Statistical Adjustment Model Summary for Alaska

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 Alaska in PY 2018 compared to all states and how the predicted level of performance (i.e., Estimate0) for Alaska 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 81.6% for Alaska for this performance indicator is calculated by summing the Variable Estimate0 values (total of 0.903) and the specific state fixed effect for this model (-0.087).

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 0.4286 5.58%
Age 25 to 44 -0.0308 0.4800 -1.48%
Age 45 to 54 -0.1545 0.1314 -2.03%
Age 55 to 59 -0.0779 0.0286 -0.22%
Age 60 or more -0.5993 0.0114 -0.68%
Hispanic Ethnicity 0.0815 0.0800 0.65%
Race: Asian -0.2333 0.0514 -1.20%
Race: Black 0.0861 0.1029 0.89%
Race: Hawaiian or Pacific Islander -0.1320 0.0286 -0.38%
Race: American Indian 0.0501 0.2686 1.34%
Race: Multiple -0.1183 0.0800 -0.95%
Highest Grade Completed: High School Equivalency -0.1257 0.5829 -7.32%
Highest Grade Completed: Some College -0.1221 0.2457 -3.00%
Highest Grade Completed: Certificate or Other Post-Secondary Degree 0.0978 0.0571 0.56%
Highest Grade Completed: Associate Degree -0.0773 0.0400 -0.31%
Highest Grade Completed: Bachelor Degree 0.1722 0.0057 0.10%
Highest Grade Completed: Graduate Degree -0.1430 0.0000 0.00%
Employed at Program Entry 0.1964 0.4343 8.53%
In School at Program Entry 0.1265 0.2229 2.82%
Individual with a Disability -0.1813 0.0857 -1.55%
Veteran 0.2901 0.0914 2.65%
Limited English Proficiency -0.0306 0.0171 -0.05%
Single Parent -0.0942 0.2000 -1.88%
Low Income 0.0081 0.8571 0.69%
Homeless -0.0534 0.0514 -0.27%
Individual who was Incarcerated 0.1550 0.1657 2.57%
Displaced Homemaker -0.1842 0.0000 0.00%
Received Wages 2 Quarters Prior to Participation 0.1889 0.5829 11.01%
Long-Term Unemployed at Program Entry 0.0157 0.3943 0.62%
UI Claimant -0.0148 0.1771 -0.26%
UI Exhaustee 0.1394 0.0857 1.20%
Supportive Services Recipient 0.0620 0.0457 0.28%
Received Needs-related Payments 0.4886 0.0000 0.00%
Received Other Public Assistance -0.0494 0.3771 -1.86%
SSI or SSDI Recipient -0.0205 0.0171 -0.04%
TANF Recipient 0.0438 0.0857 0.38%
Received Wagner-Peyser Act Services 0.0220 0.0000 0.00%
Median Days in Program -0.0002 178.0000 -3.26%
Economic Condition Natural Resources Employment 2.1266 0.0443 9.41%
Construction Employment 0.8615 0.0511 4.41%
Manufacturing Employment 0.1897 0.0394 0.75%
Information Services Employment -5.3312 0.0170 -9.09%
Financial Services Employment -4.8664 0.0359 -17.47%
Professional and Business Services Employment 3.7575 0.0878 32.99%
Educational or Health Care Employment 0.8235 0.2419 19.92%
Leisure, Hospitality, or Entertainment Employment -0.8923 0.1155 -10.31%
Other Services Employment 4.5274 0.0311 14.07%
Public Administration 2.2149 0.1272 28.17%
Unemployment Rate Not Seasonally Adjusted 0.6822 0.0644 4.39%

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 $7,083 for Alaska for this performance indicator is calculated by summing the Variable Estimate0 values (total of 39451) and the specific state fixed effect for this model (-32368).

