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FOIA Number: 2016-0531-F FOIA MARKER This is not a textual record. This is used as an administrative marker by the William J. Clinton Presidential Library Staff. Collection/Record Group: Clinton Presidential Records Subgroup/Office of Origin: Council of Economic Advisers Series/Staff Member: Vivian Wu Subseries: OA/ID Number: 21177 FolderID: Folder Title: [Minimum Wage Working Paper] Stack: Row: Section: Shelf: Position: S 21 3 8 2 OCOM 1 001 03/03/00 12:28 FAX 202 606 7797 LABOR Bureau of Labor Statistics BUREAU RS OF STATISTICS Office of the Commissioner Facsimile Cover Sheet Room 4040, Postal Square Building 2 Massachusetts Avenue, NE Washington, DC 20212 To: Michael Brien Organization: C.E.A. Phone: 395-6982 Fax: 395-6853 From: William Parks Title: Special Asst. to the Commissioner Office Phone: 202 691-7807 Office Fax: 202 691-7797 Date: 3/3/00 Pages including this 14 cover page: COMMENTS: Per Lisa Stuart's request, here are tables showing the smallest wage intervals we have for hourly paid workers. We don't have a tabulation like this for 1996 as a whole, but we do have it for the 3ʳᵈ and 4th quarters of that year, which I think would be relevant. In addition to those tables, I'm faxing the same for the 2nd and 4th quarters of 1997. 002 Table 18. Distribution of wage and salary workers paid hourly rates, third quarter 1996 averages (Numbers in thousands) Total HOURLY RATE Total 70,956 Under $3.35 1,029 Under $2.50 637 $2.13 151 $2.14 $2.49 196 $2.50 $2.99 186 $3.00 $3.34 206 $3.00 $3.04 149 $3.10 $3.19 19 $3.20 $3.29 31 $3.30 $3.34 7 $3.35 9 $3.36 - $3.49 17 $3.40 - $3.44 9 $3.45 $3.49 8 $3.50 - $3.79 72 OCOM $3.50 $3.54 23 $3.55 $3.59 5 $3.60 $3.64 9 $3.65 $3.69 12 $3.75 $3.79 22 $3.81 $3.99 4 $3.85 $3.89 4 $4.00 387 $4.01 - $4.24 18 $4.10 $4.14 5 $4.15 $4.19 6 $4.20 $4.24 7 03/03/00 12:28 FAX 202 606 7797 $4.25 1,906 $4.26 - $4.49 497 $4.26 $4.29 2 $4.30 $4.34 27 $4.35 $4.39 350 $4.40 $4.44 53 $4.45 $4.49 65 003 Table 18. Distribution of wage and salary workers paid hourly rates, third quarter 1996 averages (Numbers in thousands) - Continued Total HOURLY RATE $4.50 - $4.99 2,241 $4.50 - $4.54 988 $4.55 - $4.59 73 $4.60 - $4.64 85 $4.65 - $4.69 181 $4.70 - $4.74 51 $4.75 606 $4.76 - $4.79 9 $4.80 - $4.84 70 $4.85 - $4.89 56 $4.90 - $4.94 61 $4.95 - $4.99 61 $5.00 - $5.49 5,940 $5.00 4,033 $5.05 - $5.09 144 OCOM $5.10 - $5.14 106 $5.15 108 $5.16 - $5.19 8 $5.20 - $5.24 70 $5.25 - $5.29 1,000 $5.30 - $5.34 105 $5.35 - $5.39 160 $5.40 - $5.44 97 $5.45 - $5.49 109 $5.50 - $5.99 2,970 $5.50 - $5.74 2,200 $5.75 - $5.99 770 03/03/00 12:28 FAX 202 606 7797 $6.00 - $6.49 5,313 $6.00 3,852 $6.01 - $6.04 20 $6.05 - $6.09 63 $6.10 - $6.14 98 $6.15 56 $6.16 - $6.19 33 $6.20 - $6.24 108 004 Table 18. Distribution of wage and salary workers paid hourly rates, third quarter 1996 averages (Numbers in thousands) - Continued Total HOURLY RATE $6.25 - $6.29 666 $6.30 - $6.34 87 $6.35 - $6.39 135 $6.40 - $6.44 111 $6.45 - $6.49 83 $6.50 - $6.99 2,836 $6.50 - $6.74 2,155 $6.75 - $6.99 681 $7.00 - $7.99 7,138 $8.00 - $8.99 7,021 $9.00 - $9.99 5,256 $10.00 or more 28,301 OCOM 03/03/00 12:28 FAX 202 606 7797 005 Table 18. Distribution of wage and salary workers paid hourly rates, fourth quarter 1996 averages (Numbers In thousands) Total HOURLY RATE Total 70,431 Under $3.35 960 Under $2.50 628 $2.13 172 $2.14 - $2.49 175 $2.50- $2.99 222 $3.00 $3.34 110 $3.00 $3.04 92 $3.05 $3.09 1 $3.10 $3.19 10 $3.20 - $3.29 6 $3.35 9 $3.36 - $3.49 3 $3.45 - $3.49 3 $3.50 - $3.79 100 $3.50 $3.54 63 $3.60 $3.64 7 $3.65 $3.69 3 27 OCOM $3.75 - $3.79 $3.80 7 $3.81 $3.99 3 $3.90 $3.94 3 $4.00 272 $4.01- $4.24 28 $4.05 $4.09 2 $4.10 $4.14 11 $4.15- $4.19 6 $4.20 - $4.24 9 $4.25 643 $4.26- $4.49 215 03/03/00 12:29 FAX 202 606 7797 $4.30 $4.34 17 $4.35 - $4.39 164 $4.40 - $4.44 16 $4.45 - $4.49 18 $4.50 - $4.99 3,140 $4.50 - $4.54 532 $4.55 - $4.59 43 $4.60 - $4.64 36 $4.65 - $4.69 148 See footnotes at end of table. Table 18. Distribution of wage and salary workers paid hourly rates, fourth quarter 006 1996 averages (Numbers in thousands) - Continued Total HOURLY RATE $4.70 $4.74 43 $4.75 1,976 $4.76 $4.79 24 $4.80 $4.84 105 $4.85 $4.89 86 $4.90 $4.94 114 $4.95 - $4.99 33 $5.00- $5.49 5,943 $5.00 4,063 $5.01 $5.04 2 $5.05 $5.09 100 $5.10 $5.14 95 $5.15 129 $5.16 $5.19 12 $5.20 $5.24 111 $5.25 $5.29 993 $5.30 $5.34 119 $5.35 - $5.39 129 $5.40 $5.44 107 $5.45 $5.49 82 OCOM $5.50 - $5.99 2,901 $5.50 - $5.74 2,014 $5.75 - $5.99 886 $6.00- $6.49 4,940 $6.00 3,620 $6.01 $6.04 36 $6.05 $6.09 41 $6.10 $6.14 71 $6.15 66 $6.16 $6.19 30 $6.20 $6.24 92 03/03/00 12:29 FAX 202 606 7797 $6.25 $6.29 628 $6.30 $6.34 95 $6.35 $6.39 94 $6.40 $6.44 104 $6.45 - $6.49 64 $6.50 - $6.99 2,954 $6.50 - $6.74 2,044 $6.75 - $6.99 910 See footnotes at end of table. Table 18. Distribution of wage and salary workers paid hourly rates, fourth quarter 007 1996 averages 5. (Numbers In thousands) - Continued Total HOURLY RATE $7.00 $7.99 7,569 $8.00 $8.99 6,674 $9.00 $9.99 5,236 $10.00 or more 28,835 NOTE: Data exclude the incorporated self usually worked. These data will not sum to employed. Detail for the above race and totals because full or part-time status on the Hispanic-origin groups will not sum to totals principal job Is not Identifiable for a small because data for the "other races' group are number of multiple Jobholders. not are not presented and Hispanics are SOURCE: U.S. Department of Labor, Included in both the white and black population Bureau of Labor Statistics, unpublished groups. Also note that the distinction between tabulations from the Current Population Survey, full and part-time workers Is based on hours 1996. OCOM 03/03/00 12:29 FAX 202 606 7797 Table 18. Distribution of wage and salary workers paid hourly rates, second 008 quarter 1997 averages, not seasonally adjusted (Numbers In thousands) Total HOURLY RATE Total 70,536 Under $3.35 847 Under $2.50 534 $2.13 180 $2.14 $2.49 171 $2.50 $2.99 165 $3.00 $3.34 147 $3.00 $3.04 127 $3.05 $3.09 1 $3.10 $3.19 1 $3.20 $3.29 15 $3.30 $3.34 4 $3.35 11 $3.36 $3.49 3 $3.45 $3.49 3 $3.50 $3.79 99 $3.50 $3.54 63 $3.55 $3.59 4 $3.65 $3.69 5 OCOM $3.75 $3.79 27 $3.80 4 $3.81 $3.99 6 $3.61 3.84 5 $3.85 $3.89 1 $4.00 199 $4.01 $4.24 18 $4.10 $4.14 9 $4.15 $4.19 3 $4.20 $4.24 6 $4.25 418 03/03/00 12:29 FAX 202 606 7797 $4.26 $4.49 149 $4.30 $4.34 4 $4.35 $4.39 119 $4.40 $4.44 10 $4.45 $4.49 15 $4.50 $4.99 2,350 $4.50 $4.54 371 $4.55 $4.59 55 $4.60 $4.64 27 See footnotes at end of table. 009 Table 18. Distribution of wage and salary workers paid hourly rates, second quarter 1997 averages, not seasonally adjusted (Numbers In thousands) - Continued Total HOURLY RATE $4.65 $4.69 69 $4.70 $4.74 21 $4.75 1,499 $4.76 $4.79 6 $4.80 $4.84 35 $4.85 $4.89 124 $4.90 $4.94 86 $4.95 $4.99 57 $5.00 $5.49 6,535 $5.00 4,436 $5.01 $5.04 4 $5.05 $5.09 129 $5.10 $5.14 69 $5.15 171 $5.16 $5.19 32 $5.20 $5.24 100 $5.25 $5.29 1,167 $5.30 $5.34 116 OCOM $5.35 $5.39 152 $5.40 $5.44 74 $5.45 $5.49 86 $5.50 $5.99 2,938 $5.50 $5.74 2,050 $5.75 $5.99 888 $6.00 $6.49 5,542 $6.00 4,021 $6.01 $6.04 9 $6.05 $6.09 30 $6.10 $6.14 71 $6.15 92 03/03/00 12:30 FAX 202 606 7797 $6.16 $6.19 12 $6.20 $6.24 91 $6.25 $6.29 696 $6.30 $6.34 125 $6.35 $6.39 128 $6.40 $6.44 160 $6.45 $6.49 108 $6.50 $6.99 2,720 $6.50 $6.74 1,995 See footnotes at end of table. Table 18. Distribution of wage and salary workers paid hourly rates, second 010 quarter 1997 averages, not seasonally adjusted (Numbers in thousands) - Continued Total HOURLY RATE $6.75 $6.99 725 $7.00 $7.99 7,466 $8.00 $8.99 6,692 $9.00 $9.99 4,853 $10.00 or more 29,687 SOURCE: U.S. Department of Labor, not are not presented and Hispanics are Bureau of Labor Statistics, unpublished Included In both the white and black population tabulations from the Current Population Survey, groups. Also note that the distinction between 1997. full and part-time workers Is based on hours NOTE: Data exclude the Incorporated self usually worked. These data will not sum to employed. Detail for the above race and totals because full or part-time status on the Hispanic-origin groups will not sum to totals principal job is not Identifiable for a small because data for the "other races" group are number of multiple Jobholders. OCOM 03/03/00 12:30 FAX 202 606 7797 Table 18. Distribution of wage and salary workers paid hourly rates, fourth quarter 011 1997 averages, not seasonally adjusted (Numbers In thousands) Total HOURLY RATE Total 71,081 Under $3.35 842 Under $2.50 547 $2.13 158 $2.14-$2.49 157 $2.50 . $2.99 147 $3.00 - $3.34 148 $3.00 - $3.04 88 $3.05 . $3.09 15 $3.10-$3.19 15 $3.20 . $3.29 29 $3.35 3 $3.36 - $3.49 4 $3.36 . $3.39 4 $3.40 $3.44 1 $3.50-$3.79 48 $3.50 $3.54 36 $3.65 . $3.69 3 $3.75 . $3.79 10 OCOM $3.80 >0 $3.81 - $3.99 3 $3.85 . $3.89 2 $3.95 . $3.99 1 $4.00 146 $4.01 - $4.24 24 $4.05 . $4.09 1 $4.15 $4.19 9 $4.20 - $4.24 15 $4.25 145 $4.26 - $4.49 45 $4.30-$4.34 4 03/03/00 12:30 FAX 202 606 7797 $4.35 - $4.38 33 $4.40-$4.44 7 $4.45 - $4.49 3 $4.50 $4.99 547 $4.50 $4.54 148 $4.55 $4.59 38 $4.60 $4.64 13 $4.65 - $4.69 36 See footnotes at end of table. Table 18. Distribution of wage and salary workers paid hourly rates, fourth quarter 012 1997 averages, not seasonally adjusted (Numbers In thousands) - Continued Total HOURLY RATE $4.70 - $4.74 5 $4.75 233 $4.80 - $4.64 21 $4.85 $4.89 17 $4.90 $4.94 29 $4.95 $4.99 8 $5.00 $5.49 6,728 $5.00 2,251 $5.05 - $5.09 25 $5.10 - $5.14 38 $5.15 2,115 $5.16 - $5.19 18 $5.20 - $5.24 87 $5.25 - $5.29 1,455 $5.30 - $5.34 131 $5.35 - $5.39 216 $5.40 - $5.44 227 $5.45 - $5.49 166 $5.50 - $5.99 3,248 OCOM $5.50-$5.74 2,273 $5.50 1,897 $5.51 - $5.54 34 $5.55 - $5.59 59 $5.60 - $5.64 120 $5.65 - $5.69 112 $5.70 - $5.74 50 $5.75 - $5.99 975 $5.75 610 $5.76 - $5.79 . 27 $5.80 - $5.84 81 109 03/03/00 12:31 FAX 202 606 7797 $5.85 . $5.89 $5.90 - $5.94 78 $5.95 . $5.99 70 $6.00 . $6.49 5,665 $6.00 4,176 $6.01 . $6.04 28 $6.05 . $6.09 41 $6.10 . $6.14 89 $6.15 69 See footnotes at end of table. 013 Table 18. Distribution of wage and salary workers paid hourly rates, fourth quarter 1997 averages, not seasonally adjusted (Numbers In thousands) - Continued Total HOURLY RATE $6.16-$6.19 36 $6.20-$6.24 80 $6.25 $6.29 678 $6.30 - $6.34 88 $6.35 $6.39 121 $6.40 - $6.44 194 $8.45 . $6.49 65 $6.50 - $8.99 2,970 $6.50 $6.74 2,218 $6.50 1,773 $6.51 - $8.54 32 $6.55 - $6.59 113 $6.60 $8.64 111 $6.65 $6.69 126 $6.70-$6.74 62 $6.75 - $6.99 752 $6.75 458 OCOM $6.76 - $6.79 35 $6.80 - $6.84 74 $6.85 $6.89 84 $6.90 - $6.94 38 $6.95 $6.99 63 $7.00 - $7.99 7,794 $7.00 - $7.49 5,085 $7.00 3,633 $7.01 $7.04 76 $7.05 - $7.09 43 $7.10 $7.14 90 $7.15 40 03/03/00 12:31 FAX 202 606 7797 $7.16 . $7.19 40 $7.20-$7.24 179 $7.25 - $7.29 515 $7.30 - $7.34 113 $7.35-$7.39 96 $7.40-$7.44 129 $7.45 $7.49 130 $7.50 $7.99 2,709 $7.50-$7.74 1,998 $7.50 1,552 See footnotes at end of table. Table 18. Distribution of wage and salary workers paid hourly rates, fourth quarter 014 1997 averages, not seasonally adjusted (Numbers In thousands) - Continued Total HOURLY RATE $7.51 $7.54 23 $7.55 $7.59 101 $7.60 $7.64 106 $7.65 $7.69 98 $7.70 . $7.74 117 $7.75 $7.99 711 $7.75 209 $7.76 - $7.79 41 $7.80 . $7.84 144 $7.85 $7.89 88 $7.90 - $7.94 127 $7.95 . $7.99 102 $8.00 $8.99 7,235 $9.00 - $9.99 5,343 $10.00 or more 30,289 >0 Value too small to display. not are not presented and Hispanics are SOURCE: U.S. Department of Labor, Included In both the white and black population OCOM Bureau of Labor Statistics, unpublished groups. Also note that the distinction between tabulations from the Current Population Survey, full and part-time workers is based on hours 1997. usually worked. These data will not sum to NOTE: Data exclude the Incorporated self totals because full or part-time status on the employed. Detail for the above race and principal job is not Identifiable for a small Hispanic-origin groups will not sum to totals number of multiple Jobholders. because data for the "other races" group are 03/03/00 12:31 FAX 202 606 7797 Stuart Lisa <[email protected]> 03/07/2000 02:07:34 PM Record Type: Record To: Michael J. Brien/CEA/EOP CC: Subject: MW -- coverage From: Alan Moss[SMTP:[email protected]] Sent: Tuesday, March 07, 2000 1:58 PM To: 'Stuart Lisa'; Moss Alan-ESA Cc: Bingham Barbara Subject: RE: \asp\MINWAG98\C3.WPD These numbers check out with our publication -- data for 1996. Original Message From: Stuart Lisa [SMTP:[email protected]] Sent: Tuesday, March 07, 2000 1:23 PM To: Moss Alan-ESA Cc: Bingham Barbara Subject:FW: \asp\MINWAG98\C3.WPD Importance: High Since you couldn't open it, I've pasted the Q&A below. From: Bingham Barbara Sent: Tuesday, March 07, 2000 12:05 PM To: Stuart, Lisa; Brennan, Richard; Moss, Alan Subject: O:\asp\MINWAG98\C3.WPD Importance: High <<C3.WPD>> O:\asp\MINWAG98\C3.WPD Lisa -- this is the info we have on coverage. Alan could tell you if it needs to be updated. BB C3. WORKERS NOT COVERED (4/14/99) Question: What proportion of the workforce is not covered by the minimum wage? Answer: P Approximately 35 percentFrom Barbara's Data sheets (total # not subject to FLSA's minimum wage requirements)/ total # in civilian workforce = 42,937/ 122,359 = 35.09% KNB, June 16, 1998, 3:18:36 PM of wage and salary workers are not covered by or not subject to the FLSA's minimum wage requirements. P If you exclude executive, administrative, professional or outside sales persons from the total, the percentage of wage and salary workers not covered by or subject to the FLSA's minimum wage requirements is approximately 11 percentFrom Barbara's data sheets (Total # in civilian workforce not subject to FLSA's MW - total # of executive, administrative, professional, or outside salespersons) / (Total # in workforce - total # of executive, administrative, professional, or outside salespersons) = (42,937 - 31,729 - 1,804)/ (122,359 - 31,729 - 1804) = 10.6% KNB, June 16, 1998, 3:25:23 PM. (Most exempt executive, administrative, professional or outside sales persons earn well over the minimum wage.) « File: C3.WPD » Percentage of workers paid hourly rates earning between $5.15 and $6.14 per hour, by State (U.S. percentage = 14.0 percent) 1999 annual averages Mountain West New England North Central WASH. East North Central MAINE MONT. N.D. Middle VT. ORE. MINN. 1 Atlantic N.H. MASS. IDAHO WIS. MICH. S.D. N.Y. R.I. WYO CONN. - -IOWA PA. NEB. OHIO N.J. NEV. ILL. IND. MD. CALIF UTAH DEL. COLO. KAN. MO. W.VA. I I KY. VA. D.C. TENN. ARIZ. N.C. N.M. OKLA. , ARK. S.C. South Atlantic Pacific MISS. ALA. III GA. TEX LA. 20.0% or over FLA. 15.0% 19.9% ALASKA East 10.0% 14.9% HAWAII South Central 5.0% 9.9% West 4.9% or below South Central Source: Bureau of Labor Statistics Percentage of workers paid hourly rates earning between $5.15 and $6.14 per hour, by State (U.S. percentage = 14.0 percent) 1999 annual averages Mountain West New England North Central WASH. East North Central MAINE MONT. N.D. Middle 1 VT. ORE. MINN. Atlantic N.H. MASS. IDAHO WIS. MICH. S.D. N.Y. R.I. WYO. CONN. - IOWA PA. NEB. OHIO N.J. NEV. ILL. IND. MD. CALIF UTAH DEL. COLO. KAN. MO. W.VA. I I KY. VA. D.C. TENN. ARIZ. N.C. N.M. OKLA. , ARK. S.C. South Atlantic MISS. ALA. Pacific GA. TEX LA. 20.0% or over FLA. 15.0% 19.9% ALASKA East 10.0% 14.9% HAWAII South Central 5.0% 9.9% West 4.9% or below South Central Source: Bureau of Labor Statistics Office of the Chief Economist Room S2514 US Department of Labor 200 Constitution Avenue, NW Washington, DC 20210 202-693-6004 Fax To: Michael Brien From: Lisa B. Stuart Fax: 395-6853 Pages: 19 including cover Phone: 395-6982 Date: 03/02/00 Re: Old MW tables CC: Urgent For Review Please Comment Please Reply Please Recycle Comments: Mike, I found an odd selection: 1995, 4th quarter 97, 2nd quarter 98, 4th quarter 98 and 1998. I know there was also a 2nd quarter 97 but I can't put my figures on it. (I've left a message for a colleague to see if she can find that and 1996.) And you already have the 1999. I hope these help. P.01 MAR-02-00 THU 20:29 Table A-35. Distribution of wage and salary workere paid hourly rates, annual averages 1998 (Numbers In thousands) MAR-02-00 THU 20:30 Total HOURLY RATE Total 71,440 Under $3.35 856 Under $2.50 539 $2.13 148 $2.14 $2.49 143 $2.50 $2.00 169 $3.00 $3.34 149 $3.00 $3.04 94 $3.05 $3.00 19 $3.10-$3.19 14 $3.20 $3.29 21 $3.30 $3.34 2 $3.35 4 $3.36-$3.49 5 $3.40-$3.44 I $3.45-$3.49 4 $3.50 83.79 49 $3.50 $3.54 33 $3.55 $3.59 1 $3.65 - $3.69 2 83.75 $3.79 13 $3.80 1 $3.61-$3.99 3 $3.65 $3.89 2 $3.95 $3.99 1 $4.00 111 $4.01-$4.24 7 $4,06-$4.09 >0 $4.10-$4.14 >0 $4,15-$4.19 4 $4.20-$4.24 2 $4.25 68 $4.26 $4.49 50 $4.26-$4.29 1 $4,30-$4.34 