MRIO: Filtering Complex Analyses


When using Multi-Regional Input-Output (MRIO), with a few Events in a few Regions, it can become cumbersome to understand how the Filters will display your Results.  Here’s a guide on how to use the Filters to see the Results you want to report.





Let’s walk through an example with three Regions: A, B, and C. Here we have two Events generating Direct Effects to start; both in Region A. These Direct Effects in Region A created Indirect and Induced Effects in all three Regions as illustrated below.




Using MRIO, you can have Events in more than one Region. This example shows how we have Direct Effects now in Region A (Event 1 and Event 2) and Region B (Event 3). Each of these three Events now yields Indirect and Induced Effects in all three Regions.




The Results screen will default with no Filters applied and in the current Dollar Year. If you apply a Region Filter for Region A, your Results will display the total Effects to Region A as a Result of the analysis. In this analysis there are three Events, two of which occur in Region A. Filtering by Region A in this analysis will display the resulting Effects to Region A due to all three Events in the analysis. 





If you remove the Region Filter for Region A and replace it with a Filter for Region B, you will see total Effects to Region B due to all three Events in the analysis.





Changing the Region Filter to only include Region C will not yield a Direct Effect, as there was no Event that occurred in Region C. You will, however, see Indirect and Induced effects in Region C because of the three events.





If you remove the Region Filter completely and choose Event 1 from the Event Filter, your Results will display the total Effects of Event 1, in all three Regions.




Applying the Event Filter for only Event 2 will show the effects of only this Event in all three Regions.




Applying the Event Filter for only Event 3 will show the effects of only this Event in all three Regions.




If you remove all Event Name and Region Filters and instead Filter your Group Name for Group 1, you will see the impact of every Event in this Group (in this example Group 1 includes Event 1 and Event 2) across all three Regions.





Where things start to get complicated is when you add multiple Filters at the same time. You can Filter for any number of Event Names, Group Names, or Regions at the same time. Just be careful to ensure you know what you are seeing when you do so. In the example below, the Filter was set for Event 1 and Region C. Therefore, we are only seeing the Effects of Event 1 on Region C.




MRIO: Multi-Regional Input-Output Analysis FAQ

1. What data is required to create an MRIO?

In general, you need to have the data for your Core Region and the additional regions from which you want to see feedback linkages/impacts.

If you want to analyze data at a state level, you need to have State Package data. This data set allows you to create the Rest of State (ROS) Model by combining all of the counties in the state minus the counties where your Direct Effect occurs. These Direct Effect counties are endogenized in the State Total file, and thus you can only use a State Total file with counties that are not included in that state. Attempting to create an MRIO by linking Direct Effect counties within a state to the State Total file will produce erroneous results.

2. When would you use MRIO? Would you use MRIO if you only wanted to analyze the impacts to one specific county?

Both Single-Region and Multi-Regional Input-Output Analysis are valid methodologies. MRIO offers the advantage of providing a more robust and accurate picture of a local economy because most economies are not isolated to a single county.

An MRIO analysis allows you to keep the Multiplier identity of the core county (or region) while still being able to see how activity in the core region (where the Direct Effect takes place) touches other regions within a functional economy. Therefore, even if you were interested in the results in a single county, you could use MRIO if you wanted to capture feedback linkages to the core region from purchases your region made to those connected counties. However, in most cases this will not provide significant changes to your results.

3. Does the MRIO analysis provide a different net effect (or multiplier) than an analysis using only a single region?

The only way to determine the Multipliers associated to an MRIO anlaysis is to calculate them by hand. We recommend exporting or copying/pasting your results to an Excel spreadsheet and summing the results to calculate the Multipliers using the base equation Total Effect/ Direct Effect. Please read this FAQ article to get more information about summing results from an MRIO and calculating the new Multipliers. The reason the Multipliers are different from single-region Multipliers is that we are capturing leakages to the linked regions that are lost from a single-region analysis. Therefore, there may be feedback from linked regions that will increase the effects in the core Study Area Region as well as the additional captured linkages represented in the linked Models.

