IMPLAN Pro System Requirements

INTRODUCTION:

So you aren’t ready to move to our new platform app.implan.com?  We understand. This article is just for you to ensure that your Pro desktop system keeps running smoothly for you in an ever-changing world of technology.

 

OPERATING SYSTEM:

At this point, there is no limit on what Windows Operating System is required for IMPLAN Pro.  However, changes may occur that impair the functionality as Windows is continuously being updated.  This is one of the main reasons that we are working hard on our new platform at app.implan.com. 

 

.NET FRAMEWORK

Software applications require .NET framework to run on Windows. You really don’t need to know anything about this to run IMPLAN, but you may run into an error message that will prompt you to update your .NET framework.  

 

Pro_Requirements_-_dot_net_error.PNG

So it isn’t really an update, it’s actually kind of a downdate since it requires an older version. Depending on the permissions you may or may not have on your computer, you may need to loop in your IT team.

Use your computer’s Search Bar at the bottom left of your screen to find the “Turn Windows Features On or Off” option in order to activate the older version of .NET Framework

Pro_Requirements_-_features.png

Turn on the version of .Net Framework that was unchecked:.

Pro_Requirements_-_Turn_On.jpg

 

Now attempt re-downloading the IMPLAN Pro software. If this still gives you issues you may need to consult your IT Team to ensure they can activate .NET Framework 2.0.

 

FURTHER SUPPORT:

If your version of IMPLAN Pro still isn’t working, please contact your Customer Success Manager at support@implan.com or 800-507-9426.

Known Issues in IMPLAN

INTRODUCTION:

This article is designed to offer IMPLAN users some important descriptions of, temporary solutions for, and status updates regarding known technological issues which have been identified and are actively being addressed within IMPLAN. Should you encounter any issues which are not addressed in this article, please let us know by contacting us at (800) 507-9426 or at support@implan.com. Issues which were previously identified, but have since been resolved, are documented in IMPLAN’s product release notes which are published upon the release of new features and capabilities within the IMPLAN tool.

 

ISSUES BEING ADDRESSED:

Each of the technological bugs described below have been identified and are being addressed (as you read!) by the IMPLAN Product Team. So don’t worry—we’re on it! But, should you encounter any of these issues between now and the deployment of their official fixes, there are workarounds which can provide effective (albeit manual) solutions in the meantime.

 

1. MRIO ANALYSES TAKE LONGER TO FINISH CALCULATING RESULTS

The Issue
An MRIO study requires a much higher number of calculations than non-MRIO studies as the trade of all the sectors are analyzed between regions. As such, we expect these types of studies to take longer to finish than non-MRIO studies. The amount of time it takes to finish will depend on the number of events and the number of groups that the user has entered. The expected time for an MRIO analysis to finish can range between a few minutes for smaller studies to several hours for larger studies.

The Workaround
The best practice for MRIO and other larger studies is to leave yourself lots of time to run the analysis! Keep an eye on the Progress Panel in the lower right corner of the Impact screen that will provide notification of the progress of the study. Notification will be provided if the study has timed out. That can happen for various reasons with the most common being that the size of the study exceeds our processing limits. While we have made great strides in increasing the processing power, you still may see longer wait times. That said, in order to minimize wait times or potential for “timing out” with regard to processing performance, we suggest limiting your MRIO analyses to a) include a maximum of ten Events and b) limit your number of combined Groups to four or five. If your MRIO analysis absolutely must include more than ten Events or Groups which contain more than three Combined Regions, we suggest that you contact your Customer Success Manager at 800-507-9426 or support@implan.com to personally discuss potential strategies for managing the size and/or complexity of your study.

 

2. WHEN RUNNING MULTIPLE STUDIES, SMALL STUDIES CAN TAKE AN UNUSUALLY LONG TIME TO FINISH

The Issue
The user kicks off a large study and wants to run a second study while the first is processing. Even if the second study is a small study, it doesn’t finish in the expected time frame.

The Workaround
The best practice for larger studies, including MRIO that we expect to take longer, is to plan ahead. Run smaller studies first since studies that are kicked off after a large study get placed in queue and will not start until the large study has completed. This is to prevent too much data hitting the server at once and crashing the system. The second study analysis will automatically begin without any further action from the user.

 

3. GROUPS WITH MORE THAN 100 EVENTS MAY NOT COMPLETE.

The Issue
Groups with more than 100 events may not complete or may take a long time to complete.

The Workaround
We are still exploring, testing, and discovering the current limits of the tool’s processing power and the amounts of data that it can communicate to our servers at any one time. That said, in order to minimize wait times or potential for “timing out” with regard to large studies, we recommend keeping the number of Events in your Groups to less than 100. If your study requires more, contact your Customer Success Manager by calling 800-507-9426 or emailing support@implan.com to personally discuss potential strategies for managing the size and/or complexity of your study.

 

4. FILTERING IN REGION OVERVIEW

The Issue
When looking at the data in the Regions Overview, there is an intermittent issue facing filtering.  In a section that requires the use of a filter to choose a specific Industry or Commodity, the list of possibilities is not always populating after the first use of the search.

The Workaround
To do another search, just navigate back to the same screen and the Industry or Commodity list should be there again.  

 

5. ALL EVENTS WIPING OUT DESPITE SAVING THEM 

The Issue
If the users time out on the impacts screen, all events are being erased even if their work is saved. This occurs when a user is idle for too long causing the project to crash. Our product team is actively working towards fixing this issue. 

The Workaround
We recommend that a user leave the impact screen while the project is running or any other time that they are NOT actually active creating or editing on the page.

 

6. NO NOTIFICATION WHEN AN INDUSTRY DOES NOT EXIST IN A REGION 

The Issue
When running an Industry Event on a Sector that does not have any activity (no Output, no Employment, etc.) in the Region used in the analysis, the user will get all zero results. This is because there is no data or Sector averages for that industry in the Region, which is necessary for IMPLAN to estimate the effect of some change in that Sector within the given Region. IMPLAN does not provide any notification to the user that the Sector does not exist. When running an Industry Event on a Sector that doesn’t exist in the Region in combination with other Events that successfully produce non-zero results, it is very possible to overlook the fact that one of the Events has produced all zero results. 

The Workaround
You can ensure the Sectors you will be impacting exist by checking for data on the given Sector in the Region Details. Study Area Data (Industry Summary table) is a great place to check. Users can model the effects of a new Sector being introduced to a given Region by either first adding the Sector by customizing your Region and then modeling the effect using an Industry Event or by taking an Analysis-by-Parts approach

 

7. THE EVENTS TEMPLATE WILL NOT UPLOAD EVENTS WITH INDUSTRY SPECIFICATIONS GREATER THAN 536

The Issue

When uploading large numbers of events using the events template, industry specifications cannot be greater than 536 sectors. For the 2018 data set and later, this means that industries 537-546 cannot be included in an events template.

