This page contains release notes for each of Emsi’s quarterly US dataruns from the 2017.1 datarun forward. The release notes contain information on major methodology changes included with each datarun.
To read more on Emsi data updates, see this article. To read more about each source and what Emsi uses it for, click the link in the dataset chart.
Correction: Emsi Population Projections Adjustments
Emsi has communicated in the past that we adjust our population demographics projections to the published national projections from the Census Bureau. While reviewing and improving the code, we realized that we have been inadvertently publishing the pre-adjustment data. This release fixes that bug.
Changes to the “Non-QCEW Employees” Class of Worker
In an effort to continuously improve our core LMI industry data, this quarter we revisited and improved the processes that create Emsi industry data for employees not included in the Quarterly Census of Employment and Wages (QCEW). The Bureau of Economic Analysis (BEA) releases employment estimates as part of the State and Local Area Personal Income (SPI/LPI) programs that include these “non-covered” employees. The majority of Emsi’s non-QCEW employment estimates are calculated by subtracting QCEW employment from total SPI employment. We reviewed the SPI methodology documentation and identified ways to improve our methodology to more accurately take into account the differences in coverage between SPI/LPI and QCEW. In summary, Emsi’s methodology changes result in:
Changes to QCEW source data
QCEW recently announced a change to the methodology they use to estimate employment and earnings for non-responding establishments. Under the current methodology, QCEW takes the missing establishment’s growth rate from this same time last year and applies that to the previous month. They’ve begun to rethink this, especially in light of COVID, and have decided to begin calculating missing establishments based on the growth rates of similar establishments within the same time frame.
Beyond this, they’ve also mentioned two other improvements they’d like to make: (1) implementing a methodology change that will immediately identify employers who have ceased operations and (2) use benefit claim counts as a supplement to existing manual data review.
Population Educational Attainment
Emsi improved the model that creates educational attainment data for the population aged 25 and above. This is done by breaking out final Emsi population demographics data by seven educational attainment categories using breakouts from 2009-2019 5yr ACS and 2000 Census data.
Emsi publishes data from the BLS Employment Projections (EP) program for certain national occupation characteristics. EP is now using the same occupation definition as OES, which transitioned to 2018-based occupation codes earlier this year. This update makes a few national occupation datapoints more accurate/relevant to Emsi SOC:
We stopped using national tabulations from the Current Population Survey (CPS) for unemployment breakouts in favor of searching for the nearest good breakout from the DOL’s Characteristics of the Insured Unemployed (CIU) monthly state unemployment data.
Occupation by Residence Employment
Emsi uses a ZIP Code to Census Tract mapping from Housing and Urban Development to create ZIP Code level occupation by place of residence employment. We improved our usage of the mapping which improved the accuracy of occupation by place of residence data by more closely mapping published data from LODES.
Staffing and Occupation Data Tuning
We tuned our expansion and unsuppression algorithms for OES staffing and occupation data to produce fewer unreasonable data points, and cluster employment and earnings data around more likely places.
New Datasets in Core LMI API (API Only)
We’ve added a few new datasets to the Core LMI API. See the changelog for more information.
Bolded items indicate an update.
|Name||Source||2021.1 Datarun||2020.4 Datarun||2020.3 Datarun||2020.2 Datarun|
|Released 1/22/21||Released 10/7/20||Released 7/27/20||Released 4/28/20|
|Quarterly Census of Employment and Wages (QCEW)||BLS||2020Q2||2020Q1||2019Q4||2019Q3|
|Occupational Employment Statistics (OES)||BLS||2019||2019||2019||2018|
|National Ind/Occ Employment Matrix (NIOEM)||BLS||2019-2029||2018-2028||2018-2028||2018-2028|
|Employment Projections Tables (EP)||BLS||2019-2029||2018-2028||2018-2028||2018-2028|
|Consumer Expenditure Survey (CEX)||BLS||2019||2018||2018||2018|
|State Personal Income / Local Area Personal Income (SPI/LPI)||BEA||2019||2018||2017 Revised||2017 Revised|
|Make & Use Tables (MUTs)||BEA||2018*||2018||2018||2018|
|National Income and Product Accounts (NIPA)||BEA||2020Q3||2020Q2||2020Q1||2019Q4|
|Gross Domestic Product by State (GSP)||BEA||2019||2017 Revised||2017 Revised||2017 Revised|
|American Community Survey (ACS)||Census||2019||2018||2018||2018|
|County Business Patterns (CBP)||Census||2018||2018||2016||2016|
|ZIP Code Business Patterns (ZBP)||Census||2016**||2016**||2016**||2016**|
|Nonemployer Statistics (NES)||Census||2018||2018||2018||2016|
|Current Population Survey (CPS)||Census||2019||2019||2018||2018|
|Sate and Local Finances (Census of Government, CoG)||Census||2018||2017||2017||2017|
|Population Estimates (PopEst)||Census||2019||2019||2018||2018|
|Origin-Destination Employment Statistics (LODES)||Census||2017||2017||2017||2017|
|Quarterly Workforce Indicators (QWI)||Census||2020Q3***||2020Q2||2020Q1||2019Q4|
|Railroad Retirement Board (RRB)||Railroad Retirement Board||2019/2018||2019/2018||2018/2017||2018/2017|
|Occupational Information Network (O*NET)||US Dept. of Labor, Education & Training Administration||25.0****||25.0||24.3||24.2|
|Crime By County||Federal Bureau of Investigation (FBI)||2019||2017||2017||2017|
|Birth/Death Rates||Center for Disease Control (CDC)||2018 (Birth), 2017 (Death)||2018 (Birth), 2017 (Death)||2018 (Birth), 2017 (Death)||2015|
|Migration||Internal Revenue Service (IRS)||2018||2018||2018||2018|
* 2019 Make & Use Tables (BEA) have been released, but appear to be inconsistent with the rest of Emsi data. We will be working to incorporate them into the 2021.2 datarun.
** 2018 ZBP has been released but makes use of a new Census suppression methodology which suppresses data far more heavily than in the past. Emsi is currently working on new methodology that will allow us to calculate ZIP-level employment differently.
*** 2020Q3 QWI data for Illinois was internally inconsistent, so we are still using the 2020Q2 vintage for that state.
**** O*NET 25.1 has been released. This is the first release to use O*NET codes tied to the new 2018 SOC codes. Emsi is currently working to update O*NET classification taggers to be compatible with the 25.1 release. When this is finished, all Emsi data (postings, profiles, core LMI) will be updated to the 25.1 classification.