Glossary

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Active Job Postings
Job postings that are considered active are those that are currently available online and are open for applications. Since job postings are frequently closed or removed from the web, Emsi data only reflects the number…

Job postings that are considered active are those that are currently available online and are open for applications. Since job postings are frequently closed or removed from the web, Emsi data only reflects the number of active job postings.

Adjusted Earnings
Emsi's total earnings, adjusted by the C2ER Cost of Living Index (COLI). The Cost of Living index is based off a 100 base scale, so to adjust the earnings, Emsi first divides our earnings by…

Emsi’s total earnings, adjusted by the C2ER Cost of Living Index (COLI).

The Cost of Living index is based off a 100 base scale, so to adjust the earnings, Emsi first divides our earnings by the COLI, then multiplies the result by 100.

Example:

  • Total Earnings for Manufacturing in Michigan: $78,616
  • Cost of Living in Michigan: 98.5
  • Cost of Living Adjusted Earnings: $79,813.20*

For more information about how Cost of Living is calculated, click here.

* Some calculations may not match directly. This is due to rounding methods in the data.

Advertised Salary (Job Posting Analytics)
Advertised salary within Job Posting Analytics and Job Posting Competition is the salary information provided by the company or entity advertising the position. Advertised salary can be used to understand the unique variances of advertised…

Advertised salary within Job Posting Analytics and Job Posting Competition is the salary information provided by the company or entity advertising the position. Advertised salary can be used to understand the unique variances of advertised compensation by job title, company, region, and even sometimes skill sets. It is not necessarily the actual salary the employee receives—only the salary as advertised. To analyze actual worker earnings as reported by the BLS and QCEW, we recommend you use Emsi’s occupational earnings or industry earnings

Emsi extracts information from each job posting, and if available, determines a salary for the job posting.  Many job postings do not provide salary information. In fact, only 15-20% of all postings have salary information available. This will also vary greatly depending on the occupation, industry, and job title.

Because the sample size is often small, Emsi always identifies the number of postings in your query that include salary data (as shown below). This number will not equal the number of unique postings for the query. We encourage you to reference this number to determine whether the sample size of salary data is large enough to be included in your work.

Age Demographics
A demographic breakdown, by age, of individuals working in an occupation or industry. For occupations, available by county for all 5-digit SOCs. For industries, available by county for all 6-digit NAICS. Source: For occupations, a…

A demographic breakdown, by age, of individuals working in an occupation or industry. For occupations, available by county for all 5-digit SOCs. For industries, available by county for all 6-digit NAICS.

Source: For occupations, a combination of detailed Industry Demographics, staffing patterns, and American Community Survey. For industries, Emsi’s proprietary employment data, incorporating Census’ Quarterly Workforce Indicators and American Community Survey.

American Community Survey (ACS)
The American Community Survey (ACS) is a nationwide survey designed to provide communities a fresh look at how they are changing. It is a critical element in the Census Bureau's decennial census program. The ACS…

The American Community Survey (ACS) is a nationwide survey designed to provide communities a fresh look at how they are changing. It is a critical element in the Census Bureau’s decennial census program. The ACS collects information such as age, race, income, commute time to work, home value, veteran status, and other important data. As with the 2010 decennial census, information about individuals remains confidential.

The ACS collects and produces population and housing information every year instead of every ten years. Collecting data every year provides more up-to-date information throughout the decade about the U.S. population at the local community level. About 3.5 million housing unit addresses are selected annually, across every county in the nation.

How Emsi Incorporates ACS

Emsi’s Self-Employed Class of Worker includes all people who consider self-employment a significant part of their income and/or taking a significant part of their time. Emsi largely bases job counts, hourly earnings, and projections for these unincorporated self-employed jobs on responses to the American Community Survey (with additional input from other sources).

Emsi’s Extended Proprietors Class of Worker represents jobs that generate miscellaneous labor income, such as very small self-employment income and partnerships with many partners having limited involvement. Emsi derives job counts and hourly earnings for Extended Proprietors from differences between ACS and other proprietor counts, the latter of which are based on tax returns and other data compiled by the Bureau of Economic Analysis as well as local personal income reports.

Emsi also uses ACS to construct our demographic data for the Non-QCEW Employees, Self-Employed, and Extended Proprietors Classes of Worker.

In addition, Emsi uses ACS to build national staffing patterns for the Self-Employed and Extended Proprietor Classes, and for the Employee Classes for some industries that the BLS’s OES dataset does not cover.

Strengths of ACS

  • ACS has a relatively short lag time; data is collected monthly and released within 12 months of the survey date.
  • ACS covers a wide variety of data, providing information on national demographic, social, economic, and housing characteristics.
  • Responding to the Survey is mandatory for the housing units that are selected, so participation is strong.

Weaknesses of ACS

  • ACS is a survey, meaning it is subject to various forms of measurement error such as sampling error, misclassification (industry/occupation) error, and even incomplete or misleading responses.
  • Because it is designed to ensure good geographic coverage and does not target individuals, the Census Bureau selects only a small, random sample of about 295,000 addresses (of more than 180 million) to be included in ACS each month.
  • The full implementation of ACS began in 2005, so historical data is limited.

For more information visit the ACS website.

Annual Openings Estimate
A combination of both new jobs and replacement jobs constitutes total openings. The annual openings figure is derived by dividing total openings by the number of years in the user's selected timeframe. For example, an…

A combination of both new jobs and replacement jobs constitutes total openings. The annual openings figure is derived by dividing total openings by the number of years in the user’s selected timeframe. For example, an occupation showing 130 openings between 2016 and 2026 would result in an annual openings figure of 13.

For more information on how Openings is calculated, see this article.

Source: Emsi’s proprietary employment data, combined with occupation-specific percentages from the U.S. Bureau of Labor Statistics Employment Projections program.

Application Programming Interface (API)
An application programming interface (API) is a method for separate computer applications to talk to each other. APIs are useful because they allow one computer application (e.g. website) to surface information from another system without…

An application programming interface (API) is a method for separate computer applications to talk to each other. APIs are useful because they allow one computer application (e.g. website) to surface information from another system without needing to store all the data or handle all the complexity of the other system.

Automation
The performance of a process or procedure by a computerized (automated) machine and with minimal human assistance.

The performance of a process or procedure by a computerized (automated) machine and with minimal human assistance.

Automation Index
The automation index captures an occupation’s risk of being affected by automation using four measures: % of time spent on high-risk work % of time spent on low-risk work Number of high-risk jobs in compatible occupations Overall industry automation risk This…

The automation index captures an occupation’s risk of being affected by automation using four measures:

  • % of time spent on high-risk work
  • % of time spent on low-risk work
  • Number of high-risk jobs in compatible occupations
  • Overall industry automation risk

This methodology starts with the underlying work on task content. We use estimated task time shares, derived from O*NET work activities, and regress them for each occupation based on Frey and Osborne’s published “computerization probabilities” (2013). This helps us identify which tasks are positively and negatively correlated with automation risk.

This classification is then linked with the task time shares to identify the share of each occupation’s time spent in high- and low-risk work, from an automation perspective.

Then we look at the place of an occupation in the broader context of labor market automation risk. Using occupation compatibility scores, we look at all similar roles (defined as having an O*NET compatibility score over 75) and find the percentage of jobs in those similar roles that are at risk of automation.

Finally, using staffing pattern data, we multiply the share of an occupation’s jobs in 3-digit NAICS industries by that industry’s share of at-risk jobs to calculate the overall industry automation risk.

We then standardize all these measures and scale the index so that 100 = the “average worker,” defined as the average index across all occupations, weighted by job numbers in 2018. The index has a standard deviation of 15. Note that the share of time spent on low-risk work is a negative contributor to an occupation’s index score (making the index score lower) while the other three measures are positive contributors (making the index score higher).

Automotive Manufacturing
A subset within traditional manufacturing that is focused on vehicle production. This cluster involves basic engineering skills such as hydraulics, pneumatics, and electrical systems. Because automotive manufacturing is a heavily unionized industry, collective bargaining is…

A subset within traditional manufacturing that is focused on vehicle production. This cluster involves basic engineering skills such as hydraulics, pneumatics, and electrical systems. Because automotive manufacturing is a heavily unionized industry, collective bargaining is a common business skill.

Average Annual Wage (Industry)
Also called "Wages Salaries & Proprietor Earnings", it is the result of total pre-tax industry earnings divided by same-year industry employment. Earnings are defined as labor-related personal income—that is, income from work. Income from stock…

Also called “Wages Salaries & Proprietor Earnings”, it is the result of total pre-tax industry earnings divided by same-year industry employment. Earnings are defined as labor-related personal income—that is, income from work. Income from stock dividends or interest, rents, Social Security and other non-work sources are not included.

Source: Emsi’s proprietary employment data.

Average Earnings
Also called "Current Total Earnings", this is the total pre-tax industry earnings for a region divided by number of jobs. Includes wages, salaries, supplements (additional employee benefits), and proprietor income. Source: Bureau of Labor Statistics…

Also called “Current Total Earnings”, this is the total pre-tax industry earnings for a region divided by number of jobs. Includes wages, salaries, supplements (additional employee benefits), and proprietor income.

Source: Bureau of Labor Statistics and the Bureau of Economic Analysis. If using only QCEW and/or non-QCEW in Class of Worker settings, this figure shows only wages, salaries, and supplements paid to Employees.

Benchmarking
Providing employees with measurable targets to meet.

Providing employees with measurable targets to meet.

Big Data Analytics
The use of advanced analytic techniques against very large, diverse data sets that include structured, semi-structured, and real-time data.

The use of advanced analytic techniques against very large, diverse data sets that include structured, semi-structured, and real-time data.

Bureau of Economic Analysis (BEA)
The BEA is a source of accurate and objective data about the nation’s economy. The BEA’s economists produce some of the world’s most closely watched statistics, including U.S. gross domestic product, better known as GDP.…

The BEA is a source of accurate and objective data about the nation’s economy. The BEA’s economists produce some of the world’s most closely watched statistics, including U.S. gross domestic product, better known as GDP. They do state and local numbers, too, plus foreign trade and investment states and industry data.

Source: BEA

Bureau of Labor Statistics (BLS)
The Bureau of Labor Statistics of the U.S. Department of Labor is the principal federal agency responsible for measuring labor market activity, working conditions, and price changes in the economy. Its mission is to collect,…

The Bureau of Labor Statistics of the U.S. Department of Labor 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. As an independent statistical agency, BLS serves its diverse user communities by providing products and services that are accurate, objective, relevant, timely, and accessible.

Source: BLS 

Census of Governments (COG)
The Census of Governments identifies the scope and nature of the nation’s state and local government sector; provides authoritative benchmark figures of public finance and public employment. Source: Census Bureau 

The Census of Governments identifies the scope and nature of the nation’s state and local government sector; provides authoritative benchmark figures of public finance and public employment.

Source: Census Bureau 

Certification
Certifications are recognizable qualification standards assigned by industry or education bodies.

Certifications are recognizable qualification standards assigned by industry or education bodies.

Change
The net increase/decrease in regional jobs in an industry or occupation or demographic over the selected timeframe.

The net increase/decrease in regional jobs in an industry or occupation or demographic over the selected timeframe.

Change by Demographic (I-O)
The change in jobs modeled through demographics for males, females, and eight age cohorts. This table shows the ripple effect of the initial industry change through these demographic groups. This is a result of the…

The change in jobs modeled through demographics for males, females, and eight age cohorts. This table shows the ripple effect of the initial industry change through these demographic groups. This is a result of the Social Accounting Matrix (SAM) model.

Source: We show the effects of industry change on demographics using a variety of data, including the U.S. Census Bureau’s American Community Survey (ACS) and the U.S. Census Bureau’s Quarterly Workforce Indicators (QWI) from Local Employment Dynamics (LED).

Change by Industry (I-O)
The change in jobs modeled through all two-digit industry sectors. This table shows the ripple effect of the initial industry change through all affected industries. For further detail (including job changes in all NAICS code…

The change in jobs modeled through all two-digit industry sectors. This table shows the ripple effect of the initial industry change through all affected industries. For further detail (including job changes in all NAICS code digit-levels), see below the table.

Source: Emsi’s model, incorporating data from the Bureau of Economic Analysis (BEA) and the Bureau of Labor Statistics’ (BLS) Quarterly Census of Employment and Wages (QCEW).

Change by Occupation (I-O)
The change in jobs modeled through all two-digit occupation sectors. This table shows the ripple effect of the initial industry change through all affected occupations. This is a result of the Social Accounting Matrix (SAM)…

The change in jobs modeled through all two-digit occupation sectors. This table shows the ripple effect of the initial industry change through all affected occupations. This is a result of the Social Accounting Matrix (SAM) model. We accomplish this move from industry to occupation using regional earnings staffing patterns. For further detail (including job changes in all SOC code digit-levels), see below the table.

Source: Emsi’s model, incorporating data from the Bureau of Labor Statistics’ (BLS) Quarterly Census of Employment and Wages (QCEW).

Change in Earnings (I-O)
This number represents total change in earnings resulting from the initial, user-made change. This figure includes the initial change. The change in earnings figure is dependent upon the multiplier listed below. Source: Emsi data based…

This number represents total change in earnings resulting from the initial, user-made change. This figure includes the initial change. The change in earnings figure is dependent upon the multiplier listed below.

Source: Emsi 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).

Change in Jobs (I-O)
The total number of jobs changed, including the initial change. The figure is dependent upon the multiplier listed below. Source: Emsi's model, incorporating data from the Bureau of Economic Analysis (BEA).

The total number of jobs changed, including the initial change. The figure is dependent upon the multiplier listed below.

Source: Emsi’s model, incorporating data from the Bureau of Economic Analysis (BEA).

Characteristics of the Insured Unemployed (CIU)
Characteristics of the Insured Unemployed.