The reason that this is a recommend analysis type is that it avoids the Aggregation Bias of aggregating Model regions. The state Multipliers will represent an average of all the firms in the state and their relationships for Output per Worker and Labor Income per worker. These can be drastically different from those in a smaller region, a cluster, or an MSA. Users are occasionally confused when the state actually has smaller values than the region where the Direct Effects occur; MRIO avoids this apparent anomaly that occurs when the supply of a commodity is concentrated in a single geography or a small group of geographies in a state, and thus demand at the state level increases without a substantial increase in supply. This happens in examples like Silicon Valley when considering tech Sectors.

4. Does MRIO provide region-specific effects from the aggregate analysis or completely different results from an aggregate region analysis?

MRIO Multipliers are unique and will be different from the aggregate region’s Multipliers (a region where all the files have been built into a single Model). The Multipliers in an aggregate Model are a weighted average of the region’s individual Industries and are thus subject to Aggregation Bias. These Multipliers are displayed in the Multipliers screen in the Explore menu. Conversely, MRIO Multipliers are unique to each set of linkages and must be calculated for each analysis as at no point are the regional Study Area Data information from the different areas combined.

5. Is MRIO effectively quantifying the ongoing chain of impacts?

MRIO, in effect, extends the supply chain impacts into surrounding regions while still keeping the Multipliers for the core region intact and unique. Thus the rounds of additional impacts are extended to include feedback between all the linked regions until all purchasing dollars are leaked from the Indirect and Induced Effects.

6. Are you able to aggregate the impact results of all models in the MRIO analysis into an “Impact Summary” within IMPLAN instead of exporting to Excel?

Not at this time. Impact results of all models in an MRIO analysis must be exported in order to sum the results. This allows you to individually quantify each regional impact and provides the flexibility to sum the regional impacts together to get a Total impact.

7. How do you aggregate the counties into “regions” and the “rest of state”?

You do this through the Model build process. When you build your Models you will select all the regions that you want incorporated into a single Model and then build that Model. This article provides additional information on aggregating Study Area regions in the Model building process.

8. How do you calculate a Multiplier for an MRIO Scenario?

You take the Total Effect (the sum of all the linked regions and the core) and divide this value by the Direct Effect for each factor. For additional information on how this is done, please see this Knowledge Base article.

9. Do you need to enter the Activities into the linked models?

No, you only build the Activities in the region where your Direct Effect occurs. The Model linking process will calculate the impacts in the secondary Models. If you have Direct Effects in multiple regions, then you need to build a series of Models for each Direct Effect.

So let’s assume that we are dividing the state of CA into 4 regions: North California (NCA), North Central California (NCCA), South Central California (SCCA), and Southern California (SCA). If we only had impacts in NCA, we would need four Models: the NCA Model where Direct Effects are occurring and the three remaining Models we are linking to.

If we then have multiple Direct Effects in each region, we will need 16 Models: NCA, NCCA, SCCA, and SCA where NCA is the Direct Effect; NCA2, NCCA2, SCCA2, and SCA2 where NCCA is the Direct Effect; NCA3, NCCA3, SCCA3, and SCA3 where SCCA is the Direct Effect, and finally NCA4, NCCA4, SCCA4, and SCA4 where SCA is the Direct Effect. This prevents exponential explosion of the impacts from cross linking Models.

10. Where can I find information about the methodology IMPLAN uses to calculate the inter-regional flows of commodity?

We have a white paper in our downloads section that talks about the Gravity Model that lies behind the trade calculations. In addition, commodity flow data from the Bureau of Transportation is used as a Benchmark for the IMPLAN Trade Flows.

11. Where can I find additional documentation about MRIO?

We have some free documentation about setting up an MRIO on our website, and we also have available for purchase our Principles of Impact Analysis & IMPLAN Applications user manual. In addition, we can certainly assist you with analysis setup on our community pages.

12. Do ZIP code areas function similar to counties when conducting an MRIO Analysis?

MRIO is not viable for ZIP Codes at this time, as these data do not have Trade Flows. The level of data currently available at the ZIP Code level is too sparse for us to develop confident Trade Flows. However, there is a methodology for mock MRIO that can be done with ZIP Code level data and also Congressional Districts, which likewise do not have Trade Flow data.