6 $4.35-$4.38 34 $4.40-$4.44 7 $4.45 $4.49 3 $4.50 $4.99 234 $4.60 $4.64 78 $4,55-$4.59 B $4.60-$4.64 3 $4.65-$4.69 14 See footnoles et and of table. P.02 Table A-35. Distribution of wage and calary workers paid hourly rates, annual averages 1998 (Numbers In thousands)- Continued MAR-02-00 THU 20:30 Total HOURLY RATE $4.70- $4.74 0 $4.75 106 $4.76 $4.79 3 $4.80 $4.84 1 $4.85 $4.00 7 $4.90 $4.94 5 $4.95 $4.99 2 $5.00- $5.49 5,191 $5.00 1,398 $5.05 $6.09 12 $5.10 $5.14 18 $5.15 1,693 $5.16 $5.19 10 $5.20 $5.24 46 $5.26 $5.29 1,381 $5.30 $6.34 129 $5.35 $5.39 329 $5.40 $5.44 188 $5.45 $5.49 108 $5.50- $5.99 3,481 $5.50. $5.74 2,039 $5.50 1,604 $6.51 $5.54 17 $5.55 $5.69 62 $5.60- $5.64 131 $5.65- $5.69 158 $5.70- $5.74 67 $5.75 $5.99 1,441 $5.76 1,098 $5.76 $5.79 19 $5.80 $5.64 88 $5.85 $5.69 97 $5.90. $5.94 87 $5.95- $5.99 62 $8.00 $6.49 5,627 $6.00 4,031 $6.01 $6.04 26 $6.05. $6.09 53 $8.10. $8.14 91 $8.16 118 $8.16. $6.19 46 $6.20 $6.24 100 $6.25 $8.29 728 See footnotes at end of fable. P.03 03 Table A-35. Distribution of wage and salary workers paid hourly rates, annual averages 1998 (Numbers In thousands) - Continued MAR-02-00 THU 20:30 Total HOURLY RATE $8.30 $6.34 107 $6.35 $8.39 110 $8.40 $6.44 138 $6.45 $8.49 85 $8.50 $5.99 2,925 $8.60 $6.74 2,127 $6.60 1,509 $6.51 $6.64 28 $6.65 $6.59 59 $8.60 $6.64 66 $8.65 $8.69 59 $8.70 $8.74 86 $6.75 $6.99 798 $6.75 442 $8.76 $6.79 33 $6.60 $6.84 107 $6.85 $6.89 70 $8.90 $6.94 85 $8.96 $6.99 61 $7.00 $7.99 7,769 $7.00 $7.49 5,116 $7.00 3,715 $7.01 $7.04 18 $7.05 $7.09 68 $7.10 $7.14 91 $7.15 79 $7.16-$7.19 41 $7.20-$7.24 119 $7.25-$7.29 522 $7.30-$7.34 118 $7.35-$7.39 107 $7.40-$7.44 118 $7.45-$7.49 121 $7.60 $7.99 2,653 $7.50 $7.74 1,984 $7.50 1,580 $7.51 $7.54 23 $7.55 $7.59 95 $7.60 $7.64 114 $7.65 $7.69 88 $7.70 $7.74 84 $7.75 $7.99 669 $7.76 258 See footnotes at end of table. P.04 Table A-35. Distribution of wage and salary workers paid hourly rates, annual averages 1998 (Numbers In thousands)- Continued MAR-02-00 THU 20:31 Total HOURLY RATE $7.76 $7.79 38 $7.80 $7.84 128 $7.85 $7.69 98 $7.90 $7.94 91 $7.95 $7.99 56 $8.00 $0.99 7,193 $0.00 $9.99 5,603 $10.00 or more 32,243 >0 Value too small to and part-time workers is display. based on hours usually NOTE: Date worked, These data will exclude the not sum to totals incorporated self because full or part-time employed. Detail for the status on the principal above race and job is not Identifiable for Hispanic-origin groups a small number of will not sum to totals multiple jobholders. because date for the SOURCE: U.S. "other races' group are Department of Labor, not presented and Bureau of Labor Hispanice are included Statistics, unpublished in both the white and tabulations from the black population groups, Current Population Also note that the Survey, 1996. distinction between full P. 05 Table 18. Distribution of wage and salary workers paid hourly rates, fourth quarter 1998 averages, not seasonally adjusted (Numbers In thousands) MAR-02-00 THU 20:31 Total HOURLY RATE Total 71,436 Under $3.35 894 Under $2.50 575 $2.13 170 $2.14 $2.49 159 $2.60 $2.99 193 $3.00 $3.34 127 $3.00 $3.04 78 $3.05 $3.09 13 $3.10-$3.19 9 $3.20 $3.29 24 $3.30 $3.34 3 $3.35 6 $3.36 $3.49 8 $3.40 $3.44 1 $3.45 $3.49 7 $3.50 $3.79 37 $3.50 $3.54 25 $3.75 $3.79 12 $3.80 4 $4.00 59 $4.01 $4.24 12 $4.05 $4.09 1 $4.15 $4.19 3 $4.20 $4.24 9 $4.25 67 $4.26 $4.49 37 $4.26 $4.29 4 $4.30 $4.34 11 $4.35 $4.39 14 $4.40 $4.44 9 $4.50 $4.99 236 $4.50 $4.54 92 $4.55 $4.59 5 $4.60 $4.64 7 $4.65 $4.69 20 $4.70 $4.74 10 $4.75 86 $4.80 $4.84 5 P.06 See footnoles at end of table. Table 18. Distribution of wage and salary workers paid hourly rates, fourth quarter 1998 averages, not seasonally adjusted (Numbers In thousands) - Continued MAR-02-00 THU 20:32 Total HOURLY RATE $4.85 $4.89 4 $4.90 $4.94 8 $4.95 $4.99 3 $5.00 $5.49 4,435 $5.00 1,138 $5.05 $5.09 5 $5.10 $5.14 21 $5.15 1,203 $5.16 $5.19 6 $5.20 $5.24 18 $5.25 $5.29 1,337 $5.30 $5.34 172 $5.35 $5.39 267 $5.40 $5.44 159 $5.45 $5.49 108 $5.50 $5.99 3,283 $5.50 $5.74 1,881 $5.50 1,456 $5.51 $5.54 21 $5.55 $5.59 73 $5.60 $5.64 151 $5.65 $6.69 118 $5.70 $5.74 63 $5.75 $5.99 1,403 $5.75 1,045 $5.76 $5.79 19 $5.80 $5.84 81 $5.85 $5.89 108 $5.90 $5.94 105 $5.95 $5.99 45 $6.00 6.99 8,379 $6.00 $6.49 5,438 $6.00 3,841 $6.01 $6.04 4 $6.05 $6.09 44 $6.10 $6.14 84 $6.15 107 $6.16 $6.19 47 $6.20 $6.24 73 P.07 See footnotes at end of lable. Table 18. Distribution of wage and salary workers paid hourly rates, fourth quarter 1998 averages, not seasonally adjusted (Numbers in thousands) - Continued MAR-02-00 THU 20:32 Total HOURLY RATE $6.25 $6.29 761 $6.30 $6.34 140 $6.35 $6.39 155 $6.40 $6.44 136 $6.45 $6.49 45 $6.50 $6.99 2,941 $6.50 $6.74 2,099 $6.50 1,746 $6.51 $6.54 16 $6.55 $6.59 62 $6.60 $6.64 126 $6.65 $6.69 69 $6.70 $6.74 79 $6.75 $6.99 842 $6.75 485 $6.76 $6.79 36 $6.80 $6.84 118 $6.85 $6.89 78 $6.90 $6.94 60 $6.95 $6.99 64 $7.00 $7.99 7,793 $7.00 $7.49 5,149 $7.00 3,743 $7.01 $7.04 22 $7.05 $7.09 59 $7.10 $7.14 97 $7.15 57 $7.16 $7.19 36 $7.20 $7.24 120 $7.25 $7.29 570 $7.30 $7.34 142 $7.35 $7.39 110 $7.40 $7.44 78 $7.45 $7.49 117 $7.50 $7.99 2,644 $7.50 $7.74 1,954 $7.50 1,561 $7.51 $7.54 28 $7.55 $7.59 109 P.08 P. See foolnotes at end of table. Table 18. Distribution of wage and salary workers paid hourly rates, fourth quarter 1998 averages, not seasonally adjusted (Numbers In thousands) - Continued MAR-02-00 THU 20:32 Total HOURLY RATE $7.60 $7.64 89 $7.65 $7.69 89 $7.70 $7.74 78 $7.75 $7.99 690 $7.75 279 $7.76 $7.79 45 $7.80 $7.84 124 $7.85 $7.89 107 $7.90 $7.94 82 $7.95 $7.99 54 $8.00 $8.99 7,485 $9.00 $9.99 5,575 $10.00 or more 33,125 SOURCE: U.S. Department of Labor, not presented and Hispanics are Included In Bureau of Labor Statistics, unpublished both the white and black population groups. labulations from the Current Population Survey, Also note that the distinction between full and 1998. part-time workers Is based on hours usually NOTE: Data exclude the incorporated sell worked. These data will not sum to totals employed. Detail for the above race and because full or part-time status on the principal Hispanic-orlgin groups will not sum to totals job is not identifiable for a small number of because dala for the 'other races' group are multiple jobholders. P.09 P. 09 Table 18. Distribution of wage and salary workers paid hourly rates, second quarter 1998 averages, not seasonally adjusted (Numbers in thousands) Total MAR-02-00 THU 20:33 : HOURLY RATE Total 71,348 Under $3.35 875 Under $2.50 551 $2.13 137 I $2.14 $2.49 126 $2.50 $2.99 123 $3.00 $3.34 201 $3.00 $3.04 126 $3.05 $3.09 23 $3.10 $3.19 18 $3.20 $3.29 33 $3.35 4 $3.36 $3.49 1 $3.45 $3.49 1 $3.50 $3.79 63 $3.50 $3.54 38 $3.65 $3.69 6 $3.75 $3.79 19 $3.81 $3.99 1 $3.95 $3.99 1 $4.00 110 $4.01 $4.24 1 $4.10 $4.14 1 $4.25 119 $4.26 $4.49 65 $4.30 $4.34 1 $4.35 $4.39 49 $4.40 $4.44 5 $4.45 $4.49 10 $4.50 $4.99 270 $4.50 $4.54 74 $4.55 $4.59 6 $4.60 $4.64 6 $4.65 $4.69 26 $4.70 $4.74 12 $4.75 115 $4.76 $4.79 7 $4.85 $4.89 20 $4.85 $4.99 3 See foolnotes at end of table. P. 10 Table 18. Distribution of wage and salary workers paid hourly rates, second quarter 1998 averages, not seasonally adjusted (Numbers in thousands) - Continued Total MAR-02-00 THU 20:33 HOURLY RATE $5.00 $5.49 5,346 $5.00 1,370 $5.05 $5.09 13 $5.10 $5.14 19 $5.15 1,636 $5.16 $5.19 14 $5.20 $5.24 50 $5.25 $5.29 1,379 $5.30 $5.34 146 $5.35 $5.39 364 $5.40 $5.44 207 $5.45- $5.49 147 $5.50 $5.99 3,585 $5.50 $5.74 2,135 $5.50 1,632 $5.51 $5.54 24 $5.55 $5.59 36 $5.60 $5.64 161 $5.65 $5.69 190 $5.70 $5.74 92 $5.75 $5.99 1,450 $5.75 1,111 $5.76 $5.79 17 $5.80 $5.84 94 $5.85 $5.69 105 $5.90 $5.94 76 $5.95 $5.99 48 $6.00 6.99 8,547 $6.00 $6.49 5,514 $6.00 4,008 $8.01 $6.04 25 $6.05 $6.09 56 $6.10 $6.14 128 $6.15 110 $6.16 $6.19 55 $6.20 $6.24 128 $6.25 $6.29 600 $6.30 $6.34 70 $6.35 $6.39 75 See footnotes at end of table. P.11 Table 18. Distribution of wage and salary workers paid hourly rates, second quarter 1998 averages, not seasonally adjusted (Numbers In thousands) - Continued Total MAR-02-00 THU 20:34 HOURLY RATE $6.40 $6.44 141 $6.45 $6.49 116 $6.50 $6.99 3,033 $6.50 $6.74 2,272 $6.50 1,954 $6.51 $6.54 30 $6.55 $6.59 63 $6.60 $6.64 68 $6.65 $6.69 55 $6.70 $6.74 102 $6.75 $6.99 761 $6.75 374 $6.76 $6.79 39 $6.80 $6.84 108 $6.85 $6.89 77 $6.90 $6.94 119 $6.95 $6.99 44 $7.00 $7.99 7,599 $7.00 $7.49 5,107 $7.00 3,572 $7.01 $7.04 21 $7.05 $7.09 59 $7.10 $7.14 81 $7.15 104 $7.16 $7.19 40 $7.20 $7.24 127 $7.25 $7.29 540 $7.30 $7.34 146 $7.35 $7.39 136 $7.40 $7.44 157 $7.45 $7.49 124 $7.50 $7.99 2,492 $7.50 $7.74 1,903 $7.50 1,595 $7.51 $7.54 3 $7.55 $7.59 69 $7.60 $7.64 112 $7.65 $7.69 65 $7.70 $7.74 58 See footnotes at end of table. 12 Table 18. Distribution of wage and salary workers paid hourly rates, second quarter 1998 averages, not seasonally adjusted (Numbers In thousands) - Continued Total MAR-02-00 THU 20:34 HOURLY RATE $7.75 - $7.99 588 $7.75 243 $7.76- $7.79 24 $7.80 $7.84 106 $7.85- $7.89 65 $7.90 $7.94 102 $7.95 $7.99 49 $8.00- $8.99 7,084 $9.00- $9.99 5,937 $10.00 or more 31,743 SOURCE: U.S. Department of Labor, not presented and Hispanics are included in Bureau of Labor Statistics, unpublished both the white and black population groups. labulations from the Current Population Survey, Also note that the distinction between full and 1998. part-time workers is based on hours usually NOTE: Data exclude the incorporated self worked. These data will not sum to totals employed. Detail for the above race and because full or part-time status on the principal Hispanic-origin groups will not sum to totals job Is not Identifiable for a small number of because data for the 'other races' group are multiple Jobholders. P.13 Table 18, Distribution of wage and salary workers paid hourly rates, fourth quarter 1997 averages, not seasonally adjusted (Numbers In thousands) MAR-02-00 THU 20:34 Total HOURLY RATE Total 71,081 Under $3.35 842 Under $2.50 547 $2.13 158 $2.14 $2.49 157 $2.50 - $2.99 147 $3.00 $3.34 148 $3.00 $3.04 88 $3.05 $3.09 15 $3.10- $3.19 15 $3.20 $3.29 29 $3.35 3 $3.36 $3.49 4 $3.36- $3.39 4 $3.40- $3.44 1 $3.50 - $3.79 48 $3.50 $3.54 36 $3.65 - $3.69 3 $3.75 $3.79 10 $3.80 >0 $3.81 $3.99 3 $3.85- $3.89 2 $3.95 $3.99 1 $4.00 146 $4.01 $4.24 24 $4.05 - $4.09 I $4.15 $4.19 9 $4.20- $4.24 15 $4.25 145 $4.26 $4.49 45 $4.30- $4.34 4 $4.35- $4.39 33 $4.40 $4.44 7 $4.45 $4.49 3 $4.50- $4.99 547 $4.50- $4.54 146 $4.55 $4.59 38 $4.60 $4.64 13 $4.65 - $4.69 36 P.14 See footnotes at end of table. Table 18. Distribution of wage and salary workers paid hourly rates, fourth quarter 1997 averages, not seasonally adjusted (Numbers in thousands) - Continued Total MAR-02-00 THU 20:35 HOURLY RATE $4.70 $4.74 5 $4.75 233 $4.80 $4.84 21 $4.85 $4.89 17 $4.90 $4.94 29 $4.95 $4.99 8 $5.00 $5.49 6,728 $5.00 2,251 $5.05 $5.09 25 $5.10 $5.14 38 $5.15 2,115 $5.16 $5.19 18 $5.20 $5.24 87 $5.25 $5.29 1,455 $5.30 $5.34 131 $5.35 $5.39 216 $5.40 $5.44 227 $5.45 $5.49 168 $5.50 $5.99 3,24B $5.50 $5.74 2,273 $5.50 1,897 $5.51 $5.54 34 $5.55 $5.59 59 $5.60 $5.64 120 $5.65 $5.69 112 $5.70 $5.74 50 $5.75 $5.99 975 $5.75 610 $5.76 $5.79 27 $5.80 $5.84 81 $5.85 $5.89 109 $5.90 $5.94 78 $5.95 $5.99 70 $6.00 $6.49 5,665 $6.00 4,176 $6.01 $6.04 28 $6.05 $6.09 41 $6.10 $6.14 89 $6.15 69 See footnotes at end of table. P.15 Table 18. Distribution of wage and salary workers paid hourly rates, fourth quarter 1997 averages, not seasonally adjusted (Numbers In thousands) - Continued Total MAR-02-00 THU 20:35 HOURLY RATE $6.16 $6.19 36 $6.20 $6.24 80 $6.25 $6.29 678 $6.30 $6.34 88 $6.35 $6.39 121 $6.40 $6.44 194 $6.45 $6.49 65 $6.50 $6.99 2,970 $6.50 $6.74 2,218 $6.50 1,773 $6.51 $6.54 32 $6.55 $6.59 113 $6.60 $6.64 111 $6.65 $6.69 126 $6.70 $6.74 62 $6.75 $6.99 752 $6.75 458 $6.76 $6.79 35 $6.80 $6.84 74 $6.85 $6.89 84 $6.90 $6.94 38 $6.95 $6.99 63 $7.00 $7.99 7,794 $7.00 $7.48 5,085 $7.00 3,633 $7.01 $7.04 76 $7.05 $7.09 43 $7.10 $7.14 90 $7.15 40 $7.16 $7.19 40 $7.20 $7.24 179 $7.25 $7.29 515 $7.30 $7.34 113 $7.35 $7.39 96 $7.40 $7.44 129 $7.45 $7.49 130 $7.50 $7.99 2,709 $7.50 $7.74 1,998 $7.50 1,552 See footnotes at end of table. P.16 Table 18. Distribution of wage and salary workers paid hourly rates, fourth quarter 1997 averages, not seasonally adjusted (Numbers In thousands) - Continued MAR-02-00 THU 20:35 Total HOURLY RATE $7.51 $7.54 23 $7.55 - $7.59 101 $7.60 $7.64 106 $7,65 $7.69 98 $7.70 - $7.74 117 $7.75 $7.99 711 $7.75 209 $7.76 - $7.79 41 $7.80 $7.84 144 $7.85 $7.89 88 $7.90 $7.94 127 $7.95- $7.99 102 $8.00- $8.99 7,235 $9.00 $9.99 5,343 $10.00 or more 30,289 >0 Value too small to display. not are not presented and Hispanics are SOURCE: U.S. Department of Labor, Included In both the white and black population Bureau of Labor Statistics, unpublished groups. Also note that the distinction between labulations from the Current Population Survey, full and part-time workers Is based on hours 1997. usually worked. These data will not sum to NOTE: Data exclude the incorporated sell totals because full or part-time status on the employed. Detail for the above race and principal job Is not Identifiable for a small Hispank-origin groups will not sum to totals number of multiple jobholders. because data for the 'other races' group are P.17 GOOD NEWS FOR Low INCOME FAMILIES: EXPANSIONS IN THE EARNED INCOME TAX CREDIT AND THE MINIMUM WAGE December 1998 A report by The Council of Economic Advisers EXECUTIVE SUMMARY The strongest labor market in a generation has resulted in particularly large gains among low-wage and disadvantaged workers. From 1979 to 1993, the real wages of low-wage workers fell sharply. Recently, however, low-wage workers have experienced large increases in real wages: For low-wage men, wages are up since 1996 by 5.7 percent after inflation. And for low-wage women, real wages have risen 6.1 percent. These strong wage gains have been accompanied by a steep decline in unemployment for low-skilled workers. In 1993, 11.1 percent of workers without a high school degree were unemployed; today that rate has fallen to 7.2 percent. Among high school graduates (with no college), the rate has fallen from 6.6 to 3.9 percent. Low-wage workers are thus gaining both by working more and by earning more for every hour that they work. The effects of a strong economy have been reinforced by successful policies designed to make work pay. Expansions in the Earned Income Tax Credit (EITC) since 1993 are supplementing the incomes of low-wage working parents. The EITC is one of our most successful programs for fighting poverty and encouraging work: Lifts more than 4 million Americans out of poverty. The EITC lifted 4.3 million Americans out of poverty in 1997 -- more than double the number in 1993. Dramatically reduces child poverty. In 1997, the EITC reduced the number of children living in poverty by 2.2 million. This report finds that over half of the decline in child poverty between 1993 and 1997 can be explained by changes in taxes, most importantly the EITC. Encourages work among single women with children. In 1992, 73.7 percent of single women with children were in the labor force. In 1997, 84.2 percent of such women were in the labor force. The percentage of single women with children who received welfare and did not work has been cut by more than half -- from 19.3 percent in 1992 to 8.3 percent in 1997. Research studies suggest that the increase in labor force participation among single mothers is strongly linked to the expansion in the EITC. Increases in the minimum wage have been important in raising the earnings of low-wage workers. Empirical research suggests that recent minimum wage increases have had little or no adverse effect on employment. The combined effects of the minimum wage and the EITC have dramatically increased the returns to work for families with children. Between 1993 and 1997, families with one child and one earner who worked full-time at the minimum wage (i.e., $4.72 in 1993 and $5.15 in 1997, in 1997 dollars) experienced a 14 percent -- $1,402 -- increase in their income, after inflation, just because of these two policies alone. Similar families with two children experienced a 27 percent -- $2,761 -- increase in their income. GOOD NEWS FOR Low INCOME FAMILIES: EXPANSIONS IN THE EARNED INCOME TAX CREDIT AND THE MINIMUM WAGE 1. The Labor Market Continues to Perform at a Record Pace American workers are currently benefiting from the strongest labor market in a generation. Employment is at an all-time high, with 132 million Americans at work in November 1998, up from 119 million in January of 1993. Only 4.4 percent of the labor force is unemployed, having fallen by 2.9 percentage points since this Administration took office; the unemployment rate is now at its lowest level since 1969. Moreover, wages of workers are up sharply in the past several years, with a gain in median wages (after inflation) of 4.4 percent from 1996 through August of this year. As this report indicates, these gains are particularly strong among low-wage and disadvantaged workers, following more than a decade of labor market losses. Administration policies have been important in helping those at the bottom end of the labor market begin to catch up and share in the overall economic growth of the 1990s. 2. Low-Wage and Disadvantaged Workers are Making Particularly Large Gains Low-wage and disadvantaged workers have experienced substantial gains in wages and employment. The real wages of low-wage male workers have shown large increases in the past few years, in contrast to the period from 1979 to 1993, when they declined by 14.7 percent. (We define low-wage as those workers at the bottom decile of the wage distribution.) Among low- wage women, the decline was 15.8 percent over this period. Charts 1 and 2 show recent significant improvements in real wages among all workers, but with particularly large gains among the lowest paid. Since 1996, men in the bottom decile have increased their earnings by 5.7 percent after inflation (Chart 1), while women have gained 6.1 percent (Chart 2). At the same time, unemployment rates among the least skilled have plummeted. When this Administration took office in 1993, 11.1 percent of workers without a high school degree were unemployed; today that rate has fallen to 7.2 percent. Among high school graduates (with no college), the rate has fallen from 6.6 to 3.9 percent. Hence, low-wage workers are working more and earning more for every hour that they work. Chart 1: Hourly Wages of Men Aged 16 and Over Chart 2: Hourly Wages of Women Aged 16 and Over 16 16 14 50th declie (median) 14 Hourly wages (1997 dollars) 12 10 20th decile 8 Hourly wages (1997 dollars) 12 10 50th decile (median) 8 10th decile 20th decile 6 6 10th decle 4 1979 1982 1985 1988 1991 1994 1997 4 1979 1982 1985 1988 1991 1994 1997 Note: 1998 figure is the January through August average. 