Statistical Adjustment Model Summary for Maryland

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 Maryland in PY 2018 compared to all states and how the predicted level of performance (i.e., Estimate0) for Maryland 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 79.6% for Maryland for this performance indicator is calculated by summing the Variable Estimate0 values (total of 1.043) and the specific state fixed effect for this model (-0.247).

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 0.5613 7.31%
Age 25 to 44 -0.0308 0.5038 -1.55%
Age 45 to 54 -0.1545 0.2271 -3.51%
Age 55 to 59 -0.0779 0.1026 -0.80%
Age 60 or more -0.5993 0.0520 -3.12%
Hispanic Ethnicity 0.0815 0.0575 0.47%
Race: Asian -0.2333 0.0325 -0.76%
Race: Black 0.0861 0.5458 4.70%
Race: Hawaiian or Pacific Islander -0.1320 0.0055 -0.07%
Race: American Indian 0.0501 0.0130 0.07%
Race: Multiple -0.1183 0.0200 -0.24%
Highest Grade Completed: High School Equivalency -0.1257 0.4057 -5.10%
Highest Grade Completed: Some College -0.1221 0.1766 -2.16%
Highest Grade Completed: Certificate or Other Post-Secondary Degree 0.0978 0.0395 0.39%
Highest Grade Completed: Associate Degree -0.0773 0.0620 -0.48%
Highest Grade Completed: Bachelor Degree 0.1722 0.1691 2.91%
Highest Grade Completed: Graduate Degree -0.1430 0.0905 -1.30%
Employed at Program Entry 0.1964 0.2616 5.14%
In School at Program Entry 0.1265 0.1021 1.29%
Individual with a Disability -0.1813 0.0865 -1.57%
Veteran 0.2901 0.0550 1.60%
Limited English Proficiency -0.0306 0.0210 -0.06%
Single Parent -0.0942 0.0945 -0.89%
Low Income 0.0081 0.7319 0.59%
Homeless -0.0534 0.0245 -0.13%
Individual who was Incarcerated 0.1550 0.1386 2.15%
Displaced Homemaker -0.1842 0.0095 -0.18%
Received Wages 2 Quarters Prior to Participation 0.1889 0.6403 12.10%
Long-Term Unemployed at Program Entry 0.0157 0.0585 0.09%
UI Claimant -0.0148 0.3137 -0.46%
UI Exhaustee 0.1394 0.0170 0.24%
Supportive Services Recipient 0.0620 0.1161 0.72%
Received Needs-related Payments 0.4886 0.0025 0.12%
Received Other Public Assistance -0.0494 0.0055 -0.03%
SSI or SSDI Recipient -0.0205 0.0160 -0.03%
TANF Recipient 0.0438 0.0265 0.12%
Received Wagner-Peyser Act Services 0.0220 0.8879 1.96%
Median Days in Program -0.0002 204.0000 -3.73%
Economic Condition Natural Resources Employment 2.1266 0.0026 0.54%
Construction Employment 0.8615 0.0615 5.30%
Manufacturing Employment 0.1897 0.0414 0.78%
Information Services Employment -5.3312 0.0146 -7.80%
Financial Services Employment -4.8664 0.0510 -24.80%
Professional and Business Services Employment 3.7575 0.1739 65.35%
Educational or Health Care Employment 0.8235 0.2455 20.22%
Leisure, Hospitality, or Entertainment Employment -0.8923 0.1062 -9.48%
Other Services Employment 4.5274 0.0344 15.59%
Public Administration 2.2149 0.0915 20.26%
Unemployment Rate Not Seasonally Adjusted 0.6822 0.0377 2.57%

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 $7,099 for Maryland for this performance indicator is calculated by summing the Variable Estimate0 values (total of 44788) and the specific state fixed effect for this model (-37688).

