Office of the Assistant Secretary for Policy Development and Research, HUD.
Notice; Solicitation of comment.
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.
Comment Due Date: July 27, 2015.
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 Start Printed Page 36833make 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.
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.
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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).
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Start Supplemental Information
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.
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.
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.
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.
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 Start Printed Page 36834separate 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.
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.
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.
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 Start Printed Page 36835coefficients from those reported in the Draft Final Report for the HCV Program Administrative Fee Study.
Table 1—Updated Base Fee Formula Calculation
|Intercept 5||All PHAs||−$110.56|
|Wage index||All PHAs||+ $49.21 × wage index|
|Health insurance cost index||All PHAs||+ $27.99 × health insurance index cost|
|Program size 1||PHAs with less than or equal to 250 units||+ $16.07|
|Program size 2||PHAs with 251 to 750 units||+ $16.07 × [1 − (units − 250)/500]|
|Program size 3||PHAs with more than 750 units||+ $0|
|Percent of households with earned income||All PHAs||+ $0.93 × % of households with earned income|
|New admissions rate||All PHAs||+ $0.24 × % of households that are new admissions|
|Small area rent ratio||All PHAs||+ $60.83 × small area rent ratio|
|Percent of households more than 60 miles from PHA HQ||All PHAs||+ $1.01 × % of households living more than 60 miles from PHA HQ|
|Fee||Per Unit Month Leased (UML)||= $|
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. 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 
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 Start Printed Page 36836relative importance only changes a small amount based on these new data.
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 × [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 
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 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 Start Printed Page 36837the 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?
End Supplemental Information
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