Statistical Adjustment Model Summary for Ohio

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 Ohio in PY 2018 compared to all states and how the predicted level of performance (i.e., Estimate0) for Ohio 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 85.0% for Ohio for this performance indicator is calculated by summing the Variable Estimate0 values (total of 0.714) and the specific state fixed effect for this model (0.136).

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 0.4763 6.20%
Age 25 to 44 -0.0308 0.5217 -1.61%
Age 45 to 54 -0.1545 0.1805 -2.79%
Age 55 to 59 -0.0779 0.0754 -0.59%
Age 60 or more -0.5993 0.0691 -4.14%
Hispanic Ethnicity 0.0815 0.0377 0.31%
Race: Asian -0.2333 0.0127 -0.30%
Race: Black 0.0861 0.4624 3.98%
Race: Hawaiian or Pacific Islander -0.1320 0.0025 -0.03%
Race: American Indian 0.0501 0.0067 0.03%
Race: Multiple -0.1183 0.0105 -0.12%
Highest Grade Completed: High School Equivalency -0.1257 0.4876 -6.13%
Highest Grade Completed: Some College -0.1221 0.1870 -2.28%
Highest Grade Completed: Certificate or Other Post-Secondary Degree 0.0978 0.0621 0.61%
Highest Grade Completed: Associate Degree -0.0773 0.0726 -0.56%
Highest Grade Completed: Bachelor Degree 0.1722 0.0976 1.68%
Highest Grade Completed: Graduate Degree -0.1430 0.0347 -0.50%
Employed at Program Entry 0.1964 0.2235 4.39%
In School at Program Entry 0.1265 0.0730 0.92%
Individual with a Disability -0.1813 0.0372 -0.67%
Veteran 0.2901 0.0549 1.59%
Limited English Proficiency -0.0306 0.0242 -0.07%
Single Parent -0.0942 0.1554 -1.46%
Low Income 0.0081 0.4572 0.37%
Homeless -0.0534 0.0344 -0.18%
Individual who was Incarcerated 0.1550 0.1698 2.63%
Displaced Homemaker -0.1842 0.0009 -0.02%
Received Wages 2 Quarters Prior to Participation 0.1889 0.6342 11.98%
Long-Term Unemployed at Program Entry 0.0157 0.0722 0.11%
UI Claimant -0.0148 0.0679 -0.10%
UI Exhaustee 0.1394 0.0144 0.20%
Supportive Services Recipient 0.0620 0.1967 1.22%
Received Needs-related Payments 0.4886 0.0000 0.00%
Received Other Public Assistance -0.0494 0.0003 0.00%
SSI or SSDI Recipient -0.0205 0.0083 -0.02%
TANF Recipient 0.0438 0.0239 0.10%
Received Wagner-Peyser Act Services 0.0220 0.0000 0.00%
Median Days in Program -0.0002 158.0000 -2.89%
Economic Condition Natural Resources Employment 2.1266 0.0053 1.12%
Construction Employment 0.8615 0.0414 3.57%
Manufacturing Employment 0.1897 0.1296 2.46%
Information Services Employment -5.3312 0.0153 -8.18%
Financial Services Employment -4.8664 0.0544 -26.46%
Professional and Business Services Employment 3.7575 0.1370 51.49%
Educational or Health Care Employment 0.8235 0.2452 20.19%
Leisure, Hospitality, or Entertainment Employment -0.8923 0.1075 -9.59%
Other Services Employment 4.5274 0.0291 13.19%
Public Administration 2.2149 0.0395 8.74%
Unemployment Rate Not Seasonally Adjusted 0.6822 0.0432 2.95%

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 $6,204 for Ohio for this performance indicator is calculated by summing the Variable Estimate0 values (total of 41528) and the specific state fixed effect for this model (-35324).

