Spending Patterns can be thought of as the backward linkages or supply chain of the Industry. Spending Pattern Events are best used when modifications to an Industry’s Production Function are necessary that cannot be made with a standard Industry Event. When detailed information is known about the Industry’s spending, a Spending Pattern Event can be used and adjusted to reflect the specific purchases or ratios of purchases. Spending Patterns include all Intermediate Inputs for a given Industry.
One size may fit most, but maybe not all. While the Spending Patterns represent the average buying pattern and ratios of all firms in that Industry, it may not match the expenditure pattern of your firm. For example, if you are working with an organic farmer, you might note that there are no Sectors for organic farming. As a result your Indirect Effects include a large quantity of pesticides and herbicides that just aren’t appropriate. You can use the Industry Spending Pattern to adjust the purchases of your firm with your detailed knowledge of their spending.
The default in IMPLAN is set the Event Value of an Industry Spending Pattern to Intermediate Inputs. This includes the 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). When Intermediate Inputs is chosen, the Event Value will be run through the model.
However, only total Output may be known. Output is the total value of Industry production in producer prices.
- Manufacturing Sectors: Output = sales plus/minus change in inventory
- Service Sectors: Output = sales
- Retail & Wholesale Sectors: Output = gross margin (or Marginal Revenue)
When Output is chosen, the value will be multiplied by the total Gross Absorption percentage for the Industry before being run through the model.
INDUSTRY SPENDING PATTERN
Industry Spending Patterns allow you to build an Industry from data about its expenditures. The coefficients listed in an Industry Spending Pattern Event represent the amount spent on each commodity per dollar of that Industry's Intermediate Inputs.
An important note about these spending patterns is that the direct effect is not accounted for in the results.
Let’s say we want to model the Industry Spending Pattern for a new fast food restaurant (Industry 510 - Limited service restaurants) that is planning to open up in Rochester, NY (Monroe County). Opening up the Advanced Menu of our Event, we see the complete list of Commodities purchased by fast food restaurants in our Region.
We know that our restaurant, Stephanie’s Subs, has projected Sales of $5M. We also know that they will not be serving alcohol, so we want to eliminate this spending (Breweries, Wineries, and Distilleries). We can scroll down to find Commodities 3106, 3107, and 3108 and change the given percentage to 0% in each of them.
After our changes, we can see that the total percentage now sums to 96.29%. Clicking on the Advanced Menu allows us to Normalize the results so that they once again sum to 100%. Also, this is where we can reset the Industry Spending Pattern to IMPLAN defaults.
We also have the option to change the Local Purchase Percentage (LPP) inside the Industry Spending Pattern. The default in IMPLAN is that the LPP is set to the Social Accounting Matrix (SAM) value. Unless you know that the Commodity will be purchased locally, it is advised to leave the SAM value.
Now we are ready to hit Run and examine our Results.
Notice that there are no Direct Effects in our Results so we will need to add those back in manually. We know our total Output is $5M. Now we need to navigate back to our Regions screen and click on
Study Area Data >
Regions Industry Summary
Here we can find IMPLAN’s known totals for Industry 510 - Limited service restaurants for Output, Employment, Labor Income, and Value Added.
Calculating the ratio of Stephanie’s Output to the total Output in the county, we see her restaurant will be 0.5361% of the total. We can then apply this percentage to the other values in our impact to estimate the Direct effect. The template for these calculations is here.
Written September 4, 2019
Updated October 7, 2021