By Ben A. Rissing and Emilio J. Castilla
Immigration reform has returned to the forefront of U.S. political debate as a result of President Barack Obama’s November 2014 executive order. Yet, proposed immigration reform measures have not attended to the process by which immigrant applicants are assessed – And many aspects of U.S. immigrant evaluation systems are opaque and discretionary.
In a study recently published in the American Sociological Review, we examine the first stage of one such work authorization process, the labor certification program, which is required for the granting of most employment-based green cards in the United States. We find that there is substantial variation in approval outcomes associated with foreign workers’ country of citizenship. Specifically, while 90.5 percent of workers from Asia are approved by government agents, only 66.8 percent of foreign workers from Latin America are approved. These disparities exist even after controlling for salary, job title, job skill level requirement, location, industry, and prior visa. However, when applications are evaluated with detailed employment-relevant information obtained through government application audits, we find that approvals are equally likely for immigrant workers from the vast majority of citizenship groups.
Equal Employment Opportunity laws and immigration Acts in the United States mandate the equitable evaluation of individuals, regardless of their country of origin. The labor certification process is thus intended to be merit-based, and contains no evaluation criteria pertaining to foreign workers’ origin country or demographic characteristics. This program specifically seeks to ensure that a described foreign worker is qualified for a given job opportunity and that no qualified U.S. workers are available for the position. During evaluations, these government agents reach labor certification decisions based on fields in a submitted application and without ever communicating with a described immigrant worker. This said, each immigrant worker’s country of citizenship is visible early in the labor certification application, a field that these government agents are instructed to disregard during their training.
We analyzed the entire population of over 198,000 labor certification applications that were approved or denied between June of 2008 and September of 2011, as determined by a small team of government agents working in a single Atlanta, Georgia U.S. Department of Labor processing center. The majority of labor certification applications are filed by U.S. employers seeking to place a foreign worker into a high-skill and high-paying job. In this regard, 40 percent of applications are in computer and mathematical occupations, followed by architecture and engineering jobs (9 percent of all applications), and management positions (9 percent). The median salary for immigrant workers described in labor certification applications during this 40 month period was $73,000.
In our statistical analyses, we find unequal approval outcomes associated with immigrants from a variety of countries. Notably, foreign workers from Latin America are 23 percent less likely to receive approval than Canadian individuals (the study’s reference category), even with controls accounting for employer, occupation, and immigrant worker characteristics. Asian individuals, in contrast, are 13.3 percent more likely to receive approval relative to Canadians, all else equal.
These results suggest there is inequality based on foreign citizenship in the labor certification process, which affected employment outcomes at more than 68,000 organizations during our study period.
In our research, we further investigate how the information available to government agents during their assessments may affect evaluation outcomes. Notably, a portion of all labor certification applications are audited each year (13 percent during the 40 month period of our study). When audited, detailed employment-relevant information is collected from the sponsoring employer and used to inform a government agent’s labor certification assessment. We find no statistically significant differences in approval outcomes by immigrant world region during these evaluations of audited applications.
These results highlight the importance of using detailed employment-based information in reaching equitable employment evaluations of workers. This research is also relevant outside of immigration programs, as many decision makers in organizations use limited information when conducting initial employment screenings and selection of potential workers (for example, during reviews of resumes). The findings of this research thus highlight the unintended consequences of employment-based evaluations that only rely on limited employment-relevant information, which may lead decision makers’ judgments to be consciously or unconsciously influenced by applicants’ available demographic data.
In order to address these unequal approval outcomes based on demographics such as foreign citizenship, and in the context of the labor certification process, we recommend that all applications be audited and assessed using detailed employment-relevant information. Because we recognize the costs and administrative burden associated with such extensive auditing activity, an alternative low-cost solution may be to mask all foreign worker demographic characteristics during government agents’ application review. Given our findings, future U.S. legislation or administrative actions concerning immigration reform should address the organizational processes and criteria by which potential immigrants are evaluated.
Ben A. Rissing is the Pearson Visiting Assistant Professor of Sociology and Organizational Studies, Brown University, Department of Sociology.
Emilio J. Castilla is the NTU Professor of Management, Sloan School of Management, Massachusetts Institute of Technology.