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 0.4844 -$1,376
Age 25 to 44 -862.0930 0.5271 -$454
Age 45 to 54 -3144.2089 0.1779 -$559
Age 55 to 59 -5290.3216 0.0726 -$384
Age 60 or more -6059.0062 0.0579 -$351
Hispanic Ethnicity 232.4254 0.0402 $9
Race: Asian -4413.8578 0.0119 -$53
Race: Black -2324.8593 0.4613 -$1,072
Race: Hawaiian or Pacific Islander -6352.7320 0.0028 -$17
Race: American Indian -2692.4326 0.0062 -$17
Race: Multiple 6983.7945 0.0097 $68
Highest Grade Completed: High School Equivalency 362.0217 0.4921 $178
Highest Grade Completed: Some College 826.8902 0.1861 $154
Highest Grade Completed: Certificate or Other Post-Secondary Degree -1324.3050 0.0629 -$83
Highest Grade Completed: Associate Degree 5643.1853 0.0710 $400
Highest Grade Completed: Bachelor Degree 4052.0797 0.0974 $395
Highest Grade Completed: Graduate Degree 8539.9365 0.0347 $296
Employed at Program Entry 965.0801 0.2429 $234
In School at Program Entry 3623.2012 0.0750 $272
Individual with a Disability -989.2237 0.0339 -$34
Veteran -1349.3089 0.0526 -$71
Limited English Proficiency -4419.8922 0.0226 -$100
Single Parent 145.7630 0.1597 $23
Low Income -332.4067 0.4586 -$152
Homeless -446.4262 0.0328 -$15
Individual who was Incarcerated 2013.3031 0.1586 $319
Displaced Homemaker -1947.9185 0.0011 -$2
Received Wages 2 Quarters Prior to Participation 807.6246 0.6747 $545
Wages 2 Quarters Prior to Participation 0.3653 4637.3150 $1,694
Long-Term Unemployed at Program Entry 2011.8227 0.0612 $123
UI Claimant 685.8891 0.0682 $47
UI Exhaustee -2567.3504 0.0145 -$37
Supportive Services Recipient 912.9138 0.1980 $181
Received Needs-related Payments 15112.5289 0.0000 $0
Received Other Public Assistance 107.5299 0.0004 $0
SSI or SSDI Recipient -5911.8510 0.0068 -$40
TANF Recipient 840.8641 0.0227 $19
Received Wagner-Peyser Act Services -205.4928 0.0000 $0
Median Days in Program 3.2489 158.0000 $513
Economic Condition Natural Resources Employment 24063.8444 0.0053 $127
Construction Employment 32326.4938 0.0414 $1,339
Manufacturing Employment 39237.2625 0.1296 $5,084
Information Services Employment -48189.2565 0.0153 -$739
Financial Services Employment 4074.2901 0.0544 $222
Professional and Business Services Employment 96754.4484 0.1370 $13,259
Educational or Health Care Employment 56163.1547 0.2452 $13,772
Leisure, Hospitality, or Entertainment Employment 57668.0011 0.1075 $6,197
Other Services Employment 10767.7935 0.0291 $314
Public Administration 39658.6388 0.0395 $1,565
Unemployment Rate Not Seasonally Adjusted -6106.3827 0.0432 -$264

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 65.2% for Ohio for this performance indicator is calculated by summing the Variable Estimate0 values (total of 7.235) and the specific state fixed effect for this model (-6.583).

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 0.5133 -18.55%
Age 25 to 44 0.5218 0.5958 31.09%
Age 45 to 54 -0.0702 0.1332 -0.93%
Age 55 to 59 -0.9975 0.0322 -3.22%
Age 60 or more 2.9217 0.0140 4.09%
Hispanic Ethnicity -1.4456 0.0417 -6.03%
Race: Asian 2.1310 0.0111 2.36%
Race: Black -0.5671 0.3324 -18.85%
Race: American Indian 0.8520 0.0053 0.45%
Race: Multiple 1.9759 0.0129 2.56%
Highest Grade Completed: High School Equivalency -0.1218 0.5908 -7.20%
Highest Grade Completed: Some College -0.1842 0.1723 -3.17%
Highest Grade Completed: Certificate or Other Post-Secondary Degree 0.0731 0.0666 0.49%
Highest Grade Completed: Associate Degree -0.8544 0.0610 -5.21%
Highest Grade Completed: Bachelor Degree -0.2005 0.0497 -1.00%
Highest Grade Completed: Graduate Degree 1.8387 0.0114 2.09%
Employed at Program Entry 0.3647 0.4180 15.24%
In School at Program Entry -0.3045 0.1403 -4.27%
Individual with a Disability -0.2611 0.0415 -1.08%
Veteran 0.2508 0.0367 0.92%
Limited English Proficiency 0.8810 0.0288 2.54%
Single Parent 0.2135 0.2639 5.63%
Individual who was Incarcerated 0.7809 0.1482 11.57%
Received Wages 2 Quarters Prior to Participation -0.0013 0.2312 -0.03%
Long-Term Unemployed at Program Entry 0.0652 0.0637 0.42%
UI Exhaustee 0.0104 0.0098 0.01%
Supportive Services Recipient -0.1297 0.4328 -5.61%
SSI or SSDI Recipient 0.4929 0.0103 0.51%
TANF Recipient -0.2848 0.0394 -1.12%
Received Wagner-Peyser Act Services 0.0732 0.0000 0.00%
Median Days in Program 0.0004 202.0000 7.16%
Median Days Enrolled in Education or Training -0.0002 144.0000 -3.51%
Percent Enrolled in Education or Training Under 30 Days -0.0087 0.0991 -0.09%
Economic Condition Natural Resources Employment 10.0155 0.0053 5.30%
Construction Employment 8.9287 0.0414 36.98%
Manufacturing Employment 12.1240 0.1296 157.09%
Information Services Employment -43.8313 0.0153 -67.25%
Financial Services Employment 31.7234 0.0544 172.48%
Professional and Business Services Employment 7.5758 0.1370 103.82%
Educational or Health Care Employment 9.9286 0.2452 243.47%
Leisure, Hospitality, or Entertainment Employment 2.5813 0.1075 27.74%
Other Services Employment 32.8685 0.0291 95.79%
Public Administration -0.1431 0.0395 -0.56%
Unemployment Rate Not Seasonally Adjusted -13.5535 0.0432 -58.60%

