@ Mathematica. Progress Together How Did the COVID-19 Pandemic Affect the Education and Employment of Young People with Disabilities? Findings from the Promoting Readiness of Minors in Supplemental Security Income (PROMISE) Evaluation December 15, 2022 Anna Hill, Ankita Patnaik, and Isabel Musse Submitted to: Submitted by: Social Security Administration Mathematica Office of Research, Demonstration, and 1100 First Street, NE, 12th Floor Employment Support Washington, DC 20002-4221 6401 Security Blvd., 4303 Annex Building Phone: (202) 484-9220 Baltimore, MD 21235 Fax: (202) 863-1763 Project Officer: Jeffrey Hemmeter Project Director: Gina Livermore Contract Number: SS00-13-60044 Reference Number: 40304.6BC This page has been left blank for double-sided copying. Acknowledgements This study is part of the Promoting Readiness of Minors in Supplemental Security Income (PROMISE) national evaluation. The authors would like to thank the many people who made the PROMISE evaluation possible and who contributed to this report. We are especially grateful to the youth, parents, and guardians who enrolled in the evaluation and provided data about their lives. The evaluation would not have been possible without the invaluable support provided by staff at the U.S. Department of Education and the six PROMISE programs. We thank the PROMISE project officer at the Social Security Administration, Jeffrey Hemmeter, who contributed his keen insight and useful guidance to the evaluation in general and this report in particular. At Mathematica, we received notable assistance from many colleagues. Christian Carrillo, Addison Larson, Jeremy Page, and Liz Potamites provided excellent programming support. Karen Katz and Cayla Roby provided operations support, Donovan Griffin provided editorial assistance, and Jill Miller and Colleen Fitts provided production support. This report benefited greatly from careful review by Gina Livermore and Sheena McConnell. We thank everyone for their valuable input and support. The opinions and conclusions expressed in this report are solely those of the authors and do not represent the opinions or policy of any agency of a state or the federal government. Mathematica® Inc. This page has been left blank for double-sided copying. Contents ACKNOWIEAGEMENES ... e e e e e e e e e s r e e e ee e annee iii Acronyms and ADDreviations ... XV EXECULIVE SUMMENY ..ottt e e me e e e s m e e e e e smmne e e e e e mne e e e e amneeeas Xvii A. Study context and research qUESLIONS..........ccccooiiiiiicnie xvii O T T [ o T XVii C. Implications for policy and practiCe...........cccovricciiiiieseeee e Xviii Lo INEPOAUCHION ... e e s s e e e e e e e e e e anne e e e e nnnne 1 [I. Data and Methods............cciiiii i e e e 3 A. Data and SAMPIES........corriiiieiiieiceeeeeeee et e e e e e nnne e eeeea e aan 3 B. Methods and MeaSsUIES ... e e s sr e 4 lll. Youth Outcomes Before and During the Pandemic..........cccccooiiiniiiiieinnnieee e 9 A. ECONOMIC OULCOMES .......uviieiiiiiiire ittt s e s nne e 9 B. Education OULCOMES ...........coiiiiiieeee et e 13 IV. PROMISE Program Impacts Before and During the Pandemic.............ccccooeiiiriiinericciinee 17 A. Five-year impacts measured before and during the pandemic............ccoccooiiriiiiieee. 17 B. Impacts on employment rates and SSA payments by month ..................ccccceneen . 21 V. CONCIUSIONS ....oeiiiiiitiiiieirie e e e s e e s r e sr e e ses b r e e e s s sasae e s sensn e e e e s sennrnessennne 25 A. Discussion Of fINAINGS ....cccoeeiiiiiiicieeeir e e e s e e e e e e e e e e ean 25 = I 0 1 =1 (o o T PR 26 C. Implications for policy and practice...........cccccceeei i ccciicsiiee e 28 (= =T = 3 o= P 31 =T LT o= TN o] o 1= o Vo [ A1 A. Differences between pre- and during-pandemic survey respondents............c...ccveenn. A3 B. Supplemental results: Youth outcomes before and during the pandemic.................. A21 C. Supplemental results: PROMISE impacts before and during the pandemic.............. A.64 D. Time periods for analyses of SSA program participation outcomes ...........ccccccee..... A.79 Mathematica® Inc. This page has been left blank for double-sided copying. Tables 1.1 1.2 V.2 A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 (O 1] (olo] 0 Ll 0 [ T= L0 | 5 Outcomes examined for comparison of impacts before and during the pandemic (measured at the time of the survey, unless otherwise specified).......cccccccccevriicccnnnnnnnn. 7 Summary of differences in impacts between pre- and during-pandemic (=XYool aTo (=Y 07 E-T0 ¢ ) V2 o] e | = [ o o 21 The PROMISE programs and their enroliment periods..............cccccoeerieiiiccciiieeeeeenennn. A3 Impacts on youth's outcomes during the 18 months after random assignment, by whether the youth completed the five-year survey before or during the pandemic (values in percentages unless otherwise noted).........cccccoivciicciiiincc e, A.6 All PROMISE programs: Baseline characteristics of youth survey respondents, by timing of survey response (percentages, unless otherwise noted)........................... A7 Arkansas PROMISE: Baseline characteristics of youth survey respondents, by timing of survey response (percentages, unless otherwise noted) ............cccceeverieenns A.9 ASPIRE: Baseline characteristics of youth survey respondents, by timing of survey response (percentages, unless otherwise noted)..............ooceeieeciiiieieen e, A1 CaPROMISE: Baseline characteristics of youth survey respondents, by timing of survey response (percentages, unless otherwise noted)...............ccceceecineinencccices A13 MD PROMISE: Baseline characteristics of youth survey respondents, by timing of survey response (percentages, unless otherwise noted)............ccccccvrrveeieericciins A.15 NYS PROMISE: Baseline characteristics of youth survey respondents, by timing of survey response (percentages, unless otherwise noted)............cccccevirvriniinricciinns A7 WI PROMISE: Baseline characteristics of youth survey respondents, by timing of survey response (percentages, unless otherwise noted)...............ccccoiivieeerccciaes A19 All PROMISE programs: Unadjusted means and standard deviations of PROMISE youth's outcomes, by research group and whether the youth completed the five-year survey before or during the pandemic (percentages, UNless Otherwise NOTEd) ... ... e A.22 All PROMISE programs: Unadjusted means and standard deviations of comparison youth outcomes, by SSI receipt and disability and whether the respondent completed the survey before or during the pandemic (percentages, unless otherwise Noted) ......... ..o e e e A.23 Arkansas PROMISE: Unadjusted means and standard deviations of PROMISE youth's outcomes, by research group and whether the youth completed the five- year survey before or during the pandemic (percentages, unless otherwise Mathematica® Inc. vii Tables A13 A14 A15 A.16 A7 A18 A19 A.20 A.21 A22 A23 A24 Arkansas PROMISE: Unadjusted means and standard deviations of comparison youth outcomes, by SSI receipt and disability and whether the respondent completed the survey before or during the pandemic (percentages, unless Otherwise NOLEA)........c.coei i e -- ASPIRE: Unadjusted means and standard deviations of PROMISE youth's outcomes, by research group and whether the youth completed the five-year survey before or during the pandemic (percentages, unless otherwise noted)........... ASPIRE: Unadjusted means and standard deviations of comparison youth outcomes, by SSI receipt and disability and whether the respondent completed the survey before or during the pandemic (percentages, unless otherwise noted)..... CaPROMISE: Unadjusted means and standard deviations of PROMISE youth's outcomes, by research group and whether the youth completed the five-year survey before or during the pandemic (percentages, unless otherwise noted)........... CaPROMISE: Unadjusted means and standard deviations of comparison youth outcomes, by SSI receipt and disability and whether the respondent completed the survey before or during the pandemic (percentages, unless otherwise noted)..... MD PROMISE: Unadjusted means and standard deviations of PROMISE youth's outcomes, by research group and whether the youth completed the five-year survey before or during the pandemic (percentages, unless otherwise noted)........... MD PROMISE: Unadjusted means and standard deviations of comparison youth outcomes, by SSI receipt and disability and whether the respondent completed the survey before or during the pandemic (percentages, unless otherwise noted)..... NYS PROMISE: Unadjusted means and standard deviations of PROMISE youth's outcomes, by research group and whether the youth completed the five- year survey before or during the pandemic (percentages, unless otherwise NYS PROMISE: Unadjusted means and standard deviations of comparison youth outcomes, by SSI receipt and disability and whether the respondent completed the survey before or during the pandemic (percentages, unless Otherwise NOted)....... ..o e e WI PROMISE: Unadjusted means and standard deviations of PROMISE youth's outcomes, by research group and whether the youth completed the five-year survey before or during the pandemic (percentages, unless otherwise noted)........... WI| PROMISE: Unadjusted means and standard deviations of comparison youth outcomes, by SSI receipt and disability and whether the respondent completed the survey before or during the pandemic (percentages, unless otherwise noted)..... All PROMISE programs: PROMISE youth's outcomes, by research group and whether the youth completed the five-year survey before or during the pandemic (percentages, unless otherwise Noted) ...........cooovvvieiicciicciie e Mathematica® Inc. viii Tables A.25 A.26 A.27 A.28 A.29 A.30 A31 A.32 A.33 A34 A.35 A.36 A.37 A.38 A.39 All PROMISE programs: Outcomes of comparison youth, by SSI receipt and disability and whether the respondent completed the survey before or during the pandemic (percentages, unless otherwise noted)...........ccccccceriviiiiicciiccsee e A.37 All PROMISE programs: Youth's SSA payments before and during the COVID-19 22 T (=Y o o PP A.39 Arkansas PROMISE: PROMISE youth's outcomes, by research group and whether the youth completed the five-year survey before or during the pandemic (percentages, unless otherwise Noted) ...........oeiiieieii e A40 Arkansas PROMISE: Outcomes of comparison youth, by SSI receipt and disability and whether the respondent completed the survey before or during the pandemic (percentages, unless otherwise noted)............ccccccee v A.41 Arkansas PROMISE: Youth''s SSA payments before and during the COVID-19 PANAEMIC. ......ceieei ettt e et e e e e e e e e e e e ne e e e e mbeee e e e sne e e e e s nseeeaeennne e e e e nnneeeaennnes A43 ASPIRE: PROMISE youth's outcomes, by research group and whether the youth completed the five-year survey before or during the pandemic (percentages, unless otherwise NOLEA) ... ... e e e e e A44 ASPIRE: Outcomes of comparison youth, by SSI receipt and disability and whether the respondent completed the survey before or during the pandemic (percentages, unless otherwise Noted) ..........cooeviviiiiicciiociee e A.45 ASPIRE: Youth's SSA payments before and during the COVID-19 pandemic........... AA47 CaPROMISE: PROMISE youth's outcomes, by research group and whether the youth completed the five-year survey before or during the pandemic (percentages, unless otherwise Noted) .........ccoevvviiiiicciiciiee e A.48 CaPROMISE: Outcomes of comparison youth, by SSI receipt and disability and whether the respondent completed the survey before or during the pandemic (percentages, unless otherwise noted) ........ccccccovr i A.49 CaPROMISE: Youth''s SSA payments before and during the COVID-19 pandemic... A.51 MD PROMISE: PROMISE youth's outcomes, by research group and whether the youth completed the five-year survey before or during the pandemic (percentages, unless otherwise Noted) ..o e A.52 MD PROMISE: Outcomes of comparison youth, by SSI receipt and disability and whether the respondent completed the survey before or during the pandemic (percentages, unless otherwise Noted) ........ ... A.53 MD PROMISE: Youth's SSA payments before and during the COVID-19 PANAEIMIC. ... eee et ee et e et e et e e e e e s me e e e e s e e et e e e ame e e e e s s e ee e e e amne e e e s amnn e e e e e amnneeas A.55 NYS PROMISE: PROMISE youth's outcomes, by research group and whether the youth completed the five-year survey before or during the pandemic (percentages, unless otherwise Noted) ...........cooev e e A.56 Mathematica® Inc. Tables A.40 A.41 A42 A.43 A44 A.45 A46 A47 A48 A49 A.50 A.51 A.52 A.53 NYS PROMISE: Outcomes of comparison youth, by SSI receipt and disability and whether the respondent completed the survey before or during the pandemic (percentages, unless otherwise noted) .........cccccovr i NYS PROMISE: Youth's SSA payments before and during the COVID-19 2= T o L= o o o WI PROMISE: PROMISE youth's outcomes, by research group and whether the youth completed the five-year survey before or during the pandemic (percentages, unless otherwise NOted) ... WI PROMISE: Outcomes of comparison youth, by SSI receipt and disability and whether the respondent completed the survey before or during the pandemic (percentages, unless otherwise nNoted) ........ccccccevr v WI PROMISE: Youth's SSA payments before and during the COVID-19 7= T To (=T 14 TT oSO PPP All PROMISE programs: Impacts on youth outcomes before and during the pandemic (measured at the time of the survey; values in percentages, unless Otherwise NOLEA)...........ooiiiiiii et e e s e n e e e e e e e e eas Arkansas PROMISE: Impacts on youth outcomes before and during the pandemic (measured at the time of the survey; values in percentages, unless Otherwise NOtEd)....... ..o e e ASPIRE: Impacts on youth outcomes before and during the pandemic (measured at the time of the survey; values in percentages, unless otherwise noted)................. CaPROMISE: Impacts on youth outcomes before and during the pandemic (measured at the time of the survey; values in percentages, unless otherwise MD PROMISE: Impacts on youth outcomes before and during the pandemic (measured at the time of the survey; values in percentages, unless otherwise NYS PROMISE: Impacts on youth outcomes before and during the pandemic (measured at the time of the survey; values in percentages, unless otherwise WI PROMISE: Impacts on youth outcomes before and during the pandemic (measured at the time of the survey; values in percentages, unless otherwise All PROMISE programs: Trends in Youth's SSA payments before and during the COVID-19 pandemic - interrupted time series estimates ...............cccccveieenenieeees AR PROMISE: Trends in Youth's SSA payments before and during the COVID- 19 pandemic- interrupted time series estimates..............cc o Mathematica® Inc. Tables A.54 A.55 A.56 A.57 A.58 A.59 A.60 A.61 A.62 A.63 A.64 A.65 ASPIRE: Trends in Youth's SSA payments before and during the COVID-19 pandemic- interrupted time series estimates.........cccccovvciiceenice e A.83 CaPROMISE: Trends in Youth''s SSA payments before and during the COVID-19 pandemic- interrupted time series estimates............ccoocecier e A.84 MD PROMISE: Trends in Youth's SSA payments before and during the COVID- 19 pandemic- interrupted time series estimates...............cccccoo e A.85 NYS PROMISE: Trends in Youth's SSA payments before and during the COVID- 19 pandemic- interrupted time series estimates.............cooeeoieiiiieee e, A.86 WI PROMISE: Trends in Youth's SSA payments before and during the COVID- 19 pandemic- interrupted time series estimates...........cc..coo e, A.87 All PROMISE programs: Job search activities and perceived barriers to employment before and during the pandemic (percentages)...........ccccocvvveerieercccians A.88 Arkansas PROMISE: Job search activities and perceived barriers to employment before and during the pandemic (percentages) .........ccccecrriiiiiinnneie e A.91 ASPIRE: Job search activities and perceived barriers to employment before and during the pandemic (Percentages) .........ccocccuueeiiriiir e e e A.94 CaPROMISE: Job search activities and perceived barriers to employment before and during the pandemic (PErcentages) .........cccovereeviimn e A.97 MD PROMISE: Job search activities and perceived barriers to employment before and during the pandemic (percentages) .........cccocccccerieee e s A.100 NYS PROMISE: Job search activities and perceived barriers to employment before and during the pandemic (percentages) ..........cccccviiriieririncnieee e A.103 WI PROMISE: Job search activities and perceived barriers to employment before and during the pandemic (percentages) .........cccceeeer e A.106 Mathematica® Inc. Xi This page has been left blank for double-sided copying. Figures 1.1 .2 V.1 V.2 V.3 V.4 V.5 A1 Differences in economic outcomes before and during the pandemic, PROMISE enrollees and ACS youth in PROMISE states (percentages, unless otherwise Differences in education outcomes before and during the pandemic, PROMISE enrollees and ACS youth in PROMISE states (percentages, unless otherwise NOTEA) ...ttt e e e e e e s e n e e e e ne e e e e nne e e e s anr e e e e e nne e e e e anreees 14 Programs' average impacts on youth labor market outcomes among pre- and during-pandemic survey reSpondents .........ccoocciiieei e 18 Programs' average impacts on youth's SSA program participation in the months surrounding the beginning of the pandemic..............cco o, 19 Programs' average impacts on youth education outcomes among pre- and during-pandemic survey respondents .........ccooccoi e 20 Youth employment rates by month of five-year survey completion.............cccceveeeennnnn. 23 Youth''s SSA payment amounts by month................ccoocmmien e 24 Trends in monthly SSA payments before and during the COVID-19 pandemic.......... A.80 Mathematica® Inc. Xiii This page has been left blank for double-sided copying. Acronyms and Abbreviations ACS ASPIRE CaPROMISE COVID-19 ED GED MD N n.a. NYS OASDI p.p. PROMISE RA SD SE SNAP SSA SSI TANF VR Mathematica® Inc. American Community Survey Achieving Success by Promoting Readiness for Education and Employment California PROMISE Novel coronavirus disease 2019 U.S. Department of Education General Educational Development Maryland Sample size Not applicable New York State Old-Age, Survivors, and Disability Insurance Percentage point Promoting Readiness of Minors in Supplemental Security Income Random assignment Standard deviation Standard error Supplemental Nutrition Assistance Program Social Security Administration Supplemental Security Income Temporary Aid for Needy Families Vocational rehabilitation Wisconsin XV This page has been left blank for double-sided copying. Executive Summary In March 2020, the outbreak of the novel coronavirus disease 2019 (COVID-19) prompted the President to declare a national emergency in the United States (Proclamation No. 9994, 85 FR 15337 2020), quickly followed by a series of restrictions on the operations of non-essential businesses and public services. The economic impacts of the COVID-19 pandemic (hereafter referred to as the pandemic) were distributed unequally among workers (Lee 2021; Birinci et al. 2020). Workers with disabilities were particularly hurt by the economic downturn (Schur et al. 2021). In this report, we examine the extent to which the pandemic affected the outcomes of young people with disabilities who were enrolled in the Promoting Readiness of Minors in Supplemental Security Income (PROMISE) evaluation as well as how it affected the impacts, including the ability to measure impacts, of the PROMISE programs. A. Study context and research questions PROMISE aimed to improve the long-term self-sufficiency of youth receiving Supplemental Security Income by funding six programs to provide educational, vocational, and other services to youth and their families as well as improve service coordination between state and local agencies. The national evaluation, which used a random assignment (RA) study design, found that all six programs increased youth's use of transition services in the 18 months after RA and that some of the programs had longer- term impacts on youth's employment and income five years after RA (Mamun et al. 2019; Patnaik et al. 2022a). In this study, we use data from the PROMISE five-year surveys, SSA administrative data and information from information from the American Community Survey (ACS) to explore the following questions: 1. How did PROMISE youth's education and economic outcomes change during the pandemic relative to the pre-pandemic period? How did the changes in PROMISE youth's outcomes compare to the changes among non-PROMISE youth? 