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 0.4354 -$1,237
Age 25 to 44 -862.0930 0.5238 -$452
Age 45 to 54 -3144.2089 0.1156 -$364
Age 55 to 59 -5290.3216 0.0136 -$72
Age 60 or more -6059.0062 0.0136 -$82
Hispanic Ethnicity 232.4254 0.0884 $21
Race: Asian -4413.8578 0.0544 -$240
Race: Black -2324.8593 0.1088 -$253
Race: Hawaiian or Pacific Islander -6352.7320 0.0340 -$216
Race: American Indian -2692.4326 0.2517 -$678
Race: Multiple 6983.7945 0.0816 $570
Highest Grade Completed: High School Equivalency 362.0217 0.5714 $207
Highest Grade Completed: Some College 826.8902 0.2721 $225
Highest Grade Completed: Certificate or Other Post-Secondary Degree -1324.3050 0.0544 -$72
Highest Grade Completed: Associate Degree 5643.1853 0.0408 $230
Highest Grade Completed: Bachelor Degree 4052.0797 0.0068 $28
Highest Grade Completed: Graduate Degree 8539.9365 0.0000 $0
Employed at Program Entry 965.0801 0.4558 $440
In School at Program Entry 3623.2012 0.2381 $863
Individual with a Disability -989.2237 0.0612 -$61
Veteran -1349.3089 0.0884 -$119
Limited English Proficiency -4419.8922 0.0136 -$60
Single Parent 145.7630 0.2109 $31
Low Income -332.4067 0.8367 -$278
Homeless -446.4262 0.0476 -$21
Individual who was Incarcerated 2013.3031 0.1701 $342
Displaced Homemaker -1947.9185 0.0000 $0
Received Wages 2 Quarters Prior to Participation 807.6246 0.6327 $511
Wages 2 Quarters Prior to Participation 0.3653 4183.0000 $1,528
Long-Term Unemployed at Program Entry 2011.8227 0.3537 $712
UI Claimant 685.8891 0.1905 $131
UI Exhaustee -2567.3504 0.0952 -$245
Supportive Services Recipient 912.9138 0.0272 $25
Received Needs-related Payments 15112.5289 0.0000 $0
Received Other Public Assistance 107.5299 0.3469 $37
SSI or SSDI Recipient -5911.8510 0.0000 $0
TANF Recipient 840.8641 0.0816 $69
Received Wagner-Peyser Act Services -205.4928 0.0000 $0
Median Days in Program 3.2489 191.0000 $621
Economic Condition Natural Resources Employment 24063.8444 0.0443 $1,065
Construction Employment 32326.4938 0.0511 $1,653
Manufacturing Employment 39237.2625 0.0394 $1,545
Information Services Employment -48189.2565 0.0170 -$821
Financial Services Employment 4074.2901 0.0359 $146
Professional and Business Services Employment 96754.4484 0.0878 $8,494
Educational or Health Care Employment 56163.1547 0.2419 $13,585
Leisure, Hospitality, or Entertainment Employment 57668.0011 0.1155 $6,661
Other Services Employment 10767.7935 0.0311 $335
Public Administration 39658.6388 0.1272 $5,043
Unemployment Rate Not Seasonally Adjusted -6106.3827 0.0644 -$393

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 75.2% for Alaska for this performance indicator is calculated by summing the Variable Estimate0 values (total of 5.986) and the specific state fixed effect for this model (-5.234).

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 0.3456 -12.49%
Age 25 to 44 0.5218 0.5809 30.31%
Age 45 to 54 -0.0702 0.0625 -0.44%
Age 55 to 59 -0.9975 0.0037 -0.37%
Age 60 or more 2.9217 0.0074 2.15%
Hispanic Ethnicity -1.4456 0.0919 -13.29%
Race: Asian 2.1310 0.0809 17.24%
Race: Black -0.5671 0.1066 -6.05%
Race: American Indian 0.8520 0.1728 14.72%
Race: Multiple 1.9759 0.0993 19.61%
Highest Grade Completed: High School Equivalency -0.1218 0.4081 -4.97%
Highest Grade Completed: Some College -0.1842 0.2610 -4.81%
Highest Grade Completed: Certificate or Other Post-Secondary Degree 0.0731 0.0551 0.40%
Highest Grade Completed: Associate Degree -0.8544 0.1029 -8.80%
Highest Grade Completed: Bachelor Degree -0.2005 0.0882 -1.77%
Highest Grade Completed: Graduate Degree 1.8387 0.0368 6.76%
Employed at Program Entry 0.3647 0.5699 20.78%
In School at Program Entry -0.3045 0.2574 -7.84%
Individual with a Disability -0.2611 0.0846 -2.21%
Veteran 0.2508 0.4154 10.42%
Limited English Proficiency 0.8810 0.0147 1.30%
Single Parent 0.2135 0.1471 3.14%
Individual who was Incarcerated 0.7809 0.0551 4.31%
Received Wages 2 Quarters Prior to Participation -0.0013 0.4816 -0.06%
Long-Term Unemployed at Program Entry 0.0652 0.1324 0.86%
UI Exhaustee 0.0104 0.0147 0.02%
Supportive Services Recipient -0.1297 0.0221 -0.29%
SSI or SSDI Recipient 0.4929 0.0184 0.91%
TANF Recipient -0.2848 0.0221 -0.63%
Received Wagner-Peyser Act Services 0.0732 0.0000 0.00%
Median Days in Program 0.0004 122.5000 4.34%
Median Days Enrolled in Education or Training -0.0002 28.5000 -0.70%
Percent Enrolled in Education or Training Under 30 Days -0.0087 0.5000 -0.43%
Economic Condition Natural Resources Employment 10.0155 0.0443 44.33%
Construction Employment 8.9287 0.0511 45.66%
Manufacturing Employment 12.1240 0.0394 47.74%
Information Services Employment -43.8313 0.0170 -74.70%
Financial Services Employment 31.7234 0.0359 113.92%
Professional and Business Services Employment 7.5758 0.0878 66.51%
Educational or Health Care Employment 9.9286 0.2419 240.15%
Leisure, Hospitality, or Entertainment Employment 2.5813 0.1155 29.81%
Other Services Employment 32.8685 0.0311 102.12%
Public Administration -0.1431 0.1272 -1.82%
Unemployment Rate Not Seasonally Adjusted -13.5535 0.0644 -87.32%

