Residential Mobility, Neighborhood Change, and Income Segregation

这项研究将提高对2000年后大都市地区收入隔离趋势的认识。第一个目标是更准确地衡量过去十年中按收入划分的居住隔离是如何演变的。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？都与每个家庭的结果有关。什么样的人在不断变化的社区中进入、离开和停留？它们从哪里来，又往哪里去？这对他们的福利意味着什么？社区的变化、富裕家庭和不富裕家庭之间不断变化的分离形式，以及少数民族能否进入更好的社区，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着重大影响。本研究分析了2000年以来收入隔离的趋势，从两个方面探讨了这些趋势。第一个问题是，美国社区调查（ACS）的样本量减少对种族隔离措施有何影响。学者们现在依靠ACS来获取人口普查区层面的数据。我们有充分的理由相信，随着样本量的减少，直接测量方法的偏差会上升，因此，即使没有真正的变化，结果也可能显示出日益加剧的隔离。该项目将对联邦研究数据中心的原始样本数据应用新的方法来纠正样本偏差。使用机密数据改善了公布数据的其他方法限制，包括：1)在少数民族居民数量较少的地区按种族/民族压制数据；2)收入分配的最高编码。第二个问题是，社区收入构成的变化是如何通过居民流动模式产生的。该项目将利用2000年和2010年人口普查和2008-2012年人口普查的原始记录，这些记录可以随着时间的推移而联系起来。这项研究将选择经历了中产阶级化的社区，变得更穷的贫困社区，以及变得更排外的富裕社区。在每种类型的社区中，可以确定2000年至2010年留下的居民，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（流动性）行为如何累积到宏观层面（邻里）结果提供新的见解，这是社会科学中一个持久的问题。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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.