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8 Estimating WIC Participation Among Eligible People The panel was askocl to investigate the best ways to determine likely participation among eligible persons assuming that the program is fully funclecl. This chapter examines participation among those who are eligible for WIC. As we emphasized in Chapter 2, the level of WIC participation is, to a certain extent, a policy choice. Funcling levels can be set so that a certain number of people are servecl. Or program rules ancl administrative practices can be set so that participants are encouraged or discouraged from participating for example, more convenient office locations or office hours could be set to encourage more eligible people to participate. This chapter presumes that part of the reason USDA estimates WIC eligibility ancl par- ticipation is to better understand the performance of the program (e.g., coverage rates) ancl to understand what factors affect program participa- tion; ancl it presumes that the estimates are not used solely to guide buclget- . . ary c recisions. The chapter begins with a discussion of data sources that are available to estimate participation among eligible people. We then provide the panel's best estimates of WIC participation rates ancl discuss a method for making such estimates. Basecl on data from the Survey of Income ancl Program Participation (SIPP), we provide estimates from Bitler et al. (2002) that show that eligible infants have high WIC participation, eligible pregnant ancl postpartum women have somewhat lower participation, ancl eligible children ages 1 through 4 years have considerably lower participation. The 113

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114 ESTIMATING ELIGIBILI>~D PAR TICIPATION FOR THE ~CPROG~ chapter then shows examples of how USDA could model WIC participa- tion in order to consider how changes in program priorities or changes in policy might affect participation levels. For example, in examining corre- lates of WIC participation, Bitter et al. (2002) found that WIC participa- tion is higher in states with program rules that reduce the transaction costs of using the program (such as fewer required visits), but participation is not related to state-level measures of need, such as poverty and unemployment rates. 1 DATA SOURCES TO ESTIMATE WIC PARTICIPATION AMONG ELIGIBLE PEOPLE This section reviews data sources available to measure WIC participa- tion. The data sources reviewed include administrative data from the WIC program and data from surveys of the national population, the Current Population Survey (CPS) and SIPP. Both the CPS and SIPP have different strengths and limitations for estimating eligibility, which we discussed in Chapter 5. In this section, we focus on their strengths and limitations for measuring participation. Administrative data cannot be used to estimate eligibility because such data contain information only on WIC participants and would therefore miss eligible nonparticipants. They can, however, be used to check survey reports of participation, and so are discussed in that context here. Table 8-1 lists a number of characteristics of interest for esti- mating WIC participation that are available in selected data sets. Administrative Data The official USDA numbers regarding WIC caseloads come from counts of the number of people who actually received WIC services in a given month. People who have been certified as eligible and thus who are "on the books" but are not receiving services for some reason are not counted. A shortcoming of the official administrative caseload data is that they are not broken out by demographic subgroups, such as age, race, and education level. To remedy this deficiency, USDA conducts a biannual sur- vey of state program directors called the Survey of Program and Participant Characteristics. In addition to information about such participant charac- (2002). 1The content of this part of the chapter draws heavily from Bitler, Currie, and Scholz

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ESTIMATING WICPARTICIPATIONAMONG ELIGIBLE PEOPLE 115 teristics as race and age, this survey asks detailed information about state program characteristics, which we discuss below. Periodically, the Food and Nutrition Service (ENS) at USDA surveys a nationally representative sample of persons certified for WIC. These sur- veys allow FNS to assess the degree of need of WIC recipients and also to verify actual eligibility of persons certified for WIC. Most recently, the Survey of WIC Participants and their Local Agencies sampled persons cer- tified for WIC in spring 1998. 1995-1999 CPS Food Security Supplements2 The Food Security Supplement (FSS) is one of two different supple- ments to the regular monthly CPS that collects data on WIC participation (the annual March demographic survey is the second). The FSS contains questions about WIC participation, but it does not have enough informa- tion on income to assess WIC eligibility. The FSS provides information about whether anyone in the household received WIC benefits in the 30 days prior to the interview. A limitation of these data is that the program participation questions are asked about the household rather than about the individual, making it impossible to determine which members of the household receive benefits. A second significant problem is that households are screened before they are asked about participation in food programs, so that only households with incomes below a certain level are asked the ques- tions.3 Since the income screen depends on the number of persons in the household, the size of the household is critical to determining whether or 2This section draws from the 1995 CPS Food Security Supplement Interviewer In- structions (CPS Interviewer Memorandum no. 95-05) and from Attachment 9 of the Au- gust 1998 CPS Technical Documentation, which is the Food Security Supplement Ques- tionnaire. The Food Security Supplement was administered in April 1995, 1997, and 1999 and in September 1996 and August 1998. 3Households without this income measure ("don't know or refusals") were also asked about their use of food assistance programs. The annual income cutoff was $15,000 for a one-person household and then went up by $5,000 for each additional household member up to a household size of six. For households of seven or eight persons, the cutoffwas $50,000, for nine persons it was $60,000, and for larger households it was $75,000. WIC participa- tion questions were further restricted to households with categorically eligible persons, spe- cifically, households containing women ages 15-45 or a child under age 5. Households were first asked whether any household member had received WIC in the last 30 days. Those who answered yes to this question were then asked how many persons in the household had

