Background CHIP Variation States have three options for designing their CHIP programs: Medicaid expansion CHIP, separate CHIP, and combination CHIP. Medicaid expansion CHIP. States may operate CHIP as an extension of their Medicaid programs. Under Medicaid expansion CHIP, states expand income eligibility levels for children beyond those of the state’s Medicaid program. Medicaid expansion CHIP programs must follow Medicaid rules, including providing all Medicaid covered benefits to enrolled children. Separate CHIP. States may operate their CHIP programs separate from their Medicaid programs. In so doing, the states are not required to follow the same rules as Medicaid; thus, these states have some additional flexibility in designing CHIP, such as determining which benefits to offer and how, if at all, to charge premiums. Combination CHIP. States may have a combination program, where they operate a separate CHIP program, as well as a Medicaid expansion CHIP program, each for a different population of children. For example, some states that operate combination CHIP programs apply different age or income eligibility requirements for their Medicaid expansion CHIP and separate CHIP programs. Similar to Medicaid, CHIP program expenditures are shared between the states and the federal government, but federal matching rates for CHIP are higher than for Medicaid and federal funding for CHIP is capped, with states receiving annual CHIP allotments. The type of CHIP program a state designs may affect the amount of federal funding available to that state in the event the state exhausts available CHIP funding for the year. A state with a Medicaid expansion CHIP program that exhausts available CHIP funding may apply Medicaid funds at the Medicaid matching rate to remaining expenses for enrolled children for that year. However, a state with a separate CHIP program that exhausts available funding would not have access to such funding. In general, states administer CHIP under broad federal requirements that permit flexibility in how they design their programs, including in the services they cover, their upper income eligibility limits, and the fees they charge to participate. In terms of income eligibility, as of January 2019, 19 states, including the District of Columbia, had CHIP upper income eligibility limits of 300 percent of the FPL or higher compared with 32 states whose CHIP upper income eligibility limits were below 300 percent of the FPL. (See fig. 1.) In addition, states can charge beneficiaries fees for CHIP coverage. These fees can vary depending on whether they are enrollment fees, premiums, or other types of cost sharing. Among the states that charge CHIP premiums, the premiums can vary based on family income and the number of children in CHIP. (See table 1.) Although states may charge premiums or have other cost sharing, according to CMS, CHIP provides more affordable coverage than is generally available in the private health insurance market. CHIP Crowd-Out CHIP crowd-out may occur when employers modify or decide not to offer health insurance to their employees or to their dependents, because of CHIP availability. For example, employers who are aware of CHIP may decide not to offer health insurance to employees or their dependents due to concerns about the costs of providing insurance, especially for smaller sized firms, or as a result of changes in federal or state policies, such as requirements resulting from PPACA. Crowd-out may also occur when employees drop or decide not to enroll in insurance offered by their employers and enroll their children in CHIP, because of CHIP availability. As we have identified in prior work, assessments of the potential for crowd-out must take into account an understanding of the extent to which private health insurance is available and affordable to low-income families who qualify for CHIP. National survey results show that private health insurance is the most prevalent source of insurance for children; however, there is substantial variation across states in coverage rates. Additionally, the extent to which employers offered individuals insurance varies by family income. For additional information on factors that may affect crowd-out, see appendix I. For information on sources of health insurance for children under age 19, including CHIP and employer sponsored insurance, see appendix II. The type of CHIP program a state designs affects its responsibilities for monitoring and mitigating the potential for CHIP crowd-out. The 42 states with separate CHIP programs—including those in combination CHIP states—are required to submit CHIP plans that describe reasonable procedures to prevent crowd-out and to report annually to CMS on certain crowd-out related indicators, such as the number of CHIP applicants with access to private health insurance; however, CMS provides states flexibility to decide which crowd-out prevention procedures to use. For example, states can require CHIP applicants to undergo a period of uninsurance prior to enrollment, known as a waiting period, to deter families that have access to private health insurance from dropping that insurance to enroll in CHIP. In contrast, states are not required to take steps to prevent crowd-out for their Medicaid expansion CHIP programs and may only do so if consistent with the Medicaid statute, or if under an approved section 1115 demonstration, which allows states to implement policies that waive certain Medicaid requirements. For states with separate and combination CHIP programs, CMS provides general guidance for minimizing crowd-out, which the agency has modified over time. (See table 2 for a description of the crowd-out related responsibilities.) For example, in 2013, CMS issued regulations to align with a PPACA provision for health plans and health insurance issuers that limited waiting periods to a maximum of 90 days, and established mandatory waiting period exemptions. The regulations also eliminated the application of a CHIP policy requiring that states with separate CHIP programs have different crowd-out prevention procedures in place for children at different income levels. In making this change, CMS noted that available research called into question the prevalence of crowd-out. CMS indicated that its policy still required states to monitor crowd-out and, if a high rate of crowd-out were to occur, states should consider implementing prevention procedures, such as public outreach about other health care options available in the state. In response to crowd-out related recommendations we made in 2009, CMS modified its guidance to collect additional information from states in their 2009 through 2013 annual reports on how they assess the availability and affordability of private health insurance for CHIP applicants. For example, from 2009 through 2013, states were required to report to CMS if the state’s CHIP application asked if applicants had access to private health insurance. Additionally, states that operated a waiting period without affordability exceptions were asked if the state collected data on the cost of health insurance for an individual or family. However, CMS officials stated that the agency eliminated the questions regarding affordability of private health insurance in 2013, as part of efforts to update the electronic system states use to submit their CHIP annual reports to reflect PPACA enrollment simplification and coordination requirements. CMS officials said some of the questions were duplicative of other state reporting requirements and other questions were deemed irrelevant in light of the establishment of affordability exceptions to waiting periods. Limited Information Exists on the Extent of CHIP Crowd-Out States reported indicators of potential crowd-out to CMS in their annual reports, although some do not report on these indicators and those that do may calculate them differently. The states also varied in the extent to which they have processes for directly estimating crowd-out; however, CMS officials and officials in selected states told us they understand the occurrence of crowd-out to be low. Further, we identified few published research studies that directly estimated crowd-out; each used different methodologies, resulting in varied estimates. Some States Report Information on Two Indicators of Potential CHIP Crowd-Out; One Selected State Directly Measures Crowd-Out States with separate CHIP programs—including those in combination states—are required to annually report indicators of potential crowd-out; states must also describe in their CHIP plans other indicators of potential crowd-out they collect. CMS’s 2017 CHIP annual report asks these states to report on crowd-out related questions, including two indicators of crowd-out: (1) the percentage of individuals who enrolled in CHIP that have access to private health insurance, and (2) the percentage of CHIP applicants who cannot be enrolled, because they have private health insurance—an indicator of potential crowd-out averted. However, not all states with separate CHIP programs track and report information related to these two indicators of potential crowd-out, and those that do may calculate these indicators differently. For example, of the 42 states with separate CHIP programs, the 2017 annual reports showed the following: Four of the 42 states reported that they tracked the number of individuals who have access to private health insurance; the remaining 38 states either did not report tracking this information or did not respond to this question. Of the four states tracking this information, the percentages reported ranged between 0.5 percent and 7 percent of CHIP applicants who have access to private health insurance. Twenty-one of the 42 states reported that they tracked the percentage of applicants who could not be enrolled in CHIP because they were enrolled in private health insurance; the remaining 21 states did not report this percentage to CMS. This is a measure of crowd-out averted due to state oversight of its enrollment process. The percentages reported by the 21 states tracking this information ranged from 0 percent in several states to 18 percent in one state. Among the states that reported they do not track individuals with access to private insurance and did not provide a percentage of applicants not enrolled in CHIP because of enrollment in private health insurance, five states indicated that either their electronic eligibility systems did not allow them to capture this information or the data to report this information were not available. CMS officials acknowledged that not all states report on these indicators; however, they noted that states operating separate CHIPs have other processes in place to prevent children with other health insurance from enrolling in CHIP. Further, some states that operate separate CHIP programs describe approaches for directly estimating crowd-out in their CHIP plan amendments. The results of these estimates are not reported to CMS unless they reach a threshold defined by each state. In 2013, CMS required separate CHIP states to submit state plan amendments to CMS to update their eligibility-related policies, including their crowd-out prevention procedures. In response, 17 of the 42 states submitted these amendments and described approaches they would use to directly measure crowd-out. For example: Colorado reported conducting a biennial survey to estimate the percentage of enrollees who dropped group health insurance without good cause to gain eligibility for CHIP, according to its CHIP plan. Connecticut reported comparing the number of children denied CHIP enrollment because they were enrolled in private health insurance to those same