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1,900 | flat fee rates were leading to administrative fee deficits in small housing agencies and large administrative fee reserves at larger housing agencies. HUD has acknowledged that oversight and administrative efficiencies could be realized. As previously discussed, in recent years, the department has advanced several proposals aimed at streamlining and simplifying administration of the voucher program. Several of these proposals have advocated administrative consolidation as a means of creating administrative |
1,901 | efficiencies. For example, HUD’s 2011 version of the Transforming Rental Assistance initiative was intended to streamline and improve the delivery and oversight of rental assistance across all of the department’s rental assistance programs by means such as promoting consortiums, consolidation, and other locally designed structures for administrative functions. In addition, HUD recently initiated changes to its housing agency consortium rule. The revised rule would treat all housing agencies in a consortium |
1,902 | as one entity—HUD’s current regulation requires that consortium members be treated separately for oversight, reporting, and other purposes. Some have argued that the current rule does not allow HUD or housing agencies to realize the full benefits of consolidation— less oversight (one versus multiple agencies) and shared and thus reduced administrative responsibilities—and therefore discourages the formation of consortiums. Since 1998, nine housing agencies that administer vouchers have formed four consorti |
1,903 | ums. We evaluated the administrative consolidation in terms of its effect on assisted households and selected voucher program goals. More specifically, we looked at implications for, or likelihood of achieving (1) HUD’s mobility and deconcentration goals, (2) program administration, and (3) housing agency and industry support. Like the rent reform options we evaluated using similar criteria, consolidation has advantages over the current administrative structure, but also involves some trade-offs. Consolidat |
1,904 | ion might help HUD more readily achieve deconcentration goals. Although vouchers theoretically allow recipients to use them anywhere in the United States, the current system of program administration creates numerous hurdles for households to move out of high-poverty, central city jurisdictions in which they typically live. Most housing agencies originally were established to construct and manage public housing developments. As a result, program administration does not always align with housing markets. In |
1,905 | urban areas within the same market, several housing agencies may operate voucher programs with different admissions criteria and subsidy levels. A paper by researchers at the Brookings Institution argued that this “fragmentation of local program administration undermines the potential of the program as a mechanism for deconcentrating urban poverty.” Extending the jurisdiction of housing agencies (through consolidation, for example) likely would give assisted households access to more housing options, partic |
1,906 | ularly in surrounding suburbs. On the other hand, regionalized administration of the voucher program may make it harder for households to make or maintain contact with program administrators when necessary—for example, assisted households may not have access to transportation or may have to travel long distances to meet with housing agency officials. Several states offer examples of regional or statewide administration. Thirty-one states have programs in which one housing agency administers a voucher progra |
1,907 | m throughout a state. These housing agencies administer from less than one percent to all of their respective state’s total voucher allocation. In addition, as part of our work, we visited a number of housing agencies in the Boston, Massachusetts, metropolitan area. As a result of litigation in the mid-1990s, local housing agencies in the state are permitted to lease vouchers throughout the state (that is, outside their original jurisdictions, which typically align with city limits). Although all of the hou |
1,908 | sing agencies with which we spoke suggested that it was important that housing agencies maintain local control of their programs, each leased at least one voucher outside their original jurisdiction. In Brookline—a city with relatively high housing costs compared with the surrounding area and the nation—more than half of voucher holders rent apartments outside the city limits. Although consolidation will not alleviate housing agencies’ current administrative burden, it may begin to address some of the issue |
1,909 | s housing agencies and industry groups have raised about a particular policy—portability. Although portability is one of the hallmark objectives of the voucher program, almost all the housing agencies we contacted said that HUD’s portability polices should be revised or eliminated, noting that they are complicated and costly to administer. Under HUD’s portability rules, an assisted household may move to the jurisdiction of a different housing agency—the receiving agency either may bill the sending agency fo |
1,910 | r assistance for the transferring household or absorb the household into its own program. According to the 2000 Brookings Institution report, because of the complexity of the portability process—for example, receiving agencies may calculate subsidy levels differently than sending agencies, or apply more rigorous screening criteria—many housing agencies do not fully explain portability to households and do not encourage them to consider moving. In addition, consolidated waiting lists and single points of con |
1,911 | tact for housing assistance within a single housing market, region, or state may make the process of applying for and obtaining rental assistance less confusing and more transparent for households seeking assistance. For example, a large number of housing agencies in Massachusetts participate in a consolidated waiting list—households seeking assistance in the state need only put their name on one list and receive communications from one agency. HUD officials said that the department has been considering tak |