2. How did the pandemic likely influence the estimated impacts of PROMISE? B. Findings Young people with and without disabilities experienced worse labor market outcomes during the pandemic than before it. For example, about 60 percent of ACS youth without disabilities who were interviewed before the pandemic were employed, and this share was 6 percentage points (or 10 percent) lower among youth interviewed during the pandemic. Among ACS youth with disabilities, there was a similar decline in labor force participation rates: from 51 percent among those interviewed before the pandemic to 46 percent among those interviewed during the pandemic. These findings are consistent with other research that has documented the damaging effects of the pandemic on young people's employment outcomes (Gould and Kassa 2020; Inanc 2020; Flanagan et al. 2021). PROMISE enrollees, who were young people with disabilities receiving SSI, were similarly less likely to participate in the labor force during the pandemic than before the pandemic. Relative to the control group, PROMISE treatment group youth experienced a larger decline in labor force participation and employment rates during the pandemic. This might be because they had higher rates of labor force participation and employment before the pandemic, so there was more room for the pandemic to erode outcomes. Among pre-pandemic survey respondents, treatment group youth's labor force participation and employment rates were 61 and 31 percent, respectively, while those of control group youth were 54 Mathematica® Inc. Xvii Executive Summary and 25 percent, respectively. During the pandemic, the labor force participation and employment rates for both groups were roughly 50 percent and 25 percent, respectively. This suggests that, initially, the programs might have had larger impacts on labor force participation and employment, but the pandemic eroded these gains. The findings also suggest that the pandemic might have exacerbated disparities in outcomes between youth without disabilities and youth with disabilities receiving SSI. For example, relative to the period before the pandemic, the rates of high school completion increased slightly for youth without disabilities during the pandemic but fell by more than 10 percent for youth with disabilities receiving SSI. The pandemic induced a move from in-person to remote or hybrid education that may have limited educational opportunities and reduced access to in-school supports. As another example, the gap in labor force participation rates between youth without disabilities and those receiving SSI was 30 percentage points before the pandemic, but it grew to 44 percentage points during the pandemic. We found evidence suggesting that the pandemic dampened the impact of PROMISE on youth's economic outcomes. The findings indicate that treatment group youth had made gains in employment outcomes relative to control group youth, but the gains disappeared once the pandemic occurred. It is possible that the dampening effect of the pandemic on program impacts is temporary. Two stories could emerge in the future: treatment group youth could rebound and achieve the employment gains they experienced before the pandemic, or the temporary disruption from the pandemic could permanently alter employment trajectories such that treatment and control group youth remain on an equal footing in the long term. C. Implications for policy and practice The findings suggest two implications for policy and practice related to helping young people with disabilities recover from the pandemic's disruptions to their education and employment and helping them to better weather future economic shocks. First, the pandemic-induced downturn was short-lived, but young people with disabilities might still benefit from targeted supports to mitigate any long-term effects of the disruptions to their education and early labor market experiences. In addition to reducing employment rates, the pandemic reduced enrollment in education and training for youth with disabilities, so youth lost potential work experience as well as potential educational attainment and any related returns. Targeted supports might be needed to help this generation of young people with disabilities make up for these "lost years" so that they can catch up to other cohorts. Second, young workers with disabilities are disproportionately vulnerable to unemployment during economic shocks such as the pandemic, relative to their peers without disabilities. Transition research, policy, and practice could consider how to provide youth with disabilities the training, experiences, and supports they might need to better position them in the labor market and insulate them from future downturns in employment. For example, efforts to connect young people with disabilities to jobs might prioritize matching them to opportunities where they can gain portable skills and human capital that will make it easier to find other jobs in the future. Mathematica® Inc. Xviii l. Introduction In March 2020, the rapidly spreading outbreak of the novel coronavirus disease 2019 (COVID-19) prompted the President to declare a national emergency in the United States (Proclamation No. 9994, 85 FR 15337 2020), quickly followed by a series of restrictions on the operations of non-essential businesses and public services. The economic impacts of the COVID-19 pandemic (hereafter referred to as the pandemic) were distributed unequally among workers (Lee 2021; Birinci et al. 2020). Workers with disabilities were particularly hurt by the economic downturn (Schur et al. 2021). From March to April 2020, the number of employed working-age people with disabilities fell by 20 percent, while the number of employed working-age people without disabilities fell by 14 percent (U.S Bureau of Labor Statistics 2020). Younger workers were also hard-hit: during the first three months of the pandemic, rates of unemployment and underemployment skyrocketed for youth ages 16 to 24 and were at least twice the rates of adults ages 25 or older (Gould and Kassa 2020; Inanc 2020). People at the intersection of these two identities-young people with disabilities-were likely to be particularly vulnerable to the negative effects of the pandemic, which put them at risk of a delay in career development, absence from schools and the labor market, and worse physical and mental health. In this report, we examine the extent to which the pandemic affected the outcomes of young people with disabilities who were enrolled in the Promoting Readiness of Minors in Supplemental Security Income (PROMISE) evaluation as well as how it affected the impacts of the PROMISE programs. PROMISE was a joint initiative of the U.S. Department of Education (ED), the Social Security Administration (SSA), the U.S. Department of Health and Human Services, and the U.S. Department of Labor to support youth with disabilities receiving Supplemental Security Income (SSI) in the transition to adulthood. Under cooperative agreements with ED, six governmental entities across 11 states implemented demonstration programs for SSI recipients who were ages 14 to 16 at enrollment and their families. The programs were implemented in Arkansas (Arkansas PROMISE), California (CaPROMISE), Maryland (MD PROMISE), New York State (NYS PROMISE), Wisconsin (WI PROMISE), and a consortium of six states known collectively as Achieving Success by Promoting Readiness for Education and Employment (ASPIRE). The programs were intended to (1) provide educational, vocational, and other services to the youth and (2) make better use of existing resources by improving service coordination between state and local agencies. ED required the PROMISE programs to provide the following: (1) case management; (2) benefits counseling; (3) financial education; (4) career and work- based learning experiences for youth; as well as (5) training and information to educate parents and family members about their youth's disability, education needs, and transition processes and the family members' own needs. Under contract with SSA, we are conducting the five-year evaluation of the PROMISE programs, which uses a rigorous random assignment design. Elsewhere, we documented that the programs did not have a consistent pattern of impacts on youth's employment and earnings five years after random assignment (Patnaik et al. 2022a). However, for many PROMISE enrollees (about 73 percent), the five-year follow- up period ended while the United States was experiencing the pandemic. Thus, many youth enrolled in the PROMISE cvaluation might have experienced worse education and youth outcomes at the five-year mark than they would have in the absence of the pandemic. Further, the impacts of the PROMISE programs that we estimated in the five-year evaluation might not be an accurate representation of the potential for PROMISE to affect outcomes under more typical circumstances. Mathematica® Inc. Chapter I Introduction In this study, we examine the extent to which the pandemic induced changes in youth's education and economic outcomes, both overall and separately for treatment and control group, and assess whether the pandemic might have muted the impacts of the PROMISE programs. We focus on youth's education and economic outcomes because, relative to other outcomes examined in the national PROMISE evaluation, they were more likely to have been affected by the disruptions to the labor market and schooling caused by the pandemic. We address the following research questions: 1. How did PROMISE youth's education and economic outcomes change during the pandemic relative to the pre-pandemic period? How did the changes in PROMISE youth's outcomes compare to the changes among non-PROMISE youth? 2. How did the pandemic likely influence the estimated impacts of PROMISE? Mathematica® Inc. II. Data and Methods For this report, we conducted several types of analyses to examine the extent to which the pandemic induced changes in youth's outcomes and assess whether the impacts of the PROMISE programs are generalizable to other settings. In the sections that follow, we describe the data and methods used in these analyses. A. Data and samples We relied on three data sources to explore the relationships between the pandemic and PROMISE outcomes and impacts: (1) the PROMISE five-year parent and youth surveys, (2) SSA administrative records, and (3) the American Community Survey (ACS). Below, we describe each data source. PROMISE five-year parent and youth surveys. We surveyed youth and their parents five years after random assignment to collect information on their educational, employment, and economic outcomes. We used data from the five-year surveys to examine differences in PROMISE youth's educational, labor market, and economic well-being outcomes before and during the pandemic. Mathematica fielded the PROMISE five-year surveys from May 2019 through August 2021. In the survey data, the 1,898 youth who completed the five-year surveys before March 13, 2020, (when the President declared that the pandemic was of sufficient severity and magnitude to warrant a national emergency declaration) comprise the pre-pandemic sample; the 7,446 enrollees who completed the surveys on or after this date comprise the during-pandemic sample. A detailed description of the surveys and their administration is available in Patnaik et al. (2022b). SSA administrative data. We used SSA data on SSA disability payments and youth's age-18 redeterminations from April 2013 through April 2021. Data on SSI receipt, including dates of application and monthly payment amounts, came from the Supplemental Security Record, which also includes data on baseline characteristics such as the primary impairment forming the basis for the youth's SSI eligibility. Data on Old-Age, Survivors, and Disability Insurance program payments came from the Payment History Update System for all months from April 2013 through April 2021. We also used data on SSA's age-18 redeterminations, for which SSA reviews child SSI recipients' eligibility for SSI under the adult definition of disability around the time of their 18th birthday. These data are available for all PROMISE youth as well as a comparison group of youth who were eligible for the PROMISE programs but were not enrolled (hereafter called PROMISE-eligible non-enrollees), either because they were not recruited or decided not to participate. Administrative data are available for PROMISE youth and PROMISE-eligible non-enrollees for every month before and during the pandemic. However, during 2019-2021, there is a general decreasing trend in average monthly SSA payments received by youth (See Appendix Figure A.1). This is in part because, as youth grew older, an increasing share underwent age-18 redeterminations and had their benefits ceased because they were no longer eligible for SSI. To avoid conflating the general decreasing trend in average SSA payments with changes in payments attributable to the pandemic, for analyses of SSA disability payments we restricted the samples to youth whose age-18 redeterminations ended before the analysis time period or who did not have an age-18 redetermination either before or during the analysis time period. In Section D of the appendix, we provide more details about how we chose the pre- and during- pandemic periods for the analyses. In addition, we present results from sensitivity analyses where we did Mathematica® Inc. Chapter Il Data and Methods not limit the sample to youth whose age-18 redeterminations ended before the analysis time period or who did not have an age-18 redetermination before or during the analysis time period. ACS data. We used information from the ACS to benchmark the experiences of PROMISE youth to similarly aged populations with and without disabilities. We restricted the data to youth ages 19 to 21 living in PROMISE states. We examined three groups of these ACS sample members: (1) youth who reported receiving SSI payments in the 12 months prior to the interview, (2) youth with a disability (regardless of SSI receipt in the 12 months prior to the interview), and (3) youth without disabilities. We identified youth with disabilities using the U.S. Census Bureau six-question series, which identifies sample household members as having a disability if respondents report them as having difficulty with one of the following: hearing, vision, cognition, mobility, self-care, or independent living. We used information from the IPUMS USA versions 2019 and 2020 1-year ACS files (Ruggles et al. 2022). Because the ACS does not include information about the timing of interviews, we grouped sample members from the 2019 file in the pre-COVID sample and grouped those from the 2020 file in the during- COVID sample. The national emergency declaration occurred on March 13, 2020, so some 2020 ACS households likely completed interviews before the pandemic. The pandemic also negatively affected response rates to the 2020 ACS. We discuss these data limitations further in Section V. B. Methods and measures We examined data pooled across the six PROMISE programs for our primary analyses. Similarly, we pooled ACS data across all sample households in the states in which the programs operated. When we pooled data, we weighted the six programs equally so that programs or states with larger numbers of youth would not be more heavily represented in the samples. Thus, we estimated the average outcomes across programs for the pre- and during-pandemic periods. In supplementary analyses, we also examined the data for each program separately. 1. Comparing the outcomes of PROMISE and ACS youth before and during the pandemic We used a descriptive analysis to address the first and second research questions: (1) How did PROMISE youth's outcomes change during the pandemic relative to the pre-pandemic period? (2) How did changes in PROMISE youth's outcomes compare with COVID-19-related changes among ACS youth and PROMISE-eligible non-enrollees? To examine PROMISE youth's outcomes, we examined PROMISE survey data and SSA administrative data on enrollees. To benchmark these outcomes, we additionally examined ACS data on similarly aged youth and SSA administrative data on PROMISE-eligible non- enrollees. We report the means and standard errors of selected outcomes in the pre- and during-pandemic samples separately for PROMISE treatment and control group youth and for the three groups of ACS youth. We adjusted the statistics for age, sex, race, ethnicity, and state of residence. We also report the unadjusted means and standard deviations of the outcomes in the pre- and during-pandemic samples in Appendix Tables A.10-A.23. We conducted z-tests to assess the statistical significance of differences in outcomes between the pre- and during-pandemic samples. However, because the goal of this analysis is to describe patterns rather than attribute causality, we do not rely solely on statistical tests when discussing findings. The differences in outcomes between the pre- and during-pandemic samples provide suggestive evidence of how the pandemic affected youth outcomes. Because we cannot attribute these differences to causal effects of the Mathematica® Inc. Chapter Il Data and Methods pandemic, we refer to them as pandemic-related differences. Finally, we compare pandemic-related differences in outcomes among PROMISE youth to such differences observed among the three groups of ACS youth using #-tests to measure statistical significance. When interpreting pandemic-related differences in outcomes derived from survey data, we caution that there are differences in the compositions of the pre- and during-pandemic samples, which might contribute to the changes. Specifically, 2020 ACS respondents have higher socioeconomic status on average than respondents from prior years of the survey (Rothbaum et al. 2021). The PROMISE pre-pandemic respondent sample contains more enrollees from programs that began enrolling earlier, while the during-pandemic sample contains more enrollees from programs that began enrolling later. We discuss this issue further in Appendix Section A. We examined key PROMISE education and employment outcome measures that were available for a comparison group (either in the ACS or administrative data). Table II.1 lists the measures used in this analysis and notes differences between PROMISE and ACS measures. ] Table 1l.1. Outcome measures Outcome domains and measures Difference between PROMISE and comparison measures Education Comparison group: ACS youth ages 19-21 living in PROMISE states e Enrolled in school e None e Enrolled in postsecondary education e None e Has a GED, high school diploma, or ¢ None certificate of completion e Completed some or all of college or e None university Employment and economic well-being Comparison group: ACS youth ages 19-21 living in PROMISE states e Employed at interview o Employed individuals in the ACS include those who work for a family business (including farms) but do not earn wages. PROMISE enrollees are counted as employed if they have earnings. None e Annual earnings for the past 12 months ($) e Weekly hours worked in the past 12 We used the ACS measure of usual hours worked per week. months PROMISE enrollees' weekly hours worked are measured as the youth's average hours worked per week across all paid jobs in the year before the survey. e Labor force participation at interview e None e Household participates in non-SSA public None assistance programs in past year (including TANF, SNAP, and general assistance) Comparison group: PROMISE-eligible non-enrollees e Receives SSA payments ¢ None e SSA payment amounts ($) e None ACS = American Community Survey; GED = General Educational Development; SNAP = Supplemental Nutrition Assistance Program; SSA = Social Security Administration; TANF = Temporary Assistance for Needy Families. Mathematica® Inc. Chapter Il Data and Methods We report pre- and during-pandemic statistics of SSA program status, including a binary measure of payment status and average monthly SSA payments, for PROMISE youth separately by treatment status and for PROMISE-eligible non-enrollees. In the ACS data, we cannot observe SSA program status beyond SSI payment amounts in the previous year; therefore, we do not include the ACS samples in the analysis of these outcomes. To understand the effects of the pandemic on SSA payments, we analyzed SSA program participation and average monthly payment amounts during a narrow window of time around March 2020. We compared SSA benefit receipt and average payments in a pre-pandemic period from January through March 2020 to a during-pandemic period from April through June 2020, among youth whose age-18 redeterminations ended either before January 2020 or after June 2020. See Appendix B for more details about how we chose the lengths of the pre- and during-pandemic periods. 