit a novel causal model published in Demography by Hicks et al. (2018), designed to assess whether exposure to neighborhood disadvantage over time affects children's reading and math skills. Here, we provide corrected and new results. Reconsideration of the model in the original article raised concerns about bias due to exposure-induced confounding (i.e., past exposures directly affecting future exposures) and true state dependence (i.e., past exposures affecting confounders of future exposures). Through simulation, we show that our originally proposed propensity function approach displays modest bias due to exposure-induced confounding but no bias from true state dependence. We suggest a correction based on residualized values and show that this new approach corrects for the observed bias. We contrast this revised method with other causal modeling approaches using simulation. Finally, we reproduce the substantive models from Hicks et al. (2018) using the new residuals-based adjustment procedure. With the correction, our findings are essentially identical to those reported originally. We end with some conclusions regarding approaches to causal modeling.

Justice-involved people vary substantially in their risk of reoffending. To date, recidivism prediction and prevention efforts have largely focused on individual-level factors like antisocial traits. Although a growing body of research has examined the role of residential contexts in predicting reoffending, results have been equivocal. One reason for mixed results may be that an individual's susceptibility to contextual influence depends upon his or her accumulated risk of reoffending. Based on a sample of 2218 people on probation in San Francisco, California, this study draws on observational and secondary data to test the hypothesis that individual risk moderates the effect of neighborhood factors on recidivism. Results from survival analyses indicate that individual risk interacts with neighborhood concentrated disadvantage and disorder-and these factors increase recidivism among people relatively low in individual risk, but not those at higher risk. This is consistent with the disadvantage saturation perspective, raising the possibility that some people classified as low risk might not recidivate but for placement in disadvantaged and disorderly neighborhoods. Ultimately, residential contexts "matter" for lower risk people and may be useful to consider in efforts to prevent recidivism.

IntroductionResearch has documented that home and neighborhood contexts of children from low-income families are associated with lower cognitive and social–emotional skills than their higher-income peers. Even though over a third of young children growing up in poverty are dual language learners (DLLs), little research has examined how contextual effects differ between DLL and monolingual children. The current study examines how these two contexts, neighborhood vulnerability and family socioeconomic risk, impact executive function (EF) and social–emotional skills in DLL and monolingual preschoolers.MethodsA secondary analysis was completed on data from two Head Start programs. A series of cross-classified models with interactions were conducted to examine the moderating role of DLL status on associations between neighborhood vulnerability and family risk and preschoolers’ EF and social-emotional skills.ResultsProficient bilingual children’s EF skills were not impacted by neighborhood risks, suggesting that proficient bilingual children may have more opportunities to grow their EF skills when switching between English and Spanish regardless of neighborhood context. An unexpected result occurred for emergent bilingual children who were reported to demonstrate fewer behavior problems regardless of family risk, highlighting the importance of ensuring all DLL families have access to resources to promote their children’s social–emotional skills; and teachers have the proper training to support the behaviors of children in their classroom with varying levels of English proficiency.DiscussionAlthough speaking two languages may be a protective factor for young DLLs growing up in poverty, little research has examined how contextual effects differ between DLL and monolingual children. The current study contributes by examining how DLL status, especially two different DLL statuses (i.e., Proficient Bilinguals and Emergent Bilinguals), may vary as a buffer in moderating the negative associations between collective neighborhood vulnerability, individual family risk, and children’s EF and social–emotional skills.

Frequency and severity of extreme weather events, such as floods or heat waves, increase as a result of climate change. Therefore, it is important to investigate which factors might influence adaptation decisions at the household level. In this context, we examine whether adaptation behavior is related to adaptation decisions reported by neighboring households or to the perception that neighbors have implemented such measures. The empirical analysis is based on a large-scale household survey in Germany (4784 geo-located households) and multivariate regressions of different types of adaptation behavior: structural/behavioral flood and heat adaptation measures as well as the purchase of flood insurance for residential buildings and contents. We contribute to existing research inter alia by providing first insights on neighborhood effects regarding heat adaptation and by considering adaptation behavior as it is reported by neighbors, rather than as it is perceived by survey respondents. The results suggest positive neighborhood effects in the context of structural adaptation measures, but no effects on insurance purchase decisions. Neighborhood effects on flood adaptation are stronger for households without prior flood experience and depend on available household income. These findings show that individuals’ climate adaptation behavior may be affected by the observed behavior of social peers. Therefore, neighborhood effects are important to be considered by policy-makers to strengthen private adaptation behavior. [ABSTRACT FROM AUTHOR]