1,912 | ing steps to maintain the waiting lists of each housing agency in a centralized system. Finally, housing agencies we contacted were split on the idea of consolidation—about one quarter supported it as a way to cut costs and introduce administrative efficiencies in the voucher program, while almost half were against it. Some housing industry groups and an academic with which we spoke argued that consolidation would not save money—one noted that the administrative fees that small housing agencies receive are |
1,913 | relatively insignificant in terms of total program dollars—and would sacrifice local discretion and control of voucher programs. Others noted that administrative costs savings could result from the consolidation and single-source management of waiting lists and elimination or substantial reformation of the portability process; however, no data currently are available to assess this point. Over the past decade, Congress has responded to the increasing cost of vouchers by changing the way the program is funde |
1,914 | d. Specifically, rather than providing funding based on the number of vouchers housing agencies are permitted to lease, Congress currently provides funding based on housing agencies’ prior-year subsidy expenses. Congress also has capped appropriations so that housing agencies do not always receive the amount of subsidy or administrative funding for which they are eligible based on the funding formulas Congress annually establishes. While this approach gives Congress some control over cost increases, it does |
1,915 | not directly address the market and policy factors we identified as contributing to increases in program costs. Although policy makers can do little to alter or control market changes such as changes in rents and tenant incomes, our analysis suggests that savings could continue to be realized (or, in some cases, more households could be served without additional program funding if Congress chooses to reinvest the funds in the program) if HUD provided Congress better information on housing agencies’ subsidy |
1,916 | reserves. Enhanced information would include the extent of housing agencies’ subsidy reserves, clear and consistent criteria for determining how much housing agencies would need to retain to help ensure effective program management, and how much could be rescinded in future appropriations. Without such information, HUD faces difficulties in effectively manage the funding Congress provides for the voucher program, including ensuring that funds disbursed to housing agencies are used to assist households rath |
1,917 | er than remaining unused in reserve accounts. In tandem with providing information about the use of program funds, HUD also has an opportunity to advance proposals that would help increase the efficiency of program administration. In particular, HUD now has or will have richer, relevant experience and data from which to draw. In addition to previous reforms HUD has proposed, examples from the MTW program and HUD’s study on administrative fees can offer options to Congress for streamlining and simplifying ad |
1,918 | ministrative activities and aligning the administrative fee structure with actual administrative expenses. For example, information and analyses from these sources could help identify all current administrative requirements, determine which of those actions are necessary and which could be eliminated or streamlined, and determine the cost of performing these activities—which could help reduce program costs in the future. Although Congress and HUD have taken several steps to control rising costs in the vouch |
1,919 | er program, we have identified a range of options that offer the additional promise of managing program costs or increasing efficiency in the long term. These options would also be applicable to HUD’s other rental assistance programs and would have the potential to generate even greater savings. Implementing rent reform and administrative consolidation would require policymakers to consider some potential trade-offs—in the balance are issues such as the rent burden of assisted households, concentration of p |
1,920 | overty, and the extent of local control over voucher programs. Nevertheless, these options have certain advantages over the current program structure. For example, these options could save money or streamline program administration—both of which are important objectives in a time of fiscal constraint. Currently Congress is considering a variety of measures to address some of these issues. To help reduce voucher program costs or better ensure the efficient use of voucher program funds, we recommend that the |
1,921 | HUD Secretary provide information to Congress on (1) housing agencies’ estimated amount of excess subsidy reserves and (2) its criteria for how it will redistribute excess reserves among housing agencies so that they can serve more households. In taking these steps, the Secretary should determine a level of subsidy reserves housing agencies should retain on an ongoing basis to effectively manage their voucher programs. Further, the Secretary should consider proposing to Congress options for streamlining and |
1,922 | simplifying the administration of the voucher program and making corresponding changes to the administrative fee formula to reflect any new or revised administrative requirements. Such proposals should be informed by results of HUD’s ongoing administrative fee study and the experience of the MTW program. We provided a draft of this report to HUD for comment. In its written response, reproduced in appendix II, HUD neither agreed nor disagreed with our recommendations, but provided technical comments that we |
1,923 | have incorporated where appropriate. While the response noted that the draft report provided an accurate assessment of the program and its current outcomes, HUD identified several points for clarification and emphasis, including: HUD commented that the stated purpose of our report of identifying options for increasing efficiencies and simplifying program administration was inconsistent with our recommendations for agency action because some of the options do not result in both efficiencies and simplificati |
1,924 | on. We clarified, where appropriate, that the focus of our report was to identify reform options that could reduce costs or create efficiencies. HUD also commented that the draft report’s discussion of growth in HUD’s outlays could be misleading because this growth reflects only a change in HUD’s disbursement policy and does not relate at all to changes in program costs. Specifically, HUD stated that starting in 2006, the program was required to disburse all eligible funds, instead of the department’s maint |