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 0.5639 -$1,602
Age 25 to 44 -862.0930 0.5213 -$449
Age 45 to 54 -3144.2089 0.2184 -$687
Age 55 to 59 -5290.3216 0.0944 -$500
Age 60 or more -6059.0062 0.0446 -$270
Hispanic Ethnicity 232.4254 0.0551 $13
Race: Asian -4413.8578 0.0295 -$130
Race: Black -2324.8593 0.5567 -$1,294
Race: Hawaiian or Pacific Islander -6352.7320 0.0066 -$42
Race: American Indian -2692.4326 0.0118 -$32
Race: Multiple 6983.7945 0.0203 $142
Highest Grade Completed: High School Equivalency 362.0217 0.4052 $147
Highest Grade Completed: Some College 826.8902 0.1803 $149
Highest Grade Completed: Certificate or Other Post-Secondary Degree -1324.3050 0.0413 -$55
Highest Grade Completed: Associate Degree 5643.1853 0.0603 $340
Highest Grade Completed: Bachelor Degree 4052.0797 0.1672 $678
Highest Grade Completed: Graduate Degree 8539.9365 0.0879 $750
Employed at Program Entry 965.0801 0.2957 $285
In School at Program Entry 3623.2012 0.1062 $385
Individual with a Disability -989.2237 0.0695 -$69
Veteran -1349.3089 0.0531 -$72
Limited English Proficiency -4419.8922 0.0216 -$96
Single Parent 145.7630 0.0970 $14
Low Income -332.4067 0.7062 -$235
Homeless -446.4262 0.0177 -$8
Individual who was Incarcerated 2013.3031 0.1331 $268
Displaced Homemaker -1947.9185 0.0066 -$13
Received Wages 2 Quarters Prior to Participation 807.6246 0.7062 $570
Wages 2 Quarters Prior to Participation 0.3653 5540.0000 $2,024
Long-Term Unemployed at Program Entry 2011.8227 0.0492 $99
UI Claimant 685.8891 0.3226 $221
UI Exhaustee -2567.3504 0.0144 -$37
Supportive Services Recipient 912.9138 0.1213 $111
Received Needs-related Payments 15112.5289 0.0033 $50
Received Other Public Assistance 107.5299 0.0046 $0
SSI or SSDI Recipient -5911.8510 0.0079 -$47
TANF Recipient 840.8641 0.0236 $20
Received Wagner-Peyser Act Services -205.4928 0.8911 -$183
Median Days in Program 3.2489 201.0000 $653
Economic Condition Natural Resources Employment 24063.8444 0.0026 $61
Construction Employment 32326.4938 0.0615 $1,987
Manufacturing Employment 39237.2625 0.0414 $1,623
Information Services Employment -48189.2565 0.0146 -$705
Financial Services Employment 4074.2901 0.0510 $208
Professional and Business Services Employment 96754.4484 0.1739 $16,829
Educational or Health Care Employment 56163.1547 0.2455 $13,790
Leisure, Hospitality, or Entertainment Employment 57668.0011 0.1062 $6,127
Other Services Employment 10767.7935 0.0344 $371
Public Administration 39658.6388 0.0915 $3,627
Unemployment Rate Not Seasonally Adjusted -6106.3827 0.0377 -$230

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 61.7% for Maryland for this performance indicator is calculated by summing the Variable Estimate0 values (total of 6.895) and the specific state fixed effect for this model (-6.277).

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 0.5950 -21.50%
Age 25 to 44 0.5218 0.5623 29.34%
Age 45 to 54 -0.0702 0.1797 -1.26%
Age 55 to 59 -0.9975 0.0654 -6.52%
Age 60 or more 2.9217 0.0408 11.93%
Hispanic Ethnicity -1.4456 0.0504 -7.28%
Race: Asian 2.1310 0.0354 7.54%
Race: Black -0.5671 0.5473 -31.04%
Race: American Indian 0.8520 0.0157 1.33%
Race: Multiple 1.9759 0.0313 6.19%
Highest Grade Completed: High School Equivalency -0.1218 0.4765 -5.81%
Highest Grade Completed: Some College -0.1842 0.1770 -3.26%
Highest Grade Completed: Certificate or Other Post-Secondary Degree 0.0731 0.0449 0.33%
Highest Grade Completed: Associate Degree -0.8544 0.0565 -4.83%
Highest Grade Completed: Bachelor Degree -0.2005 0.1361 -2.73%
Highest Grade Completed: Graduate Degree 1.8387 0.0606 11.14%
Employed at Program Entry 0.3647 0.3479 12.69%
In School at Program Entry -0.3045 0.0579 -1.76%
Individual with a Disability -0.2611 0.0953 -2.49%
Veteran 0.2508 0.0531 1.33%
Limited English Proficiency 0.8810 0.0599 5.28%
Single Parent 0.2135 0.1872 4.00%
Individual who was Incarcerated 0.7809 0.1150 8.98%
Received Wages 2 Quarters Prior to Participation -0.0013 0.6576 -0.08%
Long-Term Unemployed at Program Entry 0.0652 0.1654 1.08%
UI Exhaustee 0.0104 0.0150 0.02%
Supportive Services Recipient -0.1297 0.2471 -3.20%
SSI or SSDI Recipient 0.4929 0.0293 1.44%
TANF Recipient -0.2848 0.0313 -0.89%
Received Wagner-Peyser Act Services 0.0732 0.8155 5.97%
Median Days in Program 0.0004 191.0000 6.77%
Median Days Enrolled in Education or Training -0.0002 80.0000 -1.95%
Percent Enrolled in Education or Training Under 30 Days -0.0087 0.1852 -0.16%
Economic Condition Natural Resources Employment 10.0155 0.0026 2.56%
Construction Employment 8.9287 0.0615 54.88%
Manufacturing Employment 12.1240 0.0414 50.15%
Information Services Employment -43.8313 0.0146 -64.10%
Financial Services Employment 31.7234 0.0510 161.69%
Professional and Business Services Employment 7.5758 0.1739 131.77%
Educational or Health Care Employment 9.9286 0.2455 243.78%
Leisure, Hospitality, or Entertainment Employment 2.5813 0.1062 27.43%
Other Services Employment 32.8685 0.0344 113.19%
Public Administration -0.1431 0.0915 -1.31%
Unemployment Rate Not Seasonally Adjusted -13.5535 0.0377 -51.14%