Parking citations are among the most common minor offenses, which can result in millions of dollars in revenue each year for cities. However, it is an open question whether the spatial distribution of parking citations is equitable in terms of neighborhoods’ racial/ethnic composition and economic standing. To the extent that parking citations are issued in nonwhite or low-income neighborhoods, this would represent a form of urban inequality. Thus, for the present study, we assess this understudied proposition by collecting data on neighborhoods in San Francisco, California, and estimating a series of negative binomial regression models. Although we find that measures of nonwhite ethnicities are non-significant in relation to all types of parking citations, we do find evidence that low-income neighborhoods have significantly higher rates of both street cleaning and metered parking citations, in comparison to high-income neighborhoods. We also determine that the effect of neighborhood income is moderated by the concentration of certain ethnicities. The implications of these findings for urban sociology and public policy are discussed. [ABSTRACT FROM AUTHOR]

Climate and landcover change can have synergistic impacts on wildlife populations, but the pervasiveness of these threats and factors that buffer them remain unclear despite important implications for conservation. I evaluated the additive and interactive effects of spatiotemporal variation in temperature, precipitation, and landcover change on annual territory occupancy, colonization, and extinction of a threatened top‐predator, the ferruginous pygmy‐owl (Glaucidium brasilianum), across a vast binational region of the Sonoran Desert over 16 years. I also assessed how local habitat quality and regional population size mediate impacts of these stressors. Despite significant bivariate associations between occupancy and temperature, precipitation, and landcover change, evidence for interactions was much greater than for additive effects. Occupancy of territories imbedded in increasingly disturbed landscapes declined at greater rates with warming winter temperatures, but the temperature had little effect in intact landscapes suggesting they buffer impacts of climate warming. Occupancy increased markedly with precipitation due likely to major positive impacts on prey, but again, interactive effects were stronger given territories of higher quality amplified benefits of precipitation. Impacts of landcover change and habitat quality on extinction depended markedly on regional population sizes. When populations were small and few potential colonists were present, high‐quality habitat and low landcover change failed to reduce extinction. When populations were large, however, high‐quality habitat and more intact landscapes, which best foster dispersal, reduced extinction. Hence, complex interacting processes linked to the effects of precipitation and habitat quality on carrying capacity, landcover change on habitat connectivity and vulnerability to rising temperatures, and local population sizes simultaneously drove dynamics. Efforts to identify and protect high‐quality habitat and limit landcover change can enhance conservation but will be most efficient in intact landscapes. Efforts to enhance local habitat quality and quantity, and directly augment populations should consider broader landscape contexts linked to habitat connectivity and potential source populations. [ABSTRACT FROM AUTHOR]

The ideal of U.S. public education as "a great equalizer" remains unrealized across large swaths of the country. Young people in schools are at varying levels of educational advantage and disadvantage owing to wide gaps in learning opportunities and disparate access to high-quality curriculum. Unequal educational achievement has also been linked to inequities affecting some students before they enter school due to socioeconomic circumstances, prejudice, and discriminatory social systems and structures. In this study, we begin to partition the various factors that account for inequality in student outcomes in the context of U.S. geography education. Using large-scale data sets provided by the National Center for Education Statistics within the U.S. Department of Education, we developed a two-level statistical model to analyze the extent to which geography achievement in eighth grade varies systematically with contextual opportunity to learn (OTL) factors and the relative poverty level of neighborhoods around schools. Hierarchical linear modeling was used to account for data clustering, producing an achievement estimate for each predictor and controlling for the effects of all other predictors. Statistically significant OTL predictors included instructional exposure, taking geography prior to eighth grade, teaching experience, and the availability of computers in classrooms. Schools located in neighborhoods with higher income-to-poverty ratios outperformed schools in neighborhoods closer to the federal poverty threshold. Controlling for OTL and school neighborhood effects accounted for some of the geography achievement disadvantage associated with race and other student characteristics. Geographers can further explore these relationships with formal mediational models and educational programs based on equity-oriented frameworks. [ABSTRACT FROM AUTHOR]

Adjacency neighborhood effects such as neighbor interactions or perceived neighborhood quality have been neglected in the housing literature due to a lack of data. We investigate the impact of these effects on the housing wealth perceived by homeowners. Using a national longitudinal survey, we find that perceived neighborhood quality positively impacts owner-assessed home values. However, this effect is driven by homeowners' assessment of their neighborhoods' quality relative to other neighborhoods rather than their neighborhoods' perceived cleanliness or upkeep. Depending on the financial characteristics of homeowners, we also find neighbor interactions and perceived neighborhood safety to have a significant relation with self-assessed home values. Trust and support among neighbors and joint feel of the home and neighborhood on the other hand have no relation with estimated values. While neighborhood quality consistently explains owner-assessed values, home quality only has a relation with value estimates for homeowners with certain financial characteristics. Considering the importance of perceived housing wealth for household financial decisions as well as transaction prices, our findings have implications for policy makers and developers. [ABSTRACT FROM AUTHOR]

