Targeted Employment Areas: Where Are We Now

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As we approach the sunset of the temporary extension of the Regional Center EB-5 Program (the “Program”), there continues to be little consensus among lawmakers concerning how to define a Targeted Employment Area (“TEA”).[1] Currently, a TEA is defined as an area which, “at the time of investment, is a rural area or an area which has experienced unemployment of at least 150 per cent of the national average rate”.[2] Rural “means any area not within either a metropolitan statistical area (as designated by the Office of Management and Budget) or the outer boundary of any city or town having a population of 20,000 or more.”[3]

A project’s TEA qualification matters because when an EB-5 project is located in a TEA the investment amount required is $500,000 per investor instead of $1,000,000. Clearly, TEA status is a major benefit to the EB-5 project seeking investors.

There is much to discuss in properly defining a TEA. For example, the concept of “rural” seems simple and not problematic. However, that is not the case. For example, the EB-5 definition of rural requires that the project be outside of a metropolitan statistical area (“MSA”), which is a county or group of counties identified as having significant social and economic linkage. Unfortunately, OMB has redefined and expanded MSA delineations since the original EB-5 statute was written. In expanding the MSAs, OMB has included “outlying” counties, often with low populations, that by any reasonable measure should fit the rural concept envisioned by the EB-5 statute. For example, most would think that an area categorized by farmland would be considered rural. For example, Fort Royal, VA, a town of about 14,000 people, does not qualify as a “rural” location because its surrounding county is part of an MSA. The same is true for Crosby County, Texas with a population of less than 6,000 people. It is an outlying county within the Lubbock MSA, and so, it is not considered “rural.” Clearly, the EB-5 rural definition needs to be revisited.

There have been several proposals put forth on the correct methodology for TEA analysis. The purpose of this article is to consider the various proposals and explain what methodology would make the most sense from an economic and job creation standpoint.

Currently States have the authority to designate a TEA based on valid unemployment data. Typically, this is accomplished through census tract aggregation. A State will combine multiple contiguous census tracts to show that the weighted average unemployment rate of the combined census tracts results in a TEA qualification. Sometimes, the combined census tracts may take on an unusual shape – many times because of the unusual shape of the individual census tracts. In most cases, the county’s census tract network is not laid out in a grid. Census tracts in large cities may appear as small, regular squares or rectangles. However, more often census tracts are irregularly shaped and can cover dozens or even hundreds of square miles.

Those that oppose census tract aggregation call the methodology “gerrymandering” – an emotionally charged word. We would first note that words matter, and to use a term that has been associated with disadvantaging minorities or opposition groups in the political arena is completely inappropriate. The people who matter most in this discussion -- the unemployed -- are not at all concerned about the shape of the region that encompasses their homes. They are only concerned about more job opportunities. The term “gerrymandering” should not be used in the TEA context.

As we will show below, there are viable proposals that would ensure that jobs are created for unemployed workers – the ultimate goal of the TEA designation.

Possible TEA Methodologies

1. Limit the TEA Aggregation to a Set Number of Census Tracts.

One proposed method would be to limit the number of census tracts that can be aggregated to create a TEA. This option has no basis in economics or logic. The goal of the Program is to create jobs. As it relates to TEAs, the goal is not to locate EB-5 projects in a high unemployment area but to create jobs for unemployed workers in those areas. No worker – employed or unemployed – counts the number of census tracts between their homes and their workplaces. Obviously, there are some limitations concerning how far workers will travel, but these are not addressed by arbitrarily limiting the number of census tracts in a TEA. However, they can be resolved by ensuring that TEAs fit within a reasonable commuting distance. Thus, the census tract limitation proposal does not appear economically valid.

The next two proposals both recommend using state or national unemployment thresholds and unemployment data taken directly from the Census Bureau’s American Community Survey (“ACS”) rather than employing the “Census Share” mathematical method currently used in the EB-5 industry, which has caused trouble among practitioners in the space.

2. Base the TEA designation on “sending census tracts” showing employees that actually work in the census tract where the EB-5 project is located come from a TEA.

