Concrete evidence & geographically weighted regression: A regional analysis of wealth and the land cover in Massachusetts

Several studies indicate that there is a positive relationship between green vegetation land cover and wealthy socio-economic conditions in urban areas. The purpose of this research is to test for and explore spatial variation in the relationship between socio-economic and green vegetation land cover across urban, suburban, and rural areas, using geographically weighted regression (GWR). The analysis was conducted at the census block group level for Massachusetts, using Census 2000 data and impervious surface data at 1-m resolution. To explore regional variations in the relationship, four scenarios were generated by regressing each of the following socio-economic variables – median household income, percentage of poverty, percentage of minority population, and median home value – against two environmental variables – percent of impervious surface and population density. GWR results show that there is a considerable spatial variation in the character and the strength of the relationship for each model. There are two main conclusions in this study. First, the impervious surface is generally a strong predictor of the level of wealth as measured by four variables included in the analysis, at the scale of census block group; however, the strength of the relationship varies geographically. Second, GWR, not ordinary least squares technique, should be used for regional scale spatial analysis because it is able to account for local effects and shows geographical variation in the strength of the relationship.     

Labor Market Marginalization of Youth in San Antonio,Texas

Poverty among inner-city residents is associated with their marginal status in the labor market. Marginalization in the labor market begins during youth when important educational and employment decisions are made. Analysis of 1990 U.S. Census tract data for San Antonio, Texas identifies the lack of a high school diploma, poverty, non-employment, and non-enrollment in school as conditions of marginality for youth. Spatial patterns of youth labor market marginalization show concentrations in the inner city and in sectors on the West, South, and Eastside. Regression analysis reveals that levels of youth marginalization are associated with neighborhood context represented by the employment, behavioral, and ethnic characteristics of the overall residential population of a census tract.     

Labor Market Marginalization of Youth in San Antonio,Texas

Poverty among inner‐city residents is associated with their marginal status in the labor market. Marginalization in the labor market begins during youth when important educational and employment decisions are made. Analysis of 1990 U.S. Census tract data for San Antonio, Texas identifies the lack of a high school diploma, poverty, non‐employment, and non‐enrollment in school as conditions of marginality for youth. Spatial patterns of youth labor market marginalization show concentrations in the inner city and in sectors on the West, South, and Eastside. Regression analysis reveals that levels of youth marginalization are associated with neighborhood context represented by the employment, behavioral, and ethnic characteristics of the overall residential population of a census tract.     

Declining inner suburbs? A longitudinal-spatial analysis of large metropolitan regions in Canada

Spatially referenced quantitative research that attempts systematically to assess inner suburban decline in Canadian metropolitan areas is almost completely missing from the literature. This paper aims to fill this gap and examine whether inner suburban decline is occurring in Canada. Aggregated census tract level data are used to assess all zones for decline based on relative prosperity changes in median household income, average dwelling values, and average gross rent. The results indicate that inner suburbs in Canadian cities experienced a decline in median household income, average dwelling value, and prosperity factors between 1986 and 2006. While a few possible explanations and policy approaches are offered, more research is necessary to explore the implications of these trends.     

HOUSING PROVISION IN DEVELOPED ECONOMIES

This research uses a quantitative and qualitative approach in assessing the structural effects of neighborhoods on the outcomes of noncompletion of high school and adolescent child-bearing. The results from the regression analyses indicate that median household income is the most important of the three structural variables analyzed at the block group level in terms of explaining noncompletion of high school and adolescent childbearing. Additionally, median household income has a significant nonlinear relationship with noncompletion of high school. Adolescents were interviewed in order to ascertain their perceptions of structural factors at work in their neighborhoods, to gain a clearer idea of their norm networks, and to hear their attitudes on dropping out of high school and teen pregnancy. The qualitative findings suggest that research on neighborhood-level effects on outcomes must include qualitative methodology in order to clarify what processes are occurring and how structural variables translate into adolescents' decision making.     

Estimating Future Residential Water Consumption in Phoenix,Arizona Based on Simulated Changes in Climate

Previous studies have shown that residential water consumption in Phoenix, Arizona is significantly related to changes in climate, although that sensitivity varies substantially from one census tract to another. In this investigation, we determine the empirical relationship between water consumption and variations in temperature and precipitation. We find the sensitivity of water consumption to either climate variable is positively related to the percent of land covered in mesic irrigated landscaping, mean household income, lot size, and percent of single-family residential lots containing swimming pools. We use estimated changes in temperature and precipitation for 50 model-scenario combinations presented by the IPCC, and we determined that mean water consumption should increase by an average of over 3% by ~2050, but the climate-induced change in consumption varies considerably across census tracts.     

