CEW Data

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INTRODUCTION:

The 2018 Census of Employment and Wages (CEW) dataset is complete and now available to purchase in easy to use Excel files. Because of the level of detail and historic data available, the CEW data is perfect for establishing trends and running statistical analyses. The CEW data is useful for completing trend analyses and deep dives into U.S. wage and salary information. Drilling down into specified sector data allows for users to explicitly define the industry they wish to analyze at a granular level. 

 

PRODUCT DETAILS:

The Bureau of Labor Statistics collects a quarterly count of employment and wages across the U.S. called the Quarterly Census of Employment and Wages (QCEW). It uses data that is reported by employers covering more than 95% of jobs across the country. Data is then made available at the county, state, and national levels. 

The Bureau of Labor Statistics (BLS) releases CEW data, however there are certain non-disclosures within their data. The data contains employment, wages, and establishments in a given sector and area (down to the county level) and contains this information at the 6-digit NAICS level. This allows for even greater detail in specific modeling scenarios. IMPLAN adds value by filling in these non-disclosures based on existing data to be able to provide a complete picture.

The CEW data is available for 2001 to current IMPLAN data year (2018). IMPLAN refreshes these every five years as part of the panel data process, which is currently underway. The CEW data are for counties and up (including Puerto Rico and its municipios). The CEW data contains a Read Me file with additional information.

 

DATA DELIVERY & SUPPORT:

The data will be provided in .xlsx files containing the CEW data for the requested years. Users will have unlimited access to IMPLAN Community Forum at support.implan.com for questions specific to the data. IMPLAN economists will gladly respond to questions on IMPLAN’s Community forum within 5 business days at no additional charge. IMPLAN does not support data-application or related questions via email, phone, project consultation, or community forum.

To learn more about IMPLAN CEW Data, please contact IMPLAN at 800-507-9426 or sales@implan.com.

 

LICENSE AGREEMENT:

Access to the IMPLAN CEW Data is protected with a custom license agreement.  The license agreement will be presented when you are ready to purchase data. Sorry, the lawyers make us do it.

 

RELATED ARTICLES:

CEW FAQ

 

BLOG:

New CEW Data Available Now

 

WEBINAR:

Occupational Matrices: Occupational Employment and Compensation by Industry

2018 U.S. Territories Data Release Notes

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INTRODUCTION:
IMPLAN has data for the five Island territories of the U.S. We have data on American Samoa (AS), Commonwealth of Northern Marianas Islands (MP), Guam, (GU), Puerto Rico (PR), and Virgin Islands (VI). Note that the data sets for Island Areas are not nearly as comprehensive nor timely compared to the U.S., unfortunately. The 2018 U.S. Territories data contain two significant additions.

2018 UPDATES:
PROPRIETOR EMPLOYMENT ESTIMATES
While prior U.S. territories data has included estimates of proprietor income (PI), proprietor employment was not included as part of a given industry’s employment value (unlike IMPLAN U.S. data). The decision to not include proprietor employment was a conservative one made due to a lack of data on U.S. territory proprietors. However, proprietor estimates, derived using U.S. level sector-specific rates of proprietors-per-PI, are included this year to promote definitional consistency with labor income, which includes both wage and salary income and proprietor income.

Employment overall is up, which is expected with the inclusion of proprietor employment. Those sectors seeing the largest jump in employment will be those with a higher rate of proprietors-per-PI at the U.S. level, which generally equates to those sectors with a larger proportion of proprietor employment (e.g., agriculture sectors, personal services sectors, etc.).

IMPROVED GOVERNMENT SECTOR DISTRIBUTIONS
U.S. Territories data now mimics IMPLAN’s domestic data production in the use of BLS CEW ownership codes to derive government employment and wages data for IMPLAN sectors beyond just administrative payroll for education and non-education. For Puerto Rico (PR) and Virgin Islands (VI), both of which are covered by CEW, ownership code data provide employment and wage data for additional government activities such as passenger transit, electric utilities, and other government enterprises, along with continued employment and wage data for government administrative sectors. For territories lacking BLS CEW coverage, PR and VI CEW data are used to estimate these new distributions of total non-education government employment and wages between non-education administrative government and the government enterprise sectors (passenger transit, electric utilities, and other government enterprises).