Characteristics of the Insured Unemployed.

Choropleth
A GIS data layer style (visualization method) that fills regions with a darker or lighter color shade based on numeric data. It is generally ideal for ratios and percentages, but generally not recommended for absolute…

A GIS data layer style (visualization method) that fills regions with a darker or lighter color shade based on numeric data. It is generally ideal for ratios and percentages, but generally not recommended for absolute numeric values.

CIP-to-SOC Mapping
The CIP-to-SOC mapping connects educational programs with target occupations, showing potential higher ed talent pipelines into occupations. Emsi's CIP-to-SOC mapping is based on the National Center for Education Statistics' CIP-to-SOC mapping. Emsi has made modifications…

The CIP-to-SOC mapping connects educational programs with target occupations, showing potential higher ed talent pipelines into occupations. Emsi’s CIP-to-SOC mapping is based on the National Center for Education Statistics’ CIP-to-SOC mapping. Emsi has made modifications to the mapping to make it more useful.

Click here for a tutorial on editing the existing CIP-to-SOC mapping in Analyst/Developer.

If you’d like to view the complete CIP-to-SOC map, follow the steps outlined in this article.

Source: NCES.

Class of Worker (CoW)
Class of worker categorizes jobs according to the type of employment of the worker. This variable identifies whether the respondent is a salaried employee of a business, or is self-employed. For various reasons, Emsi further…

Class of worker categorizes jobs according to the type of employment of the worker. This variable identifies whether the respondent is a salaried employee of a business, or is self-employed. For various reasons, Emsi further splits each of these categories in two, resulting in four classes of worker in Emsi Data.

  • QCEW Employees: The Bureau of Labor Statistics’ Quarterly Census of Employment and Wages (QCEW) dataset is the best source for job counts data in the United States. This quarterly near-census of workers is a byproduct of unemployment insurance reporting, which businesses are required to file monthly. QCEW covers 95% of the positions held by employees in the United States.
  • Non-QCEW Employees: The remaining 5% of employment not covered by QCEW occurs marginally in specific industries and is accounted for in other government datasets. Emsi collects employment data for these industries and puts it in the Non-QCEW Employees Class of Worker. In other words, these jobs are held by employees of businesses, but for various reasons they are not covered by unemployment insurance and therefore aren’t counted in QCEW.
  • Self-Employed: This Class of Worker includes job counts for work we typically think of as constituting self-employment. The data comes from the Census’ American Community Survey, and counts respondents who list self-employment as their primary source of income.
  • Extended Proprietors: This Class of Worker contains miscellaneous job counts recorded by the BEA that exceed counts reported in American Community Survey data. Many of these jobs are incidental self-employment that does not constitute a primary source of income (e.g. selling handmade goods on Etsy). It’s important to note that, although the goal of this Class of Worker is to account for miscellaneous income from labor, it inherently contains miscellaneous income from capital as well (since the BEA looks at profits rather than earnings).

You can use any combination of these categories, but we recommend several groupings particularly.

  • To match the BLS’s QCEW dataset most closely, use the QCEW Employees class of worker by itself.
  • For a complete picture of the employed workforce, use the QCEW and non-QCEW classes together.
  • To capture the entire employed workforce, plus self-employed persons, use the QCEW Employees, non-QCEW Employees, and Self-Employed classes in conjunction. This is the default Class of Worker setting in Analyst, and generally fits most use cases.
  • The gig economy can be approximated using the Extended Proprietors Class of Worker; however, it is critically important to keep in mind that some income and “jobs” from capital will likely be included, due to the nature of the BEA’s data. This will be an approximation of the gig economy only, likely with jobs and earnings higher than they are in actuality because of the inclusion of some “extra” jobs and income.
Classification of Instructional Programs (CIP)
A standard numerical code for a post-secondary course of study, developed and defined by the U.S. Department of Education’s National Center for Education Statistics. The classification of instructional programs provides a taxonomic scheme that supports…

A standard numerical code for a post-secondary course of study, developed and defined by the U.S. Department of Education’s National Center for Education Statistics. The classification of instructional programs provides a taxonomic scheme that supports the accurate tracking and reporting of fields of study and program completions activity.

Source: NCES

Cohort
A specific age group (which may also include gender or race/ethnicity) in demographic data, e.g., “male African Americans born between 1980 and 1984.” Over time, this cohort will move through various standard Census age categories…

A specific age group (which may also include gender or race/ethnicity) in demographic data, e.g., “male African Americans born between 1980 and 1984.” Over time, this cohort will move through various standard Census age categories such as “25 to 29 year olds” and “30 to 34 year olds.”

Commercial Real Estate (CRE)
Commercial Real Estate.

Commercial Real Estate.

Commodity Flow Survey (CFS)
The Commodity Flow Survey (CFS), a component of the Economic Census, is conducted every five years by the U.S. Census Bureau in partnership with the U.S. Department of Transportation’s Bureau of Transportation Statistics. The CFS…

The Commodity Flow Survey (CFS), a component of the Economic Census, is conducted every five years by the U.S. Census Bureau in partnership with the U.S. Department of Transportation’s Bureau of Transportation Statistics. The CFS is a shipper survey of approximately 100,000 establishments from the industries of mining, manufacturing, wholesale trade, auxiliaries (i.e. warehouses and distribution centers), and select retail and service trade industries that ship commodities.

Source: Bureau of Transportation Statistics 

Common Core of Data (CCD)
The Common Core of Data is the Department of Education’s primary database on public elementary and secondary education in the United States. CCD is a comprehensive, annual, national database of all public elementary and secondary…

The Common Core of Data is the Department of Education’s primary database on public elementary and secondary education in the United States. CCD is a comprehensive, annual, national database of all public elementary and secondary schools and school districts.

Source: NCES

Compatibility Index
This number is intended to score the compatibility of two occupations in terms of the knowledge, skills, and abilities they require: a score of 100 means complete compatibility, while a score of 0 means no…

This number is intended to score the compatibility of two occupations in terms of the knowledge, skills, and abilities they require: a score of 100 means complete compatibility, while a score of 0 means no compatibility. It is an artificial number created by our proprietary algorithm and O*NET’s data on the required Levels and Importance of competencies.

Compensation
See Wages.

See Wages.

Compensation Model
Emsi's compensation model provides occupational wage data with skill and certification premiums. It combines percentile wage data from Emsi's LMI-based government data with observations culled from worker profiles. For more information on the methodology behind…

Emsi’s compensation model provides occupational wage data with skill and certification premiums. It combines percentile wage data from Emsi’s LMI-based government data with observations culled from worker profiles.

For more information on the methodology behind the comp model, see this article.

Sources: BLS Occupational Employment Statistics (OES) and Emsi Profiles.

Competency
A specific area of knowledge, skills, or abilities in the O*NET framework. For example, a competency may be academic (mathematical knowledge), practical (mathematical problem-solving skills), or physical/cognitive (number facility, mathematical reasoning).

A specific area of knowledge, skills, or abilities in the O*NET framework. For example, a competency may be academic (mathematical knowledge), practical (mathematical problem-solving skills), or physical/cognitive (number facility, mathematical reasoning).

Competitive Effect
Competitive effect indicates how much of the job change within a given region is the result of some unique competitive advantage of the region. This is because the competitive effect, by definition, measures the job…

Competitive effect indicates how much of the job change within a given region is the result of some unique competitive advantage of the region. This is because the competitive effect, by definition, measures the job change that occurs within a regional industry that cannot be explained by broader trends (i.e. the National Growth Effect and the Industrial Mix Effect).

To measure competitive effect, we subtract Expected Change from the actual regional job change in the industry of interest.

Actual Change – Expected Change = Competitive Effect

It’s important to note that this effect can be positive even if regional employment is declining. This would indicate that regional employment is declining less than national employment.

See this article for more.

Completer
A student who receives a degree, diploma, certificate, or other formal award. In order to be considered a completer, the degree/award must actually be conferred. Emsi sources completer data from IPEDS. See also: IPEDS.

A student who receives a degree, diploma, certificate, or other formal award. In order to be considered a completer, the degree/award must actually be conferred. Emsi sources completer data from IPEDS.

See also: IPEDS.

Completions
The number of degrees or certificates conferred for a specific course of study in a given year. Includes all award levels. May be greater than the actual number of students who graduated, as Emsi includes…

The number of degrees or certificates conferred for a specific course of study in a given year. Includes all award levels. May be greater than the actual number of students who graduated, as Emsi includes both primary and secondary majors. Both primary and secondary majors are included because a graduate with a dual major in mathematics and electrical engineering should be considered part of the potential supply for occupations that map to both majors.

The reference period for a completion year is July 1 of the prior year through June 30 of the current year. For example, the 2017 Completions metric is a count of completions from 7/1/2016-6/30/2017.

Source: NCES, IPEDS.

Concentration
See Location Quotient.

See Location Quotient.

Consumer Expenditure Survey (CEX)
The Consumer Expenditure Survey program provides data on expenditures, income, and demographic characteristics of consumers in the United States. The BLS Consumer Expenditure Survey (CEX) provides data on expenditures, income, and demographic characteristics of consumers…

The Consumer Expenditure Survey program provides data on expenditures, income, and demographic characteristics of consumers in the United States. The BLS Consumer Expenditure Survey (CEX) provides data on expenditures, income, and demographic characteristics of consumers in the United States. Emsi utilizes this data heavily in the Input-Output model to model consumption on industries by national demographic by income type.

Emsi uses CEX’s annually updated tables, which are generally released in September.

Cost of Living (CoL)
The cost of living is an indication of the amount of money needed to live in a given region, including the price of food, taxes, housing, etc., and is linked to the wage level in…
The cost of living is an indication of the amount of money needed to live in a given region, including the price of food, taxes, housing, etc., and is linked to the wage level in that region.

 

Cost of Living Index (CoLI)
The Cost of Living Index (COLI) comes quarterly from C2ER and provides a baseline for understanding how regional costs of living compare to the nation and to each other. The index is comprised of six…

The Cost of Living Index (COLI) comes quarterly from C2ER and provides a baseline for understanding how regional costs of living compare to the nation and to each other. The index is comprised of six major categories: grocery items, housing, utilities, transportation, health care, and miscellaneous goods and services. For example, an index below 100 means the region has a lower cost of living, whereas above 100 means it is more expensive to live.

Council for Community and Economic Research (C2ER)
The Council for Community and Economic Research is a membership organization that promotes excellence in community and economic research by working to improve data availability, enhance data quality, and foster learning about regional economic analytic…

The Council for Community and Economic Research is a membership organization that promotes excellence in community and economic research by working to improve data availability, enhance data quality, and foster learning about regional economic analytic methods.

Source: Council for Community and Economic Research 

County Business Patterns (CBP)
County Business Patterns (CBP) is an annual series that provides subnational economic data by industry. This series includes the number of establishments, employment during the week of March 12, first quarter payroll, and annual payroll.…

County Business Patterns (CBP) is an annual series that provides subnational economic data by industry. This series includes the number of establishments, employment during the week of March 12, first quarter payroll, and annual payroll. Emsi uses CBP to help unsuppress QCEW data.

County Not Reported
Emsi geographies include a "county" within each state entitled "[(State), county not reported]". These regions are used in the Quarterly Census of Employment and Wages dataset from the Bureau of Labor Statistics, our primary source for…

Emsi geographies include a “county” within each state entitled “[(State), county not reported]”. These regions are used in the Quarterly Census of Employment and Wages dataset from the Bureau of Labor Statistics, our primary source for job counts.

Jobs that appear in these “counties” represent headcount for employers who have multiple establishments within a state, but report all those establishments in aggregate, with no geographical distinctions. In these cases the BLS is unable to assign jobs to particular counties, and so reports them all under the county not reported category. To be able to display and include these jobs in state-level estimates, Emsi also includes them using the “county not reported” geography for each state.

This arrangement affects about 2% of jobs in the United States.

Crime Data
Emsi's crime data comes from the FBI's Uniform Crime Reporting Program and includes crime counts broken into two categories: violent and property crime. Violent crime: murder and nonnegligent manslaughter, rape, robbery, and aggravated assault. Property crime: offenses…

Emsi’s crime data comes from the FBI’s Uniform Crime Reporting Program and includes crime counts broken into two categories: violent and property crime.

  • Violent crime: murder and nonnegligent manslaughter, rape, robbery, and aggravated assault.
  • Property crime: offenses of burglary, larceny-theft, and motor vehicle theft.

Local law enforcement agencies collect detailed incident level data regarding individual offenses and arrests and submit them to the National Incident-Based Reporting System using prescribed data elements and data values.

This data is often updated during the Q4 data run for the previous calendar year. Crime data is available at the county level for the United States. It is important to note that the data is collected by the location of the reporting agency, not by the location of the crime. Therefore, in cases where the reporting agency is not located in the county in which the crime was committed, the crime will be counted in the county of the reporting agency’s location.

Current Employment Statistics (CES)
Each month the Current Employment Statistics (CES) program surveys approximately 142,000 businesses and government agencies, representing approximately 689,000 individual worksites, in order to provide detailed industry data on employment, hours, and earnings for workers on…

Each month the Current Employment Statistics (CES) program surveys approximately 142,000 businesses and government agencies, representing approximately 689,000 individual worksites, in order to provide detailed industry data on employment, hours, and earnings for workers on nonfarm payrolls. Emsi uses CES to inform employment estimates for some of the industries not covered by QCEW.

Current Population Survey (CPS)
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. Emsi uses CPS unemployment data in a handful…

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. Emsi uses CPS unemployment data in a handful of cases to help break out county-level unemployment. CPS data is also the basis for the demographic breakout of data in the Input-Output model.

