Efforts by DHS to Estimate 

Southwest Border Security 

between Ports of Entry

OFFICE OF IMMIGRATION STATISTICS

September 2017
1

Office of Immigration Statistics

OFFICE OF STRATEGY, POLICY, AND PLANS

Securing the southwest land border against illegal immigration, smuggling of drugs and 

other contraband, and terrorist activities is a key part of the Department of Homeland Security’s

(DHS) mission, and a top priority for the White House, Congress, and the American public. On 

January 25, 2017, President Trump signed an Executive Order on “Border Security and 

Immigration Enforcement Improvements,” reflecting these concerns. 

In light of the effort and resources the Department has devoted to border security in recent 

decades, as well as the sustained public attention to the southwest border, Congress has directed 

the Department to provide more detailed reporting on southwest border security. The 

Consolidated Appropriations Act, 2017 directs the Department to publish “metrics developed to 

measure the effectiveness of security between the ports of entry, including the methodology and 

data supporting the resulting measures.”1

While DHS employs a number of concrete metrics to track border security operations, it is 

difficult to precisely quantify illegal flows because illegal border crossers actively seek to evade 

detection, and some flows are undetected. As a result, any effort to quantify illegal flows or 

calculate an overall enforcement success rate must rely on one or more estimation techniques. 

Measurement is also difficult because of the diversity and complexity of the enforcement mission 

along the United States’ 2,000-mile land border with Mexico.

For many years, the legacy Immigration and Naturalization Service addressed these

challenges by relying on alien apprehensions as its proxy measure of illegal immigration between 

ports of entry. More recently, the U.S. Border Patrol (USBP) and DHS have initiated a number of 

new estimation strategies to better model unknown flows.2 Some of this research remains a work 

in progress as DHS is not yet able to validate certain modeling assumptions or to quantify the 

uncertainty around its new estimation techniques. This report describes an array of indicators that, 

taken together, provide additional insight into the state of southwest border security between 

ports of entry (POEs). These indicators fall within two broad categories:

Estimated enforcement outputs refer to the immediate impact of enforcement policies. In 

particular: how difficult is it for immigrants to cross the border illegally?

 Apprehension or interdiction rate: the estimated share of intending border crossers that is 

apprehended or interdicted while attempting an illegal entry.

 Deterrence rate: the estimated share of unsuccessful border crossers who, following an 

apprehension, choose to remain in Mexico or return home rather than make an additional 

crossing attempt.

 Border crossing costs: estimated average fees paid by illegal border crossers to migrant 

smugglers.

 

1 P.L. 115-31, Division F, §107(b). The Fiscal Year 2017 National Defense Authorization Act (P.L. 114-328) also directs the Department to 

report on a more comprehensive set of border enforcement measures; the Department will publish the required Border Security 

Metrics Report in 2017.

2 Preventing illegal immigration across the southwest land border is just one element of border security. CBP is charged with 

securing all U.S. borders, at and between POE, against terrorists, illegal drugs, and other contraband, and with facilitating legitimate 

immigration and trade, among other responsibilities. DHS’ overall border security and immigration enforcement missions also 

include combatting visa overstays and detaining and removing certain aliens from the interior of the United States, among other 

priorities. The report focuses exclusively metrics of illegal migration between ports of entry, and does not address this broader set 

of border security and immigration enforcement issues.
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Office of Immigration Statistics

OFFICE OF STRATEGY, POLICY, AND PLANS

Estimated enforcement outcomes describe the bottom line number: how many people succeed in crossing 

the border illegally between POEs?

 Migrant apprehensions: USBP’s count of migrant apprehensions serves as a long-standing 

proxy measure of illegal flows.

 Known got aways: the estimated number of intending border crossers whom USBP directly 

or indirectly observes making a successful illegal entry.

 Estimated illegal inflows: based on a statistical model, the total estimated number of illegal 

border crossers who successfully enter the United States between POEs.

In light of still-unresolved concerns about some of this research, USBP and DHS also

continue to pursue additional analytical frameworks to produce the most accurate possible 

estimates of the current state of border security. As USBP continues to increase domain awareness, 

the Department anticipates more precise observational estimates over time. These additional 

methodologies are in line with both the NDAA and the Presidential Executive Order 13767,

“Border Security and Immigration Enforcement Improvements.”

This report describes these recent and ongoing efforts by DHS and USBP to better estimate 

southwest border security between POEs. For each indicator identified above, the report 

summarizes available data sources and techniques, explains the measure’s strengths and 

limitations, and presents available data. The report also describes the latest efforts by USBP to 

increase situational awareness at the border—an effort with important operational implications 

that also yields increasingly robust observational estimates of border security. A concluding section 

reviews recent trends and assesses the current state of border security. This report focuses 

exclusively on these specific efforts by the Department to better model unobservable factors that 

reflect the difficulty of crossing the border and the level of illegal migration flows between ports 

of entry along the southwest border; two forthcoming reports by the Department will present a 

more comprehensive set of enforcement metrics as directed by the Fiscal Year 2017 National Defense 

Authorization Act (NDAA, P.L. 114-328) and a broader analysis of the Department’s enterprise-wide 

border security efforts as directed by Executive Order 13767.
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Office of Immigration Statistics

OFFICE OF STRATEGY, POLICY, AND PLANS

I. Enforcement Outputs

Enforcement outputs describe the immediate impacts of border security policies: how 

difficult is it for unauthorized immigrants to cross the border? Estimation strategies and data are 

available for three types of output indicators: apprehension or interdiction rate, deterrence rate, 

and border crossing costs. Notably, while apprehension and interdiction rate depend entirely on 

actions by USBP to secure the border itself, deterrence rate and border crossing costs are also 

influenced by enterprise-wide enforcement efforts involving other components within DHS as 

well as other federal, state, and local actors.

