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Employment Projections
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Methods of Projections Evaluation
Starting with the 2002–2012 projections evaluation, BLS standardized a set of methods for evaluating future projections sets. Those methods are described here.
Due to the impact of the COVID-19 pandemic on data for 2020, BLS did not evaluate the 2010–20 projections.
Standard for comparison
Comparable projections are not available for most publication series, including the detailed sectors of both employment and the labor force. As an alternative evaluation measure, BLS uses a series of naïve models for comparison purposes.
A naïve model is any model that is simple to estimate and does not require sophisticated systems or processes. The more elaborate BLS model should outperform a naïve model for a majority of the variables presented.
Macro naïve model
For the macro naïve model, the average growth rate for CBO's potential GDP (as calculated in the base year) is calculated for the previous 10 years, and projected forward 10 years.
Labor force naïve model
BLS projects the labor force by analyzing trends in the labor force participation rates (LFPR) of granular demographic groups, which are then applied to population projections from the U.S. Census Bureau. Our naïve model is a least squares linear regression based on the participation rates observed in the ten years preceding the base year.
Industry projections naïve model
The naïve model used for evaluating industry projections is a least squares linear regression based on the industry employment levels observed in the ten years preceding the base year.
Occupational–share naïve model
BLS develops occupational projections by applying a projected staffing pattern to industry employment projections. The occupational–share naïve model shows how the projections would have looked if the overall proportion of each occupation in the economy were projected not to change.
Measures used
Dissimilarity indexes
A dissimilarity index is a way of measuring the amount of difference between two distributions. In our application, the value of the dissimilarity index is the amount that one distribution would have to change in order to match the other. Calculation details are available in Evaluating the 1996–2006 employment projections.
Mean absolute percent error
The mean absolute percent error (MAPE) provides a measure for comparing the accuracy of projections for the components of the labor force. The weighted MAPE weights each component in accordance with its share of the total, placing less emphasis on smaller components. Calculation details are available in Evaluating the 1996–2006 employment projections.
Potential
For macro variables—GDP and the Unemployment Rate—comparisons are made to potential values. Potential is the estimate of a value that would have occurred had the economy's resources been fully utilized in a sustainable manner. It is roughly the peak of a business cycle. Potential values are estimated by CBO.
Data comparison issues
The economy changes over time and with it the data collected to describe it.
Demographic categories
Changes in the race categories collected by the Current Population Survey (CPS) can limit the extent to which we can evaluate our labor force projections by race.
Occupation classifications
The Standard Occupational Classification (SOC) system used by Employment Projections is routinely re–evaluated so that it can capture new and emerging occupations. When these changes occur it can result in some occupations not being comparable between when the projection was made and when the projection can be evaluated.
Industry classifications
The North American Industry Classification System (NAICS) used by Employment Projections is reviewed and revised every five years so that it can capture changes in existing industries and introduce new and emerging industries in the system. When these changes occur it can result in some industries not being comparable between when the projection was made and when the projection can be evaluated. Greater variability exists among individual industries compared with sectors and major sectors. Therefore, we analyze only the major sectors of detail, rather than the roughly 200 industries published within the projections publications.
Data sources
Internal, unrounded and unsuppressed data were used for some calculations. Use of publicly available data will result in figures with compounded rounding issues and provide answers which may be different in significant ways.
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Last Modified Date: August 29, 2024