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 81.9% for Alaska for this performance indicator is calculated by summing the Variable Estimate0 values (total of -1.437) and the specific state fixed effect for this model (2.256).

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 0.3556 2.12%
Age 25 to 44 0.0189 0.6489 1.23%
Age 45 to 54 -0.0169 0.1467 -0.25%
Age 55 to 59 0.1060 0.0400 0.42%
Age 60 or more -0.1905 0.0267 -0.51%
Hispanic Ethnicity 0.1185 0.0978 1.16%
Race: Asian -0.2910 0.0756 -2.20%
Race: Black -0.0358 0.0622 -0.22%
Race: Hawaiian or Pacific Islander 0.8792 0.0222 1.95%
Race: American Indian -0.0983 0.1511 -1.49%
Race: Multiple -0.1947 0.0978 -1.90%
Highest Grade Completed: High School Equivalency -0.0259 0.4133 -1.07%
Highest Grade Completed: Some College -0.1942 0.3689 -7.16%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.1799 0.0978 -1.76%
Highest Grade Completed: Associate Degree -0.0907 0.0844 -0.77%
Highest Grade Completed: Bachelor Degree -0.1447 0.0044 -0.06%
Highest Grade Completed: Graduate Degree -0.1210 0.0044 -0.05%
Employed at Program Entry 0.1061 0.2978 3.16%
In School at Program Entry -0.0254 0.2089 -0.53%
Individual with a Disability -0.0527 0.0844 -0.44%
Veteran 0.0056 0.2267 0.13%
Limited English Proficiency -0.2521 0.0089 -0.22%
Single Parent 0.0446 0.1422 0.63%
Low Income -0.0518 0.4222 -2.19%
Homeless 0.0306 0.0000 0.00%
Individual who was Incarcerated 0.3775 0.0089 0.34%
Displaced Homemaker -0.2274 0.0711 -1.62%
Received Wages 2 Quarters Prior to Participation 0.1131 0.7022 7.94%
Long-Term Unemployed at Program Entry 0.0574 0.1911 1.10%
UI Claimant 0.0208 0.3156 0.66%
UI Exhaustee 0.0737 0.0533 0.39%
Supportive Services Recipient 0.0496 0.0044 0.02%
Received Needs-related Payments -0.4938 0.0000 0.00%
Received Other Public Assistance -0.1259 0.0089 -0.11%
SSI or SSDI Recipient 0.8134 0.0089 0.72%
TANF Recipient -0.5301 0.0133 -0.71%
Received Wagner-Peyser Act Services -0.0512 0.0000 0.00%
Median Days in Program 0.0000 147.0000 0.12%
Economic Condition Natural Resources Employment -2.0224 0.0443 -8.95%
Construction Employment -0.4670 0.0511 -2.39%
Manufacturing Employment -1.7064 0.0394 -6.72%
Information Services Employment -9.8998 0.0170 -16.87%
Financial Services Employment -6.2744 0.0359 -22.53%
Professional and Business Services Employment -3.6027 0.0878 -31.63%
Educational or Health Care Employment -1.9946 0.2419 -48.25%
Leisure, Hospitality, or Entertainment Employment -2.8519 0.1155 -32.94%
Other Services Employment 3.0428 0.0311 9.45%
Public Administration 1.2295 0.1272 15.63%
Unemployment Rate Not Seasonally Adjusted 0.4118 0.0644 2.65%

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 $11,547 for Alaska for this performance indicator is calculated by summing the Variable Estimate0 values (total of 29390) and the specific state fixed effect for this model (-17843).