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 84.0% for Maryland for this performance indicator is calculated by summing the Variable Estimate0 values (total of -1.776) and the specific state fixed effect for this model (2.616).

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 0.5946 3.54%
Age 25 to 44 0.0189 0.3893 0.74%
Age 45 to 54 -0.0169 0.3321 -0.56%
Age 55 to 59 0.1060 0.1562 1.66%
Age 60 or more -0.1905 0.1009 -1.92%
Hispanic Ethnicity 0.1185 0.0366 0.43%
Race: Asian -0.2910 0.0411 -1.20%
Race: Black -0.0358 0.3759 -1.35%
Race: Hawaiian or Pacific Islander 0.8792 0.0027 0.24%
Race: American Indian -0.0983 0.0125 -0.12%
Race: Multiple -0.1947 0.0143 -0.28%
Highest Grade Completed: High School Equivalency -0.0259 0.2643 -0.69%
Highest Grade Completed: Some College -0.1942 0.1705 -3.31%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.1799 0.0241 -0.43%
Highest Grade Completed: Associate Degree -0.0907 0.0670 -0.61%
Highest Grade Completed: Bachelor Degree -0.1447 0.2455 -3.55%
Highest Grade Completed: Graduate Degree -0.1210 0.1509 -1.83%
Employed at Program Entry 0.1061 0.0473 0.50%
In School at Program Entry -0.0254 0.1571 -0.40%
Individual with a Disability -0.0527 0.0366 -0.19%
Veteran 0.0056 0.0589 0.03%
Limited English Proficiency -0.2521 0.0089 -0.23%
Single Parent 0.0446 0.0580 0.26%
Low Income -0.0518 0.4607 -2.39%
Homeless 0.0306 0.0027 0.01%
Individual who was Incarcerated 0.3775 0.0500 1.89%
Displaced Homemaker -0.2274 0.0080 -0.18%
Received Wages 2 Quarters Prior to Participation 0.1131 0.8982 10.16%
Long-Term Unemployed at Program Entry 0.0574 0.0330 0.19%
UI Claimant 0.0208 0.8357 1.74%
UI Exhaustee 0.0737 0.0464 0.34%
Supportive Services Recipient 0.0496 0.0955 0.47%
Received Needs-related Payments -0.4938 0.0027 -0.13%
Received Other Public Assistance -0.1259 0.0000 0.00%
SSI or SSDI Recipient 0.8134 0.0018 0.15%
TANF Recipient -0.5301 0.0045 -0.24%
Received Wagner-Peyser Act Services -0.0512 0.9670 -4.95%
Median Days in Program 0.0000 233.0000 0.19%
Economic Condition Natural Resources Employment -2.0224 0.0026 -0.52%
Construction Employment -0.4670 0.0615 -2.87%
Manufacturing Employment -1.7064 0.0414 -7.06%
Information Services Employment -9.8998 0.0146 -14.48%
Financial Services Employment -6.2744 0.0510 -31.98%
Professional and Business Services Employment -3.6027 0.1739 -62.66%
Educational or Health Care Employment -1.9946 0.2455 -48.97%
Leisure, Hospitality, or Entertainment Employment -2.8519 0.1062 -30.30%
Other Services Employment 3.0428 0.0344 10.48%
Public Administration 1.2295 0.0915 11.24%
Unemployment Rate Not Seasonally Adjusted 0.4118 0.0377 1.55%

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 $9,336 for Maryland for this performance indicator is calculated by summing the Variable Estimate0 values (total of 39619) and the specific state fixed effect for this model (-30283).

