[Federal Register Volume 80, Number 123 (Friday, June 26, 2015)]
[Notices]
[Pages 36832-36837]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2015-15765]


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DEPARTMENT OF HOUSING AND URBAN DEVELOPMENT

[Docket No. FR-5874-N-01]


HUD Administrative Fee Formula--Solicitation of Comment

AGENCY: Office of the Assistant Secretary for Policy Development and 
Research, HUD.

ACTION: Notice; Solicitation of comment.

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SUMMARY: Housing Choice Voucher program administrative fees are 
currently calculated based on the number of vouchers under lease and a 
percentage of the 1993 or 1994 local Fair Market Rent. In 2010, HUD 
contracted Abt Associates to conduct the Housing Choice Voucher Program 
Administrative Fee Study to measure the actual costs of operating high-
performing and efficient Housing Choice Voucher programs and to develop 
an updated administrative fee formula. The results of the study were 
released on April 8, 2015. In this notice, HUD seeks public comment on 
the variables identified by the study as impacting administrative fee 
costs (including specific questions raised in this preamble), how HUD 
might use these study findings to develop a new administrative fee 
formula, and any other issues that may arise with the development and 
implementation of a new administrative fee formula.

DATES: Comment Due Date: July 27, 2015.

ADDRESSES: Interested persons are invited to submit comments regarding 
this notice to the Regulations Division, Office of General Counsel, 
Department of Housing and Urban Development, 451 7th Street SW., Room 
10276, Washington, DC 20410-0500. Communications must refer to the 
above docket number and title. There are two methods for submitting 
public comments. All submissions must refer to the above docket number 
and title.
    1. Submission of Comments by Mail. Comments may be submitted by 
mail to the Regulations Division, Office of General Counsel, Department 
of Housing and Urban Development, 451 7th Street SW., Room 10276, 
Washington, DC 20410-0500.
    2. Electronic Submission of Comments. Interested persons may submit 
comments electronically through the Federal eRulemaking Portal at 
www.regulations.gov. HUD strongly encourages commenters to submit 
comments electronically. Electronic submission of comments allows the 
commenter maximum time to prepare and submit a comment, ensures timely 
receipt by HUD, and enables HUD to

[[Page 36833]]

make them immediately available to the public. Comments submitted 
electronically through the www.regulations.gov Web site can be viewed 
by other commenters and interested members of the public. Commenters 
should follow the instructions provided on that site to submit comments 
electronically.

    Note: To receive consideration as public comments, comments must 
be submitted through one of the two methods specified above. Again, 
all submissions must refer to the docket number and title of the 
notice.

    No Facsimile Comments. Facsimile (fax) comments are not acceptable.
    Public Inspection of Public Comments. All properly submitted 
comments and communications submitted to HUD will be available for 
public inspection and copying between 8 a.m. and 5 p.m. weekdays at the 
above address. Due to security measures at the HUD Headquarters 
building, an appointment to review the public comments must be 
scheduled in advance by calling the Regulations Division at 202-708-
3055 (this is not a toll-free number). Individuals with speech or 
hearing impairments may access this number via TTY by calling the 
Federal Relay Service at 1-800-877-8339 (this is a toll-free number). 
Copies of all comments submitted are available for inspection and 
downloading at www.regulations.gov.

FOR FURTHER INFORMATION CONTACT: Todd Richardson, Associate Deputy 
Assistant Secretary for Policy Development, Office of Policy 
Development and Research, Department of Housing and Urban Development, 
451 7th Street SW., Room 8106, Washington, DC 20410; telephone number 
202-402-5706 (this is not a toll-free number). Persons with hearing or 
speech impairments may access this number by calling the Federal Relay 
Service at 800-877-8339 (this is a toll-free number).