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 0.3579 -$680
Age 25 to 44 1115.5154 0.6632 $740
Age 45 to 54 -125.9873 0.1421 -$18
Age 55 to 59 -2126.3785 0.0421 -$90
Age 60 or more -2492.9312 0.0211 -$52
Hispanic Ethnicity -857.7550 0.0842 -$72
Race: Asian -4684.9713 0.0842 -$395
Race: Black -1536.6027 0.0421 -$65
Race: Hawaiian or Pacific Islander -3269.1753 0.0211 -$69
Race: American Indian -3522.2138 0.1211 -$426
Race: Multiple -3712.0594 0.0737 -$274
Highest Grade Completed: High School Equivalency -1400.0970 0.4053 -$567
Highest Grade Completed: Some College -1902.9048 0.3789 -$721
Highest Grade Completed: Certificate or Other Post-Secondary Degree 83.4151 0.0895 $7
Highest Grade Completed: Associate Degree 1526.2402 0.0842 $129
Highest Grade Completed: Bachelor Degree 1169.4179 0.0053 $6
Highest Grade Completed: Graduate Degree 2155.0497 0.0053 $11
Employed at Program Entry 1700.7794 0.3053 $519
In School at Program Entry 3787.5103 0.2158 $817
Individual with a Disability 279.5931 0.0684 $19
Veteran 1445.8344 0.2105 $304
Limited English Proficiency -2976.1328 0.0105 -$31
Single Parent -784.4348 0.1368 -$107
Low Income -538.7097 0.3947 -$213
Homeless 7893.8250 0.0000 $0
Individual who was Incarcerated 1805.9783 0.0000 $0
Displaced Homemaker 192.7564 0.0684 $13
Received Wages 2 Quarters Prior to Participation 21.0817 0.7368 $16
Wages 2 Quarters Prior to Participation 0.0917 9741.0000 $893
Long-Term Unemployed at Program Entry 1348.3682 0.1789 $241
UI Claimant 68.6962 0.3474 $24
UI Exhaustee -2493.0132 0.0421 -$105
Supportive Services Recipient 176.1628 0.0000 $0
Received Needs-related Payments 6660.1906 0.0000 $0
Received Other Public Assistance 470.0451 0.0105 $5
SSI or SSDI Recipient -2105.8014 0.0105 -$22
TANF Recipient -4222.3011 0.0158 -$67
Received Wagner-Peyser Act Services -403.3425 0.0000 $0
Median Days in Program 2.2222 147.0000 $327
Economic Condition Natural Resources Employment -27241.5941 0.0443 -$1,206
Construction Employment 36651.6742 0.0511 $1,874
Manufacturing Employment 47186.5858 0.0394 $1,858
Information Services Employment -260263.7041 0.0170 -$4,435
Financial Services Employment 85893.1957 0.0359 $3,084
Professional and Business Services Employment 95022.1320 0.0878 $8,342
Educational or Health Care Employment 51172.3083 0.2419 $12,378
Leisure, Hospitality, or Entertainment Employment 43978.6506 0.1155 $5,080
Other Services Employment -4546.6888 0.0311 -$141
Public Administration 22271.2780 0.1272 $2,832
Unemployment Rate Not Seasonally Adjusted -5795.6816 0.0644 -$373

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 67.3% for Alaska for this performance indicator is calculated by summing the Variable Estimate0 values (total of 3.806) and the specific state fixed effect for this model (-3.133).