Unfortunately, this means that if you add a ZIP Code or Congressional District level file to your county Model, the resulting Model will not be available for MRIO.

13. As an MRIO analysis links multiple study regions, how does IMPLAN determine each region’s share of the regional purchasing coefficient?

RPCs are calculated on the basis of the Gravity Trade Flow Model in the standard build (eRPC and Supply-Demand Pooling are also options you can exercise). The Trade Flows are also the basis of the MRIO analysis. This Trade Flow Model takes into account a variety of factors including the gravity of certain economies, impedences to trade, and cross-hauling.

14. How does MRIO take into account regions that border another country (Mexico)?

Unfortunately, IMPLAN does not have international trade flows at this time. Thus if imports are from outside the U.S., they are recognized by the Model as foreign imports/exports and are not tracked after they cross the national border. Therefore, international flows cannot be captured by the current Model. The Trade Flow data and MRIO are looking at domestic commodity flows.

Currently IMPLAN does not have data for most regions of Mexico, and therefore we are unable to develop Trade Flows at this time for North America; although, that is certainly something that we have in mind. It is important to note that the foreign imports/exports of commodities themselves are known, we just don’t have at this time flows to track where those foreign commodities are produced. This limitation is also exasperated by the limits of up-to-date raw data for international countries and their states and provinces.

15. How is MRIO’s ability to account for leakages an advantage over traditional Single-Region analyses?

Knowing where leakages go allows you to account for them. In a single region analysis, leakages are just lost. Thus, importing 75% of commodity A means that 75% of the value of commodity A is lost in the first round of the impact analysis. But in reality, that 75% goes to some economy somewhere. MRIO allows you to see if and how your impact in the core region is affecting surrounding regions. Thus if you can buy an additional 5% from region R2, then you can now account for (in region R2’s results) that 5% and demonstrate both where it goes and that it results from your change to the economy. Likewise, if that 5% in region R2 is spent on a commodity that can now be imported from region R1, you capture that additional round of impact.

MRIO: Multi-Regional Input-Output Analysis When More Than One Region Includes Direct Impacts


Sometimes you may have more complicated analyses that you want to run.  Let’s say the bank opening up in Mecklenburg County, NC from the Introduction to MRIO article will also be opening up a smaller office in York County, SC.  This can be modeled with Multi-Regional Input-Output (MRIO) analysis to see what the effect of each project will have on the two counties together and separately.




In our example, the new bank HQ will be opening in Mecklenburg County, NC with $500M in projected Output.  Taking this one step further, the bank plans to open a smaller back office facility in York County, SC with a projected $10M in Output.  As with the HQ example, this office will closely resemble a financial institution and not support services, so Sector 433 – Monetary authorities and depository credit intermediation was chosen as the sector.

First, on the Regions screen, select both Mecklenburg County, NC and York County, SC.  Click Create Impact.  

Create an Industry Output event in Sector 433 – Monetary authorities and depository credit intermediation for $500M.  Save the Event and drag it into the Mecklenburg County group on the right side of the screen.  

Create a second Industry Output event in Sector 433 – Monetary authorities and depository credit intermediation for $10M.  Save the Event with a different name than the first so that it can be identified later. Drag it into the York County group on the right side of the screen.  Each Region has its own Event associated with it.

Ensure that the MRIO checkbox at the top of the screen is checked.


Click Run.  When using MRIO, the software will take a little longer than a standard analysis.  Grab a cup of coffee and when the analysis is complete, click View Results.



When you look at the Results screen, you see the Total Direct Output of $510M; $500M in Mecklenburg for the HQ and $10M in York for the back office.  Together, they have an indirect effect of $131M and an induced effect of $82M, for a total economic impact of $723M. These results include the impacts of the HQ and back office locations on both Mecklenburg County, NC and York County, SC.

Mecklenburg County & York County Impact – HQ and Back Office


Unlike when there is only one region with an Event, now there are two options for Filtering the results.  We can see how the new back office operations (located in York County, SC) will spur economic activity in Mecklenburg County, NC. In the Region box, choose Mecklenburg and in the Event Name box choose “Bank Back Office.” Hit the run button on the right.


