ABP: Using an Industry Spending Pattern

Introduction

Analysis-by-Parts is a technique by which you can analyzed the impact of an Industry's production/spending in separate components using multiple Events instead of using a single Industry Event. The purpose of this article is to explain how to analyze the Intermediate Input portion of an Analysis-by-Parts (ABP) using an Industry Spending Pattern. Alternatively, the Intermediate Input portion of an ABP could be analyzed using the Bill of Goods approach. 

Detailed Information

Step 1: Intermediate Inputs - Industry Spending Pattern

To analyze the Intermediate Input portion of an Analysis-by-Parts, begin by adding an Industry Spending Pattern Event and selecting the Sector as the Specification that best matches the spending of the Industry or organization being modeled. Let's say we want to look at soda manufacturing in South Carolina in 2019.

• By default the Value entered in this Event should be total Intermediate Inputs, meaning 100% of the entered Value will be spent on the commodities included in the Industry Spending Pattern.
• Secondly, by default all the commodities in the Industry Spending Pattern will be modeled using the SAM value for local purchases.

Industry Spending Pattern Advanced Options

Opening the Advanced Menu

Click the Menu icon on the Event and choose Show Advanced Fields.

Intermediate Inputs vs. Total Output

This will display the default selection of Intermediate Inputs, indicating the Value entered in the Event should be the value of Intermediate Inputs. This can be changed so that Value entered should be Total Output, in which case the Total Gross Absorption for the selected Industry is multiplied by the Value before it is analyzed as spending on the Commodities included in the Industry Spending Pattern.

Whether Intermediate Inputs or Total Output is selected, the Sum of Percentages will stay at 100% unless you modify the Percentage on an individual commodity. 

Modifying the Percentages:

Change values in the Percentage column for an individual Commodity will adjust how much of the total spending on these Commodities will go towards the individual Commodity. You can redistribute the other Percentages so that the Sum of Percentages is back at 100% by clicking Normalize in the Menu. 

If you don't want to keep the changes you've made to these Percentages, you can Reset in the Other Options within the Industry Spending Pattern Advanced Menu as well. 

Modifying the Local Purchase Percentages

The Local Purchase Percentage, or LPP, in an Industry or Institutional Spending Pattern tells the software what portion of the line item Commodity was purchased locally and therefore affects the local Region.  The Industry Spending Patterns by default sets the LPP values to "SAM" (Social Accounting Matrix) value  for all Commodities. When LPP is set to SAM, LPP will be set to the Regional Purchasing Coefficient (RPC) for the given Commodity and Region. This is the proportion of local demand for the Commodity that is met (according to the Data Year) by local production in whichever Region the Event is analyzed within. If the LPP is known for a given Commodity, your own value can be entered as a coefficient.

You can change an individual Percentage for a Commodity by clicking in the box to the right of the name and simply typing the Value you want. The Value you changed will turn blue and the title will be appended to include that this Spending Pattern has been edited. Note that this will change the Sum of Percentages at the bottom and you may need to click Normalize to ensure you are spending 100% of the Value entered on your Impacts screen.

Unclicking the SAM box will default to an LPP of 100%. You can also override this by simply typing in the box the Value you want. Again, edited Values will turn blue.

You have the option to Reset the Spending Pattern in the Menu as well. The Reset function will also set all the LPPs back to 100%. Clicking this will prompt a popup that will ask if you are you sure you want to reset the selected Spending Pattern to its default as all changes and edits will be lost. 

Deleting Commodities

In the final column of the Industry Spending Pattern Advance Menu you will find a Trash icon in every Commodity row which will delete the given Commodity.

Adding Commodities

By clicking Show Advanced Fields from the Menu, you can also add a Commodity that is not currently a part of this Industry's Spending Pattern. A space for your new Commodity will show up at the bottom of the current Commodity list. You can then enter the Commodity, the percentage to be spent on that Commodity, and the LPP. 

Whether a commodity is being added or removed, the Sum of Percentages here again can be balanced back to 100% by choosing Normalize in the Menu.

Step 2: Labor Income (Direct Income Spending Induced Effects)

• Use Labor Income Events in the Impacts screen.
• Specification Employee Compensation should be paired with a Value of total income for Wage and Salary workers, and Proprietor Income should be paired with a Value of total income for self-employed workers. If the impact involves both types of labor, create 1 Event for each. 

Step 3: Run the Analysis

Drag and drop all Events created in Steps 1 and 2 into a Group. Be sure your Group has a title and the appropriate Dollar Year, Data Year, and Region have been selected. Then, hit run! 

Step 4: Interpreting, Editing and Reporting Results

What to expect in your Results

Since Direct results are not analyzed with this methodology, they are also not reported. Final results require adding the Direct Effects into the table and re-summing the totals.

Industry Spending Patterns are by definition the first-round of the Indirect Effects, so the results tables will show Indirect Effects and Induced Effects. The Labor Income Event(s) will only generate Induced Effects.

Direct Effects

To estimate the Direct Effects, take what information you already know for Employment, Labor Income, and Output and enter that directly. The template is on Recalculating Direct Effects will help you to estimate the remaining pieces based on data from:

> Region Details
     > Study Area Data
          > Industry Averages

TEMPLATE

Recalculating Direct Effects

Updated April 6, 2021