Statistical Adjustment Model Summary for South Dakota

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 South Dakota in PY 2018 compared to all states and how the predicted level of performance (i.e., Estimate0) for South Dakota 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 77.7% for South Dakota for this performance indicator is calculated by summing the Variable Estimate0 values (total of 0.484) and the specific state fixed effect for this model (0.293).

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 0.5412 7.05%
Age 25 to 44 -0.0308 0.4485 -1.38%
Age 45 to 54 -0.1545 0.1602 -2.48%
Age 55 to 59 -0.0779 0.0812 -0.63%
Age 60 or more -0.5993 0.0606 -3.63%
Hispanic Ethnicity 0.0815 0.0423 0.35%
Race: Asian -0.2333 0.0378 -0.88%
Race: Black 0.0861 0.0812 0.70%
Race: Hawaiian or Pacific Islander -0.1320 0.0034 -0.05%
Race: American Indian 0.0501 0.2243 1.12%
Race: Multiple -0.1183 0.0400 -0.47%
Highest Grade Completed: High School Equivalency -0.1257 0.4680 -5.88%
Highest Grade Completed: Some College -0.1221 0.1213 -1.48%
Highest Grade Completed: Certificate or Other Post-Secondary Degree 0.0978 0.0320 0.31%
Highest Grade Completed: Associate Degree -0.0773 0.0778 -0.60%
Highest Grade Completed: Bachelor Degree 0.1722 0.0732 1.26%
Highest Grade Completed: Graduate Degree -0.1430 0.0160 -0.23%
Employed at Program Entry 0.1964 0.2277 4.47%
In School at Program Entry 0.1265 0.0343 0.43%
Individual with a Disability -0.1813 0.3009 -5.46%
Veteran 0.2901 0.0572 1.66%
Limited English Proficiency -0.0306 0.0240 -0.07%
Single Parent -0.0942 0.1510 -1.42%
Low Income 0.0081 0.4508 0.37%
Homeless -0.0534 0.0595 -0.32%
Individual who was Incarcerated 0.1550 0.1979 3.07%
Displaced Homemaker -0.1842 0.0034 -0.06%
Received Wages 2 Quarters Prior to Participation 0.1889 0.6796 12.84%
Long-Term Unemployed at Program Entry 0.0157 0.1121 0.18%
UI Claimant -0.0148 0.1270 -0.19%
UI Exhaustee 0.1394 0.0011 0.02%
Supportive Services Recipient 0.0620 0.2323 1.44%
Received Needs-related Payments 0.4886 0.0000 0.00%
Received Other Public Assistance -0.0494 0.0000 0.00%
SSI or SSDI Recipient -0.0205 0.0332 -0.07%
TANF Recipient 0.0438 0.0332 0.15%
Received Wagner-Peyser Act Services 0.0220 0.9554 2.11%
Median Days in Program -0.0002 80.5000 -1.47%
Economic Condition Natural Resources Employment 2.1266 0.0161 3.42%
Construction Employment 0.8615 0.0543 4.68%
Manufacturing Employment 0.1897 0.1052 2.00%
Information Services Employment -5.3312 0.0133 -7.09%
Financial Services Employment -4.8664 0.0686 -33.39%
Professional and Business Services Employment 3.7575 0.0789 29.63%
Educational or Health Care Employment 0.8235 0.2516 20.72%
Leisure, Hospitality, or Entertainment Employment -0.8923 0.1160 -10.35%
Other Services Employment 4.5274 0.0263 11.90%
Public Administration 2.2149 0.0640 14.17%
Unemployment Rate Not Seasonally Adjusted 0.6822 0.0291 1.98%

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 $5,731 for South Dakota for this performance indicator is calculated by summing the Variable Estimate0 values (total of 37312) and the specific state fixed effect for this model (-31581).

