Supplement: Just Facts’ Study Assumptions
* In Just Facts’ study “10% to 27% of Non-Citizens Are Illegally Registered to Vote,” the upper and lower bounds assume the following:
-
People who identified themselves as “non-citizens” in the survey are, in fact, non-citizens. This assumption is justified because:
- non-citizens (especially unauthorized immigrants) have strong legal and financial incentives to falsely claim that they are citizens.[1] [2] In contrast, citizens have no conceivable incentive to claim that they are not citizens.
- a 2013 study published by the journal Demographic Research found that certain groups of non-citizens—including Mexican men of all ages, Mexican women aged 40 and older, and immigrants who have been in the U.S. for less than five years—frequently misrepresent themselves as citizens in Census surveys.[3]
- the survey used multiple citizenship questions to limit the possibility of honest errors.[4]
-
Non-citizens who stated in the survey that they are registered to vote are, in fact, registered to vote even if they weren’t matched to a voter registration database. This assumption is justified because:
- a study published in the journal Public Opinion Quarterly in 2016 found that “several apparently viable methods of matching survey respondents to government records severely underestimate the proportion of Americans who were registered to vote.”[5]
- unauthorized immigrants routinely use fraudulent identities to interact with government.[6]
- the survey guide explains that “a record may not be matched either because the individual is not registered to vote or because of incomplete or inaccurate information that prevented a match.”[7]
- the use of alternate identities in this survey is evidenced by an earlier rendition of the same survey in which only 41% of non-citizens were matched to a database containing “information for nearly every American adult.”[8] [9] [10] [11] [12]
-
Non-citizens who were matched to a voter registration database are, in fact, registered to vote even if they stated in the survey that aren’t registered to vote. This assumption is justified because:
- non-citizens have a strong incentive to deny that they are registered since this is an illegal act punishable by fines, imprisonment, and deportation.[13] [14] [15]
- the survey guide explains that “matches are made only with records for which there is a high level of confidence that the respondent is being assigned to the correct record.” The guide also explains that “there will still be some false-positives,” but this is the exception, not the rule.[16]
- Non-citizens who stated in the survey that they aren’t registered to vote and weren’t matched to a voter registration database aren’t registered to vote. This assumption may understate voting by non-citizens because it doesn’t account for non-citizens who register using an alternate identity and falsely deny that they are registered.[17]
-
Non-citizens who participated in the survey are representative of the nation’s non-citizen population. This assumption may understate voting by non-citizens because:
- the survey was an internet survey,[18] which typically don’t involve nationally representative samples of participants.[19]
- the survey responses were matched and weighted to the citizen population of the nation.[20]
- the authors of the 2014 Electoral Studies paper weighted the results of same survey in 2008 to make it representative of non-citizens, and it found that 14.8% of non-citizens stated they were registered to vote.[21] This is about twice the 6.8% rate of the 2022 survey.[22]
- a nationally representative bilingual survey conducted by McLaughlin & Associates in 2013 found 13% of Hispanic non-citizens stated they were registered to vote.[23] This is nearly twice the 6.8% rate of the 2022 survey.[24]
- People who claim to be “citizens” in the survey actually are citizens. This is unlikely given that certain major groups of non-citizens often falsely claim to be citizens in Census surveys.[25] If these dishonest survey respondents register to vote at higher or lower rates than other non-citizens, this could skew the results of the study.
* The upper bound of 27% in Just Facts’ study assumes that the appropriate denominator for calculating the registration rate of non-citizens who are matched to a voter registration database is the number of non-citizens who appear in a broader database of consumer data. This assumption is justified because:
- unauthorized immigrants routinely use fraudulent identities to interact with government.[26]
- the use of alternate identities in this survey is evidenced by an earlier rendition of the same survey in which only 41% of non-citizens were matched to a database containing “information for nearly every American adult.”[27] [28] [29] [30] [31]
* The lower bound of 10% in Just Facts’ study assumes that the appropriate denominator for calculating the registration rate of non-citizens matched to a voter registration database is the number of non-citizens who participated in the survey. This assumption may understate voting by non-citizens because:
- unauthorized immigrants routinely use fraudulent identities to interact with government.[32]
- the use of alternate identities in this survey is evidenced by an earlier rendition of the same survey in which only 41% of non-citizens were matched to a database containing “information for nearly every American adult.”[33] [34] [35] [36] [37]
Footnotes
[1] Report: “Interior Immigration Enforcement: Criminal Alien Programs.” By William A. Kandel. Congressional Research Service, September 8, 2016. <fas.org>
Page 1:
Congress has long supported efforts to identify, detain, and remove noncitizens1 who have been convicted of crimes in the United States. More generally, all unauthorized aliens2 within the United States are potentially subject to removal, and “interior enforcement” (i.e., alien removals originating from within the United States) is a basic element of immigration control. …