The Workaround

We would encourage that you familiarize yourself with our special industries before using them in a study. As industries 537-546 are commodity-only or administrative payroll specifications, it is unlikely that they would be included for a study that makes use of the events template. If you need to include them, these industries can be added manually by clicking “Add New Event.”

 

8. DIRECT OUTPUT EFFECT OF COMMODITY EVENTS NOT EQUAL TO EVENT VALUE WHEN THEY SHOULD MATCH

The Issue

When only Industries are the producers of a Commodity in a given Region (according to the Commodity Market Share), 100% of the Event Value for these Commodity Output Events should generate Direct Output. Therefore, when Dollar Year on the Impacts Screen matches the Dollar Year on the Results Screen the Event Value and Direct Output Effect should be exactly equal. Things are working just fine when Dollar Year and Data Year are the same in the Impact Screen. The issue arises whenever Dollar Year and Data Year on the Impact Screen do not match. In this situation, currently, there is some discrepancy between the Event Value and the Direct Output when there are multiple Industry producers (and no Institutional producers) even though these values should match when Dollar Year in the Impact Screen and Results Screen are the same.

The Workaround

Aside from disregarding the slight discrepancy, a workaround to this issue is to multiply the Commodity Output Value by the Commodity Market Shares to convert the Commodity Output into Industry Output. The portions of Commodity Output produced by Industries can be analyzed as multiple Industry Output Events.  

 

9. CUSTOMIZED REGIONS

The Issue

Chrome is the recommended browser for using IMPLAN.  When customizing a Region, if you are using Edge as a browser, it will not allow any number below one to be entered. 

Once you have completed your Region customization, the Customized Region will not automatically appear in the Selected Region field. 

The Workaround

Once you have completed your Region customization, search for and select the name of the Customized Region in the search field on the Region screen. The Region will be shown in the Selected Region field. If the Region is still building your will see a spinning wheel on the Region window. Once the Region is built, you can check for your customization Behind the i

 

10. NORMALIZATION RESETS UNEDITED LPP’S TO THE SAM VALUE

The Issue

In an industry spending pattern, the option to set a local purchase percentage for each commodity is available. If you uncheck the box labeled “SAM” which sets the LPP for the commodity to the RPC pulled from our Social Accounting Matrix (SAM), the software will update the LPP to 100%. If you uncheck the SAM box to set to 100% and then use the Normalize feature, the checkbox is reset to the SAM value.

The Workaround

The appropriate methodology would be to make edits to your commodities and normalize, then set custom LPP’s if they are known. If you would still like to enter LPP’s before normalization, any commodity that you intend to have a 100% LPP for should have the LPP field cleared, and a “1” entered.

 

11. FALSE ERROR AFTER CANCELING A PROJECT

The Issue

If you are running a project, hit cancel, hit run again, and then navigate away from the Impacts Screen, when you return to the Impacts Screen a coral error bar will appear. There is actually no error, however.

The Workaround

Good news! There is nothing you need to do (aside from ignoring that coral error message).

 

12. COMMODITY EVENTS AND USER-DEFINED LPP

The Issue

When using a Commodity Event, with Total Revenue (default) selected, and changing the LPP to anything besides the default 100%, the change in LPP is not sticking.

The Workaround

This fix is in the works and should be out soon. To adjust for this, only enter the percentage that you want applied to the multipliers in the Event Value.

 

13. COMBINED REGION NAME CHANGE

The Issue

If you have two Combined Regions with the same name, and you run a project using one of them, you may find the name changed when you return to the Impacts screen.

The Workaround

Have no fear on this one. Although the name may have changed, because you have two identical Combined Regions with the same name, IMPLAN just pulled in the other name for it.

 

Total Revenue versus Marginal Revenue

INTRODUCTION:

When a good is purchased via a retailer or wholesaler, the price that is paid (Purchaser Price) for the good differs from the actual Producer Price of the good.  This is because it includes the cost for transportation and the cost of the wholesale and/or retail service of selling the good conveniently to the consumer. The cost of transportation and the wholesale/retail service are called Margins. The Producer Price of a good plus the costs of Margins equals the Purchaser Price of the good. 

TMR1.png

Margins are only applicable when you are modeling Industry Output Events with a retail or wholesale Sector specified and when you are modeling Commodity Output Events with a Commodity specified that can be sold via a retailer or wholesaler. Margins are not applicable to Industry Employment, Employee Compensation, or Proprietor Income Events. When you are in a scenario where Margins are applicable, you can indicate in the Advanced Menu of the Event whether your Event Value is a Total Revenue value, equivalent to Purchaser Price, or if your Event Value is Marginal Revenue, equivalent to Producer Price. When choosing between Total Revenue and Marginal Revenue is not an option, the Event Value is assumed to be the Producer Price. 

TRM2.png

MARGINS IN INDUSTRY OUTPUT EVENTS:

TOTAL REVENUE

Total Revenue represents the increased income resulting from the total sale of goods and services. IMPLAN defines Total Revenue as Total Purchaser Price of Commodities Sold. Total Revenue in an Industry Output Event, with a retail or wholesale Sector specified, indicates to the software that the Event Value is a retail/wholesale sales price (Purchaser Price) and includes Margin Costs for transportation, wholesaling, and retailing services, in addition to the Producer Price of the goods sold. 

In the case of applying Margins by selecting Total Revenue in an Industry Output Event, there is no way for IMPLAN to identify the good/Commodity purchased.  Therefore, the only impact that will be estimated is the portion of the Event Value that gets assigned as the Margin cost associated with the Sector specified in the Event.  This means, when Total Revenue is selected in an Industry Output Event with a retail or wholesale Sector specified, there will only be a Direct Effect in your Results to the Sector specified and it will only be a portion of the Event Value. 

For example, let’s say we know visitors during a week long event in our Region spend on average $15 per day at the gas station. If there are 1,000 visitors spending $15 per day at gas stations in our Region for 7 days, the total spending at the gas stations by these visitors would be $105,000. To model this in IMPLAN we’d be limited to modeling this via an Industry Output Event with the “Retail – Gasoline stores” Sector specified because we do not know the good/Commodity that these visitors are purchasing at the gas station. It is likely mostly gas, but they are likely also purchasing things like snacks and slushies. Because the $105,000 is the total spending by visitors at the gas station, this value is a Purchase Price and we should leave “Total Revenue” selected in the Advanced Menu to apply Margins. 

