Improving Estimates of Neighborhood Change with Constant Tract Boundaries
May 2022
Working Paper Number:
CES-22-16
Abstract
Social scientists routinely rely on methods of interpolation to adjust available data to their research needs. This study calls attention to the potential for substantial error in efforts to harmonize data to constant boundaries using standard approaches to areal and population interpolation. We compare estimates from a standard source (the Longitudinal Tract Data Base) to true values calculated by re-aggregating original 2000 census microdata to 2010 tract areas. We then demonstrate an alternative approach that allows the re-aggregated values to be publicly disclosed, using 'differential privacy' (DP) methods to inject random noise to protect confidentiality of the raw data. The DP estimates are considerably more accurate than the interpolated estimates. We also examine conditions under which interpolation is more susceptible to error. This study reveals cause for greater caution in the use of interpolated estimates from any source. Until and unless DP estimates can be publicly disclosed for a wide range of variables and years, research on neighborhood change should routinely examine data for signs of estimation error that may be substantial in a large share of tracts that experienced complex boundary changes.
Document Tags and Keywords
Keywords
Keywords are automatically generated using KeyBERT, a powerful and innovative
keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant
keywords.
By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the
text, highlighting the most significant topics and trends. This approach not only enhances searchability but
provides connections that go beyond potentially domain-specific author-defined keywords.
:
estimation,
estimating,
data,
statistical,
data census,
census data,
microdata,
respondent,
confidentiality,
estimator,
regression,
privacy,
unobserved,
socioeconomic,
neighborhood,
use census,
resident,
disparity,
2010 census,
census records
Tags
Tags are automatically generated using a pretrained language model from spaCy, which excels at
several tasks, including entity tagging.
The model is able to label words and phrases by part-of-speech,
including "organizations." By filtering for frequent words and phrases labeled as "organizations", papers are
identified to contain references to specific institutions, datasets, and other organizations.
:
Urban Institute,
Research Data Center,
Geographic Information Systems,
American Community Survey,
National Institutes of Health,
Census Bureau Disclosure Review Board,
2010 Census,
Federal Statistical Research Data Center
Similar Working Papers
Similarity between working papers are determined by an unsupervised neural
network model
know as Doc2Vec.
Doc2Vec is a model that represents entire documents as fixed-length vectors, allowing for the
capture of semantic meaning in a way that relates to the context of words within the document. The model learns to
associate a unique vector with each document while simultaneously learning word vectors, enabling tasks such as
document classification, clustering, and similarity detection by preserving the order and structure of words. The
document vectors are compared using cosine similarity/distance to determine the most similar working papers.
Papers identified with 🔥 are in the top 20% of similarity.
The 10 most similar working papers to the working paper 'Improving Estimates of Neighborhood Change with Constant Tract Boundaries' are listed below in order of similarity.
-
Working PaperSYNTHETIC DATA FOR SMALL AREA ESTIMATION IN THE AMERICAN COMMUNITY SURVEY
April 2013
Working Paper Number:
CES-13-19
Small area estimates provide a critical source of information used to study local populations. Statistical agencies regularly collect data from small areas but are prevented from releasing detailed geographical identifiers in public-use data sets due to disclosure concerns. Alternative data dissemination methods used in practice include releasing summary/aggregate tables, suppressing detailed geographic information in public-use data sets, and accessing restricted data via Research Data Centers. This research examines an alternative method for disseminating microdata that contains more geographical details than are currently being released in public-use data files. Specifically, the method replaces the observed survey values with imputed, or synthetic, values simulated from a hierarchical Bayesian model. Confidentiality protection is enhanced because no actual values are released. The method is demonstrated using restricted data from the 2005-2009 American Community Survey. The analytic validity of the synthetic data is assessed by comparing small area estimates obtained from the synthetic data with those obtained from the observed data.View Full Paper PDF
-
Working PaperWho are the people in my neighborhood? The 'contextual fallacy' of measuring individual context with census geographies
February 2018
Working Paper Number:
CES-18-11