1,925 | aining those reserves. HUD did not provide any support that outlays reflect only a change in HUD’s disbursement policy and do not relate at all to changes in program costs. While we recognize that disbursement policies may affect outlays, changes in program size and other factors would also affect outlays. Further, although the draft provides information on the trends in actual HUD outlays, it focuses on housing agencies’ expenditures because they are a better measure of what housing agencies are paying in |
1,926 | subsidies to assisted households with vouchers. Therefore, we made no changes in response to this comment. HUD also commented that the draft report did not address HUD’s ongoing efforts to limit the accumulation of subsidy reserves. We added additional language to the report on these efforts, such as the assistance HUD provides to housing agencies in ensuring that all available voucher funds are utilized. HUD noted that it currently provides quarterly reports to the Congressional Budget Office on subsidy re |
1,927 | serve levels. However, these quarterly reports do not include information on the estimated amount of housing agencies’ subsidy reserves that exceed prudent levels, as we are recommending. By providing the estimated amount of excess subsidy reserves, Congress will be better positioned to make informed funding decisions, as we illustrated in our draft report. As agreed with your offices, unless you publicly announce the contents of this report earlier, we plan no further distribution until 30 days from the re |
1,928 | port date. At that time, we will send copies to the Secretary of Housing and Urban Development and other interested committees. In addition, the report will be available at no charge on the GAO Web site at http://www.gao.gov. If you or your staff have any questions concerning this report, please contact me at (202) 512-8678 or [email protected]. Contact points for our Office of Congressional Relations and Public Affairs may be found on the last page of this report. Key contributors to this report are listed i |
1,929 | n appendix III. The objectives of our review were to (1) determine the factors that have affected costs in the Housing Choice Voucher (voucher) program from 2003 through 2011 and the actions Congress and the Housing and Urban Department (HUD) took to manage these costs and (2) identify additional steps HUD, housing agencies, or policy makers can take to limit cost growth in the voucher program and more effectively provide decent, safe, and affordable housing. To determine the factors that have affected cost |
1,930 | s in the voucher program from 2003 through 2011 and the actions Congress and HUD took to manage these costs, we reviewed and analyzed appropriations legislation, budget documents—including HUD budget proposals, Congressional Research Service reports, monthly statements from the Department of the Treasury, and the Office of Management and Budget SF-133 reports on budget execution and budget resources. We also reviewed HUD’s annual guidance on the allocation of the program’s appropriation to housing agencies. |
1,931 | We used these sources to determine the annual appropriations and outlays over the period. The starting year for our analysis reflects the year when Congress began changing the voucher program’s funding formula. We analyzed program data that HUD prepared using information derived from multiple HUD systems including the Central Accounting and Program System (HUDCAPS) and Voucher Management System (VMS) to determine how much housing agencies’ expenditures changed from 2003 through 2010. Specifically, we asses |
1,932 | sed the extent to which certain factors, such as subsidy paid to a landlord, program size (that is, the number of assisted households), and administrative expenses, contributed to the change in program expenditures over this period. We identified these factors by reviewing GAO, HUD, and stakeholder studies. We also reviewed prior work by GAO and others to describe what is known about the cost-effectiveness and characteristics of vouchers relative to other forms of rental housing assistance. To identify addi |
1,933 | tional steps HUD, housing agencies, or policy makers can take to limit cost growth in the voucher program and more effectively provide decent, safe, and affordable housing, we identified and reviewed relevant legislation, draft legislation, and studies. We analyzed HUD’s VMS data on the Net Restricted Assets (NRA) balances (or subsidy reserves) of housing agencies as of September 30, 2011, to determine the extent of housing agencies’ “excess” subsidy reserves. To derive our estimates of the potential “exces |
1,934 | s” balances, we used HUD’s 8.5 percent (about a month) threshold to estimate the excess NRA balance. Also, we analyzed HUD data to determine the number of housing agencies and amount of funding that Congress offset in fiscal years 2008 and 2009 and the additional funding Congress appropriated for and HUD provided to certain housing agencies in 2009. Further, we visited nine housing agencies in Massachusetts. We selected these housing agencies based on Massachusetts’ use of both local and regional housing ag |
1,935 | encies to provide voucher assistance and the housing agencies’ proximity to one another. In addition, we interviewed 31 of the 35 housing agencies participating in the Moving to Work (MTW) demonstration program to identify the activities the agencies had implemented in their voucher programs to reduce program costs and introduce efficiencies in the program. For example, as part of these interviews, we identified alternate rent structures these agencies had implemented or proposed. We also evaluated the cost |
1,936 | and policy implications of three types of programmatic reforms to the voucher program: increasing minimum rents, changing the percent of income tenants pay toward rent, and requiring tenants to pay a percentage of fair market rent. In identifying and assessing these programmatic reforms, we reviewed proposals included in draft legislation and HUD, Congressional Budget Office, and housing industry group reports. We also considered reforms certain agencies have implemented. To estimate the effects of these a |
