Glossary

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Advertised Salary (Job Posting Analytics)

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Advertised Salary is found within the Job Posting Analytics and Job Posting Competition reports and is the salary information provided by the company or entity advertising the position. Job postings reports can be sliced by job title, company, region, and skills, meaning users can see advertised salary information for these specific slices of data.

If present, we extract the salary information from the job posting as advertised. Only 15-20% of all postings have salary information available. The percentage of postings containing salary information varies depending on the occupation, industry, and job title.

We display the count of postings that include salary data (as shown below). This number will likely be much smaller than the number of postings returned in the report. The count of postings displaying salary information is included to help the user understand how well the postings displaying salaries represent all postings in the user’s report.

Bureau of Labor Statistics (BLS)

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The Bureau of Labor Statistics is the principal federal agency responsible for measuring labor market activity, working conditions, and price changes in the economy. Its mission is to collect, analyze, and disseminate essential economic information to support public and private decision making.

The BLS is the major source of employment and earnings data in the United States. Major BLS datasets used by Lightcast include

– Quarterly Census of Employment and Wages (QCEW)
– Occupational Employment Statistics (OES)
– National Industry-Occupation Employment Matrix (NIOEM)

Source: BLS

Current Population Survey (CPS)

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The BLS’s Current Population Survey (CPS) is a monthly survey of households, and collects data on a number of topics including employment, labor force participation, and earnings. CPS data is the basis for the demographic breakout of data in the Input-Output model.

Educational Attainment (SOC)

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SOC Educational Attainment is a breakdown of the education levels attained by the occupation’s workforce. The Educational Attainment breakout is only provided for the nation as a whole.

Source: The Bureau of Labor Statistics’ (BLS) Educational Attainment for workers 25 years and older by detailed occupation

Employed

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In our data, employed refers to any person who is currently paid as an employee or is self-employed. It is important to note that Lightcast employment counts count jobs, not people.

Filters

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In Lightcast products, tables have “filter” capabilities. A filter is a set of one or more criteria, used to display only specific rows of data in a table. For example, a criterion might be “Total 2007 Jobs greater than or equal to 350”, where the column is “Total 2007 Jobs”, the comparison method is “greater than or equal to”, and the value is “350”. When applied as a filter, this criterion will show a table with only those rows whose “Total 2007 Jobs” field is greater than or equal to 350. Various criteria in a filter can be combined with AND and OR operators.

Job Counts

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Job counts (e.g. 2018 Jobs) are based on the most recent four quarters of data available from QCEW. For example, in May 2019, 2018Q3 was the most current QCEW data available from the BLS. Our 2019.2 datarun was based on this data in combination with the prior three quarters, so the “Current Year Jobs” are the 2018 Jobs.

Our methodology for current year job counts at any given time averages the last four quarters of QCEW to produce an annual picture. In the 2019.2 datarun, 2018 job counts were based on the average of the latest 4 quarters available from QCEW: 2018Q3, 2018Q2, 2018Q1, and 2017Q4. in the 2019.3 datarun, 2018 job counts were based on QCEW 2018Q4, 2018Q3, 2018Q2, and 2018Q1. In the 2019.4 datarun, 2019Q1 QCEW became available, making 2019 the current jobs year in the 2019.4 datarun.

Job

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A job is any position in which a worker provides labor in exchange for monetary compensation. This includes those who work as employees for businesses (a.k.a. “wage and salary” employees) and proprietors who work for themselves.

Lightcast reports employment as annual averages. The exception is the Extended Proprietors Class of Worker (Class 4), which counts proprietors that existed at any time during a given year, because those data are based on tax returns. Employment averages represent jobs, not workers, since one individual may hold multiple jobs.

Due to limitations of source data, both full- and part-time jobs are included and counted equally, i.e. job counts are not adjusted to full-time equivalents. Geographically, payroll jobs are always reported by the place of work rather than the worker’s place of residence. Conversely, self-employed and extended proprietors are always reported by their place of residence. Unpaid family workers and volunteers are excluded from all Lightcast data.

Source: Lightcast data based primarily on the Quarterly Census of Employment and Wages (QCEW) from the Bureau of Labor Statistics (BLS) and the Bureau of Economic Analysis (BEA).

