The Center for the Study of Immigrant Integration (CSII) estimates of individuals who might benefit from the Dream and Promise Act of 2019 (H.R. 6) are based on underlying estimates of the population that may be unauthorized and/or beneficiaries of Temporary Protected Status (TPS) and Deferred Enforced Departure (DED).
The basic first step in the estimate involves tagging the unauthorized immigrant population in a version of the American Community Survey (ACS), 2012-2016 downloaded from IPUMS (Ruggles et al. 2017). The basics of that approach are reviewed in Le, Pastor, and Scoggins (2019). Essentially, we look at the non-citizen immigrant population and apply both a series of conditions that would imply legal status (such as veteran status) and then assign the rest of the observations based on a stratified probability model.
The probability estimates needed to do the latter exercise come from a logistic model applied to characteristics and status information in the 2014 Survey of Income and Program Participation (SIPP). Other approaches, including in some of our past work and in the estimates conducted by the Migration Policy Institute, have relied on the 2008 SIPP but it is likely that the characteristics of the unauthorized immigrant population have changed significantly since then. Using the 2014 SIPP requires a bit of extra work to estimate who is likely to have changed status if they arrived without proper documentation (a task that was easier in the 2008 SIPP) but it likely yields a more up-to-date picture.
Similar to the approach taken by the Center for Migration Studies (CMS) (Warren 2014), we then assign status as we seek to hit country targets (or “controls”) derived from residual methods developed by other researchers. We differ from the CMS approach in that we apply fewer conditions and assign status to a far larger share of immigrants based on the stratified probabilities; by contrast, CMS applies more conditions and then uses a random method to select in the rest. That creates an overall sample to which the Dream requirements under Title I of H.R. 6—involving age at arrival, enrollment or educational attainment, etc.—are applied.
Specifically, we designate as eligible all who were under age 18 upon arrival in the United States, last arrived in the country more than four years prior to the survey, and met any of the following criteria: 1.) were at least 18 years old and had a high school diploma (or equivalent); 2.) were at least 18 years old and enrolled in school (9th grade or higher only); or 3.) were between the ages of five and 17 (inclusive). While the text of the bill suggests that, among five to 17 year olds, only those with a high school diploma (or equivalent) or those enrolled in a school or educational program on track to attain a high school diploma are eligible for conditional permanent resident CPR status, we specify all five to 17 year olds as eligible. This is because the bill also indicates that children ages 5 or older are protected from removal and may apply for CPR status once they enroll in high school (or other qualifying secondary school or education program).
To estimate who is eligible for protection under TPS/DED provisions under Title II of H.R. 6, we selected from our undocumented sample individuals eligible for TPS or DED in September 2016, based on the year of arrival by country of origin requirements in place at the time (as summarized in the table below).
| Country of origin | Must have arrived
in the United States before: |
|---|
| El Salvador |
2/13/2001 |
| Guinea |
11/20/2014 |
| Haiti |
1/12/2011 |
| Honduras |
12/30/1998 |
| Liberia |
11/20/2014 |
| Nepal |
6/24/2015 |
| Nicaragua |
12/30/1998 |
| Sierra Leone |
11/20/2014 |
| Somalia |
5/1/2012 |
| South Sudan |
1/25/2016 |
| Sudan |
1/9/2013 |
| Syria |
8/1/2016 |
| Yemen |
1/4/2017 |
Note: South Sudan is not included in our estimates because it is not identifiable in the ACS. The only DED holders in September 2016 were Liberians, and they were also all eligible for TPS in September 2016.
The methods we applied are similar to those offered by Warren and Kerwin (2017) of CMS (with one key difference in assignment discussed below that takes advantage of our probability estimates). We first tag possible TPS holders as those non-citizen individuals who do not have Lawful Permanent Resident (LPR) status or another form of authorization (such as student visas), based on the procedure described above, for the three largest TPS countries (El Salvador, Honduras, and Haiti); possible TPS holders are determined on country and year of arrival characteristics according to the TPS regulations in force in 2016. We are relatively confident in these totals because we have good country controls for the larger sending countries and our totals for overall TPS eligibility are close to those for the top three TPS countries reported in Warren and Kerwin (2017).