1,937 | lternative approaches to calculating tenant payments on the subsidy levels that result, we analyzed a December 2010 extract of tenant records from HUD’s Public and Indian Housing Information Center (PIC). These records contain information about participating households, as of December 2010, including information on gross and adjusted income levels, housing unit size and rent, tenant contributions and housing assistance payments, as well as information on age, sex, and disability status of each household mem |
1,938 | ber. To focus on the core of the assisted household population, we examined only those households with five or fewer members, and living in units with one, two or three bedrooms. We determined the elderly and disability status of each household. Specifically, we defined a household as an elderly household if either of the first two household members (the head of household and possibly a spouse or co-head) were age 62 or over, and we placed a household in disability status if any of the five members were ide |
1,939 | ntified as having a disability. For the identified subsidy alternatives, we calculated an alternative tenant contribution using information on income and applicable fair market rent in the PIC file as appropriate, and calculated the resulting assistance payment. (The assistance payment is the difference between the lesser of the payment standard and gross rent, and the tenant payment, subject to any existing minimum tenant payments.) We did not consider the possible effects of any change in household behavi |
1,940 | or, either in terms of continued participation in the voucher program or in choice of housing unit or rent level that could be induced by changes in tenant contributions. In conducting our work, we assessed the reliability of datasets provided by HUD, including data files derived from HUDCAPS, VMS, and PIC. Specifically, we performed basic electronic testing of relevant data elements, such as housing assistance payment amounts, total tenant payment, and unit months leased. We reviewed HUD’s data dictionarie |
1,941 | s, instructions, and other relevant documentations. We also interviewed HUD officials knowledgeable about the data to obtain clarifications about key variables and calculation rules. Where possible, we compared our results with other sources to ensure the reasonableness of the information. We determined that the data were sufficiently reliable for the purpose of this report. Finally, for all of our objectives, we interviewed HUD officials and consulted with one academic and officials from various housing gr |
1,942 | oups including the Center on Budget and Policy Priorities, Council of Large Public Housing Authorities, National Low-Income Housing Coalition, National Association of Housing Redevelopment Officials, Public Housing Authorities Directors Association, Quadel Consulting, and the Urban Institute. Further, we contacted 53 housing agencies that administer the voucher program. In selecting these housing agencies, we considered the number of authorized vouchers, location (that is, HUD-defined regions), and leasing |
1,943 | and spending rates for the voucher program as of March 2011. We conducted this performance audit from February 2011 through March 2012 in accordance with generally accepted government auditing standards. Those standards require that we plan and perform the audit to obtain sufficient, appropriate evidence to provide a reasonable basis for our findings and conclusions based on our audit objectives. We believe that the evidence obtained provides a reasonable basis for our findings and conclusions based on our |
1,944 | audit objectives. In addition to the contact named above, Daniel Garcia-Diaz, Acting Director; Stephen Brown, William Chatlos, Karen Jarzynka-Hernandez, Cory Marzullo, John McGrail, Josephine Perez, and Barbara Roesmann made key contributions to this report. |
1,945 | The UI program was established by Title III of the Social Security Act in 1935 and is a key component in ensuring the financial security of America’s workforce. This complex program, which is administered jointly by the U.S. Department of Labor and the states, provides temporary cash benefits to workers who lose their jobs through no fault of their own. The program also serves to stabilize the economy in times of economic recession. Labor is responsible for overseeing the UI program to ensure that the state |
1,946 | s operate an effective and efficient Unemployment Insurance Program. Labor is also responsible for monitoring state operations and procedures, providing technical assistance and training, as well as analyzing UI program data to diagnose potential problems. To oversee the program, Labor’s Employment and Training Administration maintains 10 offices in 6 geographic regions that are responsible for working with states in a specific geographic area (see fig.1). The regional offices are the states’ main point of |
1,947 | contact with Labor and serve as a vital link between headquarters and the states for providing technical assistance and clarifying program policies, objectives, and priorities. Moreover, the regional offices have primary responsibility for overseeing the fiscal and management integrity of the UI program. Although Labor provides oversight and guidance to ensure that each state operates its program in a manner that is consistent with federal guidelines, the federal-state structure of UI places primary respons |
1,948 | ibility for administering the program on the states. The states also have wide latitude to administer their UI programs in a manner that best suits their needs within the guidelines established by federal law. For example, to enhance the efficiency and cost-effectiveness of their UI systems, many states have established centralized service centers that allow claimants to apply for benefits by telephone, fax, or the Internet. The UI program is funded through federal and state taxes levied on employers. The s |
1,949 | tates collect the portion of the tax needed to pay unemployment insurance benefits, whereas state and federal administrative costs and other related federal costs of the UI program are financed through the federal tax. Labor holds these funds in trust on behalf of the states in the Unemployment Trust Fund of the U.S. Treasury. To obtain annual UI administrative funding from Labor, states submit an annual request for funding as part of their State Quality Service Plan (SQSP). Labor reviews each state’s plan |
