Jobs

A job in IMPLAN = the annual average of monthly jobs in that industry (this is the same definition used by the BLS and BEA). Thus, 1 job lasting 12 months = 2 jobs lasting 6 months each = 3 jobs lasting 4 months each. A job can be either full-time or part-time.  Similarly, a job that lasts one quarter of the year would be 0.25 jobs.  Note that a person can hold more than one job, so the job count is not necessarily the same as the count of employed persons.

Information on converting between IMPLAN jobs and Full-Time Equivalents can be found in the 536 FTE & Employee Compensation Conversion Tables found in our downloads section. Download 2017 Version

Find other conversion tables here: https://implanhelp.zendesk.com/hc/en-us/articles/115002997573-536-Sectoring-Scheme

 

Please note also that Full-Time Equivalent by BLS definitions is 35+ hours.

http://www.bls.gov/opub/ils/pdf/opbils05.pdf

 

BLS also has this definition in their Glossary, but definitions depend on the survey (notice the two definitions of Full-time)

http://www.bls.gov/bls/glossary.htm#F

Labor Income

How Zip Code Files are Estimated

We only create data for those zip codes for which we have one of the following: land area from the latest Decennial Census, population or household count from the latest American Community Survey (ACS), railroad employment from the latest Railroad Retirement Board report, or Census ZBP employment.  Having at least one of those allows us to distribute part of the county’s data to the zip code. 

Our main source of data for generating zip code files comes from the Bureau of Census County Business Patterns (CBP) program, as they release 6-digit NAICs employment data at the zip code level. Rather than employment counts, the CBP data provides information on the number of firms in each of 14 firm size classes (e.g., 1-4 employees, 4-9 employees, 10-19 employees, etc.) for each 6-digit NAICs sector. This allows the CBP to avoid disclosing the exact number of employees at a single firm.

To create our data, we take the mid-point of each of the size classes and multiply this by the number of firms in that size class (e.g. if there are 6 firms reporting under a single NAICS code for 4-9 employees, we get an estimate of ~39 employees for that NAICS code and class). By summing the estimated number of employees within a 6-digit NAICS specification, and aggregating the NAICS code employment values into their appropriate IMPLAN sector, we create an estimate of the employment for that sector at a zip code level. We also add together employment data for the all zip codes represented in a larger region (county or counties) to aid in distribution of non-employment IMPLAN data to individual zip code regions.

After aggregating the 6-digit NAICs data to the 536 IMPLAN Sectors, we can create ratios for distributing the county(ies) level IMPLAN data to the desired zip-code regions. The ratio is derived by dividing the specified zip code employment by the county’s zip code employment for each IMPLAN Sector.

Employment ratios are used to distribute all industry data (Employment, Output, Employee Compensation, Proprietor Income, Other Property Type Income and Tax on Production and Imports) into their respective zip code regions.

Census of population data is also available at the zip code level. The ratio of a zip codes population compared to the county’s population for the 2000 Census is applied to the county’s current population to provide an estimate of the zip code area’s current population.

Industry Sectors that CBP Does Not Cover

Proxies are used to distribute industry sectors that CBP does not cover to ZIP Code regions. These sectors, and the proxies used to separate the zip code employment from the county(ies) are shown below:

  • Agricultural Sectors: These are estimated from current Census of Agriculture- county level farming is distributed to zip codes based on the Census number of farms by zip code.
  • Railroad: These are estimated based on trucking and warehousing distribution employment as a proxy.
  • Religious organizations: Population is used as the proxy for determining these employment values.
  • Government, except education: Total employment for the zip code is used to distribute county level government employment.
  • State & local education: Population is used.
  • Construction: Employment for NAICS 22 is used for this proxy.

Final Demand Proxies to Distribute Zip Code Regions

Final demands also need to be estimated. Below are listed the proxy values used to distribute the county(ies) final demands to a zip code area.

  • PCE (9 classes): From latest Census American Community Survey by zip code data. This data contains the number of households by income class. E.g. if the zip code area has 10% of highest income households it gets 10% of the highest PCE final demand.
  • Fed Military & Non-military: overall Employment
  • State & Local Education & non-education: overall Employment
  • Federal Sales: overall Employment
  • State & Local Gov Sales: overall Employment
  • Investment: Employment by Industry
  • Foreign Export: Employment by Industry
  • Change in Inventory: Employment by Industry

Productivity Data

Because of the limitations of the data, productivity data for the zip code area is the same as for the county(ies) containing the zip code area. The following examples are included as part of the productivity data:

  • Output per Worker
  • Earnings per Worker
  • Value Added to Output ratio

Understanding the data in your IMPLAN Zip code files

When working with Zip Code level data, there are several factors to consider. This article, while not exhaustive, lists the main items to keep in mind when using Zip Code data for your geographical study region.

