Statistical Adjustment Model Summary for Wisconsin

This is a summary of the key elements derived from the statistical adjustment models developed for PY 2020-2021. For each individual performance indicator there are plots that show how the actual level of performance for Wisconsin in PY 2018 compared to all states and how the predicted level of performance (i.e., Estimate0) for Wisconsin in PY 2020 compares to the predicted levels for all states. There are also tables that give all the relevant model estimates and pre-PY 2020 data for all of the model variables. In addition, the last tab has a table that identifies all the variables included in each individual indicator model.

Adult

Specific model data for each performance indicator in the Adult program are below.

Employment Rate 2nd Quarter after Exit

For this indicator, the tables below show the estimates for each of the variables in the statistical adjustment model and the related actual data. This data is used to determine the predicted level of performance for PY 2020 that is shown in the plot above. The PY 2020 prediction of 79.1% for Wisconsin for this performance indicator is calculated by summing the Variable Estimate0 values (total of 0.671) and the specific state fixed effect for this model (0.119).

Definitions of the terms used in the table below:

  • Coefficient - the effect (or weight) of the variable.
  • PY Prior - the actual data for each variable for this state prior to PY 2020.
  • Variable Estimate0 - the amount the variable contributed to the pre-PY 2020 predicted target for this indicator as used as a factor in negotiations. It is calculated by multiplying the Coefficient by the PY Prior.
Model Variable Estimates
Variable Type Variable Coefficient Pre-PY Variable Estimate0
Participant Characteristic Female 0.1302 0.5157 6.71%
Age 25 to 44 -0.0308 0.5761 -1.78%
Age 45 to 54 -0.1545 0.1598 -2.47%
Age 55 to 59 -0.0779 0.0561 -0.44%
Age 60 or more -0.5993 0.0238 -1.43%
Hispanic Ethnicity 0.0815 0.0928 0.76%
Race: Asian -0.2333 0.0319 -0.74%
Race: Black 0.0861 0.3059 2.63%
Race: Hawaiian or Pacific Islander -0.1320 0.0024 -0.03%
Race: American Indian 0.0501 0.0366 0.18%
Race: Multiple -0.1183 0.0233 -0.28%
Highest Grade Completed: High School Equivalency -0.1257 0.5357 -6.73%
Highest Grade Completed: Some College -0.1221 0.1518 -1.85%
Highest Grade Completed: Certificate or Other Post-Secondary Degree 0.0978 0.0490 0.48%
Highest Grade Completed: Associate Degree -0.0773 0.0837 -0.65%
Highest Grade Completed: Bachelor Degree 0.1722 0.0685 1.18%
Highest Grade Completed: Graduate Degree -0.1430 0.0195 -0.28%
Employed at Program Entry 0.1964 0.3744 7.35%
In School at Program Entry 0.1265 0.1632 2.06%
Individual with a Disability -0.1813 0.0861 -1.56%
Veteran 0.2901 0.0480 1.39%
Limited English Proficiency -0.0306 0.0328 -0.10%
Single Parent -0.0942 0.3168 -2.99%
Low Income 0.0081 0.7655 0.62%
Homeless -0.0534 0.0452 -0.24%
Individual who was Incarcerated 0.1550 0.2184 3.38%
Displaced Homemaker -0.1842 0.0100 -0.18%
Received Wages 2 Quarters Prior to Participation 0.1889 0.6413 12.12%
Long-Term Unemployed at Program Entry 0.0157 0.1822 0.29%
UI Claimant -0.0148 0.1717 -0.25%
UI Exhaustee 0.1394 0.0214 0.30%
Supportive Services Recipient 0.0620 0.0500 0.31%
Received Needs-related Payments 0.4886 0.0000 0.00%
Received Other Public Assistance -0.0494 0.1056 -0.52%
SSI or SSDI Recipient -0.0205 0.0538 -0.11%
TANF Recipient 0.0438 0.0528 0.23%
Received Wagner-Peyser Act Services 0.0220 0.1499 0.33%
Median Days in Program -0.0002 177.0000 -3.24%
Economic Condition Natural Resources Employment 2.1266 0.0111 2.35%
Construction Employment 0.8615 0.0437 3.76%
Manufacturing Employment 0.1897 0.1670 3.17%
Information Services Employment -5.3312 0.0170 -9.08%
Financial Services Employment -4.8664 0.0522 -25.41%
Professional and Business Services Employment 3.7575 0.1139 42.80%
Educational or Health Care Employment 0.8235 0.2235 18.41%
Leisure, Hospitality, or Entertainment Employment -0.8923 0.1021 -9.11%
Other Services Employment 4.5274 0.0293 13.28%
Public Administration 2.2149 0.0474 10.51%
Unemployment Rate Not Seasonally Adjusted 0.6822 0.0293 2.00%

Median Earnings 2nd Quarter after Exit

For this indicator, the tables below show the estimates for each of the variables in the statistical adjustment model and the related actual data. This data is used to determine the predicted level of performance for PY 2020 that is shown in the plot above. The PY 2020 prediction of $6,410 for Wisconsin for this performance indicator is calculated by summing the Variable Estimate0 values (total of 40553) and the specific state fixed effect for this model (-34143).

Definitions of the terms used in the table below:

  • Coefficient - the effect (or weight) of the variable.
  • PY Prior - the actual data for each variable for this state prior to PY 2020.
  • Variable Estimate0 - the amount the variable contributed to the pre-PY 2020 predicted target for this indicator as used as a factor in negotiations. It is calculated by multiplying the Coefficient by the PY Prior.
Model Variable Estimates
Variable Type Variable Coefficient Pre-PY Variable Estimate0
Participant Characteristic Female -2841.0668 0.5249 -$1,491
Age 25 to 44 -862.0930 0.5826 -$502
Age 45 to 54 -3144.2089 0.1488 -$468
Age 55 to 59 -5290.3216 0.0577 -$305
Age 60 or more -6059.0062 0.0207 -$125
Hispanic Ethnicity 232.4254 0.0966 $22
Race: Asian -4413.8578 0.0286 -$126
Race: Black -2324.8593 0.2965 -$689
Race: Hawaiian or Pacific Islander -6352.7320 0.0024 -$15
Race: American Indian -2692.4326 0.0371 -$100
Race: Multiple 6983.7945 0.0225 $157
Highest Grade Completed: High School Equivalency 362.0217 0.5286 $191
Highest Grade Completed: Some College 826.8902 0.1640 $136
Highest Grade Completed: Certificate or Other Post-Secondary Degree -1324.3050 0.0504 -$67
Highest Grade Completed: Associate Degree 5643.1853 0.0863 $487
Highest Grade Completed: Bachelor Degree 4052.0797 0.0717 $290
Highest Grade Completed: Graduate Degree 8539.9365 0.0176 $150
Employed at Program Entry 965.0801 0.4113 $397
In School at Program Entry 3623.2012 0.1725 $625
Individual with a Disability -989.2237 0.0741 -$73
Veteran -1349.3089 0.0462 -$62
Limited English Proficiency -4419.8922 0.0298 -$132
Single Parent 145.7630 0.3177 $46
Low Income -332.4067 0.7424 -$247
Homeless -446.4262 0.0437 -$20
Individual who was Incarcerated 2013.3031 0.2072 $417
Displaced Homemaker -1947.9185 0.0073 -$14
Received Wages 2 Quarters Prior to Participation 807.6246 0.7114 $575
Wages 2 Quarters Prior to Participation 0.3653 4365.0000 $1,594
Long-Term Unemployed at Program Entry 2011.8227 0.1476 $297
UI Claimant 685.8891 0.1956 $134
UI Exhaustee -2567.3504 0.0213 -$55
Supportive Services Recipient 912.9138 0.0504 $46
Received Needs-related Payments 15112.5289 0.0000 $0
Received Other Public Assistance 107.5299 0.0954 $10
SSI or SSDI Recipient -5911.8510 0.0334 -$198
TANF Recipient 840.8641 0.0468 $39
Received Wagner-Peyser Act Services -205.4928 0.1580 -$32
Median Days in Program 3.2489 171.0000 $556
Economic Condition Natural Resources Employment 24063.8444 0.0111 $266
Construction Employment 32326.4938 0.0437 $1,411
Manufacturing Employment 39237.2625 0.1670 $6,553
Information Services Employment -48189.2565 0.0170 -$821
Financial Services Employment 4074.2901 0.0522 $213
Professional and Business Services Employment 96754.4484 0.1139 $11,021
Educational or Health Care Employment 56163.1547 0.2235 $12,553
Leisure, Hospitality, or Entertainment Employment 57668.0011 0.1021 $5,889
Other Services Employment 10767.7935 0.0293 $316
Public Administration 39658.6388 0.0474 $1,882
Unemployment Rate Not Seasonally Adjusted -6106.3827 0.0293 -$179

Measurable Skill Gains

For this indicator, the tables below show the estimates for each of the variables in the statistical adjustment model and the related actual data. This data is used to determine the predicted level of performance for PY 2020 that is shown in the plot above. The PY 2020 prediction of 43.1% for Wisconsin for this performance indicator is calculated by summing the Variable Estimate0 values (total of 7.619) and the specific state fixed effect for this model (-7.188).

Definitions of the terms used in the table below:

  • Coefficient - the effect (or weight) of the variable.
  • PY Prior - the actual data for each variable for this state prior to PY 2020.
  • Variable Estimate0 - the amount the variable contributed to the pre-PY 2020 predicted target for this indicator as used as a factor in negotiations. It is calculated by multiplying the Coefficient by the PY Prior.
Model Variable Estimates
Variable Type Variable Coefficient Pre-PY Variable Estimate0
Participant Characteristic Female -0.3614 0.5217 -18.85%
Age 25 to 44 0.5218 0.5667 29.57%
Age 45 to 54 -0.0702 0.1262 -0.89%
Age 55 to 59 -0.9975 0.0330 -3.29%
Age 60 or more 2.9217 0.0201 5.87%
Hispanic Ethnicity -1.4456 0.0989 -14.29%
Race: Asian 2.1310 0.0362 7.71%
Race: Black -0.5671 0.2412 -13.68%
Race: American Indian 0.8520 0.0394 3.36%
Race: Multiple 1.9759 0.0330 6.51%
Highest Grade Completed: High School Equivalency -0.1218 0.5740 -6.99%
Highest Grade Completed: Some College -0.1842 0.1423 -2.62%
Highest Grade Completed: Certificate or Other Post-Secondary Degree 0.0731 0.0490 0.36%
Highest Grade Completed: Associate Degree -0.8544 0.0675 -5.77%
Highest Grade Completed: Bachelor Degree -0.2005 0.0740 -1.48%
Highest Grade Completed: Graduate Degree 1.8387 0.0121 2.22%
Employed at Program Entry 0.3647 0.4260 15.54%
In School at Program Entry -0.3045 0.2098 -6.39%
Individual with a Disability -0.2611 0.1133 -2.96%
Veteran 0.2508 0.0394 0.99%
Limited English Proficiency 0.8810 0.0418 3.68%
Single Parent 0.2135 0.3031 6.47%
Individual who was Incarcerated 0.7809 0.2170 16.95%
Received Wages 2 Quarters Prior to Participation -0.0013 0.7002 -0.09%
Long-Term Unemployed at Program Entry 0.0652 0.1608 1.05%
UI Exhaustee 0.0104 0.0145 0.01%
Supportive Services Recipient -0.1297 0.0860 -1.12%
SSI or SSDI Recipient 0.4929 0.0338 1.66%
TANF Recipient -0.2848 0.0410 -1.17%
Received Wagner-Peyser Act Services 0.0732 0.1037 0.76%
Median Days in Program 0.0004 208.5000 7.39%
Median Days Enrolled in Education or Training -0.0002 107.0000 -2.61%
Percent Enrolled in Education or Training Under 30 Days -0.0087 0.1503 -0.13%
Economic Condition Natural Resources Employment 10.0155 0.0111 11.07%
Construction Employment 8.9287 0.0437 38.98%
Manufacturing Employment 12.1240 0.1670 202.48%
Information Services Employment -43.8313 0.0170 -74.69%
Financial Services Employment 31.7234 0.0522 165.68%
Professional and Business Services Employment 7.5758 0.1139 86.29%
Educational or Health Care Employment 9.9286 0.2235 221.91%
Leisure, Hospitality, or Entertainment Employment 2.5813 0.1021 26.36%
Other Services Employment 32.8685 0.0293 96.42%
Public Administration -0.1431 0.0474 -0.68%
Unemployment Rate Not Seasonally Adjusted -13.5535 0.0293 -39.68%

Dislocated Worker

Specific model data for each performance indicator in the Dislocated Worker program are below.