Current Year
"Current Year" is defined by the data currently available from QCEW and OES, Emsi's major sources for industry and occupation data, respectively. QCEW defines Emsi's current year for industry and occupation job counts and industry…

“Current Year” is defined by the data currently available from QCEW and OES, Emsi’s major sources for industry and occupation data, respectively. QCEW defines Emsi’s current year for industry and occupation job counts and industry earnings, and OES defines Emsi’s current year for occupational earnings. QCEW generally lags the current calendar year by nine months, releasing the first quarter of the calendar year’s data in early September. Therefore, Emsi’s current year for job counts and industry earnings catches up to the calendar year in the last quarter of the calendar year. OES releases in the spring of the year following; for instance, 2017 OES was released in May 2018. Therefore, the current year for occupational earnings data is two years behind the calendar year in the first half of the calendar year, and one year behind the calendar year in the last half of the calendar year.

Deduplication of Job Postings
Deduplication refers to the process of identifying and accounting for job postings that advertise for the same vacancy. Because Emsi scrapes job postings from over 100,000 websites, the likelihood of scraping the same posting twice…

Deduplication refers to the process of identifying and accounting for job postings that advertise for the same vacancy. Because Emsi scrapes job postings from over 100,000 websites, the likelihood of scraping the same posting twice is extremely high. Deduplication takes this into account, yielding a more accurate count of unique job postings.

For more information on how Emsi deduplicates job postings, see the JPA methodology article.

See also Total Job Postings and Unique Job Postings.

Demand (I-O)
Demand is an estimate of the amount of goods and services required by a region in order to remain in operation at current levels. The value is calculated using industry purchases across the nation, measured…

Demand is an estimate of the amount of goods and services required by a region in order to remain in operation at current levels. The value is calculated using industry purchases across the nation, measured in terms of sales. Industry wages, taxes, and other values added payments are indirectly part of the demand through the production of the supplying industry. It is not possible to know the proportions into which demand should be broken out into categories such as wages, taxes, etc., but it is assumed that demand includes those categories.

See also: Sales, How Do Demand and Sales Differ?

Department of Labor (DoL)
The mission of the Department of Labor is to foster, promote, and develop the welfare of the wage earners, job seekers, and retirees of the United States; improve working conditions; advance opportunities for profitable employment;…

The mission of the Department of Labor is to foster, promote, and develop the welfare of the wage earners, job seekers, and retirees of the United States; improve working conditions; advance opportunities for profitable employment; and assure work-related benefits and rights.

Source: Department of Labor

Direct Effect (I-O)
The effect of new input purchases by the initially changed industries. This is the first round of impacts. This change is due to inter-industry effects. See also Initial, Indirect, and Induced Effects. Source: Emsi's model,…

The effect of new input purchases by the initially changed industries. This is the first round of impacts. This change is due to inter-industry effects.

See also Initial, Indirect, and Induced Effects.

Source: Emsi’s model, incorporating data from the Bureau of Economic Analysis (BEA).

Distance Offered Programs
Distance-offered programs (often referred to as online courses) are college courses which are available for students to attend online from a remote location, while sometimes available on campus as well. These programs allow for higher…

Distance-offered programs (often referred to as online courses) are college courses which are available for students to attend online from a remote location, while sometimes available on campus as well. These programs allow for higher enrollment rates and therefore higher graduation rates for participating schools. See this article for more information.

Earnings (Industry)
Industry earnings are the total industry wages, salaries, supplements, and proprietor income divided by the number of jobs in the region.

Industry earnings are the total industry wages, salaries, supplements, and proprietor income divided by the number of jobs in the region.

Earnings Multiplier (I-O)
The total earnings created in a region as a result of a single dollar of new earnings. This number includes the yield and the initial dollar addition. In other words, an earnings multiplier of 1.82…

The total earnings created in a region as a result of a single dollar of new earnings. This number includes the yield and the initial dollar addition. In other words, an earnings multiplier of 1.82 is made up of the initial dollar added (1.0) and the further yield (0.82).

Source: Emsi’s model, incorporating data from the Bureau of Economic Analysis (BEA).

Earnings Multipliers (General)
An earnings multiplier of 1.5 means that for every dollar of earnings generated by a new scenario, a total of $1.50 is paid out in wages, salaries, and other compensation throughout your economy. This is…

An earnings multiplier of 1.5 means that for every dollar of earnings generated by a new scenario, a total of $1.50 is paid out in wages, salaries, and other compensation throughout your economy. This is important for understanding how a given scenario will affect not the number of jobs in your region, but the quality of those jobs. A scenario whose ripple effect brought two dozen lawyers and accountants into your region would have a much higher earnings multiplier than if that scenario brought the same number of indirect jobs into the region, but mostly in Food Services and Hotels.

Earnings Per Job (EPJ)
Earnings Per Job.

Earnings Per Job.

Economic Base
An economic base refers to the industries that contribute a large percentage of jobs and earnings to a local region. Aside from producing in-region income, they often bring in outside revenue as well, which helps…

An economic base refers to the industries that contribute a large percentage of jobs and earnings to a local region. Aside from producing in-region income, they often bring in outside revenue as well, which helps to grow the region’s economy.

Economic Development Organization (EDO)
Economic Development Organization.

Economic Development Organization.

Education Level by SOC
The most significant source of education or training for an occupation. Combines typical education, experience, and on-the-job training held by workers in this field. Source: Bureau of Labor Statistics.

The most significant source of education or training for an occupation. Combines typical education, experience, and on-the-job training held by workers in this field.

Source: Bureau of Labor Statistics.

Educational Attainment (Demographics)
Educational Attainment indicates the level of education achieved by segments of the population of the United States. The data are broken out by gender and by race/ethnicity for the population ages 25 and over. Source: Census Bureau

Educational Attainment indicates the level of education achieved by segments of the population of the United States. The data are broken out by gender and by race/ethnicity for the population ages 25 and over.

Source: Census Bureau

Educational Attainment (O*NET)
O*NET Educational Attainment is a breakdown of the education levels generally required for employment in an occupation. These levels may differ from the actual education levels attained by the occupation's workforce which are presented in…

O*NET Educational Attainment is a breakdown of the education levels generally required for employment in an occupation. These levels may differ from the actual education levels attained by the occupation’s workforce which are presented in the SOC Educational Attainment section of Analyst.

Source: O*NET Database

Educational Attainment (SOC)
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)…

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
In Emsi data, employed refers to any person who is currently paid as an employee or is self-employed. Our data only counts each person once even if he or she has multiple jobs.

In Emsi data, employed refers to any person who is currently paid as an employee or is self-employed. Our data only counts each person once even if he or she has multiple jobs.

Employment Projections (EP)
The Bureau of Labor Statistics' Employment Projections program produces many datasets covering various facets of the labor force. the EP tables are updated every two years. Emsi uses several datasets from EP: Occupational Separations and…

The Bureau of Labor Statistics’ Employment Projections program produces many datasets covering various facets of the labor force. the EP tables are updated every two years. Emsi uses several datasets from EP:

  1. Occupational Separations and Openings is used to provide replacement rates for use in Emsi’s Openings calculation.
  2. Educational attainment for workers 25 years and older by occupation shows, by occupation, the percent educational breakout of the workforce for the occupation. Emsi uses this data as-is in its Educational Attainment breakouts for individual occupations:
  3. The Education and training by occupation table shows the typical education level needed to enter an occupation, as well as the work experience and typical level of on-the-job-training required.
  4. The National Industry-Occupation Employment Matrix (NIOEM) is used to adjust Emsi’s industry projections.
End Year
In the Timeframe in the toolbar this is the second year you’ve chosen. If your timeframe is 2008-2013, 2013 is your “end year.” See Timeframe and Start Year.

In the Timeframe in the toolbar this is the second year you’ve chosen. If your timeframe is 2008-2013, 2013 is your “end year.” See Timeframe and Start Year.

Establishments
Also referred to as a "Payrolled Business Location", an establishment is a single physical location of some type of economic activity (a business), used for reporting purposes in government data sources. A single company may have…

Also referred to as a “Payrolled Business Location”, an establishment is a single physical location of some type of economic activity (a business), used for reporting purposes in government data sources. A single company may have multiple establishments.

As an example, a single company with its corporate office in New York, a paper manufacturing plant in Georgia, and fifteen warehouses in various cities would comprise a total of seventeen establishments, and each establishment would be classified according to its own type of activity. In this case, three different industries would be used:

  • Corporate, subsidiary, and regional managing offices
  • Paper (except newsprint) mills
  • General warehousing and storage

Source: QCEW.

Ethnicity
See Race and Ethnicity.
Expected Change
In shift share analysis, expected change is the amount of job growth or decline that we would expect to see for a particular regional industry based on the national growth effect and the industry (or…

In shift share analysis, expected change is the amount of job growth or decline that we would expect to see for a particular regional industry based on the national growth effect and the industry (or occupation) mix effect. Job change beyond this level is “unexpected” and can therefore be attributed to the region’s unique competitive effect (see definition below).

To measure expected change, we simply add the two effects we previously calculated:

Industrial Mix Effect + National Growth Effect = Expected Change

See this article for more.

Exports (I-O)
For the purposes of this definition, “region” refers to the area defined by the user and passed into Analyst. Exports show the amount of money that is spent by industries located outside the region in…

For the purposes of this definition, “region” refers to the area defined by the user and passed into Analyst. Exports show the amount of money that is spent by industries located outside the region in exchange for goods or services produced by an industry located in the region.

Exports can be either foreign or domestic. An example of foreign exports would be a business in Toronto purchasing consulting services from a consulting firm in New York in exchange for dollars. An example of domestic exports would be a firm in Maryland selling a software product to a firm in Alabama—the Maryland firm has exported its product to Alabama in exchange for dollars. Both the consulting and software examples are considered exports, because a good or service is leaving the region, and dollars are entering the region in exchange.

The exports figure does not directly include wages of employees in the industry from which goods or services were purchased. Money entering the region in exchange for goods and services exported out of the region will likely be indirectly used to pay employees (regardless of where the employee lives), but the exports figure is agnostic of what the industry producing the good or service will do with the money.

Source: Emsi’s model, incorporating data from the Bureau of Economic Analysis (BEA).

Extended Proprietors (Class of Worker 4)
This class covers the same job types as the "Self-Employed" class of worker, but Extended Proprietor jobs represent miscellaneous labor income for persons who do not consider it a primary job. Extended Proprietor jobs include…

This class covers the same job types as the “Self-Employed” class of worker, but Extended Proprietor jobs represent miscellaneous labor income for persons who do not consider it a primary job. Extended Proprietor jobs include minor or underreported self-employment, investments trusts and partnerships, certain farms, and tax-exempt nonprofit cooperatives. This class is normally only used for Input-Output purposes, since investments and partnerships in particular will be overrepresented in certain sectors.

See also Class of Worker (CoW)

Source: Emsi’s proprietary data, combined with BEA and Census datasets.

Factor Analysis
A statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors.

A statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors.

FBI Uniform Crime Reporting (UCR)
Emsi's crime data comes from the FBI's Uniform Crime Reporting (UCR) dataset. UCR data is updated annually, provides statistics for violent and property crimes, and is available at the county level.

Emsi’s crime data comes from the FBI’s Uniform Crime Reporting (UCR) dataset. UCR data is updated annually, provides statistics for violent and property crimes, and is available at the county level.

Federal Information Processing Standards (FIPS)
FIPS are standards and guidelines for federal computer systems that are developed by the National Institute of Standards and Technology (NIST) in accordance with the Federal Information Security Management Act (FISMA) and approved by the…

FIPS are standards and guidelines for federal computer systems that are developed by the National Institute of Standards and Technology (NIST) in accordance with the Federal Information Security Management Act (FISMA) and approved by the Secretary of Commerce. These standards and guidelines are developed when there are no acceptable industry standards or solutions for a particular government requirement. Although FIPS are developed for use by the federal government, many in the private sector voluntarily use these standards.

Source: NIST

Filters
In Emsi 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…

In Emsi 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.

Freshmen Home Residency
Freshmen Home Residency shows the home state of first-time, first-year students. Transfer and returning students are not included in the data. Freshmen home residency data are reported to IPEDS by individual institutions. To ease the…

Freshmen Home Residency shows the home state of first-time, first-year students. Transfer and returning students are not included in the data.

Freshmen home residency data are reported to IPEDS by individual institutions. To ease the burden on individuals responsible for completing IPEDS reporting on behalf of their institutions, reporting of freshmen home residency data is only required every other year.

Source: Integrated Postsecondary Education System (IPEDS)

Gender
Industry: A demographic breakdown, by gender, of individuals working in the selected industry. Available by county for all 6-digit NAICS. Occupation: A demographic breakdown, by gender, of individuals working in the selected occupation. Available by county…

Industry: A demographic breakdown, by gender, of individuals working in the selected industry. Available by county for all 6-digit NAICS.

Occupation: A demographic breakdown, by gender, of individuals working in the selected occupation. Available by county for all 5-digit SOCs.

Source: (Industry) Emsi’s proprietary employment data, incorporating Census’ Quarterly Workforce Indicators and American Community Survey; (Occupation) A combination of detailed Industry Demographics, staffing patterns, and American Community Survey.

Graduate
Emsi uses the terms “completion” and “graduate” interchangeably, and it is important to understand what is meant. Both terms refer to the number of degrees awarded rather than the number of students who graduated. Although…

Emsi uses the terms “completion” and “graduate” interchangeably, and it is important to understand what is meant. Both terms refer to the number of degrees awarded rather than the number of students who graduated. Although students may graduate with multiple awards (e.g. “double majors”), our source data do not link awards to students.

See also: Completions.

Gross Domestic Income (GDI)
Gross domestic income is a measure of U.S. economic activity based on incomes. In theory, GDI should equal gross domestic product (GDP), but the different source data yield different results. BEA considers GDP more reliable…

Gross domestic income is a measure of U.S. economic activity based on incomes. In theory, GDI should equal gross domestic product (GDP), but the different source data yield different results. BEA considers GDP more reliable because it’s based on timelier, more expansive data.