For the other smaller countries, our underlying country controls are less reliable and are often guided by regional data (that is, we assume that for smaller African countries, the share of immigrants who lack authorization is essentially the regional average). This is likely incorrect for countries such as Liberia that have a long and historically special relationship with the United States. To insure that we do not overstate the TPS-eligible population for these smaller countries, we calibrate the pools for the three largest countries against the actual number of nationals with TPS status as of 2016 according to Argueta (2017). For three large countries for which we have reliable numbers on both unauthorized immigrants in general and those with TPS in 2016, we look at the implied rate of take-up. As it turns out, this is around 75 percent in the cases of El Salvador and Honduras and far lower (around 54 percent) in the case of Haiti.
We assume the highest take-up rate (75 percent) and use this to back out potential pools for the smaller countries using the numbers of actual TPS beneficiaries from Argueta (2017). With the target sizes of the potential pools for the smaller countries in place, we then selected those eligible for protection under Title II of H.R. 6 until we hit the targets. As explained in the methodology of a TPS-related blog where selecting down rather than predicting up, while CMS randomly selects from the pool till they hit country target totals, we select those with the highest likelihood of being authorized residents till we hit country target totals for adults (with the logic being TPS holders are more likely to resemble authorized immigrants); in this case, the country target totals are our pool targets. With estimates of all adults eligible for protection under the TPS/DED provisions in place, we then assign minor children as also being eligible if they meet the country and year of arrival bars and had at least one TPS parent.
Household tax contributions and spending power estimates are from the Center for American Progress (CAP), based off methodology developed by New American Economy (2019). The estimates include all households that contain a member who would be eligible for protection under the Dream and Promise Act of 2019 based on the methodology described above, including immigrant youth who will be eligible to apply for CPR status once they enroll in secondary school. Federal tax rates come from the Congressional Budget Office (2018), while state and local tax rates come from the Institute on Taxation and Economic Policy (2018). Spending power is measured as household income after federal, state, and local tax contributions.
To assign all individual- and household-level estimates to Congressional Districts, we used a 2010 population-based crosswalk between Public Use Microdata Areas (PUMAs) and Congressional Districts for the United States 116th congress from the Missouri Census Data Center’s Geocorr 2018 Geographic Correspondence Engine (beta version, revised 12/04/2018 with 2016 geographies). A geographic crosswalk was necessary because the ACS microdata includes only very limited geographic information, with the PUMA being the lowest level of geography attached to individuals. PUMAs contain a population of at least 100,000 while Congressional Districts have an average population of about 700,000. We randomly assigned individuals to Congressional Districts in proportion to the 2010 population distribution (taking care to insure that all households remained intact, that is, that individuals were assigned in household “clumps” since no household could be split between two Congressional Districts), and then aggregated the results by Congressional District to derive the final estimates presented in the interactive map. While this introduces some unknown degree of geographic error in the resulting estimates, it is likely to be relatively minimal given that most PUMAs are either entirely contained or largely contained in a single Congressional District. To caution against utilizing unreliable estimates, we include an asterisk and a note alongside the data for Congressional Districts with fewer than 50 unweighted survey respondents identified as being eligible for protection under the Dream and Promise Act of 2019. We also do not report any data for Congressional Districts in which our estimates showed fewer than 500 individuals eligible for protection.
References
Argueta, Carla N. 2017. Temporary Protected Status: Current Immigration Policy and Issues. Washington, D.C.: Congressional Research Service.
Congressional Budget Office. 2018. The Distribution of Household Income, 2015. Available at https://www.cbo.gov/publication/54646.
Institute on Taxation and Economic Policy. 2018. Who Pays? A Distributional Analysis of the Tax Systems in All 50 States: 6th Edition. Available at https://itep.org/whopays/.
Le, Thai V., Manuel Pastor, Justin Scoggins, Dalia Gonzalez, and Blanca Ramirez. 2019. Paths to Citizenship: Using Data to Understand and Promote Naturalization. Los Angeles, CA: USC Center for the Study of Immigrant Integration.
New American Economy. 2019. Methodology. Available at https://www.newamericaneconomy.org/methodology/.
Ruggles, Steven J., Katie Genadek, Ronald Goeken, Josiah Grover, and Matthew Sobek. 2017. Integrated Public Use Microdata Series: Version 7.0 2016 5-Year American Community Survey. Minneapolis, MN: University of Minnesota.
Warren, Robert. 2014. “Democratizing Data about Unauthorized Residents in the United States: Estimates and Public-Use Data, 2010 to 2013.” Journal on Migration and Human Security 2(4):305–28.
Warren, Robert and Donald Kerwin. 2017. “A Statistical and Demographic Profile of the US Temporary Protected Status Populations from El Salvador, Honduras, and Haiti.” Journal on Migration and Human Security 5(3).