Employment Rate 2nd Quarter after Exit

For this indicator, the tables below show the estimates for each of the variables in the statistical adjustment model and the related actual data. This data is used to determine the predicted level of performance for PY 2020 that is shown in the plot above. The PY 2020 prediction of 84.8% for Wisconsin for this performance indicator is calculated by summing the Variable Estimate0 values (total of -1.741) and the specific state fixed effect for this model (2.589).

Definitions of the terms used in the table below:

  • Coefficient - the effect (or weight) of the variable.
  • PY Prior - the actual data for each variable for this state prior to PY 2020.
  • Variable Estimate0 - the amount the variable contributed to the pre-PY 2020 predicted target for this indicator as used as a factor in negotiations. It is calculated by multiplying the Coefficient by the PY Prior.
Model Variable Estimates
Variable Type Variable Coefficient Pre-PY Variable Estimate0
Participant Characteristic Female 0.0596 0.5867 3.50%
Age 25 to 44 0.0189 0.4098 0.78%
Age 45 to 54 -0.0169 0.3204 -0.54%
Age 55 to 59 0.1060 0.1567 1.66%
Age 60 or more -0.1905 0.0915 -1.74%
Hispanic Ethnicity 0.1185 0.0583 0.69%
Race: Asian -0.2910 0.0236 -0.69%
Race: Black -0.0358 0.1664 -0.60%
Race: Hawaiian or Pacific Islander 0.8792 0.0014 0.12%
Race: American Indian -0.0983 0.0104 -0.10%
Race: Multiple -0.1947 0.0118 -0.23%
Highest Grade Completed: High School Equivalency -0.0259 0.4327 -1.12%
Highest Grade Completed: Some College -0.1942 0.1311 -2.55%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.1799 0.0513 -0.92%
Highest Grade Completed: Associate Degree -0.0907 0.1207 -1.09%
Highest Grade Completed: Bachelor Degree -0.1447 0.1359 -1.97%
Highest Grade Completed: Graduate Degree -0.1210 0.0631 -0.76%
Employed at Program Entry 0.1061 0.1054 1.12%
In School at Program Entry -0.0254 0.1234 -0.31%
Individual with a Disability -0.0527 0.0617 -0.33%
Veteran 0.0056 0.0520 0.03%
Limited English Proficiency -0.2521 0.0354 -0.89%
Single Parent 0.0446 0.1727 0.77%
Low Income -0.0518 0.2462 -1.28%
Homeless 0.0306 0.0028 0.01%
Individual who was Incarcerated 0.3775 0.0513 1.94%
Displaced Homemaker -0.2274 0.0229 -0.52%
Received Wages 2 Quarters Prior to Participation 0.1131 0.9064 10.25%
Long-Term Unemployed at Program Entry 0.0574 0.0839 0.48%
UI Claimant 0.0208 0.6969 1.45%
UI Exhaustee 0.0737 0.0319 0.24%
Supportive Services Recipient 0.0496 0.3128 1.55%
Received Needs-related Payments -0.4938 0.0000 0.00%
Received Other Public Assistance -0.1259 0.0021 -0.03%
SSI or SSDI Recipient 0.8134 0.0187 1.52%
TANF Recipient -0.5301 0.0104 -0.55%
Received Wagner-Peyser Act Services -0.0512 0.5798 -2.97%
Median Days in Program 0.0000 237.5000 0.19%
Economic Condition Natural Resources Employment -2.0224 0.0111 -2.24%
Construction Employment -0.4670 0.0437 -2.04%
Manufacturing Employment -1.7064 0.1670 -28.50%
Information Services Employment -9.8998 0.0170 -16.87%
Financial Services Employment -6.2744 0.0522 -32.77%
Professional and Business Services Employment -3.6027 0.1139 -41.04%
Educational or Health Care Employment -1.9946 0.2235 -44.58%
Leisure, Hospitality, or Entertainment Employment -2.8519 0.1021 -29.13%
Other Services Employment 3.0428 0.0293 8.93%
Public Administration 1.2295 0.0474 5.83%
Unemployment Rate Not Seasonally Adjusted 0.4118 0.0293 1.21%

Median Earnings 2nd Quarter after Exit

For this indicator, the tables below show the estimates for each of the variables in the statistical adjustment model and the related actual data. This data is used to determine the predicted level of performance for PY 2020 that is shown in the plot above. The PY 2020 prediction of $8,533 for Wisconsin for this performance indicator is calculated by summing the Variable Estimate0 values (total of 36308) and the specific state fixed effect for this model (-27775).