Source: https://www.bea.gov/data/income-saving/gross-domestic-income

Gross Domestic Product (GDP)
The BEA produces Gross Domestic Product estimates. GDP is the value of the goods and services produced in an economy. Emsi uses BEA's GDP by State (GSP) data for benchmarking parts of the Input-Output model.…

The BEA produces Gross Domestic Product estimates. GDP is the value of the goods and services produced in an economy. Emsi uses BEA’s GDP by State (GSP) data for benchmarking parts of the Input-Output model. GDP is updated annually.

Source: BEA

Gross Domestic Product by State (GSP)
The BEA produces Gross Domestic Product estimates. GDP is the value of the goods and services produced in an economy. Emsi uses BEA's GDP by State (GSP)   data for benchmarking parts of the Input-Output model.…

The BEA produces Gross Domestic Product estimates. GDP is the value of the goods and services produced in an economy. Emsi uses BEA’s GDP by State (GSP)   data for benchmarking parts of the Input-Output model. GSP is updated annually.

Gross Regional Product (GRP)
Gross Regional Product (GRP) is simply GDP for the region of study. More commonly, GRP is GDP for any region smaller than the United States, such as a state or metro. GRP measures the final…

Gross Regional Product (GRP) is simply GDP for the region of study. More commonly, GRP is GDP for any region smaller than the United States, such as a state or metro. GRP measures the final market value of all goods and services produced in the region of study.

GRP is the sum of total industry earnings, taxes on production & imports, and profits, less subsidies (GRP = earnings + TPI + profits – subsidies).

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

Growth Effect
The national growth effect shows the number of jobs an industry is expected to gain or lose according to the industry’s national job growth. So if the industry sees national net job growth, you can…

The national growth effect shows the number of jobs an industry is expected to gain or lose according to the industry’s national job growth. So if the industry sees national net job growth, you can expect to see job growth in most regions within the country as well.

This is sometimes explained as “the rising tide that lifts all boats.” Imagine several boats floating near the shore. If the tide begins to rise, each boat will rise with the tide–just as each boat will lower when the water lowers. This rising and falling is the national growth effect. It’s important to remember, however, that sometimes one of these “boats” (which are industries, in this case) may be pulled down deeper in the water, or may be experiencing higher tides on its own. These phenomena can be explained by competitive effect (see below). To measure the national growth effect, we simply multiply the growth rate of the overall economy to the number of jobs in your region that are part of the industry.

National Growth Rate x Number of Regional Industry Jobs= National Growth Effect

 

See this article for more.

Growth Period
See Timeframe.

See Timeframe.

Higher Education (HE)
In the U.S., Higher Education refers to colleges and universities. In the U.K., however, education after the high school level qualifies as Higher Ed. Emsi clients may use our Higher Ed data to understand how…

In the U.S., Higher Education refers to colleges and universities. In the U.K., however, education after the high school level qualifies as Higher Ed.

Emsi clients may use our Higher Ed data to understand how well their programs prepare students for the workforce and what other institutions might be offering in terms of competition.

Hires
The number of hires for the selected timeframe. When compared with Unique Postings, Hires shows how much actual hiring activity there is relative to the amount of posting activity. A hire is reported by the Quarterly…

The number of hires for the selected timeframe. When compared with Unique Postings, Hires shows how much actual hiring activity there is relative to the amount of posting activity.

A hire is reported by the Quarterly Workforce Indicators when an individual’s Social Security Number appears on a company’s payroll and was not there the quarter before. The QWI program produces a comprehensive tabulation of employment and wage information for workers covered by State unemployment insurance (UI) laws, similar to the QCEW program. For more information from the Census Bureau on how hires data is collected, see this publication.

For more information on how Emsi calculates hires for occupations, see the methodology article.

Source: Quarterly Workforce Indicators (QWI) from the Census Bureau and Emsi’s proprietary employment data

Historical Wages
Average and percentile wages are the earnings for an occupation. Historical wages are provided as far back as 2005 in Emsi tools, which enables users to track trends in wage growth or decline over time.…

Average and percentile wages are the earnings for an occupation. Historical wages are provided as far back as 2005 in Emsi tools, which enables users to track trends in wage growth or decline over time. Historical wages are nominal, meaning that they are not adjusted for inflation.

Housing and Urban Development (HUD)
The Department of Housing and Urban Development administers programs that provide housing and community development assistance. The Department also works to ensure fair and equal housing opportunity for all. Source: usa.gov

The Department of Housing and Urban Development administers programs that provide housing and community development assistance. The Department also works to ensure fair and equal housing opportunity for all.

Source: usa.gov

Importance
On a scale of 1-100, how important the required level of knowledge, skill, or ability is to an occupation. Typically Importance and Level are similar, but there are cases such as a Registered Nurse’s knowledge…

On a scale of 1-100, how important the required level of knowledge, skill, or ability is to an occupation. Typically Importance and Level are similar, but there are cases such as a Registered Nurse’s knowledge of medicine and dentistry. They require “65 out of 100” in terms of their Level of knowledge, but the Importance of having that knowledge is scored “91 out of 100.” They don’t need to know everything about the topic, but what they do need to know is very important to their job.

By comparing Importance and Level across all occupations, we can view similar occupations based on overlap between the two.

Source: O*NET Database.

Imports (I-O)
For the purposes of this definition, “region” refers to the area defined by the user and passed into Analyst. Imports show the amount of money that is spent by all industries located in the region…

For the purposes of this definition, “region” refers to the area defined by the user and passed into Analyst.
Imports show the amount of money that is spent by all industries located in the region in exchange for goods or services produced by an industry located outside the region. Money leaves the region, and a good or service is brought into the region and consumed.

Imports can be foreign or domestic. An example of foreign imports would be a firm in New York paying money for consulting services from a firm in Toronto. An example of domestic imports would be the same firm in New York purchasing consulting services from a firm in Alabama.

The imports figure does not directly include wages of employees in the industry from which goods or services were purchased. Money used to purchase imported goods and services will likely be indirectly used to pay employees of the industry from which the good or service was purchased (regardless of where the employee lives), but the imports figure is agnostic of what the industry producing the good or service will do with the money.

Source: Emsi’s model, incorporating data from the Bureau of Economic Analysis (BEA).

Income
Income refers to the amount of money an employee receives for their work. Income may be salaried or non-salaried, and therefore does not imply consistency in the amount received during each pay period.

Income refers to the amount of money an employee receives for their work. Income may be salaried or non-salaried, and therefore does not imply consistency in the amount received during each pay period.

Indirect Effect (I-O)
The subsequent ripple effect in further supply chains resulting from the direct change. In more awkward terms, this shows the sales change in the supply chains of the supply chain, as a result of the…

The subsequent ripple effect in further supply chains resulting from the direct change. In more awkward terms, this shows the sales change in the supply chains of the supply chain, as a result of the direct change. This is the second round of impacts. This change is due to inter-industry effects.

See also Initial, Direct, and Induced Effects.

Source: Emsi’s model, incorporating data from the Bureau of Economic Analysis (BEA).

Induced Effect (I-O)
This change is due to the impact of the new earnings created by the Initial, Direct, and Indirect changes. These earnings enter the economy as employees spend their paychecks in the region on food, clothing,…

This change is due to the impact of the new earnings created by the Initial, Direct, and Indirect changes. These earnings enter the economy as employees spend their paychecks in the region on food, clothing, and other goods and services. In other words, this figure represents the income effects on inter-industry trade.

See also Initial, Direct, and Indirect Effects.

Source: Emsi’s model, incorporating data from the Bureau of Economic Analysis (BEA).

Industry
A group of businesses that produce similar goods and services, and share similar production processes for creating the goods and services they sell. Industries are classified using NAICS codes. Note that in the NAICS system,…

A group of businesses that produce similar goods and services, and share similar production processes for creating the goods and services they sell. Industries are classified using NAICS codes. Note that in the NAICS system, what a business produces is given less importance than the process used to create it. See NAICS.

Industry Diversity Clusters
Emsi's diversity cluster definitions and ranking methodology come from C2ER (The Council for Community and Economic Research). These measures quantify how jobs are distributed across industry clusters in a select region compared to a typical…

Emsi’s diversity cluster definitions and ranking methodology come from C2ER (The Council for Community and Economic Research). These measures quantify how jobs are distributed across industry clusters in a select region compared to a typical one.

Background

A region’s economic function or functions represent the collection of broad economic activities in which the region’s workforce and firms engage. Practically, functions can be identified by grouping industries together into categories that are broadly similar on factors such as inputs, outputs, and/or the technological or skill requirements necessary to perform the work customary to these industries. Grouping industries according to function, rather than simply accepting the NAICS industry categories, can help to

  • Broadly characterize the economic roles a county plays in its region
  • Provide insight into the economic relationships and similarities counties have with other regions
  • Identify factors that make regions comparatively better fits for certain economic activities
  • Speak to the broader economic and demographic forces that are likely to impact a county’s economic prospects

Methodology

The entropy measure of diversity is used to calculate industry function and occupation knowledge-based measures of economic diversity across U.S. counties and a variety of other geographies.[1] These metrics were calculated according to the following formula:

where there are i = 1 to k industries and pi is the share of economic activity (e.g. employment or earnings) in the i th industry. The products of industry shares of economic activity and the natural log of the inverse industry shares of economic activity are summed to arrive at the final entropy index measurement. The index has a minimum value of 0 when all economic activity is within one industry, and the value increases as the number of industries increases and the distribution of economic activity across these industries becomes more equal.

Separate diversity rankings have been created based on geography type: county, microMSA, MetroMSA, and state.

Creating Industry Function Classifications

In an examination of the rise of services as a proportion of employment, Noyelle (1983) advanced a functional classification system for services based on the type of outputs (intermediate or final outputs) and the institutional setting under which services are provided (private, public, or nonprofit sectors).[2] Lawrence (1984) classified manufacturing industries on the basis of the primary end use of the product (e.g. intermediate goods; consumer durables; producer durables; consumer nondurables) and the necessary inputs to the industry (e.g. research and development expenditures; scientists and engineers; capital-, labor-, and resource-intensive).[3]

This analysis draws primarily from the work of Lawrence (1984) and Noyelle (1983) to categorize industries according to functional types. In an effort to focus on the economic base of counties, non-function industries or industries that often serve local populations, such as retail, trade, personal services, doctor’s offices, local government, and construction, were excluded from the analysis of functions.

[1] Malizia, E. E., & Ke, S. (1993). The influence of economic diversity on unemployment and stability. Journal of Regional Science, 33(2), 221-235.

[2] Noyelle, T. J. (1983). The implications of industry restructuring for spatial organization in the United States. In Regional analysis and the new international division of labor (pp. 113-133). Springer, Dordrecht.

[3] Lawrence, R. (1984). Sectoral Shifts and the Size of the Middle Class. The Brookings Review, 3(1), 3-11.

Industry Earnings
Emsi earnings data is presented by place of work. Emsi displays industry earnings as two separate values: “Wages and Salaries” and “Supplements” (or the total, “Earnings”). Wages and salaries are equivalent to QCEW reported earnings.…

Emsi earnings data is presented by place of work. Emsi displays industry earnings as two separate values: “Wages and Salaries” and “Supplements” (or the total, “Earnings”).

Wages and salaries are equivalent to QCEW reported earnings. The BLS defines wages and salaries as including “bonuses, stock options, severance pay, the cash value of meals and lodging, tips and other gratuities. In some states, wages also include employer contributions to certain deferred compensation plans, such as 401(k) plans. Covered employers’ contributions to old-age, survivors, and disability insurance; health insurance; unemployment insurance (UI); workers’ compensation; and private pension and welfare funds are not reported as wages. Employee contributions for the same purposes, however, as well as money withheld for income taxes, union dues, and so forth, are reported, even though they are deducted from the worker’s gross pay.”

Supplements come from the BEA’s State and Local Personal Income datasets. According to the BEA, supplements consists of “employer contributions for employee pension and insurance funds and employer contributions for government social insurance.”

  • Contributions for employee pension and insurance funds include employer contributions to private pensions, publicly administered government employee retirement plans, private group health and life insurance plans, etc.
  • Contributions for government social insurance include “employer contributions for government social insurance as well as payments by employees, the self-employed, and other individuals who participate in government social insurance programs.”

Source: BLS wage definition taken from BLS Handbook of Methods, QCEW chapter, pp. 3-4.
BEA supplements definitions drawn from BEA Regional Definitions tool.

Industry Projections
Emsi projects employment data 10 years into the future. Industry projections are built from Emsi's final industry data, which is based on the BLS's Quarterly Census of Employment and Wages (QCEW) dataset. See this article…

Emsi projects employment data 10 years into the future. Industry projections are built from Emsi’s final industry data, which is based on the BLS’s Quarterly Census of Employment and Wages (QCEW) dataset.

See this article for a more thorough treatment of Emsi’s industry projections methodology.

Sources: QCEW

Industry Requirements (Supply Chain)
Derived from Emsi's Input-Output model, this figure describes the purchases a given industry makes from all other industries—an industry's supply chain—and also estimates whether those purchases came from within or without the region of study.…

Derived from Emsi’s Input-Output model, this figure describes the purchases a given industry makes from all other industries—an industry’s supply chain—and also estimates whether those purchases came from within or without the region of study. Also known as Gap Analysis, this report is an important part of import substitution strategies employed by economic development organizations.

See also: Supply Chain Analysis

Source: Emsi’s model, incorporating data from the Bureau of Economic Analysis (BEA).

Initial Effect (I-O)
This number represents the initial change in earnings or jobs as input by the user, and therefore does not include ripple effects. See also Direct, Indirect, and Induced Effects.

This number represents the initial change in earnings or jobs as input by the user, and therefore does not include ripple effects.

See also Direct, Indirect, and Induced Effects.