Notice that there is no Direct impact.  You do see a total Output impact of almost $5M. This is money that will flow into Mecklenburg County because of the $10M in bank back office operations in neighboring York County.

Mecklenburg County Impact – Back Office


By only filtering the Region for Mecklenburg, we will see the effect of the HQ and the back office on the county.  This shows us the Direct Output of $500M for the HQ, but not the $10M in Direct Output for the back office.


Mecklenburg County Impact – HQ and Back Office


If the Region is filtered by York County, you will see the effect of the HQ and the back office on the county.  This shows us the Direct Output of $10M for the back office, but not the $500M in Direct Output for the HQ.

York County Impact – HQ and Back Office


If you add the Economic Indicators from Mecklenburg and York counties, you will get the total Output impact of $723M seen before the Filter was applied.



Introduction to Multi-Regional Input-Output (MRIO)

Considerations when using MRIO

Size of Your Impact – Questions & Concerns about Small vs. Large Study Regions & MRIO

Multi-Regional Input-Output (MRIO) Analysis FAQ

MRIO: Size of Your Impact – Questions & Concerns about Small vs. Large Study Regions


Larger study areas tend to reflect larger impacts, because larger geographies typically capture more production as ‘local’ and are subject to less in-commuting. However, analysts are occasionally surprised to find that the economy of a smaller subset region, such as a county, reflects a greater Indirect and Induced impact than that of the larger aggregate region (i.e., the state). Although not exhaustive, this article does highlight the most common reasons for such an occurrence. One easy way to avoid these issues, if you are using IMPLAN Pro, is to use the MRIO methodology.

Detail Information

Why does this occur? How can a smaller region have greater Indirect and Induced Effects than it has when you include surrounding geographies?

Typically larger Indirect and Induced impacts in a smaller subset region are the result of areas of high production surrounded by more rural regions. This creates a situation where we see only a small bump in production between the smaller geography and the larger one, but a significant increase in demand. This change can be economy wide, or it could be related to a specific commodity as a result of regional specialization or clustering. In these areas, the supply relative to demand is much higher in the smaller region than in the larger region (i.e., the RPCs for what is regionally available in the smaller region exceeds that of the larger region). Therefore, the larger geography sees a much larger increase in demand for the products produced in the smaller geography but does not substantially increase the supply available to meet that demand. Wyoming is a classic example of this type of activity because there are few regions of supply and a vast state of demand.

These same principles can apply in regards to Labor Income and Value Added because the regions of greater production often pay higher wages per worker and may pay higher taxes (or be subject to additional taxes such as city taxes not collected in the rest of the county). Since Value Added = Labor Income + Other Property Type Income + Taxes on Production & Imports Net Subsidies, if either or both income and taxes are higher, or if profits are higher in the core region, “upside down” effects, where the results are higher in the smaller region (county) than in the larger region (state), may be generated.

When using Employment to estimate the impact of an Industry an additional caveat arises because a difference in Output per Worker can generate significantly variant Output estimates. If the Output estimate in the smaller region is substantially larger the Output estimate in the larger region, this can result in Indirect impacts in smaller subset regions being larger than in the aggregate regions. Production areas with a greater Output per Worker than the larger surrounding area may reflect a larger impact than the aggregated region as a whole.


Typically, when impacting a larger study region, the results will follow the “normal” pattern of the Indirect and Induced producing large impacts. However it is still advisable to match the Event values in the larger region to those of the county, as this results in a consistent estimate of the Direct Effects.

This same technique also works for adjusting these smaller regions that produce higher impacts than their larger aggregate. Modify the Event in the larger region to match the Event in the smaller region (e.g., same output-per-worker, same labor income per worker) will typically resolve this issue.

However, if sufficient data is availalbe, IMPLAN recommends MRIO (Multi Regional Input Output) rather than direct comparisons of the aggregate state file to a county subset. Before IMPLAN had MRIO capability, analysts were forced to:

  1. Choose the small region where the actual direct impact occurs but lose much of the indirect and induced impact to leakage.
  2. Choose a larger region to capture those leaked impacts, but now the impact location is less precisely defined.

