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.
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Improving Estimates of Neighborhood Change with Constant Tract Boundaries
May 2022
Working Paper Number:
CES-22-16
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.
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WHITE-LATINO RESIDENTIAL ATTAINMENTS AND SEGREGATION
IN SIX CITIES: ASSESSING THE ROLE OF MICRO-LEVEL FACTORS
January 2016
Working Paper Number:
CES-16-51
This study examines the residential outcomes of Latinos in major metropolitan areas using new methods to connect micro-level analyses of residential attainments to overall patterns of segregation in the metropolitan area. Drawing on new formulations of standard measures of evenness, we conduct micro-level multivariate analyses using the restricted-use census microdata files to predict segregation-relevant neighborhood outcomes for individuals by race. We term the dependent variables segregation-relevant neighborhood outcomes because the differences in average outcomes for each group on these variables determine the values of the aggregate measures of evenness. This approach allows me to use standardization and components analysis to quantitatively assess the separate contributions that differences in social characteristics and differences in rates of return make towards determining the overall disparity in residential outcomes ' that is, the level of segregation ' between Whites and Latinos. Based on our micro-level residential attainment analyses we find that for Latinos, acculturation and gains in socioeconomic status are associated with greater residential contact with Whites, in agreement with spatial assimilation theory, which promotes lower segregation. However, our standardization and components analyses reveals that a substantial portion of White-Latino disparities in residential contact with Whites can be attributed to differences in rates of return; that is White-Latino differences in the ability to translate acculturation and gains in socioeconomic status into more residential contact with Whites. This is further elaborated upon by assessing the changes in contact with Whites for Whites and Latinos after manipulating single variables while holding all others constant. This can be interpreted as the role of discrimination which is emphasized by place stratification theory. Therefore we conclude that while members of minority groups make gains in residential outcomes that reduce segregation by attaining parity with Whites on social characteristics as spatial assimilation theory would predict, a substantial disparity will persist as Latinos cannot translate those gains into greater contact with Whites at the rate that Whites can. At the aggregate level of analysis, this means that White-Latino segregation remains substantial even when groups are equalized on social and economic characteristics.
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Metropolitan 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.
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Resident Perceptions of Crime: How Similar are They to Official Crime Rates?
March 2007
Working Paper Number:
CES-07-10
This study compares the relationship between official crime rates and residents' perceptions of crime in census tracts. Employing a unique dataset that links household level data from the American Housing Survey metro samples over a period of 25 years (1976-2000) with official crime rate data for census tracts in selected cities during selected years, this large sample provides considerable ability to generalize the findings. I find that residents' perception of crime is most strongly related to official rates of tract violent crime. Models simultaneously taking into account both violent and property crime consistently found that property crime actually has a negative effect on perceived crime. Among types of violent crime, the robbery rate is consistently related to higher levels of perceived crime in the tract, whereas it appears a structural shift occurred in the mid-1980s in which aggravated assault and murder rates now impact perceptions of crime, even when taking into account the robbery rate.
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Associations Between Public Housing and Individual Earnings in New Orleans
October 2015
Working Paper Number:
CES-15-32
This study uses a sample of the civilian labor force aged 16-64 constructed from the Decennial Census and American Community Survey, along with data from the HUD dataset Picture of Subsidized Households, to compare the likelihood for job earnings in relation to public housing developments in the New Orleans MSA before and after Hurricane Katrina. Results from a series of hierarchical linear models (HLM) indicate significant relationships are altered between time periods, including those from public and mixed-income developments, suggesting a fluid relationship between neighborhoods and economic outcomes during physical, demographic and economic restructuring.
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Structural 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.
