Emsi has been making quarterly data releases for many years now in order to keep our data up-to-date. Here’s what we just released for the final quarter of 2017. First is a list of the updated data sources we use in our Q4 2017 dataset, followed by a short discussion about methodology changes.
1. Updated Data Sources
• Quarterly Census of Employment & Wages, Q1 2017 (BLS). This is the most complete source for wage and salary industry employment data.
• Local Area Unemployment Statistics, September 2017 (BLS). This is the gold standard for total unemployment by geography.
• American Community Survey, Public Use Microdata, 2016 (Census). This dataset informs Self-Employment and Extended Proprietors data, and certain staffing patterns for QCEW and Non-QCEW classes of worker.
• Employment Projections Tables, 2016-2026 (BLS). This is the primary source for Emsi’s occupational replacement data as well as some occupational training and educational attainment data.
• Social Accounting Matrix (SAM) / Input-Output Modeling Data:
- Gross State Product 2017 Q1 (BEA)
- National Income and Product Accounts 2017 Q3 (BEA)
- Consumer Expenditure Survey 2016 (BLS)
- Current Population Survey, Demographic Income 2016 (Census)
- State and Local Finances 2015 (Census)
Primary Data Source Information
2. Classification and Methodology Changes
This section talks about changes to the underlying datasets. Keep in mind: Emsi never recommends comparing data releases due to the large amount of noise introduced by the continuous improvement of our processes and the number of updated data sources in each release. Each data release is a self-contained time series.
North American Industry Classification System (NAICS) 2017. Emsi switched from using NAICS 2012 to NAICS 2017. Summary of the changes:
- 4-digit: 3 removed, 3 new, 0 combined, 2 recoded, 1 split
- 5-digit: 10 removed, 7 new, 7 combined, 1 recoded, 2 split
- 6-digit: 28 removed, 20 new, 13 combined, 11 renamed, 4 split
Here’s an infographic for how the changes shake out.
Occupational Information Network (O*NET) Version 22.0. We updated from O*NET version 21.3 to version 22.0, in order to include updated knowledge, skill, and abilities (KSAs) for 100 occupations. This will slightly impact the compatibility indices of occupation pairs.
Non-QCEW (Class of Worker 2) Earnings. We fixed a bug in the code that was causing earnings to skew low. In addition to normal data changes, earnings in this class of worker are approximately 1.5% higher than previous releases.
ZIP Code Population Demographics. We improved the usage of the probability matrices used to disaggregate county-level population demographics to ZIP codes. The result is more accurate estimates for approximately 25% of the nation. Rural areas are the most improved.
ZIP Code Industry Employment Estimates. We improved our estimation of ZIP code industry employment with a more nuanced use of ZBP (ZIP Code Business Patterns, Census). Previously, if a county’s industry was not found in ZBP, we would default to using an USPS business delivery statistics to distribute that industry’s employment to all ZIP codes in the county. With the new methodology, if a county’s industry isn’t found in ZBP, we search for similar industries in ZBP before defaulting to USPS data. The use of USPS dropped from 20% to 0.5%, significantly increasing the accuracy of ZIP code employment estimates. This change affects all ZIP code employment data (industry and occupation) and does not target any specific counties or industries. However, the most significant changes will be in rural areas and in regions where an industry’s employment is small. Changes will appear as a more focused distribution of data within the ZIP codes in each county.
Local Absorption in Emsi’s Social Accounting Matrix (I-O). We slightly changed the constraints on the SAM’s bi-proportional algorithm to further maximize local absorption. This fixes some anomalies uncovered in the 2017.3 release where local absorption was too low.
Unemployment Data. Unemployment data has been brought up to date and the methodology adjusted to reflect current conditions more closely. The new methodology averages the past 12 months of unemployment to form a figure free from seasonal volatility. This change has been introduced with the 2017.4 data release, so you can expect to see differences in unemployment between the 2017.4 data release and prior releases.