applicants who reapplied for CHIP 6 months later, but did not have private health insurance. The crowd-out threshold defined by Colorado and Connecticut is 10 percent; therefore, if these states’ crowd-out estimates were to exceed 10 percent, each state would collaborate with CMS to identify other procedures to reduce crowd-out. According to CMS officials, no state using this approach to estimate crowd-out has exceeded the percentages established or expressed concerns with crowd-out. States we interviewed varied in the extent to which they estimate crowd- out; however, most states did not view crowd-out to be of concern. Among our six selected states with separate CHIP programs, one state— New York—directly measures crowd-out. New York asks applicants that dropped their private insurance in the last three months the reasons why they dropped this coverage, which includes responses such as the family’s preference for the child to have CHIP benefits over their previously held private health insurance. New York state officials told us they consider instances of crowd-out to include when individuals drop private insurance because CHIP costs and benefits are more favorable. For the last 9 months of 2014, the officials estimated crowd-out in New York to be about 1.9 percent. If New York estimates crowd-out to be higher than 8 percent, state officials told us they will report this to CMS and work with CMS on implementing additional crowd-out prevention procedures. Officials from the other five selected states said they do not actively measure crowd-out, some of them citing limited resources and difficulties developing estimates, and noted that crowd-out was not a high priority for them, because they did not think crowd-out was prevalent in their states. For example, officials from two states said they had not heard any concerns regarding crowd-out from their state legislature, state insurance agencies, or others. CMS officials also told us that no state had reported concerns about crowd-out. Research on CHIP Crowd- Out Is Limited, Used Different Methods, and Resulted in Varied Estimates; Researchers and Others Identified Challenges in Making Such Estimates Our review identified few research studies that directly estimated CHIP crowd-out. Specifically, we identified three research studies published from 2013 to 2018; each used different methods and arrived at varying estimates of crowd out. One study estimated crowd-out across 15 states that expanded their CHIP income eligibility requirements between 2008 and 2012 by examining health insurance enrollment changes in a sample of children after they became newly eligible for CHIP. This study estimated that public insurance among children under age 19 increased about 2.9 percentage points during this period, and private insurance decreased by 1.8 percentage points. The study reported that 63 percent of the 2.9 percentage point increase in public insurance was due to crowd-out. The researchers also produced state-level estimates for the effects of CHIP income eligibility expansions on insurance coverage in newly eligible children. These estimates varied by state, suggesting that crowd-out also varies by state. In particular, three states had an increase in public insurance ranging from about 4 to 12 percentage points, and three states had a decrease in private insurance that ranged from about 7 to 14 percentage points. The researchers noted they did not account for factors that may have caused privately insured individuals to increase their use of public insurance, such as changes in the affordability of private health insurance. Another study estimated the effect of CHIP income eligibility expansions on crowd-out in Illinois. This study examined the differences in public and private health insurance between children in Illinois, where CHIP income eligibility was expanded, and children from a combination of other states that did not expand CHIP—and were chosen to resemble the demographic characteristics and health insurance profile of Illinois. This study found a 6.5 percentage point increase in CHIP enrollment in 2010 among families between 200 percent and 300 percent of the FPL, and estimated that 35 percent of this increase in CHIP enrollment was due to crowd-out. At other income levels higher than 300 percent of the FPL, the study found either no net effect on private health insurance, or an increase. The third study estimated public and private insurance under different CHIP income eligibility thresholds and different premium schedules. While the study estimated that a CHIP expansion from 200 to 400 percent of the FPL with no premium contribution and a 4 month waiting period increased CHIP enrollment by about 4.5 percentage points and decreased private coverage by about 2.2 percentage points, these estimates do not provide evidence of crowd-out, because the differences in these percentage point estimates were not statistically significant. Although not reporting direct estimates of CHIP crowd-out, we identified other studies that provide related information. For example: In one study, researchers surveyed the parents of current and former CHIP enrollees in 10 states to examine access to private coverage for children enrolled in CHIP. This study found that about 13 percent of new CHIP enrollees had private health insurance in the year before enrolling in CHIP. Among the 13 percent, about 18 percent reported that they dropped their private health insurance, because CHIP was more affordable, and about 5 percent dropped their private health insurance, due to a preference for CHIP. The authors noted that access to private coverage among CHIP enrollees is low and when access is available, affordability is a serious concern for parents. The authors concluded that this suggests limited potential for crowd-out. A study published in 2015 that surveyed the parents of about 4,100 new CHIP enrollees to understand why children enrolled in CHIP, among other things, found that 35 percent of these parents reported applying for CHIP, because it was more affordable than the other health insurance options they could obtain for their children. Representatives from national organizations, researchers, and CMS officials we interviewed noted some of the challenges measuring the extent of CHIP crowd-out, including the limitations of available data sources; however, they did not consider crowd-out to be prevalent. For example: Some data sources do not separately collect or categorize CHIP information. For example, the ACS does not specifically ask respondents if their children have health insurance through CHIP; thus, researchers have to manipulate the data to separate CHIP coverage from other forms of public health insurance, such as Medicaid. The methodologies available to separate CHIP from Medicaid respondents have many limitations, according to researchers and U.S. Census Bureau officials we contacted. Accurate crowd-out estimates require researchers to account for the reasons why someone dropped his or her health insurance and enrolled in CHIP, and this information is not captured by national surveys. Researchers may also vary in what they consider to be crowd-out; for example, some may not consider dropping private health insurance and enrolling a child in CHIP because of a job loss or change in employment to constitute crowd-out. Others do not consider it to be CHIP crowd-out when parents drop their private health insurance and enroll in CHIP, because CHIP is more affordable. CMS officials also noted complexities in measuring crowd-out—such as variation in definitions of crowd-out and methodologies for measuring it—and they said that the agency has not conducted or commissioned its own evaluation. However, CMS officials reiterated that no state has reported concerns with crowd-out and based on their review of studies conducted by researchers understand that its prevalence is likely low. CMS Tracks States’ Procedures to Address Potential CHIP Crowd-Out; States Ask Applicants about Other Sources of Coverage and Use Cost-Sharing Provisions CMS monitors states’ CHIP crowd-out prevention procedures and offers technical assistance, while states ask CHIP applicants about other sources of health care coverage, and use waiting periods and cost- sharing procedures, such as enrollment fees and premiums. Several state officials we interviewed told us that their crowd-out prevention procedures are effective; however, they could not speak to the effectiveness of any particular procedure and few studies have examined the issue. CMS Tracks States’ CHIP Crowd-Out Procedures Primarily to Identify Inconsistencies in States’ Reporting and Provide Technical Assistance upon Request CMS officials told us that they track the information states submit about their CHIP crowd-out prevention procedures as part of their annual report review process to identify any inconsistencies between the information contained in their state plans and the information submitted in states’ annual reports, among other reasons. When CMS officials identify any noticeable differences in the information reported by states from year-to- year in the annual reports—such as the percentage of CHIP applicants with access to private insurance—they told us they follow-up with the state to obtain additional information about these differences, and, if needed, advise states on ways they can prevent crowd-out. CMS officials also told us they provide technical assistance, when requested, to assist states in developing crowd-out prevention procedures. For example, CMS officials said they provided states with technical assistance after issuing regulations in 2013 on the use of waiting periods that also required states to update their state plan amendments. CMS officials said they have no plans to develop additional strategies for collecting states’ crowd-out information, because states have not reported crowd-out to be a concern, and there is no need to re-examine states’ oversight if prevalence as measured in research is likely low. All States with Separate CHIP Programs Reported Implementing at Least One CHIP Crowd-Out Prevention Procedure, Such as Cost Sharing All 42 states with separate CHIP programs reported to CMS that they had implemented at least one of the following six types of procedures to prevent crowd-out: (1) asking about other health insurance and denying CHIP coverage if other sources of health insurance are identified; (2) implementing cost sharing for CHIP coverage; (3) conducting database checks for other health insurance; (4) implementing a waiting period for CHIP coverage; (5) measuring crowd-out and taking steps if certain thresholds are exceeded; and (6) offering premium assistance for private health insurance. The majority of these states (36 of the 42 states with separate CHIP programs) implemented at least three crowd-out procedures. All 42 states with separate CHIP programs asked applicants about other insurance coverage on their CHIP applications to deny applicants CHIP coverage if private insurance coverage was found, and CMS officials told us that 35 of those states required CHIP enrollees to pay premiums or make other financial contributions to the cost of the coverage. (See table 3.) Among our six selected states with separate CHIP programs, there were differences in how some crowd-out procedures were implemented. For example, three states conducted database checks to see if applicants had other sources of health insurance; however, one state checked prior to enrollment, another checked at enrollment and during application renewal, and one state ran weekly checks. Among our six selected states with separate CHIP programs, none planned to change procedures to prevent