Input-Output Model (I-O)
An Input-Output model represents the flow of money in an economy, primarily through the connection between industries; to what extent are different industries buying and selling to one another in a particular geographic region. Also…

An Input-Output model represents the flow of money in an economy, primarily through the connection between industries; to what extent are different industries buying and selling to one another in a particular geographic region. Also accounted for in an I-O model are things like government spending, household spending, investments, imports and exports, all of which help us gain a full picture of what is happening in an economy.

I-O models have three important uses:

  1. Change – An I-O model can be used to demonstrate the effect job loss or job creation will have on a regional economy–to what extent it will affect other jobs in the area, additional earnings and sales. See how to do this HERE.
  2. Supply Chain – An I-O model has the potential to expose the supply chain of goods via industries in a region. In particular, to what extent each industry is able to satisfy its purchasing needs in-region or out-region. This can be very helpful to economic development organizations who are looking to strengthen a local supply chain and increase in-region purchasing. See how to view an industry’s supply chain HERE.
  3. Industry Importance – An I-O model can be used to identify important industries in your region–not just those with a lot of jobs (like retail or healthcare) but also those which have an unusually large and positive economic impact, like advanced manufacturing, technology, etc.
Integrated Post-secondary Education Data System (IPEDS)
IPEDS is a system of interrelated surveys conducted annually by the U.S. Department’s National Center for Education Statistics (NCES). IPEDS gathers information from every college, university, and technical and vocational institution that participates in the…

IPEDS is a system of interrelated surveys conducted annually by the U.S. Department’s National Center for Education Statistics (NCES). IPEDS gathers information from every college, university, and technical and vocational institution that participates in the federal student financial aid programs. The Higher Education Act of 1965, as amended, requires that institutions that participate in federal student aid programs report data on enrollments, program completions, graduation rates, faculty and staff, finances, institutional prices, and student financial aid. Many institutions that do not receive federal funding also participate and report their data to IPEDS voluntarily.

Emsi uses IPEDS data to provide information about postsecondary institutions, especially in regard to college completions by program type and demographic (race and gender). Completions include degrees (associate’s, bachelor’s, master’s, doctoral), certificates, and any other formal award.

In addition, Emsi uses the CIP system to create program-to-occupation crosswalks, which map programs of study to occupations and reveal one measure of education supply and demand.

Strengths of IPEDS

  • Because the Higher Education Act of 1965, as amended, requires that institutions that participate in federal student aid programs report data to IPEDS, the data is a very comprehensive source.
  • IPEDS data has several uses, including providing the market research information necessary for universities and colleges to evaluate new and existing programs.
  • IPEDS allows you to view information for an individual institution, compare institutions side-by-side, or view trends for certain variables.

Weaknesses of IPEDS

  • Institutions self-report their information to IPEDS, so the possibility of error exists, particularly in regard to the reported programs of study.
  • There is about a year lag between when IPEDS collects its data and when it is released.
  • IPEDS is not comprehensive of all education and training programs (e.g. MakerSquare and other non-traditional education and training programs are not included in this data).
  • Programs that are offered online are flagged as such, but its enrollments and completions cannot be split out to show number of brick-and-mortar completions vs. number of online completions.
  • The CIP taxonomy is not intuitively organized; its classifications do not necessarily match up with the exact names of majors, and similar programs may not be found within the same six-, four-, or even two-digit series.
Inverse Staffing Patterns
A table of percentages that shows, on average, how regional occupations are divided up among regional industries. For example, a (simplified) inverse staffing pattern for registered nurses may show that 70% of RNs are employed…

A table of percentages that shows, on average, how regional occupations are divided up among regional industries. For example, a (simplified) inverse staffing pattern for registered nurses may show that 70% of RNs are employed by hospitals, 10% by local government (i.e., public schools), 10% by nursing homes, and 10% by offices of physicians. Inverse staffing patterns identify the industries currently employing this occupation, including those which are likely to be hiring due to growth or displacing workers due to contraction. See also Staffing Pattern.

Source: Primarily the national OES staffing pattern, combined with projections from the National Industry- Occupation Employment Matrix and Emsi’s proprietary employment data.

IRS Migration Data
IRS migration data is the foundation for the migration figures shown in Emsi's products. The data is based on tax returns filed and generally lags by a couple of years. The IRS's migration data can…

IRS migration data is the foundation for the migration figures shown in Emsi’s products. The data is based on tax returns filed and generally lags by a couple of years.

The IRS’s migration data can be found here.

Job
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…

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.

Emsi 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 Emsi data.

Source: Emsi 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).

Job Counts
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…

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 counts for future years are projected based on past trends. See this article for more on Emsi’s Projections.

Jobs Multipliers
A jobs multiplier indicates how important an industry is in regional job creation. A jobs multiplier of 3, for example, would mean that for every job created by that industry, 2 other jobs would be…

A jobs multiplier indicates how important an industry is in regional job creation. A jobs multiplier of 3, for example, would mean that for every job created by that industry, 2 other jobs would be created in other industries (for a total of 3 jobs).

Jobs multipliers are easily misinterpreted–jobs multipliers of 17 or higher are sometimes seen–but a high jobs multiplier for a set of one or more industries in an added-jobs scenario does not necessarily mean that attracting businesses in those industries to the region is the best of most viable option for regional economic growth.

Jobs multipliers are primarily tied to the type of industries in the scenario–industries with a high sales/labor ratio typically have a high jobs multiplier, and vice versa. For example, a nuclear power plant might have only 20 workers, but “behind” each of those workers there are millions of dollars of equipment costs and millions of dollars of electricity being generated. Thus, if we bring 20 more nuclear power jobs in to the region, it would involve a huge amount of investment flooding into the region (to build another nuclear power plant or double the size of the current one) and millions of dollars in new sales and profits.

Some of that money would go to the employees’ high salaries, some would go to local construction companies, real estate, janitorial services, etc. The overall jobs multiplier would be impressive–each new job in nuclear power might support 14 other jobs scattered throughout the rest of the economy (i.e. a jobs multiplier of 15). However, the effort it takes to attract 20 jobs in nuclear power (with all the necessary infrastructure) is substantially more than to attract 20 jobs in an industry with a lower jobs multiplier.

JPA
Job Posting Analytics.

Job Posting Analytics.

Labor Force
Labor force encompasses all employed individuals as well as individuals seeking jobs.

Labor force encompasses all employed individuals as well as individuals seeking jobs.

Labor Market Information (LMI)
Labor Market Information (LMI) is reported on two levels: traditional or government LMI, and real-time LMI. Traditional LMI is data about the labor market that is collected and published by public sources (such as the…

Labor Market Information (LMI) is reported on two levels: traditional or government LMI, and real-time LMI. Traditional LMI is data about the labor market that is collected and published by public sources (such as the Bureau of Labor Statistics, the U.S. Census, and the Bureau of Economic Analysis) for standardized industries and occupations. Real-time LMI is data taken from online job postings and profiles and is not governed by any one entity.

Learning Providers
Institutions of higher education, non-traditional training providers such as bootcamps, companies, and organizations that provide training for employers.

Institutions of higher education, non-traditional training providers such as bootcamps, companies, and organizations that provide training for employers.

LED
Local Employment Dynamics.

Local Employment Dynamics.

LEHD Origin-Destination Employment Statistics (LODES)
The Census's Longitudinal Employer-Household Dynamics (LEHD) program contains several datasets, one of which is the Origin-Destination Employment Statistics (LODES) dataset. This dataset further contains three parts: Origin Destination Residence Area Characteristics Work Area Characteristics These…

The Census’s Longitudinal Employer-Household Dynamics (LEHD) program contains several datasets, one of which is the Origin-Destination Employment Statistics (LODES) dataset. This dataset further contains three parts:

  • Origin Destination
  • Residence Area Characteristics
  • Work Area Characteristics

These three pieces together provide information on commuting patterns by 2-digit industry between census tracts.

Emsi uses them together to form the basis of Occupation by Residence data. Emsi also uses Workplace Area Characteristics (WAC) to help build the commuting data used in Emsi’s Input-Output model.

Source: Census Bureau 

Level
Attempts to score, between 1-100, the required level of knowledge, skill, or ability that is required of an occupation. Typically Importance and Level are similar, but there are cases such as a Registered Nurse’s knowledge…

Attempts to score, between 1-100, the required level of knowledge, skill, or ability that is required of an occupation. Typically Importance and Level are similar, but there are cases such as a Registered Nurse’s knowledge of medicine and dentistry. They usually require “65 out of 100” in terms of their level of knowledge, but the importance of having that knowledge is scored “91 out of 100.” They don’t need to know everything about the topic, but what they do need to know is very important to their job.

By comparing Level and Importance across all occupations, we can view similar occupations based on overlap between the two.

Source: O*NET Online

Local Area Unemployment Statistics (LAUS)
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. Emsi uses…

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.

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

Location Quotient (LQ)
Location quotient (LQ) is a way of quantifying how concentrated a particular industry, cluster, occupation, or demographic group is in a region as compared to the nation. It can reveal what makes a particular region…

Location quotient (LQ) is a way of quantifying how concentrated a particular industry, cluster, occupation, or demographic group is in a region as compared to the nation. It can reveal what makes a particular region “unique.” For example, if the leather products manufacturing industry accounts for 10% of jobs in your area but 1% of jobs nationally, then the area’s leather-producing industry has an LQ of 10. So in your area, leather manufacturing accounts for a larger than average “share” of total jobs—the share is ten times larger than normal.

For a long-form explanation of Location Quotient, see Emsi’s blog post on the subject.

Source: Emsi’s proprietary employment data.

Longitudinal Employer-Household Dynamics (LEHD)
The Longitudinal Employer-Household Dynamics program is part of the Center for Economic Studies at the U.S. Census Bureau. The LEHD program produces new, cost effective, public-use information combining federal, state and Census Bureau data on…

The Longitudinal Employer-Household Dynamics program is part of the Center for Economic Studies at the U.S. Census Bureau. The LEHD program produces new, cost effective, public-use information combining federal, state and Census Bureau data on employers and employees under the Local Employment Dynamics (LED) Partnership. Their mission is to provide new dynamic information on workers, employers, and jobs with state-of-the-art confidentiality protections and no additional data collection burden.

The Census’s Longitudinal Employer-Household Dynamics (LEHD) program contains several datasets, one of which is the Origin-Destination Employment Statistics (LODES) dataset. This dataset further contains three parts:

  • Origin Destination
  • Residence Area Characteristics
  • Work Area Characteristics

These three pieces together provide information on commuting patterns by 2-digit industry between census tracts.

Emsi uses them together to form the basis of Occupation by Residence data. Emsi also uses Workplace Area Characteristics (WAC) to help build the commuting data used in Emsi’s Input-Output model.

 

Source:  Census Bureau 

LPI
Local-Area Personal Income.

Local-Area Personal Income.

Make and Use Tables (MUTs)
The BEA produces Make and Use Tables (MUTs), which are the basis for Input-Output modeling in the United States. The make table is a matrix that describes the amount of each commodity made by each industry in a given year.…
The BEA produces Make and Use Tables (MUTs), which are the basis for Input-Output modeling in the United States. The make table is a matrix that describes the amount of each commodity made by each industry in a given year. The use table is a matrix that describes the amount of each commodity used by each industry in a given year. The tables are updated annually.
The MUTs are used in the Emsi Input-Output Model to produce an industry-by-industry matrix describing all industry purchases from all industries.

 

Median Household Income (MHI)
Median household income (MHI) refers to the distribution of household income into two equal groups, one having incomes above the median, and other having incomes below the median.   A household is defined as persons classified as…
Median household income (MHI) refers to the distribution of household income into two equal groups, one having incomes above the median, and other having incomes below the median.
 
A household is defined as persons classified as members of a married-couple family, other family type, or as an unrelated individual. Their monthly family income, therefore, represents the sum of all cash income received by the individual and/or other family members. It may represent income from employment, assets (such as CD’s, rental property, savings accounts), and other sources (such as Social Security, Aid to Families With Dependent Children, pensions , State unemployment compensation, and so on).
 

Emsi’s Median Household Income comes from the five year ACS data and includes data for individual counties, MSAs, States, and the nation. Emsi does not provide MHI when aggregating regions, since one cannot create a new median by averaging the medians of those individual regions. ACS five year data has a two-year lag between when the data is collected and when it is released (i.e. a late 2017 Emsi data run would include 2011-2015 ACS data).

Source: The Census’s Median Household Income

Metropolitan Statistical Area (MSA)
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,…

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.

Source: Census Bureau

Microcredential
A credential that reflects the mastery of knowledge and skills that is typically more narrow than traditional degrees, certificates, and certifications.

A credential that reflects the mastery of knowledge and skills that is typically more narrow than traditional degrees, certificates, and certifications.

Military Employment
Emsi's military employment counts include both active duty and Reserve military personnel. National Guard personnel are also included as they are a subset of the Reserves. Military employment is found in Emsi Class of Worker…

Emsi’s military employment counts include both active duty and Reserve military personnel. National Guard personnel are also included as they are a subset of the Reserves. Military employment is found in Emsi Class of Worker 2.

From the BEA’s SPI documentation: “The measure of employment of the military Reserves–including the National Guard–is confined to members of reserve units that meet regularly for training.”

Mix Effect
In shift share analysis, this reflects regional growth that can be attributed to positive trends in the specific industry or occupation at a national level. For example, nursing jobs might be growing in your region…

In shift share analysis, this reflects regional growth that can be attributed to positive trends in the specific industry or occupation at a national level. For example, nursing jobs might be growing in your region and that’s great. However, looking at the national trends for nursing jobs reveals that they’re growing most everywhere. In this case, your region isn’t necessarily “excelling” at providing nursing jobs; they’re doing well everywhere, and every region in the country will likely see some growth as a result.