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 0.5364 -8.09%
Age 25 to 44 -0.0655 0.5818 -3.81%
Age 45 to 54 0.2414 0.0955 2.30%
Age 55 to 59 0.4579 0.0409 1.87%
Age 60 or more 0.9139 0.0318 2.91%
Hispanic Ethnicity -0.6646 0.0864 -5.74%
Race: Asian -0.5340 0.1000 -5.34%
Race: Black -0.3293 0.0636 -2.10%
Race: American Indian 2.6465 0.1273 33.68%
Race: Multiple 0.0503 0.0818 0.41%
Highest Grade Completed: High School Equivalency -0.1922 0.3682 -7.07%
Highest Grade Completed: Some College -0.2384 0.2364 -5.63%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.2607 0.1909 -4.98%
Highest Grade Completed: Associate Degree 0.2625 0.0864 2.27%
Highest Grade Completed: Bachelor Degree -0.1123 0.0727 -0.82%
Highest Grade Completed: Graduate Degree -0.4275 0.0136 -0.58%
Employed at Program Entry -0.0215 0.4182 -0.90%
In School at Program Entry -0.2643 0.2318 -6.13%
Individual with a Disability -1.4481 0.0500 -7.24%
Veteran -0.9235 0.1091 -10.07%
Limited English Proficiency 0.4514 0.0136 0.62%
Single Parent 0.3691 0.1773 6.54%
Individual who was Incarcerated 0.4693 0.0182 0.85%
Received Wages 2 Quarters Prior to Participation 0.0287 0.7955 2.28%
Long-Term Unemployed at Program Entry 0.3881 0.0955 3.70%
UI Exhaustee 0.3561 0.0091 0.32%
Supportive Services Recipient -0.0615 0.0000 0.00%
SSI or SSDI Recipient -0.4356 0.0000 0.00%
TANF Recipient -3.8716 0.0091 -3.52%
Received Wagner-Peyser Act Services -0.0963 0.0000 0.00%
Median Days in Program -0.0003 175.5000 -5.64%
Median Days Enrolled in Education or Training -0.0003 81.0000 -2.22%
Percent Enrolled in Education or Training Under 30 Days 0.1620 0.2773 4.49%
Economic Condition Natural Resources Employment -8.0806 0.0443 -35.76%
Construction Employment 4.4493 0.0511 22.75%
Manufacturing Employment 9.8551 0.0394 38.80%
Information Services Employment -58.7056 0.0170 -100.04%
Financial Services Employment 12.1977 0.0359 43.80%
Professional and Business Services Employment 16.0554 0.0878 140.95%
Educational or Health Care Employment 7.1634 0.2419 173.27%
Leisure, Hospitality, or Entertainment Employment 1.5122 0.1155 17.47%
Other Services Employment 65.3154 0.0311 202.94%
Public Administration -2.8478 0.1272 -36.21%
Unemployment Rate Not Seasonally Adjusted -10.8237 0.0644 -69.73%

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 56.5% for Alaska for this performance indicator is calculated by summing the Variable Estimate0 values (total of -1.213) and the specific state fixed effect for this model (1.778).

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 0.3966 2.36%
Age 14 to 15 0.1226 0.0000 0.00%
Age 16 to 17 -0.1436 0.3506 -5.04%
Age 18 to 19 -0.2054 0.3764 -7.73%
Age 20 to 21 0.0105 0.1609 0.17%
Hispanic Ethnicity -0.0628 0.0920 -0.58%
Race: Asian 0.1989 0.0603 1.20%
Race: Black -0.0414 0.1149 -0.48%
Race: Hawaiian or Pacific Islander -0.5342 0.0862 -4.61%
Race: American Indian -0.3341 0.4080 -13.63%
Race: Multiple 0.1508 0.2155 3.25%
Highest Grade Completed: High School Equivalency 0.0691 0.3534 2.44%
Highest Grade Completed: Some College -0.3127 0.0115 -0.36%
Highest Grade Completed: Certificate or Other Post-Secondary Degree 1.1469 0.0057 0.66%
Highest Grade Completed: Associate or Bachelor Degree 0.4935 0.0029 0.14%
Employed at Program Entry 0.2748 0.0690 1.89%
In School at Program Entry 0.0356 0.3678 1.31%
Individual with a Disability -0.0469 0.1178 -0.55%
Limited English Proficiency -0.1392 0.0259 -0.36%
Low Income 0.0375 0.9540 3.58%
Homeless -0.2008 0.1782 -3.58%
Individual who was Incarcerated 0.0635 0.0948 0.60%
Foster Care Youth -0.0100 0.0402 -0.04%
Youth Parent or Pregnant Youth -0.0716 0.1264 -0.91%
Skills/Literacy Deficient at Program Entry 0.0349 0.0891 0.31%
Long-Term Unemployed at Program Entry -0.0867 0.9914 -8.60%
UI Claimant -0.0433 0.0115 -0.05%
Supportive Services Recipient 0.0442 0.3075 1.36%
Received Needs-related Payments 0.7660 0.0000 0.00%
Received Other Public Assistance -0.1510 0.2040 -3.08%
SSI or SSDI Recipient 0.0743 0.2845 2.11%
TANF Recipient -0.0341 0.0489 -0.17%
Pell Grant Recipient 0.0368 0.0259 0.10%
Youth Needing Additional Assistance 0.0005 0.9052 0.04%
Received Wagner-Peyser Act Services 0.0148 0.0000 0.00%
Median Days in Program 0.0000 111.5000 -0.45%
Economic Condition Natural Resources Employment -6.7872 0.0443 -30.04%
Construction Employment -1.8800 0.0511 -9.61%
Manufacturing Employment -1.3602 0.0394 -5.36%
Information Services Employment -7.2974 0.0170 -12.44%
Financial Services Employment -2.1367 0.0359 -7.67%
Professional and Business Services Employment -2.5564 0.0878 -22.44%
Educational or Health Care Employment 0.0247 0.2419 0.60%
Leisure, Hospitality, or Entertainment Employment -0.3944 0.1155 -4.56%
Other Services Employment -10.7940 0.0311 -33.54%
Public Administration 3.2993 0.1272 41.96%
Unemployment Rate Not Seasonally Adjusted -1.4872 0.0644 -9.58%