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116 ESTIMATING ELIGIBILI>~D PAR TICIPATION FOR THE ~CPROG~ TABLE 8-1 Descriptions of National Sources of Data Related to WIC Participation Data Source Participant Counts Rates FNS administrative counts (88-00) by state, for month aggregate data USDA FNS PC surveys by region, for April 92, 94, 96, 98 National Survey of WIC Recipients and their Local Agencies CPS Food Security Supplements (95-99) by state, for month before survey was done, Household data CPS Annual Demographic File (98-01) by state, for previous calendar year, individual data SIPP (1996, waves...) By state, by month, Individual data All, women, children 1-4, infants; Y women by category 91-00 All, women by category, children, Y r Intents Nationally representative sample of Y WIC recipients in the contiguous US certified in spring 1998 T1 r Ott lr pass income screen estimate: women, infants, children in household Women if pass income screen. Estimate: Y children, infants in family of women Any person last month y Acronyms: AFDC = Aid to Families with Dependent Children CPS = Current Population Survey FNS = Food and Nutrition Service PC = participant characteristics SIPP = Survey of Income and Program Participation TANF = Temporary Assistance for Needy Families USDA = U.S. Department of Agriculture WIC = Special Supplemental Nutrition Program for Women, Infants, and Children

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ESTIMATING WICPARTICIPATIONAMONG ELIGIBLE PEOPLE 117 Demographics Income Calculate Participation Eligibility Regs. Other Public Assistance Programs Effects of WIC on other outcomes? N y y y y N N Y. State level Y Y N Y Y N N N N Y (only N annual income) Y. State and individual level Y. State and individual level NA (Other N Government Sources) AFDC/TANF N Food Stamps Medicaid N Food Stamps (HH measured last month) AFDC/TANF N Food Stamps Medicaid AFDC/TANF Food Stamps Medicaid

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118 ESTIMATING ELIGIBILITY AND PAR TICIPATION FOR THE WIC PROGRAM not the questions are asked. In practice, the FSS uses the full number of persons in the household, whether or not these persons are related. This definition of a household may not correspond to the one that would be used by a local WIC office to determine eligibility. This screening procedure is likely to result in the undercounting of persons receiving WIC for several reasons. First, in states with Medicaid thresholds above the income screen, some people eligible for WIC (and who receive it) are not even asked the WIC questions. Second, other eli- gible WIC recipients will have incomes above the screen in the first month in which a household is surveyed, but below that level in subsequent months.4 Working in the other direction, the FSS's use of the broadest possible measure of the household may help to mitigate the undercounting caused by the income screen because the WIC household may not include all the unrelated members of a household, but only those deemed by a WIC eligibility worker to be "sharing resources." A second screen was added prior to the program participation ques- tions in 1998 and 1999. In addition to asking WIC questions to all house- holds passing the income screen (and all those responding "don't know" or "refuse"), households who answer "yes," "don't know," or "refuse" to a fur- ther screening question about food insecurity are asked about participation in food assistance programs.5 This additional question will mitigate the undercounting induced by the income screen only if those who are missed by the income screen experience this type of problem. In order to assess the effect of this change in the screen, Bitter et al. (2002) constructed a WIC participation measure that uses a consistent screen by discarding those per- sons who were asked about WIC only because of the new screening ques- tion. The less restrictive screening procedure yielded additional participants received WIC. This value was top-coded at 4, although relatively few households are likely to have been impacted by the top-coding, given that, in general, few households will have more than four people participating in WIC. Unless the number of persons receiving WIC is exactly equal to the number of persons who are potentially eligible, we cannot identify the specific people in the household receiving benefits. 4The FSS was not necessarily administered in the same month in which the household entered the survey, so there could easily be income discrepancies between the screening ques- tions and the household's status at the time of the FSS. 5The additional question reads: "People do different things when they are running out of money for food in order to make their food or their food money go further. In the last 12 months. . ., did you ever run short of money and try to make your food or your food money go further?"

