Users often ask, "Why don't my Direct Effects match my Direct inputs?" Running an analysis of $5M and the Results only show $2M in Direct Output. Where did the other $3M go? While there are several reasons why this may occur, it is often due to Leakages.
Leakages are dollars associated with the modeled Event that do not continue to circulate through the Region’s economy generating additional effects. A Direct Effect Leakages table is located on the Results Overview dashboard to show where those dollars leaked out from the analysis. The table may display values for one or more of the three leakages depending on the Event Type used in the analysis. The three Direct Effect Leakages are Institutional Commodity Production, Margins, and Imports to Region.
DIRECT EFFECT LEAKAGES
The Direct Effect is the initial change in production or expenditures as a result of an activity or policy. Applying these initial changes to the multipliers in IMPLAN will display how the Region will respond economically. The value of the Direct Effect that is applied to the multipliers may be reduced due to leakages in the modeled Event. Any one or more of the following leakages may cause the Direct Output in the Results to be less than the Event Value entered by the user on the Impacts screen.
INSTITUTIONAL COMMODITY PRODUCTION
This field shows the value of a Commodity produced by an Institution. These are Commodities which are produced and/or sold by the Government or those taken out of Inventory. Institutional Commodity Production leakage may occur on Commodity Output and Institutional Spending Pattern Events.
This field shows the producer, transportation, wholesale, or retail portion of the Value Chain that is not analyzed when Margins are applied. Margins are the value of the wholesale and retail trade services provided in delivering Commodities from producers' establishments to purchasers. A total Margin is calculated as sales receipts less the cost of the goods sold. This leakage will only occur when Margins are applied to an Industry Output Event with a retail or wholesale Industry as the Event Specification.
IMPORTS TO REGION
This field shows the value of goods and services purchased that are produced or sourced from outside of the Region. The Local Purchasing Percentage (LPP) on an Event Indicates what portion of the Event Value affects the local Region and should be applied to the Multipliers. When the LPP of a good or service is less than 100%, the remaining portion (or 1-LPP) is then assumed to be affecting a different Region. This leakage will occur in a Commodity Output Event or an Institutional Spending Pattern Event when the LPP of a Commodity is less than 100%.
DETAILS ON DIRECT LEAKAGES BY EVENT TYPE
The Direct Effect Leakage fields are only applicable to specific Event types. Industry Events will only generate leakages from applied Margins, whereas the Commodity and Institutional Spending Pattern Events will generate leakages from Institutional Production and/or Imports to Region.
|Event Type||Institutional Production||Margins||Imports to Region|
|Institutional Spending Pattern||X||X|
INDUSTRY OUTPUT EVENT
When an item is purchased via a retailer or wholesaler, the price paid by the consumer (Purchaser Price) differs from the actual price of the produced product (Producer Price). Value Chains describe how a good changes in value, after its produced, through the process of selling the good via a wholesaler or retailer, but does not change physically from the factory door to the final sale. The Value Chain can be thought about as the transportation component.
When analyzing an Industry Output Event in one of the Retail or Wholesale Industries, the Margin is set to ‘Purchaser Price’ by default. Unless the setting is changed to ‘Producer Price’ by the user, IMPLAN will interpret that Event Value to be the Purchaser Price or total sales received by the retailer or wholesaler. IMPLAN will then apply that Industry’s Margin to only capture the effects from the retail or wholesale operation portion of the total sales (Price of Retailing or Wholesaling). If Producer Price is selected, IMPLAN will apply the entire Event Value to the Retail or Wholesale Industry and there will be no Direct Effect Leakage.
For example, an Industry Output Event in Industry 406 - Retail - Food and beverage stores set to Purchaser Price would indicate that the Event Value was the total sales made by the Retail Food Store. The Margin for Industry 406 is approximately 33.21%, which is the portion of total sales that the Retailer gets to keep out of the total sales price.
If the Event Value was $1,000,000, then the Direct Effect Output for this Event would be $332,061 ($1,000,000 x 0.33206 = $332,061).
In this case, the remaining portion $667,939 or 66.79% of the $1,000,000 would be considered a Leakage. Here we can see the Direct Effect Leakage displayed under the Margins column.