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 $3,030 for Alaska for this performance indicator is calculated by summing the Variable Estimate0 values (total of 13925) and the specific state fixed effect for this model (-10894).

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 0.4078 -$765.68
Age 14 to 15 -92.3013 0.0000 $0.00
Age 16 to 17 -1309.0587 0.2737 -$358.35
Age 18 to 19 -1066.4762 0.4190 -$446.85
Age 20 to 21 649.4931 0.1844 $119.74
Hispanic Ethnicity 1913.4585 0.1006 $192.41
Race: Asian 649.7122 0.0503 $32.67
Race: Black -886.3703 0.1508 -$133.70
Race: Hawaiian or Pacific Islander -3388.4232 0.0670 -$227.16
Race: American Indian -184.4720 0.3296 -$60.80
Race: Multiple 933.1134 0.1955 $182.45
Highest Grade Completed: High School Equivalency 1383.9408 0.4022 $556.67
Highest Grade Completed: Some College -828.1913 0.0223 -$18.51
Highest Grade Completed: Certificate or Other Post-Secondary Degree 173.0955 0.0056 $0.97
Highest Grade Completed: Associate or Bachelor Degree 6672.3330 0.0056 $37.28
Employed at Program Entry 613.7857 0.1061 $65.15
In School at Program Entry 546.1994 0.2849 $155.62
Individual with a Disability -495.1811 0.1341 -$66.39
Limited English Proficiency 2456.3023 0.0279 $68.61
Low Income -305.7985 0.9609 -$293.84
Homeless 983.9044 0.1899 $186.89
Individual who was Incarcerated -1284.6596 0.0838 -$107.65
Foster Care Youth 1009.8293 0.0279 $28.21
Youth Parent or Pregnant Youth 854.5128 0.1508 $128.89
Skills/Literacy Deficient at Program Entry -283.4775 0.1061 -$30.09
Long-Term Unemployed at Program Entry -630.2664 0.9944 -$626.75
UI Claimant -462.5838 0.0112 -$5.17
Supportive Services Recipient 161.1750 0.4078 $65.73
Received Needs-related Payments 2823.2240 0.0000 $0.00
Received Other Public Assistance -184.0786 0.2123 -$39.08
SSI or SSDI Recipient -1658.7545 0.2235 -$370.67
TANF Recipient -539.6509 0.0559 -$30.15
Pell Grant Recipient 104.1843 0.0503 $5.24
Youth Needing Additional Assistance -4.3341 0.8994 -$3.90
Received Wagner-Peyser Act Services -27.8731 0.0000 $0.00
Median Days in Program 0.5942 153.0000 $90.91
Economic Condition Natural Resources Employment -3172.1958 0.0443 -$140.40
Construction Employment 10994.4772 0.0511 $562.25
Manufacturing Employment 21559.9593 0.0394 $848.90
Information Services Employment -55465.6493 0.0170 -$945.22
Financial Services Employment 44805.1055 0.0359 $1,608.93
Professional and Business Services Employment 14219.0161 0.0878 $1,248.28
Educational or Health Care Employment 20372.0444 0.2419 $4,927.60
Leisure, Hospitality, or Entertainment Employment 7088.2477 0.1155 $818.71
Other Services Employment 57026.8505 0.0311 $1,771.87
Public Administration 43573.5139 0.1272 $5,541.00
Unemployment Rate Not Seasonally Adjusted -10090.2192 0.0644 -$650.05

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 57.3% for Alaska for this performance indicator is calculated by summing the Variable Estimate0 values (total of 3.329) and the specific state fixed effect for this model (-2.756).