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 87.9% for Ohio for this performance indicator is calculated by summing the Variable Estimate0 values (total of -1.804) and the specific state fixed effect for this model (2.683).

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 0.4152 2.47%
Age 25 to 44 0.0189 0.3658 0.69%
Age 45 to 54 -0.0169 0.3260 -0.55%
Age 55 to 59 0.1060 0.1719 1.82%
Age 60 or more -0.1905 0.1091 -2.08%
Hispanic Ethnicity 0.1185 0.0377 0.45%
Race: Asian -0.2910 0.0173 -0.50%
Race: Black -0.0358 0.3000 -1.08%
Race: Hawaiian or Pacific Islander 0.8792 0.0061 0.53%
Race: American Indian -0.0983 0.0052 -0.05%
Race: Multiple -0.1947 0.0074 -0.14%
Highest Grade Completed: High School Equivalency -0.0259 0.3835 -1.00%
Highest Grade Completed: Some College -0.1942 0.1589 -3.09%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.1799 0.0550 -0.99%
Highest Grade Completed: Associate Degree -0.0907 0.0922 -0.84%
Highest Grade Completed: Bachelor Degree -0.1447 0.1857 -2.69%
Highest Grade Completed: Graduate Degree -0.1210 0.0866 -1.05%
Employed at Program Entry 0.1061 0.0403 0.43%
In School at Program Entry -0.0254 0.0532 -0.14%
Individual with a Disability -0.0527 0.0173 -0.09%
Veteran 0.0056 0.0636 0.04%
Limited English Proficiency -0.2521 0.0104 -0.26%
Single Parent 0.0446 0.0714 0.32%
Low Income -0.0518 0.0268 -0.14%
Homeless 0.0306 0.0069 0.02%
Individual who was Incarcerated 0.3775 0.0723 2.73%
Displaced Homemaker -0.2274 0.0156 -0.35%
Received Wages 2 Quarters Prior to Participation 0.1131 0.8597 9.72%
Long-Term Unemployed at Program Entry 0.0574 0.0528 0.30%
UI Claimant 0.0208 0.7126 1.48%
UI Exhaustee 0.0737 0.0697 0.51%
Supportive Services Recipient 0.0496 0.1619 0.80%
Received Needs-related Payments -0.4938 0.0000 0.00%
Received Other Public Assistance -0.1259 0.0000 0.00%
SSI or SSDI Recipient 0.8134 0.0026 0.21%
TANF Recipient -0.5301 0.0030 -0.16%
Received Wagner-Peyser Act Services -0.0512 0.0000 0.00%
Median Days in Program 0.0000 178.0000 0.14%
Economic Condition Natural Resources Employment -2.0224 0.0053 -1.07%
Construction Employment -0.4670 0.0414 -1.93%
Manufacturing Employment -1.7064 0.1296 -22.11%
Information Services Employment -9.8998 0.0153 -15.19%
Financial Services Employment -6.2744 0.0544 -34.11%
Professional and Business Services Employment -3.6027 0.1370 -49.37%
Educational or Health Care Employment -1.9946 0.2452 -48.91%
Leisure, Hospitality, or Entertainment Employment -2.8519 0.1075 -30.65%
Other Services Employment 3.0428 0.0291 8.87%
Public Administration 1.2295 0.0395 4.85%
Unemployment Rate Not Seasonally Adjusted 0.4118 0.0432 1.78%

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 $8,648 for Ohio for this performance indicator is calculated by summing the Variable Estimate0 values (total of 38683) and the specific state fixed effect for this model (-30036).