potential crowd-out. Among the 42 states with separate CHIP programs, some crowd-out prevention procedures vary or have changed over time. For example, while many states use a private company to collect state and national health insurance coverage information to conduct database checks, another state developed a database that contains information on insurance coverage available through over 40,000 employers in the state. Additionally, prior to 2014, 36 states imposed waiting periods, during which applicants could not have health insurance for a specified time before CHIP enrollment, to prevent crowd-out. In 2017, 14 states used waiting periods. Prior to PPACA and the implementation of CMS regulations that limited waiting periods to 90 days, waiting periods could range from 1 to 12 months. After CMS updated its regulation, 21 states eliminated their waiting periods and five states shortened them. Among our four selected states with separate CHIP programs that shortened or eliminated their waiting periods, none of the state officials expressed concerns that this change contributed to CHIP crowd-out. Administering a waiting period may involve the state tracking or determining whether the applicant meets any of the state and federal waiting period exemptions, the number of months for the waiting period before the applicant can be enrolled in CHIP, and informing the federally facilitated exchange if an exemption to the waiting period applies to the applicant. As a result, some officials noted that reducing waiting periods eased their state’s administrative burdens, as well as eliminated gaps in children’s health insurance. Among the four selected states, officials from New York said they eliminated their waiting periods because, after undergoing the various administrative steps to verify each application and apply the waiting period, the majority of the CHIP applicants met at least one waiting period exemption. However, three of the selected states with separate CHIP programs maintained waiting periods, and state officials from Texas told us that few individuals met the waiting period exemptions. Some state officials told us they attributed waiting periods—which require children to go uninsured for a period of time—to gaps in health care, and their states eliminated the waiting period in an attempt to provide continuity in children’s access to health care. Although not required by law, officials from two of our selected states with Medicaid expansion CHIP programs told us their states previously had approved 1115 demonstration waivers permitting their states to use a CHIP waiting period, but eliminated them in 2013 and 2014 to close gaps in children’s health insurance coverage. Currently, these states use similar procedures as separate CHIP states to prevent crowd-out, according to state officials. Of our three selected states with Medicaid expansion CHIP programs, one state monitors CHIP enrollment trends; a second state requires its managed care organizations to check CHIP enrollees for other sources of insurance as part of their claim processing activities; and one state conducts database checks for other health insurance at the time of enrollment and re-enrollment. The Effect of States’ Procedures to Prevent CHIP Crowd-Out is Unclear, as Relatively Few Studies Have Examined the Issue The effect of some of the states’ procedures on preventing CHIP crowd- out is unclear and, according to selected state officials and stakeholders, some crowd-out prevention procedures may have unintended consequences. For example, state officials and stakeholders told us waiting periods result in coverage gaps, which, as one stakeholder noted, could be catastrophic for a family with a sick child who would not have coverage during the waiting period. Several CHIP officials we interviewed believed their procedures are effective in preventing crowd- out; however, they either had not studied the effectiveness of their procedures or could not speak to the effectiveness of any particular procedure. Relatively few of the studies we reviewed examined the effectiveness of state procedures for preventing crowd-out. Specifically, two studies looked at this issue. Both studies concluded that cost-sharing procedures, such as premiums, can reduce the potential for crowd-out among higher- income CHIP-eligible families. A 2014 study used CHIP-related data from 2003 and found that CHIP premiums discourage individuals with private health insurance from dropping their insurance to enroll in CHIP. The study compared health insurance outcomes across 19 states for children with incomes slightly above states’ CHIP income eligibility thresholds with children in families with incomes slightly below the thresholds. The results indicated that there is an association between CHIP premiums and private insurance coverage; that is, a $1 increase in the CHIP premium above the income cut-off is associated with a 2.2 percentage point higher probability of the child being privately insured for families within 15 percent of the upper income level, and a 1.7 percentage point higher probability for families within 25 percent of the upper income level. These findings suggest that private health insurance may be a preferable alternative for CHIP eligible families at higher income levels who face higher CHIP premiums. A 2013 study used survey data from 50 states and the District of Columbia from 2002 to 2009 to estimate the effect CHIP premium contributions have on enrollment in CHIP, private insurance, and rates of uninsurance among children in families with income eligibility levels of 200 to 400 percent of the FPL. The study found that if CHIP programs expand eligibility to those at higher income levels and charge those families a higher premium, the families may be more likely to choose private health insurance, nullifying the effects of CHIP expansion among higher income families. Agency Comments We provided a draft of this report to HHS for review and comment. The department provided technical comments, which we incorporated as appropriate. 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 report date. At that time, we will send copies to the Secretary of Health and Human Services, the Administrator of CMS, appropriate congressional committees, and other interested parties. In addition, the report will be available at no charge on the GAO website at http://www.gao.gov. If you or your staff members have any questions about this report, please contact me at (202) 512-7114 or at yocomc@gao.gov. Contact points for our Offices of Congressional Relations and Public Affairs may be found on the last page of this report. GAO staff that made key contributions to this report are listed in appendix III. Appendix I: Crowd-Out and Trends in Children’s Health Insurance and Employer Sponsored Health Insurance Crowd-out may occur when employers modify or decide not to offer health insurance to their employees or to their dependents because of Children’s Health Insurance Program (CHIP) availability. For example, employers who are aware of CHIP may decide not to offer health insurance to employees due to concerns about the costs of providing insurance, especially for smaller sized firms, or as a result of changes in federal or state policies, such as requirements resulting from the Patient Protection and Affordable Care Act (PPACA). For example, PPACA required employers with a certain number of employees to offer their full-time employees a health insurance option meeting certain criteria, including affordability, or face tax penalties. Some researchers and policymakers expressed concern that this requirement may encourage employers to change how they offer insurance to employees, such as no longer offering family and dependent coverage, instead only offering health insurance to the employees, thereby causing employees with children to seek public insurance or insurance through health insurance exchanges. Other researchers and organizations point to PPACA increasing the availability of private health insurance offered by employers and through health insurance exchanges, particularly in areas and among populations where employer sponsored health insurance may not be as readily available. Crowd-out may also occur when employees drop or decide not to enroll in insurance offered by their employers and enroll their children in CHIP because of CHIP availability; however, as we have reported in the past, assessments of crowd-out should consider the affordability and availability of the employer sponsored insurance. For example, families with access to employer sponsored insurance may find CHIP more affordable or find CHIP benefits more comprehensive than employer sponsored insurance. Alternatively, they may find that CHIP provides better access to services specific to their child’s health care needs. For example, an evaluation of CHIP published in 2014 found that CHIP enrollees had better access to dental benefits than children with private insurance, although they were less likely to have a regular source of medical care and nighttime or weekend access to a provider. As we have identified in prior work, assessments of the potential for crowd-out must take into account an understanding of the extent to which private health insurance is available and affordable to low-income families who qualify for CHIP. American Community Survey (ACS) data showed that for 2013 through 2017, the most prevalent source of insurance for children in the United States under the age of 19 was private health insurance available through a parent’s employer or union. (See fig. 2.) Although private health insurance is the most prevalent source of insurance for children, there is substantial variation across states in coverage rates. (See fig. 3.) For example, in eight states, fewer than 40 percent of children were insured through an employer in 2017. In contrast, in Utah, more than 60 percent of families with children were insured by an employer in 2017. Medical Expenditure Panel Survey (MEPS) data show that the extent to which employers offered individuals insurance in 2013 through 2015 varied by family income. For example, MEPS Household Component data—which includes information on whether individuals were offered insurance by their employers—show that over 90 percent of families with incomes greater than 400 percent of the federal poverty level (FPL) were offered insurance by their employers from 2013 through 2015. The percentage of families offered insurance by their employers ranged from about 35 percent for families with incomes less than or equal to 138 percent of the FPL to about 85 percent for families with incomes above 300 and less than 400 percent of the FPL. (See fig. 4.) An Agency for Healthcare Research Quality (AHRQ) analysis of MEPS Insurance Component data—which includes information on whether employers offered insurance to their employees and the cost of that insurance— shows that in 2017, 24.2 percent of small employers (less than 50 employees) with a predominately lower-wage workforce offered their employees health insurance compared with 57.6 percent for small employers with a higher-wage workforce. In contrast, in 2017, offer rates at larger employers—that is, employers with more than 50 employees— was 94 percent for those with predominately lower-wage employees and 98.7 percent for large employers with predominately higher wage employees. With regard to affordability, the MEPS Insurance Component data show that average employee premium contributions for family coverage from 2013 through 2017 increased. Over this period, employees who work for employers with a predominantly lower-wage workforce—that is, employers that paid 50 percent or more