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Whose Neighborhood Now? Gentrification and Community Life in Low-Income Urban Neighborhoods
June 2024
Working Paper Number:
CES-24-29
Gentrification is a process of urban change that has wide-ranging social and political impacts, but previous studies provide divergent findings. Does gentrification leave residents feeling alienated, or does it bolster neighborhood social satisfaction? Politically, does urban change mobilize residents, or leave them disengaged? I assess a national, cross-sectional sample of about 17,500 respondents in lower-income urban neighborhoods, and use a structural equation modeling approach to model six latent variables pertaining to local social environment and political participation. Amongst the full sample, gentrification has a positive association with all six factors. However, this relationship depends upon respondents' level of income, length of residency, and racial identity. White residents and those with shorter length of residency report higher levels of social cohesion as gentrification increases, but there is no such association amongst racial minority groups and longer-term residents. This finding aligns with a perspective on gentrification as a racialized process, and demonstrates that gentrification-related amenities primarily serve the interests of white residents and newcomers. All groups, however, are more likely to participate in neighborhood politics as gentrification increases, drawing attention to the agency of local residents as they attempt to influence processes of urban change.
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Location, Location, Location: The 3L Approach to House Price Determination
May 2004
Working Paper Number:
CES-04-06
The immobility of houses means that their location affects their values. This explains the common belief that three things determine the price of a house: location, location, and location. We use this notion to develop the 3L Approach to house price determination. That is, prices are determined by the Metropolitan Statistical Area (MSA), town, and street where the house is located. This study creates a unique data set based on data from the American Housing Survey (AHS) consisting of small 'clusters' of housing units with information on their housing characteristics and resident characteristics that is merged with census tract-level attributes. We use this data to verify the 3L Approach: we find that all three levels of location are significant when estimating the house price hedonic equation. This indicates that individuals care about their local neighborhood, i.e. the general upkeep of their street and possibly their neighbors' characteristics (cluster variables), a broader area such as the school district and/or the town (tract variables) that account for school quality and crime rates, and the particular amenities found in their MSA.
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When and Why Does Nonresponse Occur? Comparing the Determinants of Initial Unit Nonresponse and Panel Attrition
September 2023
Working Paper Number:
CES-23-44
Though unit nonresponse threatens data quality in both cross-sectional and panel surveys, little is understood about how initial nonresponse and later panel attrition may be theoretically or empirically distinct phenomena. This study advances current knowledge of the determinants of both unit nonresponse and panel attrition within the context of the U.S. Census Bureau's Survey of Income and Program Participation (SIPP) panel survey, which I link with high-quality federal administrative records, paradata, and geographic data. By exploiting the SIPP's interpenetrated sampling design and relying on cross-classified random effects modeling, this study quantifies the relative effects of sample household, interviewer, and place characteristics on baseline nonresponse and later attrition, addressing a critical gap in the literature. Given the reliance on successful record linkages between survey sample households and federal administrative data in the nonresponse research, this study also undertakes an explicitly spatial analysis of the place-based characteristics associated with successful record linkages in the U.S.
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Examining Racial Identity Responses Among People with Middle Eastern and North African Ancestry in the American Community Survey
March 2024
Working Paper Number:
CES-24-14
People with Middle Eastern and North African (MENA) backgrounds living in the United States are defined and classified as White by current Federal standards for race and ethnicity, yet many MENA people do not identify as White in surveys, such as those conducted by the U.S. Census Bureau. Instead, they often select 'Some Other Race', if it is provided, and write in MENA responses such as Arab, Iranian, or Middle Eastern. In processing survey data for public release, the Census Bureau classifies these responses as White in accordance with Federal guidance set by the U.S. Office of Management and Budget. Research that uses these edited public data relies on limited information on MENA people's racial identification. To address this limitation, we obtained unedited race responses in the nationally representative American Community Survey from 2005-2019 to better understand how people of MENA ancestry report their race. We also use these data to compare the demographic, cultural, socioeconomic, and contextual characteristics of MENA individuals who identify as White versus those who do not identify as White. We find that one in four MENA people do not select White alone as their racial identity, despite official guidance that defines 'White' as people having origins in any of the original peoples of Europe, the Middle East, or North Africa. A variety of individual and contextual factors are associated with this choice, and some of these factors operate differently for U.S.-born and foreign-born MENA people living in the United States.
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