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ESTIMATING WICPARTICIPATIONAMONG ELIGIBLE PEOPLE 119 (between 0.89 and 0.97 million). This provides evidence that the income screen causes some participants to be missed. Annual Demographic File (March CPS)6 Starting in 1998, experimental questions on program participation were added to the March CPS. Two specific questions ask whether any females age 15 or older in the household participated in WIC in the last calendar year and the number of WIC participants in the family. In 2001, these variables were included in the publicly released data file for the first timed As in the FSS, the March CPS questions are asked only if the household's income is less than an income screen, but the income screen is generally much higher than in the FSS, and so would be expected to result in less undercounting.8 The March CPS offers a significant advantage over the FSS in that it measures household income and it also asks questions about participation in other programs, such as welfare and Medicaid. The latter is particularly important, since those who participate in Medicaid are adjunctively eli- gible for WIC, and Medicaid often has income cutoffs above 185 percent of federal poverty guidelines. 6This information comes from Appendix D of the 2001 March CPS Technical Docu- mentation, the CPS Field Representatives/Interviewer Memorandum No. 2001-03 Items Booklet Feb/March/April 2002, which is the Facsimile of March Supplement Question- naire, along with the 1998-2000 questionnaires. 7The WIC and food stamp questions in the March CPS refer to participation in the last year rather than in the last month, so they are not directly comparable to the FSS questions. Counts of WIC recipients are almost certain to be higher in the March CPS than in the FSS. 8In 1998-1999 the cutoff for being asked the WIC questions in the March CPS was $20,000 for one-person households, $30,000 for two- or three-person households, and $50,000 for four- or more person households. In 2000-2001 the screen was $30,000 for one-person households and $50,000 for larger households. Persons who answered "don't know" "refuse" to the income question were also asked WIC questions. Thus, households with fewer than seven possibly unrelated persons were more likely to be asked the WIC questions in the March CPS than in the FSS, while those with more members would be less likely to be asked in the March CPS than in the FSS. We examined the importance of the different income screens by also imposing the narrower FSS screen onto the March CPS data. Of people asked the WIC questions by the FSS, only 58 would have been missed by the March CPS. But half of those asked the WIC questions in the March CPS would have been missed under the FSS income screens.

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120 ESTIMATING ELIGIBILII~YANDPARTICIPATIONFOR THE WICPROGRAM Survey of Income and Program Participation SIPP asks about WIC each period for all households with a woman age 15-45. There are no other screens. Unlike the CPS surveys, SIPP asks which individuals in the household receive WIC. Hence, it is straightforward to estimate WIC eligibility and participation among eligible people using SIPP. WIC and Other Transfers in the CPS and SIPP Reports of WIC Receipt Program participation is generally undercounted in social surveys. Bitler et al. (2002) provide an analysis that shows substantial underreporting of WIC participation in the CPS and SIPP. The ratio of the estimated number of persons who report WIC receipt to the administrative totals is about 0.7 in the FSS data. Underreporting for infants is even worse than underreporting for adults, with a ratio of around 0.6. Reported WIC cov- erage in SIPP is similar to the FSS. SIPP appears to have somewhat better coverage of WIC infants than the CPS, but still only three-quarters of in- fant WIC recipients appear in SIPP. The undercount of food stamp partici- pation is much less severe than the undercount of WIC participation. Bitler et al. (2002) found that population estimates of the number of food stamp recipients in the FSS and in SIPP account for 85 percent of the administra- tive totals. There is less undercounting of Medicaid, Aid to Families with Dependent Children (AFDC), and Temporary Assistance for Needy Fami- lies (TANF) participation in both of these data sets. In 1999 and 2000, the March CPS estimates of the number of WIC participants were over 90 percent of the number of actual WIC recipients. One possible reason for the relatively higher coverage of the March CPS compared with the FSS is that the income screen was higher, so that more participating households are actually asked the questions about WIC par- ticipation. Bitler et al. (2002) estimate that the more generous income screen in the March CPS adds 890,000 WIC recipients in 1999 and 970,000 in 2000, relative to what would have been obtained with the more restrictive FSS screens. However, the March CPS asks about WIC receipt at any point during the year. Iffamilies receive WIC for fewer than 12 months a year, the average months of receipt will exceed the count of the number of families receiving WIC at some point during the year.

