New data collected for the Boston Metropolitan Statistical Area provide detailed information on financial assets that allow analysis to extend beyond the traditional black–white divide. Targeting US-born blacks, Caribbean blacks, Puerto Ricans, Dominicans, and other Hispanics, findings from the National Asset Scorecard for Communities of Color survey underscore the large racial and ethnic disparities in financial wealth, even after controlling for demographic and socioeconomic status. Further, some notable differences between Boston’s communities of color highlight the importance of detailed analyses for research on the racial wealth gap. In particular, among non-white communities Dominicans report comparatively low asset and high debt amounts, while Caribbean blacks report relatively higher levels of wealth. Altogether, these findings point to the need for wealth building opportunities in communities of color and further investigation of the causes and consequences of financial disparities between groups of color disaggregated by specific ancestral origin.
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Including white Hispanics.
The Boston MSA includes the following counties: Essex, Middlesex, Norfolk, Plymouth, and Suffolk in Massachusetts; and Rockingham and Strafford in New Hampshire.
All population figures come from the 2012 American Community Survey 1-year estimates. The share of the non-Hispanic white population declined from 81 % in 2000 to 74 % in 2012 .
As of 2012, there were 3,435,332 white residents; 329,500 black residents; 318,181 Asians and Pacific Islanders; and 444,517 Hispanics in the Boston MSA. These categories do not include mixed-race individuals with the exception of Hispanics/Latinos who may be of any race. Most Hispanics self-identify as “other race” in the US Census.
US Census projections at the national level estimate that by 2030 non-Hispanic whites will account for 55 % of the nation’s population. Hispanics and non-Hispanic blacks will represent 22 and 13 %, respectively. Unfortunately, population projections at the state level by race and ethnicity are not available.
In the USA in 2012, Puerto Ricans and Dominicans accounted for 9.4 and 3.1 % of the Hispanic population, respectively.
Shapiro et al. 2013 show that educational attainment gaps accounted for 5 % of the racial wealth gap.
A case can be made that error in estimating wealth may be simultaneously correlated with education as well (Hamilton et al. 2015). For most head of households, education is completed by age 25.
While experience of divorce and widowhood may have a difference impact on wealth holdings compared to those who were never married, the small sample size does not allow for these more nuanced analyses. Most respondents were either married (40 %) or single, never married (30 %).
Although investment-based incomes are typically small for most individuals from communities of color, there is still the possibility of estimating biased models with the inclusion of stochastic income as a right-hand-side variable due to its stochastic covariance with the error-term in wealth regressions.
These significant associations are not detectable with the inclusion of income which, as mentioned earlier, is likely simultaneously determined with wealth.
Some researchers choose to project these missing variables, and in this study we opted not to use projection and thus preferred mitigating measurement error by not projected missing variables in contrast to mitigating measurement error by including missing observations based on projected values.
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The NASCC-Boston data collection has been funded by the Ford Foundation and the Federal Reserve Bank of Boston.
Appendix: NASSC Methodology
Appendix: NASSC Methodology
The National Asset Scorecard for Communities of Color (NASCC) is a research initiative that includes the design and implementation of a piloted survey in targeted metropolitan areas to provide insights about the asset and debt positions of racial and ethnic groups at the detailed ancestral origin level. The study is able to delve beyond information about the net worth position of broadly defined ethnic groups such as Latinos or Asians taken as a collectivity, but, instead, collects asset and debt information on groups with more specificity, such as Mexicans, Puerto Ricans, and Cubans or Asian Indians, Chinese, Filipinos, Koreans, Vietnamese, and Japanese respondents. In addition, the study provides information on native Americans disaggregated by tribal affiliation and black Americans disaggregated by ancestral origin, whether from the Caribbean or recent immigration from the African continent. To date, very little is known about the asset positions of these more narrowly identified national origin subgroups, particularly those with native American and Asian heritage.
The survey was conducted in the Boston MSA and in four other metropolitan areas (Los Angeles, CA; Miami, FL; Tulsa, OK; and Washington, DC) chosen using a systematic approach to ascertain geographic and demographic national representativeness of the ethnic groups defined at the ancestral origin level. The criteria of choosing a metro area for sampling inclusion was based primarily on ethnic plurality and other intangibles such as geographic representation, area size, access to certain ethnic groups that might be hard to identify in an urban context. The survey instrument was designed primarily to ascertain information about specific assets, liabilities, financial resources, and the personal savings and investment activity of respondents. Additional areas of inquiry included remittance behavior—sending assets or other resources abroad—and support for relatives elsewhere in the USA The survey also provides information on home ownership, foreclosure experiences, and the equity status of homes. The survey solicited additional information that might be particular to the financial experiences of lower wealth non-white individuals, such as the use of payday lenders. The survey included core demographic characteristics found in most surveys, such as age, sex, educational attainment, household composition, nativity, income, family background, etc.
For consistency with an existing national data set, the asset and debt module of the questionnaire replicates questions used in the Panel Study of Income Dynamics (PSID). For the non-asset and debt-based questions, the NASCC survey replicated many questions found on the Multi-City Study of Urban Inequality (MCSUI), which, similar to NASCC, was a cross-sectional four-city survey aimed at gathering socioeconomic differences across ethnic and racial groups that was conducted in the early 1990s.
The average survey lasted 39 min. Various sampling techniques were utilized in order to locate and identify an ethnically plural sample consisting of the specifically defined ethnic groups. The techniques included directory-listed landline samples targeted to census tracts where specific ethnic groups were known to reside; cell phone random digit dialing (RDD) samples drawn from rate centers that cover targeted ethnic group ZIP codes; samples drawn from targeted ZIP codes based on billing address; and the use of surname-based lists targeting specific national origin groups. In sum, 59,311 personalized advance letters were sent; 64,154 telephone numbers dialed 337,085 times; and 9525 interviewer hours were spent across three shops to conduct 2343 completed surveys.
Race and ethnic identity for this study is based on self-identification of the family respondent best qualified to discuss family financial matters. The statistics in the sample utilized weights that were anchored on family characteristics in the US Bureau of the Census’ American Community Survey to generate results representative of specific ethnic group characteristics in the respondent’s metropolitan area of residence. Overall, the unweighted NASCC sample is not dissimilar from the weighted NASCC sample, suggesting the specific ethnic group observations in the particular metropolitan areas in the study are fairly representative of their populations at large.
Finally, the study was primarily designed to compare specific ethnic and racial groups within the same metropolitan area. An advantage of this approach is the implicit control with regard to asset and debt pricing and products associated with particular geographic areas.
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Meschede, T., Hamilton, D., Muñoz, A.P. et al. Inequality in the “Cradle of Liberty”: Race/Ethnicity and Wealth in Greater Boston. Race Soc Probl 8, 18–28 (2016). https://doi.org/10.1007/s12552-016-9166-9
- Racial wealth
- Ethnic and racial wealth disparities
- Wealth disparities in Boston
- Racial inequalities
- Racial wealth gap