2. Comparing PROMISE programs' impacts before and during the pandemic To explore the extent to which the pandemic might have influenced the program impacts estimated in the five-year evaluation, we compared the impacts of the PROMISE programs on youth's economic and education outcomes before and during the pandemic. We used two methods for this analyses. First, we estimated the impacts of the programs on outcomes measured before and during the pandemic and compared them. For outcomes derived from survey data, we estimated the impacts separately for the pre- and during-pandemic respondent subgroups and compared them. For outcomes derived from administrative data, we estimated impacts on outcomes measured in the pre-pandemic and during- pandemic periods for the same sample of youth and compared them. We conducted these analyses using data pooled across the programs as well as separately for each program. Table I1.2 lists the outcomes examined as part of this analysis. Second, to assess patterns over time, we examined levels and impacts for two outcomes in every calendar month: the share of enrollecs employed at the time of the five-year survey and average SSA payments. This approach enabled us to explore whether there were temporary changes in these outcomes at the start of the pandemic, which might not have been detectable when analyzing longer periods of data, as in the analysis described above. When analyzing monthly outcomes, we pooled the data from the six programs to obtain a large-enough sample to detect impacts of a reasonable size. For survey data, we examined only those months when there were at least 100 survey respondents, resulting in an analysis period from September 2019 to July 2021. For both analyses, the impact estimation approach was to compare average outcomes for the treatment and control groups while using a regression-based adjustment to control for baseline characteristics. All regression models included a core set of covariates, including the youth's sex, race, age, and type of disability. If we found any statistically significant differences in baseline characteristics between the treatment and control group (based on the five-year youth survey respondent sample), we included that characteristic as a covariate in regressions.' For ASPIRE and CaPROMISE, we also included state and region fixed effects, respectively, to account for the stratified RA implemented for these programs. ! For each PROMISE program, baseline characteristics and equivalence tests for the youth survey respondent sample are presented in the appendix to the five-year evaluation report (Patnaik et al. 2022b). Mathematica® Inc. Chapter Il Data and Methods Table Il.2. Outcomes examined for comparison of impacts before and during the pandemic (measured at the time of the survey, unless otherwise specified) Outcome measures Employment and economic well-being Employed in the past year Earnings in the past year ($) Weekly hours worked Employed in a paid job in integrated settings in the past year Employed in a paid job outside of school-sponsored activities in the past year Employed in a paid job with coaching in the past year Income in the past year ($) Employed Average weekly earnings ($) Weekly hours worked Labor force participation Household receives TANF/SNAP/housing assistance Received SSA payments? Average monthly SSA payments? ($) Education and training Has a GED, high school diploma, or certificate of completion Enrolled in post-secondary education (college or advanced degree program or vocational, trade, or technical school) Completed some or all of college or university Enrolled in a training program Received any training credential in the past year 2 This outcome is measured using SSA data, which are available for all youth both before and during the pandemic. We calculate this measure over the pre- and during-pandemic period for the same sample of youth. GED = General Educational Development; SNAP = Supplemental Nutrition Assistance Program; SSA = Social Security Administration; TANF = Temporary Assistance for Needy Families. Mathematica® Inc. This page has been left blank for double-sided copying. lll. Youth Outcomes Before and During the Pandemic Pandemic-related factors-such as the economic downturn, stay-at-home orders, and health risks, as well as increased unemployment benefits, cash assistance, and opportunities for remote schooling and work- could have affected youth's education, employment, and economic well-being. To assess the extent to which youth's outcomes changed as a result of the pandemic, we compared key economic and education outcomes in the pre- and during-pandemic samples of PROMISE and ACS youth pooled across PROMISE programs. Section B of the appendix contains program-specific results. Consistent with the pandemic's known impact on the economy and evidence from recent recessions, we found that PROMISE youth were less likely to be in the labor force and employed if they completed the five-year survey during the pandemic than if they completed it before the pandemic began. PROMISE youth interviewed during the pandemic were also less likely to be enrolled in school. To provide a context for the pandemic-related experiences of the PROMISE youth, we compared the pandemic-related differences in their outcomes to those of ACS youth. Our findings suggest that PROMISE youth experienced similar pandemic-related declines in employment and labor force participation to those experienced by ACS youth receiving SSI but larger declines than all ACS youth with and without disabilities. There were not many meaningful differences in school enrollment between PROMISE or ACS youth in the during-pandemic sample and youth in the pre-pandemic sample, but PROMISE youth were slightly more likely to have completed some college if they completed the survey during the pandemic, while there were no significant differences in this measure among any of the three ACS groups. A. Economic outcomes The likelihoods of labor force participation and employment at interview were both lower in the during- pandemic samples than in the pre-pandemic samples, and the differences are relatively similar across the groups with the exception of ACS youth without a disability, whose pandemic-associated decline in labor force participation is significantly smaller than that of PROMISE treatment group youth. Labor force participation was 9 percentage points (or 15 percent) lower among PROMISE treatment group youth who completed the five-year survey during the pandemic than those who completed it before it began; among ACS youth without disability, it was 4 percentage points (or 5 percent) lower among during-pandemic respondents than pre-pandemic respondents. Labor force participation was 8 percentage points (or 30 percent) lower among ACS youth who received SSI in the during-pandemic sample than those in the pre- pandemic sample, but the difference is not statistically significant. When we examined each program separately, we found a similar pattern of a pandemic-associated decline in labor force participation for treatment and control group youth in five of the six PROMISE programs. It also declined or did not measurably change in all five groups of ACS youth in all PROMISE states. Notably, there were large and significant declines in labor force participation for both the treatment and control groups in CaPROMISE and MD PROMISE and those declines were larger than those experienced by the three groups of ACS youth in those states. There was a large and statistically significant increase in labor force participation among NYS PROMISE control group youth. CaPROMISE was the only program to have a significant pandemic-associated difference in the likelihood of having paid employment at the time of the survey. Among treatment group youth in that program, the employment rate among pre-pandemic respondents was substantially higher (32 percent) than among Mathematica® Inc. Chapter Ill Youth Outcomes Before and During the Pandemic during-pandemic respondents (20 percent). Qualitatively, results from AR PROMISE, MD PROMISE, and WI PROMISE look similar to the pooled results. ACS youth with and without disabilities living in New York and Arkansas were less likely to be employed if they were in the during-pandemic sample, while the likelihood of being employed at interview in NYS PROMISE and ASPIRE was higher during the pandemic though none of the differences for either program are significant. The share of youth households receiving public assistance was higher in the during-pandemic samples of all five groups than in the pre-pandemic samples. PROMISE youth and ACS youth with disabilities in the during-pandemic sample were substantially more likely to live in households that received income from Temporary Assistance for Needy Families, General Assistance, or Supplemental Nutrition Assistance Program. The increase in public assistance receipt among PROMISE control group youth was smaller than the increases experienced by all three groups of ACS youth. Households of ACS youth without disabilities were the least likely to report receiving public assistance in either period. We found no meaningful differences in the likelihood of receiving or the amounts of SSA payments in the months immediately preceding and following the start of the pandemic among PROMISE youth or PROMISE-eligible non-enrollees who did not complete the redetermination process during our measurement window (Appendix Table A.26). We observed statistically significant but small declines in SSA payment amounts during the pandemic-the average monthly benefit amount in the first three months of the pandemic was lower than it was during the three months immediately preceding the pandemic, but the difference was no larger than $5 in any of the three groups. We found a similar pattern for monthly SSI payments, which comprised the bulk of youth's SSA payments. When we examined the six programs separately, no PROMISE programs had meaningfully different results from the pooled analysis." Results from a sensitivity analysis, in which we included all youth regardless of redetermination status and modeled pre- and during-COVID trends in payments, also provides no evidence that the pandemic was associated with a substantial change in SSA payments (see Appendix Tables A.52 through A.58). There was a flattening of the downward trend in payments in the during-pandemic period for PROMISE youth and PROMISE-eligible non-enrollees. This might reflect the pandemic's impact on SSA operations, which led to delays in the processing of age-18 redeterminations during the initial months of the pandemic. 2 A possible exception is Arkansas PROMISE. The decline in average SSA payments during the pandemic relative to before the pandemic was qualitatively larger among youth in the Arkansas PROMISE treatment group ($11) than youth in the other programs' treatment groups ($3 to $6); we did not test whether such differences across programs were statistically significant. However, when we compared youth in the Arkansas PROMISE treatment group to youth in that program's control group or eligible non-enrollees, we did not find statistically significant differences in the declines in average SSA payments during the pandemic relative to before the pandemic. 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S SIOLID PJEPUR)S 3U) JO SIjBWIISS |apow uoissalbay 'aouspisal Jo dle)s pue 'aoel 'xas 'abe o) pajjonuod sjapow uoissalbal ay| "AjpAnoadsal ((0z0g ul) Jaye Jo §10¢ Ul AsAIns ay) pajadwiod oym sjuspuodsal asudwos sejdwes ojwapued-6uunp pue -aid ayj 'YinoA SOV ay3 104 "AjeAdadsal '9)ep Jeyy Jaye Jo UOo pue '0z0g '€l Uole aiojeq Aanins ay) paje|dwos oym YnoA asiudwos sejdwes ojwspued-buunp pue -aid 8y} 'sasjjoius JSINOHC 104 "1LZ 0} 61 sebe yinoA goy Buowe pue dnoib yoJeasal 3S|INOHd yoes uiypm sajdwes ojwapued-6uunp pue -aid sy} usamiag SSLWOINO Ul S33UBISYIP paisnipe-uolissalbal sy smoys ainby siyl :9JON olwapued sy} Buung pue a1ojag SBWONQO YINOA |1I J93deyd Chapter Ill Youth Outcomes Before and During the Pandemic B. Education outcomes The pattern of pandemic-related differences in education outcomes differed across the groups. While enrollment in school tends to increase during economic downturns, the pandemic-related shutdowns and changes to remote schooling might have made youth less likely to enroll in school and obtain credentials. The likelihood of school enrollment was modestly smaller among PROMISE control group youth and ACS youth with disabilities in the during-pandemic period than in the pre-pandemic period (Figure III.2). However, it was slightly larger among PROMISE treatment group youth and ACS youth without disabilities. None of the pandemic-related differences in school enrollment were statistically significant. While the pooled pandemic-associated differences in school enrollment are not statistically significant, there are several statistically significant differences in individual PROMISE programs. Enrollment in school was significantly lower during the pandemic than it was before it began among control group youth in AR PROMISE, treatment and control group youth in ASPIRE, treatment group youth in MD PROMISE, and control group youth in NYS PROMISE. There was a large increase in school enrollment (39 percent) among treatment group youth in MD PROMISE. There were few statistically significant differences in school enrollment among ACS youth, though most estimated differences among ACS youth with disabilities are negative, suggesting a decline in school enrollment. ACS youth with a disability who lived in Maryland were much less likely to be enrolled in school during the pandemic and youth without a disability were significantly more likely to be enrolled in school during the pandemic. There were several positive pandemic-related differences in educational attainment among PROMISE youth and several negative differences among ACS youth receiving SSI. ACS youth receiving SSI was the only group with a substantial difference in high school completion between the during-pandemic and pre-pandemic samples: the during-pandemic sample was 11 percentage points less likely to have completed high school than the pre-pandemic sample. PROMISE treatment and control group youth were less likely than ACS youth to have completed some college overall, but PROMISE youth in the during- pandemic sample were significantly more likely to have completed at least some college than their counterparts in the pre-pandemic sample. The differences across the periods among the three groups of ACS youth were small and not statistically significant. 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IV. PROMISE Program Impacts Before and During the Pandemic In the PROMISE five-year evaluation, we found that only two programs (NYS PROMISE and WI PROMISE) increased youth's employment, and three programs (CaPROMISE, MD PROMISE, and WI PROMISE) increased youth's income five years after random assignment (Patnaik et al. 2022a). However, these impacts were estimated using data collected primarily during the pandemic and, as shown in Section III, treatment and control group youth's outcomes during the pandemic were different than the outcomes before the pandemic. Because of the pandemic, the impacts estimated in the five-year evaluation might not be an accurate representation of the potential for PROMISE to affect outcomes under more typical circumstances. To assess the extent to which the pandemic might have influenced the programs' impacts, we estimated program impacts on youth's education and economic outcomes before and during the pandemic and compared them. The findings suggest that the pandemic likely affected the ability of the programs to affect youth employment and earnings. We did not find evidence that the pandemic affected the ability of programs to impact youth's education or SSA program participation. We describe the findings in more detail below. A. Five-year impacts measured before and during the pandemic We found evidence suggesting that the pandemic dampened the potential of the programs to have an impact on youth's employment and economic well-being (Figure IV.1). For example, the programs' average impact on youth employment rates was to increase the share of youth employed in the past year by 8 percentage points (or 17 percent of the control group mean) among pre-pandemic respondents. In contrast, the programs had no impact on this outcome among during-pandemic respondents, on average. Similarly, on average, the programs increased pre-pandemic youth respondents' earnings and income in the past year by $984 and $1,125 respectively but had no impacts on these outcomes for during-pandemic respondents. We see a similar pattern of suppressed impacts during the pandemic for outcomes such as weekly hours worked and employment in a paid job outside of school-sponsored activities in the past year, as well as employment, earnings, weekly hours worked, and labor force participation at the time of the five-year survey. Statistical tests of the differences between the groups indicates that the impacts on these outcomes for the pre- and during-pandemic respondents are significantly different from each other. This suggests that the six programs' average impacts on youth's labor market outcomes and income (as reported in Patnaik et al. 2022) are not necessarily representative of the impacts the programs might have generated under more typical circumstances, or the typical program itself. In exploratory analyses, we examined the job search activities of youth who were not employed but looking for work at the time of the five-year survey (Appendix Table A.59). Before the pandemic, 37 percent of control group youth reported looking for work during the four weeks before the five-year survey, and PROMISE increased this share by 7 percentage points. During the pandemic, a smaller share of youth reported seeking work (31 percent of control group youth), and there are no statistically significant differences between the control and treatment group youth. We also found differences between pre- and during-pandemic youth in how they sought work. Among youth looking for work before the pandemic, control group youth were more likely than treatment group youth to seek work by asking friends or relatives or look through job advertisements in a newspaper or on the internet; during the pandemic, the two groups did not differ in their likelihood of using these approaches to find work. This difference might in part be due to differences in the composition of the sample of youth who were looking Mathematica® Inc. 17 8l sjuapuodsal olwapued-buung Jesk leaf jsed 1sed sy} ayj urswoou| uisbujuie | | | | | | 1 1 1 | | 1 | | | I | 1 1 1 | I 1 | | | 1 | 1 1 I I | I | | | 1 | 1 | 1 1 "oU| gEOlEWaYle "Jse} pajie}-om} e Buisn (107/G0°/0L" UBY) SS8| S| anjeA-d) 018z Loy Jualeylp ARUBOYUBIS S| S1eWNSS DBAW] yu/xls "S|Iejep aIowW Joj G'y o|gel Xipuaddy esg '(AjeAjoadsal 'ejep Jey) Jaye 1o Uo pue '0zZ0Z 'Sl Yolel alojeq AeAins sy} palojdwod oym yinoA 'si jey}) sjuspuodsael Aeains olwapued-6ulnp pue -aid sy Buowe sawooino YnoA uo sweiboid xis sy} Jo s}oedw abeiaae ay) smoys ainby sy :8]JON ueaw dnoib [o5uoy) s sjuapuodsai olwapued-aig Jeaf jsed 8y} Ul aWoou| seLs XX¥ leak jsed ay} ul sbuiuseq 0$ 0002$ - 000'%$ - 000'9$ 000'e$ 000°0L$ - 000Z}$ Aenlns 8y} Jo awp ay Je 8010} loqej ayj uj 'Aenuns JeaA-aAl JSINOYd :82Jn0S 10eduw| - sjuapuodsai ojwapued-buung sjuapuodsal olwapued-aid fanins ay} Jeak jsed joawn ey sy ulqgof pred Je pafojdws e ul pekojdwg au} Jo awy AoAins ay) 1eak i1sed sy jesoio) joawnay ey ulqolpred logejayyu] Je pakojdw e ul pakojdug I I I 1 I , femns I I I 1 I abejusniad ¥ ON 08 sjuapuodsal AaAins olwapued-6uunp pue -aid Buowe sawoo3no Jaxlelw Joge| YinoA uo sjoeduw abesaae sweiboid "|°Al 8inbi4 Jllapued ay) Buung pue alojeg sioedw| welbold JSINONC Al 18ydeyd Chapter IV PROMISE Program Impacts Before and During the Pandemic For work- treatment group were more likely than control group to be employed and thus, not looking for work, especially before the pandemic (Figure IV.2).In contrast to the findings for youth's labor market outcomes, we found no evidence that the pandemic affected the programs' average impacts on youth's education and training and SSA program participation (Figures IV.2 and IV.3). Youth's education and training outcomes did not differ between the pre- and during-pandemic survey respondents. We also found no differences in youth's monthly SSA payments when we compared the period January-March 2020 and the period April-June 2020. Thus, we found no evidence suggesting that the programs' average impacts on these outcomes (as reported in Patnaik et al. 2022) differ significantly from what would have occurred under more typical circumstances. Figure IV.2. Programs' average impacts on youth's SSA program participation in the months