Local Area Unemployment Statistics (LAUS)

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The Local Area Unemployment Statistics (LAUS) program produces monthly and annual employment, unemployment, and labor force data for Census regions and divisions, States, counties, metropolitan areas, and many cities, by place of residence.

We use LAUS data to produce unemployment counts and labor force participation data. Each datarun includes the latest month of LAUS data that was available when the datarun was processed.

Metropolitan Statistical Area (MSA)

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A metropolitan statistical area is an area containing a substantial population nucleus, together with adjacent communities having a high degree of economic and social integration with that core. According to the United States Census Bureau, each metropolitan statistical area must have at least one urbanized area of 50,000 or more inhabitants. Pending approval, this minimum population threshold will increase to 100,000 according to the recommendations of the Metropolitan and Micropolitan Statistical Area Standards Review Committee.

Source: Census Bureau

Occupation

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The term occupation refers to professions or careers in the workforce. In Lightcast data, occupations are differentiated from jobs, as jobs show the count of positions held within a certain occupation.

For example, Health Educators would be considered an occupation; in a report focused on the Minneapolis-St. Paul-Bloomington, MN MSA, there might be 970 currently held jobs for Health Educators.

Occupational Employment Statistics (OES)

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The Occupational Employment Statistics (OES) program estimates employment and wages for most occupations by industry and sector at the national level, and by occupation at the state and metropolitan statistical area (MSA) and non-MSA levels in the 50 states and the District of Columbia. OES accounts for 1.1 million establishments and 57% of national employment, including railroad, but excluding military, agriculture, fishing, forestry, private households, self-employment, and others.

How Lightcast Incorporates OES

OES is our primary source of occupation data, but we compensate for OES’s general weaknesses and lack of valid historical data by utilizing stronger, more accurate industry employment counts from QCEW, County Business Patterns (CBP), and American Community Survey (ACS), among others. We then apply regionalized, OES-based staffing patterns to the industry data to show the distribution of jobs by occupation.

Lightcast gathers occupation earnings data from OES. We use unsuppression techniques to fill in missing values as appropriate, and also build a time series of OES data in order to present historical occupation earnings.

For a more detailed explanation of how Lightcast incorporates OES data into occupational processes, see this article.

Strengths of OES

– OES has estimates for specific industries, including national industry-specific occupational employment and wage estimates.
– OES has estimates for individual states, including cross-industry occupational employment and wage estimates for individual states.
– OES has estimates for metropolitan and nonmetropolitan areas, which together cover the entire United States.

Weaknesses of OES

– OES is merely a survey and is not based on administrative records like Quarterly Census of Employment and Wages (QCEW) from the BLS; because of this, OES’s figures aren’t as comprehensive as most industry data.
– Not all metropolitan and nonmetropolitan areas have information for all occupations.
– Only 57% of employment is covered in the OES survey (compared to the 95% of wage-and-salary jobs captured by QCEW), which excludes all industries under NAICS 11 (agriculture, forestry, fishing, and hunting) except for logging, support activities for crop production, and support activities for animal production.
– The OES survey takes up to three years to complete, so the BLS states that it is less useful for measuring change in job counts or wages over time. An apparent increase in wages, for example, could just as likely be due to different businesses responding to the survey in one year, changes in the occupational, industrial, and geographical classification systems, changes to collection or estimation methods, or changes to other methodologies in the survey. OUr occupation methodology (see article referenced above) is designed to counteract this weakness in OES data.

Occupational Information Network (O*NET)

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O*NET provides occupation data such as knowledge, skills, and abilities needed to perform the work, as well as education and training requirements and alternate job titles. We incorporate this data throughout its tools in various ways.

The O*NET Program is the nation’s primary source of occupational information. The data are essential to understanding the rapidly changing nature of work and how it impacts the workforce and U.S. economy. From this information, applications are developed to facilitate the development and maintenance of a skilled workforce.

Central to the project is the O*NET database, containing hundreds of standardized and occupation-specific descriptors on almost 1,000 occupations covering the entire U.S. economy. The database, which is available to the public at no cost, is continually updated from input by a broad range of workers in each occupation.

ONET updates do not follow a schedule; Lightcast monitors ONET for updates and downloads new data as it becomes available.