Apprehension or Interdiction Rate

The apprehension rate refers to the share of intending border crossers that is successfully 

apprehended by USBP, and the interdiction rate refers to the share that is either apprehended or 

“turned back,” meaning the alien abandons his or her crossing attempt and returns to Mexico. 

These are intuitive indicators because a perfect apprehension or interdiction rate would result in a 

perfectly secure border, though analysts do not consider this goal to be realistic or cost effective.3

In principle, DHS would calculate the apprehension or interdiction rate by dividing the 

number of intending aliens who are apprehended or interdicted by the total number attempting 

illegal entry, i.e., by the sum of apprehensions or interdictions and successful illegal entries. As 

noted above, missing information about successful illegal entries—sometimes referred to as the 

“denominator problem”—rules out this direct approach. As a result, DHS currently relies on three 

main approaches to estimate apprehension or interdiction rates. 

Survey Data on Apprehension Rate

Several government and academic institutions sponsor long-running migrant surveys that 

include questions about migrants’ experiences trying to cross the border, including how often 

they crossed illegally and how often they were apprehended when attempting to cross.

4 Survey 

data can be used to estimate an overall apprehension rate by dividing the total number of illegal 

entries by the sum of illegal entries and apprehensions in the survey sample, but this remedy to 

the “denominator problem” only shifts challenges to survey design and its true coverage.

 

3 See for example, U.S. GAO Director of Homeland Security and Justice Issues Rebecca Gambler, Testimony before U.S. House 

Committee on Homeland Security, Subcommittee on Border and Maritime Security, “Border Patrol: Goals Not Yet in Place to 

Inform Border Security Status and Resource Needs,” GAO-13-330T, February 26, 2013, 

http://www.gao.gov/assets/660/652331.pdf; Edward Alden, “Immigration and Border Control,” Cato Journal 32, 1 (Winter 

2012): 107-124, https://object.cato.org/sites/cato.org/files/serials/files/cato-journal/2012/1/cj32n1-8.pdf. 

4 Key surveys include the Mexican Migration Project (MMP), a binational household survey by Princeton University and the 

University of Guadalajara (Mexico) conducted annually in Mexico and the United States every year since 1982; the Mexican 

Migration Field Research Program (MMFRP), a binational household head survey by the University of California – San Diego 

conducted every year since 2004 in a rotating set of three migrant-sending communities in Mexico and corresponding migration 

destinations in the United States; and the Survey of Migration at Mexico’s Northern Border (EMIF, by its Spanish acronym), 

sponsored by the Mexican government and the College of the Northern Border and conducted annually since 1993 among samples 

of north- and south-bound migrants, including deportees. See Alicia Carriquiry and Malay Majmundar, eds., Options for Estimating 

Illegal Entries at the U.S.-Mexico Border, National Academies Press, 2013.

The USBP also collects information from detainees for intelligence purposes, and since 2011 the Alien Smuggler 

Identification and Deterrence (ASID) unit has attempted to interview a sample of aliens from each group apprehended from each 

station in each southwest border sector to gain situational awareness and to support tactical operations and criminal investigations.
4

Office of Immigration Statistics

OFFICE OF STRATEGY, POLICY, AND PLANS

A key advantage to migrant survey data is that they provide first-hand information about 

the apprehension rate: unauthorized migrants know how often they are apprehended. Yet survey 

data should be treated as estimates and interpreted with caution given the difficulty of 

constructing a valid sample of successful and unsuccessful border crossers. Migrants also may 

intentionally misrepresent their histories, particularly when being interviewed by USBP.

Academic surveys led by Princeton University, the University of California – San Diego, 

and the College of the Northern Border in Mexico have reported apprehension rates of 

between 30 and 50 percent.5

Interdiction Effectiveness Rate and Total Interdiction Rate

The Interdiction Effectiveness Rate (IER) and Total Interdiction Rate (TIR) are calculated by 

dividing interdictions by estimated total illegal attempts. Both terms define interdictions the same 

way, as the sum of USBP apprehensions and USBP’s observational estimate of turn backs (see text 

box on following page). The terms differ in how they define total attempts: IER defines the 

denominator as the sum of apprehensions, turn backs, and the USBP observational estimate of 

known illegal entries, or “got aways” (see text box on following page); and TIR defines the 

denominator as the sum of apprehensions, turn backs, and a model-based estimate of total illegal 

entries developed for DHS by the Institute for Defense Analyses (IDA):

6

IER =

Apprehensions + Turn backs

Apprehensions + Turn backs + Got aways

TIR =

Apprehensions + Turn backs

Apprehensions + Turn backs + Estimated illegal entries

An advantage to examining these interdiction rates, rather than an apprehension rate, is that they 

capture USBP’s actual enforcement practices, which include efforts to turn back border crossers, in 

addition to efforts to apprehend them. On the other hand, some analysts consider IER and TIR to 

be ambiguous indicators of enforcement success since an unknown share of turn backs make 

additional entry attempts.

As noted, IER and TIR rely on a mix of several different types of data: apprehensions are 

based on USBP administrative data; turn backs and got aways are estimates based on USBP agent 

observations; and estimated illegal entries are calculated from a mix of administrative and survey 

data. Therefore, there is not a straightforward way to describe the statistical significance of these

estimates.

An advantage to using USBP’s observational estimates of turn backs and got aways in the 

IER is that these data are based on methodology USBP has been refining for over a decade, and one 

that the agency relies on for operational planning purposes.7 By relying exclusively on agent 

 

5 El Colegio de la Frontera Norte, EMIF North: 2015 Annual Indicators, http://www.colef.mx/emif/eng/indicadores.php; 

Argueta, “Immigration Enforcement between Ports of Entry.”