surrounding the beginning of the pandemic 60% o ¥ $500 1.9% 1.5% 50% $10 9 ' $400 $ 40% $300 30% $200 20% $100 10% 0% : $0 . January- April-June January- April-June March 2020 March 2020 2020 2020 Received any SSA Average monthly payments? SSA payments mmm [mpact mssm Control group mean Source: SSA administrative records. Note: This figure shows the average impacts of the six programs on youth's SSA payment outcomes during the first three months surrounding the start of the public health emergency in March 2020. We observe SSA Mathematica® Inc. payments for every individual in both the time periods. We restricted the analysis sample to enrollees whose age-18 redeterminations occurred before January 2020 or who never underwent an age-18 redetermination before July 2020. See Appendix Table A.45 for more details. Impact estimate is significantly different from zero (p-value is less than .10/.05/.01) using a two-tailed f-test. SSA = Social Security Administration. * /** /*** 19 Chapter IV PROMISE Program Impacts Before and During the Pandemic Figure IV.3. Programs' average impacts on youth education outcomes among pre- and during- pandemic survey respondents 40% 35% 30% 25% 20% 15% 10% 5% 0, 0k 0% -0.3% 0.1% o 29% Enrolledinan Enrolled in a Enrolledinan Enrolled in a educational job-related educational job-related program training program training program program Pre-pandemic During-pandemic respondents respondents mmm Impact sssm Control group mean | | | | | | | | I | | I I | | | | | | | | | I | | | | | | | | 1 | | | | | | I I | | Source: PROMISE five-year survey. Note: This figure shows the average impacts of the six programs on youth outcomes among the pre- and during- pandemic survey respondents (that is, youth who completed the survey before March 13, 2020, and on or after that date, respectively). See Appendix Table A.45 for more details. **[*** Impact estimate is significantly different from zero (p-value is less than .10/.05/.01) using a two-tailed -test. The findings described above are based on data pooled across the six programs, which can mask program- level variation in the differences in impacts before and during the pandemic. When we examined the program-specific impacts during the pre- and during-pandemic periods, we found a similar pattern of programs having had impacts on some outcomes among pre-pandemic respondents but not among during- pandemic respondents (Table I'V.2 and Appendix Tables A.46-A.51). All programs improved at least one outcome among pre-pandemic respondents while they had no impact (or a smaller impact) on that outcome among during-pandemic respondents. Further, the findings likely underestimate the extent to which some programs affected the outcomes of pre-pandemic youth, because smaller samples of pre- pandemic respondents in some programs might have limited our ability to detect significant differences in Mathematica® Inc. 20 Chapter IV PROMISE Program Impacts Before and During the Pandemic impacts between the groups.? Thus, the findings from the program-specific analyses provide a conservative estimate of the extent to which the pandemic dampened each program's ability to impact youth's five-year outcomes. Table IV.2. Summary of differences in impacts between pre- and during-pandemic respondents, by program Program Significant impacts for pre-pandemic or during-pandemic survey respondents Arkansas Among pre-pandemic respondents, Arkansas PROMISE increased the likelihood of employment in a PROMISE job outside of school-sponsored activities and weekly hours worked in the past year, and employment, earnings and hours worked at the time of the survey; it had no impact on these outcomes among the during-pandemic respondents. ASPIRE ASPIRE increased the share of youth who had completed some college or university among during- pandemic respondents, but it had no impact on this outcome among pre-pandemic respondents. ASPIRE increased the share of youth who were enrolled in a training program at the time of the survey among pre-pandemic respondents, but it had no impact on this outcome among during- pandemic respondents. CaPROMISE |None MD Among pre-pandemic respondents, MD PROMISE increased weekly hours worked at the time of the PROMISE survey and decreased the share enrolled in an educational program, but it had no impact on these outcomes among during-pandemic respondents. NYS NYS PROMISE increased the share of pre-pandemic respondents who were in the labor force at the PROMISE time of the survey, but it did not impact this outcome for during-pandemic respondents. WI PROMISE | WI PROMISE increased the share of youth employed in a job with coaching in the past year among pre-pandemic respondents; it did not impact this outcome for during-pandemic respondents. Source: PROMISE five-year survey. Note: See Appendix Tables A.46-A.51. This table describes instances when a program has a statistically significant impact on an outcome either before or during the pandemic and the impacts were significantly different from each other (p-value is less than 0.10 using an adjusted Wald test). We compared the outcomes of youth who responded to the survey before the pandemic (defined as before March 13, 2020) to the outcomes of youth who responded to the survey during the pandemic. ASPIRE = Achieving Success by Promoting Readiness for Education and Employment; CaPROMISE = California PROMISE; MD = Maryland; NYS = New York State; WI = Wisconsin. B. Impacts on employment rates and SSA payments by month As might be expected, there was a decline in youth employment rates in the early months of the pandemic, and they remained lower through 2020 before picking up again in 2021 (Figure IV 4). There is evidence of a drop-off in youth employment during the initial months of the pandemic: the share of youth employed in April-June 2020 was considerably smaller than the share employed in January-March 2020. For example, among treatment group youth, the share employed at interview was more than 32 percent in each of the first three months of 2020 but was never more than 28 percent in the following three months. Indeed, it did not rise above 30 percent again until June 2021. Control group youth experienced a similar trend, though the decline during the first three months of pandemic was more modest. 3 Some programs had small samples of pre-pandemic respondents, which made it less likely that a standard statistical test could detect a significant impact on an outcome for that group. Similarly, statistical tests for differences in impacts between the pre- and during-pandemic respondents are also less likely to detect a difference as statistically significant when there are few pre-pandemic respondents. Mathematica® Inc. 21 Chapter IV PROMISE Program Impacts Before and During the Pandemic We found evidence that the pandemic dampened the potential for the programs to increase youth's employment, especially in its early months. We estimated impacts at the monthly level, comparing the share of youth in each group that was employed at interview during the pre- and during-pandemic months. The estimated impacts by month show large and positive point estimates in the three months before the pandemic, which quickly fall to zero and become negative during the first three months after the start of the pandemic. However, the monthly decline did not persist in subsequent months. This finding is consistent with concurrent trends in the U.S. economy, which experienced a short but deep contraction in the months immediately following March 2020 and then began a slow recovery. We examined average monthly SSA payments from April 2019 through April 2021 and did not find evidence that the pandemic affected the potential for the programs to impact youth's SSA payments. For both control and treatment group youth, there was a general decrease in monthly SSA payments over time (Figure IV.5). This is expected as youth grow older and leave the SSI rolls or have their payments reduced due to increased earnings. We did not find evidence of a large drop in payments coinciding with the declaration of the public health emergency in March 2020. We also did not find evidence of a change in program impacts due to the pandemic. During each month from January through June 2020, the point estimates of the programs' impacts on average monthly SSA payments were between $7 and $10 and not statistically significant. Thus, there is no evidence that the pandemic affected the programs' impacts on SSA payments in the short term. Nonetheless, because we found evidence that the pandemic dampened the programs' impacts on employment, it could affect receipt of SSA payments in the long term. 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Conclusions A. Discussion of findings Young people with and without disabilities experienced worse labor market outcomes during the pandemic than before. For example, about 60 percent of ACS youth without disabilities were employed before the pandemic, and this share was 6 percentage points (or 10 percent) lower during the pandemic. Among ACS youth with disabilities, there was a similar large drop in labor force participation rates: 51 percent before the pandemic versus 46 percent during the pandemic. These findings are consistent with other research that has documented the damaging effects of the pandemic on young people's employment outcomes (Gould and Kassa 2020; Inanc 2020; Flanagan et al. 2021). One potential reason young people were disproportionately hurt by the pandemic-induced economic downturn is that, before the pandemic, they were more likely to work in jobs that were heavily impacted by social distancing policies and reductions in consumer spending, such as those in the leisure, hospitality, and retail industries (Aaronson and Alba 2020; Berube and Bateman 2020; Hill et al. 2021). We found that the most common jobs held by PROMISE youth were jobs in those industries, including cooks or kitchen workers, factory and assembly workers, cleaners, retail stockers and order fillers, and retail store and salespersons (Farid et al. 2022). Moreover, some research indicates that even within industries, younger workers were more likely to be laid off in April and May 2020 compared to their older counterparts (Aaronson and Alba 2020). Thus, the data confirm that the pandemic led to worse labor market outcomes for young people with and without disabilities. The findings presented here hint at ways in which the pandemic might have exacerbated differences between youth without disabilities and youth with disabilities receiving SSI. For example, relative to the period before the pandemic, the rates of high school completion increased slightly for youth without disabilities during the pandemic but fell by more than 10 percent for youth with disabilities receiving SSI. Historically, lower levels of youth employment during recessions have coincided with high rates of enrollment in education (Barr and Turner 2015), because some youth choose to pursue schooling rather than search for work when hiring slows. However, during the pandemic, school closings and a move from in-person to remote education limited educational opportunities, reducing access to many in-school supports. Youth with disabilities and those from families with low incomes (such as those receiving SSI) had less access to technology and distance learning materials that facilitated remote learning (Kamenetz 2020). As another example, the gap in labor force participation rates between youth without disabilities and those receiving SSI was 30 percentage points before the pandemic, but it grew to 44 percentage points during the pandemic. These findings underscore the vulnerability of youth with disabilities to the negative effects of the pandemic compared with other young people. PROMISE enrollees, who were young people ages 14 to 16 with disabilities receiving SSI at the time of enrollment, were similarly less likely to participate in the labor force during the pandemic than before the pandemic. This could be for various reasons. Youth who were laid off during the downturn might have exited the labor force rather than try to find another job. Slowdowns in hiring might have changed youth's beliefs about the likelihood of getting a quality job, such that jobseekers exited the labor force as well. Generous government assistance in the form of increased unemployment benefits, stimulus payments, and eviction moratoriums might also have disincentivized job search and employment, especially for people with disabilities who often faced greater health risks from work outside the home compared to those without disabilities. Mathematica® Inc. 25 Chapter V Conclusions Relative to the control group, PROMISE treatment group youth experienced a larger decline in labor force participation and employment rates during the pandemic. This might be because they had higher rates of labor force participation and employment before the pandemic, so there was more room for the pandemic to erode outcomes. Among pre-pandemic respondents, treatment group youth's labor force participation and employment rates were 61 and 31 percent, respectively, while those of control group youth were 54 and 25 percent, respectively. During the pandemic, the labor force participation and employment rates for both groups were roughly 50 percent and 25 percent, respectively. This suggests that, initially, the programs might have had larger impacts on labor force participation and employment, but the pandemic eroded these gains. We found evidence suggesting that the pandemic dampened the impact of PROMISE on youth's economic outcomes. The findings indicate that treatment group youth had made gains in employment outcomes relative to control group youth, but the gains disappeared once the pandemic occurred. It is possible that the dampening effect of the pandemic on program impacts is temporary. Two stories could emerge in the future: treatment group youth could rebound and achieve the employment gains they experienced before the pandemic, or the temporary disruption from the pandemic could permanently alter employment trajectories such that treatment and control group youth remain on an equal footing in the long term. Although we cannot know what the programs' impacts would have been in the absence of the pandemic, there is strong evidence that the programs' average impacts would have been more favorable. When we pooled data across the programs, there was a clear pattern of larger impacts on youth's labor market outcomes before the pandemic than during the pandemic. The five-year impact evaluation documented that, on average, the six PROMISE programs increased youth's employment and earnings, although there was substantial variation across the programs (Patnaik et al. 2022a). The findings from this study may be interpreted cautiously to suggest that the pooled average impacts on youth's employment underestimate the average impact that PROMISE programs could have had on youth employment and other labor market outcomes under more typical circumstances. B. Limitations The analyses conducted for this study primarily rely on data pooled across the six programs but estimates of average outcomes and average impacts across the programs can mask substantial variation at the program level. When examining the potential effects of the pandemic, the pooled analyses have an additional limitation because the programs differed in their enrollment periods. The pre-pandemic respondent pooled sample contained more enrollees from programs that began enrolling earlier, while the during-pandemic pooled sample contained more enrollees from programs that began enrolling later. As a result, the mean outcomes and estimated impacts for each sample might be driven by enrollees in the programs more heavily represented in that sample. This unequal distribution of the programs across the two samples is not ideal for two reasons. First, the potential of the pandemic to have affected youth's outcomes and program impacts was larger for the programs that began enrolling families later, because later enrollees were more likely to have a portion of their follow-up period overlap with the pandemic. Second, youth's experiences of the pandemic varied across states; for example, youth unemployment was particularly affected by the pandemic in parts of the country where states introduced stricter containment measures (Inanc 2021). State-level factors such as stay-at-home orders likely contributed to variation across the programs in how the pandemic affected youth outcomes and program impacts. At the same Mathematica® Inc. 26 Chapter V Conclusions time, relying more on program-specific analyses was not feasible, due to data limitations we describe below. The PROMISE survey data have two limitations. First, because we did not survey the same youth in the pre- and during-pandemic periods, comparisons of outcomes or impacts between the periods are comparing two different cohorts of youth, who differ in their characteristics and potential outcomes in the absence of the pandemic (see Section A of the appendix for a comparison of baseline characteristics between pre- and during-pandemic cohorts). Therefore, differences in survey-based outcomes between the pre- and during-pandemic periods cannot be interpreted as the causal effects of the pandemic, though they provide suggestive evidence. Second, there were substantially fewer pre-pandemic respondents than during-pandemic respondents. This made it less likely that we could detect an impact of a certain magnitude as statistically significant for pre-pandemic respondents, compared to during-pandemic respondents. Relatedly, statistical tests were less likely to detect a difference in impacts between these two groups as being significant, compared to if the pre-pandemic respondent sample was as large as the during-pandemic respondent sample. This issue was more acute for programs that began enrolling later and thus had comparatively fewer pre-pandemic respondents. For example, in NYS PROMISE, only 53 youth responded to the survey before the pandemic, while over 1,500 responded during the pandemic. As a result, program-specific inferences may underestimate the extent of differences in impacts between pre- and during-pandemic respondents, compared to pooled analyses. The ACS data also have limitations. First, they do not contain the date of the interview. Some 2020 ACS youth likely completed interviews before the pandemic, but we counted them as during-pandemic respondents. This would cause us to underestimate the true difference in outcomes between pre- and during-pandemic ACS samples. Second, the size of the group of ACS youth receiving SSI is small; for example, there were 32,000 youth without disabilities in the pre-pandemic sample but fewer than 500 youth receiving SSI. Because the sample size of youth receiving SSI is small, we would only detect a difference between pre- and during-pandemic respondents if it was very large. This might explain why we found some differences that were large in magnitude (for example, a nearly 8 percent difference in labor force participation between pre- and during-pandemic ACS respondents receiving SSI) but not statistically significant. Third, as with the PROMISE surveys, the ACS data capture different cohorts of youth in the pre- and during-pandemic periods, so differences between these periods cannot be interpreted as the causal effects of the pandemic. In fact, the pandemic negatively affected response rates to the 2020 ACS and led to larger nonresponse bias in the sample than in previous years. Socioeconomic status was more positively correlated with response than in prior years (Rothbaum et al. 2021). To address known limitations due to nonresponse bias, the 2020 ACS file includes experimental sample weights that account for household-level nonresponse and weight individual observations to facilitate the estimation of statistics representative of geographic areas no smaller than states (Ruggles et al. 2022). However, even when using the experimental weights, estimates derived from the 2020 ACS file should be viewed with caution. All findings in this report based on the ACS data should be interpreted with the 2020 data limitations in mind. Finally, the U.S. Census six-question disability sequence is limited in its ability to identify the group of individuals with disabilities who are relevant to SSA programs - it is likely to miss a substantial portion of people who have work-limiting disabilities and also those who participate in SSA benefit programs (Burkhauser, Houtenville, and Tennant 2014). Because of this limitation, we are likely to overestimate employment outcomes among ACS youth with SSA-comparable disabilities. Mathematica® Inc. 27 Chapter V Conclusions C. Implications for policy and practice The findings have two main implications for policy and practice related to helping young people with disabilities recover from the pandemic's disruptions to their education and employment and helping them to better weather future economic shocks. 