 TRM3.png

The 2017 Retail Margin Coefficient for the Sector Retail – Gasoline stores Sector is .164.  This can be found in the 2017 COMMON (IMPLAN5) MARGINS.

This means on average 16.4% of Total Revenue at a retail gas station is the retail gas station’s revenue, or Marginal Revenue. This Marginal Revenue is the value of the retail gas stations service of selling goods in a convenient place; in other words Marginal Revenue in this example is equivalent to the retailer’s Output. 

Therefore, when this Event is Run, we’d only see $105,000 x .164 = $17,220 of Direct Output to the Retail – Gas Store Sector and no other Direct Effects (when Dollar Year = Results Dollar Year). The other $87,780 of spending at the gas station would be a leakage in this analysis because without knowing which Commodities were purchases with the $105,000, IMPLAN cannot appropriately estimate what portion of the $87,780 is the Producer Price of Commodities and what portions of this value is the transportation cost and wholesaling cost. 

Note: When additional Event Values are entered in the Advanced Menu (Employment, Employee Compensation, and/or Proprietor Income) IMPLAN assume that even when Total Revenue has been selected in the Industry Output Event, these values can only be known for the Sector specified, the retailer or wholesaler. Therefore, no Margins will be applied to these values. Margins are only applicable to the Output Event Value. 

MARGINAL REVENUE 

Marginal Revenue represents the increased income resulting from the sale of one or more unit of goods and services. Marginal Revenue in an Industry Output Event with a retail or wholesale Sector specified indicates to the software that the Event Value is a only the Producer Price of the goods sold, and does not include any Margin Costs for transportation, wholesaling, and retailing services. 

By selecting Marginal Revenue in an Industry Output Event with a retail or wholesale Sector specified, you are indicating to the software that no Margins should be applied, and therefore the full Event Value will be applied to the multipliers of the Sector specified, just as the software would treat the Event Value for a non-retail/wholesale Industry Output Event. Although it is possible to know the Marginal Revenue to a retailer, it is much more common to know the Purchaser Price paid at the retail/wholesale establishment than the Producer Price.

MARGINS IN COMMODITY OUTPUT EVENTS:

TOTAL REVENUE 

Total Revenue in a Commodity Output Event indicates to the software that the Event Value is a retail/wholesale sales price or Purchaser Price and includes Margin Costs for transportation and wholesaling/retailing services in addition to the Producer Price of the goods sold. 

There is a difference between applying Margins by selecting Total Revenue in Industry Output Events and Commodity Output Events. When the item purchased is known you should use a Commodity Output Event. Total Revenue is still the appropriate selection when only the price paid at the retailer/wholesaler is available to you. Instead of specifying the retailer or wholesaler where the item was purchased, the Commodity purchased should be specified. Margins cannot be applied in Industry Events when a non-retail/wholesale Sector has been specified. 

This is very different than the previous gas station example when we only knew that $105,000 was spent at the gas station.  Now, let’s assume we know $100,000 of the $105,000 is spent specifically on gas at the gas station. By using a Commodity Output Event, specifying Commodity 3156 – Refined petroleum products and leaving “Total Revenue” selected in the Advanced Menu, IMPLAN estimates the impact of the full Event Value, unlike in the case of applying Margins to an Industry Output Event. IMPLAN will use Commodity margins to distribute the Total Revenue to each producer in the Value Chain. This process converts the provided Total Revenue into Marginal Revenue values for the producer, transporter(s) and wholesale/retailer(s).   

When taking this approach, it is recommended to check the “SAM” box in order to set your Local Purchase Percentage (LPP) to the Regional Purchasing Coefficient (RPC) as shown below. This will set the LPP for the production of each Commodity in the Value Chain to the Regional Purchasing Coefficient for the respective Commodity. This tells IMPLAN to assume each Commodity will be purchased locally at the same rate in which each Commodity was on average purchased locally during the Data Year.

 TRM4.png

2017 Margin Coefficients for the Refined petroleum product Commodity: 

Sector

Margin Sector

Margin Coefficient Value

3156

3156 

0.63

3156

3395

0.19

3156

3402

0.17

3156

3408

0.00002

3156

3409

0.001

3156

3410

0.002

3156

3411

0.008 

3156

3413

0.005

Total

 

1.00

Data can be found in the document  2017 COMMON (IMPLAN5) MARGINS.

When examining the Margins for Commodity 3156 -Refined petroleum products, we see the full list of Margins above. The Margin from 3156 to 3156 shows the Margin Coefficient Value as 0.63. This means 63% of the Total Revenue is Marginal Revenue/Producer Price of refined petroleum products (gas) purchased at the gas station. 

Commodity 3395 – Wholesale trade distribution services represents 19% of the total cost. Commodity 3402 – Retail services – Gasoline stores gets allocated 17% of the retail purchase of the gas.  The same goes for Commodities 3408-3413; all transportation sectors. 

Therefore when this Event is Run, we see Direct Output Effects to each Sector that produces the above Commodities in the Region. 

To illustrate this, here are the Detailed Direct Output Results of this Event analyzed as if the gas station in our example is located in Mecklenburg County, NC (2017 Data Year): 

TRM5.png

These Direct Output Effects sum to $36,403.14 rather than the full Event Value modeled, $100,000, largely due to the setting of LPP to SAM. Notice there is only $52.52 of Direct Output in Petrochemical manufacturing and $14.15 in Extraction of natural gas and crude petroleum (both producers in the Region of refined petroleum) even though the Producer Price for the gas according the Margins was $100,000 x .63 = $63,000. This is because in Mecklenburg County, NC 2017 the RPC for refined petroleum is only 0.11% (found in Region Details > Social Accounts > Reports > Commodity Summary, in the Commodity Averages Summary table see “Average RPC” column). The remained of the $63,000 is a leakage, suggesting most of the gas pumped in Mecklenburg County is produced outside of the Region. The largest Direct Output Effects are to the Wholesale and Retail Sectors because these services are the most locally available portion of the Value Chain in this example. Nonetheless, this approach captured much more of the local impact of the hypothetical visitor gas spending than using an Industry Output Event in the Retail – Gasoline stores Sector. When we took the approach of using an Industry Output Event in the Retail – Gasoline stores Sector the only Direct Output Effect was to the specified retailer of $17,220 based on a Total Revenue of $105,000 (based on $100,000 of Total Revenue this value would have been $100,000 x .164 = $16,400). Notice here in the case of our margined Commodity Output Event, Direct Output Results are quite similar for Retail Gasoline stores at $16,523.72, shown above (based on a Total Revenue of $100,000). In addition to the Direct Effect on the gas station Sector, we also see the local Direct Effects to gasoline producers, transporters and wholesalers.

