Between 1970 and 1990, a surging Hispanic population succeeded whites across New York City, resulting in major increases in both all-minority and multiethnic neighborhoods. Puerto Rican and Dominican flows resulted in transitions to all-minority neighborhoods, whereas South Americans showed a more integrated pattern of settlement. The unique settlement patterns of Hispanic subgroups need to be understood in the context of larger political, social, and economic forces operating in the city. In the post-1990 period, newer Hispanic groups have begun to succeed Puerto Ricans. Thus, earlier patterns of white to Hispanic transitions now have been supplemented by ethnic succession among Hispanics.The ebb and flow of migrants, both domestic and international, have for centuries shaped and reshaped the character of New York City. From its earliest days when the Dutch and English struggled for political and economic control, through the nineteenth century when new groups such as Germans and the Irish settled in great numbers, and up through the early twentieth century with the arrival of southern and eastern Europeans, the city has always been an ever-evolving mix of ethnic groups (Binder and Reimers 1995).

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In this article, we chronicle the U.S. Census Bureau's development of the Disclosure Avoidance System (DAS) for the publicly released products of the 2020 Census of Population. We provide a brief history of the Census Bureau's fulfillment of its dual mission of conducting and disseminating the constitutionally mandated decennial information on the U.S. population and its promise of safeguarding the confidentiality of that information. We discuss the basis for and development of a new DAS for released data products from the 2020 Census and the evidence that emerged from various user communities on the accuracy and usability of data produced under this new DAS. We offer some assessments of this experience, the dilemmas and challenges that the Census Bureau faces for producing usable data while safeguarding the confidentiality of the information it collects, and some recommendations for addressing these challenges in the future.

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The American Community Survey (ACS) is a continuous measurement survey program designed to replace the census long form sample. While the census sample provides detailed socioeconomic data once a decade, the ACS will provide these data annually using a questionnaire that largely mirrors the census long form. This paper examines operational data in Bronx County, one of 36 ACS test counties, and finds the ACS superior to the census on two important measures of data quality. First, applying the minimal data requirement for inclusion of a long form in the census sample, ACS questionnaires were significantly more likely than the long forms to meet this threshold. Second, the level of nonresponse to items on the ACS was often one-half the census level.The ACS and census have sharply divergent goals and operational methods that affect data quality. The primary objective of the census is a population count for reapportionment and redistricting; collecting long form information is a secondary goal. In contrast, the primary objective of the ACS is to estimate the characteristics of an area based on answers to all items on the survey. Operationally, the census follows up every nonresponding household, using a pool of minimally trained, temporary workers. In comparison, the ACS follows up only one-in-three nonresponding households, using a permanent cadre of professional interviewers. This results in superior nonresponse follow-up in the ACS, with lower levels of non-sampling error, even in more difficult-to-enumerate high poverty areas of the Bronx.The ACS is to be fully implemented in July 2004, pending Congressional funding. With detailed socioeconomic data available annually from the ACS, the 2010 census would then be able to focus primarily on a population headcount. The paper concludes by discussing operational aspects of the ACS that must be improved, including increasing its visibility, for the survey to be accepted as an integral part of the nation's data collection system.