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ESTIMATING WICPARTICIPATIONAMONG ELIGIBLE PEOPLE 121 Characteristics of WIC Recipients Nationally and in the CPS and SIPP These results raise the question of whether the data are acloquate for supporting analyses of WIC eligibility ancl participation. One way to assess potential biases that might arise from using the CPS ancl SIPP to study WIC, is to compare the characteristics of WIC recipients in the CPS ancl SIPP with those reported from the ENS publications WIC Participants and Program Characteristics 1998, a census of WIC recipients in April 1998, ancl the National Survey of WIC Participants and Their Local Agencies, a survey of WIC recipients. Bitter et al. (2002) show that for April 1998 (the reference period for the 1998 national survey), the distribution of race ancl ethnicity of the WIC population is very close to that in the national data in the FSS ancl the March CPS. The proportion of the WIC sample in SIPP that is black closely matches the national totals, but SIPP seems to overrepresent white WIC recipients ancl unclerrepresent Hispanic recipients. SIPP more accurately allocates WIC recipients into categorical eligibility groups than the CPS. Since the CPS does not identify which people in the household actually receive WIC, analysts must either assume that everyone within the house- holcl gets benefits or make some alternative ad hoc assumption. One striking discrepancy between the survey data ancl the aclministra- tive data is that income for the total WIC population ancl across almost every subgroup is higher in SIPP ancl the March CPS than it is in the national WIC survey, even when using a family rather than a household measure of income in the CPS. The fact that WIC participants appear to have higher incomes on average than those that are reported to WIC acl- ministrators does not necessarily imply noncompliance with program rules, since the incomes reported to CPS ancl SIPP surveyors remain below WIC cutoffs. We estimate that in the 2000 March CPS, for example, 80 percent of WIC participants reported incomes less than 185 percent offecleral pov- erty guiclelines, ancl 48 percent had incomes less than 100 percent of the guiclelines. Furthermore, given the flexibility that WIC staff workers have in determining the time period for which income is measured to establish .. ..... . . . . . . . . ellglulllty anc ~ income variation over the year, it IS not surprising that the survey ancl administrative data do not match. It is clear that the FSS, the March CPS, ancl SIPP unclercount WIC recipients, ancl the problem is more severe for WIC than it is for other transfers. But these comparisons suggest that missing recipients appear to be approximately randomly distributed across categorically eligible WIC

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122 ESTIMATING ELIGIBILII~YANDPARTICIPATIONFOR THE WICPROGRAM groups. While the incomes of WIC recipients are higher in the CPS and SIPP than in the WIC administrative data, it is plausible that incomes are underreported to WIC administrators. But the discrepancies documented in this section serve as a qualification to CPS- and SIPP-based analyses of WIC. Those with incomes greater than 185 percent of federal poverty guidelines are likely to be adjunctively eligible. Despite underreporting of WIC participation in the CPS and SIPP, the characteristics of WIC recipients in the SIPP and CPS are similar to the characteristics of WIC recipients nationally. We conclude that SIPP- and CPS-based analyses of WIC may be informative. These comparisons sug- gest that estimates of WIC eligibility and participation based on the CPS could be improved with several modifications to the current methods used by the FSS and the March CPS to obtain information on WIC participa- tion. RECOMMENDATION: The income screen used to determine whether a CPS Food Security Supplement respondent is asked survey questions about WIC participation should be modified or eliminated so that all people who are in fact eligible for WIC are asked the ques- tion about WIC participation. RECOMMENDATION: The March CPS and the Food Security Supplement should ask which individuals in the household receive WIC. RECOMMENDATION: A monthly measure of WIC participation should be collected on the March CPS and the Food Security Supple- ment. A more appropriate income screen for the WIC participation ques- tions in the FSS would mean that more people who are eligible and who may participate in WIC will be asked about their WIC participation, and more accurate measures of WIC participation could be made. Asking which individuals in the household receive WIC would help parcel out participa- tion counts into eligibility categories. Two alternative measures of monthly WIC participation could be considered. One could ask about WIC partici- pation for each month in the year prior to the survey. This would yield a more accurate measure of WIC participation than the current annual mea- sure used which asks about WIC participation in the prior calendar year and it would correspond to the time period for which income is