6 See John W. Bailey et al., “Assessing Southern Border Security,” Institute for Defense Analyses, IDA Paper NS P-5304, May 2016.

7 In addition, since 2015, USBP has reported the IER in its Annual Performance Report as a performance measure pursuant to the 

Government Performance and Results Modernization Act (GPRMA) of 2010 (Pub. L. No. 111-352 § 4, 124 Stat. 3866, 3871-73 

(codified at 31 U.S.C. § 1116)).
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Office of Immigration Statistics

OFFICE OF STRATEGY, POLICY, AND PLANS

observations—both direct and indirect—turn backs and got aways are concrete approaches to 

estimating flows. The primary disadvantage to turn back and got away data has already been 

identified: that they exclude an unknown number of unobserved got aways—though USBP’s 

recent work to increase situational awareness, including through the use of Geospatial Intelligence, 

gives the Department growing confidence in its got away count (see Known Got Aways). An 

additional limitation to turn back and got away data is that they aggregate potentially subjective 

observations from thousands of individual agents, though USBP has taken a number of steps to 

establish reliable turn back and got away methodologies (see text box).

TIR, unlike IER, includes an estimate of total attempts in the denominator (i.e., estimated 

total illegal entries). However, the methodology used to calculate TIR makes a number of 

modeling assumptions that are difficult to validate or refine, as discussed below.

Figure 1 describes the IER and TIR for 2006 – 2016. As the figure indicates, IER increased 

from 69 percent in 2006 to 83 percent in 2016, while TIR increased from 49 percent to 75

percent during the same period. Notably, as long as some illegal entries evade USBP detection, the 

difference between known got aways and total illegal entries means that IER should always exceed 

TIR. The convergence of the two trends since 2006 suggests that as USBP works to increase 

domain awareness they are observing a larger share of border crossers.

USBP Methodology for Counting Turn Backs and Got Aways

Illegal crossings primarily result in one of four potential outcomes: (1) a failed attempt 

resulting in an apprehension, (2) a detected successful entry or known got away, (3) a 

detected turn back, or (4) an undetected, presumably successful entry or unknown got away. 

Since 2006, CBP agents at the southwest land border have reported on turn backs and got 

aways. A got away is defined as a subject who, after making an illegal entry, is not turned back 

or apprehended, and is no longer being actively pursued by USBP agents. A turn back is 

defined as a subject who, after making an illegal entry into the United States, returns to the 

country from which he or she entered, not resulting in an apprehension or got away.

Since 2014, USBP agents use standard border-wide definitions for determining when to 

report a subject as a got away or turn back. Some subjects are observed directly as evading 

apprehension or turning back; others are acknowledged as got aways or turn backs after agents 

follow evidence that indicate entries have occurred such as foot sign, sensor activations, 

interviews with apprehended subjects, camera views, and communication between and among 

stations and sectors. The scope of these data includes all areas of the southwest land border at 

or below the northernmost law enforcement posture (typically a USBP checkpoint) within a 

given area of responsibility, and those individuals apprehended less than 30 days after entering 

the United States. 

In an effort to maintain reliable best practices, command staff at all southern border 

stations ensure all agents are aware of and utilize proper definitions for apprehensions, got 

aways and turn backs at their respective stations. They also ensure the necessary 

communication takes place between and among sectors and stations to minimize doublecounting when subjects cross more than one station’s area of responsibility. In addition to 

station-level safeguards, designated USBP Headquarters components validate data integrity by 

utilizing various data quality reports.
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Office of Immigration Statistics

OFFICE OF STRATEGY, POLICY, AND PLANS

Figure 1: Interdiction Effectiveness Rate and Total Interdiction Rate, 2006-2016

Source: U.S. Border Patrol; Office of Immigration Statistics calculations based on data provided by the IDA Corporation.

Notes: Data for 2006-2013 should be interpreted with caution since USBP first established uniform methodologies for estimating 

turn backs and got aways in 2014. TIR also should be interpreted with caution since DHS is still working to validate or refine a 

methodology for estimating total illegal inflows.

Partial Apprehension Rate

IDA’s methodology for estimating illegal entries is based on an estimated apprehension 

rate for only a particular subset of border crossers and is, therefore considered to be a partial 

apprehension rate (PAR). The PAR is estimated based on a long-standing social science 

methodology known as the Repeated Trials Model (RTM).8 The approach focuses on illegal border 

crossers who are apprehended and deported to the Mexican border and who make a subsequent 

re-entry attempt. The logic of the PAR is to use USBP biometric data to assess what share of 

migrants who make repeated entry attempts is subsequently re-apprehended, and to assume that 

this re-apprehension rate is an indicator of the overall apprehension rate. 

The PAR methodology consists of three main steps (see Figure 2). First, the model 

identifies a subset of illegal border crossers who are candidates to attempt re-entry, the so-called 

RTM population. Under IDA’s methodology, this group excludes all non-Mexicans, those deported 

to the Mexican interior or remotely through the Alien Transfer and Exit Program, aliens who have 

ever requested asylum, those facing criminal charges, and children under 18 years old. 

 

8 For a fuller discussion see Bailey et al. 2016.; Thomas J. Espenshade, “Using INS Border Apprehension Data to Measure the Flow 

of Undocumented Migrants Crossing the U.S.-Mexico Frontier,” International Migration Review (1995): 545-565; Joseph Chang, “CBP 

Apprehensions at the Border,” Homeland Security Studies and Analysis Institute, 2006. 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

IER TIR
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Office of Immigration Statistics

OFFICE OF STRATEGY, POLICY, AND PLANS

Figure 2: Partial Apprehension Rate Methodology

Source: OIS adaptation of Bailey et al. 2016.