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 0.5306 -$1,508
Age 25 to 44 -862.0930 0.4544 -$392
Age 45 to 54 -3144.2089 0.1659 -$522
Age 55 to 59 -5290.3216 0.0747 -$395
Age 60 or more -6059.0062 0.0523 -$317
Hispanic Ethnicity 232.4254 0.0433 $10
Race: Asian -4413.8578 0.0433 -$191
Race: Black -2324.8593 0.0867 -$202
Race: Hawaiian or Pacific Islander -6352.7320 0.0030 -$19
Race: American Indian -2692.4326 0.2003 -$539
Race: Multiple 6983.7945 0.0389 $271
Highest Grade Completed: High School Equivalency 362.0217 0.4723 $171
Highest Grade Completed: Some College 826.8902 0.1181 $98
Highest Grade Completed: Certificate or Other Post-Secondary Degree -1324.3050 0.0269 -$36
Highest Grade Completed: Associate Degree 5643.1853 0.0762 $430
Highest Grade Completed: Bachelor Degree 4052.0797 0.0762 $309
Highest Grade Completed: Graduate Degree 8539.9365 0.0164 $140
Employed at Program Entry 965.0801 0.2571 $248
In School at Program Entry 3623.2012 0.0374 $135
Individual with a Disability -989.2237 0.2586 -$256
Veteran -1349.3089 0.0643 -$87
Limited English Proficiency -4419.8922 0.0239 -$106
Single Parent 145.7630 0.1570 $23
Low Income -332.4067 0.4335 -$144
Homeless -446.4262 0.0478 -$21
Individual who was Incarcerated 2013.3031 0.2033 $409
Displaced Homemaker -1947.9185 0.0030 -$6
Received Wages 2 Quarters Prior to Participation 807.6246 0.7354 $594
Wages 2 Quarters Prior to Participation 0.3653 4929.6850 $1,801
Long-Term Unemployed at Program Entry 2011.8227 0.0912 $183
UI Claimant 685.8891 0.1405 $96
UI Exhaustee -2567.3504 0.0015 -$4
Supportive Services Recipient 912.9138 0.2197 $201
Received Needs-related Payments 15112.5289 0.0000 $0
Received Other Public Assistance 107.5299 0.0000 $0
SSI or SSDI Recipient -5911.8510 0.0254 -$150
TANF Recipient 840.8641 0.0299 $25
Received Wagner-Peyser Act Services -205.4928 0.9596 -$197
Median Days in Program 3.2489 78.0000 $253
Economic Condition Natural Resources Employment 24063.8444 0.0161 $387
Construction Employment 32326.4938 0.0543 $1,755
Manufacturing Employment 39237.2625 0.1052 $4,129
Information Services Employment -48189.2565 0.0133 -$640
Financial Services Employment 4074.2901 0.0686 $280
Professional and Business Services Employment 96754.4484 0.0789 $7,629
Educational or Health Care Employment 56163.1547 0.2516 $14,131
Leisure, Hospitality, or Entertainment Employment 57668.0011 0.1160 $6,691
Other Services Employment 10767.7935 0.0263 $283
Public Administration 39658.6388 0.0640 $2,537
Unemployment Rate Not Seasonally Adjusted -6106.3827 0.0291 -$177

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 26.6% for South Dakota for this performance indicator is calculated by summing the Variable Estimate0 values (total of 7.739) and the specific state fixed effect for this model (-7.473).

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 0.5570 -20.13%
Age 25 to 44 0.5218 0.3757 19.60%
Age 45 to 54 -0.0702 0.0916 -0.64%
Age 55 to 59 -0.9975 0.0374 -3.73%
Age 60 or more 2.9217 0.0206 6.01%
Hispanic Ethnicity -1.4456 0.0523 -7.57%
Race: Asian 2.1310 0.0280 5.97%
Race: Black -0.5671 0.0953 -5.41%
Race: American Indian 0.8520 0.2299 19.59%
Race: Multiple 1.9759 0.0505 9.97%
Highest Grade Completed: High School Equivalency -0.1218 0.3364 -4.10%
Highest Grade Completed: Some College -0.1842 0.1271 -2.34%
Highest Grade Completed: Certificate or Other Post-Secondary Degree 0.0731 0.0150 0.11%
Highest Grade Completed: Associate Degree -0.8544 0.0617 -5.27%
Highest Grade Completed: Bachelor Degree -0.2005 0.0523 -1.05%
Highest Grade Completed: Graduate Degree 1.8387 0.0112 2.06%
Employed at Program Entry 0.3647 0.3215 11.73%
In School at Program Entry -0.3045 0.2449 -7.46%
Individual with a Disability -0.2611 0.3234 -8.44%
Veteran 0.2508 0.0355 0.89%
Limited English Proficiency 0.8810 0.0393 3.46%
Single Parent 0.2135 0.1944 4.15%
Individual who was Incarcerated 0.7809 0.1720 13.43%
Received Wages 2 Quarters Prior to Participation -0.0013 0.6486 -0.08%
Long-Term Unemployed at Program Entry 0.0652 0.1346 0.88%
UI Exhaustee 0.0104 0.0000 0.00%
Supportive Services Recipient -0.1297 0.3159 -4.10%
SSI or SSDI Recipient 0.4929 0.0150 0.74%
TANF Recipient -0.2848 0.0542 -1.54%
Received Wagner-Peyser Act Services 0.0732 0.9720 7.11%
Median Days in Program 0.0004 144.0000 5.11%
Median Days Enrolled in Education or Training -0.0002 79.0000 -1.93%
Percent Enrolled in Education or Training Under 30 Days -0.0087 0.2879 -0.25%
Economic Condition Natural Resources Employment 10.0155 0.0161 16.12%
Construction Employment 8.9287 0.0543 48.48%
Manufacturing Employment 12.1240 0.1052 127.57%
Information Services Employment -43.8313 0.0133 -58.26%
Financial Services Employment 31.7234 0.0686 217.67%
Professional and Business Services Employment 7.5758 0.0789 59.74%
Educational or Health Care Employment 9.9286 0.2516 249.81%
Leisure, Hospitality, or Entertainment Employment 2.5813 0.1160 29.95%
Other Services Employment 32.8685 0.0263 86.39%
Public Administration -0.1431 0.0640 -0.92%
Unemployment Rate Not Seasonally Adjusted -13.5535 0.0291 -39.38%