1 Note: 1998 figure is the January through August average One group in particular -- single mothers -- has also experienced significant increases in labor force participation during this time period. Labor force participation rates among single mothers began to climb in 1993 after remaining essentially unchanged at 74 percent since 1984. By 1997, 84 percent of single mothers were in the labor force, a marked change for a group that has traditionally had extremely high rates of poverty and welfare usage. 3. Administration Policies Have Played a Key Role in These Gains The strong overall economy has been an important factor in increasing the wages and employment of less-skilled workers. Typically, employment among workers with less education is more sensitive to changes in the economy, with larger gains in recoveries and larger losses in downturns. This Administration has worked hard to maintain an environment in which economic growth can flourish and American businesses can compete fairly, both at home and abroad. However, the strong economy is not the only reason for these gains among less skilled workers. Administration policies to "make work pay" by expanding the Earned Income Tax Credit and raising the minimum wage have also been important. 3.1 Expanding the Earned Income Tax Credit Description of the EITC The goals of the Earned Income Tax Credit (EITC) are to make work pay, to help ensure that working parents do not have to raise their children in poverty, and to offset the total tax burden of low and moderate income working families. As a result, the EITC eases the transition from welfare to work. To achieve these goals, the EITC consists of a refundable tax credit for working families with low incomes that offsets a family's total tax burden. Because the credit is refundable, individuals can receive the full amount to which they are entitled even if the amount exceeds the individual income taxes they owe. About 80 percent of EITC payments offset individual income, social security, and other Federal taxes borne by families receiving the credit. Only families that work are eligible for the tax credit, and the amount of the credit depends on a family's labor market earnings. In 1998, for every dollar a low-income worker earns up to an established limit, as much as 40 cents is added to compensation in the form of a tax credit. In particular, the amount of the credit rises with earnings up to a maximum credit of $2,271 for a family with one child and $3,756 for a family with two or more children. The credit is flat for a range of earnings and then is phased out. 2 The EITC was significantly expanded in Chart 3: The Earned Income Tax Credit in 1993 and 1998 the Omnibus Budget Reconciliation Acts (OBRA) 4,000 of 1990 and 1993. As a consequence of these 1998 expansions, the EITC now provides a greater 3,000 incentive for labor force participation than in Credit amount (1997 dollars) 1993. In 1993, very low-income parents receive an additional 19 to 20 cents for each additional 2,000 dollar earned. In 1998, a very low income parent 1993 with one child will receive 34 cents for additional 1,000 earnings; if he or she has two children, the EITC will add 40 cents to their take-home pay (Chart 3). 0 5,000 10,000 15,000 20,000 25,000 30,000 OBRA 1993 significantly increased the Earnings credit for families with two or more children. The Note: Credit amount depicted is for a family with two or more children maximum credit was increased by over $1,500 (1998 dollars), while eligibility for the credit was extended to families with incomes up to $30,050 (or about $3,600 above the prior law level). In addition, the 1993 expansion helped lower taxes for 15 million working families in 1996. About 19.7 million workers are expected to claim the EITC in tax year 1998, receiving an average credit of $1,547. About 16.5 million of these claims will be for workers living with children, who will receive an average credit of $1,807. The EITC is a non-bureaucratic way to reward work effort. There are no middlemen service providers, no long lines at government offices, and there is no need to take time off from work to apply for the credit. Working families apply directly to the Internal Revenue Service for the EITC and generally receive the credit as part of their tax refund. Participation in the EITC While the EITC offers a substantial incentive to work and move out of poverty, the credit is effective if low-income families apply for it. A relatively high fraction of families eligible for the EITC -- 81 to 86 percent in 1990 -- have claimed the credit.¹ The participation rate has been substantially higher than those for other antipoverty programs, including AFDC (62 to 72 percent in 1986/87), and Food Stamps (54 to 66 percent in 1986/87).² ¹Scholz, J.K. (1994). "The Earned Income Tax Credit: Participation, Compliance, and Antipoverty Effectiveness." National Tax Journal, 59-81. ²Blank, R. and P. Ruggles (1996). "When Do Women Use AFDC and Food Stamps? The Dynamics of Eligibility VS. Participation." Journal of Human Resources, 57-89. 3 The EITC has reduced poverty Chart 4: Number of People Removed from Poverty The EITC is targeted to families living in by the EITC poverty with the goal of lifting their income above 5 the poverty line. As shown in Chart 4, the latest 4.3 4.3 estimate from the Census Bureau shows that the 4 3.7 EITC removed 4.3 million persons from poverty in were removed from poverty in 1993. Millions of persons 3.1 1997, which is more than double the number who 3 2.1 Over half of the people removed from 2 poverty by the EITC (2.2 million) were children under the age of 18, and 1.8 million were living in 1 families headed by unmarried women. Updating analyses reported in the 1998 Economic Report of 0 1993 1994 1995 1996 1997 the President, it is found that over half of the decline in child poverty between 1993 and 1997 can be explained by changes in taxes, most importantly the EITC (Table 1). In addition, the EITC removed about 1.1 million African- Americans and nearly 1.2 million persons of Hispanic origin from poverty in 1997. It is clear that the EITC has become a major weapon in our fight against poverty. The EITC has increased the labor force participation of single mothers Between 1993 and 1997, the real value of the maximum EITC payment increased by 38 percent for single mothers with one child and by 116 percent for single mothers with two or more children.³ These increases coincided with the period when the proportion of single mothers in the labor force increased dramatically, from 73.7 percent in 1992 to 84.2 percent in 1997. In contrast, the labor force participation of single women without children -- who became eligible for a very small credit in 1994 if their earnings were very low -- did not change over this period (Chart 5). As Chart 6 indicates, the difference in the labor force participation rates of single women with and without children has closely tracked the growth in maximum EITC Chart 6: Maximum EITC and Difference in Labor Force Chart 5: Labor Force Participation Rates of Single Women Participation Between Single Women With and Without Children With and Without Children 3,500 -8 100 3,000 -10 Single women without children -12 2,500 Labor force participation rate (percent) 90 Maximum EITC (1997 dollars) -14 2,000 -16 80 1,500 Maximum EITC (left axis) -18 Percentage points 1,000 -20 Single women Labor force participation 70 with children 500 difference (right axis) -22 0 -24 1984 1986 1988 1990 1992 1994 1996 60 1984 1986 1988 1990 1992 1994 1996 Note: After 1990, the maximum EITC is the average of the maximum for taxpayers with one child and with more than one child. ³The same numbers apply to two-parent families. 4 benefits.4 One recent study concluded that as much as 60 percent of the increase in employment of single mothers since 1984 was attributable to expansions in the EITC. For the period between 1992 and 1996, the EITC explains 33 percent of the increase in annual employment. A second study examined the 1986 EITC expansion, which was more modest than the 1993 expansion, and found that it significantly increased labor force participation among single mothers, especially for less educated women.⁶ Yet another study found that the EITC could result in an increase in labor supply of 19.9 million hours in 1996 relative to 1993 law and induce 516,000 families to move from welfare into the workforce.⁷ EITC benefits for married couples are based on the combined earnings of both husband and wife. Hence, married couples are more likely than single parent families to fall in the range of earnings where the EITC is being phased out. This has caused some researchers to predict that the EITC might cause a decrease in hours of work among married couples. However, the limited available evidence suggests that the expansions in 1986, 1990, and 1993 had modest disincentive effects of 1.2 percentage points on labor force participation of wives, and they actually had a small positive effect on married men (of 0.2 percentage points).⁸ How is the extra income from the EITC being used? Most families receive their EITC dollars at tax payment time, in the form of a larger refund. A recent study interviewed low-income workers who had gone to a volunteer tax preparation office in Chicago for assistance with their tax return. The study asked the workers what they planned to do with the EITC they were expecting to receive and found that 61 percent planned to use at least some of their refund for investment purposes, such as to pay for education (9 percent), repair, buy, or finance a car (10 percent), or to pay for a move (5 percent). Twenty- ⁴Liebman, J.B. (1998). "The Impact of the Earned Income Tax Credit on Incentives and Income Distribution." Tax Policy and the Economy, 12, 83-119. ⁵Meyer, B., and D.T. Rosenbaum (1998). "Welfare, the Earned Income Tax Credit, and the Employment of Single Mothers." Department of Economics, Northwestern University. Eissa, N. and J.B. Liebman (1996). "Labor Supply Response to the Earned Income Tax Credit." Quarterly Journal of Economics, 111(2): 605-637. ⁷Dickert, S., S. Houser, and J.K. Scholz (1995). "The Earned Income Tax Credit and Transfer Programs: A Study of Labor Market and Program Participation." Tax Policy and the Economy, 9, 1-50. Eissa, N. and H.W. Hoynes (1998). "The Earned Income Tax Credit and the Labor Supply of Married Couples." Department of Economics, University of California, Berkeley. 5 eight percent said they were saving at least some of the EITC for future use.⁹ 3.2 Increasing the Minimum Wage The Administration has fought for Chart 7: The Real Value of the Minimum Wage increases in the minimum wage, and on October 1, 7.00 1996 the rate was raised from $4.25 to $4.75. The rate was increased again to $5.15 on September 1, 6.50 1997. Prior to these increases, it had been five 6.00 years since the minimum wage was last raised, and its real value had decreased by 15 percent (Chart 7). 1997 dollars 5.50 As shown in Charts 1 and 2, the wages of 5.00 low-wage workers increased substantially since 1996, and the recent minimum wage increases are 4.50 likely to explain much of this rise. It has been 4.00 estimated that almost 10 million workers benefited 1979 1982 1985 1988 1991 1994 1997 from the recent minimum wage hikes. 10 Most of the workers benefiting from the wage increases are adults from lower income families, and their wages are a major source of their family's earnings. Among workers who were earning between $4.25 and $5.15 just prior to the minimum wage increases, 71 percent were adults (20 or older), 58 percent were women, and one-third were black or Hispanic workers. Almost half of the affected workers (46 percent) worked full-time, and most of the low-wage workers were in low-income households. That is, over half of the benefits from the minimum wage increases were received by households in the bottom 40 percent of the income distribution. And in 1997, the earnings of the average minimum wage worker accounted for 54 percent of their family's total earnings. One of the potential side effects of increasing the minimum wage is a reduction in employment. That is, with labor more expensive, some firms may hire fewer workers. Many empirical studies have examined this issue, and the weight of the evidence suggests that modest increases in the minimum wage have had very little or no effect on employment. In fact, a recent study of the 1996-97 wage increases used several different methods and found that the employment effects were statistically insignificant. Moreover, the unemployment rates of African- American teens and high school dropouts, who are two groups of workers most likely to be ⁹Smeeding, T., K. Ross, M. O'Connor, and M. Simon (1998). "The Economic Impact of the Earned Income Tax Credit (EITC)." Center for Policy Research, Maxwell School of Public Policy, Syracuse University. ¹⁰This finding, and the subsequent two paragraphs are based on: Bernstein, J., and J. Schmitt (1998). Making Work Pay: The Impact of the 1996-97 Minimum Wage Increase. Economic Policy Institute, Washington, D.C. 6 affected by the wage hike, are lower today than they were just prior to the increases. 4. The Combined Effects of EITC and Minimum Wage Expansions Increases in the minimum wage and expansions in the EITC reinforce each other. Among low-wage workers, these changes have produced substantial increases in income. Table 2 demonstrates the combined effect of the two policies (after inflation), comparing 1993 and 1997 (as if the minimum wage was in effect the full year). During this period the minimum wage rose by 9 percent, while the maximum EITC credit rose by 38 percent for one-child families (116 percent for two-child families). For families with one earner working full-time at the minimum wage, their combined earnings-plus-tax refund would have risen 14 percent if they had one child (27 percent if they had two or more children). This is a significant gain in real purchasing power among these parents. As the bottom of Table 2 demonstrates, full-time work at the minimum wage no longer leaves families below the poverty line. As a result of these policy changes, one and two-child families with a single full-time minimum wage worker now earn enough to escape poverty. 