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 0.5862 -$1,115
Age 25 to 44 1115.5154 0.3968 $443
Age 45 to 54 -125.9873 0.3302 -$42
Age 55 to 59 -2126.3785 0.1545 -$329
Age 60 or more -2492.9312 0.0952 -$237
Hispanic Ethnicity -857.7550 0.0317 -$27
Race: Asian -4684.9713 0.0381 -$178
Race: Black -1536.6027 0.3884 -$597
Race: Hawaiian or Pacific Islander -3269.1753 0.0032 -$10
Race: American Indian -3522.2138 0.0116 -$41
Race: Multiple -3712.0594 0.0127 -$47
Highest Grade Completed: High School Equivalency -1400.0970 0.2688 -$376
Highest Grade Completed: Some College -1902.9048 0.1725 -$328
Highest Grade Completed: Certificate or Other Post-Secondary Degree 83.4151 0.0243 $2
Highest Grade Completed: Associate Degree 1526.2402 0.0667 $102
Highest Grade Completed: Bachelor Degree 1169.4179 0.2455 $287
Highest Grade Completed: Graduate Degree 2155.0497 0.1471 $317
Employed at Program Entry 1700.7794 0.0476 $81
In School at Program Entry 3787.5103 0.1545 $585
Individual with a Disability 279.5931 0.0296 $8
Veteran 1445.8344 0.0571 $83
Limited English Proficiency -2976.1328 0.0074 -$22
Single Parent -784.4348 0.0550 -$43
Low Income -538.7097 0.4434 -$239
Homeless 7893.8250 0.0032 $25
Individual who was Incarcerated 1805.9783 0.0540 $97
Displaced Homemaker 192.7564 0.0074 $1
Received Wages 2 Quarters Prior to Participation 21.0817 0.9196 $19
Wages 2 Quarters Prior to Participation 0.0917 10445.0000 $957
Long-Term Unemployed at Program Entry 1348.3682 0.0296 $40
UI Claimant 68.6962 0.8466 $58
UI Exhaustee -2493.0132 0.0402 -$100
Supportive Services Recipient 176.1628 0.0931 $16
Received Needs-related Payments 6660.1906 0.0032 $21
Received Other Public Assistance 470.0451 0.0000 $0
SSI or SSDI Recipient -2105.8014 0.0011 -$2
TANF Recipient -4222.3011 0.0042 -$18
Received Wagner-Peyser Act Services -403.3425 0.9651 -$389
Median Days in Program 2.2222 218.0000 $484
Economic Condition Natural Resources Employment -27241.5941 0.0026 -$70
Construction Employment 36651.6742 0.0615 $2,253
Manufacturing Employment 47186.5858 0.0414 $1,952
Information Services Employment -260263.7041 0.0146 -$3,806
Financial Services Employment 85893.1957 0.0510 $4,378
Professional and Business Services Employment 95022.1320 0.1739 $16,527
Educational or Health Care Employment 51172.3083 0.2455 $12,564
Leisure, Hospitality, or Entertainment Employment 43978.6506 0.1062 $4,673
Other Services Employment -4546.6888 0.0344 -$157
Public Administration 22271.2780 0.0915 $2,037
Unemployment Rate Not Seasonally Adjusted -5795.6816 0.0377 -$219

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 63.3% for Maryland for this performance indicator is calculated by summing the Variable Estimate0 values (total of 6.355) and the specific state fixed effect for this model (-5.722).