MARGINAL REVENUE 

By selecting Marginal Revenue in a Commodity Output Event, you are indicating to the software that no Margins should be applied, and therefore the full Event Value will be analyzed as Output of the specified Commodity. 

Marginal Revenue is most commonly the appropriate selection in a Commodity Event when the Commodity specified in the Event was not purchased via a retailer or wholesaler, even though it is available via retail/wholesale sellers. For example, large corporations often source goods directly from manufacturers, but households would purchase these same goods via a retailer. 

Let’s reconsider our example of retail spending at the gas station. If we knew the price of the gas produced by the petroleum refinery before the gas was shipped out, we could enter this Producer Price as the Event Value of our Commodity Output Event with the Refined petroleum products Commodity specified, and select “Marginal Revenue” in the Advanced Menu of the Event.  Again, it is possible to know Marginal Revenue to a producer, but it is much more common to know the Purchaser Price paid at the retail/wholesale establishment than the Producer Price.

MARGINS IN SPENDING PATTERN EVENTS:

Spending Patterns in IMPLAN are made up of a list of Commodities, so think of Spending Patterns as a grouping of Commodity Events. The key difference between a Spending Pattern and a grouping of Commodity Events is that the Spending Pattern Event will not produce a Direct Effect. Learn more about using Spending Patterns and groups of Commodity Events in the context of Analysis-by-Parts here

Another variation between Spending Pattern Events and Commodity Events is that the value of each Commodity within a Spending Pattern can only be edited by updating the coefficient associated with the given Commodity. The coefficient on each Commodity reflects the spending per dollar of Intermediate Expenditures (by default) or Output, depending on what is selected in the Advanced Menu of the Spending Pattern Event. There is no option to apply Margins to the Commodities within a Spending Pattern Event because they are already marginned. As mentioned, when Margins are not applicable the Event Value is assumed to be the Producer Price/Marginal Revenue. The same is true for the coefficients associated with the Commodities of a Spending Pattern Event. 

Because Spending Patterns in IMPLAN are marginned, the coefficient for each Commodity in a Spending Pattern reflects the portion of spending that will be allocated as the Producer Price of each Commodity. Therefore, the coefficient on retail/wholesale Commodities in a Spending Pattern reflects the portion of spending that will be estimated as the Marginal Revenue to the given Commodities. 

Hospitals: Modeling Public & Nonprofit Hospital Impacts with Analysis-by-Parts

Hospitals: Modeling Private Hospital Impacts with Analysis-by-Parts

INTRODUCTION

If the hospital you are modeling is private, you can simply model spending through Industry 490 – Hospitals.  As always, enter as much data for the Industry Event as you have (Output, Employee Compensation, Proprietor Income, and/or Employment).  If you have data for more than one of these elements, you can (and should) override IMPLAN’s estimates with your known values.   

You can also modify the Industry Spending Pattern and couple that with a Labor Income change to account for any known spending differences in the hospital you are modeling.  This technique is known as Analysis-by-Parts (ABP).

 

EXAMPLE

Let’s say a new private hospital is going to open in Mecklenburg County.  We are told they will spend $5M in operations and $1.5M in Employee Compensation (EC) in their first year.  We have no information about Proprietor Income (PI), so we will only enter EC.  Remember, Labor Income = EC + PI.

 

ABP_-_Private_Hospital_Impacts.jpg

 

If we are given any further information on the proposed spending by Commodity, we can click the Advanced button and edit the percentages of the Industry Spending Pattern.  We may know, for example, that they will not be purchasing anything from a retail store; instead using only wholesalers. We can zero out all Retail Services entering zero in the place of the current percentages.  Then, choose Normalize in the Advanced Menu so that the Sum of Percentages is again 100.0%.

 

ABP_-_Private_Hospital_Edit_Spending_Pattern.jpg

 

Now drag the two Events into the Mecklenburg County Group and hit Run.

Our Results give us Indirect and Induced effects, so we will need to add back in the Direct effect from the information we were given by the hospital.

 

ABP_-_Private_Hospital_Summary_Results.jpg 

To calculate our Direct effect for our example, we will examine the Output equation in the model by navigating to the Regions screen, choosing Customize, then selecting Industry 490 – Hospitals.

 

ABP_-_Private_Hospital_Customize_Region.jpg

You can use the template ABP – Recalculating Directs with TOPI and OPI to fill in your data. 

Direct Employment = known Direct Employment. If Employment is unknown, you can calculate it on your own by dividing Direct Output by Output-per-worker.  For this clinic, we know that Output is $5M and Output/Worker is $178,061, so we can divide them and find 28.08 Direct employees.

Direct Output = Intermediate Inputs + Value Added.  In this example, we know the total Output was $5M.

Direct Value Added = Direct Labor Income + Tax on Production and Imports + Other Property Income

    • From the Output equation, we know the average TOPI and OPI per worker
    • Multiply these figures by the total employment
    • Add Labor Income + TOPI + OPI 

Direct Labor Income = EC + PI.

 

ABP_-_Private_Hospital_Output_Equation.jpg

Now we have our final results table below showing our calculated Direct effect and the modeled Indirect and Induced effects.  

TEMPLATE

ABP – Recalculating Directs with TOPI and OPI

 

RELATED TOPICS

Hospitals: Considerations when Conducting Hospital Economic Impacts

Hospitals: Modeling Public & NonProfit Hospital Impacts with Analysis-by-Parts

ABP: Introduction to Analysis-By-Parts

 

CASE STUDY

The Economic Impact of Mayo Clinic: Now, Then & All Points in Between

Hospitals: Considerations when Conducting Hospital Economic Impacts

INTRODUCTION:

Hospitals can pose an interesting case for IMPLAN analysis. Many are large institutions with immense buying power.  But even the smallest of hospitals are anchor institutions, rooted in our communities and unlikely to close or move.  

Hospitals will be classified differently in IMPLAN depending on their legal status and how they operate. They also may have facilities that fall under more than one IMPLAN Sector. 