5. Conclusion The past several years have been very good ones for less-skilled workers in the labor market. Wages are up and unemployment is down. Among single mothers, many more are participating in the labor market, while welfare caseloads have declined steeply. The research evidence indicates that these gains partially reflect the strong economy, but that the gains have been reinforced by Administration policies that have increased the financial rewards for low-wage and less skilled persons to work. Providing the economic incentives to work are an important legacy of this Administration. These gains mesh well with other goals this Administration has pursued, such as adequate child care for the children of working mothers and available training for those workers who want to increase their skills and work opportunities. In the long run, a healthy strong economy must rely on a trained and hard-working labor force, with opportunities for both the more and less educated. There has been real progress toward this goal in recent years. 7 Table 1. Factors Accounting for Changes in Child Poverty 1979-97 1979-89 1989-93 1993-97 Changes to official poverty rate attributable to changes in: Family structure 2.1% 1.2% 0.8% 0.3% Earnings and other before-tax-and-after income 1.4% 1.1% 3.5% -3.6% Cash social insurance and welfare payments 0.3% 1.0% -1.1% 0.5% Total change in official poverty measure 3.8% 3.2% 3.1% -2.8% Change in extended poverty rate attributable to changes in: Means-tested food and housing transfers 0.4% 0.4% -0.3% 0.4% Taxes -2.3% 0.3% 0.0% -2.6% Total change in extended poverty rate 1.9% 4.0% 2.9% -5.0% 8 Table 2. The Effects of Changing Minimum Wage and EITC on Earnings of Single Parents (All numbers in $1997) 1993 1997 Percent Change Program Parameters Minimum wage $4.72 $5.15 9 Maximum EITC One-child family $1,602 $2,210 38 Two-child family $1,689 $3,656 116 Earnings minus taxes* One-child family $10,320 $11,722 14 Two-child family $10,407 $13,168 27 Ratio of earnings minus taxes to poverty line One-child family 0.93 1.06 Two-child family 0.80 1.02 *Assumes one earner works full-time/full-year (2000 hours) at minimum wage. Taxes include income taxes (including the EITC) and employee share of social security taxes. 9 Strestate Gende dove Table A-32. Distribution of wage and salary workers paid hourly rates, by selected characteristics, annual averages 1999 (Numbers in thousands) Total Less $4.26 $5.16 $5.65 $6.15 $6.65 $7.15 Characteristic paid than $4.25 to $4.75 $5.00 $5.15 to to to to or hourly $4.25 $5.14 $5.64 $6.14 $6.64 $7.14 more rates SEX AND AGE Total, 16 years and over 72,306 1,047 57 1,090 25 921 1,146 3,205 5,742 3,379 4,991 51,649 16 to:24 years 16,636 460 34 569 15 487 632 1,890 2,727 1,473 1,806 7,045 16 to 19 years 6,600 198 25 354 8 305 429 1,230 1,474 727 755 1,408 20 to 24 years 10,036 262 10 215 7 182 203 659 1,253 746 1,051 5,636 25 years and over 55,670 587 22 520 11 434 514 1,316 3,015 1,906 3,185 44,605 25 to 54 years 48,070 507 19 386 8 325 415 1,015 2,477 1,607 2,665 38,978 25 to 34 years 17,051 240 12 145 4 120 180 415 1,015 662 1,041 13,341 35 to 44 years 18,172 176 3 137 1 120 140 351 917 563 979 14,906 45 to 54 years 12,846 91 3 104 4 85 96 248 545 382 645 10,731 55 years and over 7,600 80 4 134 2 109 99 301 537 298 520 5,627 55 to 64 years 5,932 58 3 71 1 60 45 166 330 210 354 4,695 65 years and over 1,669 22 1 63 1 49 54 135 208 89 166 932 Men, 16 years and over 36,073 288 28 453 11 369 446 1,226 2,404 1,286 2,119 27,825 16 to 24 years 8,556 138 16 257 7 211 289 826 1,333 707 908 4,083 16 to 19 years 3,346 60 11 162 4 136 195 565 740 368 391 854 20 to 24 years 5,210 78 4 95 4 74 93 261 593 339 517 3,229 25 years and over 27,517 150 12 196 4 158 157 400 1,071 579 1,211 23,742 Women, 16 years and over 36,233 760 29 637 14 552 700 1,980 3,338 2,093 2,872 23,824 16 to 24 years 8,080 322 19 312 7 276 343 1,064 1,394 766 898 2,962 16 to 19 years 3,254 139 14 192 4 169 233 665 734 359 364 554 20 to 24 years 4,826 184 5 120 3 107 110 398 660 407 534 2,408 25 years and over 28,153 437 10 324 7 276 357 916 1,944 1,327 1,974 20,863 RACE AND HISPANIC ORIGIN White Total, 16 years and over 58,999 915 41 846 17 730 895 2,548 4,584 2,736 3,932 42,500 Men 29,906 232 22 348 6 291 356 983 1,978 1,080 1,707 23,199 Women 29,093 683 19 498 11 439 539 1,565 2,606 1,656 2,225 19,301 Black Total, 16 years and over 10,126 91 13 195 7 146 217 546 839 489 847 6,889 Men 4,632 42 4 80 5 55 74 203 303 153 321 3,453 Women 5,494 49 9 115 2 90 144 343 536 336 526 3,437 Hispanic origin Total, 16 years and over 9,402 87 3 185 4 166 238 446 1,305 591 856 5,691 Men 5,490 37 3 86 1 80 105 184 683 279 471 3,640 Women 3,913 50 vo 99 3 86 133 261 622 311 385 2,051 See footnotes at end of table. Table A-32. Distribution of wage and salary workers paid hourly rates, by selected characteristics, annual averages 1999 (Numbers in thousands) - Continued Total Less $4.26 $5.16 $5.65 paid $6.15 $6.65 $7.15 Characteristic than $4.25 to $4.75 $5.00 $5.15 to to to to hourly or $4.25 $5.14 $5.64 rates $6.14 $6.64 $7.14 more FULL- AND PART-TIME STATUS AND SEX Full-time workers Total, 16 years and over 54,931 494 22 432 13 354 372 1,195 2,996 1,942 3,359 44,120 Men 30,582 168 12 202 5 161 169 468 1,352 828 1,535 25,847 Women 24,349 325 10 230 8 193 203 727 1,644 1,113 1,824 18,273 Part-time workers Total, 16 years and over 17,227 550 34 654 12 563 772 2,005 2,735 1,431 1,617 7,429 Men 5,410 119 15 249 6 207 276 757 1,045 454 573 1,921 Women 11,817 431 19 405 6 356 496 1,248 1,690 976 1,044 5,508 FAMILY RELATIONSHIP Husbands 17,609 74 6 89 1 71 79 190 582 317 673 15,598 Wives 16,996 233 4 191 6 165 198 522 1,101 775 1,187 12,785 Women who maintain families 5,395 118 4 77 3 63 93 261 501 357 450 3,535 Men who maintain families 1,815 6 1 24 1 21 20 43 108 56 111 1,446 Other persons In families: -Men 8,642 117 14 247 6 205 250 783 1,254 651 858 4,469 Women 7,204 222 17 275 5 246 288 896 1,180 635 770 2,921 All other men 1 8,007 91 6 93 3 71 97 209 460 262 477 6,311 All other women 1 6,638 186 4 94 >0 78 122 300 557 326 466 4,584 1 The majority of these persons are Ilving alone or with a non-relative. and part-time workers is based on hours usually worked. These data will not >0 Value too small to display. sum to totals because full- or part-time status on the principal job is not NOTE: Data exclude the Incorporated self employed. Detail for the above Identifiable for a small number of multiple jobholders. race and Hispanic-origin groups will not sum to totals because data for the SOURCE: U.S. Department of Labor, Bureau of Labor Statistics, "other races" group are not presented and Hispanics are included in both the unpublished tabulations from the Current Population Survey, 1999. white and black population groups. Also note that the distinction between full- Table A-34. Distribution of wage and salary workers paid hourly rates, by major Industry group, annual averages 1999 (Numbers in thousands) Total Less paid $4.26 $5.16 $5.65 $6.15 $6.65 $7.15 Industry than $4.25 to hourly $4.75 $5.00 $5.15 to to to to or $4.25 rates $5.14 $5.64 6.14 $6.64 $7.14 more Total, 16 years and over 72,306 1,047 57 1,090 25 921 1,146 3,205 5,742 3,379 4,991 51,649 Private sector 63,557 1,010 56 1,015 24 860 1,028 2,961 5,333 3,117 4,592 44,444 Goods producing 19,165 38 8 133 4 116 129 291 981 558 949 16,077 Agriculture 1,156 5 4 27 - 26 54 75 227 89 127 548 Mining 322 1 - 2 - 2 2 >0 4 8 7 296 Construction 4,687 11 1 30 1 27 10 38 146 81 226 4,144 Manufacturing 13,000 20 3 74 2 61 63 177 604 380 589 11,089 Durable goods 8,023 11 3 28 1 19 21 72 277 195 319 7,097 Nondurable goods 4,976 9 - 47 1 42 42 106 326 185 270 3,992 Service producing 44,392 972 48 881 20 744 899 2,670 4,352 2,559 3,643 28,367 Transp. and public utilities 4,122 10 1 19 1 14 22 49 99 93 188 3,640 Wholesale trade 2,396 8 - 21 >0 19 15 53 132 93 175 1,898 Retail trade 15,463 746 30 471 12 393 525 1,632 2,463 1,387 1,597 6,612 Eating and drinking 5,209 709 20 279 10 234 268 735 1,019 419 509 1,251 Finance, Ins., & real estate 3,001 12 2 24 - 19 8 52 128 93 173 2,509 Services 19,410 196 14 346 7 299 328 883 1,530 893 1,510 13,708 Private households 487 59 3 90 - 82 11 17 55 19 44 188 Other services 18,922 137 12 256 7 217 317 866 1,475 874 1,466 13,521 Business and repair 4,188 15 1 37 2 30 66 117 346 179 348 3,079 Personal services 1,860 38 3 65 3 53 47 143 247 151 218 948 Entertainment and recr. 1,310 23 5 39 1 29 55 151 181 106 127 624 Professional and related 11,547 61 2 114 - 105 148 454 700 438 769 8,862 Forestry and fisheries 17 - - 1 - 1 1 1 1 - 5 7 Government 8,749 37 1 75 1 61 117 244 409 261 399 7,205 Federal 1,829 7 - 6 >0 2 9 14 34 26 44 1,689 State 2,124 10 - 16 - 15 50 78 136 83 110 1,642 Local 4,796 21 1 53 1 44 58 152 239 153 245 3,874 >0 Value too small to display. and part-time workers is based on hours usually worked. These data will not - Data not available. sum to totals because full- or part-time status on the principal Job is not NOTE: Data exclude the Incorporated self employed. Detail for the above Identifiable for a small number of multiple jobholders. race and Hispanic-origin groups will not sum to totals because data for the SOURCE: U.S. Department of Labor, Bureau of Labor Statistics, "other races" group are not presented and Hispanics are Included In both the unpublished tabulations from the Current Population Survey, 1999. white and black population groups. Also note that the distinction between full- Table A-33. Distribution of wage and salary workers paid hourly rates, by major occupation group, annual averages 1999 (Numbers in thousands) Total Less $4.26 $5.16 $5.65 $6.15 $6.65 $7.15 paid Occupation than $4.25 to $4.75 $5.00 $5.15 to to to to or hourly $4.25 $5.14 $5.64 $6.14 $6.64 $7.14 more rates Total, 16 years and over 72,306 1,047 57 1,090 25 921 1,146 3,205 5,742 3,379 4,991 51,649 Managerial and professional specialty 10,078 26 6 59 1 47 37 150 271 174 308 9,047 Executive, administrative, and managerial 4,260 8 2 22 1 14 17 37 108 77 143 3,845 Professional specialty 5,818 18 3 37 - 33 21 113 163 97 165 5,202 Technical, sales, and administrative support 22,763 69 7 257 6 226 361 1,042 1,899 1,243 1,761 16,123 Technicians and related support 2,750 9 - 8 - 7 10 19 53 42 89 2,520 Sales occupations 7,445 28 5 153 1 134 231 752 1,228 752 864 3,432 Administrative support, Including clerical 12,568 32 2 96 4 84 120 271 618 448 809 10,171 Service occupations 13,438 881 26 518 14 434 470 1,275 1,928 994 1,407 5,940 Private household 425 58 2 85 - 78 11 14 48 17 34 155 Protective service 1,574 2 1 16 - 11 14 49 96 70 103 1,223 Service, except private household and protective 11,440 821 23 416 14 345 445 1,212 1,784 908 1,270 4,561 Precision production, craft, and repair 9,781 18 2 30 3 25 14 74 190 142 304 9,007 Mechanics and repairers 3,361 6 1 9 1 6 2 24 46 43 82 3,148 Construction trades 3,600 10 1 13 1 11 6 18 67 48 129 3,308 Other precision production, craft, and repair 2,820 2 1 8 8 5 32 77 51 93 2,551 Operators, fabricators, and laborers 14,882 45 12 189 3 154 198 565 1,187 725 1,043 10,918 Machine operators, assemblers, and inspectors 6,577 15 2 58 2 46 57 153 488 286 414 5,105 Transportation and material moving occupations 3,567 14 6 24 1 20 27 86 164 99 197 2,950 Handlers, equipment cleaners, helpers, and laborers 4,737 16 4 106 >0 87 115 326 536 340 431 2,863 Farming, forestry, and fishing 1,364 8 4 37 I 35 65 99 266 101 168 615 >0 Value too small to display. and part-time workers is based on hours usually worked. These data will not - Data not available. sum to totals because full- or part-time status on the principal job Is not NOTE: Data exclude the Incorporated self employed. Detail for the above Identifiable for a small number of multiple Jobholders. race and Hispanic-origin groups will not sum to totals because data for the SOURCE: U.S. Department of Labor, Bureau of Labor Statistics, "other races" group are not presented and Hispanics are Included In both the unpublished tabulations from the Current Population Survey, 1999. white and black population groups. Also note that the distinction between full- Table A-22. Hourly earnings of employed wage and salary workers paid hourly rates by educational attainment, age, sex, race, and Hispanic origin, 1999 annual averages Total, 16 years and over, Total both sexes $3.00 $3.50 $4.00 $4.50 $5.00 $5.50 $6.00 $7.00 $8.00 $9.00 $10.00 $12.00 Sex, race, Hispanic origin, Total Under to to to to to to to to to to to to and educational attainment employed $3.00 $3.49 $3.99 $4.49 $4.99 $5.49 $5.99 $6.99 $7.99 $8.99 $9.99 $11.99 $14.99 Total 72,306 726 175 53 176 119 3,828 3,228 8,362 7,888 7,356 5,690 10,345 9,453 Less than a high school diploma 13,101 153 36 16 76 53 1,818 1,375 2,889 1,806 1,281 820 1,186 897 Less than one year of high school 3,178 16 7 4 11 12 337 318 650 465 392 224 339 235 1-3 years of high school 8,775 128 26 13 60 34 1,375 973 2,002 1,175 764 516 718 550 4 years of high school, no diploma 1,148 9 3 - 5 6 106 84 236 165 125 80 129 112 High school graduate or more 59,205 573 139 37 100 67 2,010 1,853 5,473 6,082 6,075 4,870 9,159 8,555 High school graduates no college 27,819 255 65 17 49 28 1,086 1,039 2,953 3,244 3,146 2,496 4,545 3,988 Some college, no degree 16,472 222 53 13 40 26 702 594 1,801 1,908 1,808 1,382 2,505 2,270 Associate degree 6,296 48 15 5 3 5 101 110 354 481 535 479 979 1,077 Occupational program 3,472 24 7 3 1 2 53 55 175 271 294 258 512 609 Academic program 2,824 24 8 2 2 3 48 54 178 210 241 221 467 468 365 w College graduates 8,619 48 5 2 8 7 121 110 449 586 513 1,131 1,220 Bachelor's degree 6,984 39 5 2 8 7 103 88 321 382 502 442 985 1,030 Master's degree 1,296 8 1 - - >0 14 20 37 52 65 61 122 153 Professional degree 207 2 - - - >0 3 3 4 7 10 8 16 28 Doctoral degree 132 - - - - - - - 3 7 9 1 8 9 2 Table A-22. Hourly earnings of employed wage and salary workers paid hourly rates by educational attainment, age, sex, race, and Hispanic origin, 1999 annual averages - Continued Total, 16 years and over, Total both sexes Under At $15.00 $20.00 Sex, race, Hispanic origin, prevail- prevail- Standard Standard to or ing ing Median Mean and educational attainment error error $19.99 more mlnimum minimum wage wage Total 8,500 6,406 2,194 1,146 $9.53 $.06 $11.16 $.02 Less than a high school diploma 502 194 797 548 6.88 .04 7.95 .03 Less than one year of high school 126 40 151 124 7.17 .08 8.17 .05 1-3 years of high school 314 127 590 397 6.70 .06 7.77 .04 4 years of high school, no diploma 61 27 56 27 7.46 .29 8.66 .10 High school graduate or more 7,998 6,212 1,397 598 10.09 .03 11.87 .03 High school graduates no college 3,259 1,649 653 340 9.65 .07 10.71 .03 Some college, no degree 1,933 1,214 517 213 9.53 .14 10.88 .04 Associate degree 1,197 906 108 28 11.88 .13 13.15 .07 Occupational program 689 517 56 16 12.08 .17 13.32 10 Academic program 509 389 52 12 11.54 .36 12.94 .11 College graduates 1,609 2,443 119 17 13.99 .18 16.57 .11 Bachelor's degree 1,331 1,738 100 12 13.23 .27 15.68 .11 Master's degree 233 530 17 4 16.99 .60 19.48 .32 Professional degree 28 97 2 1 18.08 .93 22.05 1.07 Doctoral degree 17 77 - - 23.13 6.38 26.44 1.54 Technical Report: THE EFFECTS OF WELFARE POLICY AND THE ECONOMIC EXPANSION ON WELFARE CASELOADS: AN UPDATE August 3, 1999 A Report by the Council of Economic Advisers This study could not have been completed without the generous assistance of the Department of Health and Human Services in providing data and program information. THE EFFECTS OF WELFARE POLICY AND THE ECONOMIC EXPANSION ON WELFARE CASELOADS: AN UPDATE EXECUTIVE SUMMARY This study investigates the causes behind recent changes in welfare caseloads, updating a 1997 CEA report of caseload change. The fall in welfare caseloads has been unprecedented, wide-spread, and continuous, and employment of welfare recipients has increased. 