1,950 | and subsequently determines if any adjustment in funding is required. The regional offices may also negotiate changes and revisions to the states’ funding requests before the final allocation is approved. In fiscal year 2001, Labor provided about $2.3 billion to states to administer their programs. To be eligible for UI benefits in most states, unemployed workers must fulfill five general conditions within overall federal guidelines. They must: have worked for a specified amount of time in a job that is cov |
1,951 | ered by the unemployment insurance program; have left their prior jobs involuntarily (such as by employer layoff) or have quit their jobs for “good cause”; be currently “able and available” for work, and, in most states, actively enroll in employment services or job training programs (in some be legally eligible to work—for example, noncitizens must be lawfully admitted to work in the United States, or lawfully present for other reasons. Each state’s laws provide specific requirements for claimants to meet |
1,952 | these general conditions, and each state determines individual eligibility, the amount and duration of benefits, and disqualification provisions. Because Labor provides states with the flexibility to design their own UI program, the eligibility policies and laws governing the administration of the UI program vary from one state to another. In general, however, claimants apply for UI benefits over the telephone, via computer using the Internet, or in person at a local office. State claims representatives are |
1,953 | responsible for determining each claimant’s eligibility for UI benefits by gathering and (when possible) verifying important information, such as their identity, employment history, why they no longer are working, and other sources of income they may have. Once the claim has been submitted for processing, the state sends forms to the claimant’s employer(s) requesting them to verify the claimant’s wages and the reason they are no longer working. If the individual’s claim for UI is approved, the state then d |
1,954 | etermines the amount of UI benefits, depending on the individual’s earnings during the prior year and other factors. UI benefits may be mailed to a claimant’s home or post office box, or sent electronically to a bank account. In general, most states are expected to provide the first benefits to the claimant within 21 days of the date the state determined that the claimant was entitled to benefits. Labor funds two principal kinds of activities for detecting and measuring UI overpayments at the state level—Be |
1,955 | nefit Payment Control and Benefit Accuracy Measurement. Each state is required to operate a benefit payment control division that is responsible for detecting and recovering overpayments. This process also involves reporting the reason for the overpayment—such as wages that the claimant failed to report. Each state is required to report overpayments along with other data to Labor on a quarterly basis. By contrast, Labor’s benefit accuracy measurement data are an estimate of the total overpayments in the UI |
1,956 | program—in each state and the nation as a whole—based on a statistically valid examination of a sample of paid and denied claims. Benefit accuracy measurement is one of the main quality assurance systems that Labor uses to measure payment accuracy in the program. Of the $30 billion in UI benefits paid nationwide in 2001, Labor estimates that about $2.4 billion in UI overpayments occurred. About one-quarter of these overpayments ($577 million) were identified as fraud, according to its quality assurance data |
1,957 | . Overpayments may occur because individuals work while receiving benefits, fail to register for employment services, fail to look for a new job, or misrepresent their identity. Other sources of overpayments include agency errors and inaccurate or untimely information provided by employers. Of the $2.4 billion in projected overpayments, Labor estimates that about $1.3 billion could have potentially been detected and/or recovered in 2001 given existing state procedures and policies. In contrast, the states r |
1,958 | eported that $650 million in overpayments were made in 2001, of which $370 million was actually recovered. Overall, Labor’s overpayment estimate is about three times higher than that reported by the states. The difference in the overpayment figures produced by the two systems can be attributed to the fact that Labor’s quality assurance estimate is based on a more comprehensive examination of individual UI claims than the states’ benefit payment control activities can generally produce. Our analysis suggests |
1,959 | that Labor’s quality assurance system estimate is a more complete assessment of the true level of overpayments in the UI program, partly because the system documents overpayments that often cannot be detected in many states using their existing benefit payment control procedures. Over the past 10 years, the annual overpayment rate estimated by Labor’s quality assurance system has remained fairly constant as a percentage of total benefits paid—ranging from a low of 8.0 percent in 2001 to 9.2 percent in 1999 |
1,960 | and averaging about 8.5 percent during that period. Overpayments averaged about $1.8 billion per year and reaching a high of about $2.4 billion in 2001. (See fig. 2.) The slight increase in overpayments estimated by the quality assurance system in 2001 is likely related to the overall increase in total UI benefits paid that year. The overpayments estimated by Labor’s quality assurance data fall into a number of categories. Some overpayments result from errors in claimants’ reporting or the state agency’s r |
1,961 | ecording of important eligibility information, such as wages or other sources of income that a claimant obtained while receiving UI benefits (“benefit year earnings” violations). (See table 1.) Overpayments also occur because claimants are not able and/or available to work, fail to register for employment services as required by their state, or fail to look for a new job as required (“eligibility” violations). (See app. I.) The quality assurance data also classify overpayments as being “fraud” or “nonfraud” |
1,962 | . Fraud can occur when claimants intentionally misrepresent eligibility information, employers file fraudulent claims, or state UI program personnel abuse sensitive information such as social security numbers for personal gain. Of the total overpayments estimated by Labor in 2001, about $577 million (24 percent) were attributed to fraud. Although this estimate takes into account each state’s individual laws, we found that the states differ substantially in how they define fraud. For example, some states may |