Developing a GIS-Based Online Survey Instrument to Elicit Perceived Neighborhood Geographies to Address the Uncertain Geographic Context Problem

Although neighborhood factors have been consistently associated with health, technological difficulties in eliciting self-defined neighborhoods from large cohorts have compromised the interpretability of this research. Here, we offer a mixed-methods approach to elicit and validate self-defined neighborhoods. Participants used a customized Google.Maps interface to “draw” their neighborhood and answered questions about perceived map accuracy, neighborhood definition, and neighborhood activities. We compared geographic concordance of drawn and narrative neighborhood definitions, quantified differential accuracy by demographic characteristics, and examined factors influencing neighborhood definitions. We found similar geographic concordance between narrative and mapped boundaries in two cities, with no differences by neighborhood size. Self-reported neighborhoods had greater concordance with larger administrative areas (e.g., police precincts) than for smaller units (e.g., census tracts). To delineate their neighborhood boundaries, participants reported using administrative definitions, walking distance, their familiarity with people and structures, where they spend time, and physical landmarks. In New York City, participants also reported considering sociodemographic characteristics and transportation. Our method demonstrates the feasibility of collecting perceived (egocentric) neighborhoods through online mapping surveys, adaptable to many study settings.     

Localized income inequality, concentrated disadvantage and homicide

Several theories (e.g., routine activities, strain and social disorganization theories) suggest that there are effects of income inequality and concentrated disadvantage on crime. This study follows primarily the long line of social disorganization theorizing to explain the intraurban variation of homicide rates in Chicago. In addition to poverty, income inequality adds stress to individuals when they compare their situation to those around them. A localized income inequality (LII) index is implemented in a Geographic Information System (GIS) to measure the inequality between contiguous areas. Defining inequality in a localized context is important because geographic proximity permits close contacts between residents and thus reinforces the awareness of relative deprivation. This inequality index adds a new dimension to concentrated disadvantage in urban areas. The study shows that the new concentrated disadvantage measure is a strong predictor of homicide rates across three areal units of analysis in Chicago, i.e., census tracts, community areas and neighborhood clusters.     

Violence Change and Cohort Trajectories: Baltimore Neighborhoods, 1990-20001

Whereas the relationship between poverty and violence is incontrovertible in the American city, demographic relationships at the neighborhood level are relatively poorly understood. Patterns of violence and population change are examined at the census tract level in Baltimore, Maryland across the decade from 1990 to 2000. Aggravated assault and homicide are combined and used as a composite indicator of serious violence. Population data are examined for selected tracts representative of anomalous outliers experiencing population decline but increased violence. The data are broken down into five-year cohorts represented graphically at their beginning (1990) and end (2000) points. The analysis indicates that some neighborhoods have experienced collapse of youthful cohorts. Normally, a decline in youthful population would predict a reduction in crime, but this analysis suggests that at the neighborhood scale criminogenic processes may affect neighborhoods somewhat independently of their demographic attributes. Most notably, population decline at the neighborhood level may be accompanied by crime increase, contrary to macrolevel theoretical expectation.     

Reconsidering Race,Class, and Residential Segregation in American Cities

Scholars have often discounted social class as a substantial contributor to residential segregation by race, in part as a result of using the dissimilarity index, which is likely to show high levels of uneven group distribution regardless of socioeconomic status (SES), and in part as a result of using limited categories of SES. This study expands on prior research by examining residential segregation between black-alone and white-alone households in 36 metropolitan statistical areas (MSAs) with 2000 decennial census data, using both spatial unevenness (dissimilarity) and two types of experiential indicators (exposure indices), measuring SES across income levels and accounting for the presence of other races. Findings show that black households with higher incomes live in neighborhoods with greater exposure and lower isolation than do black households with lower incomes. Additionally, while the dissimilarity of black households decreases with income, unevenness is not as strongly connected to income as are the experiential measures. While race remains a primary determinant of residential segregation, results indicate substantial class differences.     

Ecological Modernization or Aristocratic Conservation? Exploring the Impact of Affluence on Carbon Emissions at the Local Level

Social scientists have debated how affluence impacts carbon emissions at the national level. We conduct an exploratory study at the subnational level to expose another dimension of the affluence–emissions debate. Based on the notion of aristocratic conservation, we hypothesize that affluence is positively related to carbon emissions from consumption activities but negatively related to emissions from production activities. We test these hypotheses using county-level data in the United States for the year 2002. A spatial regression analysis demonstrates that median household income is positively associated with consumption-based emissions; nevertheless, we find evidence of an environmental inequality Kuznets curve in the relationship between median household income and production-based emissions. This finding suggests that the wealthiest counties are able to displace certain types of emissions, specifically those related to energy and industrial production. We discuss the theoretical and political implications of these results.     