SUPPLEMENTARY INFORMATION:

I. Background

Current Housing Choice Voucher Administrative Fee

    HUD provides funding to over 2,300 public housing agencies (PHAs) 
to administer more than 2.1 million Housing Choice Vouchers (HCV) 
nationwide, using a formula that was established by statute in 1998 to 
apply from 1999 forward, and which currently uses a calculation based 
primarily on the formulation of Fair Market Rents (FMR) from Fiscal 
Years 1993 or 1994. Section 8(q)(1)(B) of the United States Housing Act 
of 1937 (1937 Act), which was established in its current form in Title 
V, Section 547 of the Quality Housing and Work Responsibility Act, 
Public Law 105-276 (approved October 21, 1998) provides how the 
administrative fee from 1999 and thereafter is calculated. 
Additionally, the 1937 Act, in section 8(q)(1)(C), provides HUD with 
broad authority to establish the administrative fee for years 
subsequent to 1999 based on changes in wage data or other objectively 
measurable data that reflect the costs of administering the program, as 
determined by the Secretary.
    The Fiscal Year 1999 calculation is provided in section 8(q)(1)(B) 
of the 1937 Act, 42 U.S.C. 1437f(q)(1)(B), and provides that the 
monthly fee for which a dwelling unit is covered by an assistance 
contract shall be, for a PHA with 600 or fewer units, 7.65 percent of 
the base amount. For a PHA with more than 600 units, the fee is 7.65 
percent of the base amount for the first 600 units, and 7.0 percent of 
the base amount for additional units above 600. The base amount is 
calculated as the higher of the Fiscal Year 1993 FMR for a 2 bedroom 
existing dwelling unit in the market area, or the amount that is the 
lesser of the Fiscal Year 1994 FMR for the same type of unit or 103.5 
percent of the 1993 FMR for the same type of unit. This amount is 
adjusted for wage inflation from 1993 or 1994 to the current year.
    For years after 1999, section 8(q)(1)(C) of the 1937 Act, 42 U.S.C. 
1437f(q)(1)(C), provides that HUD shall publish a notice setting the 
administrative fee for each geographic area in the Federal Register. 
The fee is to be based on changes in wage data or other objectively 
verifiable data that reflect the cost of administering the program, as 
determined by HUD.\1\
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    \1\ It is important to note that the Consolidated and Further 
Continuing Appropriations Act of 2015 (Pub. L. 113-235) provides 
that administrative fees for the calendar year 2015 funding cycle 
will be calculated as provided for by section 8(q) of the 1937 Act 
and related appropriation act provisions (notably section 202 of 
Pub. L. 104-204), as in effect immediately before the enactment of 
the Quality Housing and Work Responsibility Act of 1998 (QHWRA) 
(Pub. L. 105-276). Similar language has appeared in HUD's 
appropriations acts since 1999. Although current and recent 
appropriations act language requires administrative fees to be 
calculated based on section 8(q) of the 1937 Act and related 
appropriation act provisions as in effect immediately before the 
enactment of QHWRA, the relevant statutory language (except for the 
percentages in the base amount) is the same as the current section 
8(q) provisions of the 1937 Act.
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    Despite having the statutory authority in 42 U.S.C. 1437f(q)(1)(C) 
to update the administrative fee in fiscal years subsequent to 1999 
based on changes in wage data or other objectively measurable data that 
reflect the costs of administering the program, HUD has not yet updated 
the administrative fee formula.

