1. V ISIT US AT http://surveys.virginia.edu Thomas M.Guterbock, 1 James M. Ellis, 1 Deborah L. Rexrode, 1 Casey M. Eggleston, 1 Darrick Hamilton, 2 & William A. Darity, Jr. 3 Adaptations As the study progressed, we had to adapt : Sampling methods and screening criteria More use of surname lists More specific ethnic screening Tighter geographic targeting Calling lab management Don’t use all stations at once Better feedback to interviewers Outsource for better time zone and language capabilities Programming New screener logic facilitates changes Production monitoring Change from overlapping counts to mutually exclusive categories New ways to acquire paradata from CATI system Used paradata to manage 30+ studies Racial dot map of DC Lorenz curves for ethnic distribution NASCC is supported by grants from The Ford Foundation and the Federal Reserve Bank of Boston. Author affiliations: 1) Center for Survey Research, University of Virginia. 2) Milano School of International Affairs, Management and Public Policy, The New School. 3) Research Network on Racial & Ethnic Inequality, Duke University. SPECIFICITY (Targeted group as percent of completes) High 90-100% Medium 50-89% Low 10-49% High.30-.60  Screened DC Asian Surname  Outsourced LA Chinese Surname  Outsourced LA Filipino Surname  Screened Tulsa American Indian Surname  Screened Miami Black Listed  Unscreened DC African Surname  Screened LA Black Listed  Unscreened DC Vietnamese and Korean Listed  Unscreened DC Black Listed  Unscreened LA Black Listed  Screened DC Black Listed Medium.20-.29  Outsourced LA Japanese Surname  Outsourced LA Hispanic Surname  Screened DC Hispanic Surname  Screened Tulsa Black and Latino Cell Phones  Unscreened DC Black Cell Phones  Unscreened Miami Black Cell Phones  Unscreened LA African Surname  Screened Tulsa Black and Latino Listed  Screened LA Asian Surname  Screened Tulsa Hispanic Surname  Boston Dominican Listed  Boston Puerto Rican Listed  Unscreened Miami Black Listed Low.00-.19  Screened Miami Hispanic Surname  Outsourced LA Vietnamese Surname  Outsourced LA Korean Surname  Boston Black and Latino Cell Phones  Boston Hispanic Surname  Boston Portuguese Surname  Boston Black and Latino Listed  Unscreened LA Asian Surname  Screened LA Hispanic Surname  Boston Cape Verdean Listed  Boston Caribbean Listed  Boston Haitian Listed  Screened DC Hispanic Cell Phones  Unscreened LA Black Cell Phones PRODUCTIVITY (Completions per hour) Result: A Unique Dataset Census tract and ZIP code data from 2010 ACS were used to determine if each group was sufficiently concentrated for geographic targeting. Lorenz curves represent incidence and coverage graphically. Sampling Approach Geographic Targeting Main GroupSubgroup Unique Household Count Multiple Response Count Asian Vietnamese157168 Korean107111 Chinese110122 Japanese7578 Filipino5558 East Indians104109 Other Asian 7393 Total Asian 681739 Latino Mexican 179199 Central American 6975 South American 110118 Cuban 116134 Puerto Rican 110127 Dominican 5556 Other Latino 78101 Total Latino 717810 Black US Origin 461543 Haitian/Caribbean 174183 African Immigrant 120129 Total Black 755855 Native AmericanTotal Native American 237248 WhitesTotal White 3461046 GRAND TOTAL 27363698 Note: Total household count =2,746; 10 cases were not assigned a final ethnicity. The Study The National Asset Scorecard for Communities of Color [NASCC] is a detailed telephone survey designed to better understand the asset and debt positions of various ethnic and racial groups whose wealth status is often overlooked or inadequately measured. NASCC by the Numbers 448,000 dialing attempts 87,000 numbers dialed 70,000 advance letters 12,000 interviewer hours 31 distinct studies 4.4 interviewer hrs./comp. 39 minutes long 2,746 completions This group was not concentrated enough to target geographically. Selecting these ZIP codes should yield 50% incidence and include 80% of all blacks in DC.  White  Black  Latino  Asian