1,963 | include overpayments resulting from unreported earnings as fraud, while other states do not. Thus, state-to-state comparisons of the level of fraud in the UI program and the activities that constitute fraud are difficult to make. Overall, the largest overpayment categories in 2001 were attributed to eligibility issues (35 percent), benefit year earnings (31 percent), and separation issues (21 percent). Federal and state officials told us that some categories of overpayments are more difficult to detect tha |
1,964 | n others. For example, some officials told us that it can be difficult for states to accurately determine, in a cost-effective manner, if a claimant is actively searching for a job (an eligibility requirement in some states). In particular, there is not a readily available source of information that states can access for information on whether each claimant is actively looking for employment. Work search requirements vary considerably from state to state, and can have a substantial impact on state payment a |
1,965 | ccuracy rates. Moreover, states generally lack sufficient resources to permit their benefit payment control personnel to conduct in-depth examinations of each claimant’s activities to determine if they are eligible. States that have only a limited work search requirement (or no requirement at all) may not establish overpayments for UI claimants who fail to look for a new job. In contrast, states with rigorous work search policies are more likely to establish overpayments for claimants who do not meet this r |
1,966 | equirement. Although some categories of overpayments are more difficult than others to detect or recover, Labor’s analysis suggests that the states could have potentially detected and recovered about $1.3 billion (54 percent) of the $2.4 billion in estimated overpayments in 2001. This estimate is based on Labor’s analysis of the types of overpayment errors the states’ benefit payment control operations were most likely to be able to identify and recover given their current policies and procedures. (See tabl |
1,967 | e 2.) In particular, states’ benefit payment control activities tend to focus on detecting overpayments that result from unreported income (benefit year earnings or base wage period violations) and payments to individuals who are not entitled to UI benefits due to the circumstances under which they became unemployed (separation issues). For example, benefit payment control staff may use the “Wage/Benefit Crossmatch” to identify and examine claimants who received UI benefits during a week in which they appea |
1,968 | r to have earned wages. Labor’s analysis also suggests that other types of overpayments are likely to be detected by most states given their current policies and procedures. These include unreported or underreported income from social security programs, illegal aliens claiming benefits, and unreported vacation or severance pay. Furthermore, based on Labor’s analysis, we believe that a substantial proportion of the overpayments detected by the states could be recovered using commonly available procedures suc |
1,969 | h as offsetting claimants’ current and future benefits and intercepting other sources of income such as state tax refunds. Labor determined that the remaining $1.1 billion in estimated overpayments could probably not be detected or recovered by the states due to limitations in their existing policies and procedures. For example, overpayments caused by state agency errors are generally not pursued for recovery. In contrast to Labor’s estimate, the states reported about $653 million in overpayments in 2001—ro |
1,970 | ughly half the total that Labor’s quality assurance system identified. Moreover, at the time of our review, the states reported that they had recovered about $370 million of this amount. The quality assurance and the benefit payment control systems differ in the scope and the methods of the activities they use to identify overpayments. On the basis of our analysis as well as analysis performed by Labor’s Division of Performance Management, we believe that Labor’s quality assurance system data represent a mo |
1,971 | re complete assessment of the true level of UI overpayments than the benefit payment control figure reported by the states. In particular, the quality assurance system is able to estimate all the potential overpayments that have occurred in each state’s UI program because it is based on a statistically valid sample of UI claims from each state. Moreover, quality assurance investigators are able to conduct a more detailed, comprehensive analysis of each case they review than is typically possible for most st |
1,972 | ates’ benefit payment control operations. For example, the investigator is generally able to identify many types of overpayments because they can spend more time verifying the accuracy of the information provided to the state by personally contacting employers, claimants, and third parties. In addition, investigators typically spend between 5 and 8 hours examining a single case, which allows them to perform a relatively in-depth review of a claimant’s eligibility. By contrast, the states’ benefit payment co |
1,973 | ntrol activities are often affected by operational and policy factors that limit their ability to detect and/or recover overpayments. These factors include limited staffing and funding, cost-benefit considerations (e.g., the costs associated with recovering an overpayment may be greater than the overpayment amount), and a lack of access to timely data sources. Moreover, benefit payment control personnel are required to quickly examine thousands of cases to identify overpayments, thus potentially limiting th |
1,974 | eir ability to thoroughly review cases for payment accuracy. We identified various management and operational practices at both the state and federal level that contribute to UI overpayments. At the state level, we found that a number of states place primary emphasis on quickly processing and paying UI claims and may not take the necessary steps to adequately verify claimants’ initial and continuing eligibility for benefits. In particular, five of the six states we visited were not fully staffing their bene |