Robust literatures separately estimate school effects and neighborhood effects on children's educational, economic, health, and other outcomes that measure well-being. A growing body of research acknowledges that both contexts matter and considers neighborhoods and schools jointly. In this review, we synthesize the array of results that emerge from these studies and critique the tendency for researchers to evaluate which matters more, neighborhoods versus schools. We propose a reorientation of this scholarship that incorporates research on neighborhood and school selection and segregation processes. We argue that contextual effects research would be enriched by considering local neighborhood–school structures: the ways that families choose neighborhoods and schools and that neighborhoods and schools mutually and cyclically constitute one another. We conclude with recommendations for bringing neighborhood–school structures to bear on both outcomes-oriented studies of neighborhood and school effects as well as studies of contextual selection and segregation. [ABSTRACT FROM AUTHOR]

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Abstract Background Healthy aging in place is affected by what the neighborhood provides for older adults. The mixed-methods ethnographic study explored the built environmental and contextual effects of urban parks and traditional local coffeeshops (kopitiam) on health practices among older adults in Singapore. Methods A door-to-door survey with 497 older adults from 32 residential blocks in a public housing town assessed exercise and smoking. The walking distances from the residential blocks to the facilities were calculated. Regression analysis examined the associations between the distance and rates of exercise and smoking. Ethnographic assessment data contextualized the quantitative findings. Results Older adults’ exercise was associated with proximity to an urban park but not traditional local coffeeshops. High rates of smoking were clustered in the housing blocks close to the coffeeshops, which provided casual drinking places with smoking tables. The proximity to the coffeeshops was significantly associated with increased smoking and decreased exercise. A walking distance of 200 m to the park and coffeeshops was found to discriminate the outcomes. Conclusions The findings suggested that walking distances of a few blocks influenced health behaviors among older adults. Their smoking habits appeared to be maintained through environmental features and cultural norms attached to the coffeeshops. Policy of urban planning and redevelopment for the aging population needs to consider the socioecology of healthy aging in place.

A growing literature explores how local environments, or contexts, affect political behavior, especially by shaping interpersonal contact with social out-groups. While many studies still draw directly on long-standing hypotheses from contact theory, this research agenda increasingly focuses on new research questions, beyond the classic social psychology literature, and new empirical cases, including from across the lower- and middle-income world. We develop a typology of forms of context and contact to aid the aggregation of findings across disparate cases and demonstrate that the mechanisms that may account for the political effects of intergroup context and contact are broader than those typically explored in psychologically oriented research. We propose future directions for research in this area, including greater focus on the intersection of ethnic and class-based contact and greater attention to how built or computer-based environments may mediate or mirror the effects of demographic contexts. [ABSTRACT FROM AUTHOR]

There has been a renewed interest in moving back into cities, which are close to business districts and offer affordable and unique housing. However, the available housing is limited and may require renovation as available housing close to the citycenter is often located in more economically disadvantaged neighborhoods. Property repairs and upgrading contributes not only to the improvement of individual owners' properties, but the neighborhood overall. This influx of new residents and subsequent investment in housing can impact neighborhood crime, but the majority of the research on housing and crime has focused largely on home mortgage loans. The current study extends the housing investment literature by using an underutilized data source: home improvement and refinance loans, which signal physical improvement in the housing stock. This process may be different for neighborhoods that have a higher prevalence of minority residents as historically these residents have been subjected to inequitable lending practices. The current study examines how revitalization efforts in Cleveland, Ohio have influenced crime rates for the years 2007 through 2017 with special attention paid to the interplay of neighborhood racial composition and home improvement loans. Results from fixed-effects panel analysis reveal that home improvement loans are associated with an increase in property but not violent crime rates overall. Splitting neighborhoods into predominantly Black versus all other neighborhoods, however, results show that higher rates of home improvement loans are associated with lower violent crime rates, but the effect is tempered in Black neighborhoods. This suggests that the relationship between home improvement loans and violent crime is more complicated and varies by neighborhood composition. [ABSTRACT FROM AUTHOR]

Based on Norwegian administrative registers, we provide new empirical evidence on the effects of the childhood neighborhood's socioeconomic status on early educational performance. A neighborhood's status is measured annually by its adult inhabitants' earnings ranks within larger commuting zones, and the childhood neighborhood status is the average status of the neighborhoods inhabited from the year after birth to age 15. Identification of causal effects relies on within-family comparisons only. Our results reveal a distinct hump-shaped relationship between the socioeconomic status of the childhood neighborhood and school results at age 15–16, such that the optimal neighborhood is of medium rank. [ABSTRACT FROM AUTHOR]