Occupational Matrices

INTRODUCTION:

IMPLAN offers a national Industry by Occupational Matrix based on Bureau of Labor Statistics (BLS) data. This data is available in the form of an Excel spreadsheet file and shows the occupational composition of wage and salary employment by industry, as well as compensation for each occupation. When combined with IMPLAN wage and salary employment by industry and compensation by industry, the matrices will yield estimates of employment and compensation distributions across occupations.

Levels of occupation classifications and the occupations within each level of classification correspond to the BLS Standard Occupational Classification (SOC) codes (http://www.bls.gov/soc/). Levels include Major, Minor, Broad and Detail. Major is the most aggregated (23 categories), followed by Minor (96), Broad (461), and Detail (835).  

Note that the military occupational codes used by IMPLAN do not correspond to military SOC codes. While the BLS does have military occupation codes, our source data for military employment by occupation does not come in that scheme and is only at the broader military occupation level (see tables 1 and 2 in the link below). Therefore, we created the more aggregated series of military occupation codes utilized in the matrices. For you as the user, it just means that the military occupation codes in the matrices will not match the BLS military SOC codes with which they may be familiar.
https://www.bls.gov/ooh/military/military-careers.htm

 

USAGE INSTRUCTIONS:

For help using the Occupational Matrices, please follow the instructions below and reference this video tutorial if needed. 

EXTRACTING THE NECESSARY DATA FROM IMPLAN

1. Decide what by Sector Employment/Employee Compensation data you’d like to convert. You can choose from either a Region’s Study Area Data or the Detailed Results of an Analysis.

2. Export the tables containing the chosen data. 

OCCUPATIONAL MATRICES FOR EMPLOYMENT DISTRIBUTION 

The employment values currently displayed in the IMPLAN application are the sum totals of Wage & Salary Employment and Proprietor Employment. However, we do have data on each type of employment and will provide the user with the ratios of wage and salary employment to total employment which can be used to isolate wage and salary employment values for use with the occupational suite data. The Occupational Matrices specifically provides the ability to convert Wage and Salary Employment into a breakout of Employment by occupation. Therefore, each industry’s employment value must be limited to just wage and salary employment prior to utilizing the matrices.

1. Isolate wage and salary employment using provided ratios by multiplying each Sector’s Employment by the respective Sector’s Wage & Salary Employment coefficient, found in the “WSEmployment” column in the ‘2016EmploymentRatio…’ file, by first finding the Region in which this Employment Data was pulled from (Regions are grouped alphabetically in two files Alabama-Missouri and Montana-Wyoming).

2. Copy the Wage & Salary Employment column to be pasted in a following step.

3. Open a copy of the ‘OccupationalMatrices2016_Employment’ Excel spreadsheet. For each use, we recommend making a copy of the Occupational Matrices spreadsheet. 

4. Paste the data generated from point 1 and copied in point 2 for all 536 Sectors into the ‘Employment Impact’ tab under the column heading starting in cell A2.

5. Review your results! The tabs ending in the word “Impacts” provide the actual Employment count estimate for each occupation. The numbers can be pulled from the tab of your desired level of detail to be included in your reporting. The tabs ending in the word “Ratios” won’t change as a result of you pasting in your Employment numbers as these are the ratios being used to calculate your results in the “Impacts” tabs. 

OCCUPATIONAL MATRICES FOR EMPLOYEE COMPENSATION DISTRIBUTION

1. Open a copy of the ‘OccupationalMatrices2016_Compensation’ Excel spreadsheet. For each use, we recommend making a copy of the Occupational Matrices spreadsheet. 

3. Copy and paste the exported Employee Compensation data for all 536 Sectors into the ‘Compensation Impact’ tab under the column heading starting in cell A2.

4. Review your results! The tabs ending in the word “Impacts” provide the actual Employee Compensation amount estimate for each occupation. The numbers can be pulled from the tab of your desired level of detail to be included in your reporting. The tabs ending in the word “Ratios” won’t change as a result of you pasting in your Employee Compensation numbers as these are the ratios being used to calculate your results in the “Impacts” tabs.  