of their workforce $12 or less per hour—contributed a larger amount and percentage of premiums to their employer-sponsored insurance than did employees who work for non- low-wage employers. (See fig. 5.) MEPS Insurance Component data also show that employees who work at establishments with a predominately lower-wage workforce enroll in insurance offered by their employers at a lower rate than employees of other establishments, though it is not known if this is due to affordability reasons. Finally, MEPS Insurance Component data show that the percentage of employees with deductibles and the amount of the deductibles have increased from 2004 to 2017. Between 2013 and 2017, average family deductibles increased about 36 percent, from $2,491 in 2013 to $3,396 in 2017. In addition, research published in 2018 on high deductible health insurance plans showed both increasing enrollment in these plans and that larger employers (1,000 or more employees) contributed more toward health insurance premiums for these plans than smaller employers (less than 25 employees). For example, according to this study: From 2006 to 2016, there was a 35 percentage point increase (11.4 percent to 46.5 percent) in enrollees in high-deductible health plans, with enrollees from smaller employers more likely to be enrolled in these plans compared with enrollees from larger employers (56.4 percent of enrollees from small firms compared with 42 percent of enrollees from large firms). A lower percentage of enrollees from the smaller firms had a plan with an employer-funded account, which defray health care costs, compared with enrollees from larger firms. For example, in 2016, only about one-third of enrollees in high-deductible health insurance plans from the smallest employers had an employer funded account to help pay for medical expenses compared with 89.3 percent of enrollees from the largest employers. High-deductible health insurance plan enrollees of the smallest employers were also more likely to not have the choice of an alternative plan type compared with enrollees from the largest employers. Appendix II: Source of Health Insurance for Children under Age 19 by State in 2017 Although private health insurance is the most prevalent source of insurance for children, there is substantial variation across states in coverage rates. Figure 6 provides information on the percentage of children under age 19 insured through employer sponsored insurance, Medicaid, and the Children’s Health Insurance Program, as well as those who were uninsured in 2017. Appendix III: GAO Contact and Staff Acknowledgments GAO Contact Carolyn L. Yocom, (202) 512-7114 or yocomc@gao.gov. Staff Acknowledgments In addition to the contact named above, individuals making key contributions to this report include Shannon Legeer (Assistant Director), Toni Harrison (Analyst-in-Charge), Mollie Lemon, and Courtney Liesener. Also contributing were Alison Binkowski, George Bogart, Jill Center, Leia Dickerson, Giselle Hicks, Drew Long, Kristeen McLain, Yesook Merrill, Jasleen Modi, Vikki Porter, Lisa Rogers, and Merrile Sing.


Introduction For more than 65 years, the U.S. Congress has funded international food assistance through the Food for Peace program (FFP) to alleviate hunger and improve global food security. U.S. food assistance comes in the form of in-kind food commodities purchased in the United States and shipped overseas, and through market-based approaches. Market-based approaches include purchasing food in foreign local and regional markets and then redistributing it, and providing food vouchers and cash transfers that recipients can use to buy food locally. The U.S. Agency for International Development (USAID), the lead development and humanitarian arm of the U.S. government, administers the majority of U.S. international food assistance. Within the agency, the Office of Food for Peace manages the FFP program, which provides both emergency and nonemergency food aid. Nonemergency programming once represented a significant portion of FFP, but this portion has declined (from 83% in FY1959 to 11% in FY2018) as emergency needs have continued to rise and FFP has received emergency funding from additional accounts (see Figure 3 ). The Bureau for Food Security (BFS), within USAID, manages agricultural development and nutrition programs, which support food security goals but are not considered food aid under the umbrella of the Feed the Future Initiative (FTF). The distinctions between FFP nonemergency programs and BFS development programs are found in authorizing legislation, funding flows, and congressional jurisdiction. This report focuses primarily on FFP's nonemergency activities. It explains current programs, legislative history, and funding trends. The report also discusses how FFP nonemergency programs fit within the broader food aid and food security assistance framework, and the future of FFP nonemergency programs in the context of related Trump Administration proposals. Finally, this report explores the challenges Congress faces in conducting oversight of U.S. international food assistance programs, which fall under two separate congressional committee jurisdictions. Food for Peace Nonemergency Programming In FY2018, Food for Peace (both emergency and nonemergency programs) operated in 59 countries and reached more than 76 million recipients. However, FFP had active nonemergency programs in only 15 countriesâmost of which were in sub-Saharan Africa, with the remaining in Latin America and the Caribbean, and Asia. FFP nonemergency programs seek to aid the poorest of the poor by addressing the root causes of hunger and making vulnerable communities more resilient to shocks, both natural and human-induced. Programs generally last five years and, according to FFP, "aim to reduce chronic malnutrition among children under five and pregnant or lactating women, increase and diversify household income, provide opportunities for microfinance and savings, and support agricultural programs that build resilience and reduce vulnerability to shocks and stresses." Common types of FFP nonemergency activities include in-kind food, cash or voucher distributions, educational programs to encourage dietary diversity and promote consumption of vitamin- and protein-rich foods, farmer training on agricultural value chains and climate-sensitive agriculture, and conflict sensitivity training for local leaders. In building resilience in vulnerable communities, FFP seeks to reduce the need for future emergency assistance and pave the way for communities to pursue longer-term development goals. With few exceptions, nonemergency programs are implemented by nongovernmental organization (NGO) partners. Examples of the range of FFP nonemergency programs include the following: Strengthening Household Ability to Respond to Development Opportunities (SHOUHARDO III ) in Bangladesh began in 2015 to improve "gender equitable food and nutrition security and resilience of the vulnerable people" in two of the country's regions. USAID identified four areas of concern on which interventions should focus: gender inequality and women's disempowerment, social accountability, youth, and climate adaptation. CARE, a nonprofit organization that formed in post-World War II to distribute food packages in Europe, implements SHOUARDO III. The program's goal is to reach 384,000 participants through activities that address climate change and disaster resilience training, supplementary food distributions for pregnant and lactating women, youth skills training, the organization of microenterprise groups, and water supply and sanitation activities, among others. SHOUHARDO III is one of the few FFP nonemergency programs that includes a monetization component. In FY2018, SHOUHARDO received more than $18 million in FFP Title II funding. The program is scheduled to run through the end of FY2020. Tuendelee Pamoja II in the Democratic Republic of Congo (DRC) was initiated in 2016 to improve food security and resilience among 214,000 households in selected provinces, with a special focus on women and youth. Food for the Hungry, an international Christian relief, development, and advocacy organization, implements the program. Interventions include the distribution and testing of new varieties of soybeans, beans, and maize; construction of planting terraces to reduce land erosion; training on fishing practices; literacy and numeracy education; and youth training in wood- and metal-working; among others. The program received more than $15 million in FFP Title II funding in FY2018 and is scheduled to run through the end of 2021. Njira Pathways to Sustainable Food Security in Malawi began in 2014 with the aim of improving food security for more than 244,000 vulnerable people in selected districts in Malawi. The programs were designed to address Feed the Future (FTF)-established food security goals for the country and to complement other FTF programs and development goals under USAID/Malawi Mission's Country Development Cooperation Strategy. Project Concern International (PCI), a global development program established in 1961, implements the Njira project; its activities include distributing livestock and offering animal health services to improve livestock production, increasing access to and participation in women's empowerment savings and loan groups, conducting farmer training to combat Fall Armyworm, and distributing food rations to children under five. In FY2018, the Njira project received nearly $2 million in FFP Title II nonemergency funds and nearly $2.5 million in Community Development Funds (CDF). The project is slated to run through late 2019. Food for Peace Nonemergency Programs in the Context of U.S. International Food Assistance FFP nonemergency programs are largely used to support the transition in food security assistance between short-term emergency food assistance programs and longer-term agricultural development and nutrition assistance programs. They share a close relationship with FFP emergency programs and the BFS-led Feed the Future development programs, but distinct differences exist among these aid channels, which are designed to be complementary and undertaken sequentially (see Figure 1 ) . While Food for Peace nonemergency programs address the root causes of food insecurity and seek to build resilience among vulnerable populations, FFP Title II emergency programs seek to distribute immediate, life-saving food and nutrition assistance to populations in crisis. Assistanceâprimarily through food procured in the United States but also through market-based approachesâis meant for those suffering from hunger or starvation as a result of crises. Programs are short, many running between 12-18 months, and are primarily implemented by the United Nations' World Food Programme. In FY2018, some of FFP's largest Title II emergency responses were staged in South Sudan ($335 million), Yemen ($273 million), and Ethiopia ($198 million). As noted, Food for Peace works with the poorest of the poor, focusing on building resilience. Feed the Future works with communities ready for longer-term development and focuses more on agricultural systems strengthening and market development. Catholic Relief Services, for example, currently implements both FFP nonemergency and Feed the Future development programs in Ethiopia. The FFP Ethiopia nonemergency program includes rehabilitating small-scale irrigation systems, conducting assessments on conflict management, and developing "livelihood pathways" for beneficiaries. The FTF development program includes financial education and services training, the establishment of marketing groups, and training for local leaders on youth participation