ABSTRACT

This paper presents a small-area index of the multifactorial phenomenon loosely referred to as gentrification, with application to New York City (NYC). The relative change of key input variables (median family income, median rent and proportions of non-Hispanic white, 20–34-year-olds and adults with a 4-year college degree) was computed from the years 2000 to 2016 for NYC census tracts that are spatially normalized to the year 2010. Raw scores derived from principal components analysis were then spatially smoothed through a fully Bayesian conditional autoregressive model, presenting an innovation over previous methods since it essentially blurs the otherwise artificial tract boundaries and results in a simulated posterior distribution of scores for each tract. The median and upper/lower percentiles provide a point estimate and assessment of uncertainty, respectively, of gentrification for each tract. The mapped index is visually consistent with the general understanding of gentrification in NYC, and the index is positively associated with census tract-level change in home values, as measured separately from a real property database. Although we developed this index as the quantitative part of a mixed methods approach to understanding gentrification in New York City, the methodology is intended to be applicable in other cities.

摘要

本文提出了一个多因素现象的小范围指数，该指数被松散地称为高档化，并适用于纽约市 (NYC)。纽约人口普查的关键输入变量（家庭收入中位数、租金中位数和非西班牙裔白人、20-34 岁和拥有 4 年大学学位的成年人的比例）的相对变化是从 2000 年到 2016 年计算的空间归一化到 2010 年的原始分数。然后通过完全贝叶斯条件自回归模型在空间上平滑从主成分分析得出的原始分数，与以前的方法相比具有创新性，因为它本质上模糊了其他人为的区域边界并导致模拟后验每个区域的分数分布。中位数和上/下百分位数分别提供了每个地区高档化的不确定性的点估计和评估。映射指数在视觉上与纽约市中产阶级化的一般理解一致，并且该指数与人口普查区级别的房屋价值变化呈正相关，与不动产数据库分开测量。尽管我们开发该指数作为了解纽约市高档化的混合​​方法的定量部分，但该方法旨在适用于其他城市。与不动产数据库分开测量。尽管我们开发该指数作为了解纽约市高档化的混合​​方法的定量部分，但该方法旨在适用于其他城市。与不动产数据库分开测量。尽管我们开发该指数作为了解纽约市高档化的混合​​方法的定量部分，但该方法旨在适用于其他城市。