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 0.5877 -8.87%
Age 25 to 44 -0.0655 0.4076 -2.67%
Age 45 to 54 0.2414 0.3009 7.27%
Age 55 to 59 0.4579 0.1517 6.94%
Age 60 or more 0.9139 0.1090 9.96%
Hispanic Ethnicity -0.6646 0.0450 -2.99%
Race: Asian -0.5340 0.0237 -1.27%
Race: Black -0.3293 0.3649 -12.02%
Race: American Indian 2.6465 0.0118 3.14%
Race: Multiple 0.0503 0.0071 0.04%
Highest Grade Completed: High School Equivalency -0.1922 0.2891 -5.56%
Highest Grade Completed: Some College -0.2384 0.2085 -4.97%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.2607 0.0261 -0.68%
Highest Grade Completed: Associate Degree 0.2625 0.0829 2.18%
Highest Grade Completed: Bachelor Degree -0.1123 0.2464 -2.77%
Highest Grade Completed: Graduate Degree -0.4275 0.1209 -5.17%
Employed at Program Entry -0.0215 0.0640 -0.14%
In School at Program Entry -0.2643 0.0355 -0.94%
Individual with a Disability -1.4481 0.0592 -8.58%
Veteran -0.9235 0.0687 -6.35%
Limited English Proficiency 0.4514 0.0237 1.07%
Single Parent 0.3691 0.1256 4.64%
Individual who was Incarcerated 0.4693 0.0616 2.89%
Received Wages 2 Quarters Prior to Participation 0.0287 0.8981 2.58%
Long-Term Unemployed at Program Entry 0.3881 0.1066 4.14%
UI Exhaustee 0.3561 0.0427 1.52%
Supportive Services Recipient -0.0615 0.1848 -1.14%
SSI or SSDI Recipient -0.4356 0.0071 -0.31%
TANF Recipient -3.8716 0.0047 -1.83%
Received Wagner-Peyser Act Services -0.0963 0.9645 -9.29%
Median Days in Program -0.0003 243.0000 -7.81%
Median Days Enrolled in Education or Training -0.0003 82.0000 -2.24%
Percent Enrolled in Education or Training Under 30 Days 0.1620 0.1896 3.07%
Economic Condition Natural Resources Employment -8.0806 0.0026 -2.06%
Construction Employment 4.4493 0.0615 27.35%
Manufacturing Employment 9.8551 0.0414 40.76%
Information Services Employment -58.7056 0.0146 -85.85%
Financial Services Employment 12.1977 0.0510 62.17%
Professional and Business Services Employment 16.0554 0.1739 279.25%
Educational or Health Care Employment 7.1634 0.2455 175.88%
Leisure, Hospitality, or Entertainment Employment 1.5122 0.1062 16.07%
Other Services Employment 65.3154 0.0344 224.94%
Public Administration -2.8478 0.0915 -26.04%
Unemployment Rate Not Seasonally Adjusted -10.8237 0.0377 -40.84%

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 77.5% for Maryland for this performance indicator is calculated by summing the Variable Estimate0 values (total of -0.972) and the specific state fixed effect for this model (1.746).

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 0.5291 3.15%
Age 14 to 15 0.1226 0.0449 0.55%
Age 16 to 17 -0.1436 0.1394 -2.00%
Age 18 to 19 -0.2054 0.3305 -6.79%
Age 20 to 21 0.0105 0.2474 0.26%
Hispanic Ethnicity -0.0628 0.1251 -0.79%
Race: Asian 0.1989 0.0124 0.25%
Race: Black -0.0414 0.6170 -2.55%
Race: Hawaiian or Pacific Islander -0.5342 0.0038 -0.20%
Race: American Indian -0.3341 0.0153 -0.51%
Race: Multiple 0.1508 0.0401 0.60%
Highest Grade Completed: High School Equivalency 0.0691 0.4881 3.37%
Highest Grade Completed: Some College -0.3127 0.0277 -0.87%
Highest Grade Completed: Certificate or Other Post-Secondary Degree 1.1469 0.0067 0.77%
Highest Grade Completed: Associate or Bachelor Degree 0.4935 0.0029 0.14%
Employed at Program Entry 0.2748 0.2159 5.93%
In School at Program Entry 0.0356 0.1729 0.62%
Individual with a Disability -0.0469 0.2254 -1.06%
Limited English Proficiency -0.1392 0.0115 -0.16%
Low Income 0.0375 0.9322 3.50%
Homeless -0.2008 0.0468 -0.94%
Individual who was Incarcerated 0.0635 0.1251 0.79%
Foster Care Youth -0.0100 0.0267 -0.03%
Youth Parent or Pregnant Youth -0.0716 0.2034 -1.46%
Skills/Literacy Deficient at Program Entry 0.0349 0.4575 1.60%
Long-Term Unemployed at Program Entry -0.0867 0.0210 -0.18%
UI Claimant -0.0433 0.0210 -0.09%
Supportive Services Recipient 0.0442 0.1929 0.85%
Received Needs-related Payments 0.7660 0.0000 0.00%
Received Other Public Assistance -0.1510 0.0277 -0.42%
SSI or SSDI Recipient 0.0743 0.0248 0.18%
TANF Recipient -0.0341 0.0401 -0.14%
Pell Grant Recipient 0.0368 0.0010 0.00%
Youth Needing Additional Assistance 0.0005 0.4136 0.02%
Received Wagner-Peyser Act Services 0.0148 0.3754 0.56%
Median Days in Program 0.0000 245.5000 -0.99%
Economic Condition Natural Resources Employment -6.7872 0.0026 -1.73%
Construction Employment -1.8800 0.0615 -11.56%
Manufacturing Employment -1.3602 0.0414 -5.63%
Information Services Employment -7.2974 0.0146 -10.67%
Financial Services Employment -2.1367 0.0510 -10.89%
Professional and Business Services Employment -2.5564 0.1739 -44.46%
Educational or Health Care Employment 0.0247 0.2455 0.61%
Leisure, Hospitality, or Entertainment Employment -0.3944 0.1062 -4.19%
Other Services Employment -10.7940 0.0344 -37.17%
Public Administration 3.2993 0.0915 30.17%
Unemployment Rate Not Seasonally Adjusted -1.4872 0.0377 -5.61%