2 In this report, the terms “alien” and “foreign national” are used interchangeably.
Pages 2–3:
The unauthorized alien population includes not only persons who entered without inspection or overstayed the terms of their temporary visas but also persons who have what some refer to as a “quasi-legal” status (such as temporary protected status, parole, deferred action) that affords them relief from immediate removal. Hence, not all unauthorized aliens living in the United States are subject to removal. Most unauthorized aliens, however, are removable; but few have been convicted of a crime and are classified as criminal aliens (unlawful presence in the United States itself is a civil violation, not a criminal offense).9
9 Unlawful presence is only a criminal offense when an alien is found in the United States after having been formally removed or after departing the country while a removal order was outstanding. See CRS [Congressional Research Service] Report R43892, Alien Removals and Returns: Overview and Trends, by Alison Siskin.
Page 19: “[A]rrests for civil immigration violations are for the purpose of placing individuals into removal proceedings, whereas arrests for criminal violations can lead to criminal prosecution.”
Page 22:
Civil immigration offense: A violation of federal immigration law under Title 8 of the U.S. Code, the most common being residing in the United States without authorization. A person cannot be sent to prison for a civil immigration offense. They can be penalized by being deported from the United States, which technically is not classified as punishment. …
Removable alien: An alien subject to formal removal (deportation) from the United States. This includes aliens who are inadmissible under INA [Immigration and Nationality Act] §212 or deportable under INA §237, including nonimmigrant aliens who enter legally but violate the terms of their visas or overstay their visas. Most removable aliens have never been convicted of a criminal offense.
[2] Report: “The Economic and Fiscal Consequences of Immigration.” By the National Academies of Sciences, Engineering and Medicine, Division of Behavioral and Social Sciences and Education, Committee on National Statistics, Panel on the Economic and Fiscal Consequences of Immigration. Edited by Francine D. Blau and Christopher Mackie. National Academies Press, September 22, 2016. <www.nap.edu>
Page 96: “Unauthorized immigrants and individuals on nonimmigrant visas are not eligible for the Supplemental Nutrition Assistance Program (SNAP), non-emergency Medicaid, Supplemental Security Income (SSI), and Temporary Assistance for Needy Families (TANF).”
[3] Paper: “How Well Does the American Community Survey Count Naturalized Citizens?” By Jennifer Van Hooka and James D. Bachmeierb. Demographic Research, July 2, 2013. <www.demographic-research.org>
Page 2: “In the United States, data on naturalization and citizenship largely come from Census Bureau surveys, such as the Current Population Survey (CPS), the long form of the decennial Census (2000 and earlier), and the American Community Survey (ACS).”
Page 3:
There are good reasons to suspect that citizenship is inaccurately estimated in Census data. During the late 1990s, Passel and Clark (1997) compared the number of persons that are reported as naturalized in the 1990 Census and the 1996 Current Population Survey (CPS) with the number of naturalized citizens based on administrative data from the Immigration and Naturalization Service (INS). They found the Census/CPS estimates to be much higher than the INS-based estimates for two groups. Among new arrivals (those in the U.S. fewer than five years) from all national origins, about 75% of those who were reported as naturalized were probably not. Among longer-resident Mexican and Central American immigrants, about one-third of those who were reported as naturalized were probably not.
Page 5:
To assess the current level of citizenship reporting error, we estimated the number of naturalized citizens in mid-year 2010 by age group, sex, region of origin, and duration of residence based on the number of Office of Immigration Statistics (OIS) naturalization records. We then compared the OIS-based estimates with the corresponding numbers in the 2010 American Community Survey (ACS) (also a mid-year estimate). The difference between the two provides an indication of over- or under-representation of naturalized citizenship in the ACS.
Page 17:
Table 2 reports the naturalization estimates by sex, region of birth, and duration of U.S. residence. For both men and women from all origin regions, the estimated number of naturalized citizens in the ACS is substantially and significantly higher than the OIS-based estimates among immigrants with fewer than five years in the U.S. For example, the number of naturalized Mexican men with fewer than five years of U.S. residence is nearly 27 times higher (2587%) in the ACS than the OIS estimates. Another way to express this is that among the 16 thousand reporting as citizens in the ACS, only about 600 (or about 4 percent) are likely to actually be naturalized citizens. Among those in the U.S. for five or more years, the OIS-ACS gap is much lower in relative terms, and concentrated among Mexican men.
Page 19:
In Table 3, OIS and ACS estimates are presented for Mexican and non-Mexican men and women by age group by varying rates of emigration. We note that the OIS estimates do not always decline as emigration increases from the “low” to the “moderate” to the “high” series because of age crossovers in various emigration estimates. Regardless of assumptions about emigration, ACS estimates are especially high relative to the OIS-based estimates among Mexican men of all age groups and Mexican women aged 40 and older. The same pattern does not hold among non-Mexicans, among whom the discrepancy remains relatively low across all age groups.