Scholars deploy census-based measures of neighborhood context throughout the social sciences and epidemiology. Decades of research confirm that variation in how individuals are aggregated into geographic units to create variables that control for social, economic or political contexts can dramatically alter analyses. While most researchers are aware of the problem, they have lacked the tools to determine its magnitude in the literature and in their own projects. By using confidential access to the complete 2010 U.S. Decennial Census, we are able to construct'for all persons in the US'individual-specific contexts, which we group according to the Census-assigned block, block group, and tract. We compare these individual-specific measures to the published statistics at each scale, and we then determine the magnitude of variation in context for an individual with respect to the published measures using a simple statistic, the standard deviation of individual context (SDIC). For three key measures (percent Black, percent Hispanic, and Entropy'a measure of ethno-racial diversity), we find that block-level Census statistics frequently do not capture the actual context of individuals within them. More problematic, we uncover systematic spatial patterns in the contextual variables at all three scales. Finally, we show that within-unit variation is greater in some parts of the country than in others. We publish county-level estimates of the SDIC statistics that enable scholars to assess whether mis-specification in context variables is likely to alter analytic findings when measured at any of the three common Census units.View Full Paper PDF
-
Working PaperDisclosure Avoidance Techniques Used for the 1970 through 2010 Decennial Censuses of Population and Housing
November 2018
Working Paper Number:
CES-18-47
The U.S. Census Bureau conducts the decennial censuses under Title 13 of the U. S. Code with the Section 9 mandate to not 'use the information furnished under the provisions of this title for any purpose other than the statistical purposes for which it is supplied; or make any publication whereby the data furnished by any particular establishment or individual under this title can be identified; or permit anyone other than the sworn officers and employees of the Department or bureau or agency thereof to examine the individual reports (13 U.S.C. ' 9 (2007)).' The Census Bureau applies disclosure avoidance techniques to its publicly released statistical products in order to protect the confidentiality of its respondents and their data.View Full Paper PDF
-
Working PaperChanges in Neighborhood Inequality, 2000-2010
March 2016
Working Paper Number:
CES-16-18
Recent work has suggested that higher income inequality may be a desirable attribute of a neighborhood in that it represents diversity, even though high (and rising) inequality appears to be detrimental to the nation as a whole. The research reported here has determined the key characteristics of a census tract that are associated with the level of inequality in 2000 or 2010, and those associated with changes in income inequality between 2000 and 2010. For the change, the strongest influence is a negative effect for the level of income inequality in 2000; that is, higher income inequality in 2000 leads to a decline over the decade, ceteris paribus. Neighborhoods with higher proportions or levels of the following population and housing characteristics tend to have both higher income inequality and a larger increase in income inequality between 2000 and 2010: individuals in poverty, those with a bachelor's degree, older individuals, householders living alone, and median rent, and lower median housing value and household income. Among these, perhaps the most important determinant is the percent in poverty in 2000. Furthermore, as the baseline level of demographic and economic diversity increases, the better the baseline and change characteristics explain the change in the Gini index from 2000 to 2010.View Full Paper PDF
-
Working PaperThe Effect of Low-Income Housing on Neighborhood Mobility: Evidence from Linked Micro-Data
May 2016
Working Paper Number:
carra-2016-02
While subsidized low-income housing construction provides affordable living conditions for poor households, many observers worry that building low-income housing in poor communities induces individuals to move to poor neighborhoods. We examine this issue using detailed, nationally representative microdata constructed from linked decennial censuses. Our analysis exploits exogenous variation in low-income housing supply induced by program eligibility rules for Low-Income Housing Tax Credits to estimate the effect of subsidized housing on neighborhood mobility patterns. The results indicate little evidence to suggest a causal effect of additional low-income housing construction on the characteristics of neighborhoods to which households move. This result is true for households across the income distribution, and supports the hypothesis that subsidized housing provides affordable living conditions without encouraging households to move to less-affluent neighborhoods than they would have otherwise.View Full Paper PDF
-
Working PaperStructural versus Ethnic Dimensions of Housing Segregation
March 2016
Working Paper Number:
CES-16-22