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 $3,548 for Maryland for this performance indicator is calculated by summing the Variable Estimate0 values (total of 15818) and the specific state fixed effect for this model (-12270).

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 0.5563 -$1,044.40
Age 14 to 15 -92.3013 0.0492 -$4.54
Age 16 to 17 -1309.0587 0.1332 -$174.43
Age 18 to 19 -1066.4762 0.3118 -$332.50
Age 20 to 21 649.4931 0.2561 $166.36
Hispanic Ethnicity 1913.4585 0.1229 $235.16
Race: Asian 649.7122 0.0129 $8.41
Race: Black -886.3703 0.6300 -$558.42
Race: Hawaiian or Pacific Islander -3388.4232 0.0026 -$8.77
Race: American Indian -184.4720 0.0155 -$2.86
Race: Multiple 933.1134 0.0414 $38.63
Highest Grade Completed: High School Equivalency 1383.9408 0.5097 $705.40
Highest Grade Completed: Some College -828.1913 0.0310 -$25.71
Highest Grade Completed: Certificate or Other Post-Secondary Degree 173.0955 0.0065 $1.12
Highest Grade Completed: Associate or Bachelor Degree 6672.3330 0.0039 $25.90
Employed at Program Entry 613.7857 0.2652 $162.78
In School at Program Entry 546.1994 0.1527 $83.38
Individual with a Disability -495.1811 0.1889 -$93.53
Limited English Proficiency 2456.3023 0.0129 $31.78
Low Income -305.7985 0.9224 -$282.06
Homeless 983.9044 0.0388 $38.19
Individual who was Incarcerated -1284.6596 0.1087 -$139.60
Foster Care Youth 1009.8293 0.0233 $23.51
Youth Parent or Pregnant Youth 854.5128 0.2199 $187.93
Skills/Literacy Deficient at Program Entry -283.4775 0.4631 -$131.29
Long-Term Unemployed at Program Entry -630.2664 0.0181 -$11.41
UI Claimant -462.5838 0.0259 -$11.97
Supportive Services Recipient 161.1750 0.1940 $31.28
Received Needs-related Payments 2823.2240 0.0000 $0.00
Received Other Public Assistance -184.0786 0.0323 -$5.95
SSI or SSDI Recipient -1658.7545 0.0207 -$34.33
TANF Recipient -539.6509 0.0388 -$20.94
Pell Grant Recipient 104.1843 0.0013 $0.13
Youth Needing Additional Assistance -4.3341 0.4256 -$1.84
Received Wagner-Peyser Act Services -27.8731 0.3842 -$10.71
Median Days in Program 0.5942 244.5000 $145.28
Economic Condition Natural Resources Employment -3172.1958 0.0026 -$8.10
Construction Employment 10994.4772 0.0615 $675.83
Manufacturing Employment 21559.9593 0.0414 $891.78
Information Services Employment -55465.6493 0.0146 -$811.17
Financial Services Employment 44805.1055 0.0510 $2,283.64
Professional and Business Services Employment 14219.0161 0.1739 $2,473.11
Educational or Health Care Employment 20372.0444 0.2455 $5,001.97
Leisure, Hospitality, or Entertainment Employment 7088.2477 0.1062 $753.10
Other Services Employment 57026.8505 0.0344 $1,963.91
Public Administration 43573.5139 0.0915 $3,984.85
Unemployment Rate Not Seasonally Adjusted -10090.2192 0.0377 -$380.72

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 50.2% for Maryland for this performance indicator is calculated by summing the Variable Estimate0 values (total of 4.5) and the specific state fixed effect for this model (-3.998).