14.1 million people received welfare in January 1993, and this number had fallen to 7.3 million by March 1999, according to estimates released today (August 3, 1999). In 31 states the caseload is less than half of what it was when President Clinton took office, and all states have experienced doubledigit percentage declines. For 22 states, the percent drop during 1998 was larger than during 1997 (from January to December). Previous analyses by the Department of Health and Human Services show that the percentage of welfare recipients working tripled between 1992 and 1997, and an estimated 1.5 million adults who were on welfare in 1997 were working in 1998. The 1996 legislation has been a key contributor to the recent declines. PRWORA produced a dramatic change in welfare policy: work and self-sufficiency became a primary goal; state and local governments were given much greater control of their programs; and states experimented with a host of program designs. The evidence suggests that these changes caused a large drop in welfare participation, a drop that is independent of the effects of the strong labor market. The estimates imply that TANF has accounted for roughly one-third of the reduction from 1996 to 1998, the last year of data analyzed in this study. In the earlier years, 1993-1996, most of the decline was due to the strong labor market, while welfare waivers played a smaller yet important role. The strong labor market has made work opportunities relatively more attractive, drawing people off welfare and into jobs. The unemployment rate has not declined as much in the postTANF period as it did in the 1993-96 waiver period. As a result, the share of the decline in the caseload that is attributable to improvements in the labor market was much higher in the 199396 period (roughly 26 to 36 percent) than in the 1996-98 period (8 to 10 percent). Past increases in the minimum wage have made work more attractive and, as a result, caused welfare participation to decline. The estimates imply that about 10 percent of the caseload declinewas due to increases in state and federal minimum wages. The specific program design adopted by a state can affect its caseload declines. The study examines the effects of a number of specific policies, including family caps, earnings disregards, time limits, work exemptions, and work sanctions on the size of the caseload. The large sustained declines in caseloads provide one piece of evidence about the effectiveness of welfare reform efforts. However, there are multiple indicators of the impact of welfare reform, including changes in work and earnings among welfare leavers, in marriage rates and out-of-wedlock pregnancies, and in poverty rates. The Clinton Administration is collecting and tracking information on all of these measures in order to fully assess the impact of welfare reform. 2 THE EFFECTS OF WELFARE POLICY AND THE ECONOMIC EXPANSION ON WELFARE CASELOADS: AN UPDATE INTRODUCTION The number of people receiving welfare has been declining at record rates. After peaking in March 1994, welfare caseloads have dropped by 48 percent through March 1999, At that time, just 7.3 million people representing 2.7 percent of the population were receiving welfare. Not since 1967 has such a small share of the population relied on welfare. Not only have the declines been large, they have been widespread and continuous (Table 1). Between 1993 and 1998 (this report examines caseload changes through December 1998), all 50 states and the District of Columbia experienced double digit percent reductions in welfare participation, and in most states the declines were unprecedented. Thirty-seven states have experienced drops of at least one- third, and in 23 states the number of participants is less than half of what it was in 1993. And although a substantial share of the reduction occurred between 1994 and 1996, in many states the largest declines have occurred more recently. In fact, in 22 states the percentage decline in 1998 was greater than it was in 1997 (from January to December). And in almost all states (45) caseloads were still declining during the final months of 1998. Two primary factors have been posited to explain the recent caseload changes: the strong labor market, and changes in welfare policy. The nation is in the midst of the longest peacetime expansion in its history, with low unemployment and rising wages. Moreover,gains in employment and wages have been experienced by groups who have typically had high rates of welfare use. Expanding labor market opportunities have made work more attractive to potential welfare participants, reducing their need for public transfers. While the labor market has improved since 1992, there have been substantial changes in welfare policies throughout the past decade. In the early 1990s a growing number of states requested waivers from the traditional welfare program, Aid to Families with Dependent Children (AFDC), allowing them to experiment with alternative policies such as time limits, family caps, work requirements, and 3 Table 1. Changes in the Number of Recipients in Each State Number of recipients Percentage Change From State 1993 1998 '93 to '96 '96 to '98 '93 to '98 Alabama 138,465 54,635 -26 -46 -61 Alaska 37,078 29,582 -1 -19 -20 Arizona 199,153 102,511 -16 -39 -49 Arkansas 71,989 32,633 -21 -43 -55 California 2,511,293 1,998,618 3 -23 -20 Colorado 122,890 50,746 -22 -47 -59 Connecticut 162,481 117,777 -2 -26 -28 Delaware 27,736 15,820 -16 -32 -43 DC 69,549 54,856 0 -21 -21 Florida 691,053 261,581 -22 -52 -62 Georgia 398,077 185,052 -15 -45 -54 Hawaii 57,336 46,724 16 -30 -19 Idaho 21,877 3,867 1 -83 -82 Illinois 694,050 476,576 -7 -26 -31 Indiana 215,367 111,176 -35 -21 -48 lowa 102,438 65,665 -16 -24 -36 Kansas 88,363 34,536 -26 -47 -61 Kentucky 220,766 119,360 -22 -31 -46 Louisiana 259,762 124,800 -12 -46 -52 Maine 66,914 39,423 -18 -28 -41 Maryland 219,998 116,456 -11 -40 -47 Massachusetts 321,219 167,043 -28 -27 -48 Michigan 689,139 332,240 -26 -35 -52 Minnesota 192,173 143,685 -12 -15 -25 Mississippi 168,924 52,523 -26 -58 -69 Missouri 262,382 147,105 -14 -35 -44 Montana 34,875 19,540 -13 -35 -44 Nebraska 47,840 36,665 -20 -4 -23 Nevada 36,009 25,472 -2 -28 -29 New Hampshire 29,797 15,409 -22 -34 -48 New Jersey 345,370 196,947 -19 -30 -43 New Mexico 97,246 74,170 2 -25 -24 New York 1,215,526 886,746 -5 -23 -27 North Carolina 335,620 169,144 -20 -37 -50 North Dakota 18,215 8,541 -28 -35 -53 Ohio 712,277 340,179 -24 -37 -52 Oklahoma 135,762 61,191 -27 -38 -55 Oregon 117,852 46,001 -31 -43 -61 Pennsylvania 610,531 360,009 -14 -32 -41 Rhode Island 62,187 54,150 -8 -6 -13 South Carolina 146,280 60,110 -22 -48 -59 South Dakota 19,913 9,653 -21 -39 -52 Tennessee 310,486 149,089 -20 -40 -52 Texas 784,816 370,857 -16 -44 -53 Utah 52,144 28,258 -25 -28 -46 Vermont 28,301 19,643 -12 -21 -31 Virginia 194,765 99,053 -20 -36 -49 Washington 289,965 202,573 -6 -25 -30 West Virginia 118,113 38,638 -25 -56 -67 Wisconsin 235,247 40,167 -33 -75 -83 Wyoming 17,859 2,471 -32 -80 -86 Total 14,007,468 8,199,666 -13 -33 -41 Data are the average monthly caseloads for the calendar year. a variety of other options. During the Clinton Administration (from the beginning of 1993 to 1996), 43 states received welfare waivers, more than any previous Administration. At the federal level, welfare policy was changed dramatically by the Personal Responsibility and Work Opportunity Reconciliation Act of 1996 (PRWORA), which replaced the AFDC program with the Temporary Assistance for Needy Families (TANF) block grant. Under PRWORA, welfare became more work- focused and time-limited: with few exceptions, federal welfare assistance is strongly linked to the recipient's efforts to find a job. In most cases, adults cannot receive federal aid for more than a total of 5 years during their lifetime, and some states have chosen to set shorter time limits. PRWORA also shifted primary responsibility for welfare program design and management to States and localities. In 1997, the Council of Economic Advisers issued a report using 1976 to 1996 data that examined the reasons for the decline in caseloads between 1993 and 1996. That study found that roughly 45 percent of the decline was accounted for by improved labor market conditions, about 30 percentwas due to welfare waivers, and the remaining 25 percent was explained by other factors. Several subsequent studies were conducted that examined changes in welfare caseloads during this and earlier periods (Bartik and Eberts, 1998; Blank, 1997; Figlio and Ziliak, 1998; Levine and Whitmore, 1998; Moffitt, 1999; Stapelton, 1998; Wallace and Blank, 1998; Ziliak, Figlio, Davis, and Connolly, 1997). Since 1996 caseloads have continued to fall, the labor market has grown even stronger, and welfare policy has been fundamentally changed, making it important to update the earlier report. This study extends the earlier study on several dimensions. Most importantly,the effects of TANF are assessed by analyzing data through 1998. In addition, the study provides more recent evidence of the effects of labor market conditions on changes in caseloads, and the study examines whether increases in the minimum wage also played a role. The large sustained declines in caseloads provide one piece of evidence about the effectiveness of welfare reform efforts. However, there are multiple indicators of the impact of welfare reform, including changes in work and earnings among welfare leavers, in marriage rates and out-of-wedlock 4 pregnancies, and in poverty rates. The Clinton Administration is collecting and tracking information on all of these measures in order to fully assess the impact of welfare reform. FACTORS AFFECTING CASELOAD TRENDS Economic Conditions Caseloads normally fluctuate with the business cycle, rising in periods of high unemployment and declining when unemployment falls. Chart 1 illustrates this relationship between labor market opportunities and welfare participation (i.e., the number of welfare recipients divided by the total population) over the past three decades. When unemployment increased in the early 1970s, so too did welfare participation. The increase in welfare participation in the late 1980s and early 1990s, as well as the decline that began in 1994, also correspond with changes in employment opportunities during these periods. However, the trend in welfare participation does not always match that in unemployment, most notably when other important changes are taking place, including changes in family structure and welfare policies. Indeed, increases in welfare participation during the recession of the early 1980s were truncated by eligibility restrictions that were part of President Reagan's welfare reform efforts in 1982. Over the entire 1980s the simple correlation between unemployment and welfare participation was much lower (0.23) than in the 1970s (0.41) or the 1990s (0.78). Chart 1. Welfare Participation and Unemployment Rates 10 Unemployment rate 8 6 Percent 4 Correlations: Welfare 1970-98: 0.28 participation rate 2 1970-79: 0.41 1980-89: 0.23 1990-98: 0.78 0 1970 1974 1978 1982 1986 1990 1994 1998 5 Chart 2. Welfare Participation Rate Versus Unemployment Rate for Each State, 1994 16 Correlation: 0.65 14 D.C. # of participants/population under 65 12 California 10 New York 8 6 4 2 0 0 2 4 6 8 10 Unemployment rate Economic conditions vary across states as well as over time. Chart 2 displays ascatterplot of the unemployment rate versus the welfare participation rate for each state and the District of Columbia in 1994, when participation was near its peak. (California and New York are highlighted because they are home to roughly one-third of the nation's welfare recipients, and DC is highlighted because it is an outlier on this Chart.) This relationship is quite strong, with a simple correlation of 0.65. While this correlation suggests a strong role for economic factors, it is likely to over-state the true role of economic factors. Fixed characteristics of states that cause them to have high unemployment rates may also lead them to high welfare participation. These characteristics include the state's age distribution, educational level, metropolitan/rural population shares, and racial and ethnic composition. While these factors may change over time, such change occurs more slowly than changes in policy or economic conditions. One way to abstract from these factors is to examine changes over time within states, which is the approach employed in the econometric models below. Chart 3 displays the simple relationship between thechange in the unemployment rate and the change in the welfare participation rate in each state between 1994 and 1998 to illustrate the potential importance of these fixed characteristics. The chart demonstrates that once state fixed effects are removed by examining changes in these variables, the relationship is not nearly as strong as the simple cross-sectional one, with a correlation of 0.17. 6 Chart 3. Change in Welfare Participation Rate Versus Change in Unemployment Rate for Each State, 1994-98 0 Correlation: 0.17 -1 Change in welfare participation rate -2 -3 New York California -4 -5 -4 -3 -2 -1 0 1 Change in unemployment rate Federal and State Policies Welfare Waivers. Since 1962, the Secretary of Health and Human Services has had the authority to waive federal welfare requirements if a state proposed experimental or pilot programs that furthered the goals of AFDC. Although there were a few waivers granted in the early 1980s, it was not until the early to mid-1990s that major, state-wide waivers became widespread. These waivers varied substantially across states, and in many cases they differed greatly from the rules under AFDC. Some waivers increased the amount of earnings recipients were allowed to keep and still be eligible for welfare. Other waivers expanded work requirements to a larger number of recipients, established limits on the length of time recipients could remain on aid, permitted states to sanction participants who failed to meet work requirements, or allowed states to eliminate benefit increases to families who conceived and gave birth to children while on welfare (the so-called "family cap"). Given the widespread use of waivers and the degree to which these policies differed from traditional AFDC policy, there is substantial reason to believe that waivers contributed to changes in welfare caseloads. PRWORA. In August of 1996, President Clinton signed the Personal Responsibility and Work 7 Opportunity Reconciliation Act into law, dramatically changing federal welfare policy. PRWORA was designed to emphasize self-sufficiency and employment in place of welfare dependency, and it gave states greater flexibility to design and implement programs to achieve these goals. Benefits are time- limited; adults usually cannot receive federal aid for more than 5 years during their lifetime, and some states have chosen to set shorter time limits. Most recipients must also participate in a work activity within two years to continue receiving aid. Under the TANF block grant established by PRWORA, federal assistance consists of an annual fixed transfer to each state equal to the amount of federal transfers the state received in fiscal year 1994, 1995, or the average of 1992-4, whichever was higher. In addition, most of the authority to design welfare programs was passed along to the states, who are required to have half of all recipients working by 2002 (40 percent by 2000). As a result, there are now substantial differences in how welfare programs operate across the nation. Some states increase benefits to welfare families who have additional children, while others do not. Some states stop payment of benefits to the entire family at the first instance of their failure to meet work activity requirements, while other states never sanction more than the adult. And some states allow welfare recipients to keep a substantial portion of their labor market earnings without reducing their welfare payments, while others do not. AFDC/TANF Benefit Levels. States have long set their own level of maximum monthly benefit payments, with variation by family size and composition. All else equal, higher benefit levels are expected to increase the number of participants. Over the period of this study, the inflation-adjusted level of welfare benefits fell in almost all states. In some cases the state explicitly changed benefits, but in most states benefit levels were fixed and eroded over time with inflation. Minimum Wage. The real value of the federal minimum wage decreased substantially between 1976 and 1989. A $0.45 legislated increase in 1990, followed by a $0.45 increase in 1991, offset some of this long-run decline, but by 1995 the real minimum wage ($4.55) was nearly as low as it was in 1989. The minimum was then legislatively raised by $0.50 in 1996 and an additional $0.40 in 1997. During the period analyzed in this study, 1976-1998, several states established minimum wage levels 8 that were above the federal minimum that prevailed at that time! A higher minimum wage can make work more attractive, giving welfare participants a greater incentive to enter the workforce and leave public assistance. On the negative side, if a higher minimum wage reduces employment of low-skilled workers, some people may lose their jobs and enter welfare. At the same time, an increase in the minimum wage may lead employers to substitute away from teenagers (a relatively large share of whom work for the minimum wage) and towards older welfare workers (who are perhaps not as likely to work at the minimum wage, but more likely to be working just above the minimum than teenagers). The evidence on the disemployment effects of the minimum wage is mixed. Some studies have found that a 10 percent increase in the minimum wage causes a 1 to 2 percent decline in employment (e.g., Neumark and Wascher, 1992; Neumark and Wascher, 1994; or the estimates surveyed by Brown et al., 1982), while other studies have found no disemploymenteffects (e.g., Katz and Krueger, 1992; Card, 1992a; Card, 1992b; Card, Katz, and Krueger, 1994; Bernstein and Schmitt, 1998; Card and Krueger, 1998). Two recent studies have examined the effects of minimum wages on welfare caseloads, with one finding a negative effect over the 1990-91 period (Turner, 1999) and the other finding a positive effect over the 1983-96 period (Page, Spetz, Millar, 1999). There are a variety of other factors that may affect caseloads, including the Earned Income Tax Credit, the availability of child care, transportation, and Medicaid coverage, family structure, and out- of-wedlock births. Although our models do not directly examine these factors, our approach controls for them indirectly, as described in the next section². ECONOMETRIC SPECIFICATION Two approaches are implemented to estimate the effects of policy and economic conditions over the 1 The states that had minimum wages above the federal level during 1976-98, and the years in which they had such policy, are: Alaska from 1976-98, California from 1989-90, Connecticut from 1976-90 and 1992-98, DC from 1976- 98, Hawaii from 1976-77, 1988-90, and 1993-98, lowa from 1990 and 1992-95, Maine from 1985-1990, Massachusetts from 1987-89 and 1995, Minnesota from 1988-90, New Hampshire from 1987-89, New Jersey from 1993-96, Oregon from 1990-98, Rhode Island from 1987-90 and 1992-96, Vermont from 1987-89 and 1995-98, Washington from 1989-90 and 1995-96. 