Press Releases

Jaime Herrera Beutler Urges HUD to Improve Accuracy of Data Used to Determine Grant Eligibility for Lewis County Towns

Criticizes HUD for planning to use recently released data with up to 91.5% margin of error to measure small town incomes

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Washington, DC, May 5, 2016 | comments
Yesterday, Congresswoman Jaime Herrera Beutler urged the federal housing and development department via letter to improve its plans to evaluate development grant eligibility for towns like Toledo, Pe Ell and Vader that have erroneously been qualified as “too affluent.”
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Yesterday, Congresswoman Jaime Herrera Beutler urged the federal housing and development department via letter to improve its plans to evaluate development grant eligibility for towns like Toledo, Pe Ell and Vader that have erroneously been qualified as “too affluent.”  The Department of Housing and Urban Development (HUD) plans to use census data released at the end of 2015 that has margins of error as high as 91.5% to determine eligibility. 

Towns in Lewis County lost access to community development grants because HUD was using imprecise data to measure income levels and award those grants. Jaime has been leading an effort with the Appropriations Committee that oversees HUD’s budget to assist the agency in finding alternative data sources to correct its classification of Pe Ell, Toledo and Vader as “too affluent.” 

In today’s letter, Jaime also reiterated her 2014 invitation to Secretary Castro to visit the affected Lewis County towns to see firsthand the economic challenges that exist within the community.

Click here for Jaime’s latest letter to U.S. HUD Secretary Castro.

Secretary Julián Castro
U.S. Department of Housing and Urban Development
451 7th St., S.W.
Washington, D.C. 20410

Dear Secretary Castro,

I am writing to express my deep concerns and to urge you to address eligibility criteria for the State administered portion of the Community Development Block Grant (CDBG) program. 

 Several communities in my district lost access to the CDBG program not because of a sudden surge in household income or prosperity in those areas, but solely because HUD is using imprecise data to measure income levels and award those grants.  In 2014, HUD began using low-and moderate-income (LMI) data based on 2006-2010 American Community Survey (ACS) data to determine eligibility for the State portion of the CDBG program.  As you know, ACS data is often inaccurate in small rural communities.  Even the U.S. Census Bureau (Census) acknowledged challenges attaining accurate income data in these communities, and increased its oversampling in 2011 in hopes of correcting this problem. 

 It is my understanding that HUD presumes that Census’ increased oversampling will address this inequity, stating: “While [increased oversampling] does not address the current concern being expressed by communities, when HUD updates the low-mod areas in 2017 or 2018, it will have these new higher sampling rates for the 2011-2015 ACS data.”  However, relying on increased oversampling simply does not suffice as a solution.  The 2010-2014 data for the six communities in my district that lost eligibility still have deplorably high margins of error for median household income: the lowest margin of error is 17.5% and the highest is 91.5%.  As you know, data with a 91.5% margin of error is essentially worthless.  This data contains four of the five years to be included in the next LMI iteration; this demonstrates a continued high margin of error and further reveals that HUD has failed to recognize the poor quality of data that oversampling will produce.  It’s hard to imagine that a solution lies here.

Also troubling is the double standard HUD has laid out for communities.  Specifically, the HUD regulations at 24 CFR 570.483 (b)(1)) state that “…units of general local government may, at the discretion of the state, use either HUD-provided data comparing census data with appropriate low and moderate income levels or survey data that is methodologically sound...”  In other words, HUD requires struggling communities lacking the funding to complete basic sewer projects to expend resources conducting methodologically sound surveys, while the data HUD uses produces a margin of error up to 91.5%.  Would HUD accept locally-generated data with a 17.5% or 91.5% margin of error as methodologically sound? 

 Putting the onus on small rural communities to produce the data needed to prove they are deserving of CDBG funds is unrealistic, and it will leave an increasing number of deserving rural communities without access to this critical program.

 Based on these concerns, I request answers to the following questions:

  • What are the margins of error for the most recently available LMI data for the following communities in Southwest Washington: Bingen, Long Beach, Pe Ell, Stevenson, Toledo, and Vader?
  • Since you are aware HUD is using data with high margins of error, what do you see as HUD’s role in finding a workable, affordable solution or second review for communities that disagree with LMI data?
  • HUD’s next iteration of LMI is not expected to be released until 2017.  If the increased oversampling does not improve the accuracy of the data, what does HUD plan to do to address this problem? 
  • It is my understanding that HUD uses Census data to calculate LMI data.  Are margin of errors in ACS data mirrored in LMI data?

To conclude, it has been more than a year and a half since I invited you to tour the communities that lost eligibility to see firsthand the discrepancy in the data being used to represent their level of wealth.  I have noticed you have been to urban areas in the Pacific Northwest since that invitation, yet that trip did not include a visit to Lewis County or any other rural area.  I understand that getting to rural communities requires more time, but having you see firsthand the chasm between the flawed data that has deemed these communities “too affluent” and the on-the-ground reality of towns that are struggling to provide basic services may be the only way to get HUD to find a workable solution.  I want to take this opportunity to again invite you to join me in touring these communities.  

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