With the 2018 data, you will now see non-zero estimates for government sectors that were previously zero. These include passenger transit, electric utilities, and other government enterprises.

DATA DELIVERY & SUPPORT:
U.S. Territories data is utilized only in IMPLAN Pro and provided in .odf form (i.e., similar to international models, but the U.S. Territories data utilizes the same Structural Matrix as the domestic data). No Journey to Work (JTW) or Trade Flow files are included. The Industry scheme is identical to that used for IMPLAN Pro domestic data and contains 544 Industries.
To learn more about our data on U.S. Territories, please contact IMPLAN at 800-507-9426 or sales@implan.com.

Canadian Data Products

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IMPLAN has released the 2012 Canadian Total File as well as Provincial level data. These IMPLAN data sets are based on the 2012 Statistics Canada data and have 103 sectors. Updated data at the national level is available using OECD data (rather than based on StatCan data.)

The Canadian data sets are not able to be aggregated, as each Provincial data file has a separate Structural Matrix. Each Province needs to have a separate model built. The current Canadian Provinces are not MRIO compatible for the same reason that the regions are not able to be aggregated.

While the data files are not downloadable, once your order is placed an IMPLAN support agent will call you to arrange the transfer of the data files.

CANADIAN PROVINCIAL LEVEL DATA
Alberta British Columbia
Manitoba Yukon
Saskatchewan Newfoundland
New Brunswick Northwest Territory
Quebec Nunavut
Nova Scotia Ontario
Prince Edward Island

SECTOR DESCRIPTIONS
Crop and Animal Production Forestry and Logging Fishing, hunting and trapping Support activity for agriculture and forestry
Oil and gas extraction Coal mining Metal ore mining Non-metallic mineral mining and quarrying
Support activities for mining and oil and gas extraction Electric power generation, transmission and distribution Natural gas distribution, water, sewage and other systems Residential building construction
Non-residential building construction Engineering construction Repair construction Other activities of the construction industry
Animal food manufacturing Sugar and confectionery product manufacturing Fruit and vegetable preserving and specialty food manufacturing Dairy product manufacturing
Meat product manufacturing Seafood product preparation and packaging Miscellaneous food manufacturing Soft drink and ice manufacturing
Breweries Wineries and distilleries Tobacco manufacturing Textile and textile product mills
Clothing and leather and allied product manufacturing Wood product manufacturing Pulp, paper and paperboard mills Converted paper product manufacturing
Printing and related support activities Petroleum and coal product manufacturing Petroleum and coal product manufacturing Resin, synthetic rubber, and artificial and synthetic fibers and filaments manufacturing
Pesticide, fertilizer and other agricultural chemical manufacturing Pharmaceutical and medicine manufacturing Miscellaneous chemical product manufacturing Plastic product manufacturing
Rubber product manufacturing Non-metallic mineral product manufacturing (except cement and concrete products) Cement and concrete product manufacturing Primary metal manufacturing
Fabricated metal product manufacturing Machinery manufacturing Computer and peripheral equipment manufacturing Electronic product manufacturing
Electrical equipment and component manufacturing Household appliance manufacturing Motor vehicle manufacturing Motor vehicle body and trailer manufacturing
Motor vehicle parts manufacturing Aerospace product and parts manufacturing Railroad product and parts manufacturing Ship and boat building
Other transportation equipment manufacturing Furniture and related product manufacturing Miscellaneous manufacturing Wholesale trade
Retail trade Air transportation Rail transportation Water transportation
Truck transportation Transit, ground passenger and sightseeing, and support activities for transportation Pipeline transportation Postal service and couriers and messengers
Warehousing and storage Motion picture and sound recording industries Radio and television broadcasting Publishing, pay/specialty services, telecommunications and other information services
Depository credit intermediation and monetary authorities Insurance carriers Lessors of real estate Owner-occupied dwellings
Rental and leasing services and lessors of non-financial intangible assets Other finance, insurance and real estate services and management of companies and enterprises Legal, accounting and architectural, engineering and related services Computer systems design and other professional, scientific and technical services
Advertising, public relations and related services Administrative and support services Waste management and remediation services Educational services
Health care and social assistance Arts, entertainment and recreation Accommodation and food services Repair and maintenance
Personal services and private households Professional and similar organisations Non-profit education services Non-profit social assistance
Non-profit arts, entertainment and recreation Religious organizations Miscellaneous non-profit institutions serving households Public educational services (except universities)
Public universities Public hospitals Public nursing and residential care facilities Other federal government services
Other provincial and territorial government services Other municipal government services Other aboriginal government services