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 0.5709 -15.75%
Age 14 to 15 -0.8106 0.0246 -1.99%
Age 16 to 17 -0.9025 0.1218 -10.99%
Age 18 to 19 -0.6998 0.3620 -25.33%
Age 20 to 21 -1.6404 0.2436 -39.96%
Hispanic Ethnicity -0.0170 0.0670 -0.11%
Race: Asian -0.0162 0.0134 -0.02%
Race: Black 0.0042 0.6637 0.28%
Race: American Indian -0.1578 0.0156 -0.25%
Race: Multiple 1.9727 0.0369 7.27%
Highest Grade Completed: High School Equivalency -0.2692 0.4626 -12.45%
Highest Grade Completed: Some College 1.0513 0.0123 1.29%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.6449 0.0034 -0.22%
Highest Grade Completed: Associate or Bachelor Degree 1.9000 0.0089 1.70%
In School at Program Entry 0.0220 0.2089 0.46%
Skills/Literacy Deficient at Program Entry 0.1976 0.6436 12.72%
UI Claimant 0.0198 0.0034 0.01%
Supportive Services Recipient -0.0712 0.3128 -2.23%
Received Other Public Assistance 0.2742 0.0011 0.03%
SSI or SSDI Recipient 0.5536 0.0223 1.24%
Pell Grant Recipient -0.8864 0.0022 -0.20%
Received Wagner-Peyser Act Services -0.0503 0.3408 -1.71%
Median Days Enrolled in Education or Training -0.0003 132.0000 -4.31%
Percent Enrolled in Education or Training Under 30 Days -0.3441 0.1419 -4.88%
Economic Condition Natural Resources Employment 7.6282 0.0026 1.95%
Construction Employment 9.5740 0.0615 58.85%
Manufacturing Employment 5.8313 0.0414 24.12%
Information Services Employment -42.8136 0.0146 -62.61%
Financial Services Employment -14.2433 0.0510 -72.60%
Professional and Business Services Employment 14.4769 0.1739 251.80%
Educational or Health Care Employment 7.0634 0.2455 173.43%
Leisure, Hospitality, or Entertainment Employment 6.2993 0.1062 66.93%
Other Services Employment 50.8391 0.0344 175.08%
Public Administration -7.3408 0.0915 -67.13%
Unemployment Rate Not Seasonally Adjusted -1.1663 0.0377 -4.40%

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 66.4% for Maryland for this performance indicator is calculated by summing the Variable Estimate0 values (total of 1.247) and the specific state fixed effect for this model (-0.583).

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 0.0801 0.5128 4.11%
Age 25 to 44 0.1086 0.4476 4.86%
Age 45 to 54 -0.0860 0.2236 -1.92%
Age 55 to 59 -0.0070 0.1126 -0.08%
Age 60 or more -0.0629 0.1309 -0.82%
Hispanic Ethnicity 0.2326 0.0422 0.98%
Race: Asian -0.2354 0.0260 -0.61%
Race: Black -0.1609 0.4465 -7.19%
Race: Hawaiian or Pacific Islander 0.9703 0.0030 0.29%
Race: American Indian -0.3062 0.0129 -0.40%
Race: Multiple 0.2471 0.0156 0.38%
Highest Grade Completed: High School Equivalency -0.0172 0.3217 -0.55%
Highest Grade Completed: Some College 0.0386 0.1770 0.68%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.0422 0.0381 -0.16%
Highest Grade Completed: Associate Degree 0.3496 0.0617 2.16%
Highest Grade Completed: Bachelor Degree -0.6768 0.1653 -11.18%
Highest Grade Completed: Graduate Degree -0.5246 0.0885 -4.64%
Employed at Program Entry 0.0865 0.0728 0.63%
In School at Program Entry -0.0903 0.0978 -0.88%
Individual with a Disability -0.3557 0.0346 -1.23%
Veteran 0.2170 0.0579 1.26%
Limited English Proficiency -0.0185 0.0016 0.00%
Single Parent 0.2027 0.0062 0.13%
Low Income 0.0926 0.0698 0.65%
Homeless -0.0667 0.0106 -0.07%
Individual who was Incarcerated 0.1850 0.0111 0.21%
Displaced Homemaker -0.2304 0.0019 -0.04%
Received Wages 2 Quarters Prior to Participation 0.3174 0.8667 27.51%
Long-Term Unemployed at Program Entry -0.1541 0.0070 -0.11%
UI Claimant -0.0385 0.2831 -1.09%
UI Exhaustee -0.0897 0.0035 -0.03%
Supportive Services Recipient -0.1026 0.0071 -0.07%
Received Needs-related Payments -9.8950 0.0001 -0.14%
Received Other Public Assistance -0.1163 0.0003 0.00%
SSI or SSDI Recipient 1.0873 0.0019 0.21%
TANF Recipient -0.5680 0.0017 -0.10%
Median Days in Program -0.0003 37.0000 -1.02%
Economic Condition Natural Resources Employment 1.6856 0.0026 0.43%
Construction Employment 1.5411 0.0615 9.47%
Manufacturing Employment 1.0127 0.0414 4.19%
Information Services Employment -0.4595 0.0146 -0.67%
Financial Services Employment 2.9649 0.0510 15.11%
Professional and Business Services Employment 0.9431 0.1739 16.40%
Educational or Health Care Employment 1.2831 0.2455 31.50%
Leisure, Hospitality, or Entertainment Employment 0.5919 0.1062 6.29%
Other Services Employment 3.9021 0.0344 13.44%
Public Administration 1.7006 0.0915 15.55%
Unemployment Rate Not Seasonally Adjusted 0.3440 0.0377 1.30%