 

PURCHASING THE OCCUPATIONAL MATRICES:

If you are interested in using the Occupational Matrices and have not yet purchased it or are interested in updating to the most recent version, you can email [email protected]

Methodology for Development of the 2017 Detailed Production Functions for IMPLAN’s Nine Electrical Power Sectors

There is a growing need to provide more detail behind the generation and sale of electricity in ways that help businesses, analysts, and policy makers understand the change in both the technologies and economics that underpin the consumption of electricity. For that reason, IMPLAN Group, LLC contracted with Skip Laitner of Economic and Human Dimensions Research Associates, both in 2014 and 2019, coinciding with releases of the 2007 and 2012 Bureau of Economic Analysis (BEA) Benchmark Input-Output tables, to break out the BEA Benchmark’s single aggregate “Electric power generation, transmission, and distribution” sector into the following eight electrical power generation sectors and one electric power transmission and distribution sector, thereby generating nine separate production functions (vectors of coefficients representing each industry’s operation expenditures per dollar of industry output):

2017 NAICS Code       Description

221111                         Electric power generation, hydroelectric
221112                        Electric power generation, fossil fuel (e.g., coal, oil, gas)
221113                        Electric power generation, nuclear
221114                        Electric power generation, solar
221115                        Electric power generation, wind
221116                        Power generation, geothermal
221117                        Power generation, biomass
221118                        Electric power generation, tidal (other)
2212                           Electric power transmission, distribution (and administration)

The production functions consist of coefficients based on the detail from the latest BEA Benchmark USE table for the commodities being purchased and include coefficients for 3 components of Value Added: Employee Compensation, taxes on production (TOPI), and gross operating surplus (GOS).  These are then adjusted to meet the new IMPLAN 546 sector scheme.  The aggregate expenditures are benchmarked to published accounts of the U.S. Energy Information Administration (EIA) for the year 2017.  Note that because of the absence of consistent data and details for government-owned utilities, this working paper documents both the array of data and the major steps necessary to generate the requisite production functions regardless of whether privately-owned or government-owned utilities.

 

AVAILABLE DATA:

Within the electric utility sector there are numerous accounting estimates for how that industry both uses and supplies Commodities. For example, based on the alignment of the many different producers of electricity we may find that “electric utilities” provide 56.4% of net generation of all “utility scale” producers of electricity (“Net Generation is the amount of electricity produced by a power plant that is transmitted and distributed for consumer use. In other words, the electricity provided for customer consumption after meeting its own electricity needs). Independent power producers (including those which use Combined Heat and Power) may provide 39.7% of the net generation. A combination of commercial and industrial producers provides the remaining balance of 3.9% of total net generation (EIA 2018, Table 1.3). Yet, in contrast,  the Edison Electric Institute EEI (2018) indicates that Investor-Owned Utilities (IOUs) sell about 36% of generation, government utilities and cooperatives provide about 20% of generation, while non-utility sources provide the balance, or about 44%. (EEI 2018, 2015-2017 Data at a Glance). 

Following the breakout of different kinds of suppliers, there are also many different categories of electric generation technologies (e.g., hydro, fossil fuel, nuclear, renewable energy technologies), as well as differing cost profiles for the costs of transmission, distribution, and administration of electricity (TDA) within that industry. For the year 2017, for example, the EIA suggests generation costs are about 62% of total costs while the transmission, distribution, and administration costs absorb 38% of total expenditures for electricity (EIA 2019b, Table 8). 

Finally, there are two other categories of divergent sources of data. In the case of primary energy (e.g., coal, nuclear, natural gas resource and other fossil fuel equivalents), about 90% of those energy costs go into the generation of electricity while 10% of those resources are used for thermal (heat) applications primarily sold to industry (EIA 2019a, various Tables in section 5).  