International OECD Data Sets

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INTRODUCTION:
IMPLAN now has data for the Organization for Economic Co-Operation and Development (OECD) countries. IMPLAN OECD data covers 35 countries with 37 Industries and corresponding Commodities. The model is created based on OECD 2015 Input-output table at basic prices.

Final Demand includes:

Final consumption expenditure of households
Final consumption expenditure of non-profit institutions serving households (NPISH)
Final consumption expenditure of general government
Gross fixed capital formation
Changes in inventories
Value added components include:

Employee Compensation
Net Taxes on Products
Gross Operating Surplus
Other Taxes less than Other Subsidies on Production

OECD COUNTRY LIST:
Argentina Colombia Korea Saudi Arabia
Australia Costa Rica Malaysia Singapore
Brazil Hong Kong Mexico South Africa
Brunei Darussalam Iceland Morocco Switzerland
Cambodia India New Zealand Thailand
Canada Indonesia Norway Tunisia
Chile Israel Peru Turkey
China Japan Philippines Vietnam
Chinese Taipei Kazakhstan Russian Federation

LIST OF INDUSTRIES:
Agriculture, forestry and fishing Fabricated metal products, except machinery and equipment Telecommunications
Mining and extraction of energy producing products Computer, electronic and optical products IT and other information services
Mining and quarrying of non-energy producing products Electrical equipment Financial and insurance activities
Mining support service activities Machinery and equipment n.e.c. Real estate activities
Food products, beverages and tobacco Motor vehicles, trailers and semi-trailers Other business sector services
Textiles, wearing apparel, leather and related products Other transport equipment Public administration and defense; compulsory social security
Wood and of products of wood and cork (except furniture) Other manufacturing; repair and installation of machinery and equipment Education
Paper products and printing Electricity, gas, water supply, sewerage, waste and remediation services Human health and social work
Coke and refined petroleum products Construction Arts, entertainment, recreation and other service activities
Chemicals and pharmaceutical products Wholesale and retail trade; repair of motor vehicles Private households with employed persons
Rubber and plastics products Transportation and storage Intermediate Taxes on Products
Other non-metallic mineral products Accommodation and food services
Manufacture of basic metals Publishing, audiovisual and broadcasting activities

To learn more about this data, please contact IMPLAN at 800-507-9426 or sales@implan.com.

Trade Flow Data

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INTRODUCTION:
Have you ever wanted to take a peek at IMPLAN’s Trade Flow data? Have you been curious about the details of IMPLAN’s Gravity Model and Trade Flow RPCs? Then this might be the place for you!

IMPLAN’s domestic Trade Flow data set is comprised of county-to-county dollar values of domestic trade in all IMPLAN commodities (including services). The data are estimated via a doubly-constrained gravity model. The trade captured by this dataset is for both intermediate and final uses, and includes trade within a county (a county to itself). Cool right?

PRODUCT DETAILS:
The gravity model was originally adapted from Newton’s Law of Gravity! This law states that the attraction between two masses is directly related to the size of the masses and inversely related to the distance between them. The gravity model was first suggested in an I-O context in Leontief and Strout (1963). In the last fifty years, the gravity model has been widely used to predict trade flows (Federal Highway Administration, 1977, p. 118; Anderson and van Wincoop, 2003; Anderson, 2011).