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 76.5% for South Dakota for this performance indicator is calculated by summing the Variable Estimate0 values (total of -1.707) and the specific state fixed effect for this model (2.472).

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 0.5471 3.26%
Age 25 to 44 0.0189 0.3767 0.71%
Age 45 to 54 -0.0169 0.2960 -0.50%
Age 55 to 59 0.1060 0.1659 1.76%
Age 60 or more -0.1905 0.1256 -2.39%
Hispanic Ethnicity 0.1185 0.0224 0.27%
Race: Asian -0.2910 0.0045 -0.13%
Race: Black -0.0358 0.0359 -0.13%
Race: Hawaiian or Pacific Islander 0.8792 0.0000 0.00%
Race: American Indian -0.0983 0.0717 -0.71%
Race: Multiple -0.1947 0.0045 -0.09%
Highest Grade Completed: High School Equivalency -0.0259 0.4350 -1.13%
Highest Grade Completed: Some College -0.1942 0.1256 -2.44%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.1799 0.0404 -0.73%
Highest Grade Completed: Associate Degree -0.0907 0.1166 -1.06%
Highest Grade Completed: Bachelor Degree -0.1447 0.1570 -2.27%
Highest Grade Completed: Graduate Degree -0.1210 0.0493 -0.60%
Employed at Program Entry 0.1061 0.1704 1.81%
In School at Program Entry -0.0254 0.0269 -0.07%
Individual with a Disability -0.0527 0.1614 -0.85%
Veteran 0.0056 0.0942 0.05%
Limited English Proficiency -0.2521 0.0000 0.00%
Single Parent 0.0446 0.0493 0.22%
Low Income -0.0518 0.1300 -0.67%
Homeless 0.0306 0.0135 0.04%
Individual who was Incarcerated 0.3775 0.0448 1.69%
Displaced Homemaker -0.2274 0.0090 -0.20%
Received Wages 2 Quarters Prior to Participation 0.1131 0.9238 10.45%
Long-Term Unemployed at Program Entry 0.0574 0.0045 0.03%
UI Claimant 0.0208 0.5516 1.15%
UI Exhaustee 0.0737 0.0000 0.00%
Supportive Services Recipient 0.0496 0.2556 1.27%
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 0.0045 0.36%
TANF Recipient -0.5301 0.0045 -0.24%
Received Wagner-Peyser Act Services -0.0512 0.9910 -5.08%
Median Days in Program 0.0000 93.0000 0.07%
Economic Condition Natural Resources Employment -2.0224 0.0161 -3.26%
Construction Employment -0.4670 0.0543 -2.54%
Manufacturing Employment -1.7064 0.1052 -17.95%
Information Services Employment -9.8998 0.0133 -13.16%
Financial Services Employment -6.2744 0.0686 -43.05%
Professional and Business Services Employment -3.6027 0.0789 -28.41%
Educational or Health Care Employment -1.9946 0.2516 -50.19%
Leisure, Hospitality, or Entertainment Employment -2.8519 0.1160 -33.09%
Other Services Employment 3.0428 0.0263 8.00%
Public Administration 1.2295 0.0640 7.87%
Unemployment Rate Not Seasonally Adjusted 0.4118 0.0291 1.20%

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 $7,908 for South Dakota for this performance indicator is calculated by summing the Variable Estimate0 values (total of 35074) and the specific state fixed effect for this model (-27167).