Across the United States in 2017, hospitals accounted for 2.5% of total Output and 2.6% of total Employment. Hospital services were split between the Hospital Sector (76.981%) and State/Local Government Non-Education (23.019%).  This means that about ¾ of hospitals across the country are privately held or are nonprofits, while ¼ are run by state and local governments. This data can be found for your study area on the Regions screen by navigating to 

Social Accounts > 

     Balance Sheets > 

          Commodity Balance Sheet > 

               Industry-Institutional Production 

and then using the Filters button to choose your Commodity of interest.  In this case, we used Commodity 3482 – Private Hospital Services.

Hosp_Intro_-_IxI.jpg

CHANGE IN DEMAND FOR HOSPITAL SERVICES:

We know from the Industry-Institutional Production information that the Commodity 3482 – Private Hospital Services is produced by both private Hospitals and State/Local Government Non-Education. If there was an increasing population and we wanted to model that change in demand for hospital services, we might not know what combination of private, nonprofit, or public  (government) hospitals will absorb the new influx of patients. In this case, running a Commodity Event would be the best option.  

SECTOR CONTRIBUTION:

Analysts may want to examine the entirety of the hospital industry.  In this case, the best method would be to conduct an Industry Contribution Analysis (ICA). ICA removes buybacks to the Sector(s) of interest and more accurately represents the true contributions of the Sector at the current level of production.

CONSTRUCTION OF HOSPITALS:

Hospitals invest significantly in construction projects and this construction differs greatly from building a new house or highway; therefore hospital construction spending should be modeled through IMPLAN Sector 52 – Construction of new health care structures.  Major improvements and renovations to hospitals should be modeled through IMPLAN Sector 62 – Maintenance and repair construction of nonresidential structures.  

All construction Sectors in IMPLAN exclude Furniture, Fixtures, & Equipment (FFE).  FFE consists of movable furniture, fixtures, and other equipment that is not directly attached to a building. Specialized medical equipment is also not included and therefore should be modeled separately.  

Additionally, any land purchases are not included in IMPLAN as the sale of the land has very little impact on the economy. The purchase of the land necessary for a construction activity should not be included as Industry Output for the construction sectors because land sales are considered asset transfers, where one person receives money while the other receives tangible property.  Thus, the land sale itself has no value in IMPLAN. Some small impact may be captured however, by creating an Event for real estate fees, and for large commercial projects legal fees.

OTHER HOSPITAL SERVICES: 

Hospitals may provide care beyond services that fall under Sector 482 – Hospitals.  For example, they may have on site home health care agencies (Sector 480 – Home health care services) or ambulance services (Sector 481 – Other ambulatory health care services).  Each of these functions should be modeled separately.

As with any type of analysis in IMPLAN, the more details you have available as the analyst, the more accurate the results.  You may have to split out a nonprofit hospital from its privately held ambulance service. Also, you may consider separately modeling the doctor and technician offices that are located on hospital grounds.  Each different function, which will fall under a different IMPLAN Sector, should be modeled as its own Event (of group of Events) so that the results can be examined for each of the business functions of the hospital.  

Physicians owning their own private practice are often sole proprietorships (LLC or S-Corp).  These sole proprietorships can be paid in different ways depending on the hospital; some might be considered wage and salary employees while others are contractors. Be careful not to double count the spending on these doctors in your analysis.

CAUTIONS:

Deciding what to include and what to exclude in your hospital economic impact analysis can be a very delicate balancing act.  While you may choose to include certain associated Sectors with your hospital impact, do not fall into the trap of adding every Sector that exists in the hospital supply chain.  Incorporating too much not only dulls the focus on the actual impact of the hospital, but it also lowers the credibility of the entire study.

You may want to assume that but for this hospital, there would be no regional impact in the Sector.  However, consider that other entities might expand or open facilities in the absence of the one you are modeling.  

COMMUNITY & HEALTH BENEFITS:

In order to model a real-life event in IMPLAN, the initial economic effect in terms of a spending or production change, needs to be determined. Some circumstances require additional assumptions by the analyst before modeling. 

A few extra steps may be necessary to determine the economic effect of a real-life event including socio-political impacts, environmental impacts, policy changes, price changes, forward linkages, and feasibility analysis.

Modeling tax impacts, like a change in Medicare or Medicaid benefits, falls under the umbrella of socio-political impacts.  Therefore, the spending behavior associated with the tax impact/change would need to be determined by the analyst before it can be modeled in IMPLAN.  These government policies can affect citizens in many different ways. For example, if a policy is enacted that decreases health care rates, households may spend the money that would have been spent on health insurance on something else. 

Another modeling consideration is the savings the hospital might see by decreasing emergency room visits in favor of encouraging patients to seek preventative care and health screenings.  The cost differential between the primary care and emergency care could be modeled as a cost savings to the hospital.

A final consideration is potential savings to companies for healthier employees.  Fewer sick days and lost productivity could be modeled. Additionally, the ability to work additional years might be modeled as productivity increases.

RELATED TOPICS:

Hospitals: Modeling Private Hospital Impacts with Analysis-by-Parts

Hospitals: Modeling Public & NonProfit Hospital Impacts with Analysis-by-Parts

ABP: Introduction to Analysis-By-Parts

CASE STUDY:

The Economic Impact of Mayo Clinic: Now, Then & All Points in Between

College: Modeling Public College & University Impacts

INTRODUCTION:

After reviewing Considerations when Conducting College & University Economic Impacts, you are ready to examine the economic impact of your public college or university. Public colleges and universities are vital to not only the education system, but also to our regional and state economies and this article outlines how to model their expenditures.  

Public colleges and universities contribute to local economic activity via different pathways, each of which ought to be evaluated separately for a robust economic impact study that best captures all the effects. The best way to model these impacts is through Analysis-by-Parts (ABP). In this example, we will use the Bill of Goods (BoG) approach and show spending across five categories: university operations, university labor, student spending, visitor spending, and capital expenditures.  Each school is unique, so each university impact can include any or all of these parts.  

 

THE PROCESS:

In this example, we will be studying our fictitious school,  Leontief State University.  It was named in honor of the father of Input-Output analysis, nobel prize winning economist Wassily Leontief.  LSU is located in Amherst, Massachusetts and we want to examine its impact on Hampshire County. 

STEP 1 – OPERATIONS EXPENDITURES

To begin modeling the impacts of operations expenditures, we will first examine the non-labor budget. In this example we will look at three example industries.  When modeling an actual university, there will likely be many more affected Industries. The budget information we know for Leontief State University is: 

Public_College_-_Table_1_Operations_Spending.jpg

For each of the expenditure categories, create a new Event. For each Event, choose Industry Output, then select the appropriate sector as the specification. Finally, enter the value of expenditures in that category. 

We recommend that you save your work after each new section of data is entered.

