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Reasonable Rent Determination Comparability Study Summary. Janell Hoppe – National Manager EZ-Reasonable Rent Determination a Division of. Topics. Compliant Data Collection Data Collection Strategy Collect Comparables Unit Data Assign Rental Market Value (RMV) Collected Data Verification

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reasonable rent determination comparability study summary

Reasonable Rent Determination Comparability Study Summary

Janell Hoppe – National Manager

EZ-Reasonable Rent Determination

a Division of

topics
Topics
  • Compliant Data Collection
  • Data Collection Strategy
  • Collect Comparables Unit Data
  • Assign Rental Market Value (RMV)
  • Collected Data Verification
  • Quality Assurance
  • Comparability Study Statistics
  • Questions and Answers
compliant data collection
Compliant Data Collection

24 CFR Section 982.507, Rent to Owner: Reasonable Rent, Section 985.3, (b) of the SEMAP rule, Notice PIH 2003-12,  Notice PIH 2009-51, Notice PIH 2010-18

  • Use only unassisted units
  • Consider all HUD characteristics – location, unit size, unit type, quality, age, amenities, housing services, maintenance, utilities provided by the owner
data collection strategy
Data Collection Strategy
  • CMHA provided Voucher Holder data by zip code
    • Those zip codes currently under lease
    • Mobility areas that might offer enhanced opportunities for Participant self-sufficiency
data collection strategy1
Data Collection Strategy
  • Nelrod developed data collection strategy within voucher holder zip codes
    • Ratio matching – Example

10% of voucher holders located in zip 45205; 10% of comps in 45205

10% of units are single family units; 10% of comparables will be single family units

(Comp ratios subj. to availability)

collect comparables unit data
Collect Comparables Unit Data

Start Comparables Collection

Various data sources used to identify comps

  • Property Manager/Real Estate Marketing Websites
  • Local Newspaper/Craigslist Ads
  • For Rent Signs
  • Local Landlords at CMHA Community Meeting
collect comparables unit data1
Collect Comparables Unit Data

Data Collected

  • Unit address
  • Landlord information
  • Unit quality (based on HQS)
    • Excellent-exceeds HQS
    • Good-meets HQS w/upgrades
    • Fair-barely meets HQS or minimum repairs needed
    • Poor-many repairs needed
collect comparables unit data2
Collect Comparables Unit Data

Data Collected

  • Age
  • Unit Type
  • Amenities ( A/C, carpeting, appliances, fireplace, community pool, etc)
  • Facilities (community pool, off-street parking, storage, etc)
  • Housing Services (package receiving, etc)
  • Maintenance (onsite, offsite, poor)
collect comparables unit data3
Collect Comparables Unit Data

Data Collected

  • Utilities included in rent
  • Rent amount (actual vs proposed when available)
  • Size (includes sq. feet when available)
  • Number of bedrooms
  • Number of bathrooms
assign rental market value rmv to collected comparables
Assign Rental Market Value (RMV) to Collected Comparables
  • View1-3 block radius surrounding comp. unit
    • High RMV – Above average neighborhood includes:
        • New construction
        • Luxury communities
        • Community amenities such as golf courses
        • State of the art systems
        • Modern appliances
assign rental market value rmv to collected comparables1
Assign Rental Market Value (RMV) to Collected Comparables
  • Medium RMV – Average neighborhood includes
    • Intermediate community (slightly less favorable than luxury communities)
    • Newer larger homes
    • Community amenities such as community pool/fitness center
    • Quality finishes, adequate systems and appliances
assign rental market value rmv to collected comparables2
Assign Rental Market Value (RMV) to Collected Comparables
  • Low RMV –Minimal, depleted or impoverished communities
    • Minimal
      • Older, smaller homes in good condition (starter-homes)
      • Community amenities such as parks
    • Depleted or Impoverished
      • Much older communities
      • Large amount of crime
      • Homes may be in bad physical condition, abandoned or vandalized
collected data verification
Collected Data Verification
  • Off-site Verifications
    • Landlord phone call/email
    • Property tax records
    • Satellite imagery
collected data verification1
Collected Data Verification
  • Onsite Verifications
    • County-wide neighborhoods tour of zip code areas
    • Performed approximately 350 onsite unit assessments
quality assurance
Quality Assurance
  • Identify/Delete Anomaly Comparability Units
    • Very high rent
    • Very low rent
    • Unit values unequal to requested rent
comparability study statistics
Comparability Study Statistics
  • 1005 comparable units as of May 2010 included both vacant and occupied units
  • Beginning June 2010 add additional 35 comps per month for 11 months
comparability study statistics1
Comparability Study Statistics
  • Comps by Bedroom Size
    • Efficiencies – 4%
    • 1 Bedroom – 33%
    • 2 Bedroom – 28%
    • 3 Bedroom – 25%
    • 4 Bedroom – 8%
    • 5 Bedroom – 2%
    • 6 Bedroom – 01%
comparability study statistics2
Comparability Study Statistics
  • Comps by Structure Types
    • Garden walkup/multi family- 64%
    • Townhouse - 6%
    • Rowhouse – 2%
    • Duplex – 0.1%
    • Highrise – 4%
    • Single family units – 24%
comparability study statistics3
Comparability Study Statistics

Zip code containing highest % of high RMV

45208

comparability study statistics4
Comparability Study Statistics

Zip codes containing 60% or greater medium RMV

45241, 45248, 45255

comparability study statistics5
Comparability Study Statistics

Zips codes representing deconcentration and/or expanding housing opportunities RMVs

45208, 45241, 45248, 45255

comparability study summary
Comparability Study Summary

Zip codes containing relatively even match of medium and low RMVs (ranged from 40% to 60%)

45213, 45219, 45239, 45230 and 45242

comparability study statistics6
Comparability Study Statistics

Zip codes containing the highest % of low RMVs

45204, 45205, 45207, 45211, 45214, 45216, 45223, 45224, 45225

comparability study statistics7
Comparability Study Statistics

Zip codes that had a significant % of high, medium and low RMVs (may offer widest selection of potential HCVP units)

45202, 45215, 45220, 45227, 45236, and 45246

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