Housing Choice Voucher (HCV) Program Administrative Fee Study

    HUD initiated, and Congress funded, the HCV Program Administrative 
Fee Study to determine how much it costs to effectively and efficiently 
administer the Housing Choice Voucher program and how PHA, housing 
market, and HCV program characteristics affect those administrative 
costs.\2\ The study measured time use over an 8 week period at 60 PHAs 
across the country. For 56 of the 60 PHAs, time measurement was 
conducted on a rolling basis commencing in January 2013 and ending in 
April 2014. Four of the 60 PHAs served as pretest sites and were 
measured in 2012. The study was completed and published on April 8 
2015.\3\ The study represents the most rigorous and thorough 
examination of the cost of administering a high-performing and 
efficient HCV program and provides the basis for calculating a fee 
formula based on actual PHA experience across a wide range of PHAs. The 
HCV Program Administrative Fee Study, which relied on a rigorous 
methodology, a range of PHA sizes and locations, and input from a large 
group of expert and industry technical reviewers over the life of the 
study, has attempted to correct those shortfalls.
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    \2\ The study excluded PHAs participating in the Moving to Work 
demonstration because the fees for these agencies are presently 
calculated in accordance with their agreements.
    \3\ The study can be found at: http://www.huduser.org/portal/hcvfeestudy.html.
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    The study (1) identified a diverse sample of 60 PHAs administering 
high performing and efficient HCV programs; (2) tested different direct 
time measurement methods; (3) collected detailed direct time 
measurement data using Random Moment Sampling via smartphones; and (4) 
captured all costs incurred by the HCV program (labor, non-labor, 
direct, indirect, overhead costs) over an 18 month period. Time data 
was collected from each PHA over an 8 week period, with just a few PHAs 
included in each 8 week window throughout the 18 month period.
    Additionally, a large and active expert and industry technical 
review group of representatives from the major affordable housing 
industry groups, executive directors and HCV program directors from 
high performing PHAs, affordable housing industry technical assistance 
providers, housing researchers, and industrial engineers reviewed the 
study design and results at

[[Page 36834]]

separate stages in the study and provided invaluable feedback.
    In addition to documenting the total cost needed to run the HCV 
program effectively, the study recommends a new formula for allocation 
of funds. It also recommends that the proposed new formula have some 
flexibility to be adjusted for unanticipated cost, program changes, and 
supplementary fees as programmatic design or goals change over time.

II. Findings of HCV Program Administrative Fee Study

    The recently published HCV Program Administrative Fee Study 
explores the actual cost to administer the HCV program effectively and 
efficiently and finds that there are variables with better theoretical 
and statistical connection to administering the program than the 1993 
FMRs.