1,975 | fit payment control operations and had moved staff to claims processing activities. In addition, while some of the states we visited use automated data sources to determine if claimants are working or obtaining other benefits while receiving UI, others rely heavily on self-reported information from claimants to make payment decisions. States also tend to establish UI program policies and priorities in response to direction from the Department of Labor, which in some instances may contribute to overpayments. |
1,976 | For example, the performance measures that Labor uses to gauge states’ operations tend to emphasize payment timeliness more heavily than payment accuracy. In addition, Labor has been reluctant to link the states’ performance on payment accuracy to the annual administrative funding process as a way of holding states accountable for performance. Labor has taken some actions to improve UI program integrity, such as working to obtain additional automated data sources that could help states make more accurate e |
1,977 | ligibility decisions and developing a payment accuracy performance measure. However, Labor and the states have not placed sufficient emphasis on balancing the often competing priorities of quickly processing and paying UI claims, with the need to ensure that only eligible individuals receive benefits. The emphasis that an agency places on critical program activities can be measured, in part, by the level of staff and other resources devoted to those activities. Most of the states we visited placed primary e |
1,978 | mphasis on quickly processing and paying UI claims, with less attention given to program integrity operations. In particular, we found that program managers commonly moved staff assigned to program integrity activities (such as benefit payment control) to claims processing positions in response to increases in the number of UI claims being filed. For example, one state was using only 4 of the 16 positions (25 percent) it was allotted by Labor for benefit payment control. Only one of the six states we visite |
1,979 | d was fully staffing its benefit payment control operations. The remaining states had transferred staff into other positions, including claims processing. Another state stopped drawing its quality assurance sample for a period of time and moved staff responsible for these operations into claims processing positions when unemployment claims increased during the third quarter of 2001. Many federal and state officials we interviewed told us that states move staff into claims processing roles from other positio |
1,980 | ns because they lack adequate funding to properly administer all the necessary activities of their UI programs. In this regard, some state officials told us that they anticipated additional funding from the federal government which they could use to increase the resources and staff dedicated to benefit payment control and other program integrity operations. However, a number of officials told us that historically the UI program’s primary objective has been to pay claimants in the most expeditious manner pos |
1,981 | sible, and that this would continue to be a guiding principle of the program. While states differed in the level of staff and resources devoted to program integrity activities, we also found variation in the processes and tools they used to verify information that could affect a claimant’s eligibility for UI benefits. The most important information requiring verification generally includes an individual’s wages and employment status, receipt of other federal or state benefits, identity, and citizenship stat |
1,982 | us. All of the states we visited conduct basic computer matches that help them to detect potential UI overpayments due to unreported earnings. For example, each state regularly conducts a Wage/Benefit Crossmatch that compares the database of UI claimants with the state’s database of individuals’ wages to identify UI recipients who may have unreported income in the same state in which they are receiving UI benefits. Labor and the states generally view this match as an effective tool for identifying claimants |
1,983 | who may have unreported wages within the state. However, because state wage data are only available quarterly, the crossmatch relies on information that may be several months old by the time the match is conducted. This delay allows some overpayments to remain undetected for a long period of time. Officials at Labor and in some states emphasized that overpayments are more likely to be recovered if they can be detected quickly. In general, the states tend to recover a substantial proportion of the overpayme |
1,984 | nts they detect by offsetting a claimant’s current and future UI benefits. Because UI benefits tend to be paid out over a relatively short period of time—about 14 weeks on average—overpayment detection and recovery activities may begin long after individuals leave the UI rolls. This inability to obtain timely eligibility information places the program at substantial risk for overpayments that may never be recovered. More timely sources of data than the Wage/Benefit Crossmatch exist to verify a claimant’s em |
1,985 | ployment status, such as the State Directory of New Hires (referred to as the “state new hires database”). The states’ new hires databases can provide information on individuals’ current employment status, and have been found to be effective in preventing or reducing the amount of UI overpayments. However, we found that this data source is not routinely used in all states. For example, two of the states we visited do not currently use their new hires database to verify claimants’ earnings or employment stat |
1,986 | us. Officials in one state told us that they currently lacked access to the state’s new hires database (but are seeking access), while those in another state questioned the cost- effectiveness of its use. However, other states that use this data source have reported that it is helpful in detecting overpayments more quickly than the Wage/Benefit crossmatch. For example, one state reported that because the new hires data detects overpayments earlier than other detection methods, the size of its average overpa |
1,987 | yment at the time of detection has been reduced from about $2,800 to roughly $750. Moreover, the same state reported that it detected about 6,700 overpayments totaling over $4 million using its new hire database between July 2000 and December 2001. Overall, use of the new hire database in this state accounted for more than 35 percent of all instances of overpayments detected during that period. Another state reported increased overpayment collections of about $19 million over 4 years, in part due to earlier |