1. Though the long-term effects of the pandemic-induced economic downturn are unknown, young people with disabilities might benefit from targeted supports to mitigate any long-term effects of the disruptions to their education and early labor market experiences The long-term effects of the pandemic on young people with disabilities are not yet known. Compared to previous recessions, the 2020 pandemic-induced recession was unique. It involved a sharp contraction that lasted only two months (National Bureau of Economic Research 2021), considerably shorter than previous recessions. It was attributable to government policies that were designed to safeguard public health, rather than economic factors, such as a financial crisis or shocks to key markets. The government also provided substantial supports to households and businesses to help them weather the initial economic shock. By July 2022, the unemployment rates of young people ages 1624 and people with disabilities had returned to the same levels as in February 2019 (U.S Bureau of Labor Statistics 2022). Nonetheless, the disruptions that the pandemic caused to youth's education and employment experiences during 2020 and 2021 could affect youth's longer-term economic well-being. Past research suggests that entering the labor market during poor economic conditions can lead to reduced earnings for several years (Oreopoulos et al. 2012; Kahn 2010; Altonji et al. 2016; Elsby et al. 2016), and that these effects are larger for less advantaged workers, such as high school dropouts (Schwandt and von Wachter 2019). In addition, as shown in this report, the pandemic led to reductions in not only employment rates but also enrollment in education and training for youth with disabilities, such that they lost out on not only potential work experience but also potential educational attainment and related returns. Therefore, while the downturn appears to have led to only a temporary spike in the unemployment rate of young people with disabilities, it might nonetheless affect their long-term earnings and career growth. Targeted supports might be needed to help this generation of young people with disabilities make up for these "lost years" so that they can catch up to other cohorts. 2. Young people with disabilities experienced a greater deterioration of labor market outcomes during the pandemic relative to their peers without disabilities; effective approaches are needed to mitigate such disparities in the effects of economic shocks. When the economy contracts, some workers experience greater challenges and setbacks than others. Past research indicates that youth and people with disabilities are particularly vulnerable to adverse labor market conditions (Fogg et al. 2010; Bell and Blanchflower 2011). Consistent with this, we found that all youth had lower employment and labor force participation rates during the pandemic compared to the pre- pandemic period, but the differences were particularly large for youth with disabilities. Because poor economic outcomes during young adulthood can negatively affect long-term earnings and well-being (Maclean 2015; Cutler et al. 2015; Bell et al. 2018; Schwandt and von Wachter 2020; von Wachter 2020),* disparities in how youth experience economic shocks can translate to systematic inequalities in 4 The average cumulative earnings loss over 10 years from entering the labor market during a large recession is estimated to be about 9 percent (von Wachter 2020). Poor initial labor market conditions can adversely affect health behaviors and are associated with excessive alcohol consumption (Maclean 2015), higher rates of obesity and Mathematica® Inc. 28 Chapter V Conclusions longer-term outcomes. Transition research, policy, and practice could consider how to provide young workers with disabilities the training, experiences, and supports they need to better position themselves in the labor market and insulate themselves from future downturns in employment. For example, efforts to connect young people with disabilities to jobs might focus on matching them to opportunities where they can gain portable skills and human capital that will make it easier to find other jobs in the future. smoking (Cutler et al. 2015), and increased mortality in middle age (Schwandt and von Wachter 2020). They also are associated with increased criminal activities (Bell et al. 2018). Mathematica® Inc. 29 This page has been left blank for double-sided copying. References Aaronson, S., and F. Alba. "Unemployment Among Young Workers During COVID-19." Brookings blog, September 10, 2020. Available at https://www.brookings.edu/research/unemployment-among- youngworkers-during-covid-19/. Altonji, J.G., L.B. Kahn, and J.D. Speer. "Cashier or Consultant? Entry Labor Market Conditions, Field of Study, and Career Success." Journal of Labor Economics, vol. 34, no. S1, 2016, pp. S361-S401. Barr, A., and S. Turner. "Out of Work and Into School: Labor Market Policies and College Enrollment During the Great Recession." Journal of Public Economics, vol. 124, 2015, pp. 63-73. Bauer, L., and J. Shambaugh. "Workers with Low Levels of Education Still Haven't Recovered from the Great Recession." Brookings blog, September 6, 2018. Available at https.//www.brookings.edu/blog/up-front/2018/09/06/workers-with-low-levels-of-education-still- havent-recovered-from-the-great-recession/. Bell, D.N.F., and D.G. Blanchflower. "Young People and the Great Recession." Oxford Review of Economic Policy, vol. 27, no. 2, 2011, pp. 241-267. Available at http://www.jstor.org/stable/43744473. Bell, B., A. Bindler, and S. Machin. "Crime Scars: Recessions and the Making of Career Criminals." The Review of Economics and Statistics, vol. 100, no. 3, 2018, pp. 392-404. Berube, A., and N. Bateman. 2020. "Who Are the Workers Already Impacted by the COVID-19 Recession?" Brookings blog, April 3, 2020. Available at https://www.brookings.edu/research/who- are-the-workers-already-impacted-by-the-covid-19-recession/. Birinci, S., and A. Amburgey. "How Has the COVID-19 Recession Affected U.S. Labor Across Occupations and Industries?"" On the Economy blog, Federal Reserve Bank of St. Louis, November 8, 2020, Available at https.//www.stlouisfed.org/on-the-economy/2020/movember/covid19-recession- affected-labor-occupations-industries. Bloom, N. "How Working From Home Works Out." Policy brief. Stanford Institute for Economic Policy Research, 2020. Available at bttps://drive.google.com/file/d/15nB9nscTj38bIADQYLIQWIzZUBNPeDIS _/view. Brynjolfsson, E., J.J. Horton, A. Ozimek, D. Rock, G. Sharma, and H.-Y. TuYe. "COVID-19 and Remote Work: An Early Look at US Data." Working Paper 27344. Cambridge, MA: National Bureau Of Economic Research, 2020. Available at https://www.nber.org/system/files/working papers/w27344/w27344.pdf. Burkhauser, R.V., A.J. Houtenville, and J.R. Tennant. "Capturing the Elusive Working-Age Population with Disabilities: Reconciling Conflicting Social Success Estimates from the Current Population Survey and American Community Survey." Journal of Disability Policy Studies, vol 24, no. 4, 2014, pp. 195-205. Cutler, D.M., W. Huang, and A. Lleras-Muney. "When Does Education Matter? The Protective Effect of Education for Cohorts Graduating in Bad Times." Social Science & Medicine Elsevier, vol. 127, 2015, pp. 63-73. Mathematica® Inc. 31 References Elsby, M., W.L. Donggyun Shin, and G. Solon. "Wage Adjustment in the Great Recession and Other Downturns: Evidence from the United States and Great Britain." Journal of Labor Economics, vol. 34, no. S1, 2016, pp. S249-S291. Farid, M., K. Katz., A. Hill, A. Patnaik, and G. Livermore. "The Education and Work Experiences of PROMISE Youth." Washington, DC: Mathematica, 2022. Flanagan, S.K., M. Margolis, A. Doyle Lynch, and M. Hynes. "The State of Youth Employment: Navigating the World of Work during COVID-19." Washington, DC: Center for Promise at America's Promise Alliance, 2021. Available at https://www.americaspromise.org/resource/state- youth-employment. Fogg, N.P., P.E. Harrington, and B.T. McMahon. "The Impact of the Great Recession Upon the Unemployment of Americans with Disabilities." Journal of Vocational Rehabilitation, vol. 33, 2010, pp. 193-202. Gould, E., and M. Kassa. "Young Workers Hit Hard by the COVID-19 Economy." 2020. Available at https://www.epi.org/publication/young-workers-covid-recession/. Hickman, A., and L. Saad. "Reviewing Remote Work in the U.S. Under COVID-19." Gallup, May 22, 2020. Available at https://news.gallup.com/poll/311375/reviewing-remote-work-covid.aspx. Hill, A., I. Musse, Y. Ben-Shalom, and W. Shaw. "The Impact of Local Labor Market Conditions on Opioid Transactions: Evidence from the COVID-19 Pandemic" Washington, DC: Mathematica, 2021. Honeycutt, T., B. Gionfriddo, and G. Livermore. "Promoting Readiness of Minors in Supplemental Security Income (PROMISE): PROMISE Programs' Use of Effective Transition Practices in Serving Youth with Disabilities." Washington, DC: Mathematica Policy Research, October 2018. Inanc, H. "Breaking Down the Numbers: What Does COVID-19 Mean for Youth Unemployment?" Cambridge, MA: Mathematica, June 2020. Inanc, H. "Youth Unemployment in the First Year of the COVID-19 Pandemic: From the Breakout to the Vaccine Rollout." Cambridge, MA: Mathematica, April 2021. Kahn, L.B. "The Long-Term Labor Market Consequences of Graduating from College in a Bad Economy." Labour Economics, vol. 17, no. 2, 2010, pp. 303-316. Kamenetz, A. "Survey Shows Big Remote Learning Gaps for Low-Income and Special Needs Children." NPR, May 27, 2020. Available at https://www.npr.org/sections/coronavirus-live- updates/2020/05/27/862705225/survey-shows-big-remote-learning-gaps-for-low-income-and- special-needs-children. Lee, S.Y., M. Park, and Y. Shin, "Hit Harder, Recover Slower? Unequal Employment Effects of the COVID-19 Shock." Federal Reserve Bank of St. Louis Review, vol. 103, no. 4, 2021, pp. 367-383. https://research.stlouisfed.org/publications/review/2021/09/01/hit-harder-recover-slower-unequal- employment-cffects-of-the-covid-19-shock. Linden, M., and K. Milchus. "Teleworkers with Disabilities: Characteristics and Accommodation Use." Work, vol. 47, no. 4, 2014, pp. 473-483. Mathematica® Inc. 32 References Livermore, G. & Schimmel Hyde, J. "Workers with Disabilities Face Unique Challenges in Weathering the COVID-19 Pandemic." 2020. Available at https://mathematica.org/blogs/workers-with- disabilities-face-unique-challenges-in-weathering-the-covid-19-pandemic. Livermore, G., T. Honeycutt, A. Mamun, and J. Kauff. "Insights About the Transition System for SSI Youth from the National Evaluation of Promoting Readiness of Minors in SSI (PROMISE)." Journal of Vocational Rehabilitation, vol. 52, no. 1, 2020, pp. 1-17. Moon, N.W., M.A. Linden, J.C. Bricout, and P. Baker. "Telework Rationale and Implementation for People with Disabilities: Considerations for Employer Policymaking." Work, vol. 48, no. 1, 2014, pp- 105-115. Maclean, J.C. 2015. "The Lasting Effects of Leaving School in an Economic Downturn on Alcohol Use." ILR Review, vol. 68, no. 1, 2015, pp. 120-152. National Bureau of Economic Research. "Business Cycle Dating Committee Announcement." July 19, 2021. Available at https://www.nber.org/news/business-cycle-dating-committee-announcement-july- 19-2021. Oreopoulos, P., T. von Wachter, and A. Heisz. "Short and Long-Term Career Effects of Graduating in a Recession." American Economic Journal: Applied Economics, vol. 4, no. 1, 2012, pp. 1-29. Patnaik, A., S. Dale, M. Farid, A. Harrati, A. Hill, T. Honeycutt, K. Katz, G. Livermore, 1. Musse, L. Potamites, and P. Sevak. "Promoting Readiness of Minors in Supplemental Security Income (PROMISE): Youth and Family Outcomes Five Years After Enrollment." Washington, DC: Mathematica, 2022a. Patnaik, A., S. Dale, M. Farid, A. Harrati, A. Hill, T. Honeycutt, K. Katz, G. Livermore, 1. Musse, L. Potamites, and P. Sevak. "Promoting Readiness of Minors in Supplemental Security Income (PROMISE): Technical Appendix to the Five-Year Evaluation Report." Washington, DC: Mathematica, 2022b. Perrin, A., and S. Atske. "Americans with Disabilities Less Likely Than Those Without To Own Some Digital Devices." Pew Research Center, September 10, 2021. Available at https://www.pewresearch.org/fact-tank/2021/09/10/americans-with-disabilities-less-likely-than- those-without-to-own-some-digital-devices/. Rothbaum, J., J. Eggleston, A. Bee, M. Klee, and B. Mendez-Smith. "Addressing Nonresponse Bias in the American Community Survey During the Pandemic Using Administrative Data." American Community Survey Research and Evaluation Report Memorandum, Series #ACS21-RER-05, 2021. Available at https://usa.ipums.org/usa/resources/Addressing_nonresponse bias_2020acs.pdf. Ruggles, S., S. Flood, R. Goeken, M. Schouweiler and M. Sobek. IPUMS USA: Version 12.0 [dataset]. Minneapolis, MN: IPUMS, 2022. Available at https://doi.org/10.18128/D010.V12.0. Schur, L., M. Ameri, and D. Kruse. "Telework after COVID: A 'Silver Lining' for Workers with Disabilities?" Journal of Occupational Rehabilitation, vol. 30, 2020, pp. 521-536. Schur, L., Y. Rodgers, and D. Kruse. "COVID-19 and Employment Losses for Workers with Disabilities: An Intersectional Approach." Social Science Research Network, February 19, 2021. Available at https://papers.ssrn.com/sol3/papers.cfm?abstract id=3788319. Mathematica® Inc. 33 References Schwandt, H., and T. von Wachter. "Unlucky Cohorts: Estimating the Long-Term Effects of Entering the Labor Market in a Recession in Large Cross-Sectional Data Sets." Journal of Labor Economics, vol. 37, no. S1S1, January 2019, pp. S161-S198. Schwandt, H., and T. von Wachter. "Socioeconomic Decline and Death: Midlife Impacts of Graduating in a Recession." NBER Working Paper 26638. Cambridge, MA: National Bureau Of Economic Research, 2020. Social Security Administration (SSA). "Follow-Up: Childhood Continuing Disability Reviews and Age 18 Redeterminations." Audit Report No. A-01-11-11118. Baltimore, MD: SSA, Office of the Inspector General, 2011. Stuart, B.A. "The Long-Run Effects of Recessions on Education and Income." American Economic Journal: Applied Economics, vol. 14, no. 1, 2022, pp. 42-74. U.S. Bureau of Labor Statistics. "The Employment Situation-July 2022." 2022. Available at https://www.bls.gov/news.release/archives/empsit 08052022 .htm. U.S. Bureau of Labor Statistics. "The Employment Situation-October 2020." 2020. Available at https://www.bls.gov/news.release/archives/empsit 11062020.htm. U.S. Department of Education. "Applications for New Awards; Promoting the Readiness of Minors in Supplemental Security Income (PROMISE)." Federal Register, vol. 78, no. 98, 2013, pp. 29733- 29748. Available at http://www.gpo.gov/fdsys/pkg/FR-2013-05- 21/pdf/2013-12083.pdf. von Wachter, T. "The Persistent Effects of Initial Labor Market Conditions for Young Adults and Their Sources." The Journal of Economic Perspectives, vol. 34, no. 4, 2020, pp. 168-194. Available at https://www .jstor.org/stable/26940895 Mathematica® Inc. 34 Technical Appendix This page has been left blank for double-sided copying. Technical Appendix A. Differences between pre- and during-pandemic survey respondents In this section, we examine the differences in the composition of the pre- and during-pandemic respondents to the Promoting Readiness of Minors in Supplemental Security Income (PROMISE) five- year surveys and discuss the implications for interpreting the findings of this study. Because the timing of survey response was not randomly assigned, pre- and during-pandemic respondents might not have the same characteristics and, therefore, might have had different outcomes even if the pandemic had not occurred. As a result, we cannot isolate the effects of the pandemic by estimating the differences in their outcomes. Although we use covariate adjustment to account for the observed differences between pre- and during-pandemic respondents (as described below), we caution readers not to interpret the findings of the study in terms of causal impacts of the pandemic. Instead, the findings should be interpreted as suggestive evidence on how the outcomes of youth with disabilities were different during the pandemic. Below, we discuss three possible reasons that the composition of pre- and during-pandemic survey respondents might differ and describe how we examined these reasons and attempted to account for them in the analyses. 1. Differences in programs' enrollment periods The main analyses in this report rely on data pooled across the six PROMISE programs, but the programs varied in their enrollment periods. Because we attempted to survey youth about five years after they enrolled in the evaluation, programs that began enrolling earlier have more pre-pandemic respondents than those that began enrolling later (Table A.1). For example, Maryland PROMISE (MD PROMISE) and Wisconsin PROMISE (WI PROMISE) were the first programs to begin enrollment, and more than 32 percent of their enrollees enrolled before March 13, 2015 (and thus would have been eligible for the five- year survey before the President's national emergency declaration related to the pandemic). In contrast, New York State PROMISE (NYS PROMISE) was one of the last programs to begin enrollment, and less than five percent of its enrollees enrolled before March 13, 2015. There are two possible ways in which the unequal distribution of respondents by program across the pre- and during-pandemic respondents might drive the findings based on pooled data: (1) differences in enrollee characteristics across programs that affect outcomes and (2) differences in program effectiveness. | Table A.1. The PROMISE programs and their enroliment periods Arkansas PROMISE | September 2014-April 2016 ASPIRE October 2014-April 2016 CaPROMISE August 2014-April 2016 MD PROMISE April 2014-February 2016 NYS PROMISE October 2014--April 2016 95 (4.8%) 1,872 (95.2%) WI PROMISE April 2014-April 2016 600 (31.7%) 1,296 (68.4%) Source: Honeycutt et al. (2018); U.S. Department of Education (2013b); Livermore et al. (2020). Note: Youth who were enrolled before (or on or after) March 13, 2015, were more likely to have been eligible for the survey before (or on or after) the President's national emergency declaration on March 15, 2020. ASPIRE = Achieving Success by Promoting Readiness for Education and Employment; CaPROMISE = California PROMISE; MD = Maryland; NYS = New York State; SSA = Social Security Administration; Wl = Wisconsin. 679 (37.6%) 365 (18.7%) 947 (30.6%) 724 (38.8%) 1,126 (62.4%) 1,588 (81.3%) 2,150 (69.4%) 1,142 (61.2%) Mathematica® Inc. A3 Technical Appendix We conducted sensitivity tests to assess the extent to which the unequal distribution of respondents by program across the pre- and during-pandemic periods might be driving the findings based on pooled data. We examined differences between the pre- and during-pandemic respondents in youth's use of services and labor market outcomes during the 18 months after random assignment, which were measured before the pandemic (Table A.2). Control group youth's use of services and labor market outcomes during the 18 months after RA did not differ significantly between the pre- and during-pandemic periods. The average impacts of the programs on service use and labor market outcomes during the 18 months after RA also did not differ between the pre- and during-pandemic periods. Thus, when comparing the outcomes of pre- and during-pandemic respondents, we did not find the same large differences in control group outcomes and program impacts for 18-month outcomes that we observed for five-year outcomes. The findings of the sensitivity test suggest that the pattern of poorer five-year outcomes and smaller or no program impacts among during-pandemic respondents compared to pre-pandemic respondents is likely to be due at least in part to the pandemic. Nevertheless, we included program-specific fixed effects in all analyses of data pooled across programs to account for differences in the distribution of respondents by program between the pre- and during-pandemic periods. 