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 0.4395 -12.12%
Age 14 to 15 -0.8106 0.0209 -1.70%
Age 16 to 17 -0.9025 0.1884 -17.00%
Age 18 to 19 -0.6998 0.3535 -24.74%
Age 20 to 21 -1.6404 0.2488 -40.82%
Hispanic Ethnicity -0.0170 0.1093 -0.19%
Race: Asian -0.0162 0.0674 -0.11%
Race: Black 0.0042 0.1535 0.06%
Race: American Indian -0.1578 0.3140 -4.95%
Race: Multiple 1.9727 0.1860 36.70%
Highest Grade Completed: High School Equivalency -0.2692 0.4140 -11.15%
Highest Grade Completed: Some College 1.0513 0.0209 2.20%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.6449 0.0023 -0.15%
Highest Grade Completed: Associate or Bachelor Degree 1.9000 0.0047 0.88%
In School at Program Entry 0.0220 0.1977 0.44%
Skills/Literacy Deficient at Program Entry 0.1976 0.0419 0.83%
UI Claimant 0.0198 0.0116 0.02%
Supportive Services Recipient -0.0712 0.4349 -3.10%
Received Other Public Assistance 0.2742 0.2907 7.97%
SSI or SSDI Recipient 0.5536 0.0419 2.32%
Pell Grant Recipient -0.8864 0.0140 -1.24%
Received Wagner-Peyser Act Services -0.0503 0.0000 0.00%
Median Days Enrolled in Education or Training -0.0003 115.0000 -3.75%
Percent Enrolled in Education or Training Under 30 Days -0.3441 0.2000 -6.88%
Economic Condition Natural Resources Employment 7.6282 0.0443 33.76%
Construction Employment 9.5740 0.0511 48.96%
Manufacturing Employment 5.8313 0.0394 22.96%
Information Services Employment -42.8136 0.0170 -72.96%
Financial Services Employment -14.2433 0.0359 -51.15%
Professional and Business Services Employment 14.4769 0.0878 127.09%
Educational or Health Care Employment 7.0634 0.2419 170.85%
Leisure, Hospitality, or Entertainment Employment 6.2993 0.1155 72.76%
Other Services Employment 50.8391 0.0311 157.96%
Public Administration -7.3408 0.1272 -93.35%
Unemployment Rate Not Seasonally Adjusted -1.1663 0.0644 -7.51%

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 57.3% for Alaska for this performance indicator is calculated by summing the Variable Estimate0 values (total of 1.281) and the specific state fixed effect for this model (-0.708).

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 0.4260 3.41%
Age 25 to 44 0.1086 0.4508 4.89%
Age 45 to 54 -0.0860 0.1938 -1.67%
Age 55 to 59 -0.0070 0.0957 -0.07%
Age 60 or more -0.0629 0.0975 -0.61%
Hispanic Ethnicity 0.2326 0.0667 1.55%
Race: Asian -0.2354 0.0832 -1.96%
Race: Black -0.1609 0.0808 -1.30%
Race: Hawaiian or Pacific Islander 0.9703 0.0383 3.72%
Race: American Indian -0.3062 0.2954 -9.04%
Race: Multiple 0.2471 0.1087 2.69%
Highest Grade Completed: High School Equivalency -0.0172 0.5481 -0.94%
Highest Grade Completed: Some College 0.0386 0.1916 0.74%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.0422 0.0395 -0.17%
Highest Grade Completed: Associate Degree 0.3496 0.0092 0.32%
Highest Grade Completed: Bachelor Degree -0.6768 0.0656 -4.44%
Highest Grade Completed: Graduate Degree -0.5246 0.0190 -1.00%
Employed at Program Entry 0.0865 0.2595 2.24%
In School at Program Entry -0.0903 0.0998 -0.90%
Individual with a Disability -0.3557 0.0696 -2.48%
Veteran 0.2170 0.0967 2.10%
Limited English Proficiency -0.0185 0.0080 -0.01%
Single Parent 0.2027 0.0821 1.66%
Low Income 0.0926 0.1694 1.57%
Homeless -0.0667 0.0856 -0.57%
Individual who was Incarcerated 0.1850 0.0740 1.37%
Displaced Homemaker -0.2304 0.0132 -0.30%
Received Wages 2 Quarters Prior to Participation 0.3174 0.6231 19.77%
Long-Term Unemployed at Program Entry -0.1541 0.0460 -0.71%
UI Claimant -0.0385 0.8366 -3.22%
UI Exhaustee -0.0897 0.1339 -1.20%
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 0.1036 -1.21%
SSI or SSDI Recipient 1.0873 0.0370 4.02%
TANF Recipient -0.5680 0.0174 -0.99%
Median Days in Program -0.0003 17.0000 -0.47%
Economic Condition Natural Resources Employment 1.6856 0.0443 7.46%
Construction Employment 1.5411 0.0511 7.88%
Manufacturing Employment 1.0127 0.0394 3.99%
Information Services Employment -0.4595 0.0170 -0.78%
Financial Services Employment 2.9649 0.0359 10.65%
Professional and Business Services Employment 0.9431 0.0878 8.28%
Educational or Health Care Employment 1.2831 0.2419 31.04%
Leisure, Hospitality, or Entertainment Employment 0.5919 0.1155 6.84%
Other Services Employment 3.9021 0.0311 12.12%
Public Administration 1.7006 0.1272 21.63%
Unemployment Rate Not Seasonally Adjusted 0.3440 0.0644 2.22%