The industrial mix effect is the number of jobs we would expect to see added (or lost) within an industry in your region, based on the industry’s national growth/decline. If the industry is growing or declining at the national level, it can dependably grow or decline in smaller regions.

Industrial mix effect is calculated by applying the job growth of the industry at the national level to the same industry at the regional level. We start by subtracting the national growth rate of the overall economy from the national growth rate of the specific industry. This gives us a national industry premium which is an indication of how much that industry outperformed or underperformed the economy as a whole nationwide.

Industry Growth Rate – National Economy Growth Rate = Industry Premium

This rate (a percentage) is then applied to the number of the industry’s regional jobs:

Industry Premium x Number of Regional Industry Jobs = Industrial Mix Effect

See this longer article on shift share and its component parts.

Multiplier
A multiplier is a way of measuring how important one industry is to other industries in the region. So if an industry has a multiplier of 2.5, for every positive or negative change on that…

A multiplier is a way of measuring how important one industry is to other industries in the region. So if an industry has a multiplier of 2.5, for every positive or negative change on that industry, the total effect on the regional economy will be 2.5 times the original change. Emsi’s multipliers are developed in-house through our proprietary Input-Output model, which uses Emsi’s final unsuppressed industry data, gravitational flows, commuting patterns, and the BEA’s “make and use” tables, among other sources.

National Center for Education Statistics (NCES)
The National Center of Education Statistics is the primary federal entity for collecting and analyzing data related to education in the U.S. and other nations. NCES is located within the U.S Department of Education and…

The National Center of Education Statistics is the primary federal entity for collecting and analyzing data related to education in the U.S. and other nations. NCES is located within the U.S Department of Education and the Institute of Education Sciences. NCES fulfills a Congressional mandate to collect, collate, analyze, and report complete statistics on the condition of American education; conduct and publish reports; and review and report on education activities internationally.

Source: NCES 

National Income and Product Accounts (NIPA)
NIPA is a set of tables produced by the Bureau of Economic Analysis (BEA). The NIPA tables cover a wide variety of economic measures for the nation. NIPA is updated periodically throughout the year and…

NIPA is a set of tables produced by the Bureau of Economic Analysis (BEA). The NIPA tables cover a wide variety of economic measures for the nation. NIPA is updated periodically throughout the year and can be between a month and several years old depending on the specific account.

Emsi uses NIPA data in the creation of the Input-Output Model. Specifically, it provides initial estimate values for the national model.

National Industry-Occupation Employment Matrix (NIOEM)
The Bureau of Labor Statistics publishes an industry-by-occupation employment matrix every two years as part of its Employment Projections program The BLS projects this matrix out 10 years into the future, essentially providing current and…

The Bureau of Labor Statistics publishes an industry-by-occupation employment matrix every two years as part of its Employment Projections program The BLS projects this matrix out 10 years into the future, essentially providing current and future staffing patterns.

Emsi uses NIOEM to adjust its industry projections.

Click here to read more about the BLS’s NIOEM dataset.

Natural Language Processing (NLP)
The use of computers to understand human language.

The use of computers to understand human language.

Net Commuters
Net Commuters is the difference between the occupational residents in a region and the occupational employment in a region. For a region in which more workers live than there are jobs in the region, net…

Net Commuters is the difference between the occupational residents in a region and the occupational employment in a region. For a region in which more workers live than there are jobs in the region, net commuting is negative (i.e. the net result is that workers commute out of the region for work). For a region in which there are more jobs than there are resident workers, net commuting is positive (i.e. the net result is that workers commute into the region for work).

Non-Employer Statistics (NES)
Non-employer Statistics is an annual series that provides subnational economic data for businesses that have no paid employees and are subject to federal income tax. The data consist of the number of businesses and total…

Non-employer Statistics is an annual series that provides subnational economic data for businesses that have no paid employees and are subject to federal income tax. The data consist of the number of businesses and total receipts by industry. Most non-employers are self-employed individuals operating unincorporated businesses (known as sole proprietorships), which may or may not be the owner’s principal source of income.

NES data informs Emsi’s self-employed (Class 3) and Extended Proprietor (Class 4) data.

Source: Census Bureau 

North American Industry Classification System (NAICS)
The North American Industry Classification System (NAICS) is the standard federal system for classifying business establishments. Each establishment is assigned a six-digit code and category title, organizing them primarily by similar production processes into five…

The North American Industry Classification System (NAICS) is the standard federal system for classifying business establishments. Each establishment is assigned a six-digit code and category title, organizing them primarily by similar production processes into five levels: sectors, subsectors, industry groups, industries, and national industries (national industries are specific to one or more of the United States, Canada, and Mexico). Codes are hierarchical: less detailed categories are derived by removing digits from the end of more detailed codes.

Example

  • 23: Construction (sector)
  • 236: Construction of Buildings (subsector)
  • 2362: Nonresidential Building Construction (Industry Group)
  • 23622: Commercial and Institutional Building Construction (industry)
  • 236220: Commercial and Institutional Building Construction (national industry which in this case is identical to its parent industry)

The NAICS classification is updated every five years to better reflect economic realities.

For information on Emsi’s use of NAICS codes (including departures from the standard classification), see this article.

See also: http://www.bls.gov/bls/naics.htm or http://www.census.gov/eos/www/naics/

Occupation
The term occupation refers to professions or careers in the workforce. In Emsi data, occupations are differentiated from jobs, as jobs show the count of positions held within a certain occupation. For example, Health Educators…

The term occupation refers to professions or careers in the workforce. In Emsi 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.

Occupation Earnings
Occupation earnings data comes from the BLS's OES dataset. It is collected from the employer's perspective, meaning earnings data is pre-tax (individual employees' tax withholdings will vary, so earnings are reported pre-tax). Because it is…

Occupation earnings data comes from the BLS’s OES dataset. It is collected from the employer’s perspective, meaning earnings data is pre-tax (individual employees’ tax withholdings will vary, so earnings are reported pre-tax). Because it is collected from the employer’s perspective, earnings data is also counted by the place of the employee’s work, not the employee’s residence. Occupations have average hourly earnings as well as percentile earnings for five percentiles (10th, 25th, 50th (median), 75th, and 90th).

Average earnings are determined by dividing the total earnings for the occupation by the number of jobs in the occupation. Percentile earnings indicate what percent of the jobs in the occupation earn that amount or less. For example, 10th percentile earnings of $12/hr. indicate that 10% of the workers in that occupation make $12/hr. or less. Median earnings of $15/hr. would mean that half of workers in that occupation make more than $15/hr., and half make less than $15/hr. 10th percentile earnings are often used as a proxy for entry level wages, as they represent some of the lowest earnings in the occupation.

Earnings are reported in terms of hourly income rather than annual income for all but a handful of occupations. For occupations with earnings reported annually, we divide by 2080 (number of hours in a working year) to determine hourly earnings.

Occupation earnings include the following:

  • Base rate
  • Commissions
  • Cost of living allowances
  • Deadheading pay
  • Guaranteed pay
  • Hazard pay
  • Incentive pay
  • Longevity pay
  • Over-the-road pay
  • Piece rates
  • Portal-to-portal rates
  • Production bonuses
  • Tips

Occupation earnings do not include the following:

  • Attendance bonuses
  • Back pay
  • Clothing allowances
  • Discount
  • Draw
  • Holiday bonus
  • Holiday premium pay
  • Jury duty pay
  • Meal and lodging payments
  • Merchandise discounts
  • Non-production bonuses
  • On-call pay
  • Overtime pay
  • Perquisites
  • Profit-sharing payments
  • Relocation allowances
  • Severance pay
  • Shift differentials
  • Stock bonuses
  • Tool/equipment allowances
  • Tuition repayment
  • Uniform allowance
  • Weekend premium pay
  • Year-end bonuses

OES provides definitions for all the categories listed above.

A Word about Percentile Earnings

Various reports within Emsi’s Analyst and Developer tools allow users to combine occupation percentile earnings for various occupations or regions. These combinations are powered by a proprietary occupation aggregation methodology that represents the combined wage curves of various occupations better than a weighted average. For this reason, users should not expect to be able to combine percentile earnings by hand and match combined percentile figures as displayed in Analyst. More information on Emsi’s occupation percentile earnings aggregation can be found here.

Source: Emsi’s proprietary employment data, relying heavily on occupational earnings reported in OES.

Occupational Employment Statistics (OES)
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…

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 1.2 million establishments and 62% of national employment, including railroad, but excluding military, agriculture, fishing, forestry, private households, self-employment, and others.

How Emsi 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.

Emsi 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 Emsi 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. Emsi’s occupation methodology (see article referenced above) is designed to counteract this weakness in OES data.
Occupational Information Network (O*NET)
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. Emsi incorporates this data throughout its tools in various…

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. Emsi incorporates 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.

O*NET updates do not follow a schedule; Emsi monitors O*NET for updates and downloads new data as it becomes available.

Source: O*NET

Occupational Programs
The programs in the region of study that may train for this occupation. Emsi uses a default crosswalk to build these associations; the occupations linked to a particular program may be edited from the program's…

The programs in the region of study that may train for this occupation. Emsi 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.

Other Vectors (I-O)
Also called "Other non-industries", this consists primarily of two non-industries that nonetheless capture genuine income-generating activity within the economy. Owner-Occupied Dwellings, which captures the activity of people who own and occupy their residences. For a…

Also called “Other non-industries”, this consists primarily of two non-industries that nonetheless capture genuine income-generating activity within the economy.

  1. Owner-Occupied Dwellings, which captures the activity of people who own and occupy their residences. For a further definition of Owner-Occupied Dwellings, see Appendix B of our Input-Output Model Documentation.
  2. Second are Government Enterprises, defined by the BEA as “Government agencies that cover a substantial portion of their operating costs by selling goods and services to the public and that maintain their own separate accounts.” This is accounted for at the Federal, State, and Local government level.

Source: Emsi’s Proprietary data, primarily from the Bureau of Economic Analysis (BEA)

Owner-Occupied Dwellings (OOD)
A housing unit is owner-occupied if the owner lives in the unit, even if it is mortgaged or not fully paid for. The owner or co-owner must live in the unit and usually is Person…

A housing unit is owner-occupied if the owner lives in the unit, even if it is mortgaged or not fully paid for. The owner or co-owner must live in the unit and usually is Person 1 on the questionnaire. The unit is “Owned by you or someone in this household with a mortgage or loan” if it is being purchased with a mortgage or some other debt arrangement such as a deed of trust, trust deed, contract to purchase, land contract, or purchase agreement. The unit also is considered owned with a mortgage if it is built on leased land and there is a mortgage on the unit. Mobile homes occupied by owners with installment loan balances also are included in this category.

Source: Census Bureau

Parsing
The process of analyzing a string of symbols, either in natural language, computer languages, or data structures, conforming to the rules of formal grammar, also known as syntax analysis or syntactic analysis.

The process of analyzing a string of symbols, either in natural language, computer languages, or data structures, conforming to the rules of formal grammar, also known as syntax analysis or syntactic analysis.

Population Estimates
The Census's Population Estimates Program produces estimates of the population of the United States. The latest US Decennial Census population figures are used as a base, and population change is estimated by modeling estimated births,…

The Census’s Population Estimates Program produces estimates of the population of the United States. The latest US Decennial Census population figures are used as a base, and population change is estimated by modeling estimated births, deaths, and migration. Population Estimates are released annually.

Emsi uses Population Estimates nearly unchanged in the years for which they are available as the basis for demographics counts for the nation, states, and counties.

Posting Intensity
Posting Intensity is the ratio of total to unique (deduplicated) job postings. A higher than average posting intensity can mean that employers are putting more effort than normal into hiring that position. Posting intensity is…

Posting Intensity is the ratio of total to unique (deduplicated) job postings. A higher than average posting intensity can mean that employers are putting more effort than normal into hiring that position. Posting intensity is available by occupation, by job title, by company, and by region.

Program
Emsi data uses the term program in reference to select courses offered at accredited colleges or universities. Programs are oriented toward a specific occupation, and completion of these programs is often signified by a specific…

Emsi data uses the term program in reference to select courses offered at accredited colleges or universities. Programs are oriented toward a specific occupation, and completion of these programs is often signified by a specific award level, such as Baccalaureate, Master’s, and Doctorate degrees.

Property Income/Profits (I-O)
Property Income, sometimes called “non-labor income” or “profits,” is generally what is left after businesses make payments for labor, taxes on production, and the purchase of produced inputs. Property income is one of the four…

Property Income, sometimes called “non-labor income” or “profits,” is generally what is left after businesses make payments for labor, taxes on production, and the purchase of produced inputs.

Property income is one of the four components of Gross Regional Product (GRP). The other elements are earnings (or labor income), taxes on production & imports, and subsidies.

Public Use Microdata Sample (PUMS)
The American Community Survey (ACS) Public Use Microdata Sample files are a set of untabulated records about individual people or housing units. The Census Bureau produces the PUMS files so that data users can create…

The American Community Survey (ACS) Public Use Microdata Sample files are a set of untabulated records about individual people or housing units. The Census Bureau produces the PUMS files so that data users can create custom tables that are not available through pretabulated (or summary) ACS data products.

Source: Census Bureau

Purdue Industry Clusters
The Purdue industry clusters were created through a joint project between Emsi and the Center for Regional Development at Purdue University.  These can be found by clicking Groups in the header bar and selecting Industry Groups, then Template Groups. Clusters…

The Purdue industry clusters were created through a joint project between Emsi and the Center for Regional Development at Purdue University.  These can be found by clicking Groups in the header bar and selecting Industry Groups, then Template Groups.

Clusters are groups of interconnected industries that typically purchase from one another or otherwise benefit from being nearby each other. Many different definitions exist for different clusters, and we encourage our clients to use their local knowledge when doing cluster analysis. The Purdue clusters can be used as is or you can create a new group based on a Purdue cluster and modify it to your local needs.