Formula Variables

    The study analyzed over 50 variables and found the following 
variables to be the most relevant cost drivers:
    (a) Wage index. The study tested the theory that areas with higher 
wages would have higher per unit administrative costs, and confirmed 
that this is the primary driver of cost differences between PHAs.
    (b) PHA size. The study tested the theory that smaller PHAs 
experience higher costs than larger PHAs, and found this theory to be a 
very strong driver of cost differences and that the impact was greater 
for PHAs administering approximately 500 or less units. The proposed 
formula applies a stepped down approach to implementing this factor by 
gradually reducing the weight of this factor in the formula amount the 
larger the PHA. While PHAs administering 250 units or less receive the 
full amount of the PHA size factor, PHAs administering between 251 and 
750 units are gradually reduced to zero for this factor. The 
researchers found that this gradual reduction is a more accurate 
measure of explaining variance between PHAs rather than a strict cut 
off of 500 units, as used in the study.
    (c) Health Insurance Cost Index. The study tested the theory that 
health insurance costs vary from state to state and are an important 
component of agency costs. The study found that health insurance costs 
explain some of the variance between PHAs but that the relationship 
between health insurance costs and administrative costs is not very 
strong. Nonetheless such costs are included in the proposed formula due 
to the strong encouragement of the technical experts advising the 
research team based on the strong theoretical relationship to HCV 
administrative costs and the fact that it captures aspects of PHA costs 
not addressed by other variables. The health insurance cost index 
offers a way of capturing regional variation that is known to exist in 
local benefits costs, which are an important component of PHA labor 
costs.
    (d) Percent households with earned income. The study tested the 
theory that the more households an agency had to manage that have wage 
earnings, the higher the agency's costs. The agency's costs are higher 
because wage earners are more likely to have changes in income over the 
course of a year, and therefore require more interim recertifications. 
The time to verify income is greater for these households than to 
verify the income for fixed income households. The study confirmed that 
this is a highly significant factor explaining variance between PHAs in 
cost.
    (e) New admission rate. The study tested the theory that PHAs with 
a higher rate of new admissions have higher costs due to additional 
time associated with intake and lease-up work. The study found that the 
time for intake and lease-up is more costly than ongoing occupancy on a 
per household basis. However, new admission rates did not have a high 
statistical significance in the study's cost driver model, likely due 
to the study occurring during a time of relatively low new admission 
rates. Refraining from issuing vouchers was often used to avoid funding 
shortfalls resulting from the 2013 sequestration, a period of time 
which was included in this study. New admission rate is included as a 
factor in the proposed formula due to the findings in the study on time 
spent per activity related to new admissions and the strong 
encouragement of the technical experts advising the research team.
    (f) Small area rent ratio.\4\ The study tested the theory that the 
time needed to assist tenants with successful leasing in zip codes with 
higher median rents than the overall market area (county or 
metropolitan area) adds to administrative costs. The findings support 
this theory, showing that among the 60 PHAs, the minutes spent per 
voucher household on expanding housing opportunities was a significant 
cost driver. Although information on minutes spent on expanding housing 
opportunities is not available for every PHA (it is only available for 
the 60 PHAs in the study), the study is able to use the location of 
where tenants lease units to assess if PHA tenants successfully lease 
units in more expensive neighborhoods within a metropolitan area.
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    \4\ For PHAs in Metropolitan counties, the small area rent ratio 
is calculated as the median gross rent for the zip codes where 
voucher holders live, weighted by the share of voucher holders in 
each zip code, divided by the median gross rent for the Metropolitan 
area; for PHAs in non-Metropolitan counties, the small area rent 
ratio is calculated as the unadjusted two-bedroom FMR for the non-
Metropolitan counties where the PHA operates, divided by the 
published FMR.
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    (g) Distance from main office greater than 60 miles. The study 
tested the theory that an agency serving a very large service area, 
such as a PHA serving an entire state or a very large county, will need 
to either travel long distances or set up satellite offices to 
administer the program, which increases administrative costs. The 
researchers found this to be particularly true for PHAs with very large 
service areas as measured by the percent of leased units more than 60 
miles from the PHA headquarters, leading to its inclusion in the 
proposed formula.

Inflation Factor

    Since the proposed formula predicts the per-unit costs for 
administering the program from July 1, 2013, through June 30, 2014, the 
formula must be adjusted to reflect changes in the cost of goods and 
services over time. That is, the formula needs a factor to account for 
inflation. The HCV Program Administrative Fee Study recommends a 
blended inflation rate that distinguishes between (i) change in wage 
rates over time; (ii) change in health insurance costs over time; and 
(iii) change in non-labor costs over time.

Base Fee Formula Calculation

    The published Draft Final Report for the HCV Program Administrative 
Fee Study establishes a recommended formula. In the process of updating 
the study data, HUD identified a more accurate method for calculating 
new admission rate than the method used in the study. In the published 
Draft Final Report for the HCV Program Administrative Fee Study, new 
admission rate was captured using an extract of PIH Information Center 
(PIC) data showing all ``New Admissions'' during a 12 month period. The 
extract used, however, undercounted new admissions because any interim 
recertification within the 12 months on a new admission overwrote the 
new admission code. HUD has corrected this. This has resulted in 
updated

[[Page 36835]]

coefficients from those reported in the Draft Final Report for the HCV 
Program Administrative Fee Study.