2 Of particular interest is the EITC, but because the most significant EITC changes are enacted nationally and effect all 9 period 1976-1998. Both approaches utilize the same dependent variable, use the unemployment rate to capture the effects of labor market conditions, and specify the minimum wage and welfare benefit levels in identical ways. The difference between the two models is the specification of the remaining welfare policy variables. The first model uses two simple 0/1 indicator variables: one to capture the period during which a major waiver was in effect in each state, and one to capture the period during which TANF was in effect in each state. Specifically, Model (1) is: (1) InRₛₜ = Waiver + TANF βₜₐₙƒ + InBenefits ßₕ + InMinWage + Unemployment ßᵤ The variables are defined for states in calendar yeart as follows: R: the ratio of the number of recipients to the population under 65 years of age (the number of recipients is obtained from administrative reports on AFDC/TANF); the model estimates the natural log of this ratio. Waiver: an indicator variable that takes the value of one if the state had a major waiver in effect; the indicator is turned off when TANF is implemented in the state.³ TANF: an indicator variable that takes the value of one if TANF was in effect in the given state (the TANF implementation date varied across states, as discussed below). Benefits: the maximum monthly benefit for a family of three on AFDC/TANF. MinWage: the value of the state-specific minimum wage expressed as a monthly amount (to make comparable with the benefits variable) assuming employment for 30 hours per week for 4.33 weeks. (In most cases, this is the federal minimum wage.) persons at the same time, these effects are subsumed by the model's time fixed effects. ³In most cases, the waiver concept becomes meaningless once TANF was implemented because states were given broad control over their welfare policies. In particular, states could operate the broad categories of policies under TANF, whether or not they were continuing a waiver. However, if a state continued a time limit waiver, then participants time clocks in that state would have been running prior to TANF implementation. As a result, these participants would reach their time limits more quickly than if their clock would have been reset on the date of TANF implementation. 10 Unemployment: the unemployment rate (current, lagged one year, lagged two years) γₛ : state fixed effects γ₁ : year fixed effects trend * γₛ : linear state-specific time trends All dollar values are expressed in 1998 dollars using the CPI-U-X1. The second approach examines the effects of specific welfare policies, regardless of whether the policy was implemented under waivers or TANF. That is: (2) lnRₛₜ = X st x + InBenefits + InMinWage mw + Unemployment In Model (2), Xₛₜ represents a vector of variables that describe specific policies that are in effect in state S in year t. There are a variety of policies that could be analyzed. The five policies that were examined were chosen because, a priori, they wereexpected to significantly influence participation and they could be quantified based on available sources. The five policies are: 1. Termination or work requirement time limitsare represented by an indicator variable for whether the state either terminates eligibility, reduces benefits, or requires participants to work (not just participate in a "work activity") after a given duration on aid. The date that participants first began to reach the time limit was used as the date that this policy came into effect. (These time limits had become binding in too few states for us to examine the distinct effects of each of these three policies.) 2. A second indicator variable takes the value of 1 (0 otherwise) if the state has afamily cap that is, the state does not increase benefits for participants who give birth to or conceive a child while on aid. 3. Work exemptions are represented by three indicator variables based on the state's policy toward families with young children: the first takes the value of 1 if the state exempts mothers with a child as old as 6 months to 3 years, 0 otherwise; a second indicator takes 4 If the state had a range of minimum wages, the highest minimum wage was used to construct this variable. In the year that the minimum wage changed, the weighted average of the minimums in effect during that year were used in the analysis, where the weights are equal to the share of the year in which each minimum wage was in effect. 11 the value of 1 if the exemption applies to mothers with a child newly born to 6 months old (and not older), 0 otherwise; and a third takes the value of 1 if the state allows no exemptions based on the age of the mother's children, 0 otherwise. Years in which a state has a traditional AFDC/JOBS exemption policy serves as the reference group. These four groups are mutually exclusive. 4. A set of three indicator variables capture the aggressiveness ofwork sanction policies One indicator represents states that impose full family sanctions with the first offense ("full/full"), a second indicator represents states that impose full family sanctions only after repeated offenses ("partial/full"), and a third indicator represents states whose maximum sanction is a partial family sanction ("partial/partial"). States that impose no sanction or some lesser sanction, which was the case under traditional AFDC,serve as the reference group. 5. The aggressiveness of disregarding earned income is represented by the amount ofearnings disregard if a welfare recipient earns $750 per month (in 1998 dollars). When the disregard formula varies with duration on welfare, the disregard applicable for the longest duration (typically more than 3 months) is assumed. The "policy oriented" approach used in Model (2) has the advantage of being able to identify the specific policies that influence caseloads. However, there a number of TANF policies and practices that may affect participation that could not be captured in Model 2 because of data limitations, such as diversion policies, work requirements and targets, and welfare office culture. The simple indicator- variable approach used in Model 1 is more effective in capturing the total effect of waiver and TANF policies. State, year, and state-specific time trends are included to capture unobserved factors, such as family structure and other policies, that may be correlated with the observed variables. Most policies were not in effect the entire calendar year that they were implemented. In these cases, fractional values are used corresponding to the share of the calendar year that the policy was in effect. The model is estimated with weighted least squares, where the weight is the population under 65 in states in year t. 12 The standard errors of the coefficient estimates are corrected for general forms ofheteroscedasticity.³ Before discussing the results, it should be acknowledged that a maintained assumption in this study is that welfare policies are exogenous to welfare participation (after controlling for the factors in the models described above). All previous studies have also made this assumption. Endogenous policy is probably more likely to affect the estimates of Model 2. While most states received waivers, and every state has implemented TANF, the specific types of policies vary considerably. For example, states whose caseloads were increasing (or not decreasing as much as desired, may have adopted relatively harsh policies.⁶ DATA Using annual calendar year data from 1976 to 1998 on all states and the District of Columbia, the analysis is based on 1,173 observations. Most of the data used in the analysis come from well-known sources, with a few exceptions (described below). The federal and state minimum wage data were obtained from the Wage and Hours Division of the Bureau of Labor Statistics. Welfare Waivers The data that are unique to this study are the waiver implementation dates and TANF policies. These policies are difficult to categorize and measure, and the pace and intensity of their implementation typically vary across and within states. Experts from the Department of Health and Human Services as well as non-government research institutions were consulted to characterize these policies as fully as possible. Specifically, information on waivers was obtained from the Department of Health and Human Services. Most waivers permitted simultaneous implementation of various provisions. For example, the California Work Pays Demonstration increased the AFDC resource limit for recipients to $2,000, increased the excludable equity value for a vehicle to $4,500, allowed recipients to place 5 As a check of the robustness of the estimates, model 1 in Table 2 was re-estimated without correcting the standard errors, and all statistically significant coefficients remained so at the 0.01 level. Estimates when the weights are not used are reported in Table 4. ⁶One set of studies has modeled welfare caseloads by including the lagged value of the dependent variable as an explanatory variable (Zilaiket al, 1997; Figlio and Ziliak, 1998). This approach is an alternative way to control for past history. We have not chosen this specification, however, and we instead include year effects, state effects, and state-specific time trends in models of the level of welfare participation. 13 up to $5,000 in restricted accounts which did not count against the resource limit and which may only be withdrawn for certain uses, and (among other things) required pregnant or parenting teens (under 19) who did not possess a high school diploma or equivalent to participate inCalLEARN. Like the 1997 CEA study, this report focuses on six "major" types of waivers that received approval to be implemented state-wide⁷: termination time limits, work requirement time limits, family caps, JOBS exemptions, JOBS sanctions, and the earnings disregard. Each of these policies was discussed in detail in the appendix to the 1997 CEA Technical Report.⁸ Some of the waivers that were approved for state-wide implementation were initially implemented state-wide, some were implemented in selected areas of the state, while still others began in small regions of the state but were eventually phased-in state-wide. Information on the pace of implementation is not available for all states. Therefore, the date that is used to signal implementation is the date that the waiver began to be implemented. The earliest dates that these waivers were approved and implemented in each state are listed in Table A1. PRWORA & TANF PRWORA was signed into law in August of 1996, but a given state could not begin its TANF-funded program until that state submitted its TANF plan and it was certified as complete by the federal government. Beginning on the date the state formally implemented its TANF planthe state could begin to draw down federal funds and was subject to all of the requirements and restrictions in TANF. The earliest official implementation date was September 1996 and the latest was July 1997, 7 In a few instances waivers were examined which were not approved to be implementedtate-wide but affected a large share of the state's caseload. 8 It was determined that the waiver in West Virginia, which was considered a "major" waiver in the 1997 CEA study, did not in fact meet this requirement (Martini and Wiseman, 1997), which is reflected in Table A1. 9 Somewhat smaller effects are estimated when the date of implementation is used instead of the date of approval which was utilized in the 1997 CEA study, as described in appendix A. 14 when all states were required to begin operating under TANF. The date that the state formally implemented its TANF plan is the date that is used to construct the TANF indicator variable in Model (1). However, in some states the initial plan was simply a placeholder, designed to allow the state to begin to draw down its TANF block grant, and some state policies were not changed until a later date. Therefore, the actual implementation date may differ from theofficial date. In particular, in five states (California, Mississippi, New Jersey, New York, and Wisconsin) specific information was available indicating that the policies most associated with TANF - time limits, work requirements, sanctions, etc. - were not implemented until a later date; in these cases, the later date was used to construct the TANF indicator. 10 Table A1 reports the official and actual TANF implementation dates for each state. To specify Model (2) the policies that were in effect in each state in each year were determinedTo construct indicator variables for the existence of a termination or work requirement time limit and a family cap, we used the date that the relevant waiver was implemented (for time limits, the date that participants began to hit the limit) and assumed that the waiver continued to be in effect until (at least) TANF was implemented in that state (i.e., the date listed in Table A1)!¹ For the TANF period, we use information on state TANF plans as of October 1997 (Gallagher et al., 1998) along with the date the current policy (as of October 1997) was implemented to determine which policies were in effect in each state in each year. It is assumed that the policies in place in October 1997 were not changed by December 1998, which is the end of our sample period. If a policy was implemented and rescinded between the date that TANF was implemented and October 1997, we would not capture this policy change. However, the earliest TANF implementation was October 1996, just one year prior to our TANF information, and many states implemented TANF in the first 6 months of 1997. Therefore, it is unlikely that a policy was both implemented and rescinded within such a short period. 12 10 Model 1 in Table 2 was re-estimated without using this additional information for these five states. The coefficient estimates changed very little; the largest change was for the TANF indicator, which increased to -23.8 with a t-statistic of 2.70. 11 Again, the date that was used was the date that the policy initially began to be phased in within the state. 