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ESTIMATING WICPARTICIPATIONAMONG ELIGIBLE PEOPLE 123 measured in the March CPS. Still, recall errors could be introduced. Asking about WIC participation in the month prior to the survey would presum- ably result in a more accurate measure of WIC participation than the cur- rent method, because it does not require as long a recall period. However, this measure would not correspond to the period over which income is measured in the survey and covers only one month. The March CPS has many uses beyond calculating WIC eligibility and participation, and USDA does not have the authority to make these recom- mended changes. However, it does sponsor the collection of the Food Secu- rity Supplement by the Census Bureau. To the extent that the questions on WIC in these two CPS supplements can be modified without compromis- ing the other goals of the survey, the panel recommends these changes be- cause the resulting improvements in data quality would clearly enhance the value of the CPS for analyzing WIC participation. WIC PARTICIPATION AMONG ELIGIBLE PEOPLE In this section we estimate the percentage of people who are income and categorically eligible who participate in WIC. The SIPP data are used to make these estimates because the data set allows direct observation of pregnant and postpartum women, because it includes monthly income for modeling eligibility, and because it specifies which household members re- ceive WIC benefits. In order to be income eligible for WIC, a categorically eligible person must have income less than or equal to 185 percent of federal poverty guidelines, or be enrolled in a program, for example Medicaid, which con- fers adjunctive eligibility. The calculations reported in this section are based on the assumption that any family whose monthly income falls below 185 percent of federal poverty guidelines is eligible for reasons discussed in Chapter 5. Although WIC offices may use annual income in some circum- stances, we believe that the use of monthly income more closely approxi- mates the concept of income that is generally used in practice. Once an individual becomes eligible for WIC, it is assumed that she remains eligible for the relevant certification period. These estimates also presume that all income-eligible persons are nutritionally at risk and fully eligible for WIC. Estimates of Participation Among Eligible People Table 8-2 presents information on average monthly WIC eligibility and participation in 1998. In the first panel, for example, we classify all

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124 ESTIMATING ELIGIBILI>~D PAR TICIPATION FOR THE ~CPROG~ TABLE 8-2 WIC Eligibility and Participation Average Monthly Totals for 1998 Number Percentage Total Infants 4,078,482 100.0 Eligible for\VlC 2~367~746 58.1 Not eligible for \VIC 1'710~736 41.9 Eligible participants 1,734,276 73.2 Eligible nonparticipants 633,470 26.8 Ineligible participants 105,724 5.7a Total Children Ages 1-4 15,947,451 100.0 Eligible for\VlC 9~039~031 56.7 Not eligible for \VIC 6,908,420 43.3 Eligible participants 3,423,755 37.9 Eligible nonparticipants 5,615,276 62.1 Ineligible participants 196,245 5.4a Total Pregnant and Postpartum Women 3,859,628 100.0 Eligible for \VIC 2,087,530 54.1 Not eligible for \VIC 1,772,098 45.9 Eligible participants 1,388,396 66.5 Eligible nonparticipants 699,134 33.5 Ineligible participants 91,604 6.2a aPercentages are the percentage of all participants who are not eligible to participate. SOURCE: Bitler, Currie, and Scholz (2002~. infants in SIPP in each month of 1998 into estimated eligibles and ineligibles and into those who do and do not receive WIC. For this portion of the analysis, an adjustment that increases the number of WIC recipients by the amount that the SIPP data undercounts recipients in a particular group is made, using the administrative data as the benchmark. These allo- cated individuals are placed in the eligible and ineligible groups in the same proportion as individuals whose status is observed in the data. A corre- sponding adjustment to the number of nonrecipients is made, reducing the number of eligible and ineligible nonrecipients by the increase in the num- ber of eligible and ineligible recipients. The first panel of the table shows that 58 percent of all infants were eligible for WIC in a given month in 1998. The WIC participation rate

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ESTIMATING WICPARTICIPATIONAMONG ELIGIBLE PEOPLE 125 among eligible infants was 73 percent. We also find that, of the infants receiving WIC, 6 percent were estimated to be ineligible for the benefits. This error rate is consistent with the error rate for infants reported in the National Survey of WIC Participants (U.S. Department of Agriculture, 2001). The second panel of the table shows a similar analysis for children. Of the 16 million children in this age group, 57 percent are estimated to be eligible for WIC. Of the 9 million eligible children, 38 percent receive WIC benefits. Of the 3.5 million children receiving benefits, we estimate that 5.4 percent do not meet the income or adjunctive eligibility criteria (and have not done so in the past six months). Thus, our evidence is consis- tent with that of Burstein et al. (2000), who show, using data from the 1993 SIPP, that infants are much more likely than older children to partici- pate in the program. Indeed, Burstein et al. show that many children exit on their first birthdays, when the dollar value of the WIC package decreases (since it no longer includes infant formula). The third panel of the table presents information on WIC eligibility and participation by pregnant and postpartum women for the first 6 months postpartum.9 We are not able to consider the second 6 months postpartum when only women who are breastEeeding are eligible, since we cannot observe their infant feeding practices and did not want to assume a distribution of women allocated into breastEeeding status by eligibility sta- tus. Of the 3.9 million pregnant women and women less than 6 months postpartum, 2.1 million or 54 percent are eligible for WIC. Of those who are eligible, 66.5 percent actually receive benefits.l We estimate that 6.2 percent of the 1.5 million women receiving WIC are not eligible for ben- efits. We have the least amount of confidence in our estimates for women, because, as shown in the table, the WIC undercounting problem in SIPP is 9The analysis for women is somewhat more complicated than the analyses for infants and children. Weighted estimates suggest that roughly 364,000 women report receiving WIC, yet they do not appear to have a child (or fetus) of an age that would lead them to be eligible. In the bottom panel of Table 8-2, we allocate these women to categorically eligible groups in proportion to the groups whose status we do observe. This procedure results in allocating 56 percent of the unclassified women to the "pregnancy group," 29 percent to nonbreastfeeding postpartum, and the remainder to breastfeeding. 10The participation rate (among eligibles) cannot be 100 percent for pregnant women under our methodology unless all pregnant women began receiving WIC benefits in the first month of pregnancy.