The last area of data are the many different ways that generation technologies are characterized. The table that follows highlights differences between new coal generation technologies based on Lazard (2018) and the average existing fossil-steam technologies within the investor-owned utilities—primarily coal, but other fossil fuels as well (EIA 2018, Table 8.4)

TABLE 1. COMPARING DIFFERENT COSTS OF ELECTRICITY GENERATION ($/MWH)

Generating Unit (Data Source)

Capital

Fixed

Variable

Fuel

Non-Capital Total

Capital Total

New Coal (Lazard 2018)

75.5

7.5

3.5

15.0

26.0

101.5

Generating Unit (Data Source)

Capital

Operation

Maintenance

Fuel

Non-Capital Total

Capital Total

Average Fossil Steam (EIA 2018)

n/a

5.01

5.13

25.27

35.41

n/a

The Lazard (2018) data shows the combined capital, fixed, and variable operating costs, and the cost of fuel for new (marginal) units of generation technologies regardless of ownership. The costs are shown in 2017 dollars per megawatt-hour ($/MWh). Note that $/MWh is the functional equivalent of mills per kilowatt-hour (mills/kWh), and that mills/kWh divided by 10 gives cents/kWh. So, for example, 101.5 $/MWh is the same as 10.15 cents/kWh or $0.1015/kWh.

At the same time, much of the data for existing generation technologies are based on published data for the Investor-Owned Utilities (IOUs) only. So, for example, the average fossil steam data are provided only for operation, maintenance and fuel costs. In the table above, that limited set of data shows a “non-capital total cost” of $35.41/MWh for existing, less efficient, or less productive fossil steam units which compares to an estimated $26/MWh for new, more efficient coal technologies. Many cost differences exist among all other generation technologies whether nuclear or renewable energy facilities. These differences, on balance, average out across the national data but may yield some differences at the regional or local level.  Labor costs or tax payments in the states largely supported by the Bonneville Power Administration, (a non-profit Federal power marketing administration based in the Pacific Northwest) may be significantly different than where the IOU American Electric Power calls home (Ohio), for example.

 

STEPS IN THE DEVELOPMENT OF THE NINE PRODUCTION COEFFICIENTS:

With such a large divergence across the various data that are available to us, we converge to a reasonable pattern of nine vectors of production coefficients in a series of steps that are described below.

STEP 1. CONVERGING TO AGGREGATE CATEGORIES OF EXPENDITURES

The first area of focus is converging the 2017 Intermediate Expenditures (IE) and Value Added (VA) expenditures as they are broken out according to the aggregate set of costs within the eight categories of generation technologies, and also to the aggregate of TDA costs. With the end result that all main categories of expenditures sum to $390,332 million dollars.

We first scale the various expenditures for 2017 “IOU Only” to the 2017 Total Gross Output (TGO) accounting. This gives us an indicative, but an initial, allocation of total electricity expenditures.  Next, we focus on the initial break out of the generation versus TDA expenditures as suggested by the Annual Energy Outlook 2019 (for year 2017) as indicated by EIA (2019b). This provides an overall aggregation while the next step gives us a calculated “Production/TDA” split to help us allocate: (a) purchased power expenditures (essentially power generated by independent producers sold wholesale to electric utilities); (b) other categories of intermediate expenditures; and (c) taxes paid by the various producers.  This is true for both generation and TDA.

At the same time, we rely on the KLEMS data (BEA 2018a) to suggest the labor compensation of 16.67% of total expenditures (part of the VA component).  We allocate initial expenditures across two columns (one for aggregate generation costs and the other for aggregate transmission and generation costs) and six rows of IE and VA.  The intermediate expenditures include (i) the cost of fuel, (ii) purchased power, and (iii) all other intermediate expenditures. The VA categories include (iv) compensation of labor, (v) taxes, and (vi) GOS.  A sum check column ensures a reasonable convergence to the $390,322 million of expenditures.

STEP 2. ALLOCATING GENERATION COSTS AMONG THE EIGHT TECHNOLOGIES

With a working estimate of $242,000 million of the various generation costs, we can now break out technology costs based on EIA 2018 (Tables 3.1.A and 3.1.B).  The result is the table below which provides key generation metrics for the eight categories of generation technologies, including net generation (in 1,000 MWh) and generation cost (in $/MWh).