Public_College_-_Events_Screen_1.jpg

SECTOR 473 TRAP:

Unfortunately, there is no IMPLAN sector for public colleges and universities. The sectors in the IMPLAN sectoring scheme are limited to Private Sectors, Government Enterprises, or unique Government Institution “Sectors” that do not include spending patterns. Don’t fall into the trap of Sector 473 – Junior colleges, colleges, universities, and professional schools.

All public education, including K-12 schools through college, are captured in the Institution for State/Local Government Education. Standard Government Institutional activities are not part of the sectoring scheme and thus public colleges and universities are not represented in the Sector listing. This is because Government Institutions don’t have production functions or Multipliers.  Specifically, there is no direct relationship between sales and production for Government Institutions since they derive revenue from collected tax dollars and not sales. Public entities, including colleges and universities, require a different approach to measure impacts.

CONSIDERATIONS:

  • You can choose to model the effect of Commodity purchases rather than Industry purchases
  • You can enter as many events as you have line items in the budget you are modeling
  • Remember to apply margins as necessary
  • Also, remember to adjust the Local Purchase Percentage (LPP) as necessary; only local purchases should be included

ALTERNATE APPROACH:

An alternative approach, as opposed to modeling each Intermediate Expenditure through a Bill of Goods approach is to run the total Intermediate Expenditures value through the Institutional Spending Pattern that best reflects the industry you are modeling; in this case, State/Local Govt Education.  

However, the Institutional Spending Pattern for State/Local Govt Education also encompasses primary and secondary schools in addition to colleges.  Because of this, you may want to consider using the private sector as a proxy. In this case, choose Sector 473 – Junior colleges, colleges, universities, and professional schools. For more information on this approach, follow the instructions for Analysis-by-Parts: Using an Industry Spending Pattern Event with Labor Income Event(s).

STEP 2 – LABOR EXPENDITURES

Since labor costs were not modeled as a part of the school’s operations expenditures in Step 1, we will have to model them independently. Let’s say that Leontief State University tells us that Labor expenditures sum to $50 Million. To analyze this impact, we create a new Labor Income Type Event, with a specification of Employee Compensation, and a Value of $50 Million. This is entered on the same Events screen as the three Industry Output Events.

CONSIDERATIONS:

  • These should be fully loaded payroll values which include wage and salary, all benefits (e.g., health, retirement) and payroll taxes (both sides of social security, unemployment taxes, etc.)
  • If the University’s employees commute into the study area for work, then they should not be included in the Labor Income Event

STEP 3 – STUDENT SPENDING

Personal spending by students on non-college goods and services (like the classic textbook Input-Output Economics (Leontief, 1966) and Moscow Mules) will also have an impact on the local economy. To estimate these impacts, we will need to know how much they spend on personal items and which items they purchase. These can then be modeled by adding expenditures to an additional Industry Output Event, with the appropriate Specification.  Some considerations on what to include in student spending are outlined below. Additional details on outlining student spending can be found in Surveying for Input-Output.  Some items to consider including are:

  • Books
  • Transportation
  • Food & beverages
  • Alcohol
  • Recreation & amusement
  • Retail

At Leontief State, we know the average student spends according to the following table. With actual survey data, you will likely have more spending categories.  

We also know that LSU has 12,000 total students.

Public_College_-_Table_2_Student_Spend.jpg

STEP 4 – VISITOR SPENDING

Personal spending by visitors on non-college goods and services (like hotels, transportation, and restaurants) will also have an impact on the local economy. To estimate these impacts, we will need to know how much they spend on personal items and what they purchase. These can then be modeled by adding expenditures to an additional Industry Output Event, again with the appropriate Specification.  Remember, visitors will not spend their money in the same was as a college student. Consider spending categories such as:

  • Lodging 
  • Transportation to the city
  • Transportation within the city
  • Gasoline
  • Food & beverages
  • Retail
  • Recreation & amusement

From a visitor survey, we are given the following information from Leontief State for their estimated 25,000 annual visitors.

Public_College_-_Table_3_Visitor_Spend.jpg

STEP 5 – CAPITAL EXPENDITURES

If in addition to its operations, the college or university supported other economic activity in the region because of new campus construction projects (note that general maintenance and repair are part of the operational spending pattern), you can model the effects of these activities as well. This analysis can be done by adding expenditures to an additional Industry Output Event, with the appropriate Specification.

College impacts often have associated capital expenditure layouts that it may be desirable to consider within the analysis. When looking at these expenditures there are some important things to keep in mind.

  1. Typically investments in buildings and equipment are temporary in nature. While the building and equipment will continue, the actual expenditures on these items tend to be one time or of a short-term, non-recurring nature, as opposed to be year-over-year expenditures. Thus it is important that we distinguish these impacts from those that are recurring.
  2. For Furniture, Fixtures, and Equipment (FFE) or other major equipment purchases, it is important to consider if the purchase is from a manufacturing sector or if the purchase is actually through a wholesaler or retailer, as these will affect how FFE is modeled. In addition to this, if the equipment is not produced in the region of the model, it may be good to report on that expenditure, but not include it’s value in the modeling process.

For example, LSU just opened up a state-of-the-art new College of Statistics at a cost of $50M.  We can run this through an Industry Output Event in Sector 55 – Construction of new educational and vocational structures.  

Our Event screen now is fully populated with all of the information we have from LSU. When creating a long list of Events as in this example, give each a name that is easy to remember so that using the FILTERS button on the Results screens is straightforward.

Public_College_-_Events_Screen_3.jpg

STEP 6 – RUN THE IMPACT

Now either use the button at the top to select all or highlight each Event and drag them into your Group.  Next, hit run.

Public_College_-_Groups.jpg

STEP 7 – ANALYZE THE RESULTS

The results will show you the economic impact of all of the Events you entered which will include the Industry Events and the Labor Income Event. To look at the results by Event, use the FILTERS button and select which of the Events you would like displayed.  For example, choosing all three Operations Events and the Labor Event will filter the results to only include the economic impact of the university operations.  

University operations are yearly impacts.  Construction impacts occur only once. Therefore, we recommend that these are not reported together.  Remember to clearly label your tables and figures so readers have a clear understanding of your results.  