In 2005, IMPLAN, in concert with the U.S. Forest Service, developed a sophisticated doubly-constrained (until all supplies go somewhere and all demands are fulfilled) gravity model to estimate trade flows for all IMPLAN commodities between all counties in the U.S. These Trade Flows show the movement of goods and services between and within counties or user-defined regions made up of counties. .

A key aspect of the data set is that the trade is on an origin-of-production basis, not an origin-of-movement basis. This means that the data set tracks from where a Commodity is produced to where it is consumed as either an intermediate or final use rather than from where a Commodity begins its export journey.

DATA SOURCES:
Each year, the IMPLAN database is used to create the attracting masses (supply and demand) for each U.S. county and each Commodity. These county masses are combined with distances (cost of transport indexes) between and within counties by mode of transport from Oak Ridge National Laboratory’s (ORNL) Transportation Network. The model is calibrated using distances traveled by Commodity from the most recent Commodity Flow Survey (CFS).

DATA DELIVERY & SUPPORT:
Data is delivered as a SQL .bak file or a .csv file. These files contain a single table with all county-county pairs and all Commodities. In this table, the counties are indexed from 1 to 3141 with no associated FIPS codes. A bridge table is included to match the county index to the appropriate FIPS code.

READY TO MODEL:
To learn more about purchasing our Trade Flow data, please contact IMPLAN at 800-507-9426 or sales@implan.com.

RESOURCES:
Anderson, J.E. and E. van Wincoop. 2003. Gravity with Gravitas: A Solution to the Border Puzzle. The American Economic Review, 93(1): 170- 192, March.

Anderson, J.E. 2011. The Gravity Model. Annual Review of Economics, Volume 3: 133-160.

Commodity Flow Survey (CFS)

Federal Highway Administration. 1977. Computer Programs for Urban Transportation Planning.

IMPLAN’s Gravity Model and Trade Flow RPCs

Leontief, W. and A. Strout. 1963. “Multiregional Input-Output Analysis.” In Barna (ed.), Structural Interdependence and Economic Development, London: Macmillan (St. Martin’s Press), pp. 119-149.

Oak Ridge National Laboratory (ORNL)

Environmental Data

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INTRODUCTION:

IMPLAN has three core values: community, respect, and stewardship. The goal of being good stewards has taken us beyond examining only the economic impacts associated with changes in production to examining some of the environmental impacts associated with current and projected levels of production. Working with the U.S. Environmental Protection Agency (EPA), IMPLAN has bridged their emissions data to our Industries, thereby tying economic impacts to environmental impacts!  

 

PRODUCT DETAILS:

IMPLAN’s environmental data consist of Industry-specific coefficients of physical emissions or resource use per dollar of Industry Output. These ratios can be applied to the IMPLAN modeling system in order to gain insight into the environmental impacts associated with economic impact scenarios. The data also allows for the comparison of environmental footprints across geographies or over time.

The coefficients are Industry-specific, but the EPA data have somewhat less Industry-specificity than the IMPLAN data, such that some EPA ratios are mapped to more than one IMPLAN Industry.  In other words, some IMPLAN Industries have the same coefficients . 

The coefficients do not double count in that they do not include the emissions associated with the upstream industries/suppliers. For example, the emissions associated with the car manufacturing Industry do not include emissions associated with the production of car parts or other inputs produced by other Industries; the emissions associated with producing those inputs would be accounted for in the coefficients for those suppliers’ respective Industries. 

Any emissions generated directly by households (those not accounted for by household expenditures on electricity and not associated with the production of other items purchased by households) – for example, emissions generated by households’ burning of wood in a wood-fired stove in the home – are not included in the EPA dataset. Therefore, they are not accounted for in the IMPLAN emissions data set.  What this means is that all induced emissions in IMPLAN stem from household purchases of energy and of goods and services, all of which require energy to produce and thus create emissions. Any additional emissions generated directly by the household, those not associated with a purchase of energy, goods, or services, will not be accounted for.  

