DYNAMIC ANALYSIS OF ECONOMIC WELL BEING AT OLDER AGES

这是一个竞争性的继续申请研究支持， 原项目的第一个项目。它建议回答问题 特别强调老年人的经济福祉， 年纪大的女人本提案将同时使用横截面和纵向 衡量老年退休人员和老年人经济福祉的数据 工人相对于其他人口，无论是在美国， 并与西方两个现代工业化国家-- 德国联邦共和国和联合王国-确定如何 弱势老年群体在过去25年中的绝对和 相对于人口中的其他人。 从方法论上讲，我们将认识到老年人内部的多样性， 在人口和各年龄组中， 他们的经济福利--平均收入，中等收入，五分位数， 基尼系数等-我们将利用新一代的 非参数不等式度量方法-核密度估计 来展示整个收入分配的形态以及它是如何变化的 随着时间当我们开始使用横截面数据进行分析时， 集中注意收入分配的动态， 个体随时间的变化，并跟踪它们在分布中的移动。 我们最终将检验重大事件--统一 德国和美国20世纪80年代的十年-对应 随着整体收入分配和地位的制度变化， 老年人和弱势群体的比例。

This is a competing continuation application for research support for project 1 of the original program project. It proposes to answer questions about the economic well-being of older persons with a special emphasis on older women. This proposal will use both cross-sectional and longitudinal data to measure economic well-being of older retired people and older workers relative to the rest of the population, both in the United States and in comparison with two modem western industrialized countries-the Federal Republic of Germany and the United Kingdom-to determine how vulnerable older groups fared over the past 25 years both absolutely and relative to others in the population. Methodologically, we will recognize the diversity both within the older population and across age groups by moving beyond summary measures of their economic well-being-mean income, median income, quintile position, Gini coefficient, etc.-and we will take advantage of a new generation of nonparametric techniques to measure inequality-kernel density estimation to show the shape of the entire income distribution and how it has changed over time. While we begin our analysis using cross-sectional data we will concentrate on the dynamics of income distribution by following individuals over time and tracing their movements across the distribution. And we will eventually test whether or not major events-the reunification of Germany and the decade of the l980s in the United States-correspond with regime changes in the overall income distribution and in the position of older and vulnerable groups within that distribution.