Definitions of the terms used in the table below:

  • Coefficient - the effect (or weight) of the variable.
  • PY Prior - the actual data for each variable for this state prior to PY 2020.
  • Variable Estimate0 - the amount the variable contributed to the pre-PY 2020 predicted target for this indicator as used as a factor in negotiations. It is calculated by multiplying the Coefficient by the PY Prior.
Model Variable Estimates
Variable Type Variable Coefficient Pre-PY Variable Estimate0
Participant Characteristic Female -1901.3415 0.5920 -$1,126
Age 25 to 44 1115.5154 0.4262 $475
Age 45 to 54 -125.9873 0.3242 -$41
Age 55 to 59 -2126.3785 0.1501 -$319
Age 60 or more -2492.9312 0.0771 -$192
Hispanic Ethnicity -857.7550 0.0564 -$48
Race: Asian -4684.9713 0.0232 -$109
Race: Black -1536.6027 0.1658 -$255
Race: Hawaiian or Pacific Islander -3269.1753 0.0017 -$5
Race: American Indian -3522.2138 0.0100 -$35
Race: Multiple -3712.0594 0.0116 -$43
Highest Grade Completed: High School Equivalency -1400.0970 0.4478 -$627
Highest Grade Completed: Some College -1902.9048 0.1244 -$237
Highest Grade Completed: Certificate or Other Post-Secondary Degree 83.4151 0.0498 $4
Highest Grade Completed: Associate Degree 1526.2402 0.1186 $181
Highest Grade Completed: Bachelor Degree 1169.4179 0.1327 $155
Highest Grade Completed: Graduate Degree 2155.0497 0.0580 $125
Employed at Program Entry 1700.7794 0.1078 $183
In School at Program Entry 3787.5103 0.1260 $477
Individual with a Disability 279.5931 0.0539 $15
Veteran 1445.8344 0.0431 $62
Limited English Proficiency -2976.1328 0.0357 -$106
Single Parent -784.4348 0.1774 -$139
Low Income -538.7097 0.2438 -$131
Homeless 7893.8250 0.0025 $20
Individual who was Incarcerated 1805.9783 0.0531 $96
Displaced Homemaker 192.7564 0.0216 $4
Received Wages 2 Quarters Prior to Participation 21.0817 0.9221 $19
Wages 2 Quarters Prior to Participation 0.0917 9101.0650 $834
Long-Term Unemployed at Program Entry 1348.3682 0.0771 $104
UI Claimant 68.6962 0.7023 $48
UI Exhaustee -2493.0132 0.0257 -$64
Supportive Services Recipient 176.1628 0.3035 $53
Received Needs-related Payments 6660.1906 0.0000 $0
Received Other Public Assistance 470.0451 0.0025 $1
SSI or SSDI Recipient -2105.8014 0.0116 -$24
TANF Recipient -4222.3011 0.0108 -$46
Received Wagner-Peyser Act Services -403.3425 0.5829 -$235
Median Days in Program 2.2222 223.0000 $496
Economic Condition Natural Resources Employment -27241.5941 0.0111 -$301
Construction Employment 36651.6742 0.0437 $1,600
Manufacturing Employment 47186.5858 0.1670 $7,880
Information Services Employment -260263.7041 0.0170 -$4,435
Financial Services Employment 85893.1957 0.0522 $4,486
Professional and Business Services Employment 95022.1320 0.1139 $10,823
Educational or Health Care Employment 51172.3083 0.2235 $11,437
Leisure, Hospitality, or Entertainment Employment 43978.6506 0.1021 $4,491
Other Services Employment -4546.6888 0.0293 -$133
Public Administration 22271.2780 0.0474 $1,057
Unemployment Rate Not Seasonally Adjusted -5795.6816 0.0293 -$170

Measurable Skill Gains

For this indicator, the tables below show the estimates for each of the variables in the statistical adjustment model and the related actual data. This data is used to determine the predicted level of performance for PY 2020 that is shown in the plot above. The PY 2020 prediction of 50.5% for Wisconsin for this performance indicator is calculated by summing the Variable Estimate0 values (total of 6.047) and the specific state fixed effect for this model (-5.542).

Definitions of the terms used in the table below:

  • Coefficient - the effect (or weight) of the variable.
  • PY Prior - the actual data for each variable for this state prior to PY 2020.
  • Variable Estimate0 - the amount the variable contributed to the pre-PY 2020 predicted target for this indicator as used as a factor in negotiations. It is calculated by multiplying the Coefficient by the PY Prior.
Model Variable Estimates
Variable Type Variable Coefficient Pre-PY Variable Estimate0
Participant Characteristic Female -0.1509 0.6225 -9.39%
Age 25 to 44 -0.0655 0.4851 -3.18%
Age 45 to 54 0.2414 0.3166 7.64%
Age 55 to 59 0.4579 0.1087 4.98%
Age 60 or more 0.9139 0.0550 5.02%
Hispanic Ethnicity -0.6646 0.0585 -3.89%
Race: Asian -0.5340 0.0323 -1.72%
Race: Black -0.3293 0.1039 -3.42%
Race: American Indian 2.6465 0.0143 3.79%
Race: Multiple 0.0503 0.0084 0.04%
Highest Grade Completed: High School Equivalency -0.1922 0.4385 -8.43%
Highest Grade Completed: Some College -0.2384 0.1326 -3.16%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.2607 0.0669 -1.74%
Highest Grade Completed: Associate Degree 0.2625 0.1266 3.32%
Highest Grade Completed: Bachelor Degree -0.1123 0.1470 -1.65%
Highest Grade Completed: Graduate Degree -0.4275 0.0406 -1.74%
Employed at Program Entry -0.0215 0.1529 -0.33%
In School at Program Entry -0.2643 0.1493 -3.95%
Individual with a Disability -1.4481 0.0502 -7.27%
Veteran -0.9235 0.0442 -4.08%
Limited English Proficiency 0.4514 0.0538 2.43%
Single Parent 0.3691 0.1959 7.23%
Individual who was Incarcerated 0.4693 0.0442 2.07%
Received Wages 2 Quarters Prior to Participation 0.0287 0.9211 2.64%
Long-Term Unemployed at Program Entry 0.3881 0.0657 2.55%
UI Exhaustee 0.3561 0.0215 0.77%
Supportive Services Recipient -0.0615 0.6595 -4.06%
SSI or SSDI Recipient -0.4356 0.0131 -0.57%
TANF Recipient -3.8716 0.0191 -7.40%
Received Wagner-Peyser Act Services -0.0963 0.4982 -4.80%
Median Days in Program -0.0003 292.0000 -9.38%
Median Days Enrolled in Education or Training -0.0003 129.0000 -3.53%
Percent Enrolled in Education or Training Under 30 Days 0.1620 0.1410 2.28%
Economic Condition Natural Resources Employment -8.0806 0.0111 -8.93%
Construction Employment 4.4493 0.0437 19.42%
Manufacturing Employment 9.8551 0.1670 164.59%
Information Services Employment -58.7056 0.0170 -100.04%
Financial Services Employment 12.1977 0.0522 63.70%
Professional and Business Services Employment 16.0554 0.1139 182.88%
Educational or Health Care Employment 7.1634 0.2235 160.11%
Leisure, Hospitality, or Entertainment Employment 1.5122 0.1021 15.44%
Other Services Employment 65.3154 0.0293 191.61%
Public Administration -2.8478 0.0474 -13.51%
Unemployment Rate Not Seasonally Adjusted -10.8237 0.0293 -31.69%

Youth

Specific model data for each performance indicator in the Youth program are below.