MRIO, Aggregation and Leakages

  1. Multi-Regional analysis is not yet possible with zip code files. While you have received trade flow data files with your data purchase, the current version of the IMPLAN Version 3 software can only estimate zip code effects with the Econometric estimation of imports (RPCs).
  2. Zip code files, like other IMPLAN files, can be combined to create a region or used independently. Please keep in mind that while an individual zip code file will create Multipliers and have impacts, these impacts will be minimal. This is because zip codes may have no population and/or little to no employment (see notes 5 and 6). Also, many individual zip codes are not large enough to allow for local sourcing of materials needed for the indirect effect or to provide adequate services to create significant induced effect leading to much of the potential impact being lost in leakages (as in note 3).
  3. Zip code regions may represent very small economic regions and consequently, be extremely open to leakages. These leakages, even to nearby regions (in some instances this could literally be across the street) are lost from the modeled region resulting in very small indirect and induced effects. Please take into consideration where indirect purchases will be located and where employees may be spending their labor income when customizing zip code regions for analysis.
  4. Many of the issues in notes 2 & 3 may be addressed once zip code files/zip code regions are able to be analyzed with the Multi-Regional modeling technique. Multi-Regional analysis will allow for purchases to be made between Study Area regions (the zip code(s) and the linked regions) by tracking trade between these regions, potentially capturing many of the lost impacts. MRIO, however, is not yet available for zip code files.

Zip Codes Not Represented

  1. Not all zip codes listed by the U.S. Postal Service may be represented in the zip code package you receive. The USPS can open/close post offices or reorganize routes on an on-going basis, thereby changing zip-code demographics. Because of this, the County Business Patterns and Census demographic zip code representation may not be current.
  2. Depending on the year, roughly 4% of zip-codes have neither County Business Patterns (CBP) employment nor Census (demographic) data. If your region includes any of these zip codes, they will not be available in the package you purchase, as there is inadequate information to create Multipliers for these regions.
  3. Depending on the year, there will be roughly 8,000 zip-code files for which there is only CBP data with no demographic data. Most of these are P.O. boxes and “unique” point codes. They serve business but do not represent residential population. With no household representation, all employment would be considered in-commuting and have no local induced effect.
  4. Conversely, there are also some zip-code files with only demographic data and no CBP data. While CBP data does not exist for these zip-codes, they may still contain employment in some sectors since CBP data do not cover all IMPLAN sectors. Population is used as a distributor for most of these non-covered sectors. Farm counts by zip-code from the 2012 Census of Agriculture are used to distribute agricultural industry data in these cases.
  5. There will be cases where you may find an industry exists in an actual zip code region but does not show up in the zip code data (or even the county data). This occurs because of unreported sectors in the CBP and inconsistencies in data between CBP and BLS covered wages and employment. When this issue occurs, you will need to Customize your IMPLAN data to add the industry to the Study Area. CBP data are primarily obtained from administrative records supplied by the IRS, Social Security, and other sources. CBP is tabulated on an establishment basis, and each business location is tabulated only once according to the primary business activity. The industry classifications of establishments in the CBP are self-reported in the vast majority of cases. BLS CEW data are obtained from quarterly tax reports submitted to State Employment Security Agencies.

Inventory valuation adjustment (IVA)

The difference between the cost of inventory withdrawals as valued at acquisition cost and the cost of withdrawals as valued at replacement cost. The IVA adjusts inventories from the change in book value reported by most businesses to the definition of inventories used in the NIPAs and industry accounts—that is, the change in physical volume valued at the average prices for the time period. The IVA is subtracted from corporate profits and nonfarm proprietors’ income to remove inventory profits or losses from the income reported by businesses. (Up through the 1997 benchmark, the IVA in the I-O accounts has differed from the IVA in the NIPAs by the amount of the LIFO-reserve adjustment.) (BEA)

How Island Area Data Sets Vary from the Rest of the US

Data sets for Island Areas are not nearly as comprehensive nor timely compared to the US. Nor are Island Areas included in the US NIPA accounts, so there are no overall controls as there are for the US states and counties.

The Five US Island Areas are:

  1. American Samoa: AS
  2. Commonwealth of Northern Marianas Islands: MP
  3. Guam: GU
  4. Puerto Rico: PR
  5. Virgin Islands: VI

BLS Covered employment and wages (CEW) is only available for PR and VI.

Census County Business Patterns cover all five island areas and are the main source for employment and income data.