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 0.5115 -$973
Age 25 to 44 1115.5154 0.3908 $436
Age 45 to 54 -125.9873 0.3046 -$38
Age 55 to 59 -2126.3785 0.1437 -$306
Age 60 or more -2492.9312 0.1149 -$287
Hispanic Ethnicity -857.7550 0.0115 -$10
Race: Asian -4684.9713 0.0057 -$27
Race: Black -1536.6027 0.0402 -$62
Race: Hawaiian or Pacific Islander -3269.1753 0.0000 $0
Race: American Indian -3522.2138 0.0575 -$202
Race: Multiple -3712.0594 0.0000 $0
Highest Grade Completed: High School Equivalency -1400.0970 0.4310 -$603
Highest Grade Completed: Some College -1902.9048 0.1379 -$262
Highest Grade Completed: Certificate or Other Post-Secondary Degree 83.4151 0.0402 $3
Highest Grade Completed: Associate Degree 1526.2402 0.1149 $175
Highest Grade Completed: Bachelor Degree 1169.4179 0.1494 $175
Highest Grade Completed: Graduate Degree 2155.0497 0.0517 $111
Employed at Program Entry 1700.7794 0.1839 $313
In School at Program Entry 3787.5103 0.0287 $109
Individual with a Disability 279.5931 0.1437 $40
Veteran 1445.8344 0.0977 $141
Limited English Proficiency -2976.1328 0.0000 $0
Single Parent -784.4348 0.0402 -$32
Low Income -538.7097 0.1034 -$56
Homeless 7893.8250 0.0172 $136
Individual who was Incarcerated 1805.9783 0.0402 $73
Displaced Homemaker 192.7564 0.0115 $2
Received Wages 2 Quarters Prior to Participation 21.0817 0.9368 $20
Wages 2 Quarters Prior to Participation 0.0917 8160.0000 $748
Long-Term Unemployed at Program Entry 1348.3682 0.0000 $0
UI Claimant 68.6962 0.5402 $37
UI Exhaustee -2493.0132 0.0000 $0
Supportive Services Recipient 176.1628 0.2701 $48
Received Needs-related Payments 6660.1906 0.0000 $0
Received Other Public Assistance 470.0451 0.0000 $0
SSI or SSDI Recipient -2105.8014 0.0000 $0
TANF Recipient -4222.3011 0.0000 $0
Received Wagner-Peyser Act Services -403.3425 0.9943 -$401
Median Days in Program 2.2222 93.0000 $207
Economic Condition Natural Resources Employment -27241.5941 0.0161 -$438
Construction Employment 36651.6742 0.0543 $1,990
Manufacturing Employment 47186.5858 0.1052 $4,965
Information Services Employment -260263.7041 0.0133 -$3,459
Financial Services Employment 85893.1957 0.0686 $5,894
Professional and Business Services Employment 95022.1320 0.0789 $7,493
Educational or Health Care Employment 51172.3083 0.2516 $12,875
Leisure, Hospitality, or Entertainment Employment 43978.6506 0.1160 $5,103
Other Services Employment -4546.6888 0.0263 -$120
Public Administration 22271.2780 0.0640 $1,425
Unemployment Rate Not Seasonally Adjusted -5795.6816 0.0291 -$168

Measurable Skill Gains

For this indicator, the tables below show the estimates for each of the variables in the statistical adjustment model and the related actual data. This data is used to determine the predicted level of performance for PY 2020 that is shown in the plot above. The PY 2020 prediction of 50.5% for South Dakota for this performance indicator is calculated by summing the Variable Estimate0 values (total of 5.295) and the specific state fixed effect for this model (-4.791).

