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

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Presentation on theme: "Reasonable Rent Determination Comparability Study Summary Janell Hoppe – National Manager EZ-Reasonable Rent Determination a Division of a Division of."— Presentation transcript:

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

2 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 3 Compliant Data Collection 24 CFR Section , Rent to Owner: Reasonable Rent, Section 985.3, (b) of the SEMAP rule, Notice PIH , Notice PIH , Notice PIH  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 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 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 % of units are single family units; 10% of comparables will be single family units (Comp ratios subj. to availability)

6 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 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 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 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 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 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 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 13 Collected Data Verification  Off-site Verifications Landlord phone call/ Property tax records Satellite imagery

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

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

16 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 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 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 19 Comparability Study Statistics Zip code containing highest % of high RMV 45208

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

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

22 22 Comparability Study Summary Zip codes containing relatively even match of medium and low RMVs (ranged from 40% to 60%) 45213, 45219, 45239, and 45242

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

24 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 25 Questions and Answers


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