This proposal would allow an EB-5 project site to qualify as a TEA by showing that high unemployment census tracts within the same or an adjacent counties contain residents who commuted to the project’s census tract. Specifically, using ACS data in conjunction with the Federal Highway Administration’s Census Transportation Planning Products program (“CTPP”), the developers of the model determined that it is possible, in a replicable manner, to ascertain both the unemployment level of any U.S. census tract and the number of residents who commute from the census tract to the project’s census tract for work. The commuting approach would qualify a TEA if the weighted average unemployment rate of all sending census tracts at or above the state or national unemployment rate produced a rate of 150 percent of the state or national average unemployment rate.

If the TEA utilizes census tracts in a contiguous county to the project county, the adjacent county must send at least 25 percent of its residents to the project county for work. The option to use either the state or national unemployment average as the benchmark would better reflect local unemployment needs and avoid penalizing states with unemployment rates either well above or below the national average. The model is designed to reflect the realities of commuter flows and employment patterns within a metropolitan statistical area and would address in a data-driven and objective manner, the concerns some lawmakers have raised in relation to the current TEA policy.

For example, consider Jefferson County (Louisville), Kentucky. We used census tract 49 in downtown Louisville as our project tract. Under the model, one would then determine the total number of census tracts in Jefferson County that contain residents who commute to the census tract in which the project is located. This data is contained in the CTPP database noted above. In this case, we can determine that 190 census tracts in the county "send" commuters to census tract 49 in Louisville, which amounts to 39,380 people who commute from somewhere in Jefferson County to the project census tract. Again, using publicly available data, one would determine the unemployment data for each of the 190 census tracts. Once compiled, we would take all of the census tracts in that group that were at or above the state or national unemployment rate and calculate a weighted average unemployment rate. In this case, the data shows us that the average is over 18 percent, well above the threshold of 150 percent of state or national unemployment. We know, therefore, that many census tracts exceeding the average unemployment rate contain residents who commute to the project census tract. Though this does not indicate who may be working on the proposed EB-5 project, it does establish a legitimate economic link and indicates that increased economic development in the EB-5 project census tract to which people from high unemployment census tracts commute has the potential to ameliorate the unemployment levels in those sending census tracts.

3. Allow TEA Analysis based on a Radius Approach derived from Population Density and Commuting Distance

This approach considers the population density of the county (or county equivalent) of the project location. Obviously there is a significant difference in the population density in Manhattan (69,468 persons per square mile) versus Des Moines (751 persons per square mile). The proposal envisions TEA construction (for non-rural areas) that allows census tract aggregation within a reasonable commuting radius based on population density. The largest radius allowed reflects the Census Bureau’s average one-way commuting distance for the nation (18.8 miles). The underlying assumption is that an unemployed person could reasonably be expected to commute the same distance as the average employed American.

To provide a reasonable basis for TEA determination, population density is calculated based on publically-available Census data for each county and county equivalent in the United States. New York County, NY is the most densely populated county, with a density more than twice the number of the next highest county. A study of the counties within metropolitan statistical areas, and thus subject to TEA unemployment analysis, shows a great variety in population density.

Based on this information, the following radii are scaled to population density, with the maximum radius reflecting the national commuting distance:

· New York County, NY: TEA radius limit 2.5 miles

· Any county or county equivalent with a population density of 7,000 people per square mile or greater (based on latest decennial census) will have a TEA radius limit of 5.0 miles

· Any county or county equivalent with a population density between 1,000 people per square mile and 6,999 (based on latest decennial census) will have a TEA radius limit of 10.0 miles

· Any county or county equivalent with a population density under 1,000 people per square mile (based on latest decennial census) will have a TEA radius limit of 20.0 miles

While some may consider a 20-mile radius quite large, the radius concept does not guarantee a qualifying TEA. In fact, the result is quite the opposite – even areas in New York County would not qualify. The takeaway from these examples is that a practitioner cannot mathematically create a qualifying TEA unless the project is fairly close to a pocket of unemployment that “outweighs” the employed population in the same vicinity.