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 0.6629 -10.00%
Age 25 to 44 -0.0655 0.5506 -3.61%
Age 45 to 54 0.2414 0.2809 6.78%
Age 55 to 59 0.4579 0.0674 3.09%
Age 60 or more 0.9139 0.0562 5.13%
Hispanic Ethnicity -0.6646 0.0449 -2.99%
Race: Asian -0.5340 0.0225 -1.20%
Race: Black -0.3293 0.0674 -2.22%
Race: American Indian 2.6465 0.0787 20.81%
Race: Multiple 0.0503 0.0225 0.11%
Highest Grade Completed: High School Equivalency -0.1922 0.4045 -7.77%
Highest Grade Completed: Some College -0.2384 0.2022 -4.82%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.2607 0.0449 -1.17%
Highest Grade Completed: Associate Degree 0.2625 0.1236 3.24%
Highest Grade Completed: Bachelor Degree -0.1123 0.1685 -1.89%
Highest Grade Completed: Graduate Degree -0.4275 0.0337 -1.44%
Employed at Program Entry -0.0215 0.1011 -0.22%
In School at Program Entry -0.2643 0.1461 -3.86%
Individual with a Disability -1.4481 0.1798 -26.03%
Veteran -0.9235 0.0449 -4.15%
Limited English Proficiency 0.4514 0.0000 0.00%
Single Parent 0.3691 0.1798 6.64%
Individual who was Incarcerated 0.4693 0.0787 3.69%
Received Wages 2 Quarters Prior to Participation 0.0287 0.9438 2.71%
Long-Term Unemployed at Program Entry 0.3881 0.0225 0.87%
UI Exhaustee 0.3561 0.0000 0.00%
Supportive Services Recipient -0.0615 0.4494 -2.76%
SSI or SSDI Recipient -0.4356 0.0000 0.00%
TANF Recipient -3.8716 0.0112 -4.35%
Received Wagner-Peyser Act Services -0.0963 1.0000 -9.63%
Median Days in Program -0.0003 125.0000 -4.02%
Median Days Enrolled in Education or Training -0.0003 71.0000 -1.94%
Percent Enrolled in Education or Training Under 30 Days 0.1620 0.2247 3.64%
Economic Condition Natural Resources Employment -8.0806 0.0161 -13.01%
Construction Employment 4.4493 0.0543 24.16%
Manufacturing Employment 9.8551 0.1052 103.70%
Information Services Employment -58.7056 0.0133 -78.03%
Financial Services Employment 12.1977 0.0686 83.70%
Professional and Business Services Employment 16.0554 0.0789 126.60%
Educational or Health Care Employment 7.1634 0.2516 180.24%
Leisure, Hospitality, or Entertainment Employment 1.5122 0.1160 17.55%
Other Services Employment 65.3154 0.0263 171.67%
Public Administration -2.8478 0.0640 -18.22%
Unemployment Rate Not Seasonally Adjusted -10.8237 0.0291 -31.45%

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 79.1% for South Dakota for this performance indicator is calculated by summing the Variable Estimate0 values (total of -0.965) and the specific state fixed effect for this model (1.756).

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 0.0595 0.5000 2.97%
Age 14 to 15 0.1226 0.0000 0.00%
Age 16 to 17 -0.1436 0.0952 -1.37%
Age 18 to 19 -0.2054 0.3714 -7.63%
Age 20 to 21 0.0105 0.2524 0.27%
Hispanic Ethnicity -0.0628 0.0381 -0.24%
Race: Asian 0.1989 0.0476 0.95%
Race: Black -0.0414 0.1000 -0.41%
Race: Hawaiian or Pacific Islander -0.5342 0.0095 -0.51%
Race: American Indian -0.3341 0.2238 -7.48%
Race: Multiple 0.1508 0.0810 1.22%
Highest Grade Completed: High School Equivalency 0.0691 0.4762 3.29%
Highest Grade Completed: Some College -0.3127 0.0143 -0.45%
Highest Grade Completed: Certificate or Other Post-Secondary Degree 1.1469 0.0000 0.00%
Highest Grade Completed: Associate or Bachelor Degree 0.4935 0.0095 0.47%
Employed at Program Entry 0.2748 0.2476 6.80%
In School at Program Entry 0.0356 0.0381 0.14%
Individual with a Disability -0.0469 0.3000 -1.41%
Limited English Proficiency -0.1392 0.0286 -0.40%
Low Income 0.0375 0.5619 2.11%
Homeless -0.2008 0.0619 -1.24%
Individual who was Incarcerated 0.0635 0.1762 1.12%
Foster Care Youth -0.0100 0.0000 0.00%
Youth Parent or Pregnant Youth -0.0716 0.1905 -1.36%
Skills/Literacy Deficient at Program Entry 0.0349 0.1667 0.58%
Long-Term Unemployed at Program Entry -0.0867 0.1286 -1.11%
UI Claimant -0.0433 0.0095 -0.04%
Supportive Services Recipient 0.0442 0.3762 1.66%
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 0.0095 0.07%
TANF Recipient -0.0341 0.0190 -0.07%
Pell Grant Recipient 0.0368 0.0190 0.07%
Youth Needing Additional Assistance 0.0005 0.3524 0.02%
Received Wagner-Peyser Act Services 0.0148 0.9619 1.43%
Median Days in Program 0.0000 108.0000 -0.43%
Economic Condition Natural Resources Employment -6.7872 0.0161 -10.92%
Construction Employment -1.8800 0.0543 -10.21%
Manufacturing Employment -1.3602 0.1052 -14.31%
Information Services Employment -7.2974 0.0133 -9.70%
Financial Services Employment -2.1367 0.0686 -14.66%
Professional and Business Services Employment -2.5564 0.0789 -20.16%
Educational or Health Care Employment 0.0247 0.2516 0.62%
Leisure, Hospitality, or Entertainment Employment -0.3944 0.1160 -4.58%
Other Services Employment -10.7940 0.0263 -28.37%
Public Administration 3.2993 0.0640 21.11%
Unemployment Rate Not Seasonally Adjusted -1.4872 0.0291 -4.32%