12 New Mexico implemented its TANF program in July 1997, but it was found unconstitutional in September of that 15 RESULTS Table 2 contains the estimates of Models 1 and 2. The table also reports a version of each of these models that excludes state-specific time trends. The rationale for including these trends is to control for unobserved changes over time that are specific to each state. For example, if there is a long-run increase in female-headed households, and the rate of this increase varies between states, other variables in the models may be biased if this factor is not controlled. On the other hand, some of the interesting and important variation for identifying effects of some of the variables of interest may be reduced substantially by the inclusion of these trends, making it difficult to identify their effects. For example, cash benefit levels follow a long-run trend in some states, and including the state-specific trends leaves much less variation in benefits to identify its effects. Therefore, estimates with (Models 1 and 2) and without (Models 1A and 2A) the state-specific trends are reported. Estimates from Model 1 Waivers had a large and precisely estimated effect on welfare participation (Table 2). The estimates in Models 1 and 1A imply that states that implemented a major waiver experienced a decline in participation that was 8 to 9 percent greater than other states. The implementation of TANF is associated with a decline in participation of 18 percent, roughly double the size of the effect of waivers. All other statistically significant estimates in Models 1 and 1A alter participation in the expected direction. Higher cash welfare benefits raise participation. The estimates in Model 1 imply that a $50 increase in the monthly benefit above its 1998 average monthly value would increase participation by 1.8 percent. For the reasons described above, the estimates from Model 1A, which exclude the state- specific linear trends, are much larger and imply that the same $50 increase would lead to a 6.2 percent increase in participation. year. A revised TANF program was implemented in April 1998. 16 Table 2. Baseline Specifications (Coefficient estimates are multiplied by 100) Model 1 Model 1A Model 2 Model 2A Beta t-stat Beta t-stat Beta t-stat Beta t-stat Mean Any waiver -9.40 2.90 -7.99 2.90 0.08 TANF -18.84 4.37 -18.12 1.75 0.09 Log maximum monthly benefit 14.98 1.93 51.74 6.20 15.01 2.37 53.84 7.63 1.55 Log monthly minimum wage -39.59 4.02 -63.91 3.61 -25.59 2.27 -51.95 2.74 1.91 Unemployment rate: Current -0.36 0.74 0.20 0.30 -0.30 0.61 -0.13 0.20 6.63 1-year lag 1.50 2.40 1.70 1.88 1.29 2.06 1.65 1.92 6.79 2-year lag 4.27 8.92 5.13 7.40 3.94 8.34 4.77 7.39 6.83 Specific welfare policy variables (X) Termination/work req. time limit -3.75 0.76 -4.30 0.73 0.03 Family cap 6.71 2.19 8.21 2.35 0.05 Work exemption based on age of youngest child: Traditional AFDC & JOBS exemption (reference group) Child as old as 6 months to 3 years 12.37 2.46 -2.79 0.57 0.05 Child newly born to 6 months old 11.56 1.53 3.05 0.40 0.03 No exemptions based on age of youngest child 4.86 0.77 0.81 0.12 0.01 Work sanctions: Traditional AFDC or JOBS (reference group) Partial/Partial -9.71 2.52 -1.36 0.32 0.05 Partial/Full -18.14 3.76 -22.76 4.20 0.04 Full/Full -39.36 5.57 -33.53 4.51 0.03 Log earnings disregard 5.38 2.40 5.86 2.00 0.64 State-specific trends? Yes No Yes No All models include state and year effects. Estimates use the population under 65 as weights and robust calculation of standard errors. N=1173. Weighted mean of the dependent variable: 1.589 Increases in the minimum wage are found to decrease welfare participation. In particular, consider an increase in the minimum wage by $0.50. If this increase were on top of the average minimum that existed in 1998, monthly earnings at the minimum wage (evaluated at 30 hours per week, full month) would increase by $65. This rise would translate into a decline in welfare participation of roughly 3.7 to 5.9 percent. 13 Tight labor markets, as measured by the unemployment rate, reduce welfare participation. The models demonstrate the lagged nature of the unemployment effects. In fact, the largest effects are for unemployment lagged two years. Model 1 implies that a one percentage point decrease in the unemployment rate that persists for three years is associated with a 5.41 percent (4.27+1.50-0.36) decline in welfare participation. The estimates are substantially higher if state-specific time trends are not included in the model. Estimates from Model 2 The effects of cash benefits, minimum wages, and the unemployment ratestimated for Models 2 and 2A are similar to those estimated in Models 1 and 1A, respectively. The welfare reform policy variables included in Models 2 and 2A show mixed results. The coefficient on the time-limit indicator variable is negative, as expected, but it is not precisely estimated. It is important to note that all participants who have hit time limits by the end of 1998 were doing so under a waiver policy. And because only a small number of states had time limit waivers, a relatively small number of participants had hit a time limit. Therefore, it is not surprising that, through 1998, time limits had not significantly altered national caseloads.¹⁴ 13 Some studies of the disemployment effects of the minimum wage have included a measure of average state wages in their specifications. Although there are problems that arise from including this variable (see Card, Katz, Krueger, 1994 for a discussion), Model 1 in Table 2 was re-estimated including the average wages of production workers because this variable is incorporated in a large number of studies. (This variable is not available for DC or for Indiana in some years.) Including this variable causes the effect of the minimum wage to fall somewhat, but it is still large (-30.45) and precisely estimated (t-statistic of 3.39). 14 Time limits may alter participants behavior before they actually hit the limit. For example, some recipients may leave the rolls sooner or not come on the rolls at all in order to save up time that could be used at a later date. When the date of implementation was used to construct this variable instead of the date that people first began to hit the limit, the estimated effects were actually positive. This counterintuitive result is likely due to thendogeneity issues raised earlier 17 As expected, a higher earnings disregard raises participation (at least in the short-run), but this effect is relatively small. The estimates suggest that an increase in the disregard equivalent to $50 on a monthly basisis associated with less than a 1 percent increase in participation. Family caps do not have the expected negative effect; in fact, they are positive and precisely estimated. Similarly, looking across Model 2 and 2A, it appears that work exemption policies based on the age of the youngest child do not play a substantial role in determining caseloads. In fact, the one significant effect is of unexpected sign. Not surprisingly, policies that sanction recipients who do not go to work are associated with large declines in welfare participation. The effects of the work sanction policies may be due to the fact that impending sanctions cause welfare recipients (or potential recipients) to accelerate their job search and find employment, or the effect may be due to the fact that recipients did not find a job and were sanctioned. States with full family sanctions on the first violation of work requirements have much lower caseloads than other states. States whose most severe work sanction policy is a partial reduction in benefits also have lower participation, but not nearly as low as the rates for states with full family sanctions. As with all policies examined in the model, the effects of these sanctioning policies on the caseload may be distinct from their effects on other important factors, such as child health and development, illegitimacy, education, poverty, and work participation. Relative Contribution of Each Factor 1993-96 Welfare Waiver Period. Table 3 provides estimates of the relative contribution of each factor to the change in welfare participation during two periods: 1993-1996 (the waiver period under the Clinton Administration) and 1996-98 (the TANF period). Specifically, the change in the national average of each variable (obtained by weighting by the state population under 65) is multiplied by its respective coefficient estimate to determine the change induced by that factor. The ratio of the share in the report. In particular, the states that chose to implement time limits under waivers may have been the states whose caseloads were increasing, or perhaps not declining as much as desired. 18 Table 3. Percentage of Change in Participation Attributable to Each Factor (Based on Estimates of Models 1 and 1A in Table 2) Based on Model 1 Based on Model 1A Factor 1993-96 1996-98 1993-96 1996-98 Welfare waivers 14.6% 12.4% TANF 36.2% 34.8% Decline in unemployment 26.4% 7.8% 35.6% 10.4% Increased minimum wage -9.7% 9.6% -15.6% 15.5% Lower cash benefits 6.3% 1.4% 21.7% 4.7% Other 62.4% 45.0% 45.9% 34.5% of this change to the total change in participation during this period is reported in Table 3. For example, 22 percent of the population under 65 lived in states with major waivers in place in 1993. By 1996, this share increased to 53 percent. Multiplying the change in the share living under waivers (0.53-0.22=0.31) by the respective coefficient estimate in Model 1 (-9.40), it is found that the expansion of waivers led to a 2.91 percent decline in participation during this period. Participation in total dropped by about 20 percent between 1993 and 1996, which implies that roughly 14 percent of the decline can be attributed to the increase in waivers. While waivers accounted for about 14 percent of the decline from 1993-96 according to Model 1, the lower unemployment rate was responsible for 26 to 36 percent of the decline (depending on the model). Cash benefits declined by about 8 percent from 1993 to 1996, which led to a decline in participation. The actual amount of the decline that can be attributed to the benefit reduction differs substantially between the two models 6 percent for Model 1 and 22 percent for Model 1A. The real value of the minimum wage fell between 1993 and 1996 (the increase in 1996 was in October, so it 19 was not effective most of the year)¹⁵, which is why the minimum wage explains a negative share of the caseload decline; the caseload would have increased between 1993 and 1996 if the only change that had occurred were the decline in the real minimum wage. TANF Period: 1996-98. Welfare participation declined by roughly 33 percent between 1996 and 1998, and TANF was a major contributing factor. Roughly one-third of the decline is due to TANF. Economic factors are still important in drawing people off welfare, but since the unemployment rate has declined relatively little since 1996, it accounts for just 8 to 10 percent of the decline in participation over this period. Higher minimum wages accounted for about 10 percent of the drop in participation, and reductions in cash benefits accounted for an additional 1 to 5 percentdecline. The remaining share is unexplained and may be due to other changes in policy, practice, or behavior. ALTERNATIVE SPECIFICATIONS Several alternative specifications were estimated to examine the robustness of the findings, and some of these results are reported in Table 4. All of the models in Table 4 include state-specific time trends, and the estimates from Model 1 of Table 2 ("Baseline") are listed for comparison. It has been argued that analyses of waiver policies should not utilize population weights (Martini and Wiseman, 1997). Comparison 1 demonstrates that the effects of waivers, TANF, cash benefits, and the unemployment rate are not very sensitive to whether weighting is used. However, the effects of the minimum wage are substantially larger when the weights are not used. Quite often it is said that welfare reform would not have been as effective in reducing caseloads if it had not been for the strength of the labor market. This hypothesis is tested in Comparison 2 by 15 Recall that the minimum wage measure used in the analysis is theveighted average of the minimum wages in effect in the state in the given year, where the weights are equal to the share of the year that the respective minimum was in effect. 20 Table 4. Alternative Specifications of Model 1 (Coefficient estimates are multiplied by 100) Comparison 1 Comparison 2 Comparison 3 Comparison 4 Comparison 5 Baseline Without Policy & Economy Changing Economic Effects With Leads of Population as an Model 1 Population Weights Interactions Model A Model B TANF and Waivers Explanatory Variable Beta t-stat Beta t-stat Beta t-stat Beta t-stat Beta t-stat Beta t-stat Beta t-stat Any waiver -9.40 2.90 -7.34 2.95 -1.90 0.21 -8.86 2.42 -9.34 2.54 -5.53 1.82 -8.29 3.01 Any waiver, lead -6.84 2.39 TANF -18.84 4.37 -18.04 2.38 -46.23 2.77 -21.28 4.23 -22.07 4.14 -15.19 3.20 -15.94 3.94 TANF, lead -4.84 1.19 Log max. monthly benefit 14.98 1.93 20.92 3.34 -5.44 0.78 -6.99 0.87 -6.10 0.75 14.91 1.95 29.06 4.27 Log monthly min. wage -39.59 4.02 -67.31 4.01 -53.00 3.73 -51.59 3.81 -47.44 3.44 -40.28 4.26 -15.14 1.48 Unemployment rate Current -0.36 0.74 0.63 1.36 3.21 8.51 3.17 8.80 -0.26 0.54 0.74 1.70 One lag 1.50 2.40 1.80 3.23 1.51 2.44 1.25 2.31 Two lags 4.27 8.92 3.66 8.12 4.17 8.78 2.68 6.04 Current*1976-80 1.48 1.93 Current*1981-86 3.20 7.97 Current*1987-92 3.87 6.03 Current*1993-98 4.37 3.54 Waiver*Current -1.01 0.63 TANF*Current 5.32 1.57 Log(Population under 65) -136.77 4.62 All models include state effects, year effects, and state-specific time trends. Estimates use the population under 65 as weights and robust calculation of standard errors, except in Comparison 1 where the weights are not used. interacting the unemployment rate with the waiver indicator and with the TANF indicator.⁶ Although the precision of the estimate of the interaction between TANF and the unemployment rate is slightly below standard levels for determining statistical significance (with a p-value of 0.12), the coefficient estimate implies that TANF policy is more effective when unemployment is low. For example, after adjusting for other factors, TANF is estimated to reduce participation by 14.8 percent if the unemployment rate were 5.9 (as it was in California when it implemented TANF in 1998) and by 20.2 percent if the unemployment rate were 4.9 (as it was in Michigan when it implemented TANF in 1996). It has been argued that the effects of waivers may be accounted for by an increase in the sensitivity of the caseload to labor market conditions in the 1990s (Moffitt, 1999). For this argument to hold, economic conditions must be correlated with waivers, the caseload must have become more sensitive to the unemployment rate over time, and the model must not have allowed the effects of the economic factors to change over time. Comparison 3 (Model B) tests this hypothesis by allowing the effects of the unemployment rate to differ between four periods: 1976-80, 1981-86, 1987-92, and 1993-98. (While Model B allows the effects of unemployment to vary across time, it does not include lagged unemployment effects. Therefore, the baseline model, which does not incorporate time-varying unemployment effects, is re-estimated with no lags in unemployment so that proper comparisons can be made. This specification appears asModel A in Comparison 3.) Indeed, the caseload has become more sensitive over the past two decades. A one percentage point increase in unemployment led to an increase in welfare participation of 1.5 percent in the 1976-80 period, 3.2 percent in the 1981-86 period, 3.9 percent from 1987-92, and 4.4 percent since 1993. (The 1976-80 period is statistically significantly different from each of the other three periods, but the three latter periods are not statistically significantly different from each other.) This rise may be due to the fact that most of the changes to AFDC introduced by waivers and TANF emphasize employment. This also suggests that the estimates of the contribution of the unemployment rate reported in Table 4may be a lower bound. Most importantly for this study, however, the effects of waivers and TANF are robust to this ¹⁶ln reality, people who make such statements are sometimes referring to the direct effect of labor market conditions on participation, and not the interaction. 