[4] “Expert Report of Jesse T. Richman in the Case of Mi Familia Vota v. Fontes.” October 13, 2023. <www.justfacts.com>
Pages 73–74:
231. Measuring citizenship in the CES survey: From its inception the CES survey has measured citizenship and immigration status using the following question:
“With of these statements best describes you?
• I am an immigrant to the USA and a naturalized citizen.
• I am an immigrant to the USA but not a citizen.
• I was born in the USA but at least one of my parents is an immigrant.
• My parents and I were born in the USA but at least one of my grandparents was an immigrant.
• My parents, grandparents and I were all born in the USA.”
Critics of my 2014 paper worried that this question was complex, and that respondents might get confused by it.
232. In the 2019 CES a more robust approach to measuring citizenship status was adopted. This involved asking two questions about citizenship status. Prior to asking the question above, a simpler question was also asked. This additional question was:
“Are you a United States citizen?
• Yes
• No”
233. The addition of this question offered two advantages over the previous approach. First, the new question was simpler, so the concern voiced by Minnite about the complexity of the old question did not apply to it. Second, it provided an opportunity to assess within the survey the robustness of responses to the longstanding question. If the more complex question was confusing or unreliable—if some citizens were mistakenly identifying themselves as noncitizens—then this should come out in the pattern of answers. There should be inconsistencies between the answers to the two questions if the critics were right.
234. Strikingly, at least based upon the published survey datasets, there don’t seem to have been any errors identified. Table 14 reports a crosstabulation for the 2019 through 2022 CES survey of answers to these two questions. As can be seen, every individual in the survey dataset had a consistent pattern of answers across the two questions. There were no instances in which someone indicated that they held a United States citizenship on one question and that they did not hold United States citizenship on the other question. This pattern of responses is striking given that the critique of my study asserted that there was a 0.5 percent error rate on the citizen status question. If there was an error rate of this magnitude, then across more than 164 thousand responses, there ought to be some error visible. Instead, there appears to be no error whatsoever. This is vastly less error than the claims made by critics of my study including Minnite would imply. These results appear to indicate no errors at all: an error rate of 0.
[5] Paper: “Measuring Voter Registration and Turnout in Surveys: Do Official Government Records Yield More Accurate Assessments?” By Matthew K. Berent, Jon A. Krosnick, and Arthur Lupia. Public Opinion Quarterly, August 2, 2016. Pages 597–621. <academic.oup.com>
Pages 597–598: We find that several apparently viable methods of matching survey respondents to government records severely underestimate the proportion of Americans who were registered to vote.”
Page 617:
Conclusion
Although many scholars attribute survey overestimation of turnout to respondent lying, we have reported evidence for a different explanation in the ANES [American National Election Studies] 2008–2009 Panel Study. Actual and self-reported turnout numbers were nearly identical among respondents for whom we could match to a government record, suggesting high accuracy of the self-reports. So whereas the ANES 2008–2009 Panel Study overestimated turnout by almost 30 percentage points, only 6 percent of matched respondents had government records contradicting their claims of having voted, and some of this discrepancy could be due to errors in government records. Hence, respondent lying apparently contributed less to turnout overestimation than is commonly presumed.
Moreover, the seeming superiority of TV [turnout validation] data over self-reports appears to have been an illusion caused by two biases. A downward bias comes from failures to match survey respondents to their government records. These failures generate implausibly low registration rate estimates. An upward bias comes from survey respondents turning out to vote at a higher rate than non-respondents (and telling the truth about their behavior when answering survey questions). The apparent accuracy of “validated” estimates is due to the downward bias being large and the upward bias being smaller.
This creates a dilemma for researchers hoping to identify and employ the most accurate measure of respondents’ turnout behaviors in their empirical investigations. On the one hand, self-reports lead a few respondents who did not vote to be erroneously coded as having turned out. On the other hand, government records lead many more respondents who did vote to be wrongly coded as not having turned out. The former inflates sample registration rates, and the latter attenuates those rates. We look forward to engaging with the research community to identify rigorous, transparent, and broadly applicable solutions to an important problem in the study of voting.
[6] Click here for facts about non-citizens’ widespread usage of false identifications and Social Security numbers.
[7] “Guide to the 2022 Cooperative Election Study.” By Stephen Ansolabehere, Brian Schaffner, and Marissa Shih. Harvard/YouGov Cooperative Election Study, August 2023. <dataverse.harvard.edu>
Page 19:
Individual records were matched to the TargetSmart database of registered voters in the United States. Matching was performed in August 2023. It should be noted that a record may not be matched either because the individual is not registered to vote or because of incomplete or inaccurate information that prevented a match. Matches are made only with records for which there is a high level of confidence that the respondent is being assigned to the correct record. However, even by setting a high threshold of confidence, there will still be some false-positives which should be considered when using the validation records.
