Who Gentrifies Low Income Neighborhoods?
January 2008
Working Paper Number:
CES-08-02
Abstract
This paper uses confidential Census data, specifically the 1990 and 2000 Census Long- Form data, to study the demographic processes underlying the gentrification of low income urban neighborhoods during the 1990's. In contrast to previous studies, the analysis is conducted at the more refined census-tract level with a narrower definition of gentrification and more narrowly defined comparison neighborhoods. The analysis is also richly disaggregated by demographic characteristic, uncovering differential patterns by race, education, age and family structure that would not have emerged in the more aggregate analysis in previous studies. The results provide little evidence of displacement of low-income non-white households in gentrifying neighborhoods. The bulk of the income gains in gentrifying neighborhoods are attributed to white college graduates and black high school graduates. It is the disproportionate in-migration of the former and the disproportionate retention and income gains of the latter that appear to be the main engines of gentrification.
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.
:
minority,
ethnicity,
ethnic,
immigrant,
metropolitan,
rural,
population,
racial,
housing,
residential,
poverty,
neighborhood,
resident,
residence,
migrate,
migration,
migrating,
migrant
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.
:
Metropolitan Statistical Area,
Decennial Census,
Chicago Census Research Data Center,
Consolidated Metropolitan Statistical Areas,
PSID,
Public Use Micro Sample,
American Housing Survey,
Duke University
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 'Who Gentrifies Low Income Neighborhoods?' are listed below in order of similarity.
-
Working PaperWho Moves to Mixed-Income Neighborhoods?🔥
August 2010
Working Paper Number:
CES-10-18
This paper uses confidential Census data, specifically the 1990 and 2000 Census Long Form data, to study the income dispersion of recent cohorts of migrants to mixed-income neighborhoods. If recent in-migrants to mixed-income neighborhoods exhibit high levels of income heterogeneity, this is consistent with stable mixed-income neighborhoods. If, however, mixed-income neighborhoods are comprised of older homogeneous lower-income (higher income) cohorts combined with newer homogeneous higher-income (lower-income) cohorts, this is consistent with neighborhood transition. Our results indicate that neighborhoods with high levels of income dispersion do in fact attract a much more heterogeneous set of in-migrants, particularly from the tails of the income distribution, but that income heterogeneity does tend to erode over time. Our results also suggest that the residents of mixed-income neighborhoods may be less heterogeneous with respect to lifetime income.View Full Paper PDF
-
Working PaperHow Low Income Neighborhoods Change: Entry, Exit and Enhancement🔥
September 2010
Working Paper Number:
CES-10-19
This paper examines whether the economic gains experienced by low-income neighborhoods in the 1990s followed patterns of classic gentrification (as frequently assumed) ' that is, through the in migration of higher income white, households, and out migration (or displacement) of the original lower income, usually minority residents, spurring racial transition in the process. Using the internal Census version of the American Housing Survey, we find no evidence of heightened displacement, even among the most vulnerable, original residents. While the entrance of higher income households was an important source of income gains, original residents also experienced differential gains in income, and reported greater increases in their satisfaction with their neighborhood than found in other low-income neighborhoods. Finally, gaining neighborhoods were able to avoid the losses of white households that non-gaining low income tracts experienced, and were thereby more racially stable rather than less.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 PaperBlack Pioneers, Intermetropolitan Movers, and Housing Desegregation
March 2016
Working Paper Number:
CES-16-23
In this project, we examine the mobility choices of black households between 1960 and 2000. We use household-level Decennial Census data geocoded down to the census tract level. Our results indicate that, for black households, one's status as an intermetropolitan migrant ' especially from an urban area outside the South ' is a powerful predictor of pioneering into a white neighborhood. Moreover, and perhaps even more importantly, the ratio of these intermetropolitan black arrivals to the incumbent metropolitan black population is a powerful predictor of whether a metropolitan area experiences substantial declines in housing segregation.View Full Paper PDF
-
Working PaperImmigration and the Demand for Urban Housing
August 2021
Working Paper Number:
CES-21-23
The immigrant population has grown dramatically in the US in the last fifty years. This study estimates housing demand among immigrants and discusses how immigration may be altering the structure of US urban areas. Immigrants are found to consume less housing per capita than native born US residents.View Full Paper PDF
-
Working PaperHas Falling Crime Invited Gentrification?
