Residential Mobility, Neighborhood Change, and Income Segregation

这项研究将增进对2000年后大都市地区收入隔离趋势的了解。第一个目标是更准确地衡量住房收入隔离在过去十年中的演变。第二个目标是分析社区收入构成的变化？比如正在士绅化或变得更加贫困的社区？与个别家庭的结果密切相关。什么样的人进入、离开和停留在改变的社区？他们从哪里来，他们去哪里？这对他们的福利有什么影响？社区变化、较富裕家庭和较不富裕家庭之间分离形式的改变以及少数人获得更好社区的机会，对与住房不平等、经济适用房和学校差异相关的城市发展有很大影响。这项研究分析了自2000年以来收入分离的趋势，解决了这些趋势的两个方面。第一个问题是，美国社区调查(ACS)中样本数量的减少如何影响了种族隔离的衡量标准，学者们现在依靠该调查获得人口普查区域层面的数据。有充分的理由相信，随着样本量的减少，直接指标会偏向上行，因此，即使没有真正的变化，结果也可能显示出日益严重的隔离。该项目将在联邦研究数据中心对原始样本数据应用新的样本偏差校正方法。使用机密数据改善了已公布数据中的其他方法限制，包括：1)在少数族裔居民较少的地区按种族/族裔压制数据；2)对收入分配进行顶层编码。第二个问题是，社区的收入构成是如何通过居民流动模式产生变化的。该项目将利用2000年和2010年人口普查的原始记录，以及可以随着时间的推移联系在一起的2008-2012年ACS。这项研究将选择经历了士绅化的社区，变得更加贫穷的贫困社区，以及变得更加排外的富裕社区。在每种类型的社区中，都可以确定从2000年到2010年留下来的居民、离开的居民和进入的居民的数量和特征。这项研究将为个人层面(流动)行为如何聚集到宏观层面(邻里)结果提供新的见解，这是社会科学中的一个持久问题。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This study will improve knowledge of trends in income segregation in metropolitan regions in the post-2000 period. The first goal is to measure more accurately how residential segregation by income has evolved in the last decade. The second goal is to analyze how changes in the income composition of neighborhoods ? such as neighborhoods that are gentrifying or becoming more impoverished ? are tied to outcomes for individual families. What kinds of people are entering, leaving, and staying in changing neighborhoods? Where do they come from and where do they go? What are the implications for their welfare? Neighborhood changes, changing forms of separation between more affluent and less affluent families, and minority access to better neighborhoods have a strong bearing on urban development related to housing inequality, affordable housing, and school disparities.This study analyzes trends in income segregation since 2000, addressing two aspects of these trends. The first question is how measures of segregation are affected by the reduction in sample sizes in the American Community Survey (ACS), which scholars now rely on for data at the census tract level. There is good reason to believe that direct measures are biased upwards as sample sizes decline, so that results may show increasing segregation even if there has been no real change. The project will apply new methods of correcting for sample bias to the original sample data in a federal Research Data Center. Working with confidential data ameliorates other methodological limitations in published data including: 1) the suppression of data by race/ethnicity in tracts with small numbers of minority residents and 2) top-coding of the income distribution. The second question is how changes in the income composition of neighborhoods are produced through patterns of residential mobility. The project will make use of the original records from Census 2000 and 2010 and the 2008-2012 ACS that can be linked over time. The study will select neighborhoods that have experienced gentrification, poor neighborhoods that have become poorer, and affluent neighborhoods that have become more exclusive. In each type of neighborhood, it is possible to identify the number and characteristics of residents who remain from 2000 to 2010, who leave, and who enter. This research will offer new insight into how individual-level (mobility) behaviors aggregate to macro-level (neighborhood) outcomes, which is an enduring issue in social science.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.