HUD Administrative Fee Formula-Solicitation of Comment, 36832-36837 [2015-15765]
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requirements that will become effective
July 6, 2015.
1. Under-Occupied Units at Time of
Conversion. Provisions affected: 24 CFR
983.259 and 24 CFR 880.605.
Alternative requirements: Families
occupying, at the time of conversion of
assistance, a unit that is larger than is
appropriate, may remain in the unit
until an appropriate-sized unit becomes
available in the covered project. For
conversions of assistance under the
Second Component, this alternative
requirement will only apply to families
who are elderly or disabled.
2. Assistance for Families when Total
Tenant Payment (TTP) Exceeds Gross
Rent. Provisions affected: Section
8(o)(13)(H) of the 1937 Act and 24 CFR
983.301 and 983.53(d); sections 8–5 C
and 8–6 A.1 of Housing Handbook
4350.3, REV–1. Alternative
requirements: PHAs and owners must
continue to treat certain families in
public housing that has converted
assistance as assisted and charge 30
percent of adjusted gross income in rent.
The families covered by this alternative
requirement must have incomes high
enough for their TTP to exceed the
contract rent yet still remain eligible for
assistance or otherwise be unable to
afford market rate housing in their
community.
3. Choice-Mobility Cap for Public
Housing Conversions to PBV. Provisions
affected: Section 8(o)(13)(E) of the 1937
Act and 24 CFR 983.261(c). Alternative
requirements: PHAs may, for projects
that have converted assistance from
public housing to PBV, provide one of
every four turnover vouchers to
households on their regular HCV
waiting list instead of for ChoiceMobility vouchers.
4. Rent Supp/RAP Contracts After
Section 236 Prepayment. Provision
affected: 24 CFR 236.725. Alternative
requirement: The original RAP or Rent
Supp contract may remain in place for
60 days after repayment of a section 236
mortgage until the PBV HAP contract is
executed.
5 Uniform Physical Condition
Standards (UPCS) Inspections.
Provision affected: 24 CFR part 5,
subpart G. Alternative requirement: All
units converting assistance to PBRA
must meet the Uniform Physical
Condition Standards no later than the
date of completion of initial repairs as
indicated in the RAD conversion
commitment.
6. Floating Units. Provision affected:
24 CFR 983.203(c). Alternative
requirement: For certain projects
(Choice, Mixed Finance, and HOPE VI),
HUD is allowing PBV assistance to float
among unassisted units.
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IV. Other New Provisions
In addition to the waivers above, the
following change to the RAD program
has been implemented:
Initial Contract Rent Setting for
Conversions of Assistance from Rent
Supp/RAP. The 2015 Appropriations
Act permitted HUD to convert Rent
Supp and RAP properties to PBRA. To
implement this authority, HUD must
establish how to set the contract rents
for these conversions. Rents will be set
on the post-rehabilitation market rents,
as determined by a rent comparability
study, not to exceed 110 percent of the
fair market rent.
V. Revised Program Notice Availability
The Revised Program Notice (PIH
2012–32, REV–2) can be found on
RAD’s Web site, www.hud.gov/RAD.
VI. Environmental Review
A Finding of No Significant Impact
with respect to the environment was
made in connection with HUD notice
PIH 2012–32 issued on March 8, 2012,
and in accordance with HUD
regulations in 24 CFR part 50 that
implement section 102(2)(C) of the
National Environmental Policy Act of
1969 (42 U.S.C. 4332(2)(C)). The
Finding remains applicable to the
Revised Program Notice and is available
for public inspection during regular
business hours in the Regulations
Division, Office of General Counsel;
Department of Housing and Urban
Development; 451 7th Street SW., Room
10276; Washington, DC 20410– 0500.
Due to security measures at the HUD
Headquarters building, please schedule
an appointment to review the Finding
by calling the Regulations Division at
202–402–3055 (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 800–877–8339.
Dated: June 19, 2015.
´
Lourdes Castro Ramırez,
Principal Deputy Assistant Secretary for
Public and Indian Housing.
Edward L. Golding,
Principal Deputy Assistant Secretary for
Housing.
Approved on: June 3, 2015.
Nani A. Coloretti,
Deputy Secretary.
[FR Doc. 2015–15764 Filed 6–25–15; 8:45 am]
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DEPARTMENT OF HOUSING AND
URBAN DEVELOPMENT
[Docket No. FR–5874–N–01]
HUD Administrative Fee Formula—
Solicitation of Comment
Office of the Assistant
Secretary for Policy Development and
Research, HUD.
ACTION: Notice; Solicitation of comment.
AGENCY:
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.
SUMMARY:
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
ADDRESSES:
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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 tollfree number). Persons with hearing or
speech impairments may access this
number by calling the Federal Relay
Service at 800–877–8339 (this is a tollfree number).