              Table 1--Updated Base Fee Formula Calculation
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           Variable                 Applies to          Calculation
------------------------------------------------------------------------
Intercept \5\.................  All PHAs.........  -$110.56
Wage index....................  All PHAs.........  + $49.21 x wage index
Health insurance cost index...  All PHAs.........  + $27.99 x health
                                                    insurance index cost
Program size 1................  PHAs with less     + $16.07
                                 than or equal to
                                 250 units.
Program size 2................  PHAs with 251 to   + $16.07 x [1 -
                                 750 units.         (units - 250)/500]
Program size 3................  PHAs with more     + $0
                                 than 750 units.
Percent of households with      All PHAs.........  + $0.93 x % of
 earned income.                                     households with
                                                    earned income
New admissions rate...........  All PHAs.........  + $0.24 x % of
                                                    households that are
                                                    new admissions
Small area rent ratio.........  All PHAs.........  + $60.83 x small area
                                                    rent ratio
Percent of households more      All PHAs.........  + $1.01 x % of
 than 60 miles from PHA HQ.                         households living
                                                    more than 60 miles
                                                    from PHA HQ
Fee...........................  Per Unit Month     = $
                                 Leased (UML).
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    The formula calculates for an individual PHA an amount of the 
administrative fee for each factor. The total of all factors is used to 
determine the UML fee for each PHA. For example, an agency with a wage 
rate that is 80 percent of the national rate would receive, on the wage 
rate factor, 0.80 times $49.21 equals $39.37 per unit month [0.80 * 
$49.21 = $39.37]. Each factor would be calculated in this same way. All 
of the resulting costs are summed to equal the per unit month cost for 
the specific PHA to run the program.
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    \5\ The intercept for the model is -110.56, which means that 
each PHA starts out with approximately a negative $110.56 fee per 
UML. (This does not make a lot of intuitive sense but is part of the 
regression model. It means that if all the other variables were 
zero, the predicted cost per UML would be -$110.56. However, that 
would not happen in practice, because several of the variables could 
never be zero.)
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    The study was based on 60 high performing PHAs. The study found 
that across the 60 PHAs, the average administrative cost per voucher, 
for calendar year 2013, ranged from $42.06 per UML to $108.87 per UML. 
A straight application of the proposed formula for the more than 2,300 
PHAs would result in predicted fees that fall below the lowest observed 
cost of $42 per UML for 2 percent of PHAs overall, half of which are 
located in the U.S. Territories of Puerto Rico, Guam, U.S. Virgin 
Islands, and the Northern Mariana Islands. All of the other PHAs in the 
study had costs that exceeded $42 and the formula is designed to 
capture those actual costs. Because $42 per UML is the lowest cost the 
study observed under which a PHA with very low cost drivers could 
operate a high-performing and efficient program, the study recommends 
that the formula establish a floor of $42 per UML. However, the 80 PHAs 
in the U.S. Territories may have costs that the fee formula is not 
capturing as reflected in their current funding levels. As such, and to 
minimize the funding disruption, a floor of $54 per UML was proposed 
for the U.S. Territories.
    The proposed formula would change the method by which PHAs are 
reimbursed for the administrative costs associated with tenant 
portability. The study found that PHAs with higher percentages of units 
that are port-ins (received from another jurisdiction under portability 
regulations) had higher average costs, supporting the theory that there 
is additional time associated with processing port-ins and working with 
issuing PHAs. Currently, as noted in the study, ``PHAs receive 100 
percent of the administrative fee for vouchers that remain within their 
jurisdiction, bill the issuing PHAs for 80 percent of the issuing PHA's 
fee for port-in vouchers, and are billed by receiving PHAs for 80 
percent of their fees for port-out vouchers.'' This process means that 
PHAs currently receive less than 100 percent of another agency's fee 
rate. The proposed formula eliminates the billing of administrative 
fees. Instead, as noted in the recommendations, PHAs would ``receive 
100 percent of their own fee for vouchers that do not port and for 
port-in vouchers administered on behalf of other PHAs. PHAs [would] 
also receive a fee equivalent to 20 percent of their own fee for port-
out vouchers that are administered by other PHAs.''
    The proposed formula accurately predicted 63 percent of the 
variance in agency costs among the 60 PHAs studied. Given the 
complexity of the HCV program and the heterogeneity of the United 
States, this is an extremely high predictive value. Nonetheless, the 
study notes that there are costs that may not be accounted for in the 
proposed formula. An example is the up-front time to establish a 
Veterans Affairs Supportive Housing (VASH) voucher program, continuing 
costs to administer a homeownership voucher program, and the up-front 
time to utilize project-based vouchers. Moreover, the study emphasizes 
that program rules may change which could impact costs. For example, 
PHAs may adopt streamlining activities which result in fewer 
inspections, and may result in lower administrative costs.
    For more details on the HCV Program Administrative Fee Study's 
proposed formula, please review the study which is available at http://www.huduser.org/portal/hcvfeestudy.html. HUD will also post at that Web 
page comments on the study from independent peer reviewers in the 
disciplines of economics and industrial engineering by June 30, 2015.