For Agricultural sectors, the Census collects “Outlying” areas – which includes the 5 island areas. The 5-year census for outlying areas is published several years after the corresponding Census for the US.

Military employment comes from the Department of Defense: https://www.dmdc.osd.mil/appj/dwp/dwp_reports.jsp.

GDP data is available in BEA news releases for US territories. The data is for overall GDP and is not sector specific, but it does provide controls. An example of such a report is can be found at this link.

There is some miscellaneous data collected from local government sources. Guam probably has the best government statistics collection, but data is still sparse.

Ratios and updates to the current data year are derived from US relationships and CEW data for Puerto Rico and Virgin Islands (as proxies).

Inventory

Stocks of goods held by the firm over a period of time. In the I-O accounts, inventory includes (1) products purchased for resale, generally held by wholesalers and retailers, (2) materials and supplies for use in the production of goods for sale or in the provision of a service, (3) products that are partly processed and that require further processing prior to sale (work in process), and (4) finished goods held for sale. (BEA)

Understanding Multipliers

INTRODUCTION:

Multipliers are the basis of how an I-O Analysis System such as IMPLAN makes estimations of the potential impacts of economic changes. Expressed as a rate of change, a Multiplier describes how for a given change in a particular Industry a resultant change will occur in the overall economy (e.g. for every dollar spent in the economy an additional $0.25 of economic activity is generated locally, implying a Multiplier of 1.25).

This article describes what a Multiplier means, the basis of how we can determine that an additional $0.25 will occur locally, and introduces the idea of aggregating Industries if you are trying to find the impact across a broad spectrum of production rather than a specific Sector.

 

DETAILED INFORMATION:

Multipliers exist in the IMPLAN Model to describe rates of changes for several different variables. The descriptions below apply to Type SAM and Type I Multipliers, which are unitless values.

  1. Output – Output is the base Multiplier from which all other Multipliers are derived. The Output Multiplier describes the total Output generated as a result of 1 dollar of Output in the target industry. Thus if an Output Multiplier is 2.25, that means that for every dollar of production in this Industry $2.25 of activity is generated in the local economy: the original dollar and an additional $1.25.
  2. Employment – Employment Multipliers describe the total jobs generated as a result of 1 job in the target industry. Thus if an Employment Multiplier is 2.33, that means that every Direct Job creates 2.33 jobs in the total economy: the original job and 1.33 additional jobs.
  3. Labor Income – Labor Income Multipliers describes the dollars of Labor Income generated as a result of one dollar of Labor Income in the target Industry. A Labor Income Multiplier of 2.2 indicates that for every dollar of Direct Labor Income in this Industry another $1.20 of Labor Income is generated in the local economy.
  4. Value Added – Value Added Multipliers describe the total dollars of Value Added generated as a result of one dollar of Value Added in the target Industry. A Value Added Multiplier of 2.3 indicates that for every dollar of Direct Value Added in this Industry another $1.30 of Value Added is generated in the local economy.

You can also compare Sectors’ Multipliers across regions. You will find that Multipliers are generally larger the larger the Study Area is. This is the result of a typical pattern that describes that larger regions will have less leakage to imports. Thus for accurate comparisons, it is most appropriate to compare states to states and counties to counties. 

TYPE I VS. TYPE SAM MULTIPLIERS: 

Type I and Type SAM Multipliers differ in their definition of “total” impact

  1. Type I – Looks only at business to business purchases and does not include the effects of local Household spending. This Multiplier is calculated as:
    (Direct + Indirect Effects) / Direct Effect.

    1. Since the denominator for the multiplier is always 1.00, the Type I Multiplier will equal the Direct Effect + the Indirect Effect
    2. Thus, the Type I Multiplier for Employment describes the direct and supply chain jobs within the study region resulting from one direct job.
  2. Type SAM – In addition to the Type I Multiplier, the Type SAM Multiplier includes the impact of Household spending and is the more common Multiplier. It is calculated as:
    (Direct + Indirect + Induced Effects) / Direct Effect.

    1. For example, the Type SAM Multiplier for Output describes the total output created in the study region resulting from one dollar of direct output.
    2. It also includes other non-industrial transactions, such as institution savings, payment of social security taxes, and commuting.