Total 2019 Operations Impact of Leontief State University on Hampshire County, Massachusetts

Public_College_-_Results_Operations.jpg

 

Total 2019 Capital Impact of Leontief State University on Hampshire County, Massachusetts

Public_College_-_Results_Capital.jpg

 

RELATED TOPICS:

Considerations when Conducting College & University Economic Impacts

Modeling Private College & University Impacts

Surveying for Input-Output

Tourism Spending

CASE STUDY:

Economic Impacts of California State University Northridge: How One University Campus Discovered Its Economic Significance

College: Modeling Private College & University Impacts

INTRODUCTION:

Now that you have read Considerations when Conducting College & University Economic Impacts, you are ready to examine the economic impact of a private college or university.  Private colleges and universities spend and save money in a very different manner than their public counterparts. Remember, each school is unique, so the more details that you enter in the model, the more accurate the results.

The goal of this article is to be a guide in framing your private college impact study.  Spending can be split across operations, university labor, student spending, visitor spending, and capital expenditures.  

 

THE PROCESS:

For this example, we will be looking at Input Output University (IOU), a four-year liberal arts school known worldwide for their advanced economic theory program.  They are located in Huntersville, NC in Mecklenburg County. We know that IOU spends $120 million in annual operating costs.  

STEP 1 – OPERATIONS EXPENDITURES 

If only total operations expenditures for the university are known, the total can be run through Sector 473 – Junior colleges, colleges, universities, and professional schools.  This Sector includes all private colleges and universities while excluding all public institutions. Note that some specialty, business, and technical schools are actually included in Sector 474 – Other educational services.

Private_College_-_Table_1_Operations.jpg

ALTERNATE APPROACH:

If detailed spending information is available, the same steps in Modeling Public College & University Impacts can be followed using the Bill of Goods approach.

STEP 2 – LABOR EXPENDITURES

Since labor costs were not modeled as a part of the school’s operations expenditures in Step 1, we can add this information to our Industry Output Event. IOU spends $90 Million on salaries and benefits to their 1,200 employees (note this was not included in the $1.2 million operations figure).  We can add the Employment, Employee Compensation, and zero out the Proprietor Income as there is no ownership entity for IOU.  

Private_College_-_Labor_Event.jpg

CONSIDERATIONS:

  • These should be fully loaded payroll values which include wage and salary, all benefits (e.g., health, retirement) and payroll taxes (both sides of social security, unemployment taxes, etc.)
  • If the University’s employees commute into the study area for work, then they should not be included in the Labor Income Event

STEP 3 – STUDENT SPENDING

Personal spending by private school students on goods and services (outside of tuition and fees paid to the school) will also have an impact on the local economy. To estimate these impacts, we will need to know how much they spend on personal items and what they purchase. Additional details on outlining student spending can be found in Surveying for Input-Output. Examples of potential spending categories include:  

Student Spending

  • Books
  • Transportation
  • Food & beverages
  • Alcohol
  • Recreation & amusement
  • Retail

IOU has 5,000 students and their yearly spending is outlined as follows: 

Private_College_-_Table_2_Student.jpg

STEP 4 – VISITOR SPENDING

Colleges and universities welcome sporting event spectators, patrons of the arts, parents, siblings, and prospective students to campus as visitors.  The spending by these visitors can be captured via survey and used as inputs in the model by adding expenditures to an additional Industry Output Event.  Consider spending categories such as:

  • Lodging 
  • Transportation to the city
  • Transportation within the city
  • Gasoline
  • Food & beverages
  • Retail
  • Recreation & amusement

IOU estimates that 15,000 total guests visit each year, for an average of two days,  and estimates their spending as follows:

Private_College_-_Table_3_Visitor.jpg

STEP 5 – CAPITAL EXPENDITURES

Often times, colleges and universities also like to show their economic impact in terms of large-scale construction projects.  IOU just opened a brand new dormitory at a cost of $2.1 million. This can be entered as an Industry Output Event in Sector 60 – Construction of new multifamily residential structures.  

Now we have a complete picture of IOU’s direct spending as shown below.  Remember to give each of your Events a memorable name so that using the FILTERS button on the Results screen is seamless.

Private_College_-_Events_Screen.jpg

STEP 6 – RUN THE IMPACT

Now either use the button at the top to select all or highlight each Event and drag them into your Group.  Next, hit run.

Private_College_-_Groups.jpg 

STEP 7 – ANALYZE THE RESULTS

The results will show you the economic impact of all of the Events you entered which will include the Industry Events and the Labor Income Event(s). If you want to look at the results by Event, use the FILTERS button and select which of the Events you would like displayed.  For example, choosing all three Operations Events and the Labor Event will filter the results to only include the economic impact of the university operations.  

Total 2019 Operations Impact of Input Output University on Mecklenburg County, North Carolina

Private_College_-_Operations_Impact.jpg

Total Impact of Input Output University 2019 Dormitory Construction on Mecklenburg County, North Carolina

Private_College_-_Capital_Impact.jpg

RELATED TOPICS:

Considerations when Conducting College & University Economic Impacts

Modeling Public College & University Impacts

Surveying for Input-Output

Tourism Spending

 

CASE STUDY:

Economic Impacts of California State University Northridge: How One University Campus Discovered Its Economic Significance

College: Considerations when Conducting College & University Economic Impacts

INTRODUCTION:

Examining the impact that a college or university has on a region is a common use case in IMPLAN, but the potential complexities warrant careful consideration when setting up and framing the study. The goal of this article is to help guide you in correctly framing your analysis and to increase awareness of some of the special considerations of college and university analyses.

 

CAPTURING NET NEW EFFECTS:

When considering our Study Area geography, a question can arise about the importance of where the funding originates when it differs from the location where the funds are spent.  

In IMPLAN, we are interested primarily in how and where money is spent, not its source. As long as we know that the money is new to the Study Area, we can consider these funds to create a measurable impact.

The idea of what new money is, however, can become more challenging when residents spend money on sporting events, conventions, fairs and other transient events, this spending is considered substitutive rather than new money to the region. This is an important designation because it means that rather than truly supporting economic change and growth in a region, resident money is simply shifting from one local venue to another. Resident spending only has a true ‘new’ impact in cases where the event draws out spending that would normally be saved.

In the context of college student spending, generally resident students aren’t counted. While they may have some short term impacts while setting up new households, the general spending they represent in the economy is not likely to significantly change beyond those one-time purchases. Why? The increase in their daily spending is offset by a decrease in their parents local spending.

When would this rule not apply? If you can make the argument that your university, college, or program is unique and thus kept the students from leaving the region. This creates a theoretical ‘new’ spending circumstance. Examples of this might be having a medical degree program or being a religious college. With these sorts of specializations an argument can be made that the students would have left the region but for these local programs.

If the goal is to see how a college or university fits within the regional economic ecosystem or no information on net new money is available, consider performing an Industry Contribution Analysis (ICA).  ICA can be used to estimate the relative extent and magnitude of an existing institution in the study area.