2. Differences in participants' baseline characteristics Pre- and during-pandemic respondents might differ in their characteristics such that their outcomes might have differed even if the pandemic had not occurred. These differences might occur for several reasons. First, the composition of youth enrolling in each program might have changed over time due to programs' enrollment experiences. For example, some programs enrolled a larger share of older youth early in the implementation period, so we expect a larger share of youth who were age 16 at RA among early enrollees and pre-pandemic respondents than among later enrollees and during-pandemic respondents.' Second, some enrollee characteristics (such as race and ethnicity) might reflect the make-up of the states in which programs operated. Therefore, pre- and during-pandemic respondents are more likely to reflect the demographic composition of the programs that began enrolling earlier and later, respectively. Finally, the timing of survey completion might be influenced by youth's outcomes. For example, among youth who enrolled around the same time, youth who were employed or in school might have been less available for surveys such that they were less likely to be early responders (and thus less likely to be pre- pandemic respondents). In exploratory analyses we found that, among youth and parents who completed the five-year survey, those who were employed took 3 to 4 days longer to respond to the survey compared to their non-employed peers (results not shown). We compared the characteristics of pre- and during-pandemic survey respondents and found several differences (Table A.3). In pooled data, pre-pandemic respondents were, on average, older at enrollment and at the time of their most recent Supplemental Security Income (SSI) application, and they were more likely to be female, prefer English as their spoken language, be non-Hispanic White, or receive SSI in the month before RA, compared to during-pandemic respondents. Similarly, there were differences in the characteristics of pre- and during-pandemic survey respondents in each program (Tables A.4-A.9). In the analyses, we control for some differences in the characteristics of pre- and during-pandemic survey respondents. When comparing the mean outcomes of pre- and during-pandemic respondents among PROMISE enrollees and American Community Survey (ACS) youth, we controlled for age, sex, race, 3 Some programs might have focused on older youth because they were at risk of becoming ineligible for PROMISE sooner. Similarly, once programs achieved their enrollment targets, the remaining eligible youth, who were disproportionately younger, could not enroll. Mathematica® Inc. Ad Technical Appendix ethnicity, and state of residence; data for these characteristics were available for both the PROMISE and ACS youth. When comparing the impacts of PROMISE programs on pre- and during-pandemic respondents, we used regression adjustment to control for the following baseline characteristics of youth measured at the time of random assignment: age, sex, preference for English as a spoken language, living arrangement, race and ethnicity, type of impairment, receipt of SSI in the prior month, years since earliest SSI eligibility, age at most recent SSI application, Social Security Administration (SSA) payments in the prior year, and parents' SSA payment status. In addition, when examining the impacts of a specific program, we controlled for characteristics that differed between that program's pre- and during-pandemic respondents. 3. Differences in participants' outcomes Youth's outcomes might influence the timing of their survey response. Youth who were employed or in school might have had less time available to dedicate to a survey, such that they completed the survey later than other youth who we attempted to survey around the same time. Among youth who were eligible for the five-year survey in the weeks before and after March 15, 2020, youth who were employed or in school might have been more likely to complete the survey after that date than before that date. As noted above, we found a slightly longer time to response among youth who were employed, however we cannot formally test this hypothesis because we cannot know how the timing of survey response would have been if the pandemic had not occurred. However, if this hypothesis is true, it would mean that some employed and in-school youth were more likely to be during-pandemic respondents than pre-pandemic respondents. This would cause our findings to understate the extent to which the pandemic dampened youth's outcomes. 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All PROMISE programs: Baseline characteristics of youth survey respondents, by timing of survey response (percentages, unless otherwise noted) Pre- During- pandemic pandemic respondents | respondents | Difference Baseline characteristic (B) (C) Youth is female 33.4 35.1 33.0 2.1* 0.09 Youth age at RA Tt 0.00 14 35.9 27.4 38.2 -10.8 15 29.1 25.7 29.9 -4.2 16 35.0 46.9 31.9 15.0 Youth prefers English for spoken language 88.4 91.9 87.4 4 5% 0.00 Youth living arrangement at SSI application 1t 0.01 In parents' household 84.5 85.7 84.1 1.6 Own household or alone 13.5 11.7 14.0 -2.3 Another household and receiving support 2.1 2.7 1.9 0.7 Youth race and ethnicity Tt 0.00 Non-Hispanic White 18.0 20.0 17.5 25 Non-Hispanic Black 31.9 37.9 30.3 7.6 Hispanic 25.0 18.8 26.6 -7.8 Non-Hispanic American Indian 1.8 1.3 1.9 -0.6 Non-Hispanic other or mixed race 7.0 7.2 6.9 0.2 Missing 16.3 14.9 16.7 -1.8 Youth primary impairment 0.12 Intellectual or developmental disability 45.0 43.3 455 -2.2 Speech, hearing, or visual impairment 1.8 2.3 1.7 0.6 Physical disability 13.9 13.7 141 -0.4 Other mental impairment 35.1 36.8 345 2.3 Other or unknown disability 4.2 4.0 4.3 -0.3 Youth SSA payment status at RA Received SSI 94.2 96.4 93.6 2.7 0.00 Received OASDI 10.9 11.5 10.7 0.9 0.29 Years between youth's earliest SSI eligibility and RA 8.8 8.9 8.8 0.1 0.65 Youth age at most recent SSI application 71 7.4 7.0 0.4*** 0.00 Youth SSA payments in the year before RA ($) 7,597 7,643 7,586 57 0.25 Household had multiple SSi-eligible children 19.5 20.8 19.2 1.7 0.12 Mathematica® Inc. Technical Appendix Pre- During- pandemic pandemic respondents | respondents | Difference Baseline characteristic (B) (C) Parent SSA payment status at RA 1t 0.00 Any parent received SSI only 9.3 104 9.0 1.4 Any parent received OASDI only 8.7 9.8 8.5 1.4 Any parent received both SSI and OASDI 5.4 6.3 5.2 1.1 No parent received any SSA payments 70.0 69.2 70.1 -0.9 No parent was included in the SSA data analyses 6.6 4.3 7.2 -3.0 Number of youth 9,344 1,898 7,446 Source: SSA administrative records, PROMISE RA system, and PROMISE 18-month survey (race and ethnicity). Note: The sample includes all youth who completed the PROMISE five-year survey before the pandemic (before March 13, 2020) and during the pandemic (March 13, 2020, or after). We weighted the statistics to adjust for survey nonresponse. The p-value for a continuous or binary variable is based on a two-tailed #-test. The p-value for a multinomial categorical variable, which we present in the row for the variable label, is based on a chi-square test across all categories. We pooled data across the six PROMISE programs and weighted the programs equally. Survey response rates were 83 percent for youth and 83 percent for parents. We weighted all statistics to adjust for survey nonresponse. **[** Difference is significantly different from zero (p-value is less than .10/.05/.01) using a two-tailed t-test. 111/ttt Difference is significantly different from zero (p-value is less than .10/.05/.01) using a chi-square test. OASDI = Old-Age, Survivors, and Disability Insurance; RA = random assignment; SSA = Social Security Administration; SSI = Supplemental Security Income. Mathematica® Inc. Technical Appendix I Appendix Table A.4. Arkansas PROMISE: Baseline characteristics of youth survey respondents, by timing of survey response (percentages, unless otherwise noted) M CH During- pandemic pandemic respondents | respondents | Difference Baseline characteristic (B) (C) Youth is female 34.0 34.6 33.8 0.8 0.78 Youth age at RA 11t 0.00 14 38.8 31.6 41.3 -9.6 15 271 26.3 27.6 -1.2 16 34.1 42.0 31.2 10.9 Youth prefers English for spoken language 97.5 95.1 98.5 -3.5"** 0.00 Youth living arrangement at SSI application 0.34 In parents' household 86.6 87.8 86.1 1.7 Own household or alone 124 10.7 13.0 -2.2 Another household and receiving support 1.0 14 0.9 0.5 Youth race and ethnicity 1 0.06 Non-Hispanic White 18.0 18.4 17.9 0.6 Non-Hispanic Black 48.2 48.8 48.0 0.7 Hispanic 6.6 9.6 55 4.1 Non-Hispanic American Indian 0.8 0.7 0.8 -0.0 Non-Hispanic other or mixed race 6.9 6.6 7.0 -0.4 Missing 19.6 15.8 20.8 -4.9 Youth primary impairment T 0.03 Intellectual or developmental disability 42.6 48.3 40.7 7.6 Speech, hearing, or visual impairment 1.1 0.8 1.3 -0.4 Physical disability 10.3 11.9 9.7 22 Other mental impairment 43.3 36.8 454 -8.6 Other or unknown disability 2.7 2.2 2.9 -0.7 Youth SSA payment status at RA Received SSI 94.2 95.3 93.7 1.6 0.25 Received OASDI 14.7 15.8 14.3 1.4 0.50 Years between youth's earliest SSI eligibility and RA 8.7 8.8 8.7 0.1 0.57 Youth age at most recent SSI application 71 7.3 71 0.2 0.44 Youth SSA payments in the year before RA ($) 7,636 7,616 7,646 -30 0.77 Household had multiple SSlI-eligible children 27.5 31.1 26.0 5.2* 0.06 Mathematica® Inc. Technical Appendix Pre- During- pandemic pandemic respondents | respondents | Difference Baseline characteristic (B) (C) Parent SSA payment status at RA 0.85 Any parent received SSI only 9.7 10.7 9.3 14 Any parent received OASDI only 11.8 12.2 11.6 0.6 Any parent received both SSI and OASDI 7.5 6.7 7.8 -1.1 No parent received any SSA payments 69.1 68.8 69.3 -0.5 No parent was included in the SSA data analyses 1.9 1.6 21 -0.4 Number of youth 1,436 380 1,056 Source: SSA administrative records, PROMISE RA system, and PROMISE 18-month survey (race and ethnicity). Note: The sample includes all youth who completed the PROMISE five-year survey before the pandemic (before March 13, 2020) and during the pandemic (March 13, 2020, or after). We weighted the statistics to adjust for survey nonresponse. The p-value for a continuous or binary variable is based on a two-tailed #-test. The p-value for a multinomial categorical variable, which we present in the row for the variable label, is based on a chi-square test across all categories. Survey response rates were 81 percent for youth and 80 percent for parents. We weighted all statistics to adjust for survey nonresponse. Difference is significantly different from zero (p-value is less than .10/.05/.01) using a two-tailed t-test. t/t1/t1t Difference is significantly different from zero (p-value is less than .10/.05/.01) using a chi-square test. OASDI = Old-Age, Survivors, and Disability Insurance; RA = random assignment; SSA = Social Security Administration; SSI = Supplemental Security Income. * /** /*** Mathematica® Inc. Technical Appendix I Appendix Table A.5. ASPIRE: Baseline characteristics of youth survey respondents, by timing of survey response (percentages, unless otherwise noted) M8 During- pandemic pandemic respondents | respondents | Difference Baseline characteristic (B) (C) Youth is female 32.6 37.3 31.9 5.4 0.14 Youth age at RA 0.40\ 14 37.6 33.5 38.3 -4.7 15 31.7 324 31.5 0.9 16 30.7 34.0 30.2 3.8 Youth prefers English for spoken language 91.3 97.5 90.4 7.0%** 0.00 Youth living arrangement at SSI application Tt 0.00 In parents' household 83.5 84.3 83.4 0.9 Own household or alone 13.6 9.4 14.2 -4.8 Another household and receiving support 2.8 6.3 24 3.9 Youth race and ethnicity Tt 0.02 Non-Hispanic White 37.7 47.2 36.5 10.7 Non-Hispanic Black 11.3 10.8 114 -0.7 Hispanic 37.4 28.0 38.5 -10.5 Non-Hispanic American Indian 5.8 4.1 6.1 -2.0 Non-Hispanic other or mixed race 7.5 9.5 7.2 2.2 Missing 0.2 0.5 0.2 0.3 Youth primary impairment 0.96 Intellectual or developmental disability 45.0 443 45.2 -0.9 Speech, hearing, or visual impairment 2.3 2.6 2.3 0.4 Physical disability 19.1 19.9 19.0 0.9 Other mental impairment 28.7 29.2 28.5 0.7 Other or unknown disability 4.9 4.0 5.0 -1.0 Youth SSA payment status at RA Received SSI 91.2 95.2 90.6 4.6*** 0.01 Received OASDI 10.0 8.2 10.2 -2.0 0.36 Years between youth's earliest SSI eligibility and RA 8.8 8.9 8.8 0.1 0.69 Youth age at most recent SSI application 7.2 7.5 71 0.4 0.27 Youth SSA payments in the year before RA ($) 7,385 7,272 7,398 -126 0.43 Household had multiple SSl-eligible children 17.8 14.8 18.3 -3.5 0.20 Mathematica® Inc. Technical Appendix Pre- During- pandemic pandemic respondents | respondents | Difference Baseline characteristic (B) (C) Parent SSA payment status at RA 1t 0.00 Any parent received SSI only 9.1 10.9 8.8 2.1 Any parent received OASDI only 9.3 9.7 9.3 0.3 Any parent received both SSI and OASDI 4.4 8.8 3.9 49 No parent received any SSA payments 69.1 67.5 69.2 -1.7 No parent was included in the SSA data analyses 8.1 3.2 8.8 -5.6 Number of youth 1,588 194 1,394 Source: SSA administrative records, PROMISE RA system, and PROMISE 18-month survey (race and ethnicity). Note: The sample includes all youth who completed the PROMISE five-year survey before the pandemic (before March 13, 2020) and during the pandemic (March 13, 2020, or after). We weighted the statistics to adjust for survey nonresponse. The p-value for a continuous or binary variable is based on a two-tailed #-test. The p-value for a multinomial categorical variable, which we present in the row for the variable label, is based on a chi-square test across all categories. Survey response rates were 84 percent for youth and 84 percent for parents. We weighted all statistics to adjust for survey nonresponse. Difference is significantly different from zero (p-value is less than .10/.05/.01) using a two-tailed t-test. t/tt/t1t Difference is significantly different from zero (p-value is less than .10/.05/.01) using a chi-square test. OASDI = Old-Age, Survivors, and Disability Insurance; RA = random assignment; SSA = Social Security Administration; SSI = Supplemental Security Income. * /** /*** Mathematica® Inc. Technical Appendix 1 Appendix Table A.6. CaPROMISE: Baseline characteristics of youth survey respondents, by timing of survey response (percentages, unless otherwise noted) M During- pandemic pandemic respondents | respondents | Difference Baseline characteristic (B) (C) Youth is female 33.0 33.5 32.8 0.7 0.80 Youth age at RA 1ttt 0.00 14 34.9 26.8 37.4 -10.6 15 31.1 29.5 31.6 -2.0 16 34.0 43.7 31.0 12.7 Youth prefers English for spoken language 64.5 75.2 61.2 13.9*** 0.00 Youth living arrangement at SSI application Tt 0.01 In parents' household 76.5 80.9 75.1 5.8 Own household or alone 20.9 15.6 22.6 -7.1 Another household and receiving support 2.6 3.5 2.3 1.2 Youth race and ethnicity 11 0.01 Non-Hispanic White 54 8.8 4.3 4.5 Non-Hispanic Black 14.5 16.9 13.7 3.2 Hispanic 54.1 50.3 55.3 -5.0 Non-Hispanic American Indian 0.5 0.3 0.5 -0.2 Non-Hispanic other or mixed race 6.5 6.1 6.6 -0.5 Missing 19.1 17.7 19.5 -1.9 Youth primary impairment 1t 0.02 Intellectual or developmental disability 48.5 46.3 49.2 -2.9 Speech, hearing, or visual impairment 3.0 55 2.2 3.3 Physical disability 18.8 18.1 191 -1.0 Other mental impairment 22.7 24.0 22.3 1.7 Other or unknown disability 7.0 6.1 7.2 -1.1 Youth SSA payment status at RA Received SSI 94.1 96.2 93.5 2.7 0.03 Received OASDI 6.9 9.2 6.2 3.0* 0.07 Years between youth's earliest SSI eligibility and RA 9.0 9.1 9.0 0.0 0.91 Youth age at most recent SSI application 6.8 7.0 6.8 0.3 0.28 Youth SSA payments in the year before RA ($) 7,606 7,649 7,601 48 0.66 Household had multiple SSlI-eligible children 13.6 14.0 13.5 0.5 0.82 Mathematica® Inc. Technical Appendix Pre- During- pandemic pandemic respondents | respondents | Difference Baseline characteristic (B) (C) Parent SSA payment status at RA 1t 0.00 Any parent received SSI only 6.3 8.0 5.7 2.2 Any parent received OASDI only 6.2 9.2 5.2 3.9 Any parent received both SSI and OASDI 2.6 3.4 2.4 1.1 No parent received any SSA payments 70.3 71.9 69.7 2.2 No parent was included in the SSA data analyses 14.7 7.5 17.0 -9.5 Number of youth 1,603 381 1,222 Source: SSA administrative records, PROMISE RA system, and PROMISE 18-month survey (race and ethnicity). Note: The sample includes all youth who completed the PROMISE five-year survey before the pandemic (before March 13, 2020) and during the pandemic (March 13, 2020, or after). We weighted the statistics to adjust for survey nonresponse. The p-value for a continuous or binary variable is based on a two-tailed #-test. The p-value for a multinomial categorical variable, which we present in the row for the variable label, is based on a chi-square test across all categories. Survey response rates were 81 percent for youth and 82 percent for parents. We weighted all statistics to adjust for survey nonresponse. Difference is significantly different from zero (p-value is less than .10/.05/.01) using a two-tailed t-test. t/t1/t1t Difference is significantly different from zero (p-value is less than .10/.05/.01) using a chi-square test. OASDI = Old-Age, Survivors, and Disability Insurance; RA = random assignment; SSA = Social Security Administration; SSI = Supplemental Security Income. * /** /*** Mathematica® Inc. Technical Appendix I Appendix Table A.7. MD PROMISE: Baseline characteristics of youth survey respondents, by timing of survey response (percentages, unless otherwise noted) M CH During- pandemic pandemic respondents | respondents | Difference Baseline characteristic (B) (C) Youth is female 35.0 35.1 34.9 0.2 0.94 Youth age at RA 11t 0.00 14 26.1 16.9 30.3 -13.5 15 26.4 134 32.1 -18.7 16 47.5 69.8 37.6 32.2 Youth prefers English for spoken language 96.8 97.3 96.6 0.7 0.46 Youth living arrangement at SSI application Tt 0.03 In parents' household 86.6 83.0 88.0 -4.9 Own household or alone 10.0 13.2 8.8 4.4 Another household and receiving support 34 3.8 3.3 0.5 Youth race and ethnicity 11t 0.00 Non-Hispanic White 15.1 11.7 16.7 -4.9 Non-Hispanic Black 49.8 61.2 44.6 16.6 Hispanic 6.7 4.4 7.8 -3.4 Non-Hispanic American Indian 1.5 15 1.5 -0.0 Non-Hispanic other or mixed race 6.3 55 6.7 -1.2 Missing 20.6 15.7 22.7 -7.0 Youth primary impairment 0.83 Intellectual or developmental disability 37.3 38.5 36.7 1.8 Speech, hearing, or visual impairment 1.7 1.5 1.9 -0.4 Physical disability 1.1 10.0 11.7 -1.7 Other mental impairment 471 47.0 47.0 0.0 Other or unknown disability 2.8 3.0 2.7 0.3 Youth SSA payment status at RA Received SSI 94.6 96.8 93.5 3.2%** 0.01 Received OASDI 11.1 11.7 10.7 1.0 0.57 Years between youth's earliest SSI eligibility and RA 8.3 8.9 8.1 0.8*** 0.00 Youth age at most recent SSI application 7.9 7.8 8.0 -0.2 0.44 Youth SSA payments in the year before RA ($) 7,573 7,727 7,511 216* 0.07 Household had multiple SSlI-eligible children 17.7 18.6 17.4 1.2 0.59 Mathematica® Inc. Technical Appendix Pre- During- pandemic pandemic respondents | respondents | Difference Baseline characteristic (B) (C) Parent SSA payment status at RA 0.28 Any parent received SSI only 7.4 8.4 6.9 1.5 Any parent received OASDI only 8.2 10.2 7.5 2.7 Any parent received both SSI and OASDI 4.7 5.3 4.5 0.7 No parent received any SSA payments 73.7 70.1 75.1 -5.0 No parent was included in the SSA data analyses 6.0 6.1 6.0 0.0 Number of youth 1,474 451 1,023 Source: SSA administrative records, PROMISE RA system, and PROMISE 18-month survey (race and ethnicity). Note: The sample includes all youth who completed the PROMISE five-year survey before the pandemic (before March 13, 2020) and during the pandemic (March 13, 2020, or after). We weighted the statistics to adjust for survey nonresponse. The p-value for a continuous or binary variable is based on a two-tailed #-test. The p-value for a multinomial categorical variable, which we present in the row for the variable label, is based on a chi-square test across all categories. Survey response rates were 81 percent for youth and 81 percent for parents. We weighted all statistics to adjust for survey nonresponse. ***p+* Difference is significantly different from zero (p-value is less than .10/.05/.01) using a two-tailed t-test. t/tt/t1t Difference is significantly different from zero (p-value is less than .10/.05/.01) using a chi-square test. OASDI = Old-Age, Survivors, and Disability Insurance; RA = random assignment; SSA = Social Security Administration; SSI = Supplemental Security Income. Mathematica® Inc. Technical Appendix I Appendix Table A.8. NYS PROMISE: Baseline characteristics of youth survey respondents, by timing of survey response (percentages, unless otherwise noted) Pre- During- pandemic pandemic respondents | respondents | Difference Baseline characteristic (B) (C) Youth is female 32.7 38.6 325 6.1 0.37 Youth age at RA 1 0.08 14 38.2 28.0 38.5 -10.5 15 31.8 45.7 314 14.3 16 30.0 26.2 30.0 -3.8 Youth prefers English for spoken language 84.8 79.9 85.0 -5.1 0.36 Youth living arrangement at SSI application 0.61 In parents' household 85.6 86.6 85.5 1.1 Own household or alone 12.6 134 12.6 0.8 Another household and receiving support 1.8 0.0 1.9 -1.9 Youth race and ethnicity 0.17 Non-Hispanic White 6.7 1.9 6.9 -5.0 Non-Hispanic Black 354 29.6 35.5 -5.9 Hispanic 34.1 38.3 34.1 4.2 Non-Hispanic American Indian 