Racial residential segregation is still very high in many American cities. Some portion of segregation is attributable to socioeconomic differences across racial lines; some portion is caused by purely racial factors, such as preferences about the racial composition of one's neighborhood or discrimination in the housing market. Social scientists have had great difficulty disaggregating segregation into a portion that can be explained by interracial differences in socioeconomic characteristics (what we call structural factors) versus a portion attributable to racial and ethnic factors. What would such a measure look like? In this paper, we draw on a new source of data to develop an innovative structural segregation measure that shows the amount of segregation that would remain if we could assign households to housing units based only on non-racial socioeconomic characteristics. This inquiry provides vital building blocks for the broader enterprise of understanding and remedying housing segregation.View Full Paper PDF
-
Working PaperThe Privacy-Protected Gridded Environmental Impacts Frame
December 2024
Working Paper Number:
CES-24-74
This paper introduces the Gridded Environmental Impacts Frame (Gridded EIF), a novel privacy-protected dataset derived from the U.S. Census Bureau's confidential Environmental Impacts Frame (EIF) microdata infrastructure. The EIF combines comprehensive administrative records and survey data on the U.S. population with high-resolution geospatial information on environmental hazards. While access to the EIF is restricted due to the confidential nature of the underlying data, the Gridded EIF offers a broader research community the opportunity to glean insights from the data while preserving confidentiality. We describe the data and privacy protection process, and offer guidance on appropriate usage, presenting practical applications.View Full Paper PDF
-
Working PaperComparing the 2019 American Housing Survey to Contemporary Sources of Property Tax Records: Implications for Survey Efficiency and Quality
June 2022
Working Paper Number:
CES-22-22
Given rising nonresponse rates and concerns about respondent burden, government statistical agencies have been exploring ways to supplement household survey data collection with administrative records and other sources of third-party data. This paper evaluates the potential of property tax assessment records to improve housing surveys by comparing these records to responses from the 2019 American Housing Survey. Leveraging the U.S. Census Bureau's linkage infrastructure, we compute the fraction of AHS housing units that could be matched to a unique property parcel (coverage rate), as well as the extent to which survey and property tax data contain the same information (agreement rate). We analyze heterogeneity in coverage and agreement across states, housing characteristics, and 11 AHS items of interest to housing researchers. Our results suggest that partial replacement of AHS data with property data, targeted toward certain survey items or single-family detached homes, could reduce respondent burden without altering data quality. Further research into partial-replacement designs is needed and should proceed on an item-by-item basis. Our work can guide this research as well as those who wish to conduct independent research with property tax records that is representative of the U.S. housing stock.View Full Paper PDF
-
Working PaperEffects of a Government-Academic Partnership: Has the NSF-Census Bureau Research Network Helped Improve the U.S. Statistical System?
January 2017
Working Paper Number:
CES-17-59R
The National Science Foundation-Census Bureau Research Network (NCRN) was established in 2011 to create interdisciplinary research nodes on methodological questions of interest and significance to the broader research community and to the Federal Statistical System (FSS), particularly the Census Bureau. The activities to date have covered both fundamental and applied statistical research and have focused at least in part on the training of current and future generations of researchers in skills of relevance to surveys and alternative measurement of economic units, households, and persons. This paper discusses some of the key research findings of the eight nodes, organized into six topics: (1) Improving census and survey data collection methods; (2) Using alternative sources of data; (3) Protecting privacy and confidentiality by improving disclosure avoidance; (4) Using spatial and spatio-temporal statistical modeling to improve estimates; (5) Assessing data cost and quality tradeoffs; and (6) Combining information from multiple sources. It also reports on collaborations across nodes and with federal agencies, new software developed, and educational activities and outcomes. The paper concludes with an evaluation of the ability of the FSS to apply the NCRN's research outcomes and suggests some next steps, as well as the implications of this research-network model for future federal government renewal initiatives.View Full Paper PDF
-
Working PaperMetropolitan Segregation: No Breakthrough in Sight
May 2022
Working Paper Number:
CES-22-14
The 2020 Census offers new information on changes in residential segregation in metropolitan regions across the country as they continue to become more diverse. We take a long view, assessing trends since 1980 and extrapolating to the future. These new data mostly reinforce patterns that were observed a decade ago: high but slowly declining black-white segregation, and less intense but hardly changing segregation of Hispanics and Asians from whites. Enough time has passed since the civil rights era of the 1960s and 1970s to draw this conclusion: segregation will continue to divide Americans well into the 21st Century.View Full Paper PDF