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126 ESTIMATING ELIGIBILI>~D PAR TICIPATION FOR THE ~CPROG~ more severe for women than it is for other groups. Hence, our assumption that unobserved WIC recipients should be allocated to eligible and ineli- gible status in the same proportion as observed WIC recipients (among the two groups of women) is a bolder assumption. The USDA has recently conducted another WIC income verification study where individuals receiving WIC were surveyed and information about their income and program participation status was collected. This study found that over all categories of eligibility, 4.5 percent of WIC par- ticipants appeared to be ineligible to receive WIC (USDA, 2001~. The figures provided by Bitler et al. (2002) are quite close to the USDA esti- mates. The results in Table 8-2 are striking, since they suggest that a program that served all eligible people would be considerably larger than the current one. Only 73 percent of eligible infants, 67 percent of eligible pregnant and postpartum women, and 38 percent of eligible children ages 1 to 4 receive benefits. These participation estimates differ sharply from the implied WIC par- ticipation rates used to prepare budget estimates. Recall that the USDA methodology assumed that 80 percent of eligible persons would participate in WIC. Estimates shown here indicate that participation rates among eli- gible people in each eligibility category are lower than the rates obtained using the current USDA methodology. Participation rates for children, par- ticularly, are much lower than 80 percent. CONCLUSION: WIC participation rates among eligible persons are substantially lower than the 80 percent rate assumed in the process of estimating the number of eligible people likely to participate in WIC. WIC participation rates also vary substantially across eligibility category. These participation rate estimates are based on eligibility estimates that differ from the estimates used to produce the current USDA eligibility estimates. Our eligibility estimates are based on the SIPP data rather than the CPS. Furthermore, our eligibility estimates use monthly rather than annual income, account for certification periods, and account for adjunc- tive eligibility factors that the panel demonstrated should be taken into account so that the estimates reflect program rules regarding eligibility as closely as possible. The denominators used to estimate these participation

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ESTIMATING WICPARTICIPATIONAMONG ELIGIBLE PEOPLE 127 rates (which are estimates of the number of eligible people) are thus larger than those used by the current estimation methodology. If those who report WIC participation even though they are not eli- gible are included as participants, these estimated participation rates (using the same estimate of eligibility that is, the same denominator) would in- crease to 78 percent for infants, 40 percent for children, and 71 percent for pregnant and postpartum women. Given these estimates, the USDA's 80 percent participation assumption is very close to the estimated participa- tion rate for infants and not far off for pregnant and postpartum women. However, participation rates for children are much below the 80 percent assumption. Coverage Rates Recalculated USDA's estimated coverage rates (the ratio of WIC participants from administrative data to the estimated number of eligible persons) were re- ported in Table 2-1. For the past several years, those coverage rates were estimated to exceed 100 percent for infants and for postpartum women, and to range from 60 to 70 percent for children and pregnant women. The estimates of eligibility presented in this chapter imply that actual coverage rates are much lower than reported in Chapter 2. Using the 1998 estimates of eligibility based on SIPP data (Table 8-2) and the 1998 administrative total number of WIC participants from administrative data, we estimate a coverage rate of 79.6 percent for infants and 41.5 percent for children. For the same year, coverages rates based on USDA estimates of eligibility were 127.7 percent for infants and 74.4 percent for children. We did not esti- mate participation rates for pregnant women separately from postpartum women and so cannot estimate new coverage rates for these groups. How- ever, coverage rates for pregnant and postpartum women based on these estimates of eligibility should also fall. CONCLUSION: Coverage rate estimates based on currently used methods of estimating eligibility are overstated. Coverage rates for chil- dren, infants, and women based on eligibility estimates that account for monthly income, adjunctive eligibility, andWIC certification prac- tices are substantially lower than those based on current estimation methods.