III. Solicitation of Comments on Proposed New Housing Choice Voucher 
Formula

    Through this notice, HUD solicits comments on the variables 
identified by the study as impacting administrative fee costs, as well 
as how HUD may use these study findings to develop a new administrative 
fee formula. While all comments are welcome, HUD specifically seeks 
comments in the following areas:
A. Seven Formula Factors \6\
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    \6\ The values for the seven formula factors are all limited in 
the proposed formula to the range of values observed in the 60 study 
PHAs.
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    As noted above, additional analysis after issuance of the report 
resulted in some changes to the importance of each variable in the 
proposed formula. The variables do not change and their

[[Page 36836]]

relative importance only changes a small amount based on these new 
data.
(1) Wages
    The data source for this variable is the Bureau of Labor Statistics 
Quarterly Census on Employment and Wages (QCEW), average annual wages 
for local government employees. For non-state PHAs located in 
metropolitan counties, the proposed formula would use the ratio of the 
average annual wage for local government employees for all metropolitan 
counties in the PHA's state divided by the national average in the most 
recent 4 quarters for which data are available times $49.21 per unit 
month. For non-state PHAs located in non-metropolitan counties, the 
proposed formula would use the ratio of the average annual wage for 
local government employees for all non-metropolitan counties in the 
PHA's state divided by the national average in the most recent 4 
quarters for which data are available times $49.21 per unit month. For 
state PHAs, the proposed formula would use the ratio of the average 
annual wage for local government employees for the PHA's state divided 
by the national average in the most recent 4 quarters for which data 
are available times $49.21. This variable is both theoretically and 
statistically very strong and, based on current statutory language, is 
a required variable.
    Specific questions for comment:
    (i) Is the average metropolitan or non-metropolitan wage rate a 
reasonable proxy for non-state PHAs?
    (ii) Is using the state average wage reasonable for a state PHA?
(2) PHA Size
    The study recommends that PHAs with 250 or fewer average units 
under lease in the most recent 4 quarters receive a factor of $16.07 
per unit month. For PHAs with more than 250 units but fewer than 750 
units, the factor is calculated as $16.07 x [1 - (units - 250)/500]. 
For PHAs with 750 or more units, the factor is zero. The unit count 
would include port-ins and subtract out port-outs. This variable is 
both theoretically and statistically very strong and, based on current 
statutory language, is a recommended variable.
    From a policy perspective, multiple small PHAs working in close 
proximity to one another is clearly inefficient. If those PHAs merged, 
this study shows their administrative costs would likely go down. On 
the other hand, as the ``60 miles'' variable shows, there is a cost to 
PHAs with very large service areas. As such, remote small PHAs may be 
no less inefficient than larger PHAs with huge service areas.
    Specific questions for comment:
    (i) As an incentive to have small PHAs in close proximity to one 
another merge, should the increase in funding for smaller PHAs only be 
applied to remote smaller PHAs?
    (ii) Should the formula consider additional size categories?
(3) Health Insurance Cost Index
    The study recommends using the ratio of the annual average health 
insurance costs to private employers from the U.S. Department of Health 
and Human Services Medical Expenditure Panel Survey in the state of the 
PHA main office divided by the national average in the most recent 3 
years for which data are available times $27.99.
    This variable is theoretically strong but not statistically very 
strong.