in economic and social development. In this case, Food for Peace is supporting resilience strategies and baseline asset-building, while Feed the Future is encouraging more diverse market engagement and economic development. The use of Food for Peace nonemergency assistance and Feed the Future development assistance can depend on their different statutory requirements and flexibilities. For example, all FFP nonemergency programs funded with Title II must include in-kind food distributions; FTF programs do not. FFP nonemergency programs have funding flexibility that FTF development programs do not: funding may be reprogrammed from nonemergency to emergency responses if a shock occurs during the course of a nonemergency program. This flexibility exists because Title II funding is authorized for both emergency and nonemergency programing (see the " Legislation " section). For example, a five-year FFP nonemergency program in Madagascar shifted some of its funding to emergency programming in 2015, when the southern part of the country was hit with a drought. Once emergency food needs were met in those areas, the program was able to refocus on nonemergency programming. In some instances, Food for Peace nonemergency and Feed the Future development programs pursue similar or overlapping programming. Where such overlap occurs, implementing partners often duplicate programs deliberately to smooth the sustainable sequencing of food security programs, from FFP nonemergency to FTF development programming. Program Coordination Within USAID As Food for Peace nonemergency programs are meant to bridge the gap between emergency programming and longer-term development programs, FFP seeks to coordinate both within the office and with its BFS counterparts. Within FFP, the office's geographic teams manage nonemergency programs alongside emergency programs, and in many cases the same staff manage both types of programs. For example, an FFP officer managing a nonemergency program in Haiti would also be managing emergency programs in the country. This integration allows the office's geographic staff to leverage resources and approaches between nonemergency and emergency programs. FFP officers also work with their Bureau for Food Security counterparts, both in Washington, DC, and in the field. FFP is a part of the Feed the Future target country selection process, and BFS works closely with FFP on its annual country selection process for new countries for FFP nonemergency resources and the subsequent program design for those countries. FFP also uses FTF indicators to measure progress toward programmatic goals in its program evaluations. In the field, BFS and FFP officers collaborate. Legislation The Food for Peace program was established in 1954 with the passage of the Agricultural Trade Development and Assistance Act of 1954 (P.L. 83-480). Title II of the act authorized the use of surplus agricultural commodities to "[meet] famine or other urgent relief requirements" around the world and provided the general authority for FFP development programs. Now referred to as the Food for Peace Act, the program has evolved to reflect changes in domestic farm policy and in response to foreign policy developments. Congress authorizes the majority of international food assistance programs, including the FFP program, in two pieces of legislation: The Farm Bill. Typically renewed every five years, legislation commonly referred to as the farm bill is a multiyear authorization that governs a range of agricultural and food programs. The majority of farm bill-authorized programs are domestic, but Title III includes the Food for Peace Act as Subtitle A. In the most recent farm bill, the Agriculture Improvement Act of 2018 ( P.L. 115-334 ), Congress authorized programs through FY2023. The Global Food Security Act of 2016 (GFSA). Congress enacted the Global Food Security Act of 2016 ( P.L. 114-195 ) to direct the President to coordinate the development of a whole-of-government global food security strategy and to provide food assistance pursuant to the Foreign Assistance Act of 1961 (P.L. 87-195; 22 U.S.C. 2151 et seq.). The GFSA also amended Sections 491 and 492 of the 1961 Act (22 U.S.C. 2292 et seq.) to establish the Emergency Food Security Program (EFSP) under International Disaster Assistance authorities, which FFP uses to provide emergency food assistance primarily through market-based approaches such as local and regional procurement (LRP), vouchers, and cash transfers for food. An extension of GFSA ( P.L. 115-266 ) was enacted in 2018 and authorizes programs through FY2023. Food for Peace nonemergency programs, in particular the Title II in-kind commodity purchase and distribution components, have historically received considerable bipartisan support from a broad domestic constituency. This support is a result of the program's link to U.S. farmers and shippers through the farm bill's statutory requirements. While FFP emergency responses make up the majority of the U.S. in-kind programming, the nonemergency food assistance programs share the same domestic connections. In a prepared statement for the House Agriculture Committee in relation to a 2017 hearing on the farm bill, the chairperson of the USA Rice Farmers Board shared the board's support of U.S. international food aid programs, noting that while U.S. Department of Agriculture (USDA) commodity procurement-purchases comprise only between 1% and 2% of total rice exports, "it is important to the industry that we continue to play a strong role in providing our nation's agricultural bounty to those in need." In written testimony for the House Subcommittee on Agriculture Appropriations, the Senior Director of Policy and Advocacy at Mercy Corps stated that "from our decades of experience working in fragile states, we have found non-emergency FFP programs to be the leading US government tool, for building the resilience of families and communities to food insecurityâ¦. [W]ith these investments, we can prevent and mitigate food security crises." Further, FFP has a close relationship with the U.S. maritime industry as a result of longstanding but evolving requirements that a percentage of FFP commodities be shipped on U.S.-flagged vessels. These agricultural cargo preference requirements can sometimes create tension; the U.S. Maritime Administration asserts that agricultural cargo preference is critical to maintaining U.S. sealift capacity while FFP often expresses concern about how the increased cost of adhering to agricultural cargo preference affects its ability to meet the needs of the world's most food insecure populations. Despite this tension, the maritime industry remains engaged and active in FFP programming and has been a vocal advocate for the commodity-based programs. These historic links to the U.S. agriculture and maritime industries have been a significant factor when Congress considers legislation. Funding Consistent with the two authorization vehicles described above, food assistance funds are appropriated through both Agriculture appropriations (for farm bill-authorized programs) and Department of State, Foreign Operations and Related Programs (SFOPS) appropriations (for GFSA-authorized programs). Funds for nonemergency programs come from two accounts: The Food for Peace Title II Grants account within the Foreign Agricultural Service in Agriculture appropriations. FFP has received Food for Peace Title II Grants since its establishment. The Development Assistance (DA) account within SFOPS appropriations. FFP receives DA fundsâdesignated as Community Development Funds (CDF)âfrom BFS to complement its Title II nonemergency resources and improve coordination between FFP and BFS. First legislated in FY2010, Congress intended CDF funds be used to help FFP reduce its reliance on monetizationâthe practice of partners selling U.S. commodities on local markets and using the proceeds to fund nonemergency programs. The level of CDF that FFP receives from BFS is not required by law; however, Congress has designated funds for CDF in the report accompanying annual appropriations (sometimes referred to as a "soft earmark") to which USAID has adhered each fiscal year. FFP receives additional funding for emergency food programs through the International Disaster Assistance (IDA) account within SFOPS appropriations. In FY2010, FFP started receiving IDA funds for the Emergency Food Security Program (EFSP) to supplement its Title II emergency funds. In FY2018, Food for Peace received nearly half of its resources through Agriculture appropriations (see Figure 2 ). Of its overall funding, FFP used 11% ($431 million) for nonemergency programsâfunded both through Title II and CDFâand 89% ($3.250 billion) for emergency programs. As previously mentioned, this was a marked change from the early years of the FFP program. When the Title II program was established, nonemergency programs constituted 65% of funding. While their share of overall programming rose in the first few years of the programâin 1959, they made up 83% of Title II programmingâthe share steadily declined in the following decades. By 2007, nonemergency programming accounted for 20% of Title II funds (see Figure 3 ). The following year, Congress established a minimum level (in U.S. dollars) of nonemergency food assistance in the 2008 farm bill ( P.L. 110-246 ). The nonemergency minimum has been maintained in subsequent authorizations but has fallen by $10 million since it was first added to the bill (see Table 1 ). The most recent farm bill ( P.L. 115-334 ), enacted in December 2018, set the minimum level of nonemergency food assistance at $365 million but allowed for Community Development Funds and the Farmer-to-Farmer Program funds to be counted toward the minimum. Issues for Congress The 116 th Congress may be interested in a number of issues related to Food for Peace nonemergency programs. Areas of interest may include proposed and ongoing reforms to the FFP program funding and structure that could change both how nonemergency programs fit into the broader landscape of U.S. international food assistance programs, and the means through which the program is funded. Proposed Elimination of Title II Funding and Food Aid Reform Since FY2018, the Trump Administration has proposed eliminating funding for the entire FFP Title II programâboth emergency and nonemergency programsâon the basis that doing so would "streamline foreign assistance, prioritize funding, and use funding as effectively and efficiently as possible." In its FY2020 foreign assistance budget request, the Administration referred to providing Title II food aid as "inefficient." Instead of relying on the FFP Title II program, which is funded through Agriculture appropriations, the Administration suggests providing food assistance solely through accounts funded by SFOPS appropriations. The Administration also proposes reducing SFOPS appropriations, indicating a preference for an overall reduction in funding for U.S. foreign assistance, including international food assistance programs. The Trump Administration is not the first to suggest significant changes to U.S. international food assistance programs. The Obama Administration also pursued a food aid reform agenda, proposing in its FY2014 budget request to shift all FFP Title II funds into three SFOPS assistance accounts. According to the Obama Administration, the proposed changes would have increased the flexibility, timeliness, and efficiency of U.S. international food assistance and allowed the programs to reach an additional "4 million more people each year with equivalent funding." While to date Congress has not accepted any proposals to defund Title II, there have been efforts on