The second step in calculating the PAR is to distinguish between deportees who give up 

and return home or otherwise remain in Mexico versus those who attempt to re-enter the United 

States—i.e., the deterrence rate (see Deterrence Rate). IDA estimates this share based on an analysis 

of a survey of recent deportees conducted by the College of the Northern Border, the so-called 

EMIF survey (see Survey Data on Deterrence).

Third, by definition, RTM assumes deportees who are not deterred following an 

apprehension always make a subsequent reentry attempt. Thus, by observing in DHS 

administrative records how many migrants from the RTM population are re-apprehended, the 

model infers the number that successfully re-enters. The ratio of re-apprehensions to successful reentries is used to estimate the partial apprehension rate. 

The PAR takes advantage of USBP’s collection of biometric data since 2000, and represents 

an advance in the Department’s efforts to quantify the southwest border apprehension rate. Unlike 

IER and TIR, the model does not depend on agent observations; and it grapples with unobserved 

flows by assuming that aliens who are not apprehended fall into one of two meaningful outcome 

groups: those who are deterred or those who evade detection.

Nonetheless, the model confronts limitations at each point in the modeling process. The 

most notable and challenging to overcome is the assumption of the RTM that subjects who are not 

deterred will always attempt re-entry until successful. One problem with this assumption is the 

lack of reliable data on who is deterred. IDA relies primarily on the EMIF survey to estimate the 

deterrence rate. And while the EMIF is widely recognized as one of the best migrant surveys 

available, its results are still dependent on the characteristics of the sample, the quality of the 

survey instrument, and the honesty of the respondents. More fundamentally, the EMIF survey asks 

recent deportees about their intentions to re-enter the United States, and it therefore does not take 

account of shifting border enforcement efforts, potential changes in behavior by individuals who 

have been exposed to consequence programs, or other deterrent factors along the border. The 

structure of the RTM model means that any resulting undercount in the estimate of the deterred 

population results in a downward bias in the PAR.
8

Office of Immigration Statistics

OFFICE OF STRATEGY, POLICY, AND PLANS

Second, the RTM population represents a shrinking share of southwest border 

apprehensions. Mexican adults quickly deported to the nearest border accounted for about 95 

percent of apprehensions when the RTM methodology was developed in the 1990s. But changes 

in the composition of border flows (i.e., rising numbers of Central Americans and asylum 

seekers); changes in CBPs enforcement strategy to emphasize criminal charges, lateral repatriation, 

and other enforcement consequences; and IDA’s restrictive modeling choices mean that as little as 

20 percent of USBP apprehensions in recent years are used to estimate the PAR. In addition, 

because the RTM sample excludes aliens who are more likely to surrender to USBP (i.e., aliens 

with a higher apprehension rate), the PAR is biased downwards as an indicator of the overall 

apprehension rate; this bias may be substantial given the number of aliens excluded from the RTM 

sample.

Third, IDA makes somewhat restrictive assumptions about which re-apprehensions to 

include in the final stage of the PAR calculation. In particular, IDA excludes apprehensions 

occurring at check points and other remote locations and those occurring more than four days 

after an illegal entry. Given USBP’s defense-in-depth strategy, which places resources at and 

behind the border, these assumptions result in a slight further downward bias in the PAR.

Figure 3 depicts IDA’s estimate of the PAR for the Mexican RTM population for 2000-

2016, the years for which data are available. IDA estimates that the PAR fell from 43 percent in 

2000, to a low of 33 percent in 2003, before climbing to an average of 55 percent in 2014-2016.

Figure 3: IDA Estimate of Partial Apprehension Rate, 2000-2016

Source: IDA Corporation.

Note: Data includes the estimated apprehension rate for Mexican adults in the RTM group of border crossers; see text for further 

explanation.

0%

10%

20%

30%

40%

50%

60%

20002001200220032004200520062007200820092010201120122013201420152016
9

Office of Immigration Statistics

OFFICE OF STRATEGY, POLICY, AND PLANS

Deterrence Rate

A second indicator of enforcement outputs is the deterrence rate (also referred to as the atthe-border deterrence rate), defined as the estimated share of migrants who, following a failed 

unlawful entry attempt, are deterred from making a subsequent reentry and decide instead to 

return home or otherwise remain in Mexico. The deterrence rate is a powerful indicator of the 

difficulty of crossing the border because it reflects decisions by people who have already decided 

to migrate illegally to abandon their effort. As with the apprehension or interdiction rate, 

deterrence cannot be observed directly. DHS relies on two main estimation strategies.

Recidivism Rate

CBP’s primary methodology for estimating deterrence is recidivism, defined as the 

percentage of deportable aliens that is re-apprehended in the same fiscal year, based on an analysis 

of fingerprint data captured at the time of apprehension. Recidivism is inversely related to 

deterrence because only migrants who are not deterred have the opportunity to be reapprehended. Thus, CBP’s Consequence Delivery System uses reductions in recidivism as an 

indicator of effective enforcement consequences.

9

An advantage to relying on recidivism as an (inverse) indicator of deterrence is that it can 

be reliably measured (i.e., not just estimated) through CBP’s fingerprint records. Recidivism is an 

imperfect metric of deterrence, however, because re-apprehensions are a function of both 

deterrence and the (re-)apprehension rate, as noted above. In other words, a drop in recidivism 

may reflect fewer deportees making re-entry attempts, or a higher success rate among those who 

make such attempts, or both.