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 $6,379 for Maryland for this performance indicator is calculated by summing the Variable Estimate0 values (total of 42186) and the specific state fixed effect for this model (-35807).

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 0.5203 -$1,444
Age 25 to 44 1526.7709 0.4726 $721
Age 45 to 54 223.6212 0.2230 $50
Age 55 to 59 1725.9534 0.1078 $186
Age 60 or more 3989.3863 0.1015 $405
Hispanic Ethnicity 1506.2736 0.0427 $64
Race: Asian -1285.7589 0.0239 -$31
Race: Black -2926.8319 0.4597 -$1,346
Race: Hawaiian or Pacific Islander -2473.0352 0.0029 -$7
Race: American Indian -5567.8497 0.0130 -$73
Race: Multiple 10678.0968 0.0154 $164
Highest Grade Completed: High School Equivalency -1763.8797 0.3249 -$573
Highest Grade Completed: Some College -2177.4526 0.1774 -$386
Highest Grade Completed: Certificate or Other Post-Secondary Degree -2180.3190 0.0397 -$86
Highest Grade Completed: Associate Degree 2095.5471 0.0645 $135
Highest Grade Completed: Bachelor Degree 72.8128 0.1691 $12
Highest Grade Completed: Graduate Degree -5012.8376 0.0858 -$430
Employed at Program Entry 456.1906 0.0877 $40
In School at Program Entry -1155.2072 0.0993 -$115
Individual with a Disability -5107.0692 0.0262 -$134
Veteran -913.8967 0.0524 -$48
Limited English Proficiency 1563.7512 0.0018 $3
Single Parent 660.1018 0.0073 $5
Low Income 634.4633 0.0728 $46
Homeless -3513.0948 0.0088 -$31
Individual who was Incarcerated 1920.7679 0.0112 $21
Displaced Homemaker -10834.3804 0.0017 -$18
Received Wages 2 Quarters Prior to Participation -219.4792 0.9053 -$199
Wages 2 Quarters Prior to Participation 0.2612 7909.1600 $2,065
Long-Term Unemployed at Program Entry 771.2849 0.0056 $4
UI Claimant 454.7967 0.2925 $133
UI Exhaustee 247.9889 0.0035 $1
Supportive Services Recipient -636.3855 0.0082 -$5
Received Needs-related Payments -21804.7067 0.0002 -$5
Received Other Public Assistance -1174.5793 0.0004 -$0
SSI or SSDI Recipient 10874.7587 0.0008 $9
TANF Recipient 1657.8393 0.0018 $3
Median Days in Program 0.8717 40.0000 $35
Economic Condition Natural Resources Employment 37057.6079 0.0026 $95
Construction Employment 42760.7710 0.0615 $2,628
Manufacturing Employment 47700.8708 0.0414 $1,973
Information Services Employment 11314.8086 0.0146 $165
Financial Services Employment 62614.6797 0.0510 $3,191
Professional and Business Services Employment 67885.3402 0.1739 $11,807
Educational or Health Care Employment 51491.7764 0.2455 $12,643
Leisure, Hospitality, or Entertainment Employment 43018.4305 0.1062 $4,571
Other Services Employment 41629.7443 0.0344 $1,434
Public Administration 51356.2602 0.0915 $4,697
Unemployment Rate Not Seasonally Adjusted -5089.3910 0.0377 -$192

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