0.6 0.0 0.6 -0.6 Non-Hispanic other or mixed race 7.9 16.2 7.6 8.6 Missing 15.2 14.0 15.3 -1.3 Youth primary impairment Tt 0.00 Intellectual or developmental disability 58.0 52.9 58.2 -5.3 Speech, hearing, or visual impairment 1.3 1.8 1.3 0.5 Physical disability 11.8 18.1 11.7 6.4 Other mental impairment 24.8 14.0 25.0 -10.9 Other or unknown disability 4.1 13.1 3.8 9.3 Youth SSA payment status at RA Received SSI 96.0 100.0 95.8 4.2 Received OASDI 10.0 8.1 10.0 -2.0 0.62 Years between youth's earliest SSI eligibility and RA 9.7 11.5 9.6 1.9%** 0.00 Youth age at most recent SSI application 6.1 4.3 6.1 -1.8%** 0.00 Youth SSA payments in the year before RA ($) 7,840 8,177 7,827 350* 0.08 Household had multiple SSlI-eligible children 18.8 13.5 19.0 -5.6 0.25 Mathematica® Inc. Technical Appendix Baseline characteristic Pre- pandemic respondents G During- pandemic respondents | Difference 9 Parent SSA payment status at RA 0.90 Any parent received SSI only 11.6 15.0 11.5 3.5 Any parent received OASDI only 8.6 57 8.6 -2.9 Any parent received both SSI and OASDI 5.8 5.5 5.9 -0.4 No parent received any SSA payments 68.7 68.4 68.8 -0.4 No parent was included in the SSA data analyses 5.3 5.5 5.3 0.2 Number of youth 1,657 53 1,604 Source: SSA administrative records, PROMISE RA system, and PROMISE 18-month survey (race and ethnicity). Note: The sample includes all youth who completed the PROMISE five-year survey before the pandemic (before March 13, 2020) and during the pandemic (March 13, 2020, or after). We weighted the statistics to adjust for survey nonresponse. The p-value for a continuous or binary variable is based on a two-tailed #-test. The p-value for a multinomial categorical variable, which we present in the row for the variable label, is based on a chi-square test across all categories. Survey response rates were 85 percent for youth and 85 percent for parents. We weighted all statistics to adjust for survey nonresponse. * /** /*** Difference is significantly different from zero (p-value is less than .10/.05/.01) using a two-tailed t-test. t/t1/t1t Difference is significantly different from zero (p-value is less than .10/.05/.01) using a chi-square test. OASDI = Old-Age, Survivors, and Disability Insurance; RA = random assignment; SSA = Social Security Administration; SSI = Supplemental Security Income. Mathematica® Inc. A18 Technical Appendix I Appendix Table A.9. WI PROMISE: Baseline characteristics of youth survey respondents, by timing of survey response (percentages, unless otherwise noted) M CH During- pandemic pandemic respondents | respondents | Difference Baseline characteristic (B) (C) Youth is female 33.3 35.5 324 3.1 0.26 Youth age at RA 11t 0.00 14 40.0 32.8 42.7 -9.9 15 26.3 30.3 24.7 5.6 16 33.8 36.9 32.6 43 Youth prefers English for spoken language 95.2 96.4 94.7 1.7 0.15 Youth living arrangement at SSI application Tt 0.05 In parents' household 88.1 91.3 86.9 4.4 Own household or alone 11.1 8.3 12.3 -4.0 Another household and receiving support 0.7 04 0.9 -0.4 Youth race and ethnicity 11t 0.00 Non-Hispanic White 25.0 30.3 23.2 7.2 Non-Hispanic Black 323 325 321 0.4 Hispanic 11.1 10.2 11.4 -1.2 Non-Hispanic American Indian 1.8 1.5 1.8 -0.3 Non-Hispanic other or mixed race 6.7 8.4 6.1 2.2 Missing 23.0 17.1 25.3 -8.3 Youth primary impairment 0.88 Intellectual or developmental disability 38.4 394 38.0 1.4 Speech, hearing, or visual impairment 1.3 1.7 1.2 0.6 Physical disability 12.5 12.4 12.6 -0.2 Other mental impairment 43.8 42.3 443 -1.9 Other or unknown disability 4.0 4.1 4.0 0.1 Youth SSA payment status at RA Received SSI 95.3 97.2 94.6 2.6** 0.01 Received OASDI 12.5 11.0 13.0 -1.9 0.29 Years between youth's earliest SSI eligibility and RA 8.4 8.4 8.4 -0.1 0.81 Youth age at most recent SSI application 7.4 7.8 7.3 0.4* 0.08 Youth SSA payments in the year before RA ($) 7,543 7,679 7,491 188* 0.08 Household had multiple SSlI-eligible children 21.6 22.8 21.2 1.6 0.50 Mathematica® Inc. Technical Appendix Pre- During- pandemic pandemic respondents | respondents | Difference Baseline characteristic (B) (C) Parent SSA payment status at RA 0.18 Any parent received SSI only 11.6 13.7 10.8 2.8 Any parent received OASDI only 8.4 8.2 8.4 -0.3 Any parent received both SSI and OASDI 7.4 8.5 6.9 1.6 No parent received any SSA payments 68.9 67.3 69.6 -2.3 No parent was included in the SSA data analyses 3.7 24 4.2 -1.8 Number of youth 1,586 439 1,147 Source: SSA administrative records, PROMISE RA system, and PROMISE 18-month survey (race and ethnicity). Note: The sample includes all youth who completed the PROMISE five-year survey before the pandemic (before March 13, 2020) and during the pandemic (March 13, 2020, or after). We weighted the statistics to adjust for survey nonresponse. The p-value for a continuous or binary variable is based on a two-tailed #-test. The p-value for a multinomial categorical variable, which we present in the row for the variable label, is based on a chi-square test across all categories. Survey response rates were 85 percent for youth and 85 percent for parents. We weighted all statistics to adjust for survey nonresponse. Difference is significantly different from zero (p-value is less than .10/.05/.01) using a two-tailed t-test. 111/ttt Difference is significantly different from zero (p-value is less than .10/.05/.01) using a chi-square test. OASDI = Old-Age, Survivors, and Disability Insurance; RA = random assignment; SSA = Social Security Administration; SSI = Supplemental Security Income. * /** /*** Mathematica® Inc. A.20 Technical Appendix B. Supplemental results: Youth outcomes before and during the pandemic Tables A.10 through A.23 present unadjusted means and standard deviations of outcomes measured before and during the pandemic among PROMISE youth and ACS youth ages 19-21 living in PROMISE states. Tables A.24 through A.26 present pandemic-related differences in outcomes among PROMISE youth and ACS youth ages 19-21 living in PROMISE states. Tables A.27 through A.44 present the pandemic-related differences in selected outcomes within each of the six programs. For outcomes derived from PROMISE survey data, the pre-pandemic sample comprises people who completed the survey before March 13, 2020, while the during-pandemic sample comprises people who completed the survey on or after that date. For outcomes measured among ACS youth, the pre-pandemic sample comprises youth from the 2019 one-year ACS file, and the during-pandemic sample comprises youth from the 2020 one-year ACS file. For outcomes derived from SSA data, the same person can be observed in both periods, but the sample is limited to youth who did not undergo an age-18 redetermination or whose redetermination ended before the window of time being examined. Mathematica® Inc. 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jeuoneonp3 [eJoudss) = q39 -asuodsaiuou Asains 10j 1snipe 0} sonsne)s e pajybiom app "siusied Joj Jusdisad g pue YyinoA Joj Juaolad |g a1am sajel asuodsal Aeaing "(1aye Jo '0z0g 'Sl udJen) oiwapued ay) Buunp pue (0zoz '€l Udsel alojeq) olwspued ay} aiojeq AsAins Jeak-aAl} 8y} paysidwiod oym yynoA 1oj dnoib yolessal Aq Ajjeledes awoo)no Yoee JO UOHEBIASD plepuels pue ueswl pajshipeun suyj sMoys aide) siyl :8JON 'Aenns Jeah-aAl JSINONd :82Jn0g 1'6¢ 8'6 €0¢ ¢ol 1'8¢ 9'8 2'8¢ L'8 Ayssonun 10 969|092 Jo ||e Jo awos paje|dwo) €6¢ G'6 Sve 8¢l g'/c 2'8 S'0¢€ €0l weiboid aa160p peoueApe 1o ab9)j00 Ausepuodas)sod Buipuapy 'Ly €8. 8'6¢€ €08 L2y 1'9L 607 18/ uona|dwod Jo S}edYIHISd Jo 'ewoldip jooyas ybiy 'q3o e seH Vv 6'l¢ LSy '8¢ oy G0c Sy L'¢e [00YyOs ul pajjoug S8y 8¢ v'8y v'.€ L6V v oy 8'ay 0o€ aouejsisse [elousb 10 'dV¥NS '4dNV.1 SeAl@dal pjoyasnoH ¢l ¢ol €6l 8'/ €91 L0l 68l L'¢l paxJom sinoy Ayeam 9v.'6 16G'S €€G°', 00L'y ¥Ze's LLL'S 1688 ¥8G'S ($) seak ysed ayy ul sbuiute S'9v 9'LE 0wy €9¢ 0Ly 6¢E 98y A1 pafojdwa Apuangd 88y 209 18y ¥'19 98y 819 €Ly 299 9010} Joge| 3} U] olwapued BurLing olwapued alojog dnoub josyuo) ojwapued BurLing olwapued alojog ALY RTIETTT=EY LT BT T T T L N IR T ETNY I [T = | TSI AT (Y § (pajou esimiayjo ssejun 'sabejuasied) ojwapued ayj Buunp Jo alojeq AeAins Jeek-aAl ay) pajsjdwod ynoA eyj Jeyjaym pue dnoib yaJdeasal Ag 'sawioajno s,4yjnok JSINONd JO SuoljelAsp piepue)s pue sueaw pajsnipeun :JSINONd SsesuedJdy "ZL'VY alqel Xipuaddy xipuaddy [eoluys9a] T 'sol|iwed ApaaN .o} aoue)sissy Alejodwia | 'weiboid aouejsissy uonuinN |ejuswalddng = JYNS 'UOHEIASP piepue)s = S 'Juswdojeaaq [euoleonps [eisuag aao "oU| gEOleWaylel dNVL 'ewoou| Ajunoeg |ejusws|ddng = |[SS {Afaaing Ajlunwwo) ueduswy = SOV 's)e)s JSINOHd J0 eAlejussaldal sejeLnsa aonpoud 0} pue ubisap ajdwes gDy ay} Joj Jsnipe 0] sonsiess |e paybiem apn (0Z0z ul) olwepued sy; Buunp Jo (g1.0Z uI) dslwspued ay) alojaq AsAins (ydieoal |SS Jo sso|piebau) Ajjigesip e yym asoy} 'sjuswied |SS Buinieoal asoy) 11z 01 61 sebe YinoA Sov Jo sdnoub ss.y) 10} Aj9jeiedas awo9)No Yo JO UCHBIASD PIJEpUE]S pue ueasw pajsnipeun ay) smoys aiqe) siyl 910N "YSN SINdI 'sely Jeak-suo 0Z0Z PUe 6102 SOV :90.n0S ay} pajedwiod Aayy Jayiaym Aq '|SS BulAieoal Jou pue AJljIgesip B INOylm asoy) pue 667 Loy 8'6Y S'Sy 0'¢ 29l L9y L'0€ 1C¢ L'l L'6€ €Ll Aysianiun Jo 969)j00 10 |[e Jo swos pajejdwo) 00§ 8'0S 6'6¥ L'€G L'EV €ve 88y 08¢ A Vil €8y 4 welboud 2a16ap paosueape Jo 969|109 Aepuooss)sod Buipuany cgec 8'v6 2¢'se A 6'vE 6'G8 6°0¢ ¥'68 14 099 9¢ce 688 uonajdwod J0 81801189 J0 'ewoldip looyos ybiy '3o e seH 667 €€g L6v 8'6g L9y 1°0€ 009 0.€ [O0YOS Ul pajjoiug ZLe 60l 9'/¢ €8 807 8'0¢ Vle 0Ll 6°6Y y'ov oSy €6¢e aouejsisse [elauab Jo 'dYNS 'INV.L SeAl@2al pjoyasnoH 18l §ec WA §g'ec L6l Sl 8l 691 Ll €S LS LG paxJom sinoy Ayeap €26'01 0.0'6 €08°0L €226 8SS'LL z8y'.L LoL's 90L'Yy €LL9 98L°c 698°c GGO'L ($) Jeak ysed ayy ul sBuluse 8'6 9'vS v'6v 9.9 €9y 10€ €8y 2'9€ 6¢E 61l 9'6¢ 06 pakojdwsa Apuaiind 6'Ly S'v9 L8y 9'€9 €ly €¢ee €09 0°'0S 6°¢E 6Ll v'0S 98¢ 8010} JOgE| 3L} U] olwapued Buung olwapued alojog Aunqesip e 3noypm yinok gov olwapued Buung olwsapued alojog Aunqesip e yim yinok sov olwapued Buung ISS BuiAesal yinok sy olwapued alojog T BT T T T T L N IR L ETNV I L [T | T AT [ Y § (pejou esimiayjo ssejun 'sebejuesied) slwepued ay} Bulinp 1o alojaq AeAins ay} pejejdwod Juspuodsal ay} Jayjaym pue Ajjiqesip pue ydiedal |SS A 'sawoa3no YyjnoA uosiedwiod Jo suoijelAsp piepue)s pue sueaw pajsnipeun :JSINO¥d Sesue}ly "¢}V 8jqel Xipuaddy 1 xipuaddy [eoluys9a] 9V "oU| gEOleWaylel 'saljiwe Apsap 10} aoue)sISSY Aeiodwa] = 4NV 'weiboid soue)sissy uonunp [ejuswsiddng = JyNS 'uoneinap piepuels = gs 0zis oidwes = N 'juswdojpasq [euoneonp3 [elouds) = g39 -asuodsaluou Asains 10j 1snipe 0} sonsne)s e pajybiom o "siusied Joj Jusdiad g pue YinoA Joj Juaoiad g alam sajel asuodsal Aeaing "(1aye Jo '0z0g 'Sl udJe) oiwapued ay) Buunp pue (0zoz 'Sl UdJel alojaq) olwspued sy} aiojaq AsAins Jeak-aAl} 8y} paysidwiod 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ayj pejs|dwod Yyjnok ey} Jeyjeym pue dnoub yateasal Aq 'sawioa3no s yinok JSINO¥Ud JO SUoljelAap piepuels pue sueaw pajsnipeun :JMIdSY ¥1'V 21qel xXipuaddy 1 ALY R TIETIT =Y xipuaddy [eoluys9a] v 'sol|iwed Apaa) .o} aoue)sissy Alelodwa] = 'weiboid aouelsissy uonunN [ejuswalddng = J¥NS (UOHEIASP pJEpUE)S as 'juswdojsAa( [euoeonp |elauss aao "oU| gEOlEWaYIelN dNVL 'ewoou| Ajunoeg |ejusws|ddng = |[SS {Afaang Ajlunwwo) uedsuswy = SOV 'sa)e)s JISINOHd J0 eAnejussaldal sajeLnsa aonpoud 0} pue ubisap ajidwes gDV ay} Jo} Jsnipe 0] sonsiess |e paybiem apn (0Z0z ul) olwepued ay; Buunp Jo (g1.0z uI) olwspued ay) alojaq AsAins ey} pere|dwiod Asy) Jayieum Aq '|SS Buiaienal Jou pue Aljigesip B Jnoylm asoy) pue Buinieoal asoy) 11z 01 g1 sebe YinoA Sov Jo sdnoib sa.y) 10} Aj9jeiedas awooINo YoBa JO UCHBIASD PIJEpUE]S pue ueaw pajsnipeun sy} smoys aiqe) Siyl (ydieoal |SS Jo ssajpiebau) Ajjigesip e ypm asoy} 'sjuswied |SS :910N "YSN SIWNdI 'sely Jeak-ouo 0Z0Z PUe 610Z SOV :90n0S 9'6Y ey 9'6y o'vy S'ey €6¢ S'ey €6¢ L'ce S'LL 8'6¢ L6 AysJianiun Jo 969100 10 |[e Jo swos paje|dwo) 009 L'2S 0°0S 0¢s 08y 8'Ge 9 6°0€ 8Ly €cc vve gel welboud 9a16ap paosuepe Jo 969|100 Aepuooss)sod Buipuany 6'9¢ 126 '8¢ v'lL6 1'8€ 1'l8 vy §'9. 9vy L'€L L'Sy 6°0L uonajdwod J0 81201189 J0 'ewoldip looyos ybiy '3o e seH 861 Svs 861 6'vS 861 ¢Sy v'6v Ley 6'9v L'ce Sy Ggee [O0YOS Ul pajjoiug L°0€ gol €/c 1'8 L'ey 6'€c 90€ ol €Ly L'€e 10€ ol aouejsisse [elauab Jo 'dYNS 'INV.L SeAl@oal pjoyasnoH 29l 8¢ 09l 0'se L/l '8l 1'8l V6l el Vi 9Ll €9 paxJom sinoy Ayeapn ZrL'cL evL'LL LigLL 06711 Lyy'oL PiE'L re8'oL 68, 8€6'G 29.'c 685'C GGGl | ($) seehysed ayy ul sbuluieg 08y 6'€9 G'9v €89 g6y 9'0v 66V €9y G'lLe Ll Sty 8'v¢ pakojdwsa Apuaiind €6y €L L'ty €. 0°0s 12§ 9'6Y 0°'/S o¢cy 9'¢c S'9v 8'0¢ 8010} JogE| 8L} U] olwapued Buung olwapued alojog Aligesip e 3noyym yinoA sy ojwapued BurLing olwapued aiojog Angesip e yyim yinok sov olwapued BuLing ISS BuiAegal yinok sy olwapued alojog LT RV T T T T L W IR L ETNY I L [T = | T T AT (Y § (pejou asimusyjo ssejun 'sabejussiad) sjwepued sy} Bulinp Jo alojaq AeAins ey} pejsjdwos Juepuodsal ey} Joyjaym pue Aypqesip pue jdiedsal |SS Aq 'sawioono yinoA uosuedwod Jo sUoleIASp piepue)s pue sueaw pajsnipeun :JNIdSY 'S'V @lqel Xipuaddy 1 xipuaddy [eoluys9a] 8Cv "oU| gEOlEWaYIelN 'saljiwe Apsap 10} aoue)sISSY Aeiodws ] = NV 'weiboid aoue)sissy uonuinN [euswaiddng = JyNS 'uoneiaap piepuels = gs 9zis sjdwes = N 'Juawdojaasq jeuoneonp3 [eJouss) = 39 -asuodsaiuou Asains 10j 1snipe 0} sonsne)s e pajybiom app "siusied Joj Jusdiad gg pue YyinoA Joj Juaoiad |g alam sajel asuodsal Aeaing "(1aye Jo '0z0g 'Sl udJe) oiwapued ay) Buunp pue (0zoz '€l UdJel alojaq) olwspued ay} aiojaq AsAins Jeak-aAl} 8y} paysidwiod oym yynoA 1oj dnoib yolessal Aq Ajjeledes awoo)no Yoee JO UOHEBIASD plepuels pue ueswl pejshipeun sy} sMoys ejde) siyl :8JON 'Aenins Jeah-aAl JSINONd :82Jn0g €9¢ LSl 9'/2 €8 €9¢ 96l 9'6¢ L6 Ayssonun 10 969]|02 Jo ||e Jo awos paje|dwo) 8'0 o'le Vv 0'ce 'Ly L'le 8'6€ 861 weiboid sa168p peoueApe 1o ab9)j00 Ausepuodas)sod Buipuapy 9'6¢ S'08 '6€ 808 607 8'8. €ob 9'6. uona|dwod Jo SjedyIIsd Jo 'ewoldip jooyas ybiy 'q3o e seH 661 0es 008 0¢cs L6 €6G 667 q'es [00YyOs ul pajjolul g6y 0Ly 8'9y Gg'ce L8y 1'8€ g8y WA aouejsisse [elousb 10 'd¥NS '4ANV.L SeAledal pjoyasnoH gLl Ly LGl 09 L€l V'S vl 18 paxJom sinoy Ayeap 9€0'8 68G'C 1G6'8 S¥8'e 656'8 GE]'e 19L'6 9/1°S ($) seak ysed ayy ul sbuiute €8¢ 6Ll Lev 0ec 1L6€ 96l 691 8¢t pakojdwsa Apuaiind '8y L9€ 86V 8'Gy 88y 2'6¢ L6V €6G 8010} Joge| 3Ly} U] olwapued BurLing olwapued alojag olwapued BuLing olwapued alojog LT BT T T T T L N IR T ETNY I L [T = | T I AT [ Y § ALY RTIETTT=EY dnoub jonuo) (pajou asimieljo ssajun 'sebejuasiad) sjwapued ayj Bulinp Jo alojaq AsAins Jeak-aAal ayj peje|dwod Yyjnok sy} Jeyjeym pue dnoub yateasal Aq 'sawioajno s,ynoA JSINOMJ JO SUollelAap piepue)s pue sueaw pajsnipeun :3SINONde) '91'V 2lqel xipuaddy 1 xipuaddy [eoluys9a] 6C'V 'weibolid eouejsissy uonunN |ejuewsalddng dVNS :Uoeiasp pJepuess = s 'sol|iwe4 Apaa .o} aoue)sissy Aletodwia | Juswdojaaa( |euol}eanpy |elauss) 'sa)e)s JSINOHd JO aAnrussaldal sa)jeLnsa aao "oU| gEOlEWaYIelN dNVL 'ewoou| Ajunoeg |ejusws|ddng = |[SS {Afaang Ajunwwo) uedsuswy = SOV aonpoud 0} pue ubisap ajdwes gDV ay} Jo} Jsnipe 0] sonsiess |e pawybiem apn (0Z0z ul) olwepued ay; Buunp Jo (61.0z uI) olwspued ay) alojeq AsAins '(3dis0a1 |SS Jo sso|plebal) Ajjigesip e yym asoy} 'sjuswied |SS Buinieoal asoy) 11z 0} g1 sebe YinoA §ov Jo sdnoib sa.y) 10} Aj9jeiedas awooINo YoB JO UCHBIASD PJEpUE]S pue ueaw pajsnipeun sy} smoys aiqe) Siyl 910N "YSN SN 'sely Jeak-ouo 0Z0Z PUe 6102 SOV :90n0S ay} paje|dwioo Asyj Jeyiaym Aq |SS Buiaieoal Jou pue AJjIgesip B 1noyjim asoy) pue 008 L'6v 0°'0s Vg 0Ly 6¢c 6'9v 9¢e 9'Sy A4 '8¢ Gl AysJianiun Jo 969)j00 10 |[e Jo swos paje|dwo) 0'8y L'v9 9'8y 9'L9 6'6¥ 0Ly 6'6¥ 0'9 €8y ¥'9€ S8y v'.l€ welboud 9a16ap paosueape Jo 969|00 Aepuooss)sod Buipusny 8'¢c S'v6 v've 1L'€6 6'8¢ v'18 L0V 661 v'8y 6°¢9 0'sy L¢L uonajdwod J0 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[eoluys9a] ocv "oU| gEOlEWaYIelN 'saljiwe Apsap 10} aoue)sISSY Aeiodws | = NV 'weiboid aoue)sissy uonuin [euswaiddng = JyNS uoneiaap piepue)s = gs 9zis sjdwes = N Juawdojaasq jeuoneonp3 [eJoudss) = 39 -asuodsaiuou Asains 10j 1snipe 0} sonsne)s e pajybiom o "siusied Joj Jusdiad | g pue yinoA Joj Juaoiad |g alam sajel asuodsal Aaaing "(1aye Jo '0z0g 'Sl udJe) oiwapued ay) Buunp pue (0zoz 'Sl UdJe alojaq) olwspued sy} aiojaq AsAins Jeak-aAl} 8y} paysidwiod oym yynoA 1oj dnoib yolessal Aq Ajjeledes awoo)no Yoee JO UOHEBIASD plepuels pue ueswl pajshipeun suyj sMoys ejde) siyl :8JON 'Aenns Jeah-aAl JSINONd :82Jn0g 6'8¢ 6 1'9¢ L2 6'6¢ ool 8'/¢ g'8 Ayssonun 10 969]|02 Jo ||e Jo awos paje|dwo) g'le a'bl 8'0¢ 90l 6°0€ L0l zee Z2's weiboid aa160p paoueApe 10 ab9)j00 Asepuodas)sod Buipuapy 9'6y S'0L V'ey 8'v. 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Supplemental results: PROMISE impacts before and during the pandemic Tables A.45 through A.51 present estimated impacts of each of the six programs on outcomes of youth in the pre- and during-pandemic periods. As for other analyses, for outcomes derived from survey data, the pre-pandemic sample comprises people who completed the survey before March 13, 2020, while the during-pandemic sample comprises pecople who completed the survey on or after that date. For outcomes derived from SSA data, the same person can be observed in both periods, but the sample is limited to youth who did not undergo an age-18 redetermination or whose redetermination occurred before the window of time being examined. Mathematica® Inc. A.64 oY "oU| geoliewsyieN 690 969°¢ 0S.'e 820 L0 26 6 ¥S56 68°0 20 S. 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Aanins ojwapued-aud jo aidwes ay] 'sdnolb om) sy} usamiaq SOSUSIOBIBYD BUI[9SEq Ul S92UBISKIP J0} Buljjosuod ajiym dlwspued ay) buunp AaAins ay) 0} papuodsal oym YinoA Jo sawiodyno sy} 0} (0Z0Z 'Sl YoJe elojaq se pauysp) olwepued sy} alojaq ABAIns ay) 0} papuodsal oym ynoA Jo sawoo)no ay) pasedwod am 'ejep ASAINS WOJ PaALIBP SAWO02)N0 JO4 'asuodsaiuou Asains Joj 3snipe o} sonsnels payybiam app 'dnolb jonuos 9y} JO} uBBW PaAISSCO Y} 0) djewnysa Joedwi ay) Buippe Aq paje|nojes oq ues dnolB Juswieal) ay) J0j Uesw pajsnipe Sy 'SOWOIINO UOeINPS pue oJwiouoos s, YinoA uo JSINOHd IM Jo sjoeduw ay) jo sejewisa pajsnipe-uoissalbal sy} pue dnoub josuod 8y} Joj SUBSW PBAISSJO 8L} SMOYS 9|dE} SIYL :9JON *SpJ0O2aJ SAljesiS|UlWpPe YSS pue AsAins Jeak-aAly JSINOYd :82inog €90 699 995 100 bV L'S 6le Gle 900 29 Ll Jeak 1sed ay) ul [enuapalo Bujuiel e paAleoay 8.0 z€s LS LE0 0¢- 9Cl oLe oLe 1.0 6'0- 61l weJboud Buiuiely pajejal-qol e ui pajjoiug sjoedwi ur | N dnoab N dnoub |anjea| joedwy ueaw | N dnouib [N L Y9 (1]-E=111] EITEI G AT (Y} CETIEY YT I TV (e 2o U T TTTH -V |ouo) | |osuon | juswiyeal) [[TETTTeTo) LT ) I L I te RITEL VLT T T xipuaddy [eoluys9a] Technical Appendix D. Time periods for analyses of SSA program participation outcomes When we examine PROMISE youth's monthly SSA payments, we observe a declining trend over time (see Figure A.1). This is expected as youth grow older because they might lose benefits as part of the age- 18 redetermination process or receive reduced benefits due to increased earnings. When we examined differences in youth's outcomes and programs' impacts on youth outcomes before and during the pandemic, we wanted to separate the potential effects of the pandemic from the pre-existing downward trend in SSA payments to youth. To do so, we restricted the analysis sample to enrollees whose age-18 redeterminations occurred before the analysis window (described in detail below) or who never underwent an age-18 redetermination during the analysis window. We also excluded youth who died during the analysis window. As a result, the findings on the pre- and during-pandemic differences in SSA payment outcomes do not generalize to youth whose age-18 redeterminations concluded after the analysis window began. These youth are younger on average than the youth included in the analysis. We used a data-driven approach to determine the optimal window of time for the analysis of the SSA payment outcomes before and during the pandemic. For the pre-pandemic period, we selected a period that was long enough to provide a stable measure of average monthly payments but was short enough to yield a reasonably large number of enrollees whose age-18 redeterminations had occurred before the period began. As a result, we chose a three-month window from January to March 2020. We chose a during-pandemic period of three months, from April 2020 through June 2020. We considered different during-pandemic period lengths ranging from 3 to 12 months and selected the number of months that yielded the smallest root mean squared error for the estimated adjusted difference in average monthly SSA payments between the during and pre-pandemic periods for control group youth across all programs (Cattaneo et al. 2020). As a sensitivity test, we also conducted an interrupted time series analysis that included all youth who remained alive during the analysis window regardless of redetermination status and modeled trends in monthly payments before and during the pandemic (Tables A.52 through A.58). Mathematica® Inc. A.79 08'V "ou| geoljewsyie 'awoou| Aundag |ejuswalddng = |SS {uonelsiuIWpPY AUNaS [BIDOS = YSS "$99||0Jua-uoU 3|q1B119-3SINOHd PUE YinoA ISINOXHd 10} 1.Z0Z Yyote ybnouys 610z 1udy wouy sjuswAed yss Alyjuow abelaae smoys ainbiy siyl '010N "SPJ0DAI SAlJRSIUILIP. 