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128 ESTIMATING ELIGIBILII~YAND PAR TICIPATION FOR THE WIC PROGRAM RECOMMENDATION: If participation rate estimates are used to make budgetary forecasts or to understand responses in changes to program rules and policies, separate estimates should be made for each eligibility category. FACTORS CORRELATED WITH WIC PARTICIPATION The decision to participate in WIC is a choice that a family makes (if they are eligible). In making this choice, the family may weigh what it believes to be are the benefits of WIC (the value and content of the food packages and the value of nutritional services and referrals) against what they believe are the costs of the program (e.g., time and effort to find out about the program, going into the WIC office, going through the eligibility screen, a stigma of participation) in deciding whether to go through the eligibility screening process.1l Understanding the factors that affect WIC participation could be ad- vantageous to program administrators because such information could be used to forecast changes in participation levels (e.g., in times of recession) or to understand where outreach might be most effectively targeted. In this section, we outline a framework for considering WIC participation. We examine four sets of factors that may influence WIC participation. First, we examine how participation in WIC correlates with participation in other programs. For example, current ENS methodology for estimating eligibil- ity and participation assumes that WIC participation is closely linked to participation in the food stamp program but ignores the linkage between WIC and Medicaid. Second, personal characteristics may make people more or less likely to participate. Third, WIC program characteristics differ substantially from state to state, and these variations may also be linked to differences in WIC participation. Fourth, such external factors as the economy or birth rates may change, and that may affect eligibility and . . . partlclpatlon. 1lIn weighing the costs and benefits of WIC participation, it is possible that a family may change its behavior to make itself eligible for WIC (e.g., the benefits of the WIC pro- gram are enough to affect a woman's labor supply decisions and hence affect her income). However, the value of the food packages is small enough to make it hard to believe that the presence of the WIC program greatly affects this choice. The panel's estimates of participa- tion assume that income is exogenous to this decision.

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ESTIMATING WICPARTICIPATIONAMONG ELIGIBLE PEOPLE 129 We summarize work conducted by Bitter et al. (2002), who used three different models and data sets to examine WIC participation. They exam- ined (1) state-level variations in WIC participation using state administra- tive data from 1992-2000 and (2) individual-level differences in partici- pation with individual-level data from the March CPS for years 1997-2000 and 1998 SIPP data. The state-level model is estimated to better understand how features of the administration of WIC programs (e.g., food package costs, timing of benefit issuance) are correlated with participation; how WIC program characteristics and other program char- acteristics (e.g., the maximum monthly AFDC/TANF benefit or the Med- icaid eligibility threshold) are correlated with participation; and how state- level economic and demographic characteristics (e.g., the unemployment rate or the percentage of births to unmarried mothers) are correlated with WIC participation. State-Level Models of WIC Participation Results from Bitter et al. (2002) show that variations in WIC partici- pation over the period 1992-2000 are not strongly related to changes in need, at least as measured by the unemployment rate or the poverty rate. However, demographic characteristics are important. The share of the state population that is Hispanic has a consistently large and positive effect on WIC participation rates. The share of blacks has the opposite effect. The share of births to unmarried mothers has a significantly negative effect on the probability that children participate. The programmatic variables indi- cate that there is no strong relationship between WIC participation and AFDC/TANF participation. However, higher AFDC/TANF benefits are associated with lower WIC participation rates, perhaps because the larger TANF benefits offset the need for the relatively smaller WIC benefits. The Medicaid enrollment rate is positively associated with WIC participation among children but negatively associated with participation for infants. Features of the way that WIC programs are administered across states are also correlated with participation levels in states. The cost of the women's food package is positively correlated with participation for children, mean- ing that the higher costs of women's food packages are associated with higher levels of participation for children, and negatively correlated with participation for infants, meaning that the higher costs of women's food packages are associated with lower levels of participation for infants. This coefficient is difficult to interpret, however, given that if a woman does not