In the maps below, green tracts are those that individually qualify (based on 2009-2013 ACS data). San Francisco’s population density of 17,129 persons per square mile requires the 5-mile radius approach. In the map immediately following, there is no mathematical option to create a TEA for the project site marked in red.

San Francisco Non-Qualifying Sample Project Site

Jeff C.



In the next map, we depict a different project site located nearer to the pockets of unemployment. This proposed site easily qualifies as a TEA with a rate of 20.38% using only five tracts. The entire TEA is only 2.5 miles long. Clearly, unemployed people would travel 2.5 miles for work.











San Francisco Qualifying TEA

Jeff C.

This methodology has been tested on a number of different cities and the results are the same. If the project is not located reasonably close to unemployment, the law of averages makes it impossible to create a qualifying TEA. The radius reflects a logical and reasonable commuting distance for unemployed workers. Using this approach, the following cities would have these TEA radii:

1. New York— 2.5 mile

2. Chattanooga, TN—20 mile

3. Des Moines, IA—20 mile

4. Dallas, Texas—10 miles

5. Columbus, OH—10 miles

6. Roanoke, VA—20 miles

7. Louisville, KY—10 miles

8. Salt Lake City, UT—10 miles

9. San Jose, CA—10 miles

10. East Baton Rouge, LA—20 miles

11. Mobile, AL—20 miles

12. San Francisco, CA—5 miles

4. Eliminate TEAs.

This may be the best alternative. Instead of the endless bickering over TEAs, why can’t we just eliminate TEAs all together? This would put all projects on a level playing field. If lawmakers still feel compelled to incentivize investment in critically impoverished areas, an exception could be made that would not: (a) swallow the rule which many TEA opponents says occurs now with the current TEA process and (b) encourages investment in a very small, narrowly defined area that is critically impoverished. For example, a critically impoverished area could encompass areas within the boundaries of Enterprise Zones, Renewal Communities, Promise Zones, and other designations created under Federal, state and local programs for the purpose of neighborhood revitalization. Moreover, a census tract where at least 20 percent of its residents live below poverty levels could qualify as a critically impoverished area TEA.

Conclusion

As the TEA debate rages, it is important to remember that in the end we are talking about real people – the unemployed. Unlike “gerrymandering”, employing a mathematical aggregation of census tracts is not devious, not political, and definitely not a game. We should allow mathematics and logic to determine the size and shape of TEAs, not arbitrary decisions made in a vacuum for the sake of consensus.

As can been seen above, using a set number of census tracts has little basis in economics or logic. The other methodologies – sending census tract analysis or population density analysis -- are better methodologies from an economics perspective. But, perhaps, the best solution might be eliminating TEAs completely.



[1] This article is a collaboration by many leaders in the EB-5 space – Kim Atteberry, Laura Reiff, Duane Desiderio, Jeff Campion, and Matt Virkstis. Each is a member of the EB-5 Investment Coalition. See EB5coaltion.org.

[2] Eight C.F.R 204.6(e).

[3]Id.

Reprinted with permission.


About The Author

Mr. Campion received his J.D. with Honors from the University of Florida College of Law in 1997. While in law school he also completed the coursework for a Masters in Arts Latin American Studies. He received his B.B.A. in International Finance and Marketing in 1993 from the University of Miami graduating Cum Laude with Departmental Honors and from the Honors Program. Mr. Campion has a unique perspective in the EB-5 industry in that he has been involved in all sides of the EB-5 process – forming regional centers for clients, ensuring projects are EB-5 compliant, reviewing projects for immigration risks for his investor clients, and overseeing regional centers as ceo of several regional centers. Mr. Campion began working with EB-5 projects as an attorney in 2008. He is currently serving as: Founder of Jeffrey E. Campion P.A and ceo of Pathways – a family of approved regional centers that operate in every major U.S. population area. He also is a co-founder of EB-5IC, is a member of AILA EB-5 Committee, was voted as “Top 25 EB-5 attorney” by “EB5 Investors,” and was an IIUSA Best Practices Committee Member and Public Policy Committee Member.


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