COMMODITY OUTPUT EVENT
Commodity Output Events are most appropriate to use when an analyst knows there is a change in Commodity demand or production but does not know which Industries or Institutions will meet that demand. Remember, a Commodity is a good or service which may be produced or sold by one or more Industries or Institutions. The portion of the total locally-produced supply of a Commodity that is produced by an Industry or Institution in the Region is known as its Market Share.
When analyzing a Commodity Output Event there are two Event Options that a user must specify: the Local Purchase Percentage and Margins. However, Margins are only applicable on Commodities that can be sold via a wholesaler or retailer, known as Marginable Commodities. If the Commodity selected is not sold via a retailer or wholesaler, the default Margin is set to Producer Price. Meaning that the entire Event Value will be distributed to the Producers of the Commodity based on their Market Share. The order of operations for Commodity Events are different depending on whether the Commodity is set to Purchaser or Producer Price.
When any Commodity Event is set to Producer Price, then the Margin is equal to 100% and there is no option to change the Margined Commodity LPP. So the order of operations is:
Event Value x Event LPP x Market Share
For Purchaser Price, the total Event Value must be distributed across the Value Chain, prior to distribution amongst the Commodity producers. The order of operations is as follows :
Event Value x Margins x Margined Commodity LPP x Market Share
For example, Commodity 3001 - Oilseeds is not sold directly to consumers through a wholesaler or retailer, so the default for this Commodity is set to Producer Price. However, this scenario would be identical had we chosen a Marginable Commodity, like Commodity 3002 - Grains and set the Margin to Producer Price.
Following our order of Operations for Producer Price, we need to take the Event Value multiplied by the Event LPP, then distribute to all Producers based on their Market Share. The Market Share distribution for Commodity 3001 at the national level shows that Industry 1 - Oilseed Farming produces 89.41% and the remaining 10.59% is sold by the Federal Government or taken out of Inventory.
If we create a Commodity Output Event with an Event Value of $1,000,000 for Commodity 3001, we would expect each Industry or Institution to receive a portion of the Event Value based on their Market Share. Therefore, Industry 1 - Oilseed Farming, will receive $894,114 ($1,000,000 x 89.411% = $894,114). The portion that is distributed to Institutions or taken out of inventory is considered a leakage. As such, the remaining value $105,886 ($1,000,000 - $894,114 = $105,886) will be displayed in the Direct Effect Leakage table under Institutional Commodity Production, as shown below.
In this example, the Event LPP was left at 100% which is not always the case. If a user set the Event LPP to anything less than 100%, then the Event Value would be reduced by that amount. Essentially, the user is telling IMPLAN that only a portion of the sales/purchase occurred locally, the rest was sourced from outside the Region. The remainder would then be displayed in the Direct Effect Leakage table under ‘Imports to Region’.
Let’s say we set the Event LPP = 60%. In that case, the $1,000,000 would be reduced to 60% or $600,000 of the Event Value. The remaining $400,000 was purchased from outside the Region and is considered a leakage. So, using the same Commodity the $600,000 would then be distributed to producers based on their Market Share. So our new results would be $536,469 in Direct Output ($600,000 x 89.411% = $536,469) and the Direct Effect Leakages would total $463,531 ($1,000,000 - $536,469 = $463,531).
The Direct Effect Leakage table shows $400,000 as Imports and $63,531 as Institutional Commodity Production.
When analyzing a Commodity Output Event on a Marginable Commodity (a Commodity which can be sold to consumers via a retailer or wholesaler), the user must select whether the Event Value represents a Producer Price or a Purchaser Price. When Purchaser Price (total revenue) is selected, the total Event Value must be distributed across the entire Value Chain first, prior to distribution amongst the Commodity producers. IMPLAN will follow this order of operations:
Event Value x Margins x Margined Commodity LPP x Market Share
In this scenario, there will be two areas where Direct Effect Leakages may occur. After Margins are applied, if the Margined Commodity’s LPP is less than 100%, this may result in a leakage due to imports. Lastly, if any producers of the Margined Commodities are Institutions, this will result in a leakage due to Institutional Commodity Production.
Let’s look at an example, analyzing a $1,000,000 Commodity Output Event for Commodity 3002 - Grains at the national level, set to Purchaser Price.
By selecting Edit, we can explore the Value Chain of this Commodity to identify each of the Margined Commodities. By Default, the Margined Commodity LPP is set to Social Accounting Matrix (SAM) or the Regional Purchase Coefficient (RPC) for that Commodity. The entire Value Chain and LPPs can be edited by the user. Any changes to these would alter the Direct Effect Output and Leakages for this Commodity.
