What Has Been Capitalized into Property Values: Human Capital, Social Capital, or Cultural Capital?
October 2005
Working Paper Number:
CES-05-25
Abstract
Urban amenities can be capitalized into land values or property values. However, little attention has been paid to the capitalization of social amenities. This paper classifies three types of social-interaction-based social amenities: human capital, social capital, and cultural capital at residential neighborhood levels. We use the restricted version of the 1990 Massachusetts Census data and estimate hedonic housing models with social amenities. The findings are as follows: (1) Human capital has significant positive effects on property values. This tests the Lucas conjecture. (2) Different types of social capital have different effects on property values: an increase in the percentage of new residents has significant positive effects on property values, probably due to the strength of weak ties. However, an increase in the percentage of single-parent households has negative effects on property values. An increase in the home ownership rate has positive effects at large geographic levels. (3) Cultural capital effects vary from high to low geographic levels, the effects of English proficiency and racial homogeneity are positive at and beyond the tract level, but insignificant at the block level. This may imply that cultural capital is more important in social interactions at large geographic scale.
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.
:
social,
state,
capital,
metropolitan,
population,
household,
urban,
city,
housing,
residential,
neighborhood,
resident,
amenity,
residence,
community,
rent,
homeowner,
apartment
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
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 'What Has Been Capitalized into Property Values: Human Capital, Social Capital, or Cultural Capital?' are listed below in order of similarity.
-
Working PaperSmart Cafe Cities: Testing Human Capital Externalities in the Boston Metropolitan Area🔥
October 2005
Working Paper Number:
CES-05-24
Existing studies have explored either only one or two of the mechanisms that human capital externalities percolate at only macrogeographic levels. This paper uses the 1990 Massachusetts Census data and tests four mechanisms at the microgeographic levels in the Boston metropolitan area labor market. We propose that individual workers can learn from their occupational and industrial peers in the same local labor market through four channels: depth of human capital stock, Marshallian labor market externalities, Jacobs labor market externalities, and thickness of the local labor market. We find that all types of human capital externalities are significant across Census blocks. Different types of externalities attenuate at different speeds over distances. For example, the effect of human capital depth decays rapidly beyond three miles away from block centroid. We conclude that knowledge spillovers are very localized within microgeographic scope in cities that we call Smart Caf' Cities.View Full Paper PDF
-
Working PaperSpillovers from Immigrant Diversity in Cities
November 2015
Working Paper Number:
CES-15-37
Using comprehensive longitudinal matched employer-employee data for the U.S., this paper provides new evidence on the relationship between productivity and immigration spawned urban diversity. Existing empirical work has uncovered a robust positive correlation between productivity and immigrant diversity, supporting theory suggesting that diversity acts as a local public good that makes workers more productive by enlarging the pool of knowledge available to them, as well as by fostering opportunities for them to recombine ideas to generate novelty. This paper makes several empirical and conceptual contributions. First, it improves on existing empirical work by addressing various sources of potential bias, especially from unobserved heterogeneity among individuals, work establishments, and cities. Second, it augments identification by using longitudinal data that permits examination of how diversity and productivity co-move. Third, the paper seeks to reveal whether diversity acts upon productivity chiefly at the scale of the city or the workplace. Findings confirm that urban immigrant diversity produces positive and nontrivial spillovers for U.S. workers. This social return represents a distinct channel through which immigration generates broad-based economic benefits.View Full Paper PDF
-
Working PaperInteractions, Neighborhood Selection, and Housing Demand
August 2002
Working Paper Number:
CES-02-19
This paper contributes to the growing literature that identifies and measures the impact of social context on individual economic behavior. We develop a model of housing demand with neighborhood e'ects and neighborhood choice. Modelling neighborhood choice is of fundamental importance in estimating and understanding endogenous and exogenous neighborhood effects. That is, to obtain unbiased estimates of neighborhood effects, it is necessary to control for non-random sorting into neighborhoods. Estimation of the model exploits a unique data set of household data that has been augmented with contextual information at two di'erent levels ('scales') of aggregation. One is at the neighborhood cluster level, of about ten neighbors, with the data coming from a special sample of the American Housing Survey. A second level is the census tract to which these dwelling units belong. Tract-level data are available in the Summary Tape Files of the decennial Census data. We merge these two data sets by gaining access to confidential data of the U.S. Bureau of the Census. We overcome some limitations of these data by implementing some significant methodological advances in estimating discrete choice models. Our results for the neighborhood choice model indicate that individuals prefer to live near others like themselves. This can perpetuate income inequality since those with the best opportunities at economic success will cluster together. The results for the housing demand equation are similar to those in our earlier work [Ioannides and Zabel (2000] where we find evidence of significant endogenous and contextual neighborhood effects.View Full Paper PDF