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 $3,855 for South Dakota for this performance indicator is calculated by summing the Variable Estimate0 values (total of 15578) and the specific state fixed effect for this model (-11723).

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 0.4969 -$932.99
Age 14 to 15 -92.3013 0.0000 $0.00
Age 16 to 17 -1309.0587 0.0736 -$96.37
Age 18 to 19 -1066.4762 0.3804 -$405.65
Age 20 to 21 649.4931 0.2515 $163.37
Hispanic Ethnicity 1913.4585 0.0429 $82.17
Race: Asian 649.7122 0.0552 $35.87
Race: Black -886.3703 0.1104 -$97.88
Race: Hawaiian or Pacific Islander -3388.4232 0.0061 -$20.79
Race: American Indian -184.4720 0.1963 -$36.22
Race: Multiple 933.1134 0.0675 $62.97
Highest Grade Completed: High School Equivalency 1383.9408 0.4724 $653.76
Highest Grade Completed: Some College -828.1913 0.0184 -$15.24
Highest Grade Completed: Certificate or Other Post-Secondary Degree 173.0955 0.0000 $0.00
Highest Grade Completed: Associate or Bachelor Degree 6672.3330 0.0123 $81.87
Employed at Program Entry 613.7857 0.2699 $165.68
In School at Program Entry 546.1994 0.0245 $13.40
Individual with a Disability -495.1811 0.2699 -$133.67
Limited English Proficiency 2456.3023 0.0245 $60.28
Low Income -305.7985 0.5337 -$163.22
Homeless 983.9044 0.0552 $54.33
Individual who was Incarcerated -1284.6596 0.1902 -$244.32
Foster Care Youth 1009.8293 0.0000 $0.00
Youth Parent or Pregnant Youth 854.5128 0.1840 $157.27
Skills/Literacy Deficient at Program Entry -283.4775 0.1656 -$46.96
Long-Term Unemployed at Program Entry -630.2664 0.0920 -$58.00
UI Claimant -462.5838 0.0123 -$5.68
Supportive Services Recipient 161.1750 0.3865 $62.29
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 0.0000 $0.00
TANF Recipient -539.6509 0.0245 -$13.24
Pell Grant Recipient 104.1843 0.0245 $2.56
Youth Needing Additional Assistance -4.3341 0.3436 -$1.49
Received Wagner-Peyser Act Services -27.8731 0.9509 -$26.51
Median Days in Program 0.5942 111.5000 $66.25
Economic Condition Natural Resources Employment -3172.1958 0.0161 -$51.06
Construction Employment 10994.4772 0.0543 $596.95
Manufacturing Employment 21559.9593 0.1052 $2,268.54
Information Services Employment -55465.6493 0.0133 -$737.20
Financial Services Employment 44805.1055 0.0686 $3,074.34
Professional and Business Services Employment 14219.0161 0.0789 $1,121.20
Educational or Health Care Employment 20372.0444 0.2516 $5,125.78
Leisure, Hospitality, or Entertainment Employment 7088.2477 0.1160 $822.40
Other Services Employment 57026.8505 0.0263 $1,498.87
Public Administration 43573.5139 0.0640 $2,787.62
Unemployment Rate Not Seasonally Adjusted -10090.2192 0.0291 -$293.18

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 33.2% for South Dakota for this performance indicator is calculated by summing the Variable Estimate0 values (total of 3.166) and the specific state fixed effect for this model (-2.834).