For this Commodity Event, there are 7 Margined Commodities in the Value Chain. The percentage that each Margined Commodity receives is their Margin with the total summing to 100% or Purchaser Price. In this example, the Producer’s Margin is roughly 71%, the wholesale Margin is less than 1%, retail Margin is 17%, and the total transportation Margin is 11%.
|Code||Commodity Description||Margin||LPP||Local Sales|
|3398||Wholesale services - Grocery and related product||0.85%||100%||$8,508|
|3406||Retail services - Food and beverage stores||17.08%||100%||$170,812|
|3414||Air transportation services||0.24%||81.1%||$1,955|
|3415||Rail transportation services||4.32%||100%||$43,230|
|3416||Water transportation services||2.50%||100%||$24,984|
|3417||Truck transportation services||3.57%||100%||$35,723|
Using the Order of Operations for this Event, the Output Event Value of $1,000,000 is distributed to the Margined Commodities in the Value Chain based on their Margin. After Margins are applied to the Event Value, each Commodity’s value is then multiplied by the Margined Commodity LPP to determine the Local Commodity Sales. The LPP for all Margined Commodities is set to ‘SAM’ or RPC by default. The last step is to then distribute the Local Commodity Sales to the producers of each Commodity based on their Market Share of supply.
In this example, only Commodity 3002 and 3416 are produced or sold by Institutions (for 3002 = 10.11%, 3416 = 0.26%). For those two Commodities, the total Commodity Sales are reduced by those amounts. This results in a Direct Effect Output of $909,943 and Direct Effect Leakages of $90,057 ($1,000,000 - $909,943 = $90,057).
The Direct Effect Leakage table shows $19,703 as Imports ($1,000,000 - $980,297 = $19,703) and $70,354 as Institutional Commodity Production ($980,297 - 909,943 = $70,354).
INSTITUTIONAL SPENDING PATTERN
Institutional Spending Patterns, like all Spending Patterns, are made up of a list of Commodities. Because Institutions are Final Demanders, in the case of Institutional Spending Patterns, each Commodity in the Spending Pattern is treated like a Commodity Output Event and will create a Direct Effect.
As each Commodity is treated like a Commodity Output Event, when analyzing an Institutional Spending Pattern Event there may be Direct Effect Leakages due to Imports and Institutional Production. Each Commodity listed in the Spending Pattern is already set to Producer Price, meaning that Margins have already been accounted for. Therefore, the order of operations for this Event will be identical to a Commodity Output Event set to Producer Price. So the order of operations for each Commodity listed in the Spending Pattern is as follows:
Event Value x Event LPP x Market Share
For example, an Institutional Spending Pattern Event for 12002 - State/Local Govt Education with an Event Value of $1,000,000 will be multiplied by the distribution percentage of each Commodity purchase in the Spending Pattern. As shown below, Commodity 3002 - Grains is 0.00755% of the total spending by that Institution, therefore the Commodity Event Value of that purchase will be $7,550 ($1,000,000 x 0.00755%). The LPP for all Commodities is set to ‘SAM’ by default but can be changed to a user-defined percentage.
Let’s say we leave the LPP set to the default ‘SAM’ or RPC value and run this Event. In that case, the $1,000,000 would be distributed to each Commodity in the spending pattern then multiplied by the RPC of each Commodity to get Local Commodity Sales. The other portion that is not sourced locally is considered a leakage and will be displayed in the Direct Effect Leakage table under Imports.
The Local Commodity Sales value is then distributed to producers based on their Market Share. The results of our analysis would be $983,449 in Direct Output and the Direct Effect Leakages would total $16,551 ($1,000,000 - $983,449 = $16,551). The Direct Effect Leakage table shows $4,105 as Imports and $12,446 as Institutional Commodity Production.
NOTE ON DATA AND DOLLAR YEARS
All examples in this article were analyzed using the US Totals Region in Data Year 2019, with the Group Dollar Year set to 2019. This allowed for easier calculations between the Direct Effect Output and Direct Effect Leakages. If the Group Dollar Year and Results Dollar Year Filter are different from the Data Year, the results will not add up to the total Direct Effect Input Value. This is a result of different Industry Deflators being applied to the producing Industries used in the analysis.
Updated August 30, 2023