21 specification, changing very little from the baseline model. Comparison 4 permits "lead" effects of TANF and waivers. The 1997 CEA study argued that welfare policies may begin to have an effect on behavior in the year leading up to their enactment because of the heightened awareness generated by the debate surrounding their passage. Indeed, the 1997 study found that state caseloads were declining significantly in the year prior to receiving approval for a waiver. The estimates with the data through 1998 and incorporating TANF imply a fairly large and statistically significant association between welfare participation and the one-year lead of waivers; the lead of TANF is not significant. However, it is difficult to interpret these estimates. While a true causal interpretation is plausible, an alternative interpretation is that the leads are picking up unobserved differences across states or within states across time. For example, perhaps states with recently declining caseloads (or caseloads declining more -- or increasing less - than expected) had slack resources and manpower to design and submit a waiver. In this case, waivers themselves may not be causing the decline. For this reason, the estimates without the leads are emphasized.⁷ The final alternative specification, Comparison 5, uses a less restrictive functional form by using the population variable as an explanatory variable instead of using it as the denominator in the dependent variable. In this model the dependent variable is simply the natural log of the number of recipients. The results are fairly stable to this specification change. However, the coefficient estimate on the minimum wage, while still negative, is reduced, and it has a p-value of 0.14. CONCLUSIONS There has been an unprecedented decline in welfare caseloads. The drop has occurred in every state in the nation, and it has persisted now for almost 5 years. In the earlier years, from 1993 to 1996, most of the decline was due to the strong labor market and welfare waivers. The declines in the more recent period, from 1996 to 1998, have been very large, and the single most important factor that can 17 Models that include lagged values of the waiver and TANF indicator variables were also examined to determine whether there was an effect of these policy changes above and beyond the initial-year change. Although in some specifications there were substantial lagged effects the estimates were quite sensitive to specification, especially sample weighting and inclusion of data from California and New York. 22 be identified is the implementation of TANF. PRWORA produced a dramatic change in welfare policy: work and self-sufficiency became a primary goal; state and local governments were given much greater control of the programs they ran; and states experimented with a host of program design changes. The evidence suggests that these changes have caused a large drop in welfare participation, a drop that is independent of the effects of the strong labor market during this period. The estimates imply that TANF alone has accounted for roughly one-third of the reduction from 1996-98. The strong labor market has made work opportunities relatively more attractive, drawing people off welfare and into jobs. In fact, the size of the caseload has become more sensitive to labor market changes in recent periods. However, the unemployment rate has not declined as much in the post- TANF period (1996-98) as it did in the 1993-96 waiver period. As a result, the share of the decline in the caseload that is attributable to improvements in the labor market was much larger in the 1993-96 period (roughly 26 to 36 percent) than in the 1996-98 period (8 to 10 percent). While this study helps to explain the post-TANF changes in welfare participation, there is much about welfare participation that is unknown. In most models that were estimated, a large share of the variation over time could not be explained. The variation across states in welfare policy and management has increased as a result of TANF, and the research community will struggle to keep abreast of these changes. Merely documenting the changes, let alone understanding their effects on caseloads, work, self-sufficiency, childwell-being and the like, is a major challenge. 23 Appendix A Comparison with the 1997 CEA Study A replication of the estimates reported in the 1997 CEA study is provided in Table A2. There are five reasons why the "old" estimates may differ from the "new" estimates: 1. different time periods of analysis 2. different variables included in the models 3. use of approval vs implementation date of waivers 4. use of calendar VS fiscal year data 5. use of population under 65 instead of all population in calculating participation rates. All models in Table A2 analyze the 1976-1996 period and include the same explanatory variables. Comparison between the "old CEA" estimates and the estimates in Model I of Table A2 shows that the effects of waivers are larger when calendar year data is used instead of fiscal year data. This finding is not surprising because the caseload continued to decline at the end of 1996, and some of this decline is attributed to waivers in Model I.⁸ Table A2 also demonstrates that the effects of waivers is somewhat smaller when the implementation date (Model IV) is used instead of the approval date (Model II). Use of the population under 65 (Model IV) instead of the total population (Model III) in the denominator of the recipiency rate alters the results very little. Although the use of the implementation date instead of the approval date and a different population control does not alter our results substantially, two other choices do. First, we include a second lag of the unemployment rate in our models in the current study (Table 2). The effect of the second lag is quite large and precisely estimated. It turns out that the inclusion of the second lag explains an important difference in the reported results between the two studies. With only one lag in unemployment, the 1997 study found that unemployment could explain 45 percent of the change in 18 Some of the effects of waivers in 1996 may be picking up the effects of PRWORA, or the heightened public awareness of reform prior to PRWORA (Moffitt, 1999). Re-estimating Model IV in Table A2 without 1996 data leads to a coefficient on the waiver dummy of -3.65 (t-statistic of 1.60). 24 participation from 1993-96. (See Table 3, column labeled (3), in the 1997 report.) Using the 1976- 1998 data, and the full specification reported as Model 1 in Table 2 but without the second lag in unemployment, we find results that are almost identical to those reported in the 1997 study: unemployment explains 42 percent of the change between 1993 and 1996. But with the second lag included, the share explained by unemployment falls to 26 percent. Therefore, the specification of the lag structure does alter the results from the simulations. However, the effects of waivers change very little with the specification of the lag structure of unemployment: the share explained by waivers between 1993-96 based on Model 1 in Table 2 is approximately 15 percent with either one or two lags. The studies also differ in their findings regarding the importance of waivers. However, the primary difference is not due to different estimates within the same specification, but in the choice of which specification to emphasize. The 1997 study emphasized results from a specification that included a lead value of the waiver variables (model 6 in Table 2 of the 1997 report) while the current study emphasizes models that exclude the leads (model 3 in Table 2 of the 1997 report). As described in the 1997 technical report, " it may be that the waiver application process, the publicity surrounding it, and potential changes in case workers' behavior and attitudes may provide a signal to potential recipients that the environment in which the welfare system operates is about to change. It may lead some individuals contemplating applying for benefits to find other sources of income support, whether from work or elsewhere (p. 15)." While this is a plausible scenario, an alternative interpretation is that the leads are picking up unobserved differences across states or within states across time. For example, perhaps states with recently declining caseloads (or caseloads declining more -- or increasing less - than expected) had slack resources and manpower to design and submit a waiver. For this reason, the current study uses the simple contemporaneous value for waivers and TANF. Excluding the leads does not change the estimates of the effect of unemployment rates. However, the waiver effects are substantially smaller without the leads. As reported in Table 3 of the 1997 study, the share of the 1993-96 change explained by waivers falls from 31 percent if the leads are included to 13 percent if the leads are not included. The 13 percent estimate in the 1997 study is comparable to 25 the estimate of 14.6 percent in Table 3 of the current study. Other than these differences, the updated study is quite consistent with the earlier report. Most importantly, strong labor markets, as measured by the unemployment rate, and welfare waivers played important roles in explaining the declines from 1993-96. The new study builds on the 1997 report and finds that TANF has had an even more profound effect on participation than did waivers. 26 Table A1. Dates of TANF Implementation and Major Welfare Waivers Date of First Major Waiver TANF Implementation Approval Implementation Official Actual, if Different from Official Alabama November-96 Alaska July-97 Arizona May-95 November-95 October-96 Arkansas April-94 July-94 July-97 California October-92 December-92 November-96 January-98 Colorado July-97 Connecticut August-94 January-96 October-96 Delaware May-95 October-95 March-97 DC March-97 Florida June-96 October-96 Georgia November-93 January-94 January-97 Hawaii June-94 February-97 July-97 Idaho August-96 July-97 Illinois November-93 November-93 July-97 Indiana December-94 May-95 October-96 lowa August-93 October-93 January-97 Kansas October-96 Kentucky October-96 Louisiana January-97 Maine June-96 November-96 Maryland August-95 March-96 December-96 Massachusetts August-95 November-95 September-96 Michigan August-92 October-92 September-96 Minnesota July-97 Mississippi September-95 October-95 October-96 July-97 Missouri April-95 June-95 December-96 Montana April-95 February-96 February-97 Nebraska February-95 October-95 December-96 Nevada December-96 New Hampshire June-96 October-96 New Jersey July-92 October-92 February-97 July-97 New Mexico July-97 New York December-96 November-97 North Carolina February-96 July-96 January-97 North Dakota July-97 Ohio March-96 July-96 October-96 Oklahoma October-96 Oregon July-92 February-93 October-96 Pennsylvania March-97 Rhode Island May-97 South Carolina May-96 October-96 South Dakota March-94 June-94 December-96 Tennessee July-96 September-96 October-96 Texas March-96 June-96 November-96 Utah October-92 January-93 October-96 Vermont April-93 July-94 September-96 Virginia July-95 July-95 February-97 Washington September-95 January-96 January-97 West Virginia January-97 Wisconsin June-94 January-96 September-96 September-97 Wyoming January-97 * New Mexico implemented its TANF program in July 1997. It was found unconstitutional in September 1997. A revised TANF program was implemented in April 1998. Table A2. "Old CEA" Compared with "New CEA" for the 1976-1996 Period (Coefficient estimates multiplied by 100) New CEA Old CEA Model I Model II Model III Model IV Beta t-statistic Beta t-statistic Beta t-statistic Beta t-statistic Beta t-statistic Any waiver -5.17 2.97 -6.74 3.33 -6.81 3.33 -5.66 2.67 -5.71 2.67 Unemployment Current -0.90 2.09 -0.58 1.18 -0.63 1.28 -0.61 1.24 -0.66 1.33 Lagged 4.97 11.83 4.60 9.50 4.66 9.52 4.61 9.47 4.67 9.49 Log max. monthly benefit 7.93 1.65 6.57 1.02 5.75 0.88 7.06 1.09 6.23 0.96 Years 1976-1996 1976-1996 1976-1996 1976-1996 1976-1996 Date of waivers Approval Approval Approval Implementation Implementation Population All All Under 65 All Under 65 Calendar vs fiscal Fiscal Calendar Calendar Calendar Calendar All models include state effects, year effects, and state-specific time trends. "Old CEA" refers to the estimates for Model 3 in Table 2 of the 1997 CEA report. To be consistent with the 1997 CEA report, the waiver in West Virginia is assumed to be a "major" waiver. References Bartik, Timothy J., and Randall W. Eberts (1998). "Examining the Effect of Industry Trends and Structure on Welfare Caseloads," mimeograph, November, W.E. Upjohn Institute for Employment Research. Bernstein, Jared, and John Schmitt (1998). Making Work Pay: The Impact of the 1996-97 Minimum Wage Increase. Economic Policy Institute, Washington, D.C. Blank, Rebecca M. (1997). "What Causes Public Assistance Caseloads to Grow?" National Bureau of Economic Research Working Paper No. 6343. Blank, Rebecca M., and Patricia Ruggles (1996). "When Do Women Use AFDC and Food Stamps? The Dynamics of Eligibility VS. Participation, "Journal of Human Resources, 31(1): 57-89. Brown, Charles, Curtis Gilroy, and Andrew Kohen. (1982). "The Effects of the Minimum Wage on Employment and Unemployment," Journal of Economic Literature, 20(June): 487-528. Card, David (1992a). "Using Regional Variation in Wages to Measure the Effects f the Federal Minimum Wage," Industrial and Labor Relations Review, 46(1): 22-37 Card, David (1992b). "Do Minimum Wages Reduce Employment? A Case Study of California, 1987- 1989," Industrial and Labor Relations Review, 46(1): 38-54 Card, David, Lawrence F. Katz, and Alan B. Krueger (1994). "Comment on David Neumark and William Wascher, "Employment Effects of Minimum andSubminimum Wages: Panel Data on State Minimum Wage Laws," Industrial and Labor Relations Review, 47(3): 487-496. Card, David, and Alan B. Krueger (1998). "A Reanalysis of the Effect of the New Jersey Minimum 27 Wage Increase on the Fast-Food Industry with Representative Payroll Data," National Bureau of Economic Research Working Paper 6386. Council of Economic Advisers (1997). "Explaining the Decline in Welfare Receipt, 1993-1996: Technical Report," Executive Office of the President of the United States. Figlio, David N., and James P. Ziliak (1998). "Welfare Reform, the Business Cycle, and the Decline in AFDC Caseloads," mimeograph, October, University of Florida. Gallagher, L. Jerome, Megan Gallagher, KevinPerese, Susan Schreiber, and Keith Watson (1998). "One Year after Federal Welfare Reform: A Description of State Temporary Assistance for Needy Families (TANF) Decisions as of October 1997, Urban Institute Occasional Paper Number 6. Katz, Lawrence F., and Alan B. Krueger (1992). "The Effect of the Minimum Wage on the Fast-Food Industry," Industrial and Labor Relations Review, 46(1): 6-21. Levine, Phillip B. and Diane M. Whitmore (1998). "The Impact of Welfare Reform on the AFDC Caseload," National Tax Association Proceedings - 1997. Washington, DC: National Tax Association, pp. 24-33. Martini, Alberto, and Michael Wiseman (1997). "Explaining the Recent Decline in Welfare Caseloads: Is the Council of Economic Advisers Right?" mimeograph, July, Urban Institute. Moffitt, Robert A. (1999). "The Effects of Pre-PRWORA Waivers on AFDC Caseloads and Female Earnings, Income, and Labor Force Behavior," mimeograph, May, Johns Hopkins University. Neumark, David, and William Wascher (1997). "The New Jersey-Pennsylvania Minimum Wage Experiment: A Re-Evaluation Using Payroll Records," mimeo, March, Michigan State University. Neumark, David, and William Wascher (1992). "Employment Effects of Minimum and Subminimum 28 Wages: Panel Data on State Minimum Wage Laws," 'Industrial and Labor Relations Review, 46(1): 55-81. Neumark, David, and William Wascher (1994). "Employment Effects of Minimum and Subminimum Wages: Reply to Card, Katz, and Krueger," Industrial and Labor Relations Review, 47(3): 497-512. Page, Marianne E., Joanne Spetz, and Jane Millar (1999). "Does the Minimum Wage Affect Welfare Caseloads?" mimeograph, Public Policy Institute of California. Scholz, John Karl (1994). "The Earned Income Tax Credit: Participation, Compliance, and Antipoverty Effectiveness," National Tax Journal, 59-81. Stapelton, David C., Gina Livermore, and Adam Tucker (1998). "Determinants of AFDC Caseload Growth," report by the Lewin Group to the Assistant Secretary for Planning and Evaluation, Department of Health and Human Services. July 1997. Turner, Mark (1999). "The Effects of Minimum Wages on Welfare Recipiency," mimeo, June, Urban Institute and Johns Hopkins University. Wallace, Geoffrey, and Rebecca M. Blank (1998). "What Goes Up Must Come Down? Explaining Recent Changes in Public Assistance Caseloads, "mimeograph, Northwestern University Department of Economics. Ziliak, James P., David N. Figlio, Elizabeth E. Davis, and Laura S. Connolly. (1997). "Accounting for the Decline in AFDC Caseloads: Welfare Reform or Economic Growth," Institute for Research on Poverty Discussion Paper No. 1151-97, University of Wisconsin. 29