    Specific questions for comment:
    (i) Is this a good measure of the health insurance costs facing 
PHAs?
    (ii) Are health insurance costs a good proxy for the benefits costs 
facing PHAs?
    (iii) Should this variable, given its weak statistical 
significance, be included as part of the formula?
(4) Percent Households With Earned Income
    The study recommends using an average of the count of number of 
households served during each of the most recent 12 quarters with 
income from wages as reported to HUD on Form 50058 \7\ divided by total 
number of vouchers under lease reported to HUD on Form 50058 in the 
same time period times $0.93. This variable is both theoretically and 
statistically very strong. Several members of the industry group noted 
that elderly and disabled, with their many receipts for health care 
expenses, did not appear to be accounted for in the formula. The study 
finds that PHAs spend more time on annual and interim recertifications 
for family households (a large share of which have earned income) than 
for elderly and disabled households and also that the percentage of 
households with wages was a significant cost driver explaining the 
variance on PHA costs.
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    \7\ See http://portal.hud.gov/hudportal/documents/huddoc?id=50058.pdf.
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    Specific question for comment: Are there exceptional costs for non-
wage earners that should be considered for the formula?
(5) New Admission Rate
    The study recommends using the average of the count of households 
admitted to the program during each of the most recent 12 quarters as 
reported to HUD on Form 50058 divided by the total number of vouchers 
under lease during the same time period as reported to HUD on Form 
50058 times $0.24.
    This variable is theoretically strong but not statistically very 
strong. It was included based on a weak statistical relationship and 
the strong views of the expert panel.
    Specific question for comment: To smooth out year-to-year 
fluctuations in admissions rates, HUD is proposing to use three-years 
of admission data to calculate this variable. Is that a long enough 
period or should HUD consider 5 years?
(6) Small Area Rent Ratio
    The study recommends using the most recent 4 quarter average of the 
sum of program unit ratios in Metropolitan areas and program unit 
ratios outside of Metropolitan areas divided by total number of program 
units for which a ratio is calculated during the same time period times 
$60.83. For program units in Metropolitan areas, the ratio for each 
program unit is the most recent median gross rent of the zip code of 
the program unit based on the program unit address reported on HUD form 
50058 divided by Metropolitan average median gross rent for the 
Metropolitan or HUD FMR area during the same time period. For program 
units outside of Metropolitan areas, the ratio is the sum of the count 
of program units during each of the prior three calendar years under 
lease in each county based on tenant addresses reported to HUD on Form 
50058 times the most recent unadjusted 2-bedroom FMR of the county as 
determined by HUD divided by the published 2-bedroom FMR of the county.
    This variable is a proxy measure of agency's cost in successfully 
assisting tenants with leasing units in neighborhoods that are assumed 
to have higher quality assets such as lower crime and higher performing 
schools. The research supports that effort to lease in higher costs 
areas is more burdensome on PHAs.
    Specific question for comment: While this may serve as a motivator 
for PHAs with a low-rent service area to merge with a PHA with a higher 
cost service area, it is a disincentive for the PHAs within a higher 
cost service area to merge. How could this factor be used to 
incentivize both parties to merge?
(7) Distance From Main Office Greater Than 60 Miles
    The study recommends using the average of the count of households 
served by the program during each of