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 0.4125 -$784
Age 25 to 44 1115.5154 0.3740 $417
Age 45 to 54 -125.9873 0.3279 -$41
Age 55 to 59 -2126.3785 0.1688 -$359
Age 60 or more -2492.9312 0.1000 -$249
Hispanic Ethnicity -857.7550 0.0380 -$33
Race: Asian -4684.9713 0.0173 -$81
Race: Black -1536.6027 0.3043 -$468
Race: Hawaiian or Pacific Islander -3269.1753 0.0058 -$19
Race: American Indian -3522.2138 0.0048 -$17
Race: Multiple -3712.0594 0.0072 -$27
Highest Grade Completed: High School Equivalency -1400.0970 0.3832 -$536
Highest Grade Completed: Some College -1902.9048 0.1625 -$309
Highest Grade Completed: Certificate or Other Post-Secondary Degree 83.4151 0.0538 $4
Highest Grade Completed: Associate Degree 1526.2402 0.0928 $142
Highest Grade Completed: Bachelor Degree 1169.4179 0.1803 $211
Highest Grade Completed: Graduate Degree 2155.0497 0.0880 $190
Employed at Program Entry 1700.7794 0.0418 $71
In School at Program Entry 3787.5103 0.0558 $211
Individual with a Disability 279.5931 0.0168 $5
Veteran 1445.8344 0.0630 $91
Limited English Proficiency -2976.1328 0.0106 -$31
Single Parent -784.4348 0.0716 -$56
Low Income -538.7097 0.0255 -$14
Homeless 7893.8250 0.0072 $57
Individual who was Incarcerated 1805.9783 0.0726 $131
Displaced Homemaker 192.7564 0.0149 $3
Received Wages 2 Quarters Prior to Participation 21.0817 0.8716 $18
Wages 2 Quarters Prior to Participation 0.0917 9212.0000 $844
Long-Term Unemployed at Program Entry 1348.3682 0.0519 $70
UI Claimant 68.6962 0.7178 $49
UI Exhaustee -2493.0132 0.0659 -$164
Supportive Services Recipient 176.1628 0.1630 $29
Received Needs-related Payments 6660.1906 0.0000 $0
Received Other Public Assistance 470.0451 0.0000 $0
SSI or SSDI Recipient -2105.8014 0.0014 -$3
TANF Recipient -4222.3011 0.0034 -$14
Received Wagner-Peyser Act Services -403.3425 0.0000 $0
Median Days in Program 2.2222 175.0000 $389
Economic Condition Natural Resources Employment -27241.5941 0.0053 -$144
Construction Employment 36651.6742 0.0414 $1,518
Manufacturing Employment 47186.5858 0.1296 $6,114
Information Services Employment -260263.7041 0.0153 -$3,993
Financial Services Employment 85893.1957 0.0544 $4,670
Professional and Business Services Employment 95022.1320 0.1370 $13,022
Educational or Health Care Employment 51172.3083 0.2452 $12,549
Leisure, Hospitality, or Entertainment Employment 43978.6506 0.1075 $4,726
Other Services Employment -4546.6888 0.0291 -$133
Public Administration 22271.2780 0.0395 $879
Unemployment Rate Not Seasonally Adjusted -5795.6816 0.0432 -$251

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 67.0% for Ohio for this performance indicator is calculated by summing the Variable Estimate0 values (total of 6.421) and the specific state fixed effect for this model (-5.751).

