IMPLAN is the leading provider of economic impact data and analytical software. The company began in 1972 working with the US Forest Service and has grown to a current user base of academics, governments, economic developers, corporations, nonprofits, and consultants. For a brief review of IMPLAN through the years, check out our History page.
Input-Output (I-O) modeling is based on the work of Nobel Prize winner Wassily Leontief. The foundational concept is that all industries, households, and government in the economy are connected through buy-sell relationships, therefore a given economic activity supports a ripple of additional economic activity throughout the economy. IMPLAN is an I-O modeling system that uses annual, regional data to map these buy-sell relationships so users can predict how specific economic changes will impact a given regional economy or estimate the effect of past or existing economic activity.
One of the tenets that makes IMPLAN so attractive is that there are no black boxes. Analysts can view the background data used in the models and customize them with local data and knowledge.
Constructing IMPLAN's annual databases requires gathering data from a large variety of federal sources, converting them to a consistent sectoring scheme and year, estimating the missing components, and controlling the newly formatted data against other known data sources to maintain accuracy. For details on how IMPLAN constructs the datasets, visit the Data Sources & Methodology for a full explanation.
IMPLAN Sector codes are based on definitions put forth by the Bureau of Economic Analysis. Each year, IMPLAN gathers current data at the national level, compiles it into the IMPLAN data format, and derives new national Input-Output matrices, as well as national tables for deflators, margins, and regional purchasing coefficients. Data for state, county, zip code, and congressional districts are then gathered and controlled to the national totals.
Employment data in IMPLAN follows the same definition as Bureau of Economic Analysis Regional Economic Accounts (BEA REA) and Bureau of Labor Statistics Census of Employment and Wages (BLS CEW) data, which is full-time/part-time annual average. 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. Jobs in IMPLAN are not the same as a full-time equivalent number.
Labor Income represents the total value of all forms of employment income paid throughout a defined economy during a specified period of time. It reflects the combined cost of total payroll paid to employees (e.g. wages and salaries, benefits, payroll taxes) and payments received by self-employed individuals and/or unincorporated business owners (e.g. capital consumption allowance) across the defined economy. Labor Income (LI) encompasses two additional representative metrics called Proprietor Income (PI) and Employee Compensation (EC).
Value Added represents the difference between Output and the cost of Intermediate Inputs throughout a defined economy during a specified period of time. It equals gross Output minus Intermediate Inputs (consumption of goods and services purchased from other industries or imported). Value Added is a measure of the contribution to GDP made by an individual producer, Industry, or Sector.
All analysis in IMPLAN is based on Output, which is the value of production by industry in a calendar year. IMPLAN Output data largely come from the same sources as those used by the BEA in developing their Benchmark Input-Output tables. Since output is the total production value of a Sector, it includes all components of production value or output for a given Sector: Output = Employee Compensation + Proprietor Income + Intermediate Inputs + Tax on Production and Imports + Other Property Income.
Other Property Income (OPI), previously denoted as “Profit” includes consumption of fixed capital (CFC), corporate profits, and business current transfer payments (net). Subsidies for government enterprises is considered negative profit, therefore any subsidization of a government enterprise will count as a negative value towards the government enterprise Sector’s OPI.
Taxes on Production & Imports, less subsidies (TOPI) includes sales and excise taxes, customs duties, property taxes, motor vehicle licenses, severance taxes, other taxes, and special assessments. For all Sectors other than government enterprises, subsidies are counted as a negative value towards TOPI.
Input-Output (I-O) Analysis and IMPLAN is designed to predict the ripple effect of an economic activity by using data about previous spending. Production in a given Sector in an economy supports demand for production in Sectors throughout the economy, both due to supply chain spending and spending by workers. For details on how this works, visit the article Industry Impacts: Direct, Indirect, and Induced Effects.
A Direct effect is the initial exogenous change in final demand in terms of Industry Output, Employment, and Labor Income Dollars. When consumers purchase goods and services, they create final demand to the Industries producing the goods and services they consume. When you analyze final demand in IMPLAN, we call this a Direct Effect.
For Industry, Commodity, and Institutional Spending Pattern Events, the Event Value entered is assumed to be final demand. Thus, the Event Value(s) entered in these Event Types will be used to determine the Direct Effect of the Event. Labor Income, Household Income, and Industry Spending Pattern Events do not generate Direct Effects.
Indirect effects are the business to business purchases in the supply chain taking place in the region that stem from the initial industry input purchases. As the Industry specified in an Event spends their money in the region with their suppliers, this spending is shown through the Indirect Effect.
Labor Income and Household Income Events do not generate Indirect Effects because no initial industry is specified in these Event Types.
The Induced Effects stem from income being spent throughout the Selected Region. Typically, the income being analyzed are the wages of employees working in the Direct/Indirect Industries.
Written November 12, 2019
Updated September 17, 2020