Capitol Hill to change parts of the Title II program. For example, in the 115 th Congress, Senate Foreign Relations Committee Chairperson Bob Corker and House Foreign Affairs Committee Chairperson Edward Royce both introduced versions of the Food for Peace Modernization Act, with bipartisan support ( S. 2551 and H.R. 5276 , respectively). The two bills would have made changes to the Title II programâincluding eliminating the requirement to purchase all Title II food aid commodities in the United States and removing the monetization requirementâin an effort to reduce cost and gain efficiency. Neither bill received further consideration, but some elements of the proposals were incorporated into the most recent farm bill ( P.L. 115-334 ). In FY2018 and FY2019, Congress did not accept Administration proposals to eliminate Title II funding, and for FY2020, the House-passed Agriculture appropriations include $1.85 billion for Title II. As Congress considers its annual appropriations and future authorization measures, Members may consider how to balance calls for reform with the priorities and vested interests of domestic constituencies, including agricultural interests and development groups, and how the often conflicting viewpoints may affect the effectiveness and efficiency of the Title II nonemergency programs. Nonemergency Programs in the Context of USAID's Transformation Initiative40 As part of USAID's internal reform initiative, referred to as Transformation , the agency is planning to merge the FFP Office with the Office of U.S. Foreign Disaster Assistance (OFDA) into a new Bureau for Humanitarian Assistance (HA). OFDA is currently responsible for leading the U.S. government response to humanitarian crises overseas. In creating a new HA bureau, USAID would be consolidating its food (currently administered by FFP) and nonfood (currently administered by OFDA) humanitarian responses in an effort to remove potential duplication and present a more unified and coherent U.S. policy on humanitarian assistance on the global stage. In the new HA bureau, FFP and OFDA would no longer remain separate from one another with independent functions; instead, they would be consolidated into one bureau comprising eight officesâthree geographically focused (Africa; Asia, Latin America, and Caribbean; and Middle East, North Africa, and Europe) and five technical (covering issues such as award management, program quality, donor coordination, and business operations, among others). (See Appendix B .) The humanitarian community remains engaged with the U.S. government on this proposal and its potential effects on the broader efficiency, effectiveness, and coordination of humanitarian assistance. Some food assistance stakeholders have raised concerns about the dissolution of FFP and its potential impact on Title II programming. According to a USAID congressional notification on the intent to form the HA bureau, Title II nonemergency programming would remain in the new HA bureau, though it is unclear how that arrangement will look in practice. For the moment, USAID is planning to have the new HA geographic offices be responsible for managing both emergency and nonemergency Title II programming; however, a number of details need to be worked out by USAID leadership. These include whether and how nonemergency programs will be incorporated into larger disaster risk reduction efforts, and how the nonemergency programs will fit in with the programs to be managed by the new Bureau for Resilience and Food Security. As part of its Transformation process, USAID has held a number of consultations with Members of Congress. While the structural redesign is underway (HA is currently slated to be operational by the end of 2020, though implementation timelines may change), Congress has opportunities to provide feedback and guidance to the agency as it finalizes office-level details. Separation of Food for Peace Nonemergency and Feed the Future Development Programs Some policymakers have questioned why two different offices within USAID are responsible for similar programming, and have suggested either moving FFP's nonemergency portfolio to BFS or vice versa. In either consolidation scenario, the program could potentially benefit from increased coordination. For example, having one office manage all programming and present a unified voice to all stakeholders (including Congress) may reduce communication and coordination challenges. However, USAID could face significant tradeoffs in both consolidation scenarios. If FFP's nonemergency portfolio were to move to USAID's Bureau for Food Security, the programs could lose their focus on serving the most vulnerable populations. Unlike Food for Peace, Feed the Future does not focus its programs on the poorest of the poor, does not include in-kind food distributions in its projects, and cannot shift its funding to meet emergency needs should a shock occur. Were FFP nonemergency programming to move to BFS, these unique FFP qualities may be deprioritized in favor of the more traditional development model BFS has pursued with its Feed the Future programs. Additionally, during a disaster FFP often uses its nonemergency programs as a component in the overall emergency response, by either diverting existing resources or injecting new emergency resources to support an early response. Conversely, if BFS programming were to move to the Office of Food for Peace, the FTF programs could be deprioritized in favor of emergency programming. As discussed earlier, emergency programs have grown to dwarf nonemergency programming in funding terms (see Figure 3 ). If emergency funding needs continue to rise consistent with their previous trajectory, the demands from the emergency portfolio could outpace and overtake the traditional development assistance, jeopardizing the FTF gains already made and risking future programming. Use of Community Development Funds (CDF) Since FY2010, Food for Peace has received Community Development Funds (CDF) from the Development Assistance account in SFOPs appropriations to support its nonemergency programs and reduce reliance on monetization. Over the years, FFP has grown to rely on CDF to pursue the full range of its nonemergency programs. Implementing partners have raised concerns that if the level of CDF funding were to drop, USAID would have to choose between routing CDF funds through BFS to FFP and fully funding BFS-administered programs. If FFP lost its CDF funding, it would likely need to return to using monetization to partially fund its nonemergency programs. To address this potential challenge, Congress could consider changes in legislation, including but not limited to the following: Increasing flexibilities in Title II funding , including the authorized level of Section 202(e). An increase in flexibility through Section 202(e) could mimic the programmatic flexibilities FFP has gained through the use of CDF, including interventions that do not rely on in-kind food distributions. Proposed increases in flexibility have been opposed by some FFP stakeholders, in particular U.S. agricultural commodity groups. Designating in law a specific CDF level for FFP âinstead of using the "soft earmark" in the bill reportâthereby guaranteeing a secure line of funding for FFP's nonemergency programs. This approach would likely be supported by the implementing partner community, as it would provide some assurance that the CDF level would remain constant from year to year. However, this approach could negatively affect Feed the Future programming if the overall DA funding were to drop. It also would institutionalize the coordination between FFP and BFS that the sharing of CDF has already propagated. Congressional Oversight The various U.S. international food assistance programs fall under two separate congressional committee jurisdictions, which some argue can reduce Congress's ability to pursue comprehensive, integrated oversight of these programs. In the nonemergency context, FFP Title II-funded programs fall under the jurisdiction of the Agriculture Committees and Agriculture Appropriations Subcommittees, but the CDF-funded programming falls under the jurisdiction of the Foreign Affairs and Foreign Relations Committees and SFOPS Appropriations Subcommittees (see Appendix A ). FFP reports on both of these in the International Food Assistance Report (IFAR), the farm bill-mandated annual report to Congress, even though it is not required to include Community Development Funds. This report offers a complete perspective on the FFP nonemergency programs, but it does not contextualize the programs with the entire U.S. international food assistance landscape. The IFAR does not include Emergency Food Security Program or Feed the Future reporting, because both are overseen by the Foreign Affairs/Relations Committees and are subject to different reporting requirements. As such, no single report currently mandated by Congress captures the entirety of international food assistance. The two oversight jurisdictions also present unique challenges to USAID. The two committee groupings often have different (and sometimes competing) priorities, the push and pull of which can sometimes lead USAID and its implementing partners to shoulder a higher administrative burden than other programs that reside in only one jurisdiction. For example, FFP was subject to eight Government Accountability Office (GAO) audits from 2014 to July 2019, covering issues from the monitoring and evaluation of cash-based food assistance programs to how U.S. in-kind commodities are shipped and stored. By comparison, BFS was the primary subject for one GAO audit in that same time-frame. Looking Ahead With enactment of the 2018 farm bill ( P.L. 115-334 ), Food for Peace Title II nonemergency programs are authorized through FY2023. However, the Administration continues to propose the elimination of the FFP Title II program in its annual budget requests. By moving forward with USAID's Transformation initiative, the Administration is implementing changes to organizational structures through which nonemergency food assistance programs are administered. Congress may consider addressing its priorities for FFP nonemergency programs in annual appropriations legislation, stand-alone bills that address certain components of the program, and Transformation -related consultations. Appendix A. U.S. International Food AssistanceÂ Programs This graphic illustrates the suite of U.S. international food assistance programs, including their administering agency and congressional jurisdiction. The programs highlighted in this graphic are the nonemergency programs discussed in this report. Appendix B. USAID's Proposed Bureau for Humanitarian Assistance