As figure 4 illustrates, the southwest border recidivism rate declined from 31 percent in 

2005 (the first year for which data are available) to 12 percent in 2016, a trend which suggests 

fewer deportees making additional re-entry attempts. The sharp drop in recidivism since 2014 

likely also reflects the growing share of non-Mexicans among border apprehensions, as aliens 

deported to more remote countries face greater barriers to making a further migration attempt.

 

9 See DHS Office of Inspector General, “Streamline: Measuring Its Effect on Illegal Border Crossing,” OIG-15-95, May 15, 2015, 

https://www.oig.dhs.gov/assets/Mgmt/2015/OIG_15-95_May15.pdf; Fisher 2011; Argueta 2016.
10 Office of Immigration Statistics

OFFICE OF STRATEGY, POLICY, AND PLANS

Figure 4: Recidivist Apprehensions as a Percentage of Total Apprehensions, 2005-2016

 Source: U.S. Border Patrol.

Survey Data on Deterrence

An alternative methodology for estimating deterrence is to rely on migrants surveys. The 

most important survey data on deterrence comes from the EMIF Devueltos survey, which 

interviews deportees immediately at repatriation facilities upon their return to Mexico and asks

them about their intentions to return to the United States within the next 7-90 days. In its work 

for DHS, the IDA Corporation used a combination of EMIF and CBP data to build an econometric 

model of 90-day deterrence for all USBP apprehensions since 2000.

10

An advantage to survey data is that surveys can specifically identify intending border 

crossers who describe themselves as being deterred as a result of U.S. enforcement efforts. Yet in 

addition to the standard concerns about the validity of survey samples and survey instruments, 

questions about deterrence are especially hard to measure accurately given the ever-evolving 

enforcement environment, as noted above. A further limitation is that the EMIF data is restricted to 

Mexican northern border deportees, and cannot be assumed to apply to migrants from other 

regions/countries because they face different trade-offs and geographic barriers when considering 

a re-entry attempt. 

 

10 See Bailey et al. 2016.

0%

5%

10%

15%

20%

25%

30%

35%

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Recidivists % of total apprehensions
11 Office of Immigration Statistics

OFFICE OF STRATEGY, POLICY, AND PLANS

Figure 5: Estimated Percent of Deportees Deterred from a Reentry Attempt, 1993-2016

 Source: OIS analysis of EMIF Survey; the IDA Corporation.

Figure 5 depicts the EMIF and IDA estimates of deterrence. Unsurprisingly, 90-day 

deterrence is somewhat lower than 7-day deterrence. The data describe relatively limited 

deterrence levels prior to 2007 (20-40 percent in the 7-day survey and 10 – 30 percent in the 90-

day model), and substantial growth in the deterrence rate since that time. As Figure 5 illustrates, 

estimated 7-day deterrence rates have exceeded 75 percent every year since 2012 and estimated 

90-day deterrence rates hovered around 60 percent in 2014 through 2016.

Apprehensions, Deterrence, and Illegal Inflows

Substantial attention focuses on the apprehension rate as a key measure of border security, 

but it bears emphasis that deterrence essentially is just as important as apprehensions in preventing 

illegal inflows. By definition, deportees who are not deterred will reattempt until they are either 

deterred on a subsequent effort or eventually succeed. When deportees are not deterred, even a 

high apprehension rate will only result in a “revolving door” model of enforcement, as was

observed during the 1980s.11 This analysis highlights the importance of CBP’s enforcement efforts 

and post-apprehension analysis of consequence recommendations to increase deterrence—efforts 

that require a whole of government approach. 

 

11 Philip Martin, “Mexican Workers and U.S. Agriculture: The Revolving Door,” International Migration Review 36.4 (2002): 1124-

1142; Gambler 2013.

0

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199319941995199619971998199920002001200220032004200520062007200820092010201120122013201420152016

% Deterred

7 day Deterrence 90 day EMIF weights 90 day IDA model
12 Office of Immigration Statistics

OFFICE OF STRATEGY, POLICY, AND PLANS

Figure 6: Contour Plot of Illegal Inflows as a Function of Apprehension and Deterrence Rates

Source: Office of Immigration Statistics.

Figure 6 illustrates this relationship by graphing the expected number of illegal inflows 

resulting from each crossing attempt as a function of the apprehension rate (on the Y axis) and 

deterrence rate (on the X axis). The light yellow band in the upper-right corner depicts 

apprehension and deterrence rates near their maximums and is the region in which fewer than 10 

percent of intending crossers successfully enter the United States. The dark stripe in the middle of 

the graph is a region in which about half of intending migrants eventually succeed (i.e., after one 

or more attempts). Areas below and to the left of this region describe conditions under which a 

majority of intending migrants eventually succeed. For example, in the area marked as Zone 1, 

corresponding to an apprehension rate of 40 percent and a deterrence rate of 25 percent—the 

approximate conditions in the year 2000—over 90 percent of intending border crossers eventually 

succeed. Indeed, with a deterrence rate of 25 percent, the apprehension rate would have to 

approach 90 percent for a majority of intending immigrants to fail in their attempt, as in Zone 2. 

The situation for the RTM population as of the end of FY2016 was characterized by apprehension 

and deterrence rates of approximately 60 percent (according to the IDA PAR estimate and the EMIF 

survey). As illustrated by Zone 3, about 60 percent of intending RTM migrants eventually succeed 

under these conditions—a number that marks substantial progress from Zone 1, but still leaves 

room for improvement.
13 Office of Immigration Statistics

OFFICE OF STRATEGY, POLICY, AND PLANS

Border Crossing Costs

A third indicator of enforcement outputs is the costs to migrants of crossing the border: in 

particular the share of migrants who hire a smuggler and the average fees that smugglers charge.

