D. Targeting
IV. Data
To examine the impact of backlog on judicial decision making in immigration courts, I use a proprietary dataset that contains over five million juvenile immigration removal cases decided between 1950 and October 2016. The Transaction Records Access Clearinghouse (TRAC) obtained this dataset pursuant to a FOIA request from the
Executive Office for Immigration Review (EOIR), the division of the Department of
Justice that retains jurisdiction over immigration court proceedings.34 I am able to access this data through my appointment as a TRAC Fellow. The names of the respondents, as well as any other personal identifiers, are removed from DHS records before the
information is released to TRAC.
The TRAC dataset is ideal for my analysis not only because it captures all juvenile cases decided in the immigration court system, but also because it is rich in information that is otherwise unavailable elsewhere, including court outcomes and demographic characteristics of respondents. EOIR employees extracted this data from EOIR’s CASE database system, which tracks the workloads of immigration courts. One limitation of this dataset is that it was recorded purely for EOIR internal recordkeeping and was not intended for individuals to engage with it for data analysis. Therefore, EOIR does not impute values for certain variables and there are missing values for many variables in the data. Throughout my analysis, I create indicator variables for missing values for each variable that I use. There also may be a rate of error in the reporting by EOIR, as these data were used for in-house reporting only. As long as the measurement error is random for a given variable, my estimates will only suffer from attenuation bias and will be biased towards zero. If this bias occurs, my coefficients will be conservative estimates of the true effect. I address specific issues with measurement error for key variables in my analysis, such as with case duration, below.35
34 TRAC is a data gathering and research nonprofit organization that operates out of Syracuse University.
35 The TRAC data is compiled into many different large files with different information regarding charge data, individual judges, attorneys, and hearing schedules. I merge these datasets across individual case numbers (labeled idncase in the files). Each individual has one case number, even if they are associated with the same family. In each case, each different proceeding also has its own proceeding identification.
However, I merge on case numbers as a whole, and assign any judge information and attorney information to the entire case.
The TRAC data contain case-level data regarding demographic characteristics of the individual and identifies the judge, attorney status, and the court in which the decision took place. The data contain demographic characteristics such as whether the individual is detained, crimes charged against the individual, and the individual’s country of origin.36 The data also contain case-level detail such as the type of case, number of grounds for removal charged, number of applications for relief filed, and whether the individual was present during the hearing when the decision was rendered.
There are a variety of different types of cases that arrive before an immigration judge, including removal cases, asylum cases, and withholding of removal cases. Over 98 percent of cases in the TRAC data from 2003 until 2013 are removal cases. As the merits and procedures of different case types may result in heterogeneous effects on case
duration and the likelihood of relief, I drop cases other than removal cases from my sample. In removal cases, I code a decision as a denial of relief if the individual was denied any relief sought or the judge otherwise rules that an individual is subject to removal by authorities. In my sample, denial includes voluntary departure orders, where an immigration court judge sustains the charges against the individual and issues an order for voluntary departure.
I code all grants of relief and termination of proceedings as relief granted. These outcomes include actual grants of relief, in which the immigration judge finds that the individual is entitled to relief from removal and may remain in the United States. There are exist a variety of circumstances in which a case may be closed. These include cases in which the government attorney prosecuting the individual’s case exercises prosecutorial
discretion and drops the request for a removal order, or when the immigration judge terminates proceedings after finding that DHS has not established that the individual is removable. Under these closures, the individual is permitted to stay in the United States.
There are a few types of resolutions to specific cases that do not fall squarely in the relief granted or denied dichotomy. An example of this is when the case is transferred to a different court. I drop these cases from my sample. I remove from my sample cases in which the final decision is missing.
I create an indicator variable, in absentia, indicating whether the individual was present at the hearing in which the decision was rendered. The data also contain
indicators for whether the individual is detained at the time of hearing, was detained but released from custody, or was never detained since court proceedings began. I create an indicator variable equal to one if an individual was ever detained. The TRAC data also contain a variable that tracks whether an attorney was present in the case at any time. I use this to create an indicator variable for attorney presence in a case. The TRAC data also include whether the individual was charged with a crime other than being illegally present in the United States. I create an indicator variable indicated that the individual committed a crime.