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 0.3653 -5.51%
Age 25 to 44 -0.0655 0.4611 -3.02%
Age 45 to 54 0.2414 0.3042 7.34%
Age 55 to 59 0.4579 0.1379 6.31%
Age 60 or more 0.9139 0.0547 5.00%
Hispanic Ethnicity -0.6646 0.0368 -2.45%
Race: Asian -0.5340 0.0084 -0.45%
Race: Black -0.3293 0.1895 -6.24%
Race: American Indian 2.6465 0.0032 0.84%
Race: Multiple 0.0503 0.0021 0.01%
Highest Grade Completed: High School Equivalency -0.1922 0.4611 -8.86%
Highest Grade Completed: Some College -0.2384 0.1621 -3.86%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.2607 0.0400 -1.04%
Highest Grade Completed: Associate Degree 0.2625 0.0989 2.60%
Highest Grade Completed: Bachelor Degree -0.1123 0.1432 -1.61%
Highest Grade Completed: Graduate Degree -0.4275 0.0653 -2.79%
Employed at Program Entry -0.0215 0.0463 -0.10%
In School at Program Entry -0.2643 0.0989 -2.62%
Individual with a Disability -1.4481 0.0189 -2.74%
Veteran -0.9235 0.0642 -5.93%
Limited English Proficiency 0.4514 0.0221 1.00%
Single Parent 0.3691 0.1274 4.70%
Individual who was Incarcerated 0.4693 0.0747 3.51%
Received Wages 2 Quarters Prior to Participation 0.0287 0.2821 0.81%
Long-Term Unemployed at Program Entry 0.3881 0.0768 2.98%
UI Exhaustee 0.3561 0.0516 1.84%
Supportive Services Recipient -0.0615 0.3937 -2.42%
SSI or SSDI Recipient -0.4356 0.0011 -0.05%
TANF Recipient -3.8716 0.0032 -1.22%
Received Wagner-Peyser Act Services -0.0963 0.0000 0.00%
Median Days in Program -0.0003 193.0000 -6.20%
Median Days Enrolled in Education or Training -0.0003 103.5000 -2.83%
Percent Enrolled in Education or Training Under 30 Days 0.1620 0.1674 2.71%
Economic Condition Natural Resources Employment -8.0806 0.0053 -4.27%
Construction Employment 4.4493 0.0414 18.43%
Manufacturing Employment 9.8551 0.1296 127.69%
Information Services Employment -58.7056 0.0153 -90.07%
Financial Services Employment 12.1977 0.0544 66.32%
Professional and Business Services Employment 16.0554 0.1370 220.02%
Educational or Health Care Employment 7.1634 0.2452 175.66%
Leisure, Hospitality, or Entertainment Employment 1.5122 0.1075 16.25%
Other Services Employment 65.3154 0.0291 190.35%
Public Administration -2.8478 0.0395 -11.24%
Unemployment Rate Not Seasonally Adjusted -10.8237 0.0432 -46.80%

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 74.5% for Ohio for this performance indicator is calculated by summing the Variable Estimate0 values (total of -1.102) and the specific state fixed effect for this model (1.847).

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 0.5956 3.54%
Age 14 to 15 0.1226 0.1137 1.39%
Age 16 to 17 -0.1436 0.1535 -2.20%
Age 18 to 19 -0.2054 0.2747 -5.64%
Age 20 to 21 0.0105 0.1996 0.21%
Hispanic Ethnicity -0.0628 0.0438 -0.27%
Race: Asian 0.1989 0.0035 0.07%
Race: Black -0.0414 0.5126 -2.12%
Race: Hawaiian or Pacific Islander -0.5342 0.0012 -0.06%
Race: American Indian -0.3341 0.0049 -0.16%
Race: Multiple 0.1508 0.0258 0.39%
Highest Grade Completed: High School Equivalency 0.0691 0.4276 2.96%
Highest Grade Completed: Some College -0.3127 0.0203 -0.64%
Highest Grade Completed: Certificate or Other Post-Secondary Degree 1.1469 0.0078 0.90%
Highest Grade Completed: Associate or Bachelor Degree 0.4935 0.0070 0.34%
Employed at Program Entry 0.2748 0.1384 3.80%
In School at Program Entry 0.0356 0.3090 1.10%
Individual with a Disability -0.0469 0.3568 -1.67%
Limited English Proficiency -0.1392 0.0276 -0.38%
Low Income 0.0375 0.9420 3.53%
Homeless -0.2008 0.0798 -1.60%
Individual who was Incarcerated 0.0635 0.2956 1.88%
Foster Care Youth -0.0100 0.0806 -0.08%
Youth Parent or Pregnant Youth -0.0716 0.3565 -2.55%
Skills/Literacy Deficient at Program Entry 0.0349 0.5927 2.07%
Long-Term Unemployed at Program Entry -0.0867 0.0113 -0.10%
UI Claimant -0.0433 0.0154 -0.07%
Supportive Services Recipient 0.0442 0.5123 2.26%
Received Needs-related Payments 0.7660 0.0000 0.00%
Received Other Public Assistance -0.1510 0.0000 0.00%
SSI or SSDI Recipient 0.0743 0.0061 0.05%
TANF Recipient -0.0341 0.3641 -1.24%
Pell Grant Recipient 0.0368 0.0592 0.22%
Youth Needing Additional Assistance 0.0005 0.8091 0.04%
Received Wagner-Peyser Act Services 0.0148 0.0000 0.00%
Median Days in Program 0.0000 207.0000 -0.83%
Economic Condition Natural Resources Employment -6.7872 0.0053 -3.59%
Construction Employment -1.8800 0.0414 -7.79%
Manufacturing Employment -1.3602 0.1296 -17.62%
Information Services Employment -7.2974 0.0153 -11.20%
Financial Services Employment -2.1367 0.0544 -11.62%
Professional and Business Services Employment -2.5564 0.1370 -35.03%
Educational or Health Care Employment 0.0247 0.2452 0.61%
Leisure, Hospitality, or Entertainment Employment -0.3944 0.1075 -4.24%
Other Services Employment -10.7940 0.0291 -31.46%
Public Administration 3.2993 0.0395 13.02%
Unemployment Rate Not Seasonally Adjusted -1.4872 0.0432 -6.43%