[8] “Expert Report of Jesse T. Richman in the Case of Mi Familia Vota v. Fontes.” October 13, 2023. <www.justfacts.com>
Page 72:
Each year the CES [Cooperative Election Study (CES) survey (formerly known as the Cooperative Congressional Election Study or CCES)] asks respondents their citizenship status with at least one question (and more recently with two questions) and asks respondents whether they were registered to vote or not. In addition, the CES long retained the voter file firm Catalist to match survey respondents with voter-file and commercial records in an effort to verify respondents’ statements of whether they were registered to vote. In 2022 the CES switched its voter file matching from Catalist to instead use the TargetSmart database.
[9] Calculated with data from the paper: “Do Non-Citizens Vote in U.S. Elections?” By Jesse T. Richman, Gulshan A. Chattha, and David C. Earnest. Electoral Studies, December 2014. Pages 149–157. <www.sciencedirect.com>
Page 150: “Of 339 non-citizens identified in the 2008 survey, Catalist matched 140 to a commercial (e.g. credit card) and/or voter database.”
CALCULATION: 140 / 339 = 41%
[10] Email from Just Facts to Dr. Jesse Richman, April 16, 2024:
What portion of the people who identified themselves as non-citizens in the 2022 CES were matched in the TargetSmart database?
Email from Dr. Jesse Richman to Just Facts, April 16, 2024:
It was 7.21 percent. … Unlike Catalist (especially in the earlier years of the CCES) targetsmart doesn’t seem to be matching on anything other than the voter registration list. Thus, if someone is matched by them, it’s mostly because they are registered to vote.
[11] Report: “Beyond the Core and Periphery: A New Look at Voter Participation Across Elections.” By Stephen Ansolabehere and Brian Schaffner. Harvard/YouGov Cooperative Congressional Election Study, November 30, 2015. <cces.gov.harvard.edu>
Pages 3–4:
The second source of data we analyze in this paper is a 1% sample (N=2,969,951) of American adults from Catalist. Catalist is a prominent voter file firm typically providing data to progressive clients, but also to academic institutions under a special subscription plan. Catalist maintains a database of information for nearly every American adult. The database is first built on voter file records acquired from all 50 states, and then a variety of different information is appended to that data from marketing firms, census data, and other sources. Catalist also builds several of its own models into the dataset to distinguish, for example, the partisanship, ideology, and political activism of each individual. The Catalist dataset is ideal for studying voter turnout because it includes precise information on each individual’s turnout behavior and is sufficiently large so that even relatively uncommon voter types can still be studied with precision.
[12] Webpage: “Catalist Data.” Catalist. Accessed November 15, 2016 at <bit.ly>
Catalist provides data and data-related services to progressive organizations to help them better identify, understand, and communicate with the people they need to enhance, persuade, and mobilize.
COMPREHENSIVE
Our national database contains more than 240 million unique voting-age individuals. We start with a rich, reliable foundation of 185 million registered voters—a unified national voter file—collected from Election Officials in all 50 states and the District of Columbia.
Commercial data adds another 55 million unregistered individuals and enhances the entire database with hundreds of fields, including household attributes, purchasing and investment profiles, donation behavior, occupational information, recreational interests, and engagement with civic and community groups.
We also integrate data from the Census, specialty data, and media market geographies. We have records going back more than a decade, giving our clients the unique ability to see both short-term and long-term trends.
ACCURATE
Catalist data is continually updated and audited by data quality experts. Catalist’s Data Operations team adheres to a rigorous multi-step quality assurance process that ensures that each update improves the quality of the database.
THE CATALIST NATIONAL DATABASE BY THE NUMBERS:
240 Million+ unique voting-age individuals
185 Million+ registered voters
55 Million+ unregistered voting age persons
NOTE: 240 million voting-age individuals = 96.3% of the U.S. adult population of 249,291,898 people in 2016 (when this Catalist webpage was accessed). [Calculated with the dataset: “Annual Estimates of the Resident Population by Single Year of Age and Sex for the United States: April 1, 2010 to July 1, 2019.” U.S. Census Bureau. Accessed May 9, 2024 at <www.census.gov>]
[13] “Register to Vote in Your State by Using This Postcard Form and Guide For U.S. Citizens.” U.S. Election Assistance Commission, September 21, 2022. <www.eac.gov>
Page 1:
How to Find Out If You Are Eligible to Register to Vote in Your State
Each State has its own laws about who may register and vote. Check the information under your State in the State Instructions. All States require that you be a United States citizen by birth or naturalization to register to vote in federal and State elections. Federal law makes it illegal to falsely claim U.S. citizenship to register to vote in any federal, State, or local election. You cannot be registered to vote in more than one place at a time.
