This report assesses state performance based on state reported performance indicator results for PY 2021 compared to the adjusted negotiated levels of performance. The negotiated levels are adjusted based on the estimates from the statistical adjustment models and the actual characteristics of the participants served and economic conditions within the state in PY 2021. This assessment focuses specifically on those indicators and scores that are being formally assessed in 2021.
For PY 2021, there is one way a state can have a performance failure:
The figures below provide an overview of the performance results for states in PY 2021. Any state with at least one individual indicator score failure is shown in purple. States that have a failure on any individual indicator will receive technical assistance from the Department of Labor.
The figures below have the individual indicator scores. Each tab has all the individual indicators within that program. States have a performance failure if an individual indicator score is below 50%.
These data tables list the values for each of the following data points, which are used to derive the performance scores. For PY 2020 and PY 2021 only individual indicator scores are assessed. The definitions are as follows:
Click the button to download the full target level data shown in the tables below for all states, programs, and indicators.
This table shows the individual indicator performance data for the Adult program indicators.
This table shows the individual indicator performance data for the Dislocated Worker program indicators.
This table shows the individual indicator performance data for the Youth program indicators.
This table shows the individual indicator performance data for the Wagner-Peyser program indicators.
The analysis below gives an overview of how well the models performed in adjusting and assessing performance in PY 2021. This section includes some aspects of the overall performance of the models and highlights the model variables which had a significant impact.
The figures below provide some information on the how well the models performed using PY 2021 data. Overall, there is some variance in the performance of the different models which was primarily driven by issues discussed in the About section of this report. Click on the tabs below to see the figures for each of the program indicator models.
The distribution plots show how the adjustment process (using the statistical adjustment model) affected the performance scores for states. The blue shows the distribution of the performance scores for states in the hypothetical scenario of not using the statistical adjustment model to adjust negotiated levels. In this scenario, actual performance is compared to the original negotiated level. The green shows the distribution of performance scores for states when comparing a state’s actual performance to the adjusted level of performance. Overall, the scores using the model adjustments are more in line with performance expectations. In most cases, there are less high and low outlier scores. In addition, the higher peak for the performance scores (i.e., the green) also indicates less variance with a larger concentration of scores around 100%.
Below the distribution plots are scatter plots that show how the model predictions using the actual PY 2021 data (i.e., Estimate1) compare to the actual performance results reported for each program indicator. These plots highlight that there is some variance in the performance of different program indicator models. Overall, the better performing models have smaller residuals (i.e., points that are closer to the line which would indicate that the prediction matches the actual performance) and those residuals are evenly distributed (i.e., the points are evenly spread around the line).
Plots of the Employment Rate 2nd Quarter after Exit indicator models for each program.
Plots of the Median Earnings 2nd Quarter after Exit indicator models for each program.
There were some model variables that had a larger impact in determining the adjustment factor and resulting performance score for each program indicator model. The reason that a variable has a large impact can vary, but includes factors such as: the relative importance that element has on a particular performance outcome and the variance in state reporting the data on particular variables. The bar plots below show the variables with the largest average adjustment for each model.
Plots of the variables in the Employment Rate 2nd Quarter after Exit indicator models for each program.
Plots of the variables in the Median Earnings 2nd Quarter after Exit indicator models for each program.