 

LIFETIME EARNINGS & LOANS

While we do not recommend looking at forecasting the prospective value of college student’s education on their economic potential, IMPLAN has been used as a factor in some of these scenarios. If you are looking at projecting earning potentials of students, please keep in mind the effects of loans. These loans must be paid back and thus reduce the earning potential of students and their ability to create effects on the local economies where they live. Some other caveats to consider if you are looking at these types of impacts are:

  1. Will students actually receive job placements in their target degree area, and how long will it take them to get the experience needed to get these jobs?
  2. How much of their increased earning is attributable to this degree, especially if their job is outside of their field or they go on to graduate school?
  3. Will the student remain in the region after receiving training?
  4. What percentage of students remain long-term in their degree field?
  5. How many open positions or places for advancement are available and are these accounted for within the calculation for potential future income generation?

 

DOUBLE COUNTING:

Impacts that involve multiple stages, like many college impacts, can easily incur scenarios for double counting. For instance, spending on tickets for sporting games may be a separate impact, but those ticket funds may also be accounted for as part of the college’s operations budget. Likewise, tuition covered by scholarships that are provided by the school creates no additional impacts because these are already accounted for in the college’s budget.  

It is important then, when framing the impact to consider where funds are captured. The total college operations budget should include all sources of revenue. Tuition is obviously captured here, but, depending on the school and the services or programs it offers, funds coming in from on-campus sporting events (such as ticket and drinks sales), campus owned bookstores, college owned dormitories, and college meal plans could also be sources of double-counting if they are also captured as part of student spending.

 

OPERATIONS AND CAPITAL IMPACTS

University operations are yearly impacts.  Construction impacts occur only once. Therefore, we recommend that these are not reported together.  There are two main reasons that we recommend that you do not report operations impact and capital impact together.  

  1. People love job numbers. It is not uncommon for studies that report rolled up construction and operational impacts to have job numbers that mix both temporary and ongoing Employment picked up and reported by others as the recurring Employment impact. This is one source of the idea that Input-Output Analysis studies overestimate impacts.
  2. The same principles apply to other economic factors as well. The Labor Income, Value Added and Output of the construction are occurring only over a short period of time and thus have a more limited impact than operational changes. This is best reflected when the two types of impacts are handled separately.

 

PUBLIC VERSUS PRIVATE SCHOOLS: 

There are many factors for the analyst to consider when modeling any institution of higher learning. Most importantly, public and private colleges and universities will follow very different spending and additionally will attract different students and visitors. The sheer size of some large public universities will lend them to have immense overall budgets. They also might see large influxes of visitors in town for a playoff game. Alternatively, universities that focus heavily on research tend to invest in the sciences as well as research and development activities and may not offer any sports programs.  Small fine arts schools might be more selective but have talented and famous alumni network that generously subsidizes their capital budget. Knowing the details of each school will ensure that the analysis is accurate and defendable. For details on the specifics on public and private college and university impacts, visit the pages below.

 

RELATED TOPICS:

Modeling Public College & University Impacts

Modeling Private College & University Impacts

Surveying for Input-Output

Tourism Spending

 

CASE STUDY:

Economic Impacts of California State University Northridge: How One University Campus Discovered Its Economic Significance

Casinos: Acing the Impact

INTRODUCTION:

Casinos and the gambling Industry are unique in IMPLAN and don’t follow a single Sector.  This article outlines a few considerations to bet on when modeling them.

 

THE GAMBLER:

One thing to keep in mind when thinking through casino impacts is that Output for casinos is revenue net returns to the gambler.  That means that the casino Output already excludes all of the payments made to those that walked away winners. This is total revenue less losses to the house. Your Output value may need to be adjusted to reflect that definition. 

 

CORNER POCKET:

Sometimes what seems like gambling, may be considered basic amusement.  Remember to check the IMPLAN Sectors or the NAICS codes to ensure that you are capturing the Industry you want to model.  For example, IMPLAN Sector 496 – Other amusement and recreation industries includes billiards and pool halls while Sector 490 – Racing and track operation covers dog and horse racing tracks.

 

NUMBERS GAME:

Running a basic casino through IMPLAN can be done through Sector 495 – Gambling industries (except casino hotels).  This assumes, however, that the only activity in the facility is gambling. Many modern casinos operate a few businesses under one roof; restaurants, retail, and hotels.  Splitting out the operations of each entity is the best way to model a casino with multiple businesses.

Following the definition of the BEA, IMPLAN separates the different business functions of both Sector 503 – Gambling industries (except casino hotels) and Sector 507 – Hotels and motels, including casino hotels (546 Sectoring scheme).  These are divided between  

  • Construction
  • Retail
  • Real Estate
  • Performing Arts
  • Gambling
  • Amusement
  • Hotels
  • Personal Services

The casino’s business may match multiple IMPLAN sectors and should be distributed appropriately.  Note that some entities within the hotel may actually operate as separate businesses. For example, a casino may contain a chain restaurant that would not be included in the Output for the casino.

 

ATLANTIC CITY TO YAVAPAI:

Gambling is not legal everywhere in the US.  Therefore, when you are trying to model it in your region, it may not exist.  You can borrow the Output equation from a comparable region or the national model as outlined in the article Adding an Industry by Customizing a Region or Adding an Industry that Doesn’t Exist Yet.

Also, a state may be drastically changing their laws.  For example, they could currently have a state lottery, which would fall under the same Sector as casino gambling. Adding a large-scale casino to the state would drastically change the spending that occurs within that Industry.  Even though Sector 495 exists, it may not reflect the spending that will happen when the casino opens.

Even when a state has legalized gambling, illegal activities might still occur.  At this point, they are not included in the BEA accounts (Fun Fact: Eurostat already addresses this in their data).  You can read all about it in the article Including Illegal Activity in the U.S. National Economic Accounts by Rachel Soloveichik.  Per the BEA’s Concepts and Methods of the U.S. National Income and Product Accounts, “these activities are excluded from the U.S. accounts because they are by their very nature conducted out of sight of public scrutiny and so data are not available to measure them.”

 

THE HOUSE:

Casinos are owned by different entities.  Corporately-owned casinos will fall under Sector 495 – Gambling industries (except casino hotels).  However, many casinos are owned by Native American tribes and these establishments will actually show up in Sector 526 – Other local government enterprises. 

 

RELATED ARTICLES:

Adding an Industry by Customizing a Region

Adding an Industry that Doesn’t Exist Yet

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