TABLE 2. HIGHLIGHTING KEY TECHNOLOGY GENERATION METRICS

Vector #

Unit Category

Generation (1000 MWh)

Share

Cost ($/MWh)

1

Hydro

300,333

7.4%

41.3

2

Fossil-Fuels

2,502,250

62.0%

62.8

3

Nuke

804,950

20.0%

56.6

4

PV

50,017

1.2%

70.9

5

Wind

254,303

6.3%

44.2

6

Geo

15,927

0.4%

90.9

7

Bio

62,762

1.6%

67.8

8

Tidal Other

50,221

1.2%

70.7

 

Pumped Storage

-6,495

-0.2%

n/a

 

Net Generation

4,034,268

100.00%

60.0

Including the information from the table above, we confirm the actual pattern of net generation by technology category (or by one of the eight vectors of technology production).  And we can also confirm a reasonable pattern of generation costs for each category of technology ($/MWh).

STEP 3. ISOLATE ENERGY PURCHASES, PURCHASED POWER COSTS, AND OTHER GENERATION EXPENDITURES

The generation costs are allocated to two intermediate categories of: (i) fuel costs with a combined $36,516 million dollars, and (ii) all other operating and maintenance costs adding up to $73,014 million.  Adding the VA categories of labor ($40,334 million), taxes ($33,941 million) and surplus ($58,154 million), we then have a total generation cost of $241,958 million (rounded to $242,000 million). These costs are then isolated according to the eight vectors of generation technologies based on items like fuel costs (where appropriate), maintenance costs, purchases from independent producers, and total costs of production, including the VA contribution.

STEP 4. ISOLATE TRANSMISSION, DISTRIBUTION, AND ADMINISTRATIVE EXPENDITURES

In a similar accounting pattern for generation costs, Transmission, Distribution, and Administrative (TDA) IE that total $72,095 million which are complemented by the VA categories of labor ($24,725 million), taxes ($14,814 million) and surplus ($36,730 million). Hence total TDA costs add to $148,364 million.

STEP 5. ALLOCATION TO THE 546 IMPLAN COMMODITIES

The combined $241,958 million for the aggregate of generation costs together with the $148,364 million of TDA expenditures, add up to the desired 2017 set of electricity expenditures which total $390,322 million.  The final allocation to the eight vectors of generation and the one vector of TDA is a further two-step process that uses the BEA 2012 Use Table (BEA 2018b) and the IMPLAN-provided bridge from the 2012 BEA Benchmark sectoring scheme to IMPLAN’s 546 sectoring scheme (IMPLAN 2019).

Three fuel categories – coal, other fossil fuels, and nuclear – are allocated directly to key sectors within the IMPLAN structure.  That is, coal is directly allocated to the IMPLAN coal mining sector (Sector 21), the other fossil fuels are allocated to the IMPLAN oil and gas extraction sector (Sector 20), and nuclear fuels are allocated to IMPLAN’s uranium-radium-vanadium ore mining sector (Sector 26). At the same time, purchased power expenses and other minor operating and maintenance expenses are directly allocated to the IMPLAN’s electric power generation Sectors (sectors 39 through 46), and the electric power transmission and distribution Sector (Sector 47).  All other intermediate expenditures are allocated based on the matrix of expenditures from BEA 2012 patterns as adjusted to the IMPLAN 546 Sectors mapping scheme.

At the same time, the VA expenditures are allocated in a straightforward manner to ensure that labor and tax allocation are consistent with the KLEMS data described in Step 1. The GOS (consisting largely of profit and depreciation) provides the balance of allocation as a function of all remaining expenditures. The outcome is then consistent with the generation costs as highlighted in Table 2 above (62% of total expenditures), and the TDA cost categories (38%) described in Step 1.

FURTHER REVIEW IN DEVELOPMENT OF THE NINE PRODUCTION COEFFICIENTS:

As a further step toward understanding the development of production coefficients, this section explores the specific set of assumptions for nuclear energy. More specifically it explains how the data builds to a final set of IE and VA expenditures. To start we build on key data that reconciled EIA with KLEMS-AEO 2019-EEI data.  With that as the start, we first explore the boundary conditions of the industry-wide aggregate expenditures. We then examine  the specific allocation and breakout for nuclear technologies as they fit within the industry-wide totals.

