<img src="//bat.bing.com/action/0?ti=5564067&amp;Ver=2" height="0" width="0" style="display:none; visibility: hidden;">

IMPLAN Blog

Amazon HQ2: When the Losers are Winners

Photo by Osman Rana on Unsplash
November 12, 2018 by Tim French

After more than a year since Amazon’s deadline for RFP submissions, over 200 subsequent submissions, and a culling of 20 possible locations earlier this spring, we’ve finally (almost) got our answer—an HQ2 with one foot in Crystal City, Virginia and another in Queens, New York. And mere hours after the news broke, markets are already reacting in some rather severe (and not altogether unexpected) ways.

Earlier this year, we took a look at which cities might enjoy the greatest economic benefit from winning Amazon’s heart. But this bifurcation of HQ2 dynamically changes things. So let’s take a look at what this new scenario plays out—not only for the winning locations, but also for the loser cities (it's not all bad!) in the region.

Amazon’s Original Budget

This is part 2 of a 2-part series. Check out part 1, "Amazon HQ2: When the Losers are Winners," in which we share our heartfelt sympathy for our roommate Raleigh (and all the other cities which didn't win Amazon's heart). For more background, check out our analysis from earlier this year, "An Apples-to-apples Look at Amazon HQ2 Candidate Cities."

To recap, the inputs for our original analysis looked like this (based on Amazon’s own RFP):

Construction

Let's assume two years for each construction phase.

  • Phase I (starting 2019): $450,000,0000 (RFP lists $300,000,000-$600,000,000)
  • Phase II Building: $837,000,000 ($600,000,000-$1,260,000,000)
  • Phase III Building: $1,622,500,000 ($1,260,000,000-$1,985,000,000)

Operations

We’ll model the first ten years of regular operations wherein spending looks like this:

  • 50,000 Employment
  • $100,000 average compensation per employee
  • $1.4 billion operational expenditures (utilities and maintenance)

New Assumptions

For our new analysis, we’re looking only at the economic impact that results from investing in the two locations for HQ2 (rather than all 20 cities from our original study). Aside from that, here are a few more assumptions we’ve made for this revised analysis:

  • Even split: Actual costs may vary due to the difference in the cost of materials between one location and the other as well as the reality that one location may require more refurbishment than the other. For simplicity’s sake, we’re assuming equal expenditure between the two locations.
  • The study regions include states which contain not only Crystal City and Queens, but also 5 of the cities which made it to the top 20. The base regions where the direct effects will be felt are Virginia and New York. The linked regions are Massachusetts (home to Boston), Pennsylvania (Philadelphia), Maryland, North Carolina (Raleigh), and Washington, D.C.
  • Multi-Region Input-Output (MRIO) is the star of the show for this analysis. MRIO allows you to see the ripple effects that are generated in other regions that don’t take part in the direct effect. Ripple effects in other regions occur by way of supply chains and commuting patterns.
  • Broad Strokes: We’re looking at a state-by-state MRIO to get a big-picture perspective of how Amazon’s new HQ2 will affect the region. Taking the analysis down to the county level would surface insights such as regional commodity linkages, economic dead zones inside the states, and lots of other very interesting things. But if you want to get far into the weeds, then we should get together some time.

Our Findings

First, the states included on the maps are there because they were pre-defined as study regions. The reality is, if we were to look at every state in the Union, we’d find some effect—however marginal—due to the fact that the national economy is dynamically linked. Don’t assume that because there’s nothing on the map for some states that there wouldn’t be if we included them in the analysis.

Total Economic Impact

Total Employment Impact

 

A Note About Methodology

Some would argue that the best way to measure the sort of impact comparison that we’re looking at here would be with a computable general equilibrium (CGE) model. However, since Amazon reported the impacts of its HQ1 based on the results of an input-output model, I felt it best to follow suit—if for no other reason than to maintain thematic consistency (input-output modeling is not a reliable forecasting tool so the results we’re looking at are purely speculative).

IMPLAN is actually really well suited for this type of analysis! However, since HQ2 will be so large, it may have some pretty big effects of other types that IMPLAN can't get at (many of which CGE also wouldn't get at). The things it will miss (that should be considered separately if possible) are things like:

  • Environmental or Social issues (traffic, gentrification, wage effects, etc.)
  • Investment the city would have to make in infrastructure to support it (new roads, pipes, traffic lights, etc.).
  • What amount of money each city is putting up as incentive and what the city would have done with those funds otherwise (e.g., are we skimping on improving our roads and schools so we can incentivize Amazon?)

The IMPLAN modeling system can examine U.S., state, county, multi-county, city level, Congressional District, and international economies to assess the total economic impact of a variety of situations; a capital investment in a project, a business change, the economic consequences of natural disasters, the current value of a business to a regional economy, or the jobs supported by a local supplier.

By constructing social accounts that describe the structure and function of a specific economy, IMPLAN allows users to create localized models to facilitate investigation into the potential consequences of projected economic activities. IMPLAN allows you to identify and quantify the direct, indirect, and induced impacts of a business or project, or the economic contribution of an entire industry.

IMPLAN databases are constructed exclusively by IMPLAN’s team of PhD economists. All IMPLAN datasets use a set of annual national I-O matrices as the background framework for the software and database interaction. All data files include numerous economic and demographic variables at a 536 Industrial sector level. Data variables include employment, value-added (GDP), government and household purchases, taxes, and more.

Wrapping it up

Just because Amazon isn’t coming to your hometown doesn’t mean that you won’t see some economic impact from the new headquarters. Cities which were initially willing to offer immense tax incentives to attract the online retail giant’s attention might just see a significant economic boost at no cost to their municipal or state incentive programs by way of indirect expenditures that stem from the new headquarters. For those cities which are more far-flung from the new HQ2s, IMPLAN data can help you determine your strengths and areas of opportunity. Extending the scope of an economic impact analysis to include a gap analysis helps cities identify industries which would enrich their sector diversity and complement an existing labor force.

Whatever your economic need, we have the tool for you. Request a Demo.

Topics: Economics, Methodology

Why IMPLAN?

Put simply, IMPLAN is built for everyone.

With IMPLAN there are no black boxes. All of the background data used to create your personalized input-output models can be viewed and customized to reflect your Study Area. So now, what used to take economists weeks can be done in minutes. By anyone!

Reasons why IMPLAN is the best choice:

  • Easy to learn
  • Easy to use
  • Outstanding customer support
  • Instills confidence in your analyses

Subscribe to Email Updates

Recent Posts