This is no longer necessary with the ability to use MRIO. Now the smaller region can be chosen for the Direct impact while still affording analyst the ability to see the impact on the neighboring regions (and those regions’ feedback effects back on the smaller region). MRIO also allows for each region to keep it’s unique identity and for you to be able to see how the impacts in the core sub-region and the larger aggregate region occur.

MRIO: Considerations when using Multi-Regional Input-Output Analysis

Building your Economic Analysis with multiple regions utilizing MRIO (Multi Regional Input/Output) enhances your study. That is, MRIO demonstrates how an impact in your Study Area disperses into other regions and allows you to see how these effects in surrounding areas create additional local effects. For each Industry, MRIO not only tracks the imports from every other Industry, but also where those Imports are coming from. Each region’s production relationships and local purchasing abilities remain distinct. While the MRIO model will still lose the same dollar amounts as imports within the defined local area, these impacts will be visible in the linked models. Additionally, MRIO can look back to the original regional model and capture expenditures made in auxiliary regions that will impact the original local model, capturing impacts that are completely untraceable without MRIO capacity.

In the past, other MRIO methodologies have been attempted as the best available option, but were not true MRIOs. The following considerations demonstrate the problems that may be caused if MRIO is not utilized.

1. To create a comparable analyses, the Sector of the larger Model file will need to be modified to demonstrate local relationships.

The Industry relationships at the state or U.S. level would need to be forced to be the same as the Industry at the local level. This means that the US or state level Model’s Industry must have the same Output Per Worker, Earnings Per Worker, etc as the local Industry. This is the only way to attempt to adequately represent how the local Industry is making its purchases relative to the larger Model. However, this is just an approximation; the actual relationships with which the larger region would purchase products are unknown in this instance.

For additional information on performing this type of analysis click here.

 2. The local region and the larger region will have differences in internalized Imports, which cannot be adjusted.

The ability of a product to be sourced locally may be significantly higher at the state or U.S. level than at the local level (or in some rare instances, they may be lower). This in turn will impact the Multipliers of the model.

Additionally because there is no way to separate out the local region’s economy in standard analysis, the two studies and impacts must be considered as two completely independent impacts. Since the larger geographic region may include local purchases to what would be considered Imports in the regional Model, there may also be increased impacts resulting in the regional portion of the Model. Therefore even with the modifications in Consideration 1, the regional impacts which will accurately represent the local region cannot just be “subtracted” from the larger area.

MRIO: Introduction to Multi-Regional Input-Output Analysis


Multi-Regional Input-Output (MRIO) analysis makes it possible to track how an impact on any of the 536 IMPLAN sectors in a Study Area region affect the production of all 536 sectors and household spending in any other region in the US (state to state, county to county, zip code to zip code, county to multi-county, county to state, etc). Now you can demonstrate how an impact in your Study Area disperses into other regions and see how these effects in surrounding areas create additional local effects.  


Let’s say a new bank is opening up a HQ in your county and the state gave them a huge tax incentive to locate there.  Using MRIO you can show each county how the bank locating in one county will also impact their county, thus making it a valuable investment of state tax dollars.

We live in regional ecosystems and when running an impact analysis you can see how much money leaks out of your city through trade and commuting.  Using MRIO you can see where some of that leakage ends up – supporting other cities across the county or state. 

There are many reasons you may want to consider using MRIO.

  • To improve the methodology of your study
  • To improve the regional specificity and limit aggregation bias
  • To examine the interconnectedness of multiple regions
  • To track leakages from a study region and determining the impacts they create in other regions



MRIO expands backward supply linkages beyond the boundaries of a single-region Study Area.  MRIO analyses utilize interregional commodity trade and commuting flows to quantify the demand changes across many regions stemming from a change in production and/or income in another region. This powerful analytical method allows analysts to go beyond a single study region, measuring the economic interdependence of regions.

In an MRIO analysis, the Direct Effect in one region, Region A, can trigger Indirect and Induced Effects in linked regions, capturing some of what would have been a leakage in a traditional I-O model.

