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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]
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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
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