The residential segregation of San Antonio,Texas in 1910: an analysis of ethno-racial and occupational spatial patterns with the colocation quotient

The segregation of cities can be traced to a time when the compartmentalization of space and people was based on factors other than race. In segregation research, one of the limiting factors has always been the geographic scale of the data, and the limited knowledge that exists of segregation patterns when the household is the unit of analysis. Historical census data provides the opportunity to analyze the disaggregated information, and this paper does so with San Antonio during 1910. A spatial analysis of residential segregation based on race, ethnicity, and occupations is carried out with the colocation quotient to map and measure the attraction of residents. Results reveal the presence of residential segregation patterns on different sectors of the city based on households’ ethno-racial and occupational attributes; therefore, providing evidence of the existence of residential segregation prior to the commonly cited determinants of segregation of the 20th century.     

基于HLM和GWR的汪清县农村贫困成因探究

明确贫困成因是提高精准扶贫效率和稳定脱贫成效的基本前提。对偏远少数民族聚居区——吉林省汪清县农村贫困成因进行解析,采用多层线性模型(HLM)同时分析了家庭层次和环境层次因素对农村贫困家庭年纯收入的影响,并利用地理加权回归方法(GWR)探索了环境层次变量影响的空间异质性。研究结果显示： ① 汪清县贫困农户家庭层次因素对家庭年纯收入的影响强于环境层次因素,但环境层次因素的影响作用亦不可忽视; ② 剔除环境层次因素的影响后,绝大多数家庭层次因素对贫困家庭年纯收入存在显著影响; ③ 环境层次因素能够在不同程度上解释家庭层次因素影响效应的差异性; ④ 环境层次因素的影响在不同区域的作用方向和强度上存在显著差异。最后从村域发展环境、医疗就业、区域内部贫困差异方面提出改善建议。     

An Analysis of Environmental and Economic Impacts of Fossil Fuel Production in the U.S. from 2001 to 2015

The production and burning of fossil fuels is the primary contributor to CO₂ emissions for the U.S. We assess the impact of producing coal, crude oil, and natural gas on the environment and economic well-being by analyzing state-level data from 2001 to 2015. Our findings show that coal production has led to more CO₂ emissions and no significant benefit to economic well-being. Crude oil production has a non-significant impact on CO₂ emissions but is related to a lower poverty rate, a higher median household income, and a higher employment rate. Natural gas withdrawals have a positive impact on median household income. We discuss these findings in the context of current U.S. energy policies and then provide directions for future research.     

Measuring Concentrated Poverty in a Global Metropolis: Lessons from Los Angeles∗

The traditional definition of concentrated poverty—40 percent of a census tract population living below the federal poverty threshold—is problematic in light of burgeoning working poor populations, increasing inner-suburban poverty, and problems with the federal poverty threshold itself. This article questions the meaning of concentrated poverty as traditionally defined and measured through an analysis of social and built environments in selected Los Angeles area communities that meet the 40 percent threshold. Such neighborhoods face significant challenges, yet do not conform to stereotypes of concentrated poverty areas. Findings indicate the need for measures that recognize the increasingly heterogeneous forms and landscapes of poverty in globalizing urban regions.     

Assessing housing growth when census boundaries change

The US Census provides the primary source of spatially explicit social data, but changing block boundaries complicate analyses of housing growth over time. We compared procedures for reconciling housing density data between 1990 and 2000 census block boundaries in order to assess the sensitivity of analytical methods to estimates of housing growth in Oregon. Estimates of housing growth varied substantially and were sensitive to the method of interpolation. With no processing and areal‐weighted interpolation, more than 35% of the landscape changed; 75–80% of this change was due to decline in housing density. This decline was implausible, however, because housing structures generally persist over time. Based on aggregated boundaries, 11% of the landscape changed, but only 4% experienced a decline in housing density. Nevertheless, the housing density change map was almost twice as coarse spatially as the 2000 housing density data. We also applied a dasymetric approach to redistribute 1990 housing data into 2000 census boundaries under the assumption that the distribution of housing in 2000 reflected the same distribution as in 1990. The dasymetric approach resulted in conservative change estimates at a fine resolution. All methods involved some type of trade‐off (e.g. analytical difficulty, data resolution, magnitude or bias in direction of change). However, our dasymetric procedure is a novel approach for assessing housing growth over changing census boundaries that may be particularly useful because it accounts for the uniquely persistent nature of housing over time.     