See this article on how to create a new group from a template group for more info.

Qualifications
In Emsi data, the term qualifications refers to the certifications decided on by a third-party entity (school, government, industry, etc.) that acknowledges a body of skills and abilities (e.g. MBA, Certified Registered Nurse). For example,…

In Emsi data, the term qualifications refers to the certifications decided on by a third-party entity (school, government, industry, etc.) that acknowledges a body of skills and abilities (e.g. MBA, Certified Registered Nurse).

For example, a job posting for a Registered Nurse may state that the qualifications for the position include a Bachelor’s of Science in Nursing from an accredited university and a nursing license from the state nursing board.

Quarterly Census of Employment and Wages (QCEW)
Quarterly Census of Employment and Wages (QCEW) is a dataset published by the Bureau of Labor Statistics (BLS). QCEW is the backbone of Emsi's core LMI data, providing establishment counts, monthly employment, and quarterly wages,…

Quarterly Census of Employment and Wages (QCEW) is a dataset published by the Bureau of Labor Statistics (BLS). QCEW is the backbone of Emsi’s 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 (national, State, and Metropolitan Statistical Area (MSA)).

Emsi produces a slightly modified form of the BLS QCEW dataset.

  • Emsi provides estimates for suppressed data (roughly 60% of QCEW data points are suppressed). For more on the importance of unsuppression, see this article.
  • Emsi alters the NAICS classification of public-sector employment to make it more compatible with other data sources. For more information, see this article.
  • Emsi 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.
Quarterly Workforce Indicators (QWI)
Quarterly Workforce Indicators (QWI) provides local labor market statistics by industry, worker demographics, employer age, and size. Unlike statistics tabulated from firm or person-level data, QWI source data is unique job-level data that link workers…

Quarterly Workforce Indicators (QWI) provides local labor market statistics by industry, worker demographics, employer age, and size. Unlike statistics tabulated from firm or person-level data, QWI source data is unique job-level data that link workers to their employers. Because of this link, labor market data in QWI is available by worker age, sex, educational attainment, and race/ethnicity. This allows for analysis by demographics of a particular local labor market or industry—for instance, identifying industries with aging workforces. Links between workers and firms also allow QWI to identify worker flows—hires, separations, and turnover—as well as net employment growth. (Since most hiring activity is the consequence of worker turnover rather than employment growth, a focus on employment growth alone may misrepresent employment opportunity in the local labor market.

How Emsi Incorporates QWI

Industry Demographics Data

Emsi uses QWI to create our detailed industry data, augmenting our regular employment data with QWI’s age/gender, and race/ethnicity demographics. After downloading individual state files, we prep QWI data through several steps.

First, we unsuppress QWI at its native level of industry detail (approximately 4-digit NAICS). Since QWI is compatible with QCEW, we then use QWI age/gender and race/ethnicity percentages to disaggregate our class of worker QCEW values, which are at 6-digit NAICS detail. However, we rely less heavily on QWI for creating detailed industry data for the remaining classes of worker (Non-QCEW, Self-Employed, and Extended Proprietors), preferring American Community Survey in these instances.

Hires

Emsi also uses industry hires data from QWI as the basis for occupational hires. Job growth for occupations in each industry are combined with Bureau of Labor Statistics (BLS) separations data to model the pattern of occupational hiring needs for each industry–the percent of openings in each industry that come from openings in each occupation. This percent breakout is then applied to the QWI industry hires figure, yielding occupation hires.

Strengths of QWI

  • QWI provides a unique link between individuals and employers
  • QWI helps distinguish actual employment opportunity from general employment growth in a given area
  • QWI allows for easy wage comparisons between new hires, continuing workers, and similar workers across various regions
  • QWI data is released quarterly and the numbers are recalculated with every release to improve accuracy
  • QWI is compatible with Quarterly Census of Employment and Wages, Emsi’s most important industry dataset

Weaknesses of QWI

  • QWI data is published at the 4-digit NAICS level rather than the 6-digit
  • QWI is produced on a quarterly schedule with a time lag of nine months (three quarters)
  • Like many public datasets, QWI contains many nondisclosed values that must be replaced with educated estimates
  • QWI does not distinguish between voluntary and involuntary separations

The Census’s QWI Explorer tool can be used to dig deeper into QWI data.

Race and Ethnicity
The federal government tracks several racial categories (White, Black or African American, Asian, etc.) but only two ethnic categories, Hispanic and Non-Hispanic. There may be some overlap between race and ethnicity unless the two characteristics…

The federal government tracks several racial categories (White, Black or African American, Asian, etc.) but only two ethnic categories, Hispanic and Non-Hispanic. There may be some overlap between race and ethnicity unless the two characteristics are clearly separated, e.g., “White non-Hispanic,” “White Hispanic,” and “Non-white Hispanic.”

Railroad Retirement Board (RRB)
Because the BLS's Quarterly Census of Employment and Wages (QCEW) dataset does not cover the railroad industry, Emsi uses supplemental data from the Railroad Retirement Board to supply job counts for the industry. This data…

Because the BLS’s Quarterly Census of Employment and Wages (QCEW) dataset does not cover the railroad industry, Emsi uses supplemental data from the Railroad Retirement Board to supply job counts for the industry. This data is published annually, usually in July. Job counts data does not contain suppressions, even at the county level.

Regional Matrix (I-O)
The Regional Matrix  (Z Matrix) is an 1800 by 1800 matrix that describes the spending from one sector of the regional economy to the other. It is part of the foundation for Input-Output Modeling. Emsi's Input-Output…

The Regional Matrix  (Z Matrix) is an 1800 by 1800 matrix that describes the spending from one sector of the regional economy to the other. It is part of the foundation for Input-Output Modeling. Emsi’s Input-Output model goes above and beyond the usual I-O model in that Emsi also models the changes to Occupations and Demographics. For further explanation, we recommend reading the Input-Output documentation available here.

Source: The Regional Matrix is primarily based on Emsi’s proprietary data and data from the Bureau of Economic Analysis (BEA).

Regional Requirements (I-O)
A table quantifying the goods and services that your region requires from each industry, as well as the degree to which those requirements are met within the region. For instance, if the regional requirements of…

A table quantifying the goods and services that your region requires from each industry, as well as the degree to which those requirements are met within the region. For instance, if the regional requirements of Seattle for Petroleum Refineries (324110) is $8.4B, that means that all of the industries in Seattle spend $8.4B on Petroleum Refineries. The table will also contain columns outlining how much of the $8.4B demand is satisfied in the region, and how much of the $8.4B must be purchased from outside the region to satisfy the remainder of demand. See also Industry Requirements.

Source: Emsi’s model, incorporating data from the BEA.

Remote Job Postings
The titles and bodies of all job postings are scanned for language indicating that the position is remote. This includes looking for phrases such as "work from home", "remote", "position can be located anywhere", and…

The titles and bodies of all job postings are scanned for language indicating that the position is remote. This includes looking for phrases such as “work from home”, “remote”, “position can be located anywhere”, and the like. Postings found to contain remote language are tagged as remote. Remote postings also includes positions that need to be located in a particular region but not in an office.

A detailed description of Emsi’s job postings methodology is available here.

Replacements
Replacements are jobs that will need to be filled by new hires due to existing workers leaving the occupation. Replacements are part of the Openings calculation. Openings = Replacements + Growth. For more information on…

Replacements are jobs that will need to be filled by new hires due to existing workers leaving the occupation. Replacements are part of the Openings calculation.

Openings = Replacements + Growth.

For more information on how Replacements are calculated, see Emsi’s methodology for Openings.

Resident Workers/Occupation by Residence Data
Unlike the majority of Emsi data, resident worker data is presented in terms of where workers live rather than where they work. For instance, though ZIP code 85042 might have 50 software developers working in…

Unlike the majority of Emsi data, resident worker data is presented in terms of where workers live rather than where they work. For instance, though ZIP code 85042 might have 50 software developers working in the region, there might only be 25 software developers who live there. This data is helpful in demonstrating workforce availability and helping companies locate the talent they need.

Source: This data comes from the Census’ LODES program and is most commonly used in their On The Map tool. Within the LODES dataset, Emsi makes particular use of the Origin and Destination (OD) data, Regional Area Characteristics (RAC), and Workforce Area Characteristics (WAC) data to produce occupation by residence data.

ROI
Return on Investment.

Return on Investment.

RPC
Regional Purchasing Coefficient.

Regional Purchasing Coefficient.

Sales (I-O)
In input-output modeling, Sales is an industry’s total annual sales (gross receipts), both to other industries and to consumers as well. Sales is representative of all four Classes of Worker. For the Retail (44), Wholesale (42),…

In input-output modeling, Sales is an industry’s total annual sales (gross receipts), both to other industries and to consumers as well. Sales is representative of all four Classes of Worker. For the Retail (44), Wholesale (42), and Transportation (48) sectors, sales are only inclusive of the respective margin.

Source: Emsi’s model, incorporating data from Bureau of Economic Analysis (BEA).

See also: Demand, How Do Demand and Sales Differ? 

Sales Multipliers
Sales multipliers show how “deeply-rooted” an industry is in your region—for example, a highly-developed cluster will have a high sales multiplier because every dollar fed into the cluster from the outside has a high ripple…

Sales multipliers show how “deeply-rooted” an industry is in your region—for example, a highly-developed cluster will have a high sales multiplier because every dollar fed into the cluster from the outside has a high ripple effect, propagating through the regional economy for some time before it leaks out. One dollar of sales coming into a highly-developed Automotive Manufacturing cluster, for example, might have a ripple effect of 2.8 (that dollar led to a total of $2.80 in regional sales). Industries and clusters with very low multipliers are usually owned outside of the region (so the profit is lost immediately) and also buy mostly from outside the region (a “shallow root system”).

Scraping
Web scraping is the process of gathering data from the internet, usually using automated bots or web crawlers. Emsi's job postings are scraped from company websites and job boards and aggregators. For more about how…

Web scraping is the process of gathering data from the internet, usually using automated bots or web crawlers. Emsi’s job postings are scraped from company websites and job boards and aggregators. For more about how Emsi scrapes job postings, see this article.

Search Engine Optimization (SEO)
Search Engine Optimization is often about making small modifications to parts of your website. When viewed individually, these changes might seem like incremental improvements, but when combined with other optimizations, they could have a noticeable…

Search Engine Optimization is often about making small modifications to parts of your website. When viewed individually, these changes might seem like incremental improvements, but when combined with other optimizations, they could have a noticeable impact on your site’s user experience and performance in organic search results.

Source: Google Support

Self-Employed
A self-employed individual directly offers their personal services to others in return for compensation, instead of earning an income from a business, corporation, or employer.

A self-employed individual directly offers their personal services to others in return for compensation, instead of earning an income from a business, corporation, or employer.

Separations
A separation is indicated when a job is present in one quarter, but is not present in the following quarter. A separation is reported by the Quarterly Workforce Indicators when an individual's Social Security Number…

A separation is indicated when a job is present in one quarter, but is not present in the following quarter.

A separation is reported by the Quarterly Workforce Indicators when an individual’s Social Security Number that appeared on a company’s payroll in the previous quarter is no longer present. Separations data is published at the industry level and modeled to occupation via staffing patterns. The QWI program produces a comprehensive tabulation of employment and wage information for workers covered by State unemployment insurance (UI) laws, similar to the QCEW program. For more information, see this publication.

Source: Census Bureau and Emsi’s proprietary employment data

Shift Share
Used in both industry and occupation contexts, Shift Share is a standard method of regional economic analysis that helps identify whether job change in an industry/occupation in a region is due to national factors--the "rising…

Used in both industry and occupation contexts, Shift Share is a standard method of regional economic analysis that helps identify whether job change in an industry/occupation in a region is due to national factors–the “rising tide lifts all boats” phenomenon–or whether it’s due to factors within the region of study itself.

An industry/occupation could be growing/declining in a region because of one or several of the following factors:

  • Growth Effect, the overall growth/decline of the entire national economy;
  • Industry/Occupation Mix Effect, the growth/decline of the industry/occupation in question at a national level;
  • Competitive Effect, growth/decline that cannot be explained completely by national trends and therefore highlights something unique about the region of study.

The most important of the three is Competitive Effect, which identifies region-specific factors as being responsible for the growth/decline of the industry/occupation in question.

Expected Change shows the expected growth/decline for the industry/occupation in region in question given the National Growth Effect and the Industry/Occupation Mix Effect. The Competitive Effect is the leftover effect (if any) that cannot be explained by the National Growth Effect and Industry/Occupation Mix Effects as shown in the Expected Change metric.

For a deeper dive into Shift Share, see this article.

Source: Emsi’s proprietary employment data.

Skill Shape
The unique skill demands associated with a given career field, region, or individual.

The unique skill demands associated with a given career field, region, or individual.

Skillify
Skillify (verb): to translate curricular content (e.g. course descriptions or syllabi) into the skill-based language of the modern labor market. In practical terms, “skillifying” your curriculum means identifying the work-relevant skills that you already teach,…

Skillify (verb): to translate curricular content (e.g. course descriptions or syllabi) into the skill-based language of the modern labor market.

In practical terms, “skillifying” your curriculum means identifying the work-relevant skills that you already teach, in the courses you already offer, and surfacing those skills to faculty, students, and other stakeholders.

Learn more about the significance of skill data for higher ed and the key advantages of a skillified curriculum.

 

Skills
In Emsi 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…

In Emsi 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.

Skills Cluster
A set of correlated skills that relate to a particular theme of work.

A set of correlated skills that relate to a particular theme of work.

Social Accounting Matrix (SAM)
A Social Accounting Matrix is a square matrix in which each account is represented by a row and a column. It provides a comprehensive picture of the economic transactions of an economy. Each cell shows…

A Social Accounting Matrix is a square matrix in which each account is represented by a row and a column. It provides a comprehensive picture of the economic transactions of an economy. Each cell shows the payment from the account of its column to the account of its row. Thus, the incomes of an account appear along its row and its expenditures along its column. For each account in the SAM, total revenue (row total) should be equal to total expenditure (column total).