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 $2,932 for Ohio for this performance indicator is calculated by summing the Variable Estimate0 values (total of 14116) and the specific state fixed effect for this model (-11184).

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 0.6117 -$1,148.41
Age 14 to 15 -92.3013 0.0417 -$3.85
Age 16 to 17 -1309.0587 0.1395 -$182.66
Age 18 to 19 -1066.4762 0.3102 -$330.85
Age 20 to 21 649.4931 0.2233 $145.06
Hispanic Ethnicity 1913.4585 0.0465 $89.00
Race: Asian 649.7122 0.0035 $2.28
Race: Black -886.3703 0.5033 -$446.10
Race: Hawaiian or Pacific Islander -3388.4232 0.0004 -$1.49
Race: American Indian -184.4720 0.0057 -$1.05
Race: Multiple 933.1134 0.0276 $25.79
Highest Grade Completed: High School Equivalency 1383.9408 0.4950 $684.99
Highest Grade Completed: Some College -828.1913 0.0263 -$21.80
Highest Grade Completed: Certificate or Other Post-Secondary Degree 173.0955 0.0105 $1.82
Highest Grade Completed: Associate or Bachelor Degree 6672.3330 0.0092 $61.48
Employed at Program Entry 613.7857 0.1746 $107.19
In School at Program Entry 546.1994 0.2295 $125.35
Individual with a Disability -495.1811 0.3488 -$172.74
Limited English Proficiency 2456.3023 0.0189 $46.35
Low Income -305.7985 0.9324 -$285.13
Homeless 983.9044 0.0785 $77.28
Individual who was Incarcerated -1284.6596 0.2949 -$378.80
Foster Care Youth 1009.8293 0.0702 $70.90
Youth Parent or Pregnant Youth 854.5128 0.3809 $325.46
Skills/Literacy Deficient at Program Entry -283.4775 0.5985 -$169.66
Long-Term Unemployed at Program Entry -630.2664 0.0132 -$8.30
UI Claimant -462.5838 0.0171 -$7.92
Supportive Services Recipient 161.1750 0.5691 $91.73
Received Needs-related Payments 2823.2240 0.0000 $0.00
Received Other Public Assistance -184.0786 0.0000 $0.00
SSI or SSDI Recipient -1658.7545 0.0061 -$10.19
TANF Recipient -539.6509 0.3401 -$183.51
Pell Grant Recipient 104.1843 0.0724 $7.54
Youth Needing Additional Assistance -4.3341 0.8021 -$3.48
Received Wagner-Peyser Act Services -27.8731 0.0000 $0.00
Median Days in Program 0.5942 239.0000 $142.01
Economic Condition Natural Resources Employment -3172.1958 0.0053 -$16.78
Construction Employment 10994.4772 0.0414 $455.36
Manufacturing Employment 21559.9593 0.1296 $2,793.53
Information Services Employment -55465.6493 0.0153 -$850.98
Financial Services Employment 44805.1055 0.0544 $2,436.03
Professional and Business Services Employment 14219.0161 0.1370 $1,948.56
Educational or Health Care Employment 20372.0444 0.2452 $4,995.68
Leisure, Hospitality, or Entertainment Employment 7088.2477 0.1075 $761.74
Other Services Employment 57026.8505 0.0291 $1,661.93
Public Administration 43573.5139 0.0395 $1,719.14
Unemployment Rate Not Seasonally Adjusted -10090.2192 0.0432 -$436.25

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 37.8% for Ohio for this performance indicator is calculated by summing the Variable Estimate0 values (total of 4.279) and the specific state fixed effect for this model (-3.9).