Employment Rate 2nd Quarter after Exit

For this indicator, the tables below show the estimates for each of the variables in the statistical adjustment model and the related actual data. This data is used to determine the predicted level of performance for PY 2020 that is shown in the plot above. The PY 2020 prediction of 78.9% for Wisconsin for this performance indicator is calculated by summing the Variable Estimate0 values (total of -1.106) and the specific state fixed effect for this model (1.894).

Definitions of the terms used in the table below:

  • Coefficient - the effect (or weight) of the variable.
  • PY Prior - the actual data for each variable for this state prior to PY 2020.
  • Variable Estimate0 - the amount the variable contributed to the pre-PY 2020 predicted target for this indicator as used as a factor in negotiations. It is calculated by multiplying the Coefficient by the PY Prior.
Model Variable Estimates
Variable Type Variable Coefficient Pre-PY Variable Estimate0
Participant Characteristic Female 0.0595 0.5134 3.05%
Age 14 to 15 0.1226 0.0158 0.19%
Age 16 to 17 -0.1436 0.1682 -2.42%
Age 18 to 19 -0.2054 0.4044 -8.31%
Age 20 to 21 0.0105 0.2125 0.22%
Hispanic Ethnicity -0.0628 0.1051 -0.66%
Race: Asian 0.1989 0.0292 0.58%
Race: Black -0.0414 0.2978 -1.23%
Race: Hawaiian or Pacific Islander -0.5342 0.0032 -0.17%
Race: American Indian -0.3341 0.0300 -1.00%
Race: Multiple 0.1508 0.0332 0.50%
Highest Grade Completed: High School Equivalency 0.0691 0.5292 3.66%
Highest Grade Completed: Some College -0.3127 0.0190 -0.59%
Highest Grade Completed: Certificate or Other Post-Secondary Degree 1.1469 0.0039 0.45%
Highest Grade Completed: Associate or Bachelor Degree 0.4935 0.0055 0.27%
Employed at Program Entry 0.2748 0.2820 7.75%
In School at Program Entry 0.0356 0.1580 0.56%
Individual with a Disability -0.0469 0.3207 -1.50%
Limited English Proficiency -0.1392 0.0292 -0.41%
Low Income 0.0375 0.8586 3.22%
Homeless -0.2008 0.0814 -1.63%
Individual who was Incarcerated 0.0635 0.1406 0.89%
Foster Care Youth -0.0100 0.0450 -0.05%
Youth Parent or Pregnant Youth -0.0716 0.2299 -1.65%
Skills/Literacy Deficient at Program Entry 0.0349 0.5877 2.05%
Long-Term Unemployed at Program Entry -0.0867 0.0063 -0.05%
UI Claimant -0.0433 0.0332 -0.14%
Supportive Services Recipient 0.0442 0.4676 2.07%
Received Needs-related Payments 0.7660 0.0000 0.00%
Received Other Public Assistance -0.1510 0.0348 -0.52%
SSI or SSDI Recipient 0.0743 0.0506 0.38%
TANF Recipient -0.0341 0.0355 -0.12%
Pell Grant Recipient 0.0368 0.0340 0.13%
Youth Needing Additional Assistance 0.0005 0.2962 0.01%
Received Wagner-Peyser Act Services 0.0148 0.0466 0.07%
Median Days in Program 0.0000 296.0000 -1.19%
Economic Condition Natural Resources Employment -6.7872 0.0111 -7.50%
Construction Employment -1.8800 0.0437 -8.21%
Manufacturing Employment -1.3602 0.1670 -22.72%
Information Services Employment -7.2974 0.0170 -12.44%
Financial Services Employment -2.1367 0.0522 -11.16%
Professional and Business Services Employment -2.5564 0.1139 -29.12%
Educational or Health Care Employment 0.0247 0.2235 0.55%
Leisure, Hospitality, or Entertainment Employment -0.3944 0.1021 -4.03%
Other Services Employment -10.7940 0.0293 -31.67%
Public Administration 3.2993 0.0474 15.65%
Unemployment Rate Not Seasonally Adjusted -1.4872 0.0293 -4.35%

Median Earnings 2nd Quarter after Exit

For this indicator, the tables below show the estimates for each of the variables in the statistical adjustment model and the related actual data. This data is used to determine the predicted level of performance for PY 2020 that is shown in the plot above. The PY 2020 prediction of $3,819 for Wisconsin for this performance indicator is calculated by summing the Variable Estimate0 values (total of 15132) and the specific state fixed effect for this model (-11313).

Definitions of the terms used in the table below:

  • Coefficient - the effect (or weight) of the variable.
  • PY Prior - the actual data for each variable for this state prior to PY 2020.
  • Variable Estimate0 - the amount the variable contributed to the pre-PY 2020 predicted target for this indicator as used as a factor in negotiations. It is calculated by multiplying the Coefficient by the PY Prior.
Model Variable Estimates
Variable Type Variable Coefficient Pre-PY Variable Estimate0
Participant Characteristic Female -1877.4943 0.5289 -$993.04
Age 14 to 15 -92.3013 0.0137 -$1.26
Age 16 to 17 -1309.0587 0.1661 -$217.49
Age 18 to 19 -1066.4762 0.4017 -$428.38
Age 20 to 21 649.4931 0.2103 $136.59
Hispanic Ethnicity 1913.4585 0.1083 $207.24
Race: Asian 649.7122 0.0294 $19.13
Race: Black -886.3703 0.3028 -$268.43
Race: Hawaiian or Pacific Islander -3388.4232 0.0042 -$14.25
Race: American Indian -184.4720 0.0294 -$5.43
Race: Multiple 933.1134 0.0358 $33.36
Highest Grade Completed: High School Equivalency 1383.9408 0.5521 $764.01
Highest Grade Completed: Some College -828.1913 0.0231 -$19.16
Highest Grade Completed: Certificate or Other Post-Secondary Degree 173.0955 0.0042 $0.73
Highest Grade Completed: Associate or Bachelor Degree 6672.3330 0.0063 $42.10
Employed at Program Entry 613.7857 0.3260 $200.08
In School at Program Entry 546.1994 0.1556 $85.00
Individual with a Disability -495.1811 0.3186 -$157.77
Limited English Proficiency 2456.3023 0.0294 $72.32
Low Income -305.7985 0.8412 -$257.24
Homeless 983.9044 0.0715 $70.35
Individual who was Incarcerated -1284.6596 0.1209 -$155.35
Foster Care Youth 1009.8293 0.0442 $44.60
Youth Parent or Pregnant Youth 854.5128 0.2366 $202.17
Skills/Literacy Deficient at Program Entry -283.4775 0.5783 -$163.95
Long-Term Unemployed at Program Entry -630.2664 0.0063 -$3.98
UI Claimant -462.5838 0.0336 -$15.57
Supportive Services Recipient 161.1750 0.4637 $74.74
Received Needs-related Payments 2823.2240 0.0000 $0.00
Received Other Public Assistance -184.0786 0.0315 -$5.81
SSI or SSDI Recipient -1658.7545 0.0347 -$57.56
TANF Recipient -539.6509 0.0347 -$18.73
Pell Grant Recipient 104.1843 0.0368 $3.83
Youth Needing Additional Assistance -4.3341 0.2797 -$1.21
Received Wagner-Peyser Act Services -27.8731 0.0494 -$1.38
Median Days in Program 0.5942 302.5000 $179.75
Economic Condition Natural Resources Employment -3172.1958 0.0111 -$35.06
Construction Employment 10994.4772 0.0437 $479.98
Manufacturing Employment 21559.9593 0.1670 $3,600.61
Information Services Employment -55465.6493 0.0170 -$945.16
Financial Services Employment 44805.1055 0.0522 $2,339.96
Professional and Business Services Employment 14219.0161 0.1139 $1,619.59
Educational or Health Care Employment 20372.0444 0.2235 $4,553.32
Leisure, Hospitality, or Entertainment Employment 7088.2477 0.1021 $723.89
Other Services Employment 57026.8505 0.0293 $1,672.93
Public Administration 43573.5139 0.0474 $2,067.40
Unemployment Rate Not Seasonally Adjusted -10090.2192 0.0293 -$295.41

Measurable Skill Gains

For this indicator, the tables below show the estimates for each of the variables in the statistical adjustment model and the related actual data. This data is used to determine the predicted level of performance for PY 2020 that is shown in the plot above. The PY 2020 prediction of 29.4% for Wisconsin for this performance indicator is calculated by summing the Variable Estimate0 values (total of 3.977) and the specific state fixed effect for this model (-3.684).

Definitions of the terms used in the table below:

  • Coefficient - the effect (or weight) of the variable.
  • PY Prior - the actual data for each variable for this state prior to PY 2020.
  • Variable Estimate0 - the amount the variable contributed to the pre-PY 2020 predicted target for this indicator as used as a factor in negotiations. It is calculated by multiplying the Coefficient by the PY Prior.
Model Variable Estimates
Variable Type Variable Coefficient Pre-PY Variable Estimate0
Participant Characteristic Female -0.2758 0.5378 -14.83%
Age 14 to 15 -0.8106 0.0227 -1.84%
Age 16 to 17 -0.9025 0.2293 -20.69%
Age 18 to 19 -0.6998 0.3885 -27.19%
Age 20 to 21 -1.6404 0.1811 -29.70%
Hispanic Ethnicity -0.0170 0.1274 -0.22%
Race: Asian -0.0162 0.0291 -0.05%
Race: Black 0.0042 0.3076 0.13%
Race: American Indian -0.1578 0.0264 -0.42%
Race: Multiple 1.9727 0.0419 8.26%
Highest Grade Completed: High School Equivalency -0.2692 0.4468 -12.03%
Highest Grade Completed: Some College 1.0513 0.0227 2.39%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.6449 0.0055 -0.35%
Highest Grade Completed: Associate or Bachelor Degree 1.9000 0.0036 0.69%
In School at Program Entry 0.0220 0.2675 0.59%
Skills/Literacy Deficient at Program Entry 0.1976 0.5369 10.61%
UI Claimant 0.0198 0.0264 0.05%
Supportive Services Recipient -0.0712 0.5086 -3.62%
Received Other Public Assistance 0.2742 0.0591 1.62%
SSI or SSDI Recipient 0.5536 0.0500 2.77%
Pell Grant Recipient -0.8864 0.0846 -7.50%
Received Wagner-Peyser Act Services -0.0503 0.0200 -0.10%
Median Days Enrolled in Education or Training -0.0003 122.0000 -3.98%
Percent Enrolled in Education or Training Under 30 Days -0.3441 0.1483 -5.10%
Economic Condition Natural Resources Employment 7.6282 0.0111 8.43%
Construction Employment 9.5740 0.0437 41.80%
Manufacturing Employment 5.8313 0.1670 97.39%
Information Services Employment -42.8136 0.0170 -72.96%
Financial Services Employment -14.2433 0.0522 -74.39%
Professional and Business Services Employment 14.4769 0.1139 164.90%
Educational or Health Care Employment 7.0634 0.2235 157.87%
Leisure, Hospitality, or Entertainment Employment 6.2993 0.1021 64.33%
Other Services Employment 50.8391 0.0293 149.14%
Public Administration -7.3408 0.0474 -34.83%
Unemployment Rate Not Seasonally Adjusted -1.1663 0.0293 -3.41%

Wagner-Peyser

Specific model data for each performance indicator in the Wagner-Peyser program are below.