The coefficients are national-based.  The EPA is working on state-level data, which we plan to incorporate into subsequent iterations of the IMPLAN environmental data. Stay tuned.

 

DATA SOURCE:

IMPLAN’s environmental ratios are sourced from the U.S. EPA’s Environmentally-Extended Input-Output model (EEIO) data and the methodology put forth by Yang, Ingwersen, Hawkins, Srocka, and Meyer (2017). The data represented falls into 8 broad categories. Within these categories, tags are assigned to represent more specific types of each category. 

The categories are:

  • Criteria Pollutants
    • 267 tags
    • Examples: Nitrogen Oxides, Chromium III, Cellosolve Solvent
  • Greenhouse Gas Emissions
    • 15 tags
    • Examples: CO2, N2O, CH4, CF4
  • Land Use
    • 220 tags
    • Examples: Urban Land, Urban Transportation, Rural Transportation, Coal Exploration Licenses
  • Mineral Use
    • 5 tags
    • Examples: Boron, Gypsum, Salt
  • Nitrogen and Phosphorus Release to Water
    • 2 tags
    • Includes: N and P
  • Pesticide Emissions
    • 747 tags
    • Examples: Spirodiclofen/air, Norflurazon/water, Fluxapyroxad/groundwater
  • Toxic Chemical Releases
    • 408 tags
    • Examples: 1,2-Dichloropropane, 1,2-Phenylenediamine, 1,3-Butadiene
  • Water Use
    • 247 tags
    • Examples: Alpacas; On-farm surface source, Alpacas; surface water, Aquaculture; groundwater

 

DATA DELIVERY & SUPPORT:

Until the data are available in the IMPLAN application, the data will be provided in a .csv file containing the coefficients for each IMPLAN Industry. To analyze an environmental impact, one would take the industry Output figures from IMPLAN and multiply them by the coefficients from the environmental data. It’s as easy as that.

Users will have unlimited access to IMPLAN Community Forum at support.implan.com for questions specific to the bridging of the EPA data to IMPLAN Industries.  We can also refer users to the EPA for any questions regarding the calculation of their coefficients. IMPLAN economists will gladly respond to questions on IMPLAN’s Community forum within 5 business days at no additional charge. IMPLAN does not support data-application or related questions via email, phone, project consultation, or community forum.

 

LICENSE AGREEMENT:

Access to the IMPLAN Environmental Data is protected with a custom license agreement.  The license agreement will be presented when you are ready to purchase data. Sorry, the lawyers make us do it.

 

SAMPLE DATA:

Sample Environmental Data

 

GO GREEN:

To learn more about our environmental data, please contact IMPLAN at 800-507-9426 or sales@implan.com.

 

RESOURCES:

Ingwersen, W. An Introduction to USEEIO. The Strategic Analysis team for the Advanced Manufacturing Office, Cincinnati, OH, December 06, 2018. 

Yang, Y., W.W. Ingwersen, T.R. Hawins, M. Srocka, and D.E. Meyer, 2017. USEEIO: A new and transparent United States environmentally extended input-output model. Journal of Cleaner Production, 158: 308-318.

546 Industry Scheme

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INTRODUCTION:

The 2018 data is now the default year in IMPLAN! The data release this year is especially exciting because we have a brand new Industry scheme with 546 Industries based on the updated BEA Benchmark and Census of Agriculture.

The new Industry scheme obviously has some changes from the 536 Industry scheme. We only lost three Industries due to disaggregation. Notably, wholesale trade has been split into 10 different wholesale Industries. Insurance carriers is now split into direct life and all others. Real estate is now split into tenant-occupied and other real estate. Finally, at both the local and state levels, the non-education spending pattern will be split into hospitals and health services and other services. Details on the changes can be found in the article BEA Benchmark & The New 546 Industry Scheme.

 

COMPARING DATA ACROSS TIME:

Compare data across time (2001 – 2018) in IMPLAN, using the most up-to-date Industry Scheme!