[14] U.S. Code Title 18, Chapter 47, Section 1015: “Naturalization, Citizenship or Alien Registry.” Accessed October 20, 2022 at <www.law.cornell.edu>
(a) Whoever knowingly makes any false statement under oath, in any case, proceeding, or matter relating to, or under, or by virtue of any law of the United States relating to naturalization, citizenship, or registry of aliens; or
(b) Whoever knowingly, with intent to avoid any duty or liability imposed or required by law, denies that he has been naturalized or admitted to be a citizen, after having been so naturalized or admitted; or
(c) Whoever uses or attempts to use any certificate of arrival, declaration of intention, certificate of naturalization, certificate of citizenship or other documentary evidence of naturalization or of citizenship, or any duplicate or copy thereof, knowing the same to have been procured by fraud or false evidence or without required appearance or hearing of the applicant in court or otherwise unlawfully obtained; or
(d) Whoever knowingly makes any false certificate, acknowledgment or statement concerning the appearance before him or the taking of an oath or affirmation or the signature, attestation or execution by any person with respect to any application, declaration, petition, affidavit, deposition, certificate of naturalization, certificate of citizenship or other paper or writing required or authorized by the laws relating to immigration, naturalization, citizenship, or registry of aliens; or
(e) Whoever knowingly makes any false statement or claim that he is, or at any time has been, a citizen or national of the United States, with the intent to obtain on behalf of himself, or any other person, any Federal or State benefit or service, or to engage unlawfully in employment in the United States; or
(f) Whoever knowingly makes any false statement or claim that he is a citizen of the United States in order to register to vote or to vote in any Federal, State, or local election (including an initiative, recall, or referendum)—
Shall be fined under this title or imprisoned not more than five years, or both. Subsection (f) does not apply to an alien if each natural parent of the alien (or, in the case of an adopted alien, each adoptive parent of the alien) is or was a citizen (whether by birth or naturalization), the alien permanently resided in the United States prior to attaining the age of 16, and the alien reasonably believed at the time of making the false statement or claim that he or she was a citizen of the United States.
[15] Ruling: Matter of Margarita Del Pilar Fitzpatrick. U.S. Department of Justice, Executive Office for Immigration Review, Board of Immigration Appeals, May 7, 2015. <www.justice.gov>
An alien who has voted in an election involving candidates for Federal office in violation of 18 U.S.C. § 611(a) (2012) is removable under section 237(a)(6)(A) of the Immigration and Nationality Act, 8 U.S.C. § 1227(a)(6)(A) (2012), regardless of whether the alien knew that he or she was committing an unlawful act by voting. …
Because our determination that the respondent is removable under section 237(a)(6)(A) of the Act is dispositive of the appeal, we need not address whether she is also removable under section 237(a)(3)(D).
[16] “Guide to the 2022 Cooperative Election Study.” By Stephen Ansolabehere, Brian Schaffner, and Marissa Shih. Harvard/YouGov Cooperative Election Study, August 2023. <dataverse.harvard.edu>
Page 19:
Individual records were matched to the TargetSmart database of registered voters in the United States. Matching was performed in August 2023. It should be noted that a record may not be matched either because the individual is not registered to vote or because of incomplete or inaccurate information that prevented a match. Matches are made only with records for which there is a high level of confidence that the respondent is being assigned to the correct record. However, even by setting a high threshold of confidence, there will still be some false-positives which should be considered when using the validation records.
[17] Click here for facts about non-citizens’ usage of false identifications.
[18] “Guide to the 2022 Cooperative Election Study.” By Stephen Ansolabehere, Brian Schaffner, and Marissa Shih. Harvard/YouGov Cooperative Election Study, August 2023. <dataverse.harvard.edu>
Page 13:
The 2022 CES survey was conducted over the Internet by YouGov. The Common Content was asked of 60,000 adults interviewed in September–November 2022 (for pre-election data), and in November–December 2022 (for post-election data). The sampling method uses YouGov’s matched random sample methodology.
[19] Textbook: Mind on Statistics (4th edition). By Jessica M. Utts and Robert F. Heckard. Brooks/Cole Cengage Learning, 2012.
Pages 164–165:
Surveys that simply use those who respond voluntarily are sure to be biased in favor of those with strong opinions or with time on their hands. …
According to a poll taken among scientists and reported in the prestigious journal Science … scientists don’t have much faith in either the public or the media. … It isn’t until the end of the article that we learn who responded: “The study reported a 34% response rate among scientists, and the typical respondent was a white, male physical scientist over the age of 50 doing basic research.” … With only about a third of those contacted responding, it is inappropriate to generalize these findings and conclude that most scientists have so little faith in the public and the media.
[20] “Guide to the 2022 Cooperative Election Study.” By Stephen Ansolabehere, Brian Schaffner, and Marissa Shih. Harvard/YouGov Cooperative Election Study, August 2023. <dataverse.harvard.edu>
Page 13:
Sampling and Sample Matching
Sample matching is a methodology for selection of “representative” samples from non-randomly selected pools of respondents. It is ideally suited for Web access panels, but could also be used for other types of surveys, such as phone surveys. Sample matching starts with an enumeration of the target population. For general population studies, the target population is all adults, and can be enumerated through the use of the decennial Census or a high quality survey, such as the American Community Survey. …
The purpose of matching is to find an available respondent who is as similar as possible to the selected member of the target sample. The result is a sample of respondents who have the same measured characteristics as the target sample. Under certain conditions, described below, the matched sample will have similar properties to a true random sample. That is, the matched sample mimics the characteristics of the target sample. It is, as far as we can tell, representative of the target population (because it is similar to the target sample).
