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COSCDA Program Manager’s and Legislative Training Conference March 12, 2012

COSCDA Program Manager’s and Legislative Training Conference March 12, 2012 Ben Winter, Policy Development, PD&R, HUD. Redistribution Effects of Introducing ACS and Census 2010 Data Into the CDBG Formula. Policy Development & Research (PD&R) & Community Planning and Development (CPD)

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COSCDA Program Manager’s and Legislative Training Conference March 12, 2012

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  1. COSCDA Program Manager’s and Legislative Training Conference March 12, 2012 Ben Winter, Policy Development, PD&R, HUD Redistribution Effects of Introducing ACS and Census 2010 Data Into the CDBG Formula

  2. Policy Development & Research (PD&R) & Community Planning and Development (CPD) CDBG Analysis Needs Study Distribution Effects of New Data huduser.org Introduction

  3. Goal: Isolate and examine the effects of introducing new data into the CDBG formula Holds constant FY 2011 appropriation amount and grantee universe Examines changes in variables Design of Study

  4. Formula Mechanics for Entitlements 3 Grantees: metropolitan cities, urban counties, & states (non-entitlement communities) Formula A: {0.25 x Pop (a) + 0.50 x Pov (a) + 0.25 x Ocrowd (a) } x {0.7 x Appropriation} Pop (MA) Pov (MA) Ocrowd (MA) Formula B (cities): {0.20 x Glag (a) + 0.30 x Pov (a) + 0.50 x Age (a) } x {0.7 x Appropriation} Glag (MC) Pov (MA) Age (MA) Formula B (urban counties): {0.20 x Glag (a) + 0.30 x Pov (a) + 0.50 x Age (a) } x {0.7 x Appropriation} Glag (ENT) Pov (MA) Age (MA)

  5. Mechanics for Non-entitlements Formula A: {0.25 x Pop (a) + 0.50 x Pov (a) + 0.25 x Ocrowd (a) } x {0.3 x Appropriation} Pop (Nent) Pov (Nent) Ocrowd (Nent) Formula B: {0.20 x Pop (a) + 0.30 x Pov (a) + 0.50 x Age (a) } x {0.3 x Appropriation} Pop (Nent) Pov (Nent) Age (Nent)

  6. Overall Trends in Variables

  7. Grantee Examples Formula A – Louisiana

  8. Grantee Examples Formula B – Indiana

  9. Grantee Examples Formula B – Ohio

  10. [1] Percent change by variable does not add up exactly to the total percent change due to rounding. Change in $ per Formula Variable

  11. HUD Administrative Regions

  12. States by Region

  13. Census Long Form vs. ACS Similarities: Common questions Response rate (97%+) Sampling frame (all addresses in the US) Differences: Sample size (18 million vs. 15 million) Point-in-time vs. period estimates Precision and accuracy of data

  14. Confirming Key Trends Overcrowding (more than 1 person per room): 5.7%  3% Moves closer to AHS estimates (around 2.2% to 2.5% during 2001-2009) Results from fewer small units; not change in household size Pre-1940 housing (structure built before 1940): 20.4%  3% AHS: net decrease in pre-1940 units from 2001 to 2007 Non-response problem, particularly in older rental buildings ACS estimates are closer to administrative data

  15. HOME Formula and LMI Data HOME Formula affected by similar issues to CDBG. Overcrowding not a factor. Pre-1950 housing instead of pre-1940. Low & Moderate Income (LMI) Data for CDBG Area Benefit: Will be based on census tracts instead of block groups Produced by Census Bureau along with CHAS data and other custom tabulations of ACS. Delivery of 2005-2009 LMI Data delayed, but expected by February 2012.

  16. Contact Ben Winter: Ben.J.Winter@hud.gov Formula Allocations Paul Joice: Paul.A.Joice@hud.gov Census data Abu Zuberi: Abubakari.D.Zuberi@hud.gov CDBG/HOME Allocations & Census Data

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