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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. 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

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  1. Reasonable Rent Determination Comparability Study Summary Janell Hoppe – National Manager EZ-Reasonable Rent Determination a Division of

  2. 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

  3. 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

  4. 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

  5. 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)

  6. 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

  7. 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

  8. 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)

  9. 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

  10. 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

  11. 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

  12. 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

  13. Collected Data Verification • Off-site Verifications • Landlord phone call/email • Property tax records • Satellite imagery

  14. Collected Data Verification • Onsite Verifications • County-wide neighborhoods tour of zip code areas • Performed approximately 350 onsite unit assessments

  15. Quality Assurance • Identify/Delete Anomaly Comparability Units • Very high rent • Very low rent • Unit values unequal to requested rent

  16. 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

  17. 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%

  18. 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%

  19. Comparability Study Statistics Zip code containing highest % of high RMV 45208

  20. Comparability Study Statistics Zip codes containing 60% or greater medium RMV 45241, 45248, 45255

  21. Comparability Study Statistics Zips codes representing deconcentration and/or expanding housing opportunities RMVs 45208, 45241, 45248, 45255

  22. 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

  23. Comparability Study Statistics Zip codes containing the highest % of low RMVs 45204, 45205, 45207, 45211, 45214, 45216, 45223, 45224, 45225

  24. 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

  25. Questions and Answers

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