-
Working PaperUrban Immigrant Diversity and Inclusive Institutions
January 2016
Working Paper Number:
CES-16-07
Recent evidence suggests that rising immigrant diversity in cities offers economic benefits, including improved innovation, entrepreneurship and productivity. One potentially important but underexplored dimension of this relationship is how local institutional context shapes the benefits firms and workers receive from the diversity in their midst. Theory suggests that institutions can make it less costly for diverse workers to transact, thereby catalyzing the latent bene ts of heterogeneity. This paper tests the hypothesis that the effects of immigrant diversity on productivity will be stronger in locations featuring more 'inclusive" institutions. It leverages comprehensive longitudinal linked employer-employee data for the U.S. and two distinct measures of inclusive institutions at the metropolitan area level: social capital and pro- or anti-immigrant ordinances. Findings confirm the importance of institutional context: in cities with low levels of inclusive institutions, the benefits of diversity are modest and in some cases statistically insignificant; in cities with high levels of inclusive institutions, the benefits of immigrant diversity are positive, significant, and substantial. Moreover, natives residing in cities that have enacted laws restricting immigrants enjoy no diversity spillovers whatsoever, while immigrants in these cities continue to receive a diversity bonus. These results confirm the economic significance of urban immigrant diversity, while suggesting the importance of local social and economic institutions.View Full Paper PDF
-
Working PaperLocation, 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.View Full Paper PDF
-
Working PaperExternalities of Public Housing: The Effect of Public Housing Demolitions on Local Crime
March 2016
Working Paper Number:
CES-16-16
This paper evaluates the potential for negative externalities from public housing by examining crime rates before and after demolition of public housing projects in Chicago between 1995 and 2010. Using data on block-level crimes by type of crime merged to detailed geographic data on individual public housing demolitions, I find evidence that Chicago's public housing imposed significant externalities on the surrounding neighborhood. Using a difference in difference approach comparing neighborhoods around public housing projects to nearby neighborhoods I find that crime decreases by 8.8% after a demolition. This decrease is concentrated in violent crime. I use an event study to show that the decrease occurs at the approximate date of the eviction of the residents and persists for at least 5 years after the demolition. Neighborhoods with large demolitions and demolitions of public housing that had been poorly maintained display the largest crime decreases.View Full Paper PDF
-
Working PaperThe Opportunity Atlas: Mapping the Childhood Roots of Social Mobility
September 2018
Working Paper Number:
CES-18-42R
We construct a publicly available atlas of children's outcomes in adulthood by Census tract using anonymized longitudinal data covering nearly the entire U.S. population. For each tract, we estimate children's earnings distributions, incarceration rates, and other outcomes in adulthood by parental income, race, and gender. These estimates allow us to trace the roots of outcomes such as poverty and incarceration back to the neighborhoods in which children grew up. We find that children's outcomes vary sharply across nearby tracts: for children of parents at the 25th percentile of the income distribution, the standard deviation of mean household income at age 35 is $4,200 across tracts within counties. We illustrate how these tract-level data can provide insight into how neighborhoods shape the development of human capital and support local economic policy using two applications. First, we show that the estimates permit precise targeting of policies to improve economic opportunity by uncovering specific neighborhoods where certain subgroups of children grow up to have poor outcomes. Neighborhoods matter at a very granular level: conditional on characteristics such as poverty rates in a child's own Census tract, characteristics of tracts that are one mile away have little predictive power for a child's outcomes. Our historical estimates are informative predictors of outcomes even for children growing up today because neighborhood conditions are relatively stable over time. Second, we show that the observational estimates are highly predictive of neighborhoods' causal effects, based on a comparison to data from the Moving to Opportunity experiment and a quasi-experimental research design analyzing movers' outcomes. We then identify high-opportunity neighborhoods that are affordable to low-income families, providing an input into the design of affordable housing policies. Our measures of children's long-term outcomes are only weakly correlated with traditional proxies for local economic success such as rates of job growth, showing that the conditions that create greater upward mobility are not necessarily the same as those that lead to productive labor markets.View Full Paper PDF
-
Working PaperLocal Industrial Conditions and Entrepreneurship: How Much of the Spatial Distribution Can We Explain?