When there are significant changes to the underlying data, there is no longer an apples to apples comparison. Therefore, you will not be able to compare data sets, Projects or Event Templates in the 536 Industry scheme (or another) non-546 Industry scheme) with the new 546 Industry scheme. 

For comparing across different Industry Schemes, we have a bridge that should help in most instances. 

The 2018 data and the 546 Industry Scheme is the default on your Regions screen. The Regions screen will show you data from 2001-2018 in the 546 Industry Scheme. 

time_series.png

 

FINDING OLDER DATA:

To find the older data years (2012-2017), navigate from your home screen to the Projects screen.  On the Projects screen, click the NEW PROJECT button in the upper right.

 

New_Project.jpg

 

In the pop-up box, give your new Project a title and then in Industry Set, choose “US – 536 Sectors.” Then ensure that your Household Set is “Set 1 – (2015 Datasets or later).” This will give you the choice on your Regions screen between 2015, 2016, and 2017 datasets.  To find data from 2012-2014, choose “Set 2 – (2014 Datasets or earlier).”

 

 546_Sectoring_Scheme_-_Finding_2017.jpg

 

Click CREATE PROJECT and you will be taken to your Regions screen to set up as always!

 

New_Project_-_Create_Project_Button.jpg

 

 

RELATED TOPICS:

2018 Data Release Notes

546 Industries, Conversions, Bridges, & Construction – 2018 Data

BEA Benchmark & The New 546 Industry Scheme

IMPLAN Sectoring & NAICS Correspondences

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INTRODUCTION:

Sectors are a way of describing your Industry. All versions of the Sectoring schemes (except the 528) are based on NAICS codes but represent differing levels of NAICS code rollups. Generally speaking, manufacturing Sectors are 4-5 digit NAICS; whereas, agriculture and services are 3-4 digit NAICS. Choosing the correct Sector is vital to an accurate analysis.

 

DETAILS: 

The Sectoring schemes represent rollups of NAICS descriptions, and each Sector has its own spending pattern derived from the BEA expenditures patterns. To see what NAICS codes and descriptions are associated to a particular Sector, you can start typing the words in the Sector directly into the Specification box on the Impacts screen.

Type in a keyword to pull up associated descriptions. Note that subsets of words will also be displayed, so for example the word “wine” will also bring up twine. Curiously, plurals are not always recognized, so if you type in “books” but do not receive fields related to your search try “book“. Alternatively, in our downloads section are spreadsheets that provide NAICS code descriptions and IMPLAN Sector bridges.

One other key element to keep in mind when selecting a Sector is that the Sector also contains the representative ratios of Intermediate Expenditures:Value Added and the Value Added ratios for that Industry in that Study Area. For all these reasons it is very important to ensure that your Sector represents the Industry you are modeling. If you have a line-item budget and want to create your own Sector, please see the section on Analysis-by-Parts (ABP).

Please note also that in data sets prior to 2012 there are no NAICS 23* correspondences, and while descriptions are included in 2012 forward, there are no corresponding IMPLAN Sector Codes because our construction Sectors come from Census rather than NAICS. Please see related articles for this and other information about special Sectors in the IMPLAN Sectoring scheme.

 

USAGE: 

Below is the current (2018 data) IMPLAN Sectoring scheme. Manual bridges can be found in the article 546 Sector Industries, Conversions, Bridges, & Construction – 2018 Data.  

 

546 SECTORING SCHEME (2018)

Special Sector Definitions

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INTRODUCTION:

Certain IMPLAN Sectors require additional explanation, either because they are not NAICS based or they have special properties. Below are the special Sector descriptions (sector numbers are based on the 546 sector scheme for 2018 IMPLAN data sets).1

 

SECTORS 50-59: CONSTRUCTION

IMPLAN construction Sectors are classified by structure type (Census definitions) rather than NAICs codes. For this reason, Sector searches for construction will not pull up corresponding IMPLAN Sectors. Thus, when working with Construction Sectors, the Definitions of IMPLAN’s 546 Construction Sectors can be helpful.