Source: O*NET

Occupational Programs

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The programs in the region of study that may train for this occupation. Lightcast uses a default crosswalk to build these associations; the occupations linked to a particular program may be edited from the program’s Program Overview page.

Source: IPEDS, NCES’s CIP-SOC Crosswalk with some modifications.

Quarterly Census of Employment and Wages (QCEW)

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Quarterly Census of Employment and Wages (QCEW) is a dataset published by the Bureau of Labor Statistics (BLS). QCEW is the backbone of our core LMI data, providing establishment counts, monthly employment, and quarterly wages, by NAICS industry, by county, and by ownership sector, for the entire United States. These data are aggregated to annual levels, to higher industry levels (NAICS industry groups, sectors, and supersectors), and to higher geographic levels (nation, state, and Metropolitan Statistical Area [MSA]).

We produce a slightly modified form of the BLS QCEW dataset.

– Lightcast provides estimates for suppressed data (roughly 60% of QCEW data points are suppressed). For more on the importance of unsuppression, see
– Lightcast alters the NAICS classification of public-sector employment to make it more compatible with other data sources. For more information, see
– Lightcast transforms the data to use consistent county and NAICS definitions from 2001 to the present; original QCEW data does not use consistent definitions year-to-year.

Strengths of QCEW

– Because QCEW is based on official government documentation (via state and federal unemployment agencies), the data is highly reliable and is considered the “gold standard” of industry data and of employment counts in the United States.
– QCEW is comprehensive, capturing 95% of US wage-and-salary jobs.
– QCEW can be viewed at a variety of detail levels, both geographically (by county, MSA, state, or national levels) and by industry level (available at 2-, 3-, 4-, 5-, and 6-digit levels).

Weaknesses of QCEW

– There is about a five- to six-month lag between when the initial data is collected and when it is released. The releases occur quarterly.
– Much of QCEW’s private-sector county level data (approximately 60%) is suppressed to protect the confidentiality of certain local businesses.
– QCEW does not report on self-employed, military, railroad, and certain farm, domestic, and non-profit workers, among others.

Skills

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In Lightcast data, skills are competencies at specific tasks or familiarity with specific subjects acquired through education or experience.

Common Skills: Common skills can be self-taught and usually do not necessitate a certain completed level of education, such as a Master’s degree, or other certifications/credentials. They are essential in many industries and occupations (e.g. problem-solving, project management).

Technical/Hard Skills: Hard skills are specific, learnable, measurable, often industry- or occupation-specific abilities related to a position. A hard skill for nurses might be CPR, and a hard skill for a data analyst might be JavaScript.

Standard Occupation Classification (SOC)

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The Standard Occupational Classification (SOC) system is used by Federal statistical agencies to classify workers into occupational categories for the purpose of collecting, calculating, or disseminating data. All workers are classified into one of about 775 detailed occupations according to their occupational definition. To facilitate classification, detailed occupations are combined to form about 450 broad occupations, about 95 minor groups, and 23 major groups. Detailed occupations in the SOC with similar job duties, and in some cases skills, education, and/or training, are grouped together.

The SOC system uses hyphenated codes to divide occupations into four levels: major groups, minor groups, broad occupations, and detailed occupations.

– 29-0000: Healthcare practitioners and technical occupations (major group)
– 29-1000: Health diagnosing and treating practitioners (minor group)
– 29-1020: Dentists (broad occupation)
– 29-1021: Dentists, general (detailed occupation)

The SOC classification system was updated in 2010, and the update to the 2018 classification is currently happening across various government LMI datasets.

Timeframe

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A timeframe is a period of study, defined by a start and an end year. In Lightcast reports, users select timeframes for which they want to study data. Lightcast provides data back to 2001 for most datasets, and projects data out 10 years from the current year for some datasets.

Unique Job Postings

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Unique Job Postings is the number of deduplicated job vacancy advertisements scraped from over 100,000 websites.

Deduplication is the process of identifying duplicate job postings and only counting one of the duplicates. The unique posting count is the count of postings after the deduplication process has taken place. The total posting count is the count of postings before deduplication. For example, if a user runs a report that returns 12 total job postings and 2 unique job postings, this means that the 12 postings contained 10 duplicates and only 2 unique job advertisements.

Wages

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Occupational wages, which are sometimes referred to as compensation, consist of percentile earnings and average earnings for the occupation.