THE INDUSTRY-WIDE AGGREGATES

In turn we draw from the EIA Electricity Annual Report with data for 2017, Table 8.3 Revenue and Expenses for Investor-Owned Utilities (IOUs). We expand the IOU’s total operating revenue of $286,501 million to the $390,322 million – a 36% difference. As an example, we then have the purchase of fuel as a maximum of $43,821 million.  But the decision is made to account for labor costs so that this subtotal is modified by multiplying the fraction of (1 – the 16.67% share of labor), or 0.8333 times $43,821 million, to generate a net industry-wide fuel cost in the intermediate expenditure rows of $36,516 million. But this is an expenditure only generation category.

A similar procedure is used to generate an industry-wide purchase power cost of $55,662 million. The difference here is an assumption that the TDA category of expenditures, by their very nature, are also likely to purchase power in the wholesale market as their percentage split of the section C “Production/TDA Split.” This results in the allocation of $38,751 million allocation to Generation and $16,911 being allocated to TDA. Those sums add to $55,662. All remaining intermediate expenditures are shown to equal $89,460 million, allocating in the same way, and also backing out labor share, so that generation and TDA are assigned $34,277 million and $55,184 million, respectively.

In the VA row we also have three aggregate subtotals of labor compensation, taxes, and GOS.  We have previously determined that TGO equivalent for generation is to equal 62% of the 390,322 million as suggested in Section B. Ergo, the total cost for generation (or TGOgen) is set at $242,000 million for 2017 while the total cost for TDA (or TGOTDA) is set at 38% or $148,322 million, also for 2017. So, labor becomes 16.67% of $242,000 million for generation, or $40,341 million, and $24,275 million for TDA.

Taxes are allocated also in a similar way. The aggregate expenditures are shown as $48,761 million.  GOS then becomes the implied delta between TGO less Intermediate Expenditures less Compensation less Taxes. In the case of generation that is $58,167 million and $36,689 million.

THE ALLOCATION FOR INDIVIDUAL GENERATION TECHNOLOGIES: THE NUCLEAR EXAMPLE

With the aggregate of generation and TDA allocations set, we can now turn to the specific example of nuclear generation to show how the calculations are set to build the column of coefficients of Intermediate Expenditures in particular. Given the above, we then turn to two additional tasks.

The first is to focus on nuclear, determining both IE and VA expenditures for that technology.  Nuclear fuel costs, net of labor compensation, and as a share of the overall energy costs ($36,516 million) are determined as $4,635 million.  Similarly, the nuclear equivalent of total power purchases for generation technologies (how the industry buys and sells from and to each other), again net of labor costs ($38,744 million), are estimated as 19.9% of total net generation, or $7,719 million.  Finally, nuclear expenditures of total operating and maintenance costs for generation technologies ($34,270 million) are calculated as $6,828 million. Similar calculations were done for labor costs, taxes, and GOS.

With that information, we then feed the relevant data into the bridge between sectoring schemes.   

SOME CAVEATS

There is an array of values which have not been completely resolved so that miscellaneous residuals, now about 2.4% of the industry TGO of $390,322, can be moved closer to zero. Moreover, things like fuel and purchase power costs can also be refined so that deltas are also closer to zero. At the same time, fuel costs, as calculated by means of other independent estimates, are larger than the value (net of labor compensation) of $36,516 million. But these costs are constrained by the assumption of an IOU set of accounts as if they reflected total industry-wide costs. The assumption is that these are expenditures which, in effect, become part of the purchased power costs assigned to each of the generation technology columns.  This, together with other assumptions such as the IOU pattern of expenditures, provides a reasonable recipe of the industry-wide pattern of purchases.

 

POST-DELIVERY ADJUSTMENTS MADE BY IMPLAN:

Upon the receipt of the data from Mr. Laitner, IMPLAN made the following adjustments, in line with similar adjustments made in the previous iteration of this project in 2014.:

  1. Adjusted the transmission and distribution Sector’s purchase of electricity to equal total Commodity Output of all electricity Commodities.
  2. Removed the purchase of turbines by the transmission and distribution sector
  3. Moved a portion of the transmission and distribution Sector’s purchases of rail transportation and pipeline transportation (which were relatively high) to the fossil fuels generation Sector, for which these purchases were relatively low.
  4. Each electricity-producing Sector’s purchase of its own type of electricity has been re-expressed as purchases of the transmission and distribution commodity.