October 2008
Working Paper Number:
CES-08-37
Why are some places more entrepreneurial than others? We use Census Bureau data to study local determinants of manufacturing startups across cities and industries. Demo- graphics have limited explanatory power. Overall levels of local customers and suppliers are only modestly important, but new entrants seem particularly drawn to areas with many smaller suppliers, as suggested by Chinitz (1961). Abundant workers in relevant occupations also strongly predict entry. These forces plus city and industry fixed effects explain between sixty and eighty percent of manufacturing entry. We use spatial distributions of natural cost advantages to address partially endogeneity concerns.View Full Paper PDF
-
Working PaperNeighborhood Effects on High-School Drop-Out Rates and Teenage Childbearing: Tests for Non-Linearities, Race-Specific Effects, Interactions with Family Characteristics, and Endogenous Causation using Geocoded California Census Microdata
May 2008
Working Paper Number:
CES-08-12
This paper examines the relationship between neighborhood characteristics and the likelihood that a youth will drop out of high school or have a child during the teenage years. Using a dataset that is uniquely wellsuited to the study of neighborhood effects, the impact of the neighborhood poverty rate and the percentage of professionals in the local labor force on youth outcomes in California is examined. The first section of the paper tests for non-linearities in the relationship between indicators of neighborhood distress and youth outcomes. Some evidence is found for a break-point at low levels of poverty. Suggestive but inconclusive evidence is also found for a second breakpoint, at very high levels of poverty, for African-American youth only. The second part of the paper examines interactions between family background characteristics and neighborhood effects, and finds that White youth are most sensitive to neighborhood effects, while the effect of parental education depends on the neighborhood measure in question. Among White youth, those from single-parent households are more vulnerable to neighborhood conditions. The third section of the paper finds that for White youth and Hispanic youth, the relevant neighborhood variables appear to be the own-race poverty rates and the percentage of professionals of youths' own race. The final section of the paper estimates a tract-fixed effects model, using the results from the third section to define multiple relevant poverty rates within each tract. The fixed-effects specification suggests that for White and Hispanic youth in California, neighborhood effects remain significant, even with the inclusion of controls for any unobserved family and neighborhood characteristics that are constant within tracts.View Full Paper PDF
-
Working PaperJob Referral Networks and the Determination of Earnings in Local Labor Markets
December 2010
Working Paper Number:
CES-10-40
Referral networks may affect the efficiency and equity of labor market outcomes, but few studies have been able to identify earnings effects empirically. To make progress, I set up a model of on-the-job search in which referral networks channel information about high-paying jobs. I evaluate the model using employer-employee matched data for the U.S. linked to the Census block of residence for each worker. The referral effect is identified by variations in the quality of local referral networks within narrowly defined neighborhoods. I find, consistent with the model, a positive and significant role for local referral networks on the full distribution of earnings outcomes from job search.View Full Paper PDF
