Michelin has decided to build a tire manufacturing plant in Anderson County, South Carolina. Construction is supposed to begin in two to three weeks and once completed the plant will take on up to 500 new workers. County officials also estimate that they will see “spinoff jobs coming to the county.” According to Input/Output in Analyst, this means that they’re looking to add 777 new jobs into the economy, which will help the 8,000 workers who are currently unemployed. We’ll take a closer look at this impact in a moment.
This disclosure has of course gotten lots of attention, including a mention in The Wall Street Journal. And it is a big deal. It’s the biggest jobs announcement that the county has seen in years. Naturally, it’s too early to tell whether this is the key to overhauling the county’s economy, but it’s certainly a big step.
Site Selection
So how and why did Michelin pick Anderson County? According to the article, the three big factors were: (1) the company already had a presence in the region, (2) state and local tax incentives were favorable, and (3) the workers in the county are not unionized. There were surely other variables that went into its decision.
To get a better handle on those variables we can use an input-output model, which is part of EMSI’s Analyst, to see why Michelin might choose to locate in the area. This is a great opportunity to show you how to use Analyst to aid economic development in your region.
Calculating Spinoff Jobs, Using Input/Output
First, for a region to decide what kinds of tax breaks to offer a company, it has to gauge the benefits of having the company locate in the region. This means that it needs to understand the total impact of a new employer.
When the county officials mentioned “spinoff jobs,” they were speaking of an economic idea that comes straight out of modern input-output (IO) theory (as measured by EMSI’s Input/Output tool). In this case spin-off jobs are the additional jobs that occur in the region due to the related supply chain and worker income spending effects.
The following silent video shows you how to use an IO model to generate this number:
NOTE: Because we don’t know exactly how Anderson County conducted the analysis, we’re taking certain liberties with our example here. The article says that these 500 jobs will be added to Anderson and Lexington counties, but, to keep our example simple, we’re only adding them to Anderson County.
According to the model, the region will gain almost $50 million in earnings through the addition of these jobs, and a total of 777 jobs. The average earnings of the jobs added will be over $62,000 per year. In Anderson County’s case, these might be some of the numbers that county officials looked at to help influence the benefits package they extended to Michelin. These figures — the money brought into the region, the jobs, the earnings — make a pretty compelling case.
First, let’s discuss the job figure.
Our analysis says that about 777 jobs would be created. That includes the 500 jobs we just added. Then it includes additional 277 spin-off jobs added as a result of increased added business input purchases and increased consumer spending. The IO model takes a lot of supply chain and personal consumption purchasing behavior into account and makes it quite easy to estimate the number of additional jobs generated by this change.
Let’s unpack the idea behind these spin-off jobs.
Because industries within a region are interconnected by input purchases, when you add workers in one industry, other industries feel the effects. These effects are primarily based on supply chains in the region.
Supply chains are the strings of industries from which a given industry satisfies its goods and services input needs. Tire manufacturing requires goods and services from synthetic rubber manufacturing, and carbon black manufacturing, and many others. The industries that tire manufacturing relies on make up its supply chain.
We’ll refer to this image here as we move through these effects.
The initial effect is comprised of those 500 jobs we added. The direct, indirect, and induced effects all result in the spinoff jobs.
The direct effect flows out of the initial impact. Those 500 jobs mean that this industry becomes more active. Tire manufacturing then requires more activity from its supply chain. As the supply chain industries increase their production, they boost their employment. This results in that gain of 74 jobs listed there.
The indirect effect is really a secondary supply chain effect — these jobs result from the supply chains of tire manufacturing’s supply chain. This happens when tire manufacturing’s increased activity prompts job gain in an industry like synthetic rubber manufacturing, which sets off the same kind of reaction in its own supply chain. Those 8 indirect jobs result from this process.
The induced effect is a much broader effect, as evidenced by the number of jobs represented there. Think of this as the grocery store effect. We’ve added 500 jobs due to our initial effect, 74 due to the direct effect, and 8 due to the indirect effect, for a total of 582 jobs. Those 582 jobs are new to the region. They represent 582 new paychecks. And those paychecks get spent. They get spent on whatever you spend your paycheck on. This increase in economic activity results in grocery stores hiring more workers, or new grocery stores moving into the area. As the region grows, more restaurants flow in. The mall expands to meet the needs of new shoppers, and so on. These 582 jobs result in 196 additional jobs, due to the induced effect.
(Note: Our more attentive readers will have noticed that 582 plus 196 is 778, which is one more than 777, which means that we’ve got some fractional jobs in there. Nothing to worry about.)
Staffing Patterns & Finding Occupations
There are a number of ways we can talk about the occupations that staff industries. The goal is to show that a region has the sorts of workers the industry needs. We could go as far as getting into the skills that the jobs in the industry rely on, but for now we’ll just focus on finding the jobs the industry needs and looking at how they’re doing in the region.
Before we go further, just a quick reminder on the difference between occupations and industries: industries are groups of businesses that all engage in producing the same good or service. McDonalds and Burger King are both part of the fast food industry. Occupations are the actual jobs that people have, like manager, or line cook, or cashier.
The following video walks us through how we can interact with an industry staffing pattern in Analyst. The staffing pattern will let us look at all of the occupations within an industry.
Here are the three primary things we can draw out of this data.
(1) More information about the industry. Now that we know the occupations the industry will be looking for, we’re just better informed about their needs. This is going to facilitate conversations, and bolster credibility.
(2) Are the occupations growing or declining? In this instance they’re declining. We’re looking at a period from 2006-2011, so surely some of these workers have left the region. But perhaps some of those 37 tire builders in the region are still around and unemployed or under-employed.
(3) We’ve also got data here for the 2011 median hourly wage. We can give the employer an idea what the going rate for these occupations might be.
One more thing: in this situation it might not be a bad idea to also pull up the data for the entire state again. The following video will demonstrate that for you, briefly. We’re going to switch from the Anderson County region to a region containing all of the counties in South Carolina. (These are regions that I built for this example, not regions that preexist in the tool.)
Now that same report that showed us all of the occupations in tire manufacturing for Anderson County shows us all of the occupations in tire manufacturing for the entire state. Now we can compare between the two. We can see if occupations declining in Anderson County are also declining in the rest of South Carolina, and compare the wages at the county level with those at the state level.
We can use staffing patterns to gain insight into this industry in the region and help employers get a picture of what locating in Anderson County will be like.
Conclusion
That’s a fairly thorough description of how to find and understand the spinoff jobs in your region. This figure helps community stakeholders form a cohesive picture of what this new addition to the region will mean, which helps them decide what kinds of incentives they’re willing to offer.
Obviously, this sort of analysis might occur at various points in the process of attracting a business. If the company has expressed interest in your area, you might start with this. If you’re pursuing a company, it could happen later on in the process. But it’s sure to be an important step that helps everyone measure the value of the scenario and get on the same page.
If you have any questions about doing this kind of analysis for an opportunity arising in your region, let us know, and we’ll be glad to help.
Find out more about EMSI here. You can reach us via Twitter @DesktopEcon or by emailing Josh Stevenson. Illustration by Mark Beauchamp.