[[Page 36837]]

the most recent 4 quarters determined by HUD to be 60 miles or more 
from the PHA headquarters address using tenant address data as reported 
to HUD on Form 50058 divided by the total number of vouchers under 
lease during the same time period as reported to HUD on Form 50058 
times $1.01.
    This variable is both theoretically and statistically very strong 
and is reflected in the statutory language as a recommended variable.
    Specific issues for comment: The research is clear that PHAs that 
serve voucher holders over a very large area have higher costs. The 
researchers have used as a proxy for this the average distance from the 
main office of over 60 miles. HUD recognizes that this could be 
problematic if an agency primarily serves households in a relatively 
small geography, but that small geography is more than 60 miles from 
its ``main'' office. HUD is exploring different ways to implement this 
finding such that it does not have this problem. HUD encourages comment 
on approaches to implementing the research finding most effectively 
without providing more funding than is appropriate.
B. Inflation Factor
    The study also recommends a blended inflation factor. HUD is 
seeking comment on the data to be used for each inflation factor as 
well as how to weight the different inflation factors.
    Specific issues for comment: HUD is soliciting comment on the value 
of using the following three data sources:
    (i) The change between the average over the most recent 4 quarters 
and 2013 in the Consumer Price Index for all Urban Consumers in the 
U.S. as published by the Bureau of Labor Statistics;
    (ii) The change between the average over the most recent 4 quarters 
and 2013 in the Bureau of Labor Statistics QCEW data on local 
government employees for the U.S.; and
    (iii) The change between the average over the most recent 4 
quarters and 2013 in health insurance costs from the U.S. Department of 
Health and Human Services Medical Expenditure Panel Survey for the U.S.
C. Fee Floor
    The fee floor is projected at $42 per unit month. Can PHAs operate 
for less than this fee floor amount per month? If so, what would the 
proposed amount be and what are the supporting data that might be 
available?
D. Fee Floor for U.S. Territories
    The fee floor for U.S. Territories is projected at $54 per unit 
month. What data that might be available for U.S. Territories that 
might support a lower or higher rate?
E. Maximum Funding
    Among the 60 study sites, the highest calculated per unit month 
rate was $108.87. Should HUD set a maximum funding amount per unit 
month? If so, what should the maximum funding amount per unit month be?
F. Adjusting Fees for Future Program Changes
    Where, in the future, there are reductions in cost associated with 
program changes such as less frequent reexaminations or inspections, 
how should HUD account for those reductions in the administrative fee 
formula? Should HUD review and revise the fee on a set schedule? How 
much advance notice do PHAs need?
G. Reducing Funding Disruptions
    How might HUD reduce funding disruptions for the small number of 
PHAs likely to have a decrease in funding under the proposed formula 
relative to recent year funding levels? The research shows that even if 
Congress funded the proposed formula at 100 percent, there would still 
be a small number of PHAs (8 percent) with a funding reduction relative 
to their 2013 and 2014 funding levels.
H. Additional Cost Factors for Consideration
    While the study team had no additional recommendations on the 
formula other than what has been described above, the team did note 
that they expected HUD to consider modifications to the formula or 
supplemental fees to support PHAs in addressing program priorities, 
strategic goals, and policy objectives at both the local and the 
national level. (See section 7.7 of the draft final report.) The 
findings from the study suggested four specific areas for further 
analysis and consideration:
    (1) Special voucher programs;
    (2) serving homeless households;
    (3) performance incentives; and
    (4) expanding housing opportunities.
    HUD also requests feedback on inclusion of a factor for enforcement 
actions, specifically an incentive for PHAs to investigate potential 
fraud or errors and how such a formula factor might be constructed with 
the data currently reported by PHAs to HUD.
    HUD is specifically seeking comment on whether additional 
compensation should be provided to address any or all of these areas. 
In addition, what other areas should be considered for additional 
compensation? What would be the appropriate amount of compensation for 
these areas or any other areas, and what data would support the 
proposed amounts? What form should the compensation take--should it be 
built into the fee formula as a cost driver or should it be provided 
outside of the administrative fee formula as a separate supplemental 
fee?

    Dated: June 22, 2015.
Katherine M. O'Regan,
Assistant Secretary for Policy Development and Research.
[FR Doc. 2015-15765 Filed 6-25-15; 8:45 am]
 BILLING CODE 4210-67-P