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 0.4744 -13.09%
Age 14 to 15 -0.8106 0.0205 -1.66%
Age 16 to 17 -0.9025 0.2082 -18.79%
Age 18 to 19 -0.6998 0.4027 -28.18%
Age 20 to 21 -1.6404 0.2253 -36.95%
Hispanic Ethnicity -0.0170 0.0751 -0.13%
Race: Asian -0.0162 0.0375 -0.06%
Race: Black 0.0042 0.1024 0.04%
Race: American Indian -0.1578 0.2765 -4.36%
Race: Multiple 1.9727 0.0751 14.81%
Highest Grade Completed: High School Equivalency -0.2692 0.2321 -6.25%
Highest Grade Completed: Some College 1.0513 0.0273 2.87%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.6449 0.0000 0.00%
Highest Grade Completed: Associate or Bachelor Degree 1.9000 0.0000 0.00%
In School at Program Entry 0.0220 0.3515 0.77%
Skills/Literacy Deficient at Program Entry 0.1976 0.3584 7.08%
UI Claimant 0.0198 0.0034 0.01%
Supportive Services Recipient -0.0712 0.3140 -2.24%
Received Other Public Assistance 0.2742 0.0000 0.00%
SSI or SSDI Recipient 0.5536 0.0273 1.51%
Pell Grant Recipient -0.8864 0.0375 -3.33%
Received Wagner-Peyser Act Services -0.0503 0.9625 -4.84%
Median Days Enrolled in Education or Training -0.0003 111.0000 -3.62%
Percent Enrolled in Education or Training Under 30 Days -0.3441 0.1809 -6.22%
Economic Condition Natural Resources Employment 7.6282 0.0161 12.28%
Construction Employment 9.5740 0.0543 51.98%
Manufacturing Employment 5.8313 0.1052 61.36%
Information Services Employment -42.8136 0.0133 -56.90%
Financial Services Employment -14.2433 0.0686 -97.73%
Professional and Business Services Employment 14.4769 0.0789 114.15%
Educational or Health Care Employment 7.0634 0.2516 177.72%
Leisure, Hospitality, or Entertainment Employment 6.2993 0.1160 73.09%
Other Services Employment 50.8391 0.0263 133.62%
Public Administration -7.3408 0.0640 -46.96%
Unemployment Rate Not Seasonally Adjusted -1.1663 0.0291 -3.39%

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 70.4% for South Dakota for this performance indicator is calculated by summing the Variable Estimate0 values (total of 1.289) and the specific state fixed effect for this model (-0.585).

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 0.4401 3.52%
Age 25 to 44 0.1086 0.4658 5.06%
Age 45 to 54 -0.0860 0.1836 -1.58%
Age 55 to 59 -0.0070 0.0898 -0.06%
Age 60 or more -0.0629 0.0984 -0.62%
Hispanic Ethnicity 0.2326 0.0673 1.57%
Race: Asian -0.2354 0.0222 -0.52%
Race: Black -0.1609 0.0830 -1.34%
Race: Hawaiian or Pacific Islander 0.9703 0.0041 0.40%
Race: American Indian -0.3062 0.2383 -7.30%
Race: Multiple 0.2471 0.0248 0.61%
Highest Grade Completed: High School Equivalency -0.0172 0.4783 -0.82%
Highest Grade Completed: Some College 0.0386 0.1364 0.53%
Highest Grade Completed: Certificate or Other Post-Secondary Degree -0.0422 0.0197 -0.08%
Highest Grade Completed: Associate Degree 0.3496 0.0731 2.56%
Highest Grade Completed: Bachelor Degree -0.6768 0.0857 -5.80%
Highest Grade Completed: Graduate Degree -0.5246 0.0243 -1.27%
Employed at Program Entry 0.0865 0.2509 2.17%
In School at Program Entry -0.0903 0.0382 -0.34%
Individual with a Disability -0.3557 0.1053 -3.74%
Veteran 0.2170 0.0923 2.00%
Limited English Proficiency -0.0185 0.0018 0.00%
Single Parent 0.2027 0.0700 1.42%
Low Income 0.0926 0.2284 2.11%
Homeless -0.0667 0.0434 -0.29%
Individual who was Incarcerated 0.1850 0.0894 1.65%
Displaced Homemaker -0.2304 0.0037 -0.09%
Received Wages 2 Quarters Prior to Participation 0.3174 0.6916 21.95%
Long-Term Unemployed at Program Entry -0.1541 0.0335 -0.52%
UI Claimant -0.0385 0.1795 -0.69%
UI Exhaustee -0.0897 0.0036 -0.03%
Supportive Services Recipient -0.1026 0.0247 -0.25%
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 0.0109 1.18%
TANF Recipient -0.5680 0.0239 -1.36%
Median Days in Program -0.0003 47.0000 -1.30%
Economic Condition Natural Resources Employment 1.6856 0.0161 2.71%
Construction Employment 1.5411 0.0543 8.37%
Manufacturing Employment 1.0127 0.1052 10.66%
Information Services Employment -0.4595 0.0133 -0.61%
Financial Services Employment 2.9649 0.0686 20.34%
Professional and Business Services Employment 0.9431 0.0789 7.44%
Educational or Health Care Employment 1.2831 0.2516 32.28%
Leisure, Hospitality, or Entertainment Employment 0.5919 0.1160 6.87%
Other Services Employment 3.9021 0.0263 10.26%
Public Administration 1.7006 0.0640 10.88%
Unemployment Rate Not Seasonally Adjusted 0.3440 0.0291 1.00%