 

EFFECTS VS. MULTIPLIERS:

When the dollars or jobs associated to all the rounds of local purchasing are summed, the resultant values are the Effects. The Multiplier Effects come in 4 types:

    1. Direct Effect 
      1. For Output, these effects are either 1.00 or 0.00. For every dollar spent in an Industry, if the Industry exists in the region, there is a dollars worth of activity in the local economy. If the Industry doesn’t exist in the region, the effect is 0.00.
      2. For Employment, the Effect represents the number of jobs per $1,000,000 of production in the Industry.
      3. Labor Income Effects represent the Labor Income dollars per $1,000,000 of production in the Industry.
      4. Value Added Effects represent the Total Value Added and various Value Added subset dollars per $1,000,000 of production in the Industry.
    2. Indirect Effects
      1. For Output, the Effect represents the sum of local business to business purchases per dollar of Output.
      2. For Employment, the Effect represents the number of jobs per $1,000,000 of business to business purchases by all resultant rounds of local Industry purchases.
      3. Labor Income Effect represents the value of Labor Income dollars per $1,000,000 of business to business purchases by all resultant rounds of local Industry purchases.
      4. Value Added Effect represents the of Value Added dollars per $1,000,000 of business to business purchases by all resultant rounds of local Industry purchases.
    3. Induced Effects
      1. For Output, the Effect represents the sum of local Household purchases per dollar of Output, based on Labor Income payments made by the target Industry and the local Industries from which they purchase.
      2. For Employment, the Effect represents the number of jobs supported in local Industries per $1,000,000 of Direct spending in the target Industry as a result of Household purchases derived from Labor Income payments throughout all rounds of the impact.
      3. Labor Income Effect represents the value of Labor Income dollars per $1,000,000 of Direct spending in the target Industry in local Industries as a result of Household purchases derived from Labor Income payments throughout all rounds of the impact.
      4. Value Added Effect represents the Value Added dollars per $1,000,000 of Direct spending in the target Industry in local Industries as a result of Household purchases derived from Labor Income payments throughout all rounds of the impact.
    4. Total Effects are the sum of the Direct, Indirect, and Induced Effects. For Output, this value is the same as the SAM Multiplier.

 

HOW MULTIPLIERS ARE CREATED:

While the complex process of creating the Social Accounting Matrix is not described here, the results of those calculations are a complete transactions table showing what every Industry needs to purchase in order to make its products and the value of every Industry’s labor payments (Labor Income), taxes (Taxes on Production & Imports), and profits (Other Property Type Income) and what each Household income group buys.

We also know how much of each commodity is produced locally, which Industries or Institutions produce it in the local economy, and how much of the production is attributed to each producer.

The combination of these two factors allows the software to determine, based on the entered or estimated value of Industry Sales, how much of each commodity will be required to meet the change in production of the target Industry (Gross Absorption) and how much can be obtained from local vendors (Regional Absorption). After multiple rounds of purchases are accomplished and all the spending not attributed to local vendors is lost from the system, the resulting values spent locally on each commodity can be summed to show the total purchasing requirements for that commodity from the local economy in dollars and cents. These results can be viewed in the Detailed Multipliers sheet.

 

AVERAGE OUTPUT MULTIPLIER RANGE: 

Typically we expect Output Multiplier ranges to follow this general pattern:

  1. at a county level an Output Multiplier is between 1-2.
  2. at a state level an Output Multiplier is 2-3 and
  3. at a national level the expected range is 2-7.

However, individual regions may vary greatly depending on their concentrations of activity. 

 

AGGREGATE MULTIPLIERS: 

Multiplier specificity is a key to accuracy within an analysis. The more dissaggregate an Industry specification is the more accurate the results of the analysis will be, as the Multiplier for each Industry reflects:

    1. the target Industry’s specific purchasing pattern,
    2. its specific relationships for Labor Income / Worker
    3. its specific relationships for Output per Worker
    4. its specific relationships for Other Property Type Income / Output
    5. its specific relationships for Taxes on Production & Imports / Output

However, there are times when it may be necessary to aggregate Industries together in order to perform an analysis. Please read more about Aggregation Bias and Aggregating Industries if you are unable to attach your dollar value to a specific Industry Sector in IMPLAN.

 

USAGE:

Unless you have a significant background in using Multipliers in analysis, we highly recommend letting IMPLAN do the analysis for you or using the existing multipliers to help you tell your story.

If you are looking to use IMPLAN Multipliers in a different tool, this requires a custom license. We would be happy to work with you to create a license that meets your needs. Please give us a call at 800-507-9426.

Intermediate Expenditures

Purchases of non-durable goods and services such as energy, materials, and purchased services that are used for the production of other goods and services rather than for final consumption. These inputs are sometimes referred to as current-account expenditures. They do not include any capital-account purchases nor do they include the inputs from the primary factors of production (capital and labor) that are components of value added. (BEA)

Summary Description of Elements of the IxC Social Accounting Matrix