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 $5,652 for Alaska for this performance indicator is calculated by summing the Variable Estimate0 values (total of 38601) and the specific state fixed effect for this model (-32949).

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 0.4297 -$1,192
Age 25 to 44 1526.7709 0.4560 $696
Age 45 to 54 223.6212 0.2015 $45
Age 55 to 59 1725.9534 0.0968 $167
Age 60 or more 3989.3863 0.0888 $354
Hispanic Ethnicity 1506.2736 0.0690 $104
Race: Asian -1285.7589 0.1064 -$137
Race: Black -2926.8319 0.0799 -$234
Race: Hawaiian or Pacific Islander -2473.0352 0.0395 -$98
Race: American Indian -5567.8497 0.2607 -$1,452
Race: Multiple 10678.0968 0.1034 $1,104
Highest Grade Completed: High School Equivalency -1763.8797 0.5483 -$967
Highest Grade Completed: Some College -2177.4526 0.1988 -$433
Highest Grade Completed: Certificate or Other Post-Secondary Degree -2180.3190 0.0418 -$91
Highest Grade Completed: Associate Degree 2095.5471 0.0100 $21
Highest Grade Completed: Bachelor Degree 72.8128 0.0727 $5
Highest Grade Completed: Graduate Degree -5012.8376 0.0173 -$87
Employed at Program Entry 456.1906 0.2991 $136
In School at Program Entry -1155.2072 0.0934 -$108
Individual with a Disability -5107.0692 0.0510 -$260
Veteran -913.8967 0.0921 -$84
Limited English Proficiency 1563.7512 0.0077 $12
Single Parent 660.1018 0.0810 $54
Low Income 634.4633 0.1388 $88
Homeless -3513.0948 0.0555 -$195
Individual who was Incarcerated 1920.7679 0.0635 $122
Displaced Homemaker -10834.3804 0.0105 -$114
Received Wages 2 Quarters Prior to Participation -219.4792 0.7418 -$163
Wages 2 Quarters Prior to Participation 0.2612 6305.2700 $1,647
Long-Term Unemployed at Program Entry 771.2849 0.0350 $27
UI Claimant 454.7967 0.8074 $367
UI Exhaustee 247.9889 0.1641 $41
Supportive Services Recipient -636.3855 0.0000 $0
Received Needs-related Payments -21804.7067 0.0000 $0
Received Other Public Assistance -1174.5793 0.0869 -$102
SSI or SSDI Recipient 10874.7587 0.0241 $262
TANF Recipient 1657.8393 0.0140 $23
Median Days in Program 0.8717 18.0000 $16
Economic Condition Natural Resources Employment 37057.6079 0.0443 $1,640
Construction Employment 42760.7710 0.0511 $2,187
Manufacturing Employment 47700.8708 0.0394 $1,878
Information Services Employment 11314.8086 0.0170 $193
Financial Services Employment 62614.6797 0.0359 $2,248
Professional and Business Services Employment 67885.3402 0.0878 $5,960
Educational or Health Care Employment 51491.7764 0.2419 $12,455
Leisure, Hospitality, or Entertainment Employment 43018.4305 0.1155 $4,969
Other Services Employment 41629.7443 0.0311 $1,293
Public Administration 51356.2602 0.1272 $6,531
Unemployment Rate Not Seasonally Adjusted -5089.3910 0.0644 -$328

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