广州市家庭收入与住房特征对应关系的区位差异性

以广州市中心区(天河区)和郊区(南沙区)为研究案例,依托2010年中国(广东)家庭动态跟踪调查数据,基于家庭户住房的邻里特征、建筑特征、区位特征、家庭收入等13个指标构建路径分析模型,研究广州市居民家庭收入与住房特征的映射关系和影响方向。在此基础上,采用多群组路径分析方法研究区位因素对“收入→住房特征”的影响程度及其差异性。最后利用方差方程和均值方程,分析不同区位条件下(中心区和郊区)的住房特征差异。结果表明：① 家庭收入更显著地决定住房特征,对邻里特征的影响并不显著;② 区位对“收入→住房邻里特征”的关系具有显著调节作用,而对“收入→住房建筑特征”的调节作用较弱;③ 在中心城区和郊区的内部,家庭收入更显著地影响住房建筑特征,而对邻里特征基本无显著影响;④ 郊区家庭收入对公共交通时间便利性、住房面积、厕所设施水平、拥有住房数量、住房综合条件等几个主要住房特征指标的影响程度大于中心城区;⑤ 中心城区住房的邻里特征明显优于郊区,但建筑特征明显差于郊区。显示出广州市住房邻里特征与建筑特征在不同区位条件下的“互换特征”。     

欠发达农区家庭贫困的动态转变分析——以河南省为例

精准扶贫战略实施以来,以收入标准衡量的农村贫困人口大幅下降,但贫困具有多维性、动态性的特点,开展农户贫困动态变化研究对新时期农村贫困的有效治理具有重要的指导意义。论文基于2010—2018年河南农村固定观察点数据,从收入、生活条件、教育3个维度构建农户多维贫困评价指标体系,并运用马尔科夫概率转移矩阵和面板Logit模型对贫困状态类型转移及家庭陷入贫困的影响因素进行实证分析。结果表明：① 多维贫困比单维贫困(尤其是收入贫困)更能准确反映农区贫困状况;② 2010—2018年间,单维贫困发生率与多维贫困发生率之间差距不断扩大,这很大程度与教育贫困发生率大幅上升,而生活条件贫困、收入教育贫困和三维贫困明显下降有关;③ 单维贫困家庭更易转入教育贫困,多维贫困家庭更容易转入教育生活条件贫困;④ 农户贫困的发生是户主特征、家庭特征和村庄特征共同作用的结果,但不同类型贫困发生的影响因素有显著差异。与单维贫困发生相比,多维贫困发生受到更少因素的显著影响,并且各影响因素的作用更大。上述结论意味着新时期扶贫工作重点转向多维贫困的同时,应依据贫困类型制定具体扶贫措施,尤其重视教育等公共服务的供给。     

Neighborhood Diversity and Segregation in the Chicago Metropolitan Region, 1980-2000

This article examines how neighborhood racial diversity shaped segregation in Chicago from 1980 to 2000, utilizing data from the 1980, 1990, and 2000 United States censuses. Three questions framed this research project. First, how racially diverse were Chicago neighborhoods? Second, which neighborhood factors were associated with racial diversity? And third, how has the change in neighborhood racial diversity changed patterns of segregation in Chicago? The Theil entropy score and the Theil H index were used to create racial diversity scores for each census tract and global segregation scores, respectively. Evidence is presented that supports the thesis that racial diversity in census tracts increased, which fostered a decline in overall segregation. However, new patterns of segregation are emerging between the Latino and black populations that are creating new spatial divisions within the city and suburbs.     

The Assassination of New York. Bob Fitch; From Redlining to Reinvestment: Community Responses to Urban Disinvestment. Gregory D. Squires,editor; At Road’s End Transportation and Land Use Choices for Communihs. Daniel Carlson et al.

This study disentangles the relationship between income and real estate value development in Dutch urban neighborhoods. Within the literature on upgrading and downgrading, it is often assumed that neighborhood income and real estate value development are strongly linked. The results reported here—based on research in Amsterdam, The Hague, and Tilburg—indicate that income and real estate values develop simultaneously in only a relatively small number of neighborhoods, which are at the top and bottom of the housing market hierarchy. The majority reveal a more complex relationship: a number of neighborhoods show a time lag between the trends, whereas in other neighborhoods income and real estate values show partially diverging trends. Several tentative explanations are offered for the complex relationship, and stress the importance of place-specific knowledge. Three points of attention are suggested for further research: understanding the role of household dynamics, the position of neighborhoods within their urban system, and the role of the state and housing associations in neighborhood change.