Index Of Wanted 2009

[Gabby Dreher]

ScheduleA is the one way that the federal government officially tracks shortage occupations. It is also a mechanism by which the fixed number of employment-based green cards authorized by Congress can be directed to the areas of the economy most in need. But the Schedule A shortage occupation list has not been updated in over three decades, leaving it totally disconnected from current labor market conditions.

As a proof-of-concept, this paper proposes a transparent, objective, and data-driven method by which the Department of Labor (DOL) can regularly update the Schedule A shortage occupation list. Our method relies on a new economic index, which we call the Help Wanted Index, designed to identify and rank occupations by how likely they are to be facing shortage conditions. The Help Wanted Index includes lagged variables and longer data trends to strike a balance between favoring persistent shortages and being responsive to changing labor markets.

We apply our method with recent labor market data and suggest that DOL should update the Schedule A list to include 28 occupations, which together represent about six percent of PERM applications. The most notable additions to Schedule A in our proposed update would include:

An objective Schedule A list would be the first systematic way the federal government would monitor and diagnose labor supply gaps and market shortages. With this information, the federal government could also target workforce training programs, educational programs, and similar spending to the areas they are needed most.

The authors would like to thank everyone who provided valuable comments and suggestions on this report, including David Autor, Burt Barnow, Malcolm Cohen, Daniel Goroff, Ethan Lewis, David Muusz, Amy Nice, Andrew Reamer, Santi Ruiz, Madeleine Sumption, and Caleb Watney.

According to the Bureau of Labor Statistics (BLS), there were 8.7 million vacant job openings in October 2023, near a fifty-year high.1 So many jobs going unfilled slows economic growth and increases prices.

Updating the list poses significant challenges. Many employers complain of shortages, and it can be difficult to evaluate when these complaints represent legitimate needs. While some employers struggle to hire in occupations with specialized skills due to lengthy and costly delays for the prerequisite training, others bemoan shortages without actually raising wages or improving working conditions to attract workers.

Historically, updating the Schedule A list has involved fairly subjective evaluations of labor market conditions. We propose that DOL regularly update Schedule A with a transparent, data-driven approach.

We identify ten indicators of shortage conditions that can each be measured using existing labor market data. Aggregating across these indicators would allow DOL to objectively evaluate which occupations could be added to the Schedule A list without adversely affecting the wages or working conditions of similarly employed U.S. workers. We also use recent data to show what the Schedule A list would look like if DOL used this method to update the list today (and if it had used the list over the last decade for regular updates).

The federal government awards 40,000 employment-based green cards each for the employment-based second preference and employment-based third preference (EB-2 and EB-3) categories of immigrants, allowing recipients to permanently live and work in the United States.11

For an employer to successfully sponsor an EB-2 or EB-3 green card for a worker, DOL must certify that 1) there are insufficient workers able, willing, qualified, and available and 2) that the employment of the green card beneficiary will not adversely affect the wages and working conditions of similarly employed workers.15 Almost always, this certification includes going through the lengthy and costly individualized permanent labor certification (since 2005 referred to as PERM) process.

In the first decade following passage of the Immigration and Nationality Act of 1965, Schedule A brought a variety of workers to the United States, including physicists, engineers, physicians and surgeons, mathematicians, and chemists.18 Up through the 1990s, the list dwindled to include only nurses and physical therapists, in no small part because of significant lobbying efforts to restrict the inflow of specific groups of workers, such as foreign physicians.19 20

Schedule A could provide certainty and predictability to eligible beneficiaries, and to employers hiring in occupations with tight labor markets where there are high job vacancies, and where immigration will not harm U.S. workers. If it were regularly updated in a data-driven way, besides directly addressing labor needs, Schedule A could help agencies and policymakers identify gaps in the workforce beyond those that immigrants can fill. An objective, evidence-based Schedule A list would be the first systematic way the federal government would monitor and diagnose labor supply gaps and market shortages. This would also help target workforce training programs, educational programs, and similar spending to the areas they are needed most. Instead, discussion about shortages currently relies heavily on anecdotes from employers and industry associations, which are unlikely to be objective or complete.21

Although it may be difficult to measure occupational labor shortages directly, their symptoms will be reflected in labor market data. In this section, we introduce the Help Wanted Index to identify labor market tightness by occupation, incorporating ten critical shortage indicators. For comparison, we take the objective component of the process used by the UK to generate its Shortage Occupation List (which includes many but not all of the indicators used in our Help Wanted Index) and substitute in U.S. data as a benchmark against our preferred method. We also describe the U.S. data required to measure each of these indicators, how to aggregate across indicators to produce a shortage ranking, and where to set the cutoff to determine which occupations make it onto the Schedule A list.

To develop the Index, we modified the UK-based list of indicators in light of differences in data availability and included additional important indicators of shortage conditions. In addition to unemployment and lagged unemployment, we also incorporated a new measure of labor market tightness in the literature, the job-to-job transition rate within each occupation over a year, following the work of Autor, Dube, and McGrew (2023). In the end, we measure the following indicators of labor market tightness for each of about 400 occupational categories23 drawn from the Standard Occupational Classification (SOC) as defined by the American Community Survey (ACS). The federal statistical system is dedicated to independence and integrity, limiting the risk that the index could be manipulated by companies who could stand to benefit.

These indicators include some that give a snapshot of the labor market (e.g., unemployment, the job-to-job transition rate, income premium for the year), others that show a snapshot of the labor market in the recent past (e.g., lagged unemployment), and still others that measure change over time (e.g., change in wages over one year, change in employment). This combination, and the inclusion of lagged variables and longer trends, is designed to strike a balance between 1) favoring persistent shortages and 2) being responsive to changing labor markets. Too many lagged variables would make for a Schedule A list that could not respond to emerging trends like COVID supply chain disruptions or federal efforts to onshore

semiconductor manufacturing. On the other hand, too little focus on persistence would identify transient shortages that are likely to resolve themselves, not to mention yield a volatile list that would change too frequently to be useful for employers and the prospective immigrants, adding to the unpredictability of the U.S. immigration system.

The method described in the section above yields a rank order list of occupations, but does not directly inform how many of these occupations should be placed on the shortage list. Using a fixed threshold creates two problems: 1) different occupations represent different shares of the economy, so it makes little sense to treat each occupation with equal weight; and 2) current economic conditions will determine the number of occupations that are currently in shortage. Put differently, when the economy is booming, a relatively large number of occupations are likely to be in shortage. When the economy is in a downturn, fewer occupations will be experiencing elevated levels of labor demand. The threshold must reflect that.

The Schedule A lists for the most recent available data (i.e., 2021) generated by the Help Wanted Index and the UK-based benchmark are shown in Table 2 below. The occupation lists for previous years can be found in Appendices D and E.

Using the Help Wanted Index, we propose a Schedule A list with 28 occupations, which together account for 6% of PERM applications. These occupations fall roughly into three main categories: health occupations; STEM occupations; and business occupations.

The UK-based benchmark is another feasible option for a Schedule A update, though not radically different from the Help Wanted Index. In fact, the lists have 20 occupations in common suggesting that the methodology is not too sensitive to the indicator set. Still, by including additional indicators that we think are important (see above), our method adds critical health-based occupations, including registered nurses and diagnostic technicians, and STEM management occupations, such as architecture and engineering managers and natural science managers.

How would the Schedule A list have looked if DOL updated it in a data-driven way in previous years? What would be the impact on the U.S. workforce and PERM applications? We analyzed data from 2013, 2016, 2019, and 2021 using the Help Wanted Index and the UK benchmark and applied our threshold as described earlier. The historical lists can also be found in Appendices D and E.

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