12

Smuggling usage and average smuggling fees are useful indicators of the difficulty of crossing the 

border because migrants will only tolerate higher fees to the extent that smugglers provide an 

essential and successful service. Smugglers also compete to attract customers by offering their 

services at the lowest profitable rate, so higher fees indicate rising costs to smugglers. Rising

smuggling fees also reflect an increased risk to smugglers of a criminal conviction; smugglers pass 

this risk along to customers in the form of higher fees.

The dynamic between an increasingly secure border and rising smuggler fees is driven by 

changes in smuggler behavior. For example, according to USBP custodial interviews, many 

smugglers have adapted to enforcement efforts by utilizing sophisticated scouting networks and 

observation posts to guide smuggling activities through increasingly isolated areas to evade 

detection. In addition, USBP routinely interdicted single smugglers leading dozens of migrants 

during the 1980s, but many smugglers now work with groups of just three or four migrants at a 

time. These adaptations mean improved border security translates into higher costs per crosser—

and likely fewer crossing attempts as migrants are priced out of the market—rather than always 

into a higher apprehension or interdiction rate.13

Survey Data on Smuggler Fees

The only available data on smuggling fees come from migrant surveys (including 

interview data collected by USBP), with several surveys asking about whether illegal border 

crossers hire a smuggler and about fees charged by smugglers. These survey data also may be 

subject to response bias if migrants are reluctant to admit to hiring a smuggler, but once again 

such bias should be broadly consistent over time, so changes in survey/interview data should 

reflect changes in the difficulty of crossing the border.

One finding across multiple surveys is that smuggler usage rates have increased steadily 

over the last five decades. Previous research by the Office of Immigration Statistics found that 

smuggler usage rates climbed from 40-50 percent during the 1970s, to 59 percent in the late 

1970s and early 1980s, 70-80 percent in the 1980s to 1990s, 80 to 93 percent in the 1990s to 

2000s, and 95 percent for first-time crossers surveyed in 2006.14 According to USBP interviews, 

relatively few illegal border crossers hired a smuggler prior to 2001, but usage rates climbed to 

80-95 percent among apprehended border crossers in 2015.

Survey results also indicate steady increases in fees paid to migrant smugglers. Custodial 

interviews conducted by USBP have found that smuggling fees are often paid in stages. Initial fees 

required to approach staging locations along the border were often lower than $100 prior to the 

late 2000s, and an additional $1,000-$3,000 in fees were charged upon delivery to the final 

 

12 For a fuller discussion, see Bryan Roberts, Gordon Hanson, Derekh Cornwell, and Scott Borger, “An Analysis of Migrant 

Smuggling Costs along the Southwest Border,” U.S. Department of Homeland Security Office of Immigration Statistics Working 

Paper, November 2010, https://www.dhs.gov/xlibrary/assets/statistics/publications/ois-smuggling-wp.pdf. Also see Christina 

Gathmann, “The Effects of Enforcement on Illegal Markets: Evidence from Migrant Smuggling along the Southwestern Border,” IZA 

Discussion Paper 1004, ftp://ftp.iza.org/dps/dp1004.pdf. 

13 Skerry, Peter, and Stephen J. Rockwell, “The Cost of a Tighter Border: People-Smuggling Networks.” Brookings (1998), 

https://www.brookings.edu/opinions/the-cost-of-a-tighter-border-people-smuggling-networks/

14 Roberts et al., p. 4. Also see Pia Orrenius, “Illegal Immigration and Enforcement along the Southwest Border,” Federal Reserve 

Bank of Dallas, June 2010, https://www.dallasfed.org/assets/documents/research/border/tbe_orrenius.pdf.
14 Office of Immigration Statistics

OFFICE OF STRATEGY, POLICY, AND PLANS

destination. More recently, smuggling fees for Mexicans and Central Americans reportedly have 

been as high as $1,200 for the initial staging payment and up to $8,000 at the final destination. 

Custodial interviews also find evidence of an increase in alternative forms of payment in exchange 

for passage, including migrants being required to participate in smuggling controlled substances 

or other illicit items across the border or to work off debts upon arrival in the United States, as 

well as reports of harsh negotiations concerning payment plans with family members.

Figure 7 plots average smuggling fees in inflation-adjusted dollars according to two 

academic surveys and USBP data. Averaging across the available sources, smuggling fees increased 

by five percent per year during the 1980s, 12 percent per year during the 1990s, and nine percent 

per year during the decade ending in 2015.15

Figure 7: Average Fees Paid to Migrant Smugglers at Southwest Border

Source: U.S. Border Patrol, El Colegio de la Frontera Norte Encuestas sobre Migracion en las Fronteras Norte y Sur de Mexico 

(EMIF), Princeton University Mexican Migration Project (MMP).

 

15 Figure 11 may understate actual smuggling fees since data are mostly collected from unsuccessful crossing attempts, and 

therefore may exclude final payments, and may be biased toward less successful smuggling operations. The figure also understates 

the real increase in border crossing costs because the typical smuggling contract during the 1980s-90s provided for as many entry 

attempts as necessary to succeed; but as entry has become more difficult contracts now cover a limited number of attempts, further 

boosting per-entry costs.

$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

$4,000

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Smuggling fees (real 2014 dollars)

USBP EMIF Det EMIF US EMIF South MMP
15 Office of Immigration Statistics

OFFICE OF STRATEGY, POLICY, AND PLANS

II. Enforcement Outcomes 

Enforcement outcomes describe how many unauthorized immigrants successfully cross the 

border—ultimately the indicator with the greatest impact on the U.S. public.