SUPPLEMENTARY INFORMATION:
I. Background
tkelley on DSK3SPTVN1PROD with NOTICES
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
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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
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
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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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 highperforming 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.
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
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: https://
www.huduser.org/portal/hcvfeestudy.html.
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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.
(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.
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.
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.
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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.
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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
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coefficients from those reported in the
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Draft Final Report for the HCV Program
Administrative Fee Study.
TABLE 1—UPDATED BASE FEE FORMULA CALCULATION
Variable
Applies to
Intercept 5 ........................................
Wage index .....................................
Health insurance cost index ............
Program size 1 ................................
All PHAs ........................................
All PHAs ........................................
All PHAs ........................................
PHAs with less than or equal to
250 units.
PHAs with 251 to 750 units ...........
PHAs with more than 750 units ....
All PHAs ........................................
¥$110.56
+ $49.21 × wage index
+ $27.99 × health insurance index cost
+ $16.07
All PHAs ........................................
All PHAs ........................................
All PHAs ........................................
+ $0.24 × % of households that are new admissions
+ $60.83 × small area rent ratio
+ $1.01 × % of households living more than 60 miles from PHA HQ
Per Unit Month Leased (UML) ......
=$
Program size 2 ................................
Program size 3 ................................
Percent of households with earned
income.
New admissions rate .......................
Small area rent ratio .......................
Percent of households more than
60 miles from PHA HQ.
Fee ..................................................
tkelley on DSK3SPTVN1PROD with NOTICES
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.
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.
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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Calculation
+ $16.07 × [1 ¥ (units ¥ 250)/500]
+ $0
+ $0.93 × % of households with earned income
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 portin 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
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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 https://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
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
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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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 nonmetropolitan 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 nonmetropolitan wage rate a reasonable
proxy for non-state PHAs?
(ii) Is using the state average wage
reasonable for a state PHA?
tkelley on DSK3SPTVN1PROD with NOTICES
(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 × [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
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Jkt 235001
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.
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
7 See https://portal.hud.gov/hudportal/documents/
huddoc?id=50058.pdf.
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Frm 00080
Fmt 4703
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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 2bedroom 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
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Federal Register / Vol. 80, No. 123 / Friday, June 26, 2015 / Notices
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.
tkelley on DSK3SPTVN1PROD with NOTICES
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
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18:15 Jun 25, 2015
Jkt 235001
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
PO 00000
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Fmt 4703
Sfmt 4703
36837
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
DEPARTMENT OF HOUSING AND
URBAN DEVELOPMENT
[Docket No. FR–5828–N–26]
Federal Property Suitable as Facilities
To Assist the Homeless
Office of the Assistant
Secretary for Community Planning and
Development, HUD.
ACTION: Notice.
AGENCY:
This Notice identifies
unutilized, underutilized, excess, and
surplus Federal property reviewed by
HUD for suitability for use to assist the
homeless.
FOR FURTHER INFORMATION CONTACT:
Juanita Perry, Department of Housing
and Urban Development, 451 Seventh
Street SW., Room 7266, Washington, DC
20410; telephone (202) 402–3970; TTY
number for the hearing- and speechimpaired (202) 708–2565 (these
telephone numbers are not toll-free), or
call the toll-free Title V information line
at 800–927–7588.
SUPPLEMENTARY INFORMATION: In
accordance with 24 CFR part 581 and
section 501 of the Stewart B. McKinney
Homeless Assistance Act (42 U.S.C.
11411), as amended, HUD is publishing
this Notice to identify Federal buildings
and other real property that HUD has
reviewed for suitability for use to assist
the homeless. The properties were
reviewed using information provided to
HUD by Federal landholding agencies
regarding unutilized and underutilized
buildings and real property controlled
by such agencies or by GSA regarding
its inventory of excess or surplus
Federal property. This Notice is also
published in order to comply with the
December 12, 1988 Court Order in
National Coalition for the Homeless v.
Veterans Administration, No. 88–2503–
OG (D.D.C.).
Properties reviewed are listed in this
Notice according to the following
SUMMARY:
E:\FR\FM\26JNN1.SGM
26JNN1
Agencies
[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]
-----------------------------------------------------------------------
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.
-----------------------------------------------------------------------
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\
---------------------------------------------------------------------------
\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.
---------------------------------------------------------------------------
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.
---------------------------------------------------------------------------
\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: https://www.huduser.org/portal/hcvfeestudy.html.
---------------------------------------------------------------------------
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.
---------------------------------------------------------------------------
\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.
---------------------------------------------------------------------------
(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
------------------------------------------------------------------------
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 https://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 https://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