Page 15:
Weighting
The sample is weighted to adjust for any remaining imbalance that exists among the matched sample. Such imbalance results from the fact that the closest match for a particular individual from the target sample is not necessarily a perfect match across all demographics. The matched cases and the frame were combined and the combined cases were balanced on multiple moment conditions using the politically representative citizen frame.
[21] Paper: “Do Non-Citizens Vote in U.S. Elections?” By Jesse T. Richman, Gulshan A. Chattha, and David C. Earnest. Electoral Studies, December 2014. Pages 149–157. <www.sciencedirect.com>
Page 151:
It is impossible to tell for certain whether the non-citizens who responded to the survey were representative of the broader population of non-citizens, but some clues can be gained by examining education levels. … We confront this issue primarily by weighting the data.
Throughout the analysis (with the exception of the appendix) we report results produced from weighted data. Weight construction began with CCES [Cooperative Congressional Election Study] case weights, but then adjusted these by race to match the racial demographic of the non-citizen population. Our concern with using regular CPS [Current Population Survey] case-weights was that weights were constructed based upon overall demographic characteristics without attention to the demographic character of the non-citizen population. … Weighting produces a non-citizen sample that appears to be a better match with Census estimates of the population. For instance, 32.5 percent of the weighted sample had no high school degree. …
… Among the 337 immigrant non-citizens who responded to the CCES, 50 (14.8%) indicated in the survey that they were registered.
[22] Email from Dr. Jesse Richman to Just Facts, April 16, 2024:
“Voter Registration Status … Yes [=] 32 … No [=] 441 … Don’t know [=] 18”
CALCULATION: 32 / (32 + 441) = 6.8%
[23] Poll: “National Hispanic Survey Results.” By John McLaughlin. McLaughlin & Associates, June 21, 2013. <mclaughlinonline.com>
Page 3:
This bi-lingual national survey of 800 Hispanics was conducted from June 5th through June 16th, 2013.
Interview selection was within predetermined census units of Hispanic adults. 560 interviews were conducted via landline telephone by professional interviewers. To increase coverage, this landline sample was supplemented with 240 interviews, 30%, conducted via internet of cellphone only users. 64% of all respondents use cell phones. 60% of all interviews were conducted in Spanish. 93% of all respondents speak at least some Spanish at home. These samples were then combined and structured to correlate with actual adult Hispanic census population.
Page 4:
The uniqueness of this poll is that it is very strong demographically and methodologically. 60% of the interviews were actually conducted in Spanish; 76% speak Spanish mostly or equally. 23% always speak Spanish; 93% speak at least some Spanish at home; 30% of the interviews were conducted among cell phone only users. 64% of Hispanic adults have cell phones.
Page 68: “Voter Profile … Non-Citizen … Registered [=] 13%”
NOTE: Credit for bringing this poll to attention belongs to Rowan Scarborough of the Washington Times.
[24] Email from Dr. Jesse Richman to Just Facts, April 16, 2024:
“Voter Registration Status … Yes [=] 32 … No [=] 441 … Don’t know [=] 18”
CALCULATION: 32 / (32 + 441) = 6.8%
[25] Paper: “How Well Does the American Community Survey Count Naturalized Citizens?” By Jennifer Van Hooka and James D. Bachmeierb. Demographic Research, July 2, 2013. <www.demographic-research.org>
Page 2: “In the United States, data on naturalization and citizenship largely come from Census Bureau surveys, such as the Current Population Survey (CPS), the long form of the decennial Census (2000 and earlier), and the American Community Survey (ACS).”
Page 3:
There are good reasons to suspect that citizenship is inaccurately estimated in Census data. During the late 1990s, Passel and Clark (1997) compared the number of persons that are reported as naturalized in the 1990 Census and the 1996 Current Population Survey (CPS) with the number of naturalized citizens based on administrative data from the Immigration and Naturalization Service (INS). They found the Census/CPS estimates to be much higher than the INS-based estimates for two groups. Among new arrivals (those in the U.S. fewer than five years) from all national origins, about 75% of those who were reported as naturalized were probably not. Among longer-resident Mexican and Central American immigrants, about one-third of those who were reported as naturalized were probably not.
Page 5:
To assess the current level of citizenship reporting error, we estimated the number of naturalized citizens in mid-year 2010 by age group, sex, region of origin, and duration of residence based on the number of Office of Immigration Statistics (OIS) naturalization records. We then compared the OIS-based estimates with the corresponding numbers in the 2010 American Community Survey (ACS) (also a mid-year estimate). The difference between the two provides an indication of over- or under-representation of naturalized citizenship in the ACS.