 

SECTOR 449: OWNER-OCCUPIED DWELLINGS

This Sector estimates what owner/occupants would pay in rent if they rented rather than owned their homes. This Sector creates an industry out of owning a home, and its production function represents repair and maintenance of that home. The Sector’s sole product (Output) is ownership and is purchased entirely by personal consumption expenditures (i.e., the household Sector).

There is no Employment or Employee Compensation for this industry. Taxes on production for this Sector are largely made up of property taxes paid by the homeowner, while Other Property Income is the difference between the rental value of the home and the costs of home ownership. Interest payments and mortgage payments are a transfer in the SAM and are not part of the production function for this Sector.

Sector 449 is included in the database to insure consistency in the flow of funds. It captures the expenses of home ownership such as repair and maintenance construction, various closing costs, and other expenditures related to the upkeep of the space in the same way expenses are captured for rental properties.

 

SECTOR 525: PRIVATE HOUSEHOLDS

While not a true special Sector, there are often many questions regarding what Sector 525 produces. This sector covers live-in household staff: maids, butlers, chauffeurs, etc. 

 

SECTORS 526-534: GOVERNMENT ENTERPRISES

IMPLAN Sectors 526-534 represent government agencies that cover a substantial portion of their operating costs by selling goods and services to the public. They operate much like private sector firms, hiring labor and purchasing other inputs to produce goods that are sold through markets. Other Federal\State\Local government enterprises (i.e., those other than postal, electric utility, and transportation services) include things such as government owned and operated liquor stores, airports, sewer and sanitation services, gas, and water supply2. This differs from Administrative Government sectors (components of consumption – i.e., final demand), because administrative do not respond to local market demands.

 

SECTORS 535-538: COMMODITY ONLY SECTORS

IMPLAN Sectors 535-538 are Commodities not produced intentionally by any US industry:

  • Used and secondhand goods are goods that are traded but were not produced during the current year. While used goods are not part of the current-period gross output of the economy, they are part of the supply available for consumption. They come from capital, government institutions, and households.
  • Scrap consists of commodities that are cast off as part of a production process and then resold. Examples include sales of used aluminum cans to recyclers and sales of scrapped vehicles to metal recyclers.
  • Rest of world adjustment  “The rest-of-the-world adjustment to final uses consists of values for exports and imports that have offsetting adjustments to personal consumption expenditures (PCE) and government… This adjustment is required in order to conform the commodity treatment of the I-O use table to the expenditure concepts used for final uses in the NIPAs. This is accomplished by making offsetting adjustments between PCE and gross exports and between Federal Government nondefense purchases and exports and imports…For example, foreigners traveling in the United States consume goods and services, such as accommodations, that are included in the source data for PCE. In order to put the PCE estimate on a NIPA basis, an adjustment is made to account for these purchases.”3
  • Non-comparable foreign imports are goods that are not available anywhere in the nation. They consist of three types of services: (1) services that are produced and consumed abroad, such as airport expenditures by U.S. airlines in foreign countries; (2) service imports that are unique, such as payments for the rights to patents, copyrights, or industrial processes; and (3) service imports that cannot be identified by type, such as payments by U.S. companies to their foreign affiliates for an undefined basket of services.

 

SECTORS 539-546: ADMINISTRATIVE PAYROLL SECTORS

Administrative government activities (e.g., legislatures, police protection) are not subject to local market forces (i.e., not driven by local demand); as such, they are held exogenous to the multiplier model.

IMPLAN Sectors 539-546 represent the payroll/value added of these administrative government Sectors. This is necessary because, while the Commodity purchases of these government institutions are already represented in the SAM, there is no payroll Commodity; thus, these Sectors are included as a bookkeeping element to account for these institutions’ payrolls. By definition, these Sectors have no intermediate purchases and thus will not generate indirect effects. For these sectors, Employee Compensation or Employment should be used as Event values; entering the operational value of the government as an Output value will greatly overestimate the impact. When modeling government programs or budgets, you will need to use the appropriate spending pattern associated to the budget activity. 