Employment Rate 2nd Quarter after Exit

For this indicator, the tables below show the estimates for each of the variables in the statistical adjustment model and the related actual data. This data is used to determine the predicted level of performance for PY 2020 that is shown in the plot above. The PY 2020 prediction of 74.7% for Wisconsin for this performance indicator is calculated by summing the Variable Estimate0 values (total of 1.338) and the specific state fixed effect for this model (-0.591).

Definitions of the terms used in the table below:

  • Coefficient - the effect (or weight) of the variable.
  • PY Prior - the actual data for each variable for this state prior to PY 2020.
  • Variable Estimate0 - the amount the variable contributed to the pre-PY 2020 predicted target for this indicator as used as a factor in negotiations. It is calculated by multiplying the Coefficient by the PY Prior.
Model Variable Estimates
Variable Type Variable Coefficient Pre-PY Variable Estimate0
Participant Characteristic Female 0.0801 0.4820 3.86%
Age 25 to 44 0.1086 0.4203 4.56%
Age 45 to 54 -0.0860 0.2370 -2.04%
Age 55 to 59 -0.0070 0.1282 -0.09%
Age 60 or more -0.0629 0.1345 -0.85%
Hispanic Ethnicity 0.2326 0.0844 1.96%
Race: Asian -0.2354 0.0214 -0.50%
Race: Black -0.1609 0.1769 -2.85%
Race: Hawaiian or Pacific Islander 0.9703 0.0025 0.24%
Race: American Indian -0.3062 0.0190 -0.58%
Race: Multiple 0.2471 0.0136 0.34%
Highest Grade Completed: High School Equivalency -0.0172 0.4893 -0.84%
Highest Grade Completed: Some College 0.0386 0.0823 0.32%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.0422 0.0402 -0.17%
Highest Grade Completed: Associate Degree 0.3496 0.0937 3.27%
Highest Grade Completed: Bachelor Degree -0.6768 0.1290 -8.73%
Highest Grade Completed: Graduate Degree -0.5246 0.0541 -2.84%
Employed at Program Entry 0.0865 0.1680 1.45%
In School at Program Entry -0.0903 0.1520 -1.37%
Individual with a Disability -0.3557 0.0643 -2.29%
Veteran 0.2170 0.0574 1.25%
Limited English Proficiency -0.0185 0.1158 -0.21%
Single Parent 0.2027 0.2017 4.09%
Low Income 0.0926 0.3868 3.58%
Homeless -0.0667 0.0239 -0.16%
Individual who was Incarcerated 0.1850 0.0510 0.94%
Displaced Homemaker -0.2304 0.0141 -0.32%
Received Wages 2 Quarters Prior to Participation 0.3174 0.9045 28.70%
Long-Term Unemployed at Program Entry -0.1541 0.0869 -1.34%
UI Claimant -0.0385 0.7183 -2.76%
UI Exhaustee -0.0897 0.0117 -0.10%
Supportive Services Recipient -0.1026 0.0105 -0.11%
Received Needs-related Payments -9.8950 0.0000 0.00%
Received Other Public Assistance -0.1163 0.0022 -0.03%
SSI or SSDI Recipient 1.0873 0.0235 2.55%
TANF Recipient -0.5680 0.0157 -0.89%
Median Days in Program -0.0003 15.0000 -0.41%
Economic Condition Natural Resources Employment 1.6856 0.0111 1.86%
Construction Employment 1.5411 0.0437 6.73%
Manufacturing Employment 1.0127 0.1670 16.91%
Information Services Employment -0.4595 0.0170 -0.78%
Financial Services Employment 2.9649 0.0522 15.48%
Professional and Business Services Employment 0.9431 0.1139 10.74%
Educational or Health Care Employment 1.2831 0.2235 28.68%
Leisure, Hospitality, or Entertainment Employment 0.5919 0.1021 6.04%
Other Services Employment 3.9021 0.0293 11.45%
Public Administration 1.7006 0.0474 8.07%
Unemployment Rate Not Seasonally Adjusted 0.3440 0.0293 1.01%

Median Earnings 2nd Quarter after Exit

For this indicator, the tables below show the estimates for each of the variables in the statistical adjustment model and the related actual data. This data is used to determine the predicted level of performance for PY 2020 that is shown in the plot above. The PY 2020 prediction of $6,662 for Wisconsin for this performance indicator is calculated by summing the Variable Estimate0 values (total of 41750) and the specific state fixed effect for this model (-35088).

Definitions of the terms used in the table below:

  • Coefficient - the effect (or weight) of the variable.
  • PY Prior - the actual data for each variable for this state prior to PY 2020.
  • Variable Estimate0 - the amount the variable contributed to the pre-PY 2020 predicted target for this indicator as used as a factor in negotiations. It is calculated by multiplying the Coefficient by the PY Prior.
Model Variable Estimates
Variable Type Variable Coefficient Pre-PY Variable Estimate0
Participant Characteristic Female -2774.8460 0.4832 -$1,341
Age 25 to 44 1526.7709 0.4338 $662
Age 45 to 54 223.6212 0.2422 $54
Age 55 to 59 1725.9534 0.1270 $219
Age 60 or more 3989.3863 0.1105 $441
Hispanic Ethnicity 1506.2736 0.0838 $126
Race: Asian -1285.7589 0.0218 -$28
Race: Black -2926.8319 0.1769 -$518
Race: Hawaiian or Pacific Islander -2473.0352 0.0024 -$6
Race: American Indian -5567.8497 0.0181 -$101
Race: Multiple 10678.0968 0.0136 $145
Highest Grade Completed: High School Equivalency -1763.8797 0.4924 -$869
Highest Grade Completed: Some College -2177.4526 0.0806 -$176
Highest Grade Completed: Certificate or Other Post-Secondary Degree -2180.3190 0.0415 -$90
Highest Grade Completed: Associate Degree 2095.5471 0.0953 $200
Highest Grade Completed: Bachelor Degree 72.8128 0.1297 $9
Highest Grade Completed: Graduate Degree -5012.8376 0.0511 -$256
Employed at Program Entry 456.1906 0.1837 $84
In School at Program Entry -1155.2072 0.1507 -$174
Individual with a Disability -5107.0692 0.0525 -$268
Veteran -913.8967 0.0545 -$50
Limited English Proficiency 1563.7512 0.1162 $182
Single Parent 660.1018 0.1995 $132
Low Income 634.4633 0.3673 $233
Homeless -3513.0948 0.0199 -$70
Individual who was Incarcerated 1920.7679 0.0460 $88
Displaced Homemaker -10834.3804 0.0131 -$142
Received Wages 2 Quarters Prior to Participation -219.4792 0.9367 -$206
Wages 2 Quarters Prior to Participation 0.2612 7673.6150 $2,004
Long-Term Unemployed at Program Entry 771.2849 0.0733 $57
UI Claimant 454.7967 0.7239 $329
UI Exhaustee 247.9889 0.0117 $3
Supportive Services Recipient -636.3855 0.0114 -$7
Received Needs-related Payments -21804.7067 0.0000 $0
Received Other Public Assistance -1174.5793 0.0022 -$3
SSI or SSDI Recipient 10874.7587 0.0184 $201
TANF Recipient 1657.8393 0.0143 $24
Median Days in Program 0.8717 15.0000 $13
Economic Condition Natural Resources Employment 37057.6079 0.0111 $410
Construction Employment 42760.7710 0.0437 $1,867
Manufacturing Employment 47700.8708 0.1670 $7,966
Information Services Employment 11314.8086 0.0170 $193
Financial Services Employment 62614.6797 0.0522 $3,270
Professional and Business Services Employment 67885.3402 0.1139 $7,732
Educational or Health Care Employment 51491.7764 0.2235 $11,509
Leisure, Hospitality, or Entertainment Employment 43018.4305 0.1021 $4,393
Other Services Employment 41629.7443 0.0293 $1,221
Public Administration 51356.2602 0.0474 $2,437
Unemployment Rate Not Seasonally Adjusted -5089.3910 0.0293 -$149

Full Model Variable Table

The table below shows which variables are included in which models. It also includes both the variable names used in the modeling process and the full name of the variables.

Variable Names
Adult
Dislocated Worker
Youth
Wagner-Peyser
Model Variable Full Variable Name Q2ER ME MSG Q2ER ME MSG Q2ER ME MSG Q2ER ME
female Female x x x x x x x x x x x
age1415 Age 14 to 15 x x x
age1617 Age 16 to 17 x x x
age1819 Age 18 to 19 x x x
age2021 Age 20 to 21 x x x
age2544 Age 25 to 44 x x x x x x x x
age4554 Age 45 to 54 x x x x x x x x
age5559 Age 55 to 59 x x x x x x x x
age60 Age 60 or more x x x x x x x x
hispanic Hispanic Ethnicity x x x x x x x x x x x
raceasian Race: Asian x x x x x x x x x x x
raceblack Race: Black x x x x x x x x x x x
racehpi Race: Hawaiian or Pacific Islander x x x x x x x x
raceai Race: American Indian x x x x x x x x x x x
racemulti Race: Multiple x x x x x x x x x x x
hsgrad Highest Grade Completed: High School Equivalency x x x x x x x x x x x
collegedropout Highest Grade Completed: Some College x x x x x x x x x x x
certotherps Highest Grade Completed: Certificate or Other Post-Secondary Degree x x x x x x x x x x x
associate Highest Grade Completed: Associate Degree x x x x x x x x
ba Highest Grade Completed: Bachelor Degree x x x x x x x x
associateorba Highest Grade Completed: Associate or Bachelor Degree x x x
gradschool Highest Grade Completed: Graduate Degree x x x x x x x x
empentry Employed at Program Entry x x x x x x x x x x
edstatentry In School at Program Entry x x x x x x x x x x x
disabled Individual with a Disability x x x x x x x x x x
veteran Veteran x x x x x x x x
englearner Limited English Proficiency x x x x x x x x x x
singleparent Single Parent x x x x x x x x
lowinc Low Income x x x x x x x x
homeless Homeless x x x x x x x x
offender Individual who was Incarcerated x x x x x x x x x x
dishomemaker Displaced Homemaker x x x x x x
yfoster Foster Care Youth x x
yparent Youth Parent or Pregnant Youth x x
basiclitdeficient Skills/Literacy Deficient at Program Entry x x x
recwages2qprior Received Wages 2 Quarters Prior to Participation x x x x x x x x
wages2qprior Wages 2 Quarters Prior to Participation x x x
longtermunemp Long-Term Unemployed at Program Entry x x x x x x x x x x
uiclaimant UI Claimant x x x x x x x x x
uiexhaustee UI Exhaustee x x x x x x x x
recsuppserv Supportive Services Recipient x x x x x x x x x x x
recneeds Received Needs-related Payments x x x x x x x x
recotherasst Received Other Public Assistance x x x x x x x x x
recssi SSI or SSDI Recipient x x x x x x x x x x x
rectanf TANF Recipient x x x x x x x x x x
recpell Pell Grant Recipient x
ynaa Youth Needing Additional Assistance x x
wp Received Wagner-Peyser Act Services x x x x x x x x x
daysinprog Median Days in Program x x x x x x x x x x
daysenrolled Median Days Enrolled in Education or Training x x x
daysenrolled_under30 Percent Enrolled in Education or Training Under 30 Days x x x
natresources Natural Resources Employment x x x x x x x x x x x
construction Construction Employment x x x x x x x x x x x
manufacturing Manufacturing Employment x x x x x x x x x x x
information Information Services Employment x x x x x x x x x x x
financial Financial Services Employment x x x x x x x x x x x
business Professional and Business Services Employment x x x x x x x x x x x
edhealthcare Educational or Health Care Employment x x x x x x x x x x x
leisure Leisure, Hospitality, or Entertainment Employment x x x x x x x x x x x
otheremp Other Services Employment x x x x x x x x x x x
publicadmin Public Administration x x x x x x x x x x x
ur Unemployment Rate Not Seasonally Adjusted x x x x x x x x x x x