1,988 | detections from the new hires database. Labor’s OIG has identified the new hire database as a potentially useful tool for detecting overpayments resulting from unreported income, which makes up a substantial portion of the total overpayments estimated by the quality assurance system each year. Although Labor has encouraged each state to use its own new hires database for purposes of administering their UI program, we found that nationally a number of states still do not use this data source. While the stat |
1,989 | es’ directory of new hires data are useful for verifying claimants’ employment status, a main limitation is that they only identify this information for claimants within a given state. To detect unreported or underreported wages in other states, some states also use various types of interstate matches that are facilitated by Labor. One match (called the “Interstate Crossmatch”) is conducted quarterly by most states for all UI claims and is designed to detect claimants who may have wages in another state. Ho |
1,990 | wever, this match typically relies on wage data that are typically about 4 to 6 months old and, therefore, is of limited use in determining claimants’ initial eligibility for benefits. The states may also use another type of match called the “Interstate Inquiry.” This system allows a UI claims representative to check a claimant’s UI and employment status in other states. However, officials at Labor and the states we visited told us that this system is generally only used if the claims representative is susp |
1,991 | icious about the validity of the claim. Moreover, the system can only be used to check individual claimants and is not designed to verify the status of large numbers of claimants simultaneously. Finally, two of the states we visited periodically conduct their own matches with bordering states. However, this method generally requires individual states to develop formal data sharing agreements with one another, which can be time-consuming and cumbersome. To enhance the ability of states to verify the status o |
1,992 | f claimants who could be working or receiving UI benefits in other states, many of the officials we spoke with advocated giving states access to the Office of Child Support Enforcement’s National Directory of New Hires (NDNH). The NDNH is a comprehensive source of unemployment insurance, wage, and new hires data for the whole nation. However, current law limits access to the NDNH and does not permit individual states to obtain data from it for purposes of verifying claimants’ eligibility for UI. Moreover, o |
1,993 | ur prior work examining the NDNH has revealed concern among some federal officials that wider access to the database could jeopardize the security and confidentiality of the information it contains. One possible alternative to the NDNH suggested by federal and state officials for tracking interstate wages and UI benefit receipt is the Department of Labor’s Wage Record Interchange System (WRIS). This system, which was developed in response to the Workforce Investment Act (WIA) of 1998, is a “data clearinghou |
1,994 | se” that makes UI wage records available to states seeking employment and wage information on individuals in other states. Certain federal officials and others familiar with WRIS told us that with some modification—such as incorporating the more timely new hires data from the states—WRIS could be a logical alternative to the NDNH because the computer network for sharing data among the states already exists. However, one official familiar with the system noted that while it contains the necessary data to sho |
1,995 | w whether a claimant is earning wages in another participating state, it currently lacks important pieces of information (such as states’ new hires data) that would make it most useful as an interstate verification tool. Moreover, in a recent report, we noted that some states have been reluctant to become involved with WRIS, partly because of concerns about the cost of administering the system. Furthermore, we noted that if not all states participate, the value of WRIS will be diminished—even for participat |
1,996 | ing states—because no data will be available from nonparticipating states’ UI wage records. This is an area where Labor could potentially play a larger role. In particular, Labor could explore options for enhancing WRIS as an overpayment detection tool and facilitating states’ participation in any modified system. Although modifying existing systems and obtaining access to new, more timely data sources may entail additional costs for Labor and the states, our review and prior work in other programs suggests |
1,997 | that the potential savings in program funds could outweigh these costs. Claimants’ eligibility for UI benefits may be affected if they are receiving benefits from other state or federal programs. For example, claimants in some states are ineligible for UI benefits, or they may receive reduced benefits if they are receiving workers’ compensation. Overpayments can occur if claimants do not accurately report the existence or amount of such benefits when they apply for UI, or if the state employment security a |
1,998 | gency fails to verify the information in a timely manner. Only two of the six states we visited verify claimants’ receipt of workers’ compensation using independent sources of information. Moreover, at least one of these states only checks for receipt of workers’ compensation if the claimant self-reports that he or she is currently receiving such benefits. Similarly, receipt of some federal benefits such as cash payments from Social Security programs may affect a UI claimant’s eligibility for or amount of b |
1,999 | enefits. For example, one state’s policy manual requires claims representatives to ask claimants if they are currently receiving Social Security Disability Insurance (DI) or Old Age and Survivors Insurance (OASI) benefits, which could reduce or eliminate the amount of UI benefits they are eligible to receive. If a claimant states that he or she is not receiving DI benefits, then no further actions are taken to independently verify this information. Labor’s quality assurance data estimates that in 2001, abou |
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