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All PROMISE programs: Trends in Youth's SSA payments before and during the COVID-19 pandemic - interrupted time series estimates Payment amount ($/SE) Any payment (p.p./SE) SSA payments PROMISE control group (N=6,223) Pre-pandemic trend 0.02 -4.03** -4.36*** -0.00*** -0.01*** -0.01*** (0.18) (0.41) (0.33) (0.00) (0.00) (0.00) Change between March and April -0.13 -0.43 4.48* 0.00 0.00 0.01 2020 (2.06) (3.04) (2.10) (0.00) (0.00) (0.00) Difference between during-pandemic 0.48 1.86*** 2.47** 0.00*** 0.00*** 0.00*** trend and pre-pandemic trend (0.48) (0.53) (0.41) (0.00) (0.00) (0.00) PROMISE treatment group (N=6,223) Pre-pandemic trend 0.15 -5.40%** -5.44* -0.00%** -0.01*** -0.01*** (0.22) (0.44) (0.36) (0.00) (0.00) (0.00) Change between March and April 0.77 3.30 6.48** 0.01*** 0.00 0.00 2020 (1.59) (3.07) (2.17) (0.00) (0.00) (0.00) Difference between during-pandemic 0.25 2.71*** 3.46%** 0.00*** 0.01*** 0.01*** trend and pre-pandemic trend (0.33) (0.59) (0.45) (0.00) (0.00) (0.00) PROMISE-eligible non-enrollees (N=68,849) Pre-pandemic trend -0.27** -4.33*** -4.53*** -0.00*** -0.01*** -0.01*** (0.05) (0.13) (0.10) (0.00) (0.00) (0.00) Change between March and April 2.10** 3.96*** 4.83** 0.00*** 0.00** 0.00*** 2020 (0.46) (0.98) (0.61) (0.00) (0.00) (0.00) Difference between during-pandemic 0.18* 2.02*** 2.66™** 0.00*** 0.00***t 0.00***t trend and pre-pandemic trend (0.08) (0.17) (0.13) (0.00) (0.00) (0.00) Source: SSA administrative records. Note: This table shows interrupted time series estimates of the trends in SSA payments before the onset of the pandemic, the change in the level of the SSA payment outcome at the beginning of the pandemic, and differences in the trends in SSA payment outcomes between the during- and pre-pandemic periods for the treatment group, control group, and non-enrollees. SSA payments before the pandemic represent payments in the 12 months between April 2019 and March 2020; SSA payments during the pandemic represent payments in the 12 months between April 2020 and March 2021. We pooled data across the six PROMISE programs and weighted the programs equally. Estimate is significantly different from zero (p-value is less than .10/.05/.01) using a two-tailed f-test. 1 The difference between the pre- and during-pandemic values is significantly different from the difference in those values observed among PROMISE treatment group youth (p-value is less than .05) using a two-tailed f-test. 1 The difference between the pre- and during-pandemic values is significantly different from the difference in those values observed among PROMISE control group youth (p-value is less than .05) using a two-tailed t-test. * /** /**'k N = sample size; OASDI = Old-Age, Survivors, and Disability Insurance; p.p. = percentage point; SE = standard error; SSA = Social Security Administration; SSI = Supplemental Security Income. Mathematica® Inc. A.81 Technical Appendix | Appendix Table A.53. AR PROMISE: Trends in Youth's SSA payments before and during the COVID-19 pandemic- interrupted time series estimates Payment amount ($/SE) Any payment (p.p./SE) SSA payments PROMISE control group (N=894) Pre-pandemic trend -0.04 -6.40** -1.47** -0.00*** -0.01*** -0.01*** (0.74) (0.98) (0.86) (0.00) (0.00) (0.00) Change between March and April -2.38 227 8.1 0.00 0.02* 0.02* 2020 (7.20) (6.23) (5.07) (0.00) (0.01) (0.01) Difference between during-pandemic 0.05 3.88** 4.77+* 0.00** 0.01*** 0.01*** trend and pre-pandemic trend (0.86) (1.27) (1.06) (0.00) (0.00) (0.00) PROMISE treatment group (N=892) Pre-pandemic trend -0.37 -9.90*** -9.61*** -0.00** -0.01*** -0.01*** (0.25) (1.08) (0.97) (0.00) (0.00) (0.00) Change between March and April 3.29 1.81 5.01 0.01* 0.00 0.00 2020 (2.17) (6.75) (5.63) (0.00) (0.01) (0.01) Difference between during-pandemic 0.49 6.80*** 6.93*** 0.00 0.01*** 0.01*** trend and pre-pandemic trend (0.36) (1.34) (1.17) (0.00) (0.00) (0.00) PROMISE-eligible non-enrollees (N=7,767) Pre-pandemic trend -0.49** -4 .54*** -5.33*** -0.00*** -0.01*** -0.01*** (0.16) (0.32) (0.27) (0.00) (0.00) (0.00) Change between March and April -0.20 3.11 3.95* 0.00 0.00* 0.00* 2020 (1.20) (2.46) (1.69) (0.00) (0.00) (0.00) Difference between during-pandemic 0.13 1.53***t 2.52"*t% 0.00*** 0.00***t% 0.00***t% trend and pre-pandemic trend (0.20) (0.44) (0.36) (0.00) (0.00) (0.00) Source: SSA administrative records. Note: This table shows interrupted time series estimates of the trends in SSA payments before the onset of the pandemic, the change in the level of the SSA payment outcome at the beginning of the pandemic, and differences in the trends in SSA payment outcomes between the during- and pre-pandemic periods for the treatment group, control group, and non-enrollees. SSA payments before the pandemic represent payments in the 12 months between April 2019 and March 2020; SSA payments during the pandemic represent payments in the 12 months between April 2020 and March 2021. */**/*** Estimate is significantly different from zero (p-value is less than .10/.05/.01) using a two-tailed t-test. 1 The difference between the pre- and during-pandemic values is significantly different from the difference in those values observed among PROMISE treatment group youth (p-value is less than .05) using a two-tailed t-test. + The difference between the pre- and during-pandemic values is significantly different from the difference in those values observed among PROMISE control group youth (p-value is less than .05) using a two-tailed t-test. N = sample size; OASDI = Old-Age, Survivors, and Disability Insurance; p.p. = percentage point; SE = standard error; SSA = Social Security Administration; SSI = Supplemental Security Income. Mathematica® Inc. A.82 Technical Appendix | Appendix Table A.54. ASPIRE: Trends in Youth's SSA payments before and during the COVID-19 pandemic- interrupted time series estimates Payment amount ($/SE) Any payment (p.p./SE) SSA payments PROMISE control group (N=960) Pre-pandemic trend 0.22 2.77* -2.86*** -0.00 -0.00*** -0.01*** (0.34) (1.05) (0.79) (0.00) (0.00) (0.00) Change between March and April 1.46 -1.08 0.62 0.00 -0.00 0.00 2020 (3.15) (8.83) (4.94) (0.00) (0.01) (0.01) Difference between during-pandemic 0.36 0.91 2.32¢ 0.00 0.00** 0.00*** trend and pre-pandemic trend (0.58) (1.35) (0.96) (0.00) (0.00) (0.00) PROMISE treatment group (N=968) Pre-pandemic trend 0.26 -3.99** -3.91*** -0.00 -0.01*** -0.01*** (0.40) (1.28) (0.82) (0.00) (0.00) (0.00) Change between March and April -2.21 8.23 5.79 0.00 0.01 0.01 2020 (2.50) (9.62) (5.28) (0.00) (0.01) (0.01) Difference between during-pandemic 0.69 0.84 2.71** 0.00 0.00* 0.00* trend and pre-pandemic trend (0.49) (1.65) (1.03) (0.00) (0.00) (0.00) PROMISE-eligible non-enrollees (N=12,453) Pre-pandemic trend -0.22 -3.08*** -3.16*** -0.00*** -0.00*** -0.01** 0.11) (0.32) (0.21) (0.00) (0.00) (0.00) Change between March and April 3.57**t 4.34 6.20*** 0.00* 0.01** 0.01*** 2020 (1.11) (2.35) (1.29) (0.00) (0.00) (0.00) Difference between during-pandemic 0.28 1.47*** 2.13** 0.00*** 0.00*** 0.00™** trend and pre-pandemic trend (0.18) (0.40) (0.27) (0.00) (0.00) (0.00) Source: SSA administrative records. Note: This table shows interrupted time series estimates of the trends in SSA payments before the onset of the pandemic, the change in the level of the SSA payment outcome at the beginning of the pandemic, and differences in the trends in SSA payment outcomes between the during- and pre-pandemic periods for the treatment group, control group, and non-enrollees. SSA payments before the pandemic represent payments in the 12 months between April 2019 and March 2020; SSA payments during the pandemic represent payments in the 12 months between April 2020 and March 2021. **[*** Estimate is significantly different from zero (p-value is less than .10/.05/.01) using a two-tailed ¢-test. 1 The difference between the pre- and during-pandemic values is significantly different from the difference in those values observed among PROMISE treatment group youth (p-value is less than .05) using a two-tailed t-test. The difference between the pre- and during-pandemic values is significantly different from the difference in those values observed among PROMISE control group youth (p-value is less than .05) using a two-tailed t-test. N = sample size; OASDI = Old-Age, Survivors, and Disability Insurance; p.p. = percentage point; SE = standard error; SSA = Social Security Administration; SSI = Supplemental Security Income. + Mathematica® Inc. A.83 Technical Appendix | Appendix Table A.55. CaPROMISE: Trends in Youth's SSA payments before and during the COVID-19 pandemic- interrupted time series estimates Payment amount ($/SE) Any payment (p.p./SE) SSA payments PROMISE control group (N=1,537) Pre-pandemic trend 0.09 -1.04 -2.34** -0.00 -0.00*** -0.00*** (0.29) (0.97) (0.70) (0.00) (0.00) (0.00) Change between March and April -0.00 -13.47 1.79 0.00 0.00 0.00 2020 (2.21) (7.04) (4.10) (0.00) (0.00) (0.00) Difference between during-pandemic 0.38 0.50 1.521 0.00 0.00** 0.00** trend and pre-pandemic trend (0.40) (1.15) (0.85) (0.00) (0.00) (0.00) PROMISE treatment group (N=1,531) Pre-pandemic trend 0.11 -2.31% -2.10** -0.00 -0.00*** -0.00*** (0.19) (0.92) (0.66) (0.00) (0.00) (0.00) Change between March and April 3.42 4.17 6.24 0.00 0.01 0.01 (2.65) (7.05) (4.13) (0.00) (0.00) (0.00) Difference between during-pandemic -0.08 -1.91 -1.14 0.00 0.00 0.00 trend and pre-pandemic trend (0.40) (1.59) (0.90) (0.00) (0.00) (0.00) PROMISE-eligible non-enrollees (N=18,042) Pre-pandemic trend -0.02 -2.55*** -2.90*** -0.00*** -0.00*** -0.01*** (0.10) (0.26) (0.20) (0.00) (0.00) (0.00) Change between March and April 1.00 -1.15 2.25 0.00*** -0.00 0.00 2020 (0.84) (2.04) (1.23) (0.00) (0.00) (0.00) Difference between during-pandemic -0.14 0.17 0.77**f 0.00*** 0.00*** 0.00*** trend and pre-pandemic trend (0.13) (0.33) (0.25) (0.00) (0.00) (0.00) Source: SSA administrative records. Note: This table shows interrupted time series estimates of the trends in SSA payments before the onset of the pandemic, the change in the level of the SSA payment outcome at the beginning of the pandemic, and differences in the trends in SSA payment outcomes between the during- and pre-pandemic periods for the treatment group, control group, and non-enrollees. SSA payments before the pandemic represent payments in the 12 months between April 2019 and March 2020; SSA payments during the pandemic represent payments in the 12 months between April 2020 and March 2021. > Estimate is significantly different from zero (p-value is less than .10/.05/.01) using a two-tailed t-test. 1 The difference between the pre- and during-pandemic values is significantly different from the difference in those values observed among PROMISE treatment group youth (p-value is less than .05) using a two-tailed f-test. + The difference between the pre- and during-pandemic values is significantly different from the difference in those values observed among PROMISE control group youth (p-value is less than .05) using a two-tailed t-test. N = sample size; OASDI = Old-Age, Survivors, and Disability Insurance; p.p. = percentage point; SE = standard error; SSA = Social Security Administration; SSI = Supplemental Security Income. Mathematica® Inc. A.84 Technical Appendix | Appendix Table A.56. MD PROMISE: Trends in Youth's SSA payments before and during the COVID-19 pandemic- interrupted time series estimates Payment amount ($/SE) Any payment (p.p./SE) SSA payments PROMISE control group (N=918) Pre-pandemic trend -0.19 -3.97* -3.81*** -0.00 -0.01*** -0.01*** (0.28) (0.89) (0.75) (0.00) (0.00) (0.00) Change between March and April -2.88 0.72 3.87 0.00 0.00 0.00 2020 (5.54) (6.57) (4.55) (0.00) (0.01) (0.01) Difference between during-pandemic 1.71 2.31 1.74% 0.00 0.00* 0.00** trend and pre-pandemic trend (1.76) (1.21) (0.90) (0.00) (0.00) (0.00) Pre-pandemic trend 0.40 -5.57** -5.54*** -0.00 -0.01*** -0.01*** (0.73) (0.93) (0.83) (0.00) (0.00) (0.00) Change between March and April -2.89 5.15 7.33 0.01* 0.01 0.01 2020 (4.51) (6.06) (4.90) (0.00) (0.01) (0.01) Difference between during-pandemic 0.42 4.88*** 4,75 0.00* 0.01*** 0.01*** trend and pre-pandemic trend (1.07) (1.30) (1.06) (0.00) (0.00) (0.00) PROMISE-eligible non-enrollees (N=5,563) Pre-pandemic trend -0.57*** -4.29*** -4 .45%* -0.00*** -0.01*** -0.01*** (0.17) (0.38) (0.31) (0.00) (0.00) (0.00) Change between March and April 2.60 210 0.13 0.01*** -0.00 -0.00 2020 (1.33) (3.07) (1.98) (0.00) (0.00) (0.00) Difference between during-pandemic 0.72** 1.94***t 2.75"** 0.00*** 0.00*** 0.00***t+ trend and pre-pandemic trend (0.24) (0.53) (0.39) (0.00) (0.00) (0.00) Source: SSA administrative records. Note: This table shows interrupted time series estimates of the trends in SSA payments before the onset of the pandemic, the change in the level of the SSA payment outcome at the beginning of the pandemic, and differences in the trends in SSA payment outcomes between the during- and pre-pandemic periods for the treatment group, control group, and non-enrollees. SSA payments before the pandemic represent payments in the 12 months between April 2019 and March 2020; SSA payments during the pandemic represent payments in the 12 months between April 2020 and March 2021. * /** /*** Estimate is significantly different from zero (p-value is less than .10/.05/.01) using a two-tailed f-test. 1 The difference between the pre- and during-pandemic values is significantly different from the difference in those values observed among PROMISE treatment group youth (p-value is less than .05) using a two-tailed t-test. + The difference between the pre- and during-pandemic values is significantly different from the difference in those values observed among PROMISE control group youth (p-value is less than .05) using a two-tailed t-test. N = sample size; OASDI = Old-Age, Survivors, and Disability Insurance; p.p. = percentage point; SE = standard error; SSA = Social Security Administration; SSI = Supplemental Security Income. Mathematica® Inc. A.85 Technical Appendix Appendix Table A.57. NYS PROMISE: Trends in Youth's SSA payments before and during the COVID-19 pandemic- interrupted time series estimates Payment amount ($/SE) Any payment (p.p./SE) SSA payments PROMISE control group (N=977) Pre-pandemic trend -0.64* -4.08*** -4.93*** -0.00** -0.01*** -0.01*** (0.32) (0.88) (0.80) (0.00) (0.00) (0.00) Change between March and April 6.26 6.96 5.32 0.01** 0.00 0.01 2020 (3.42) (7.51) (5.00) (0.00) (0.01) (0.01) Difference between during-pandemic 0.40 1.45 3.48** 0.00 0.00*** 0.01*** trend and pre-pandemic trend (0.56) (1.14) (0.94) (0.00) (0.00) (0.00) Pre-pandemic trend 0.08 -5.44*** .5 94*** -0.00** -0.01*** -0.01*** (0.40) (1.09) (0.84) (0.00) (0.00) (0.00) Change between March and April 5.00 -1.73 4.49 0.01*** 0.00 0.00 2020 (5.74) (9.35) (4.94) (0.00) (0.01) (0.01) Difference between during-pandemic -0.95 2.25 3.38** 0.00 0.01*** 0.00** trend and pre-pandemic trend (0.76) (1.43) (1.06) (0.00) (0.00) (0.00) PROMISE-eligible non-enrollees (N=18,009) Pre-pandemic trend -0.44*** -6.21*** 8.37*** -0.00*** -0.01*** -0.01*** (0.11) (0.23) (0.18) (0.00) (0.00) (0.00) Change between March and April 2.76** 9.12%** 7.94%** 0.00***} 0.01*** 0.01*** 2020 (0.98) (1.73) (1.07) (0.00) (0.00) (0.00) Difference between during-pandemic 0.19 3.49*** 4.12%** 0.00*** 0.01*** 0.01*** trend and pre-pandemic trend (0.15) (0.30) (0.22) (0.00) (0.00) (0.00) Source: SSA administrative records. Note: This table shows interrupted time series estimates of the trends in SSA payments before the onset of the pandemic, the change in the level of the SSA payment outcome at the beginning of the pandemic, and differences in the trends in SSA payment outcomes between the during- and pre-pandemic periods for the treatment group, control group, and non-enrollees. SSA payments before the pandemic represent payments in the 12 months between April 2019 and March 2020; SSA payments during the pandemic represent payments in the 12 months between April 2020 and March 2021. **[*** Estimate is significantly different from zero (p-value is less than .10/.05/.01) using a two-tailed i-test. 1 The difference between the pre- and during-pandemic values is significantly different from the difference in those values observed among PROMISE treatment group youth (p-value is less than .05) using a two-tailed t-test. The difference between the pre- and during-pandemic values is significantly different from the difference in those values observed among PROMISE control group youth (p-value is less than .05) using a two-tailed t-test. N = sample size; OASDI = Old-Age, Survivors, and Disability Insurance; p.p. = percentage point; SE = standard error; SSA = Social Security Administration; SSI = Supplemental Security Income. + Mathematica® Inc. A.86 Technical Appendix | Appendix Table A.58. WI PROMISE: Trends in Youth's SSA payments before and during the COVID-19 pandemic- interrupted time series estimates Payment amount ($/SE) Any payment (p.p./SE) SSA payments PROMISE control group (N=937) Pre-pandemic trend 0.46 -4.82** -4.31%* -0.00* -0.01*** -0.01*** (0.30) (1.01) (0.80) (0.00) (0.00) (0.00) Change between March and April 1.07 1.80 5.88 0.00 0.00 0.00 2020 (2.76) (7.76) (5.67) (0.00) (0.01) (0.01) Difference between during-pandemic -0.39 1.27 1.56 0.00 0.00* 0.00 trend and pre-pandemic trend (0.53) (1.27) (1.07) (0.00) (0.00) (0.00) PROMISE treatment group (N=940) Pre-pandemic trend 0.30 -4.23** -4.69*** -0.00 -0.01*** -0.01*** (0.46) (1.02) (0.85) (0.00) (0.00) (0.00) Change between March and April 0.92 1.08 8.34 0.00 0.00 0.00 2020 (3.91) (7.41) (5.28) (0.00) (0.01) (0.01) Difference between during-pandemic 0.36 1.13 2.55* 0.00 0.00** 0.01*** trend and pre-pandemic trend (0.79) (1.30) (1.06) (0.00) (0.00) (0.00) PROMISE-eligible non-enrollees (N=7,015) Pre-pandemic trend 0.11 -5.32*** -4.96*** -0.00*** -0.01*** -0.01** (0.14) (0.40) (0.30) (0.00) (0.00) (0.00) Change between March and April 2.83* 5.81* 7.94*** 0.00** 0.00 0.00 2020 (1.29) (2.81) (1.76) (0.00) (0.00) (0.00) Difference between during-pandemic -0.04 3.55%** 3.70%** 0.00*** 0.01*** 0.01*** trend and pre-pandemic trend (0.23) (0.51) (0.37) (0.00) (0.00) (0.00) Source: SSA administrative records. Note: This table shows interrupted time series estimates of the trends in SSA payments before the onset of the pandemic, the change in the level of the SSA payment outcome at the beginning of the pandemic, and differences in the trends in SSA payment outcomes between the during- and pre-pandemic periods for the treatment group, control group, and non-enrollees. SSA payments before the pandemic represent payments in the 12 months between April 2019 and March 2020; SSA payments during the pandemic represent payments in the 12 months between April 2020 and March 2021. * /** /*** Estimate is significantly different from zero (p-value is less than .10/.05/.01) using a two-tailed f-test. 1 The difference between the pre- and during-pandemic values is significantly different from the difference in those values observed among PROMISE treatment group youth (p-value is less than .05) using a two-tailed t-test. + The difference between the pre- and during-pandemic values is significantly different from the difference in those values observed among PROMISE control group youth (p-value is less than .05) using a two-tailed t-test. N = sample size; OASDI = Old-Age, Survivors, and Disability Insurance; p.p. = percentage point; SE = standard error; SSA = Social Security Administration; SSI = Supplemental Security Income. Mathematica® Inc. 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'asuodsaiuou AsAins Joj Jsnipe 0} sonsne)s pajybiam app "dnoib [o5uod ay) Joj Ueaw paAlasqo sy} 0} ajewnise joedw sy} Buippe Aq peje|nojes aq ueo dnoub Juswiesl} ay) Joj uealw psjsnipe ay] -oiwapued ay) Buunp AsAins sy 0) pepuodsal oym YinoA xipuaddy [eoluys9a] This page has been left blank for double-sided copying. Mathematica Inc. Princeton, NJ » Ann Arbor, MI « Cambridge, MA " Mathematica. Chicago, IL Oakland, CA- Seattle, WA w Progress Together Woodlawn, MD * Washington, DC mathematica.org EDI Global, a Mathematica Company Operating in Tanzania, Uganda, Kenya, and the United Kingdom Mathematica, Progress Together, and the "spotlight M" logo are registered trademarks of Mathematica Inc.