BEA Benchmark & The New 546 Sectoring Scheme

INTRODUCTION:

IMPLAN’s sectoring schemes is based largely on the US Bureau of Economic Analysis’s (BEA’s) sectoring scheme. 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.  What does this mean for you? A new 546 IMPLAN Sectoring Scheme!

Not only will most of the Sector numbers change from our beloved 536 scheme, but there are other changes as well.  Some industries are split into further detail, while a few are being aggregated into less detail.  

 

DETAILS:

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.  The benchmarks are prepared approximately once every five years based on detailed data from the Census Bureau’s Economic Census.1  They provide detailed statistics on economic processes and relationships and essential information for other economic accounts. They are used to set the level of GDP in the National Income and Product Accounts (NIPA) and commodity detail on the composition of the final-use categories. In addition, they provide information on what industries use to produce their output and on what commodities are produced by each industry. The benchmark I-O accounts consist of make tables, use tables, and direct and total requirements tables. 

The economy is constantly changing and with new BEA benchmarks come changes to the industrial makeup of the nation. When the BEA releases a new benchmark, IMPLAN follows suit and introduces those new underlying sets of industry production functions. Say goodbye to 536 Sectors and hello to 546 Sectors!

 

IMPLAN Database Years

Number of IMPLAN Sectors

BEA Benchmarks

1996-2000

528

1987 & 1992

2001-2004

2006

509

1997

2007-2012

440

2002

2013-2017

536

2007 with parts of 2002 and 1997

2018+

546

2012 with parts of 2007, 2002, & 1997

 

CHANGES FROM 536 TO 546:

There are three cases where two sectors in the 536 sectoring scheme are becoming one sector in the 546 sectoring scheme.  This is due to loss of NAICS codes for these sectors. Without a NAICS code for these sectors, there will be no employment or wages data for these sectors in the Bureau of Labor Statistics’s annual Census of Employment and Wages data sets; therefore, there will be no other raw data for these sectors going forward.

 

  • Sectors 20 (Extraction of natural gas and crude petroleum) and 21 (Extraction of natural gas liquids) in the 536 sectoring scheme will now be a single sector (20).  
  • Sectors 26 (Lead and zinc ore mining) and 27 (Copper ore mining) in the 536 sectoring scheme will now be a single sector (22).  
  • Sectors 287 (Pump and pumping equipment manufacturing) and 289 (Measuring and dispensing pump manufacturing) in the 536 sectoring scheme will now be a single sector (285).  

 

The good news is that there are more instances of further disaggregation from the old 536 sectoring scheme into the new 546 sectoring scheme.

 

  • Sector 395 (Wholesale trade) will be split into 10 sectors in the new 546 sectoring scheme: sectors 392-401.  
    • Wholesale – Motor vehicle and motor vehicle parts and supplier
    • Wholesale – Professional and commercial equipment and supplies
    • Wholesale – Household appliances and electrical and electronic goods
    • Wholesale – Machinery, equipment, and supplies
    • Wholesale – Other durable goods merchant wholesalers
    • Wholesale – Drugs and druggists’ sundries
    • Wholesale – Grocery and related product wholesalers
    • Wholesale – Petroleum and petroleum products
    • Wholesale – Other nondurable goods merchant wholesalers
    • Wholesale – Wholesale electronic markets and agents and brokers
  • Sector 437 (Insurance carriers) will be split into 2 sectors in the new 546 sectoring scheme: sectors 443 and 444.  
    • Insurance carriers, except direct life
    • Insurance agencies, brokerages, and related activities
  • Previous sector 440 (Real estate) will be split into 2 sectors in the new 546 sectoring scheme: sectors 447 and 448.  
    • Other real estate
    • Tenant-occupied housing
  • New State and Local Government institution: Whereas there were 2 State and Local Government institutions in the old 536 sectoring scheme, the new 546 sectoring scheme will have 3 State and 3 Local Government institutions:  State and Local Government Education, State and Local Government Hospitals and Health Services, and State and Local Government Other Services. As such, previous state government payroll sector 531 will be split into 2 sectors (sectors 540 and 541) and previous local government payroll sector 533 will be split into 2 sectors (sectors 543 and 544) in the new 546 sectoring scheme.  
    • * Employment and payroll of state govt, hospitals and health services
    • * Employment and payroll of state govt, other services
    • * Employment and payroll of local govt, hospitals and health services
    • * Employment and payroll of local govt, other services