16

For decades, the U.S. Border Patrol has used apprehensions of unauthorized immigrants as 

its primary proxy indicator of total illegal inflows. More recently, the USBP has begun 

systematically estimating the number of known got aways, as noted above, and IDA’s 

methodology estimates successful illegal entries based on apprehensions and the PAR.

Apprehensions

Apprehension data are available from USBP’s administrative records. As Figure 8 indicates,

southwest border apprehensions increased from 202,000 in 1970 to 1.6 million in 2000, a period 

associated with rising illegal immigration to the United States. More recently, apprehensions fell to 

a 40-year low of 328,000 in 2011, before rebounding to 409,000 in 2016.

Figure 8: Southwest Border Apprehensions by USBP, 1970-2016

 Source: U.S. Border Patrol.

To the extent that the apprehension rate is constant, changes in apprehensions are a direct 

indicator of changes in illegal inflows. Thus, if the apprehension rate were unchanged between 

2000 and 2016, the observed drop in USBP apprehensions would suggest a 75 percent reduction 

in illegal inflows between ports of entry on the southwest land border during this period. If the 

apprehension rate has increased since 2000, as the IER, TIR, and PAR suggest, the actual drop in 

illegal inflows over this time period would be somewhat greater than 75 percent.

 

16 Notably, while apprehensions represent successful enforcement outcomes for USBP, apprehensions are only the beginning of the 

enforcement process for DHS as a whole. At the enterprise level, successful enforcement also depends on the ability of the 

Department along with its interagency partners to adjudicate claims for immigration benefits and, as appropriate, enforce postapprehension removal orders. 

0

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16

Office of Immigration Statistics

OFFICE OF STRATEGY, POLICY, AND PLANS

Known Got Aways

U.S. Border Patrol agents estimate the number of got aways (i.e., subjects who, after 

making an illegal entry, are not turned back or apprehended) based on direct observation, physical 

evidence, and intelligence data, as discussed above. As Figure 9 indicates, estimated got aways 

declined from just over 600,000 in 2006 to a low of just under 100,000 in 2011. Estimated got 

aways increased to about 170,000 in 2013, before falling back to 106,000 in 2016.

Figure 9: USBP Estimated Got Aways, 2006-2016

 Source: U.S. Border Patrol.

Estimated Illegal Entries

In work on behalf of DHS, IDA used the RTM-based partial apprehension rate and CBP’s 

administrative data on apprehensions to estimate total illegal entries. After estimating the PAR, the 

analysis proceeds in three additional steps. First, IDA divides the universe of border crossers into 

two groups. The larger group includes adults without children, who are not asylum seekers and 

not from Cuba; the smaller group consists of minors, family units, Cubans, and individuals who 

request asylum. Aliens in the larger group are subject to a full range of potential enforcement 

consequences, including expedited removal and criminal charges; but aliens in the second group

historically are usually released into the United States with a notice to appear in immigration 

court—often only months or years later. Thus, the larger group of aliens are assumed to be 

potentially “impactable” by USBP enforcement policies, but the smaller group is assumed to be 

“non-impactable” by traditional enforcement policies because even if they are apprehended they 

are still likely to succeed in entering the United States.17

 

17 IDA refers to these groups as “traditional” and “non-traditional,” respectively. IDA includes Cubans in the second group because 

they were routinely allowed to enter the United States during the period under consideration under the wet-foot/dry-foot policy; 

the Obama administration terminated the wet-foot/dry-foot policy in January 2017.

0

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700,000

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
17 Office of Immigration Statistics

OFFICE OF STRATEGY, POLICY, AND PLANS

Second, IDA makes different assumptions about the behavior of each group. IDA assume 

that aliens in the impactable group routinely attempt to evade detection, and that all aliens in this group 

are apprehended at the same rate as the RTM population (i.e., adult Mexican non-asylum seekers) as described 

by the PAR. With respect to the non-impactable population, IDA assumes that aliens make no 

attempt to evade detection, and that all aliens in this group surrender to the first USBP agent they 

encounter. Thus, IDA assumes aliens in the non-impactable group have an apprehension rate of 

100 percent. The distinction between impactable and non-impactable aliens is especially important 

because with the surge of Central American child and family migration in recent years, among 

other factors, the share of non-impactables increased from less than two percent in 2003-2009 to 

over 33 percent in 2016. 

Third, IDA uses the PAR apprehension rate to estimate the odds of successful entry,18 and 

then multiplies the odds of successful entry times the impactable apprehension count to estimate 

the total number of illegal entries. Because of the assumptions made in the second step, IDA only 

includes single adults who do not claim asylum in this equation because family units, children, 

asylum seekers, and Cubans are assumed to be apprehended 100 percent of the time—and 

therefore never to successfully evade detection:

Illegal Entries = Odds of Succesful Entry ∗ Apprehensions∗

*Excludes most minors, family units, Cubans, and asylum seekers.

Like the PAR, the estimate of illegal entries represents an important step forward because it 

is the Department’s first rigorous estimate of total illegal inflows—a number long sought by 

Congress and the public. But the estimate of illegal entries is limited by the same modeling 

assumptions that afflict the PAR, along with the additional assumption that apprehensions can be 

neatly divided into the two groups described above and that they consistently behave as the model 

assumes. DHS is working to relax certain aspects of IDA’s modeling assumptions, to more fully 

describe the impact of each assumption on estimated illegal entries, and thereby to construct a 

range around the estimate that describe its uncertainty. As part of this effort, the Department is 

exploring additional data sources to quantify the differences between the RTM population and 

other illegal border crossers and conducting additional analysis on non-impactable border crossers.

