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

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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

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INTRODUCTION:

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.  

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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

 

HOW MRIO WORKS:

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. 

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THE PROCESS:

STEP 1 – SETTING UP THE REGIONS

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.  

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STEP 2 – SETTING UP THE EVENT

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.

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

STEP 3 – VIEWING THE 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

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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.

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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

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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

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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.

 

USEFUL TIPS:

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.

 

CASE STUDY:

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

 

WEBINAR:

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

 

RELATED TOPICS:

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

Personal Taxes

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Personal Taxes include Income Tax (net of refunds), Property Tax, Motor Vehicle License, Non-Taxes, and Other Taxes. Income Tax is paid not only on wages, but also on rental income, dividend income, interest income, and capital gains. Contributions for government social insurance are not included.

The effective personal income tax rate in IMPLAN is a weighted average of the individual rates, depending on the amount of each paid in a given region in a given year.  In IMPLAN, all personal income tax is assumed to be paid at the place of residence; however, in the real world, the personal income tax paid on wage income (which is part of what is withheld from your paycheck) is paid to the place of employment.  

For additional details, visit the IMPLAN Tax Impact Report.

Personal consumption expenditures (PCE)

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NIPA final-demand component for purchases by the household sector. In addition to showing what households spend, it also includes the current operating expenses of nonprofits that primarily serve households.  (BEA)

PCE bridge table

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Table that identifies the I-O commodity composition of each PCE category in the NIPAs. It shows the value of the transactions in producers— and purchasers—prices and the associated transportation costs and margins. (BEA)

Own-account construction

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(Previously force account construction). Own-account new construction refers to construction activities performed by businesses, governments, or persons for themselves rather than by purchasing from construction businesses. Beginning with the 1997 benchmark I-O accounts, own-account new construction is treated as being produced by the industries in which the construction occurs and then “purchased” in final uses as investment. In the 1997 standard make and use tables, own-account new construction, including output and all inputs, is shown as a secondary product of the industry in which the activity occurs. Previously, own-account construction was reassigned to the new-construction industry and included as part of its primary production. In cases where the general contractor for a new housing unit intends to be an owner-occupant, the resulting new construction is now shown in the owner-occupied dwellings industry. For government, it is now shown in the general government industry. Beginning with the 1997 standard and supplementary make and use tables, own-account maintenance and repair construction is no longer treated as output. Previously, own-account maintenance and repair activities were included in the maintenance and repair construction industry and then purchased by the industry producing those services. This change is intended to facilitate comparisons of data from the I-O accounts with other statistical data on industries. (BEA)

Output multipliers

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Derived from the I-O total requirements tables, the output multipliers show the amount of output required to satisfy a given level of final-use expenditures. For the commodity-by-commodity total requirements table, it is the production required both directly and indirectly of the commodity at the beginning of each row per dollar of delivery to final use of the commodity at the top of the column. For the industry-by-commodity total requirements table, it is the industry output required to deliver a dollar of a commodity to final users. For the industry-by-industry total requirements table, it is the industry output required to deliver a dollar of industry output to final users. (BEA)

Output

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Output represents the value of industry production. In IMPLAN these are annual production estimates for the year of the data set and are in producer prices. For manufacturers this would be sales plus/minus change in inventory. For service sectors production = sales. For Retail and Wholesale trade, Output = gross margin (or Marginal Revenue) and not gross sales (Total Revenue), which includes the value of the goods sold.   

For industries that do not hold inventory, output equals revenues (sales).  For industries that do hold inventory, output equals revenues less any net change in inventory (additions to inventory less sales out of inventory); for these industries, it is possible for a year’s sales to exceed that year’s value of production, if some of those sales came out of inventory (a previous year’s production); in I-O models, what matters is the value of production that occurred in a year, since production is what drives the purchases of inputs.  Sales of items that have been sitting in inventory do not generate indirect and induced impacts this year since they were produced in a previous year; thus, we don’t want to count them as part of this year’s output, else we’d overstate the indirect and induced impacts.

IMPLAN defines Total Industry Output as the Value of Production or Labor Income + Intermediate Expenditures + Tax on Production and Imports + Other Property Income. For detailed information about Output and its components visit Understanding Output (O).

Other value added (OVA)

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A term used prior to the 2003 comprehensive NIPA revision for the residual component of value added, sometimes referred to as profit type income. For most industries, OVA was derived by subtracting total intermediate inputs, compensation of employees, and indirect business tax and nontax liability from total industry output. It included consumption of fixed capital, proprietors\’ income, corporate profits, and business transfer payments. OVA has now been replaced by gross operating surplus (GOS). (BEA)
 
 

Other secondary products

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Secondary products that are neither redefined nor reclassified. For these products, which generally have inputs similar to those of the primary products of the industry where they are produced, BEA follows the Census classification. Thus, no adjustments are made that affect either industry or commodity output. (BEA)
 
 

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