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 0.5817 -16.05%
Age 14 to 15 -0.8106 0.1232 -9.99%
Age 16 to 17 -0.9025 0.3175 -28.65%
Age 18 to 19 -0.6998 0.2565 -17.95%
Age 20 to 21 -1.6404 0.1504 -24.67%
Hispanic Ethnicity -0.0170 0.0627 -0.11%
Race: Asian -0.0162 0.0062 -0.01%
Race: Black 0.0042 0.4668 0.20%
Race: American Indian -0.1578 0.0109 -0.17%
Race: Multiple 1.9727 0.0351 6.92%
Highest Grade Completed: High School Equivalency -0.2692 0.2058 -5.54%
Highest Grade Completed: Some College 1.0513 0.0186 1.96%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.6449 0.0045 -0.29%
Highest Grade Completed: Associate or Bachelor Degree 1.9000 0.0030 0.57%
In School at Program Entry 0.0220 0.5252 1.16%
Skills/Literacy Deficient at Program Entry 0.1976 0.7050 13.93%
UI Claimant 0.0198 0.0190 0.04%
Supportive Services Recipient -0.0712 0.7542 -5.37%
Received Other Public Assistance 0.2742 0.0000 0.00%
SSI or SSDI Recipient 0.5536 0.0103 0.57%
Pell Grant Recipient -0.8864 0.0469 -4.15%
Received Wagner-Peyser Act Services -0.0503 0.0000 0.00%
Median Days Enrolled in Education or Training -0.0003 324.0000 -10.57%
Percent Enrolled in Education or Training Under 30 Days -0.3441 0.1021 -3.51%
Economic Condition Natural Resources Employment 7.6282 0.0053 4.03%
Construction Employment 9.5740 0.0414 39.65%
Manufacturing Employment 5.8313 0.1296 75.56%
Information Services Employment -42.8136 0.0153 -65.69%
Financial Services Employment -14.2433 0.0544 -77.44%
Professional and Business Services Employment 14.4769 0.1370 198.39%
Educational or Health Care Employment 7.0634 0.2452 173.21%
Leisure, Hospitality, or Entertainment Employment 6.2993 0.1075 67.70%
Other Services Employment 50.8391 0.0291 148.16%
Public Administration -7.3408 0.0395 -28.96%
Unemployment Rate Not Seasonally Adjusted -1.1663 0.0432 -5.04%

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 72.5% for Ohio for this performance indicator is calculated by summing the Variable Estimate0 values (total of 1.187) and the specific state fixed effect for this model (-0.462).

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 0.4480 3.59%
Age 25 to 44 0.1086 0.3894 4.23%
Age 45 to 54 -0.0860 0.2673 -2.30%
Age 55 to 59 -0.0070 0.1427 -0.10%
Age 60 or more -0.0629 0.1540 -0.97%
Hispanic Ethnicity 0.2326 0.0452 1.05%
Race: Asian -0.2354 0.0083 -0.20%
Race: Black -0.1609 0.1649 -2.65%
Race: Hawaiian or Pacific Islander 0.9703 0.0037 0.35%
Race: American Indian -0.3062 0.0071 -0.22%
Race: Multiple 0.2471 0.0093 0.23%
Highest Grade Completed: High School Equivalency -0.0172 0.4122 -0.71%
Highest Grade Completed: Some College 0.0386 0.1651 0.64%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.0422 0.0329 -0.14%
Highest Grade Completed: Associate Degree 0.3496 0.0898 3.14%
Highest Grade Completed: Bachelor Degree -0.6768 0.1607 -10.88%
Highest Grade Completed: Graduate Degree -0.5246 0.0549 -2.88%
Employed at Program Entry 0.0865 0.0225 0.19%
In School at Program Entry -0.0903 0.1776 -1.60%
Individual with a Disability -0.3557 0.0824 -2.93%
Veteran 0.2170 0.1337 2.90%
Limited English Proficiency -0.0185 0.0082 -0.02%
Single Parent 0.2027 0.0000 0.00%
Low Income 0.0926 0.0049 0.05%
Homeless -0.0667 0.0048 -0.03%
Individual who was Incarcerated 0.1850 0.0111 0.21%
Displaced Homemaker -0.2304 0.0000 0.00%
Received Wages 2 Quarters Prior to Participation 0.3174 0.9038 28.68%
Long-Term Unemployed at Program Entry -0.1541 0.0000 0.00%
UI Claimant -0.0385 0.6699 -2.58%
UI Exhaustee -0.0897 0.0000 0.00%
Supportive Services Recipient -0.1026 0.0000 0.00%
Received Needs-related Payments -9.8950 0.0000 0.00%
Received Other Public Assistance -0.1163 0.0000 0.00%
SSI or SSDI Recipient 1.0873 0.0000 0.00%
TANF Recipient -0.5680 0.0004 -0.03%
Median Days in Program -0.0003 162.0000 -4.46%
Economic Condition Natural Resources Employment 1.6856 0.0053 0.89%
Construction Employment 1.5411 0.0414 6.38%
Manufacturing Employment 1.0127 0.1296 13.12%
Information Services Employment -0.4595 0.0153 -0.71%
Financial Services Employment 2.9649 0.0544 16.12%
Professional and Business Services Employment 0.9431 0.1370 12.92%
Educational or Health Care Employment 1.2831 0.2452 31.46%
Leisure, Hospitality, or Entertainment Employment 0.5919 0.1075 6.36%
Other Services Employment 3.9021 0.0291 11.37%
Public Administration 1.7006 0.0395 6.71%
Unemployment Rate Not Seasonally Adjusted 0.3440 0.0432 1.49%