 

NON-SECTORS: GOVERNMENT INSTITUTIONS

Government Institutions in IMPLAN do not have Sector designations. Instead, they can be modeled from the Impacts screen using an Institutional Spending Pattern Event. For details on how to edit and use these, visit Editing Institutional Spending Pattern Events. The following governmental spending patterns are available.

  • Federal Government
    • NonDefense
    • Defense
    • Investment
  • State/Local Government
    • NonEducation
    • Education
    • Investment
  • Capital
  • Inventory Additions/Deletions

Sectoring Schemes

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INTRODUCTION:

Sectoring schemes provide a means of classifying and aggregating Industry and Commodity data. Each database source can have its own unique format or scheme for presenting Industry data (e.g. IMPLAN scheme or the REA scheme). An Industrial classification scheme allows categorization according to the type of products or services produced by the Industry or Industries.

Employment and Value Added data used in IMPLAN originates from surveys of industry establishments. This establishment may be a small business with a single location, or it may be a branch location of a large firm. Each establishment in the defined region is counted separately on the covered (social security or unemployment) employment rolls. When the establishment submits a report or responds to a census or a survey, its data are collected and assigned an establishment code depending on the primary product produced by that establishment.

The industry classification scheme used for all federal government industry based data sets is the 6-digit North American Industrial Classification Scheme (NAICS), as described in the most current NAICS manual, published by the Office of Management and Budget.

This scheme was adopted in 1997 and replaced the previously used Standard Industrial Classification (SIC) codes. Unlike the SIC, NAICS was developed jointly by the United States, Mexico, and Canada to allow for comparability between all North American Industrial data.

The current NAICS scheme is 2017. NAICS reports five levels of Industry detail, ranging from the 2-digit detail (the most aggregate) to the 6-digit (the most detailed). To learn more about the history of NAICS click here. Certain IMPLAN Sectors – including the construction Sectors (50-62), Sector 449 – Owner-occupied dwellings, Sector 525 – Private households, and Sectors 526-546, do not follow a normal NAICS pattern. Read more information about these Specialty Sectors. Read more for additional information on the IMPLAN Sectoring scheme and for a listing of the current 546 scheme.

 

DATA SOURCES:

REGIONAL ECONOMIC ACCOUNTS (REA) SECTORING

A major data source used to derive IMPLAN databases is the Bureau of Economic Analysis’ Regional Economic Accounts (REA – formerly known as REIS). At the state level, REA reports in 3-digit NAICS detail for employment and income. At the county level, income is reported at 3-digit NAICS but employment is provided at the 2-digit NAICS detail.

BUREAU OF LABOR STATISTICS

Data from the Bureau of Labor Statistics (BLS) is used for deflators and some output estimates. The BLS uses a different sectoring scheme, again based on the NAICS code system.

BEA BENCHMARK

IMPLAN’s current 546-sector scheme is based on the Bureau of Economic Analysis’ latest Benchmark Input-Output Study. Since every five years the BEA updates their input-output accounts, it means that on those years, IMPLAN data sets also undergo important updates as well. In late 2018, the BEA released its 2012 industry statistics and benchmark make-use tables (also known as I-O tables) which include methodological improvements to more accurately reflect the ever-changing national economy.  For more information, visit BEA Benchmark & The New 546 Sectoring Scheme.

 

IMPLAN Database years Number of IMPLAN Sectors BEA Benchmarks
1996-2000 528 1987 and 1992
2001-2004, 2006 509 1997
2007-2012 440 2002
2013-2017 536 2007 with parts of 1997 and 2002
2018 546 2012

 
STANDARD INDUSTRIAL CLASSIFICATION (SIC) CODES

Prior to NAICS, this was the most common scheme as described in the 1987 Standard Industrial Classification Manual. This scheme had four levels of detail ranging from 1-digit detail as the most aggregate to 4-digit as the most detailed. IMPLAN datasets prior to 2001 are SIC-based.