Introduction For roughly the first 100 years of the electric power industry, electricity generation occurred mostly in large, c entralized power plants. Partly in response to the energy crisis of the 1970s, Congress established policies to promote, among other things, alternatives to centralized power plants, including generation capacity located on customer property. Customer-sited generation is a type of distributed generation (DG) and can be located on commercial, industrial, or residential properties. One policy intended to promote DG is net metering. In the Energy Policy Act of 2005 (EPACT05; P.L. 109-58 ) Congress encouraged states to adopt net metering, defined in the law as service to an electric consumer under which electric energy generated by that electric consumer from an eligible on-site generating facility and delivered to the local distribution facilities may be used to offset electric energy provided by the electric utility to the electric consumer during the applicable billing period. State net metering policies may be relevant to congressional discussions about the role of renewable energy sources, like solar, in the nation's electricity system. Solar photovoltaic (PV) is the most commonly deployed energy type participating in net metering, comprising 97% of net metering capacity in 2018. Other federal and state policies (e.g., tax incentives, renewable portfolio standards, carbon pricing) may interact with net metering policies to determine the deployment pace of distributed solar energy sources and other types of DG. Also, some Members of Congress may be interested in how some states have modified their net metering policies in recent years, including the effect of those modifications on stakeholders. Some recent state policy changes are expected to expand solar energy development, while others are expected to slow it. Among other options, Congress could choose to restrict, encourage, or require certain kinds of state policy modifications, or take no action on state net metering policies, depending on congressional priorities. This report provides background information and discusses current issues related to net metering policy. What Is Net Metering? Net metering policies determine how electricity customers with distributed generation are compensated for electricity they deliver to the grid. Net metering is frequently used to mean a policy of net energy metering (NEM), which specifies that electricity delivered to the grid from a net metering customer is compensated on a one-to-one basis for electricity purchased from the grid. Every unit of electricity generated by the customer (typically expressed in kilowatt-hours, kWh) is subtracted from the amount of electricity they consume, for billing purposes. This is frequently described as "the meter running backward." Other analyses and discussions sometimes distinguish different policy options, including: buy-all, sell-all , under which a utility buys all electricity generated by the net metering customer at one (usually, lower) rate and sells all the electricity consumed by the customer at a different rate (usually the same retail rate charged to any other customer); and net billing , under which electricity delivered to the grid is compensated at a pre-determined value, which might be measured as a rate or a fixed amount. This report will generally use the term net metering to refer to any of these policies since they are closely related to each other, in that they provide financial support for DG. How Common Is Net Metering? As of April 2019, 45 states had net metering policies in place that require utilities to offer net metering to customers. Some of these policies include alternatives to net energy metering. Further, some of these policies predate EPACT05. In the states that do not require utilities to offer net metering, some utilities voluntarily offer net metering service to customers. According to the U.S. Energy Information Administration (EIA), almost 2 million customers participated in net metering programs in the United States in 2018, compared to over 153 million electricity customers overall. In other words, about 1% of U.S. electricity customers in 2018 participated in net metering. The number of net metering customers increased from 2013 to 2018 as shown in Figure 1 . Data before 2013 also show growth in net metering participation, but EIA changed the way it reported net metering data beginning in 2013, so these data are not shown below, in the interest of consistency. Net metering participation can be measured in other ways, such as total net metering capacity or the amount of electricity delivered to the grid from net metering generators. According to the EIA data, these measures have seen average annual increases similar to customer count. Levels of net metering participation vary by state, as shown in Figure 2 . In many states, less than 0.1% of electricity customers participate in net metering. Hawaii has the highest participation rate, with over 15% of customers participating in the state's net metering programs. Some potentially relevant factors for the differences among states include design of state net metering policies, presence of other state policies such as renewable portfolio standards (which may incentivize renewable DG), average electricity prices, and solar resource quality. A full analysis of the factors behind different state participation rates is beyond the scope of this report. Overview of Electricity Ratemaking This section provides an overview of how electricity rates are set in general, in order to clarify major areas of debate for state net metering policies. Electricity ratemaking is the process of allocating to customers the total costs that utilities incur when producing and delivering electricity. Many complexities and local factors influence ratemaking. A full discussion is beyond the scope of this report. As an illustrative example, this section discusses typical ratemaking considerations for vertically-integrated investor-owned utilities. In its service territory, this type of utility owns and operates all parts of the electricity system, from electricity generation to transmission and distribution to customers. State regulators conduct the ratemaking process and approve rates that the utility can charge its customers. Regulators design rates so that utilities can recover their costs through customers' bill payments. These costs generally include: the costs of building and operating power plants, including fuel costs and compliance with any applicable regulations (e.g., environmental, safety, reliability); the costs of building and maintaining transmission and distribution systems (i.e., the grid); regular utility operating costs, such as ensuring reliable grid operation (i.e., grid services) or collecting meter data for billing; any programmatic costs, such as bill relief for low-income consumers or implementation of other public policies; and a return on the utility investments (i.e., return on equity or ROE). A common method for setting rates is to establish volumetric rates (sometimes called flat rates). All customers within a given type, or customer class, will pay the same rate expressed in cents per kilowatt-hour (cents/kWh). The more electricity a customer uses, the higher a bill they will have. Customers' bills will vary each month based on the amount of electricity they consume. Regulators estimate a value for the volumetric rate that will allow the utility to recover its total costs, based on projections of total sales for all customer classes. In this way, the costs for electricity generation, transmission, distribution, and other utility expenses are shared among all customers. Costs associated with customer service (e.g., billing, connections) sometimes are separated from the electricity rate and recovered in a separate customer charge. This charge would appear as a fixed value on the customer's bill and would not change from month to month. Customer charges are additional to rates. In other words, a customer's bill would have volumetric charges (rate times kWh consumed) plus a fixed customer charge. Some customer classes, such as large industrial facilities or institutions, consume so much electricity that utilities might make special system modifications for them. In some cases, utilities recover these costs in a demand charge that is only paid by those high-consuming customers. Like customer charges, demand charges are generally additional to volumetric charges and do not typically change from month to month. Net Metering Compensation EPACT05 encouraged states to adopt net metering, but the law did not specify how customers should be compensated. States with net metering have taken different approaches in implementing their policies, and many states have revised their compensation approaches in recent years. These decisions may affect DG markets. As one study from the National Renewable Energy Laboratory observed, "compensation mechanisms impact DG deployment because they strongly influence the value proposition of a DG investment for individual customers." This section describes some elements of states' approaches to implementing net metering. Retail Rates for Net Metering Customers A common approach to net metering is to compensate net metering customers at the utility's approved retail rate of electricity. This is frequently described as a net energy metering (NEM) policy, or simply net metering. A 2019 review of state net metering policy revisions describes how state policymakers initially viewed the retail rate as a "close-enough proxy" for rate setting, as follows: Initially, NEM was largely understood to be an administratively simple, rough-justice approach that was acceptable at a time when markets for solar PV and other DG were uneconomic. In many of the initial decisions about NEM, policy makers assumed that the retail rate was a close-enough proxy for the value of solar or value of DG, and the total numbers of participating customers and kilowatt hours being credited at the retail price were relatively small ... the small number of participating customers multiplied by the small quantity of energy each would deliver to the grid, meant that any error associated with under- or over-estimating the true value would be small. Retail rates provide relatively high compensation for net metering generation (see Figure 3 ). As described above (under "Overview of Electricity Ratemaking"), this is because the retail rate for any electric utility customer reflects the total costs the utility incurs for delivering electricity, including generating electricity and maintaining the grid. Retail rates may encourage net metering participation to a greater extent than other compensation approaches because customers can recover the upfront costs of a DG system more quickly. Some stakeholders have noted the possibility that compensating net metering customers at the retail rate may result in increased costs for non-net metering customers. This possibility, known as a cost shift or cross-subsidy, arises from the fact that the ratemaking process allocates total utility costs among all customers. Net metering customers generate electricity for their own consumption, which reduces the amount of utility-provided electricity they need (and, consequentially, the utility's costs to produce electricity). However, self-generation does not necessarily reduce the amount of other utility-provided services a customer uses (or, generally, the utility's costs to provide those services, such as maintaining the grid). For example, solar net metering customers might consume electricity from the grid at night and derive reliability benefits from the grid even when the sun is shining. Over time, rates for non-net metering customers could increase so the utility could recover the costs of maintaining the grid that are not recovered from net metering customers. Some stakeholders also have noted that residential net metering customers have tended to have higher incomes than non-net metering customers, raising potential equity concerns over cross-subsidies. Studies disagree on the extent to which non-net metering customers may be cross-subsidizing net metering customers. Studies have used different methodologies in estimating cross-subsidies, including which costs and benefits are included and over what timeframe the costs and benefits are considered. These methodological differences may help explain the lack of a consensus view on the magnitude of cross-subsidies. Also, any observed cross-subsidies may be affected by local factors, such as DG penetration and electricity demand growth, which may change over time. As a