 

HOW IMPLAN COMPARES TO BEA:

You may notice that the new BEA benchmark has only 405 Sectors.  However, IMPLAN now has 546. Where do the other 141 Sectors come from? Well, there are a few places.

Using input from industry experts, IMPLAN provides production functions for sectors that the BEA has never provided.  Also, IMPLAN uses earlier benchmarks to split the absorption coefficients, byproduct coefficients, and institutional spending into previously-existing detail.  So you may notice a few places where the BEA data is less aggregated than the IMPLAN data.  

 

COMPARING DATA ACROSS TIME:

Sometimes you may want to compare data across time using IMPLAN.  However, 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 the 536 Sectoring scheme with the new 546 Sectoring scheme.

In fact, you may see cases where an Industry will seem smaller in 2018 than it was in 2017 even though this is not what the economy really looks like.  This is due to the changes in the methodology, sectoring scheme, and ratios that are used in IMPLAN.

Do not worry!  IMPLAN has two options to smooth the transition.  First, we will provide a bridge across the Sectoring schemes that should help in most instances.  Second, IMPLAN also has panel data available that allows for a more detailed analysis.  

 

DOWNLOADS:

 

IMPLAN 546 INDUSTRIES AND COMMODITIES

 

Download

2017 NAICS TO IMPLAN 546 SECTORS

Convert BEA’s 2017 NAICS codes to IMPLAN Sectors (546 scheme) using this downloadable spreadsheet.

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2012 NAICS TO IMPLAN 546 SECTORS

Convert BEA’s 2012 NAICS codes to IMPLAN Sectors (546 scheme) using this downloadable spreadsheet.

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DEFINITIONS OF IMPLAN’S 546 CONSTRUCTION SECTORS

View the breakdown of IMPLAN’s construction sectors (546 scheme) using this downloadable spreadsheet. 

Download

536 TO 546 BRIDGE

This bridge allows you to convert from the 536 sectoring scheme (2013-2017 data years) to the new 546 sectoring scheme. Note that the ratios only work one way: The 536 to 546 bridge is useful for converting 536-based sectors to 546-based sectors, but is not useful for converting 546-based sectors to 536-based sectors.

In the 536 to 546 bridge, a ratio of 1 means that 100% of the 536 sector should be classified as the corresponding 546 sector. In theory, there could be any number of sectors with a ratio of 1 merged into a single sector. So, the ratio of 1 for two different 536-based sectors simply means that both fit entirely into the same 546-based sector. In general, this happens rarely since we disaggregated more sectors than we aggregated.

 Download

546 TO 536 BRIDGE

This bridge allows you to convert from the 546 sectoring scheme to the old 536 sectoring scheme (2013-2017 data years) . Note that the ratios only work one way: The 546 to 536 bridge is useful for converting 546-based sectors to 536-based sectors, but is not useful for converting 536-based sectors to 546-based sectors.

In the 546 to 536 bridge, a ratio of 1 means that 100% of the 546 sector should be classified as the corresponding 536 sector. In theory, there could be any number of sectors with a ratio of 1 merged into a single sector. So, the ratio of 1 for two different 546-based sectors simply means that both fit entirely into the same 536-based sector. In general, this happens rarely since we disaggregated more sectors than we aggregated.

 Download

 

BEA RESOURCES:

BEA Input-Output Accounts

Comprehensive Update of Industry Accounts Now Available

Measuring the Nation’s Economy: An Industry Perspective | A Primer on BEA’s Industry Accounts

 

https://www.bea.gov/sites/default/files/methodologies/industry_primer.pdf#page=5

 

Written September 4, 2019