IDA’s estimate of illegal entries from 2000-2016 is depicted in Figure 10. As the figure 

illustrates, IDA estimates that 1.8 million aliens successfully crossed the border in 2000, versus

170,000 in 2016—a 91 percent decline over this period. Unlike border apprehensions, which 

have rebounded somewhat from the low point observed in 2011, estimated illegal entries remain 

well below 200,000 because a large share of recent apprehensions are UACs and asylum seekers 

who are routinely apprehended, and therefore have no impact on the number of successful illegal 

entries, as noted above.

 

18 Mathematically, odds of successful entry = (

1−PAR

PAR ).
18 Office of Immigration Statistics

OFFICE OF STRATEGY, POLICY, AND PLANS

Figure 10: Estimated Successful Illegal Entries between POEs, 2000-2016

 Source: The IDA Corporation.

III. Operational Control

Concurrent with these ongoing efforts to estimate Southwest Border Security, DHS is also 

pursuing alternative modeling and estimation methodologies that will further inform southwest 

border security, while also supporting implementation of Presidential Executive Order 13767. 

Notably, the Executive Order calls for “complete operational control (OPCON) of the southern 

border.” DHS employed OPCON as an enforcement outcome measure from 2004 until 2010. At 

that time, OPCON was a subjective and mostly qualitative measure of the degree to which DHS 

employed the proper mix of personnel, technology and infrastructure to deny or deter access of 

illegal entry at the immediate border. The U.S. Government Accountability Office, among others, 

cited the need for additional, more empirical measures of border security and OPCON was 

discontinued. 

In the re-introduction of operational control pursuant to the Executive Order 13767, 

OPCON will be measured directly. USBP’s ability to ensure the physical security of the immediate 

U.S. Border with Mexico depends upon three major elements: impedance and denial, situational 

awareness, and law enforcement response and resolution. USBP is working to develop multiple 

subordinate metrics to describe each of these major elements.

Among the three elements, situational awareness is a cornerstone of OPCON because it 

combines domain awareness with intelligence data and other information. Over the past several 

years DHS has invested millions of dollars in technology that has facilitated the ability to see and 

detect more at the border. Improvements in situational awareness give DHS an ever-increasing,

real-time ability to understand how much illegal activity agents are encountering at the immediate 

border and their ability to respond. As a result, despite the fact that overall border entries are 

substantially lower today than in any previous fiscal year, agents are currently interdicting slightly 

lower percentages of the total known flow. This observation reflects USBP’s increased domain 

awareness—i.e., that through technological advances, the agency has improved its awareness of 

illegal entry attempts (known got aways)—rather than a drop in enforcement effectiveness.

 -

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19 Office of Immigration Statistics

OFFICE OF STRATEGY, POLICY, AND PLANS

Beyond the operational implications of increased situational awareness, technological 

advances at the border also allow USBP and DHS to pursue modeling efforts based on the 

Department’s more complete information about illegal entry attempts. Increasing situational 

awareness narrows the gap between the known and unknown flow, and puts DHS in a position to 

build ever better observational estimates of border security. The Department will continue to 

refine these observational estimates and to estimate their statistical reliability.

IV. Assessment of Border Security Trends

The six indicators of border security described in this report provide the Department’s best 

available estimates of southwest border enforcement outputs—how difficult is it for aliens to cross 

the border illegally?—and of enforcement outcomes—how many successfully do so? As noted, 

this report is limited in scope to USBP’s ability to prevent illegal entries across the southwest 

border; it does not address broader questions about the Department’s overall ability to control 

illegal immigration, which depends on actions by a broader range of DHS and other enforcement 

agencies, as well as a number of social and economic factors outside the Department’s control.

With respect to border enforcement outputs, available data indicate that the southwest land 

border is more difficult to illegally cross today than ever before. First, survey data, mathematical 

models, and USBP assessments suggest that a growing share of attempting crossers between POEs

are apprehended or interdicted: 55 to 85 percent today (depending on the specific estimate), 

versus 35 to 70 percent a decade ago. Second, administrative and survey data suggest that a much 

higher share of unlawful immigrants are deterred from making a subsequent attempt after being 

repatriated: about 55 to 75 percent today versus 10 to 40 percent a decade or two ago. Third, 

survey data and USBP assessments indicate that almost all illegal border crossers resort to hiring a 

smuggler today, versus just over half 30 years ago. Meanwhile, average smuggler fees have 

increased from a few hundred dollars in the 1980s to almost $4,000 today, accounting for 

inflation. 

With respect to border enforcement outcomes, available data also indicate the lowest 

number of illegal entries at least since 2000, and likely since the early 1970s. First, the U.S. Border 

Patrol made 408,000 southwest border apprehensions in 2016, the fourth-lowest number since

1972, and a 75 percent drop from 1.6 million apprehensions in 2000. The drop in apprehensions 

likely understates the drop in illegal entries given the apparent increase in the apprehension rate. 

Second, USBP’s observation-based estimate of known got aways fell 83 percent between 2006 and 

2016, from 615,000 to 106,000, in spite of improved detection capacity. Third, the IDA 

Corporation estimates that successful illegal entries fell 91 percent between 2000 and 2016 (from 

1.8 million to 170,000), though DHS is still working to validate and refine IDA’s methodology.

DHS will continue to work to develop valid estimates of unobserved border flows between 

POEs. In the near term, DHS will consider an array of indicators as described above, while also 

analyzing more traditional operational data. The Department will continue to strengthen existing 

indicators by refining estimation methodologies and by improving their statistical reliability. In 

the long run, the Department also intends to achieve a level of situational awareness that can not 

only be used as a tool for strategic resourcing decisions and tactical resource deployment 

optimization, but that also provides more reliable estimates of total illegal flows.