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130 ESTIMATING ELIGIBILITYANDPARTICIPATIONFOR THE WICPROGRAM breastSeed, the value of her food package is smaller than if she does, but the value of her infant's food package increases because of the addition of for- mula given to her infant. Three other characteristics that relate to the strin- gency with which the programs are operated are negatively correlated with participation: dispersing WIC benefits monthly (as opposed to less fre- quently, which means fewer visits into the WIC office), requiring proof of income, and having a higher nutritional risk cutoff for pregnant women. These models were estimated with state fixed effects that is, a dummy variable for each state was included in the model to control for unmeasured differences between states. The results indicate that there is considerable variation in total WIC participation rates across states, even after control- ling for all the variables included in these models. Differences may reflect important unobserved differences in the way that the program operates across states and suggest that further information about how the program is operated might be useful in explaining WIC participation. Individual-Level Models Individual-level data from the March CPS and SIPP were used to ex- amine individual characteristics associated with WIC participation among eligibles. Several findings are consistent across both data sets. First, Medic- aid enrollment is strongly linked to WIC participation. Results based on the SIPP data show that Medicaid participants are 50 percent more likely to participate in WIC than those not enrolled in Medicaid. Food stamp participation is also positively associated with WIC participation, but the association is not as strong. Results from both data sets also show that Hispanics are more likely to participate in WIC than whites, and Asians are less likely to participate than whites. The mother's education level is nega- tively associated with WIC participation (i.e., more educated mothers are less likely to participate). This finding may reflect a lack of awareness among some more educated women of their eligibility (i.e., because income eligi- bility levels for low-income assistance programs are not typically as high as 185 percent of poverty), or a higher opportunity cost of participating in the program among the more educated. These analyses of WIC participation suggest several tentative conclu- sions. First, WIC participation does not seem to be strongly correlated with state-level indicators of economic need, such as poverty and unemploy- ment rates. Given the WIC income eligibility cutoff of 185 percent of federal poverty guidelines, it is possible that many families who fall into

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ESTIMATING WICPARTICIPATIONAMONG ELIGIBLE PEOPLE 131 poverty as a result of an economic recession were already eligible for WIC. Second, WIC participation is strongly associated with individual demo- graphic characteristics, such as education, race, and marital status, even after conditioning on income. For example, eligible Hispanics are more likely to participate in WIC, while eligible Asians are less likely. These find- ings could, for example, be used as an indicator that outreach targeted toward Asian women might be beneficial. Third, WIC program character- istics may play an important role in WIC participation. In general, factors that increase the transaction costs of applying for WIC (e.g., monthly dis- tribution of benefits compared with quarterly distribution) are associated with reduced participation. This type of analysis could be conducted in a state using local-level data. Such an analysis could give state-level officials a better idea of how administrative changes in the programs could be made in order to achieve program goals. These results have important implications for the process of forecast- ing future WIC participation levels. On one hand, if the economy does not have a huge impact on levels of participation, then it may not be crucial to account for changes in the economy when forecasting participation levels into future years, although changes in the economy will affect the number of people who are eligible for WIC. On the other hand, participation rates differ significantly across demographic groups. Demographic changes among groups with high propensities to participate could affect the overall participation rate. Although demographic changes can be slow to occur, such changes could introduce uncertainty in the forecasted counts. Results from these analyses also suggest that changes in program rules or adminis- trative practices are associated with changes in participation rates. Thus, another source of uncertainty in forecasted estimates of participation is introduced if states change the way they run their WIC programs or if changes in program rules are implemented. The next chapter discusses the implications of these results while comparing different methods for fore- casting WIC participation. SUMMARY This chapter has reviewed data sources for estimating WIC participa- tion among those who are estimated to be eligible for WIC. This review found that SIPP is a good source of data for these estimates. Furthermore, it was noted that the March supplement to the CPS and the Food Security Supplement of the CPS could be used to estimate WIC participation, but

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132 ESTIMATING ELIGIBILITYANDPARTICIPATIONFOR THE WICPROGRAM there are limitations. The FSS procedure to screen for WIC participation results in not asking some people who are eligible for WIC and may partici- pate in it whether they receive WIC. And neither the March CPS nor the FSS asks for monthly measures of WIC participation or collects informa- tion on which individuals in the household receive WIC. The panel recom- mends improvements to these data sources that will improve estimates of . . . - . . participation among ellglule persons. Results from the Bitter et al. (2002) study that used 1998 SIPP data to estimate eligibility and participation show that participation rates are much lower than the 80 percent participation rates used in USDA's current meth- odology. Furthermore, participation rates vary considerably across eligibil- . . try categories. Finally, the panel outlined a framework for estimating the relationship between WIC participation and demographic characteristics, economic conditions, and state programmatic conditions. Results of this analysis show that WIC participation is not closely related to economic conditions, but it is strongly associated with some demographic characteristics of individuals (e.g., Hispanics are more likely to participate than Asians) and that state- level administrative and program rules can affect WIC participation.