Let’s say a new firm is opening in Region A. Some of the construction inputs may be produced in linked Region B and are imported into Region A. Through this trade there is a production change in Region B that triggers a whole new change of spending in Region B. If the construction materials produced in Region B require an input produced back in Region A, thus creating a new branch of backward linkages in Region A. 

As always jobs supported by the new production and the affected supply chain earn income, but potentially workers in Region A will live in Region B and visa versa.  As dollars trickle to household spending, there is likely trade between the regions in the supply chain. For example, restaurants in region A frequented by the workers that reside in region A may buy produce from a farmer in Region B. The income earned by workers on the farm would trigger a new chain of labor income. Some of the farm workers may live in Region A, so household spending cycles through both regions. 

Trade and commuting dollars bounce between regions until they funnel through the rest of the economy or are leaked out as imports to other regions or through profits and taxes. 




Charlotte, NC is the second largest financial center in the US. For this example, let’s say a new bank will be opening and you want to see the effect not only in Mecklenburg County, NC, but also in neighboring York County, SC. 

First, on the Regions screen, select both Mecklenburg County, NC and York County, SC.  Click Create Impact. In some cases you may want to create Combined Regions to build a clustered surrounding area. For example, we want to additionally see the effect on the surrounding Charlotte MSA within North Carolina in which case we could select all the Counties in the Charlotte MSA in NC except for Mecklenburg County and Combine these Regions to form 1 new Region. We must exclude Mecklenburg if we are including it as its own Region, otherwise the effects in Mecklenburg will be double-counted in our MRIO Analysis. Combining Regions is beneficial especially within an MRIO Analysis because it will reduce the analysis run time.  



Create an Industry Output event in Sector 433 – Monetary authorities and depository credit intermediation for $500M.  This sector was chosen because the primary function of the HQ in this instance more resembles a financial institution than the traditional HQ functionality.  If the firm was following a traditional HQ, then Sector 461 – Management of companies and enterprises, would be the correct choice. For more information, visit the US Census Bureau.

Save the Event and drag it into the Mecklenburg County group on the right side of the screen.  No event will be added to the York County group as the bank will operate in Mecklenburg.  

Ensure that the MRIO checkbox at the top of the screen is checked.


Click Run.  When the analysis is complete, click View Results.


When you look at the Results screen, you see the Total Direct Output of $500M which has an indirect effect of $123M and an induced effect of $80M, for a total economic impact of $703M.  These results include both the impacts on Mecklenburg County, NC and York County, SC.

Mecklenburg County & York County Impact



In order to see how this new bank will affect its home county of Mecklenburg, we need to Filter our results.  In the Region box, choose Mecklenburg and then hit the run button on the right.


The Total Direct Output remains $500M, because the bank will be located within Mecklenburg.  However, the indirect and induced effects are only showing the activity within this county, so you see a total of $698M in Output impact.


Mecklenburg County Impact


If you change the Region Filter to York County, SC and hit run, you see the impact that the new bank in NC will have on York County, SC.  Notice that there is no Direct impact. You do see a total Output impact of almost $5M. This is money that will flow into York County because of the bank operations in neighboring Mecklenburg.


York County Impact


If you add the Economic Indicators from Mecklenburg and York counties, you will get the total Output impact of $703M seen before the Filter was applied.



MRIO works best with up to seven regions.  When possible, create aggregated regions to examine the effects on the other areas.  For example, to look at the economic impact on Mecklenburg County and the remainder of North Carolina, create a region of the remaining 99 counties.  

Every region has a unique set of commuter rates, trade flows, and region specific identities (Output per worker, Intermediate Expenditures to Value Added, etc.)  Therefore, you will see different results if you run an impact on a combined Region A + Region B versus an MRIO on Region A and Region B.



Regional Fission: How MSU Accelerated Their Research Facility Funding Using MRIO



Multi-Regional Input-Output: A Primer, How-To Guide, and Best Practices 



Multi-Regional Input-Output (MRIO): When More Than One Region Includes Direct Impacts

Considerations when using MRIO

Size of Your Impact – Questions & Concerns about Small vs. Large Study Regions & MRIO

Multi-Regional Input-Output (MRIO) Analysis FAQ