Page 17:
Table 2 reports the naturalization estimates by sex, region of birth, and duration of U.S. residence. For both men and women from all origin regions, the estimated number of naturalized citizens in the ACS is substantially and significantly higher than the OIS-based estimates among immigrants with fewer than five years in the U.S. For example, the number of naturalized Mexican men with fewer than five years of U.S. residence is nearly 27 times higher (2587%) in the ACS than the OIS estimates. Another way to express this is that among the 16 thousand reporting as citizens in the ACS, only about 600 (or about 4 percent) are likely to actually be naturalized citizens. Among those in the U.S. for five or more years, the OIS-ACS gap is much lower in relative terms, and concentrated among Mexican men.
Page 19:
In Table 3, OIS and ACS estimates are presented for Mexican and non-Mexican men and women by age group by varying rates of emigration. We note that the OIS estimates do not always decline as emigration increases from the “low” to the “moderate” to the “high” series because of age crossovers in various emigration estimates. Regardless of assumptions about emigration, ACS estimates are especially high relative to the OIS-based estimates among Mexican men of all age groups and Mexican women aged 40 and older. The same pattern does not hold among non-Mexicans, among whom the discrepancy remains relatively low across all age groups.
[26] Click here for facts about non-citizens’ widespread usage of false identifications and Social Security numbers.
[27] “Expert Report of Jesse T. Richman in the Case of Mi Familia Vota v. Fontes.” October 13, 2023. <www.justfacts.com>
Page 72:
Each year the CES [Cooperative Election Study (CES) survey (formerly known as the Cooperative Congressional Election Study or CCES)] asks respondents their citizenship status with at least one question (and more recently with two questions) and asks respondents whether they were registered to vote or not. In addition, the CES long retained the voter file firm Catalist to match survey respondents with voter-file and commercial records in an effort to verify respondents’ statements of whether they were registered to vote. In 2022 the CES switched its voter file matching from Catalist to instead use the TargetSmart database.
[28] Calculated with data from the paper: “Do Non-Citizens Vote in U.S. Elections?” By Jesse T. Richman, Gulshan A. Chattha, and David C. Earnest. Electoral Studies, December 2014. Pages 149–157. <www.sciencedirect.com>
Page 150: “Of 339 non-citizens identified in the 2008 survey, Catalist matched 140 to a commercial (e.g. credit card) and/or voter database.”
CALCULATION: 140 / 339 = 41%
[29] Email from Just Facts to Dr. Jesse Richman, April 16, 2024:
What portion of the people who identified themselves as non-citizens in the 2022 CES were matched in the TargetSmart database?
Email from Dr. Jesse Richman to Just Facts, April 16, 2024:
It was 7.21 percent. … Unlike Catalist (especially in the earlier years of the CCES) targetsmart doesn’t seem to be matching on anything other than the voter registration list. Thus, if someone is matched by them, it’s mostly because they are registered to vote.
[30] Report: “Beyond the Core and Periphery: A New Look at Voter Participation Across Elections.” By Stephen Ansolabehere and Brian Schaffner. Harvard/YouGov Cooperative Congressional Election Study, November 30, 2015. <cces.gov.harvard.edu>
Pages 3–4:
The second source of data we analyze in this paper is a 1% sample (N=2,969,951) of American adults from Catalist. Catalist is a prominent voter file firm typically providing data to progressive clients, but also to academic institutions under a special subscription plan. Catalist maintains a database of information for nearly every American adult. The database is first built on voter file records acquired from all 50 states, and then a variety of different information is appended to that data from marketing firms, census data, and other sources. Catalist also builds several of its own models into the dataset to distinguish, for example, the partisanship, ideology, and political activism of each individual. The Catalist dataset is ideal for studying voter turnout because it includes precise information on each individual’s turnout behavior and is sufficiently large so that even relatively uncommon voter types can still be studied with precision.
[31] Webpage: “Catalist Data.” Catalist. Accessed November 15, 2016 at <bit.ly>
Catalist provides data and data-related services to progressive organizations to help them better identify, understand, and communicate with the people they need to enhance, persuade, and mobilize.
COMPREHENSIVE
Our national database contains more than 240 million unique voting-age individuals. We start with a rich, reliable foundation of 185 million registered voters – a unified national voter file—collected from Election Officials in all 50 states and the District of Columbia.
Commercial data adds another 55 million unregistered individuals and enhances the entire database with hundreds of fields, including household attributes, purchasing and investment profiles, donation behavior, occupational information, recreational interests, and engagement with civic and community groups.
We also integrate data from the Census, specialty data, and media market geographies. We have records going back more than a decade, giving our clients the unique ability to see both short-term and long-term trends.