Median Earnings 2nd Quarter after Exit

For this indicator, the tables below show the estimates for each of the variables in the statistical adjustment model and the related actual data. This data is used to determine the predicted level of performance for PY 2020 that is shown in the plot above. The PY 2020 prediction of $5,339 for South Dakota for this performance indicator is calculated by summing the Variable Estimate0 values (total of 39091) and the specific state fixed effect for this model (-33752).

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 0.4435 -$1,231
Age 25 to 44 1526.7709 0.4790 $731
Age 45 to 54 223.6212 0.1930 $43
Age 55 to 59 1725.9534 0.0852 $147
Age 60 or more 3989.3863 0.0806 $322
Hispanic Ethnicity 1506.2736 0.0745 $112
Race: Asian -1285.7589 0.0236 -$30
Race: Black -2926.8319 0.0866 -$253
Race: Hawaiian or Pacific Islander -2473.0352 0.0042 -$10
Race: American Indian -5567.8497 0.1942 -$1,081
Race: Multiple 10678.0968 0.0220 $235
Highest Grade Completed: High School Equivalency -1763.8797 0.4761 -$840
Highest Grade Completed: Some College -2177.4526 0.1412 -$307
Highest Grade Completed: Certificate or Other Post-Secondary Degree -2180.3190 0.0198 -$43
Highest Grade Completed: Associate Degree 2095.5471 0.0802 $168
Highest Grade Completed: Bachelor Degree 72.8128 0.0926 $7
Highest Grade Completed: Graduate Degree -5012.8376 0.0249 -$125
Employed at Program Entry 456.1906 0.2943 $134
In School at Program Entry -1155.2072 0.0362 -$42
Individual with a Disability -5107.0692 0.0870 -$444
Veteran -913.8967 0.0876 -$80
Limited English Proficiency 1563.7512 0.0020 $3
Single Parent 660.1018 0.0620 $41
Low Income 634.4633 0.1981 $126
Homeless -3513.0948 0.0329 -$116
Individual who was Incarcerated 1920.7679 0.0849 $163
Displaced Homemaker -10834.3804 0.0029 -$31
Received Wages 2 Quarters Prior to Participation -219.4792 0.7811 -$171
Wages 2 Quarters Prior to Participation 0.2612 5764.5500 $1,505
Long-Term Unemployed at Program Entry 771.2849 0.0233 $18
UI Claimant 454.7967 0.1887 $86
UI Exhaustee 247.9889 0.0030 $1
Supportive Services Recipient -636.3855 0.0263 -$17
Received Needs-related Payments -21804.7067 0.0000 $0
Received Other Public Assistance -1174.5793 0.0000 $0
SSI or SSDI Recipient 10874.7587 0.0078 $85
TANF Recipient 1657.8393 0.0182 $30
Median Days in Program 0.8717 46.0000 $40
Economic Condition Natural Resources Employment 37057.6079 0.0161 $596
Construction Employment 42760.7710 0.0543 $2,322
Manufacturing Employment 47700.8708 0.1052 $5,019
Information Services Employment 11314.8086 0.0133 $150
Financial Services Employment 62614.6797 0.0686 $4,296
Professional and Business Services Employment 67885.3402 0.0789 $5,353
Educational or Health Care Employment 51491.7764 0.2516 $12,956
Leisure, Hospitality, or Entertainment Employment 43018.4305 0.1160 $4,991
Other Services Employment 41629.7443 0.0263 $1,094
Public Administration 51356.2602 0.0640 $3,286
Unemployment Rate Not Seasonally Adjusted -5089.3910 0.0291 -$148

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