result, an estimate conducted in one state in one year cannot necessarily be extrapolated to all states in all future years. One synthesis of estimates conducted in or around 2015 found that net metering cost shifts range from $444 to $1,752 per net metering customer per year. Observers may disagree on how much of a cross-subsidy is large enough to warrant policy action. Net metering, and any associated cross-subsidies, is only one factor affecting electricity rates. A 2017 study assessed the potential rate effects of a variety of factors, including net metering, energy efficiency, natural gas prices, state renewable portfolio standards, the federal Clean Power Plan (which was never implemented), and utility capital expenditures. That study found that the rate effects of DG would likely be increases between 0.03 cents/kWh and 0.2 cents/kWh, compared to increases up to 3.6 cents/kWh caused by other factors. The possible presence of a cost shift does not necessarily mean that non-net metering customers are transferring money to net metering customers. The extent to which this might occur would depend, among other things, on net metering participation rates and ratemaking decisions made by regulators. There could be a delay in addressing cost shifts through normal ratemaking processes because those processes have inherent time lags. Further, cost shifts are not unique to DG. As noted in a guide for state regulators, "cost shifting, or subsidies, is unavoidable in practical rate design but regulators endeavor to mitigate these effects in the larger context of the many, often conflicting, rate design principles." Responses to Retail Rates Concerns Some states are seeking to move from the "close-enough proxy" of the retail rate to more precise allocations of system costs and benefits to net metering customers. Often state policy debates focus on addressing concerns about potential cross-subsidies from retail rate compensation. Conceptually, states are exploring two options: adding fixed charges (e.g., customer charge, demand charge) to net metering customers' bills or changing the compensation rate. In practice, states are considering variations of these options, and some states have implemented one of these options or both at the same time. Fixed Charges Adding fixed charges to net metering customers' bills is meant to allow utilities to recover costs for grid maintenance and operation. At the same time, this approach might preserve some perceived advantages for compensating net metering customers at the retail rate (e.g., administrative simplicity, ease of understanding). Proponents of this approach typically include utilities and some advocates for low-income customers. They often assert that adding fixed charges (or other revisions like alternative compensation rates) reduces cost shifting and increases fairness. Opponents typically include the solar industry and environmental advocates. They often contend that net metering promotes competition in the electricity industry and that fixed charges (or other revisions that would discourage DG) ignore societal benefits that DG (especially solar energy) can provide. In addition, while the concept of adding fixed charges may be straightforward, determining a value for fixed charges that accurately reflects net metering customers' use of the grid has been complex and controversial in practice. Alternative Compensation Rates Some states have adopted an alternative compensation rate that attempts to represent the energy costs the utility avoids when net metering customers supply some of their own energy (see Figure 3 ). This approach, referred to in this report as an avoided cost rate, is sometimes called an energy rate, a wholesale rate, a supply rate, or variations of these terms. While the retail rate reflects all costs associated with producing energy, operating and maintaining the grid, and other utility expenses, an avoided cost rate primarily reflects costs associated with producing energy. Some states also might consider network upgrades required to reliably integrate DG, especially solar PV. Depending on circumstances, the avoided cost rate might be estimated by a regulator using an independent methodology or by referral to wholesale electricity markets. Avoided cost rates are usually lower than retail rates. Another alternative compensation rate applies to net metering customers with installed solar PV. Under this method, net metering customers are compensated according to a value of solar (VOS) rate. As illustrated in Figure 3 , this approach reflects many of the same considerations as an avoided cost rate and, additionally, reflects estimated societal benefits associated with distributed solar PV (e.g., reduced air emissions). Solar advocates generally favor inclusion of societal benefits in all aspects of net metering policy and rate design. Some states (and stakeholders) may consider reduced greenhouse gas emissions a benefit of distributed solar PV as well. VOS is often calculated to be larger than avoided cost rates but smaller than retail rates, though states could potentially determine a VOS rate greater than the retail rate, depending on the perceived benefits of solar included in the analysis. A related compensation rate applies to any distributed energy resource (DER), not just distributed solar generation, and reflects estimated grid and societal benefits of DERs. New York is one state taking this approach. Regardless of which rate is set (i.e., avoided cost or VOS) and how it is calculated, it could be applied in either a buy-all, sell-all net metering arrangement or a net billing arrangement (see definitions in the section " What Is Net Metering? "). Points of debate about alternative compensation approaches have included which costs and benefits to consider, and how to quantify them. One challenge around quantification is that costs and benefits of DG can be time- and location-specific. Another challenge is that costs and benefits might change as the level of DG penetration changes. States vary in their approach to evaluating net metering, as evidenced by a 2018 analysis conducted for the U.S. Department of Energy (DOE). That analysis, which reviewed 15 state studies of net metering costs and benefits released between 2014 and 2017, noted that states used various assumptions, and that "the set of value categories included, and whether these categories represent costs or benefits, have a significant impact on the overall results of a given study." Other State Net Metering Policy Provisions In addition to differing in net metering compensation, state net metering policies differ in a variety of other aspects. Some differences pertain to provisions on program caps, source eligibility, credit retention, and system ownership. Provisions in these areas can affect deployment of DG. Program Caps Program caps, sometimes called aggregate capacity limits, set limits on the number of customers or amount of generation capacity that may participate. Program caps can be expressed in units of power (e.g., megawatts; MW), a percentage of electricity demand over some period of time, or other measures as determined by a state. The choice of whether to have program caps and, if so, how to define them can affect the amount of DG that a state's net metering policy might promote. Program caps may be established to reduce risks to the electricity system, such as potential reliability risks from DG, or reduce the likelihood that cross-subsidies would occur. Caps also might reduce the potential for sales losses or other negative financial impacts for utilities. On the other hand, program caps might create a barrier to achieving other policy goals, for example the renewable energy goals that some states have. Source Eligibility States specify which generation sources can participate in net metering, often based on capacity limits (i.e., generator size) and technology type. Solar energy is the dominant energy source for net metering capacity, but some states allow other energy types to participate as well. Whether a non-solar project will participate is usually due to cost factors, but other factors such as customer type (e.g., residential, commercial, or industrial) and location (e.g., urban, rural) may be influential as well. For example, combined heat and power facilities might be attractive mostly to large commercial and industrial customers that use steam. Distributed wind projects might be attractive mostly to farms or other customers with relatively large acreage. Credit Retention Net metering customers often have periods when their electricity consumption exceeds their generation and periods when the opposite is true. When net metering generation exceeds consumption, net metering customers can deliver this surplus generation to the grid. Many state net metering policies compensate net metering customers in some way for the total amount of electricity they generate, but some states only compensate the surplus generation (i.e., the amount delivered to the grid). Typically, if a net metering customer has a surplus over an entire billing period, the customer receives a credit on the next bill. States have different provisions for how long credits can carry over. Credit retention policies can determine the extent to which customers might reduce their total electricity costs to $0. System Ownership Many net metering customers have a single generator located behind a single electricity meter. A single-family home with a rooftop solar installation is one example. Other arrangements are possible though, and some states allow these. Aggregate net metering applies to single customers with multiple electricity meters on their property, for example farms, municipalities, or school districts. Shared net metering applies to multiple customers associated with the same net metering generation capacity, for example participants in community solar projects (sometimes called solar gardens). A version of shared net metering called virtual net metering applies when the shared project is located onsite, for example multi-family dwellings. A related policy is whether third party participation is allowed. In third party participation arrangements, such as solar leasing and power purchase agreements, the solar system is owned by an entity other than the electricity consumer on whose property the system is installed. Areas of Congressional Interest Some Members of Congress have introduced legislation addressing aspects of states' net metering policies. Some proposals would influence state policies directly. For example, S.Amdt. 3120 in the 114 th Congress would have limited the ability of state regulators to move net metering customers to lower compensation rates or to add fixed charges to their bills. S.Amdt. 3053 , also in the 114 th Congress, would have required state regulators to consider the extent to which their net metering policies created cross-subsidies. H.R. 4175 in the 116 th Congress would require states to consider adopting net billing policies for community solar. Other legislation would require studies to better understand the costs and benefits of net metering. For example, in a committee report on an FY2017 appropriations bill, Congress requested a DOE study on "the costs and benefits of net-metering and distributed solar generation to the electrical grid, utilities and ratepayers." DOE transmitted the report to Congress in 2019. In the 116 th Congress, S. 346 and H.R. 1009 would require the National Academies of Sciences, Engineering, and Medicine to study various aspects of net metering such as alternative incentives for DG, net metering planning and operating techniques, and consumer and industry incentives for net metering.