Finally, the data contain the date when the case was opened and the date of the final decision. I use these dates to calculate the duration of each individual’s case in immigration court by counting the days elapsed from the date of the case opening to the date of the final decision.37 This information at the individual case level provides a more accurate measure of individual case duration across courts than previous studies of case
37 I find that for 56 individuals (less than one-hundredthof one percent of my sample), the TRAC data reports a negative case duration. This could be due to an incorrect recording of the date. I remove these individuals from my sample.
duration, which relied on the ratio of cases that are postponed or remain unresolved at the end of the year to the total number of cases introduced during the year (Mitsopoulos and Pelagadis 2007).
To obtain data on the number of cases pending, I use data from the TRAC Immigration supplements available online.38 These supplements include the number of cases pending at the conclusion of each fiscal year (September 30) at each immigration court. I restrict the case-level data from 2003 until the end of 2013. Restricting my sample to these dates avoids the confounding effects from one of the largest immigration reform acts in history, the Immigration Reform and Immigrant Responsibility Act of 1996 and potential short-term effects of 9/11. Further, limiting cases to only those before 2014 avoids potential confounding effects of both a large hiring of immigration judges and a surge of immigrant children to the borders of the United States in the summer of 2014.
To obtain an exogenous measure of backlog pressure, I construct a measure of the percentage change in adult immigration cases pending. I use the total amount of cases pending and subtract the total number of juvenile cases resolved in that year to arrive at the total number of adult cases pending. To obtain the percentage change in adult immigration cases pending, I subtract the number of cases pending last year in a given court from the cases pending this year and divide this number by the number of cases pending last year. Using the percentage change in adult cases allows for an exogenous measure of backlog pressure that is not tied to the individual juvenile case at issue. Using the percentage change in total cases or juvenile cases only would be endogenous, as
longer juvenile case duration could cause an increase in juvenile case backlog. Using the percentage change in adult cases pending only avoids this endogeneity.
Table 1 shows summary statistics for the entire case sample. I find, nationwide, and over the entire sample period, that there are an average of 8,533 cases pending in the court that the individual case is located. The average case duration from opening to completion is just under on year, or 364.5 days. Less than half (35 percent) of individuals have an attorney at any point during their immigration court case. One-fifth of individuals are in absentia, or fail to show to a court date when a decision is rendered. 21.8 percent of individuals in my sample have successful applications for relief to remain in the United States, and the remainder (78.2 percent) of individuals are denied relief and are
subsequently deemed removable from the United States. 16 percent of sampled individuals have committed a crime other than being present illegally in the United States, yet almost 60 percent of individuals have been detained at one point during their case.
Table 2 shows the summary statistics over time. Consistent with other evidence regarding immigration court backlog, the average number of cases pending across cases in my sample increased sharply from 2003–2010 levels, from under 8,000 cases to over 11,000 cases in 2011–2013. As this increase occurred, the average case duration
increased slightly over time, from 375 days in 2003–2010 to 441 days in 2011–2013. The number of individuals with attorneys also increased over time, with a low of 32 percent of individuals represented in 2003–2006 to a high of 47 percent of individuals
represented in 2011–2013. My sample also depicts evidence of increased immigration enforcement: the number of individuals detained has steadily increased from 43 percent
in 2003–2006 to 72 percent in 2011–2013. Overall, the changes that I observe in my data over time comport with anecdotal evidence of increased backlogs and increased
immigration enforcement. I next determine how these changes over time have affected case duration in immigration courts.
Table 3 depicts summary statistics by attorney presence. Attorneys in immigration court cases are likely better equipped to present specific evidence in an individual’s case, or could strategically delay the individual’s case. Attorneys may also be hired in cases that are substantially more complicated than others. Therefore, it is unsurprising that individuals with attorneys have a substantially longer case duration, with a case duration of over 721 days as compared to 164 days for those without an attorney. In the
immigration court context, individuals may decide to hire an attorney only if they
anticipate that they cannot adequately represent their own claims to an immigration court judge. Individuals with attorneys are also more likely to obtain relief from removal: over half of all individuals with attorneys are granted relief in immigration courts, while only 5 percent of pro se individuals are granted relief. I examine the effects of the presence of an attorney in my analysis of both case duration and the probability of a successful case.