ACCURATE
Catalist data is continually updated and audited by data quality experts. Catalist’s Data Operations team adheres to a rigorous multi-step quality assurance process that ensures that each update improves the quality of the database.
THE CATALIST NATIONAL DATABASE BY THE NUMBERS:
240 Million+ unique voting-age individuals
185 Million+ registered voters
55 Million+ unregistered voting age persons
NOTE: 240 million voting-age individuals = 96.3% of the U.S. adult population of 249,291,898 people in 2016 (when this Catalist webpage was accessed). [Calculated with the dataset: “Annual Estimates of the Resident Population by Single Year of Age and Sex for the United States: April 1, 2010 to July 1, 2019.” U.S. Census Bureau. Accessed May 9, 2024 at <www.census.gov>]
[32] Click here for facts about non-citizens’ widespread usage of false identifications and Social Security numbers.
[33] “Expert Report of Jesse T. Richman in the Case of Mi Familia Vota v. Fontes.” October 13, 2023. <www.justfacts.com>
Page 72:
Each year the CES [Cooperative Election Study (CES) survey (formerly known as the Cooperative Congressional Election Study or CCES)] asks respondents their citizenship status with at least one question (and more recently with two questions) and asks respondents whether they were registered to vote or not. In addition, the CES long retained the voter file firm Catalist to match survey respondents with voter-file and commercial records in an effort to verify respondents’ statements of whether they were registered to vote. In 2022 the CES switched its voter file matching from Catalist to instead use the TargetSmart database.
[34] Calculated with data from the paper: “Do Non-Citizens Vote in U.S. Elections?” By Jesse T. Richman, Gulshan A. Chattha, and David C. Earnest. Electoral Studies, December 2014. Pages 149–157. <www.sciencedirect.com>
Page 150: “Of 339 non-citizens identified in the 2008 survey, Catalist matched 140 to a commercial (e.g. credit card) and/or voter database.”
CALCULATION: 140 / 339 = 41%
[35] Email from Just Facts to Dr. Jesse Richman, April 16, 2024:
What portion of the people who identified themselves as non-citizens in the 2022 CES were matched in the TargetSmart database?
Email from Dr. Jesse Richman to Just Facts, April 16, 2024:
It was 7.21 percent. … Unlike Catalist (especially in the earlier years of the CCES) targetsmart doesn’t seem to be matching on anything other than the voter registration list. Thus, if someone is matched by them, it’s mostly because they are registered to vote.
[36] Report: “Beyond the Core and Periphery: A New Look at Voter Participation Across Elections.” By Stephen Ansolabehere and Brian Schaffner. Harvard/YouGov Cooperative Congressional Election Study, November 30, 2015. <cces.gov.harvard.edu>
Pages 3–4:
The second source of data we analyze in this paper is a 1% sample (N=2,969,951) of American adults from Catalist. Catalist is a prominent voter file firm typically providing data to progressive clients, but also to academic institutions under a special subscription plan. Catalist maintains a database of information for nearly every American adult. The database is first built on voter file records acquired from all 50 states, and then a variety of different information is appended to that data from marketing firms, census data, and other sources. Catalist also builds several of its own models into the dataset to distinguish, for example, the partisanship, ideology, and political activism of each individual. The Catalist dataset is ideal for studying voter turnout because it includes precise information on each individual’s turnout behavior and is sufficiently large so that even relatively uncommon voter types can still be studied with precision.
[37] Webpage: “Catalist Data.” Catalist. Accessed November 15, 2016 at <bit.ly>
Catalist provides data and data-related services to progressive organizations to help them better identify, understand, and communicate with the people they need to enhance, persuade, and mobilize.
COMPREHENSIVE
Our national database contains more than 240 million unique voting-age individuals. We start with a rich, reliable foundation of 185 million registered voters—a unified national voter file—collected from Election Officials in all 50 states and the District of Columbia.
Commercial data adds another 55 million unregistered individuals and enhances the entire database with hundreds of fields, including household attributes, purchasing and investment profiles, donation behavior, occupational information, recreational interests, and engagement with civic and community groups.
We also integrate data from the Census, specialty data, and media market geographies. We have records going back more than a decade, giving our clients the unique ability to see both short-term and long-term trends.
ACCURATE
Catalist data is continually updated and audited by data quality experts. Catalist’s Data Operations team adheres to a rigorous multi-step quality assurance process that ensures that each update improves the quality of the database.
THE CATALIST NATIONAL DATABASE BY THE NUMBERS:
240 Million+ unique voting-age individuals
185 Million+ registered voters
55 Million+ unregistered voting age persons
NOTE: 240 million voting-age individuals = 96.3% of the U.S. adult population of 249,291,898 people in 2016 (when this Catalist webpage was accessed). [Calculated with the dataset: “Annual Estimates of the Resident Population by Single Year of Age and Sex for the United States: April 1, 2010 to July 1, 2019.” U.S. Census Bureau. Accessed May 9, 2024 at <www.census.gov>]
