Because ZIP Code files do not include Trade Flow Data, they cannot be used for standard MRIO Analysis. However, there may still be times when we would like to estimate how an impact in a group of ZIP Codes will ripple into a larger functional economy. While the mock MRIO methodology is not as accurate as a true MRIO analysis, it is a way to make a rough estimation of the flows from your core ZIP Code region to the larger region of interest.
Trade Flow Data are not available at the zip-code level because there is no solid data for tracking commodities from ZIP Code to ZIP Code at this time. This affects Zip Code files in 2 primary ways.
- MRIO analysis will not be possible with models built from these files.
- The econometric Regional Purchasing Coefficient (RPC) methodology is used for creating Multipliers for these files. Thus in order to get comparable Multipliers between a ZIP Code file and county or state level file, you will need to change the county or state file build to the econometric RPC method.
Why isn't the mock methodology ideal?
There are a couple of caveats that have to be understood about a mock MRIO methodology.
- Econometric RPC: While this methodology for estimating trade is certainly acceptable, it is a limitation that comparing ZIP Codes to larger Models brings to every circumstance. The Econometric RPC methodology is an accepted standard for Input-Output Analysis, but the methodology dates back to the 70s and is now recognized to have some inherent flaws of overestimation for local impacts.
- The beauty of a true MRIO Model is that each region in the analysis keeps its unique economic identity. Thus Output per Worker relationships, Labor Income per Worker relationships, Value Added to Intermediate Expenditures ratios, and other unique identifiers that contribute to the Multipliers are all maintained for each specified region. With a mock MRIO, we don't have the ability to keep these unique identities, so rather than seeing how the ZIP Code makes purchases from the county and the county from the ZIP Code region, our larger Study Area provides results that average the ZIP Code region's unique identity with the identity of the remaining ZIP Codes in the region.
The basics of the Model are actually pretty straightforward. You can also approximate MRIO for ZIP Codes with the following methodology.
1. Create a model and run the impacts on the ZIP Code region of your choice.
This is done in the same manner that you would run any analysis in any Model. More information about running an analysis can be found here.
So we now have the first portion of our results from our ZIP Code Model.
2. Create a Model for the region into which you would like to see the ripple effects stem.
In this example we have built the corresponding state file for which we want to see the ripple effects.
3. Run the same set of impacts on the larger study area model.
Customize the Event in the larger study area so that it exactly matches the Event in the zip code area. To streamline the process, you can simply import each of the impacts straight from your ZIP Code Model.
- Go to Activity Options > Import > From Another Model.
- Then select your ZIP Code Model.
- Click Open to view the screen below.
- Select the Activity or Activities that you want to move from the ZIP Code Model to your state Model, and select Import. You now have the Activity or Activities needed to run your Scenario and see your results.
4. Subtract the results from ZIP Code Model from the results in the state Model.
Typically we recommend copying and pasting the results to Excel, or exporting them, to do the math. This difference is the extra impact from the feedback loops between the modeled regions.
|State||Impact Type||Employment||Labor Income||Value Added||Output|
|Zip-Code Area||Impact Type||Employment||Labor Income||Value Added||Output|
|Difference||Impact Type||Employment||Labor Income||Value Added||Output|