January 2017
Working Paper Number:
CES-17-27
Over the past two decades, crime has fallen dramatically in cities in the United States. We explore whether, in the face of falling central city crime rates, households with more resources and options were more likely to move into central cities overall and more particularly into low income and/or majority minority central city neighborhoods. We use confidential, geocoded versions of the 1990 and 2000 Decennial Census and the 2010, 2011, and 2012 American Community Survey to track moves to different neighborhoods in 244 Core Based Statistical Areas (CBSAs) and their largest central cities. Our dataset includes over four million household moves across the three time periods. We focus on three household types typically considered gentrifiers: high-income, college-educated, and white households. We find that declines in city crime are associated with increases in the probability that highincome and college-educated households choose to move into central city neighborhoods, including low-income and majority minority central city neighborhoods. Moreover, we find little evidence that households with lower incomes and without college degrees are more likely to move to cities when violent crime falls. These results hold during the 1990s as well as the 2000s and for the 100 largest metropolitan areas, where crime declines were greatest. There is weaker evidence that white households are disproportionately drawn to cities as crime falls in the 100 largest metropolitan areas from 2000 to 2010.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 PaperMobility, Opportunity, and Volatility Statistics (MOVS): Infrastructure Files and Public Use Data
April 2024
Working Paper Number:
CES-24-23
Federal statistical agencies and policymakers have identified a need for integrated systems of household and personal income statistics. This interest marks a recognition that aggregated measures of income, such as GDP or average income growth, tell an incomplete story that may conceal large gaps in well-being between different types of individuals and families. Until recently, longitudinal income data that are rich enough to calculate detailed income statistics and include demographic characteristics, such as race and ethnicity, have not been available. The Mobility, Opportunity, and Volatility Statistics project (MOVS) fills this gap in comprehensive income statistics. Using linked demographic and tax records on the population of U.S. working-age adults, the MOVS project defines households and calculates household income, applying an equivalence scale to create a personal income concept, and then traces the progress of individuals' incomes over time. We then output a set of intermediate statistics by race-ethnicity group, sex, year, base-year state of residence, and base-year income decile. We select the intermediate statistics most useful in developing more complex intragenerational income mobility measures, such as transition matrices, income growth curves, and variance-based volatility statistics. We provide these intermediate statistics as part of a publicly released data tool with downloadable flat files and accompanying documentation. This paper describes the data build process and the output files, including a brief analysis highlighting the structure and content of our main statistics.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 PaperYou Can Take it With You: Proposition 13 Tax Benefits, Residential Mobility, and Willingness to Pay for Housing Amenities
June 2008
Working Paper Number:
CES-08-15
The endogeneity of prices has long been recognized as the main identification problem in the estimation of marginal willingness to pay (MWTP) for the characteristics of a given product. This issue is particularly important when estimating MWTP in the housing market, since a number of housing and neighborhood features are unobserved by the econometrician. This paper proposes the use of a well defined type of transaction costs ' moving costs generated by property tax laws - to deal with this type of omitted variable bias. California's Proposition 13 property tax law is the source of variation in transaction costs used in the empirical analysis. Beyond its fiscal consequences, Proposition 13 created a lock-in effect on housing choice because of the implicit tax break enjoyed by homeowners living in the same house for a long time. First, I provide estimates of this lock-in effect using a natural experiment created by two subsequent amendments to Proposition 13 - Propositions 60 and 90. These amendments allow households headed by an individual over the age of 55 to transfer the implicit tax benefit to a new home. I show that mobility rates of 55-year old homeowners are approximately 25% higher than those of 54 year olds. Second, all these features of the tax law are then incorporated into a household sorting model. The key insight of this model is that because of the property tax law, different potential buyers have different user costs for the same house. The exogenous property tax component of this user cost then works as an instrument for prices. I find that MWTP estimates for housing characteristics are approximately 100% upward biased when the model does not account for the price endogeneity.View Full Paper PDF
