We get this question a lot at IMPLAN. You run an analysis of $5M and your Results only show $4.8M in Direct Output. Where did the other $200,000 go?
There are seven reasons that these numbers won’t match. Let’s walk through them.
THE SEVEN REASONS WHY
If you are modeling a list of Industries, it is possible that one of them doesn’t exist in your Region. If it doesn’t exist in the IMPLAN data, there will be no effect from that Industry. If you know that the Industry does now operate in your Region, you can add it by Customizing your Region.
Different Dollar Years
In order to see the exact number that you used on the Impacts screen in your Direct Effects, you will need to ensure that your Dollar Year matches on both screens. For example, if you analyzed your Events using 2018 Dollar Year, filter your Results for 2018 Dollar Year. If different years are used, you will not see exact matches between the Impacts screen and the Results screen. Check out the article on Dollar Year & Data Year for more details.
The only Event Types that will give you a Direct Effect are Industry Events, Industry Contribution Events, Commodity Output Events, and Institutional Spending Pattern Events. Direct Effects are not a part of Labor Income Events, Household Income Events, or Industry Spending Pattern Events. More details are in the article Explaining Event Types.
A Margin is the value of the transportation, wholesale, and retail trade services provided in delivering Commodities from the factory floor to buyers. Margins are calculated as sales receipts less the cost of the goods sold. They consist of the trade Margin plus sales taxes and excise taxes that are collected by the trade establishment.
Most Input-Output models, including IMPLAN, record expenditures in producer prices (known as Marginal Revenue). This allocates expenditures to the Industries that produce the goods or services. Any Output or sales you want to apply to multipliers that are in purchaser prices (prices paid by final consumers) need to be converted from purchaser price (Total Revenue) to producer prices (Marginal Revenue) or allocated to the producing Industries. Margins enable the move from producer to purchaser prices or vice-versa.
IMPLAN values are based on the actual costs of producing the product or service being sold. Margins are necessary whenever an item is purchased from a retailer or wholesaler. Margins can be applied to retail and wholesale Industry Events and Commodity Events.
When margins are applied, you will not see the full Value from your Impacts screen in your Results. The portion that you do see in the Results is the margin coefficient for retail or wholesale Industry. Details can be found in these two articles: Retail and Wholesale: Industry Margins and Retail and Wholesale: Commodity Margins.
Local Purchase Percentage
The Local Purchase Percentage (LPP) in Commodity Output Events and Spending Pattern Events is by default set to 100%, but this can be edited via the Advanced Menu. Remember, the LPP indicates to the software how much the Event impact affects the local Region and should therefore be applied to the Multipliers. If the LPP is set to anything less than 100%, you won’t see your inputs match the Results. Learn more in the article Local Purchase Percentage (LPP) & Regional Purchase Coefficients (RPC).
Commodity Market Share
The portion of Commodity supply coming from each source for a given Commodity is called a Market Share. If you are analyzing Commodities, some of the Market Share can come from Institutional Sales (like out of inventory or produced by the government). When LPP is less than 100%, the remaining portion (or 1-LPP) is then assumed to be affecting a different Region. The portion happening outside the Region of your analysis does not create any local effect.
Because Commodity Market Shares allocated to Institutions will be treated as leakages, these portions of Commodity Output will not be included in the Direct Effect of the Results. Check out where to find the Market Shares in the article on Social Accounts.
Commodity Events and Deflators/Inflators
When a Commodity Event is run with the same Dollar Year and Data Year and the Results are viewed in that same Dollar Year, the Direct Effect will match the Direct Commodity input. However, when the Dollar Year on the Impacts screen or the Dollar Year on the Results screen do not match the Data Year, the Direct Effect will be slightly different than the Direct inputs. This is because the Commodity Event is adjusted using Commodity deflators/inflators and then those dollars are deflated/inflated on the Results using Industry deflators/inflators. The slight difference in the Results you see in the Direct Effect is due to the differences between Commodity and Industry deflators/inflators.
Written May 21, 2020
Updated July 10, 2020