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 $7,550 for Ohio for this performance indicator is calculated by summing the Variable Estimate0 values (total of 41687) and the specific state fixed effect for this model (-34137).

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 0.4527 -$1,256
Age 25 to 44 1526.7709 0.4151 $634
Age 45 to 54 223.6212 0.2808 $63
Age 55 to 59 1725.9534 0.1418 $245
Age 60 or more 3989.3863 0.1146 $457
Hispanic Ethnicity 1506.2736 0.0411 $62
Race: Asian -1285.7589 0.0088 -$11
Race: Black -2926.8319 0.1686 -$493
Race: Hawaiian or Pacific Islander -2473.0352 0.0038 -$9
Race: American Indian -5567.8497 0.0074 -$41
Race: Multiple 10678.0968 0.0093 $100
Highest Grade Completed: High School Equivalency -1763.8797 0.4094 -$722
Highest Grade Completed: Some College -2177.4526 0.1648 -$359
Highest Grade Completed: Certificate or Other Post-Secondary Degree -2180.3190 0.0335 -$73
Highest Grade Completed: Associate Degree 2095.5471 0.0923 $193
Highest Grade Completed: Bachelor Degree 72.8128 0.1658 $12
Highest Grade Completed: Graduate Degree -5012.8376 0.0559 -$280
Employed at Program Entry 456.1906 0.0211 $10
In School at Program Entry -1155.2072 0.1760 -$203
Individual with a Disability -5107.0692 0.0694 -$354
Veteran -913.8967 0.1199 -$110
Limited English Proficiency 1563.7512 0.0046 $7
Single Parent 660.1018 0.0000 $0
Low Income 634.4633 0.0037 $2
Homeless -3513.0948 0.0036 -$13
Individual who was Incarcerated 1920.7679 0.0090 $17
Displaced Homemaker -10834.3804 0.0000 $0
Received Wages 2 Quarters Prior to Participation -219.4792 0.9325 -$205
Wages 2 Quarters Prior to Participation 0.2612 8749.0000 $2,285
Long-Term Unemployed at Program Entry 771.2849 0.0000 $0
UI Claimant 454.7967 0.6803 $309
UI Exhaustee 247.9889 0.0000 $0
Supportive Services Recipient -636.3855 0.0000 $0
Received Needs-related Payments -21804.7067 0.0000 $0
Received Other Public Assistance -1174.5793 0.0000 $0
SSI or SSDI Recipient 10874.7587 0.0000 $0
TANF Recipient 1657.8393 0.0002 $0
Median Days in Program 0.8717 140.0000 $122
Economic Condition Natural Resources Employment 37057.6079 0.0053 $196
Construction Employment 42760.7710 0.0414 $1,771
Manufacturing Employment 47700.8708 0.1296 $6,181
Information Services Employment 11314.8086 0.0153 $174
Financial Services Employment 62614.6797 0.0544 $3,404
Professional and Business Services Employment 67885.3402 0.1370 $9,303
Educational or Health Care Employment 51491.7764 0.2452 $12,627
Leisure, Hospitality, or Entertainment Employment 43018.4305 0.1075 $4,623
Other Services Employment 41629.7443 0.0291 $1,213
Public Administration 51356.2602 0.0395 $2,026
Unemployment Rate Not Seasonally Adjusted -5089.3910 0.0432 -$220

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