Source: un.org

Staffing Pattern
Staffing patterns show the occupational makeup of an industry in percentages. For example, a (simplified) staffing pattern for the industry "Hospitals" might show that 10% of jobs in the hospitals industry are occupied by surgeons,…

Staffing patterns show the occupational makeup of an industry in percentages. For example, a (simplified) staffing pattern for the industry “Hospitals” might show that 10% of jobs in the hospitals industry are occupied by surgeons, 15% by general practitioners, 20% by nurses, 5% by information technology support staff, 5% by janitors, 1% by chief executives, and so on. See also Inverse Staffing Pattern.

Source: Primarily the national OES staffing pattern, combined with projections from the National Industry-Occupation Employment Matrix and Emsi’s proprietary employment data.

Standard Occupation Classification (SOC)
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…

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.

For more information on Emsi’s use of SOC codes (including departures from the standard classification), see this article.

Start Year
In the Timeframe in the toolbar this is the first year you’ve chosen. If your timeframe is 2008-2013, 2008 is your “start year.” See Timeframe and End Year.

In the Timeframe in the toolbar this is the first year you’ve chosen. If your timeframe is 2008-2013, 2008 is your “start year.” See Timeframe and End Year.

State and Local Government Finances
The Census's State and Local Government Finances dataset (also called Census of Government, COG) contains comprehensive information on local government finances. The data is updated annually, usually in September. Emsi uses State and Local Government…

The Census’s State and Local Government Finances dataset (also called Census of Government, COG) contains comprehensive information on local government finances. The data is updated annually, usually in September.

Emsi uses State and Local Government Finances data in the Input-Output model to aid in breaking out state and local data reported in the BEA’s Make and Use Tables.

State Personal Income/Local Area Personal Income (SPI/LPI)
The BEA's State Personal Income (SPI) and Local Area Personal Income (LPI) datasets contain primarily earnings data, but also include employment estimates. Emsi uses the SPI/LPI datasets primarily to provide earnings and employment estimates for…

The BEA’s State Personal Income (SPI) and Local Area Personal Income (LPI) datasets contain primarily earnings data, but also include employment estimates.

Emsi uses the SPI/LPI datasets primarily to provide earnings and employment estimates for various industries not covered in the QCEW Employees Class of Worker, most notably Military employment.

Suppression
Suppression refers to the practice of not disclosing ("suppressing") data points that can be traced back to a particular person or business in a particular location. Government entities suppress data points in data sets whenever…

Suppression refers to the practice of not disclosing (“suppressing”) data points that can be traced back to a particular person or business in a particular location. Government entities suppress data points in data sets whenever disclosing the data point in question would expose a business or individual.

Because Emsi’s mission is to drive economic prosperity in our clients’ communities, we provide the most accurate labor market data possible. Accurate LMI allows our clients to make informed decisions for the good of their communities. For this reason, we apply sophisticated unsuppression techniques to government LMI data, providing educated and bounded estimates for suppressed data points.

To read more on government suppression and the extent to which suppression can impact data, see our blog post.

Talent
In Emsi data, Talent indicates the workforce currently available to employers. Data for Talent supply comes from Traditional LMI, job postings, and professional profiles.

In Emsi data, Talent indicates the workforce currently available to employers. Data for Talent supply comes from Traditional LMI, job postings, and professional profiles.

Talent Growth Index (TGI)
Emsi's Talent Growth Index scores companies on a 0-100 scale where 100 signals top performing companies and 0 signals worst performing companies in the state within that 3-digit industry. There are three categories that comprise…

Emsi’s Talent Growth Index scores companies on a 0-100 scale where 100 signals top performing companies and 0 signals worst performing companies in the state within that 3-digit industry. There are three categories that comprise the Talent Growth Index: company postings, industry trends, and regional trends. The industry and regional trends compare change compared to the previous year. Company postings identify the most recent month of postings to the company’s 6 month rolling average.

This scoring was developed using a statistical model looking at 18 years of data to understand what metrics matter to company growth and how much each metric should be weighted. The model is both regionalized and unique to each industry. For instance an aerospace company in Washington will be scored differently than a aerospace company in Maryland. Similarly an aerospace company in Washington will be scored differently than a finance company in Washington.

Taxes on Production and Imports (TPI)
Taxes on production and imports (TPI) consist of state and local taxes—primarily non-personal property taxes, licenses, and sales and gross receipts taxes—and Federal excise taxes on goods and services. Special assessments are also included. To…

Taxes on production and imports (TPI) consist of state and local taxes—primarily non-personal property taxes, licenses, and sales and gross receipts taxes—and Federal excise taxes on goods and services. Special assessments are also included.

To see the tax implications of adding or removing 50 manufacturing jobs in Denver, TPI will measure the change in local, state, and federal tax revenue through the increased or decreased industry sales, specifically general sales and property taxes. It’s important to note that this change in tax revenue corresponds to the ripple effects and cannot be tied to a particular timeframe.

TPI is one of the four components of Gross Regional Product (GRP). The other elements are earnings (or labor income), profits/property income, and subsidies.

Source: Emsi’s model, incorporating data from the Bureau of Economic Analysis (BEA).

Timeframe
A timeframe is a period of study, defined by a start and an end year. In Emsi reports, users select timeframes for which they want to study data. Emsi provides data back to 2001 for…

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

Top Regional Businesses
The businesses in the selected industry with the most local employment according to DatabaseUSA, Emsi's provider of business-level data. DatabaseUSA's sources and methodology differ significantly from Emsi's, and some differences in NAICS classification can be…

The businesses in the selected industry with the most local employment according to DatabaseUSA, Emsi’s provider of business-level data. DatabaseUSA’s sources and methodology differ significantly from Emsi’s, and some differences in NAICS classification can be expected. Analyst lists the first 5 businesses as a convenience for all customers; detailed tables are available for an additional fee.

Source: DatabaseUSA

Total Earnings (I-O)
The total industry earnings for a region. Includes wages, salaries, supplements (additional employee benefits), and proprietor income. Total Earnings is one of the four components of Gross Regional Product (GRP). The other elements are profits/property…

The total industry earnings for a region. Includes wages, salaries, supplements (additional employee benefits), and proprietor income.

Total Earnings is one of the four components of Gross Regional Product (GRP). The other elements are profits/property income, taxes on production & imports, and subsidies.

Source: Emsi’s model, incorporating data from the Bureau of Economic Analysis (BEA).

Total Job Postings
Total Job Postings is the total and unduplicated number of online vacancies scraped from over 100,000 websites. Deduplication is the process of identifying duplicate job postings and only counting one of the duplicates. The total…

Total Job Postings is the total and unduplicated number of online vacancies scraped from over 100,000 websites.

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

Turnover Rate
Turnover rate gives context for how often employees in a given occupation are moving to different employers. Turnover rate is calculated by comparing total separations to total jobs (separations divided by jobs). A separation is…

Turnover rate gives context for how often employees in a given occupation are moving to different employers.

Turnover rate is calculated by comparing total separations to total jobs (separations divided by jobs). A separation is recorded when an individual’s Social Security Number that appeared on a company’s payroll is no longer present. By comparing separations to the total number of jobs in an occupation, we can benchmark the level of movement taking place in that occupation.

 

Typical Entry Level Education
The education level most often needed to enter an occupation. Typical entry-level education is reported at the national level, so alternate paths to employment may exist in a region of study. Source: BLS' Education and…

The education level most often needed to enter an occupation. Typical entry-level education is reported at the national level, so alternate paths to employment may exist in a region of study.

Source: BLS’ Education and training assignments by detailed occupation

Unclassified Industry
The Unclassified industry (999999) is used by Quarterly Census of Employment and Wages to categorize businesses who did not report a NAICS code. These are mostly newer businesses who have not yet determined their proper…

The Unclassified industry (999999) is used by Quarterly Census of Employment and Wages to categorize businesses who did not report a NAICS code. These are mostly newer businesses who have not yet determined their proper NAICS code. The BLS sends a special form to these businesses to help them determine their proper NAICS so that future reporting is improved.

Unclassified Occupation
The Unclassified occupation (99-9999) is a special SOC code Emsi uses for the Extended Proprietors class of worker (Class 4). The Unclassified occupation is used as an occupational bucket for industries that don't have self-employed…

The Unclassified occupation (99-9999) is a special SOC code Emsi uses for the Extended Proprietors class of worker (Class 4). The Unclassified occupation is used as an occupational bucket for industries that don’t have self-employed staffing patterns.

Underemployment
Underemployment data helps communities identify the portions of their population who are underutilizing their skills or time. There are three types of underemployment: Over-skilled Under-payed Low hour The underemployment data in the Economy Overview compares…

Underemployment data helps communities identify the portions of their population who are underutilizing their skills or time. There are three types of underemployment:

  • Over-skilled
  • Under-payed
  • Low hour

The underemployment data in the Economy Overview compares the educational attainment of the working age population (25+) to the number of jobs (25+) by typical entry level education in the region. 

Example

  • 15% of region A’s population has a high school diploma. 34% of jobs only require a typical entry level education of a high school diploma. This means that 19% of the region’s working age population would be over-skilled and have a higher degree than necessary for this jobs.

Sources:

  • Population educational attainment level by county (ACS data from the Census)
  • Typical entry level education by occupation (BLS)
Unemployed
An estimate of total unemployed persons by industry or occupation in a region. Emsi uses LAUS as the basis of its unemployment data, which uses a definition of unemployment roughly equivalent to U3, the most…

An estimate of total unemployed persons by industry or occupation in a region. Emsi uses LAUS as the basis of its unemployment data, which uses a definition of unemployment roughly equivalent to U3, the most widely used measure. Available by county for all 2-digit NAICS and 2-digit SOCs.

Source: LAUS, combined with CIU and Emsi’s proprietary employment data.

Unemployment Compensation for Federal Employees (UCFE)
The Unemployment Compensation for Federal Employees program provides benefits for eligible unemployed former civilian Federal employees. The program is administered by States as agents of the Federal government. This program is operated under the same…

The Unemployment Compensation for Federal Employees program provides benefits for eligible unemployed former civilian Federal employees. The program is administered by States as agents of the Federal government. This program is operated under the same terms and conditions that apply to regular State Unemployment Insurance. In general, the law of the State in which your last official duty station in Federal civilian service was located will be the State law that determines eligibility for unemployment insurance benefits.

Source: Department of Labor

Unemployment Insurance (UI)
The U.S. Department of Labor’s Unemployment Insurance programs provide unemployment benefits to eligible workers who become unemployed through no fault of their own, and meet certain other eligibility requirements. The following resources provide information about…

The U.S. Department of Labor’s Unemployment Insurance programs provide unemployment benefits to eligible workers who become unemployed through no fault of their own, and meet certain other eligibility requirements. The following resources provide information about who is eligible for these benefits and how to file a claim.

Source: Department of Labor

Unique Job Postings
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…

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.

USPS
United States Postal Service.

United States Postal Service.

Veteran Data
Emsi's veteran data comes from the five year 2015 ACS data and includes veteran counts by county for the United States. As defined by the ACS, veterans are men and women who have served (even…

Emsi’s veteran data comes from the five year 2015 ACS data and includes veteran counts by county for the United States.

As defined by the ACS, veterans are men and women who have served (even for a short time), but are not currently serving, on active duty in the U.S. Army, Navy, Air Force, Marine Corps, or the Coast Guard, or who served in the U.S. Merchant Marine during World War II. People who served in the National Guard or Reserves are classified as veterans only if they were ever called or ordered to active duty, not counting the 4-6 months for initial training or yearly summer camps.

ACS five year data has a two-year lag between when the data is collected and when it is released (i.e. late 2017 data run would include 2011-2015 ACS data). This data is typically updated during a late year data run.

Wages
Wages, which are sometimes referred to as compensation, are the total percentile earnings for the occupation divided by the number of jobs in the occupation in the region.

Wages, which are sometimes referred to as compensation, are the total percentile earnings for the occupation divided by the number of jobs in the occupation in the region.

Workforce
See Labor Force.

See Labor Force.

Workforce Investment Board (WIB)
Workforce Investment Boards direct federal, state, and local funding to workforce development programs. They also oversee the American Job Centers, where job seekers can get employment information, find out about career development training opportunities and…

Workforce Investment Boards direct federal, state, and local funding to workforce development programs. They also oversee the American Job Centers, where job seekers can get employment information, find out about career development training opportunities and connect to various programs in their area.

Source: data.gov

Zip Code Business Patterns (ZBP)
Emsi uses ZBP to model county-level data down to ZIP codes. ZBP provides establishment and employment counts that Emsi uses to create employment breakouts that are applied to county-level data. ZBP is released annually by…

Emsi uses ZBP to model county-level data down to ZIP codes. ZBP provides establishment and employment counts that Emsi uses to create employment breakouts that are applied to county-level data. ZBP is released annually by the Census as part of the County Business Patterns program.

ZIP-Code Tabulation Area (ZCTA)
ZIP Code Tabulation Areas are generalized areal representations of United States Postal Service (USPS) ZIP Code service areas. The USPS ZIP Codes identify the individual post office or metropolitan area delivery station associated with mailing…

ZIP Code Tabulation Areas are generalized areal representations of United States Postal Service (USPS) ZIP Code service areas. The USPS ZIP Codes identify the individual post office or metropolitan area delivery station associated with mailing addresses. USPS ZIP Codes are not areal features but a collection of mail delivery routes. The term ZCTA was created to differentiate between this entity and true USPS ZIP Codes. ZCTA is a trademark of the U.S. Census Bureau; ZIP Code is a trademark of the U.S. Postal Service.

Source: Census Bureau