INTRODUCTION

The restrictive stance of the US government toward undocumented migration from Latin America, in particular from Mexico and Central America, is a factor that may lead to an increase in the number of permanent or temporary settlements in Mexico. This arrival of demographic contingents of unknown dimensions in some regions of this country as well as the invested time of stay might trigger social conflicts via their interaction with the Mexican population.

The duration of Central American migrants’ stay in Mexican localities may last indefinitely, or else shrink, if restrictions to mobility are reduced. Some of the difficulties that prevent or delay the arrival of migrants to the final destination could be due to a number of reasons, e.g., lack of economic resources to carry on traveling, health deterioration, lack of documents to travel over some territories, the response time for asylum keepers and the prevailing violence in certain regions, among others. Adding to mobility restrictions, there exist other elements that make it easy for migrants to settle in certain localities, that is to say, offer of temporary employment, humanitarian or human rights organizations, and also the agencies in charge of processing the required migration documents.

The places of temporary stay can be grouped in at least two types: the places the migrants choose and occupy as parts of their entire migratory journey, and stagnation places, defined by external agents, such as detention centers, lazarettos² and refugee camps, for instance.

A concern regarding the spaces of prolonged stay is whether these places correspond to localities located mainly at border regions. As for Central Americans toward the US, it is conjectured that the places of stagnation are mostly located in Mexican cities next to the US border, as a consequence of the difficulties to cross.

Another concern is whether these migrant-recipient spaces are prepared to address the social and economic needs of the foreign population in the face of the new context of social relationships established with the residing population, something that comes from the migrants’ lengthier stays. At this point, it is inevitable to bring to mind how the phenomenon of the caravans of migrants has produced various reactions, from humanitarian aid to xenophobic attitudes; the latter are expressed as discrimination and violence from the Mexican population.

The goal of this article is to identify the main localities where Central American migrants spend most of their journey over Mexico traveling toward the US. The article divides into four parts. The first presents the contextual frame which describes the main places of transit and the duration of stay in such places. The second develops the theoretical frame to revise the mobility-immobility and aspiration/ability approaches, the definition of waiting territories and the variable duration in transit as an analysis element. The third part presents the methodological developments, while the fourth, the results from the exploration of localities where migrants spent most of their time.

Firstly, the results identify the cities bordering the US with most of the crossings and the longest stays. Later on, the main localities where migrants spent most of their time in Mexico are defined. Finally, the main localities where migrant detentions took place are described, as well the proportion at which they match the Mexican cities where migrants stayed the longest is presented.

PLACES OF TRANSIT IN MEXICO AND DURATION OF STAY

In a context of increasing complexity to cross into the US, a consequence of the restrictive stance of the American government, the migrants are encouraged to decide to stay in Mexico (^{Giorguli, 2018}; ^{Zijlstra, 2014}) or else, stay longer waiting in a city or locality in Mexico. These longer stays in certain regions of the country impose the responsibility of warning about the positive and negative implications of the migrants’ greater presence at these points.

The relevance of transit spaces is noticed in the magnitude of the contingents that travel across them and the time invested on these locations. In this sense, the present document intends to explore the geography of transit spaces incorporating these two dimensions: the number of travels across them and the duration of stay. This research differentiates from contributions of other studies on the main migration routes to the extent that the time variable (duration) comes into play.

The routes identified by other authors as the most used are the Gulf and Pacific Routes (^{Casillas, 2006}; ^{Martínez, Cobo and Narváez, 2015}). The states comprised in the first route are Tabasco, Veracruz, and Tamaulipas (^{Casillas, 2006}). The second route, which heads for the border with California and Arizona, travels over Mazatlán, Los Mochis and Culiacán, in Sinaloa, and Guaymas, in Sonora (^{Martínez et al., 2015}).

Furthermore, other important places for the migrants’ journey have been identified: in the center of the country, distinguishable is the transit over the states of Mexico, San Luis Potosi, Hidalgo as well as Mexico City; in the center-north, the route that reaches Chihuahua traverses the states of Zacatecas and Durango (^{Martínez et al., 2015}).

As regards other border zones, certain cities have become hubs that concentrate a large part of migration activities. On one side, at the norther border, eleven cities are identified: Tijuana and Mexicali, in Baja California; Nogales and Agua Prieta, in Sonora; Ciudad Juárez and Ojinaga, in Chihuahua; Ciudad Acuña and Piedras Negras, in Coahuila; as well as Nuevo Laredo, Reynosa and Matamoros, in Tamaulipas (^{García, 2008}). One the other, cities at the southern border are Ciudad Hidalgo, Talisman, Ciudad Cuauhtémoc and Frontera Corozal, all of them in the state of Chiapas.³ In like manner, there are also non-border cities or localities with an important presence of migrants in transit.

The border strip in northern Mexico is the final step before crossing, but it is also a space to receive migrants deported by American authorities. Thus, such spaces turn into waiting spaces for new crossing attempts and to earn the economic resources necessary for crossing (^{Jasso and Barboza, 2017}). For its part, Mexico’s southern border region receives permanent and temporary day workers (^{Nájera, 2013}). Moreover, it serves as a border crossing for migrants to reach other regions in Mexico and the United States.

Besides, the spatial distribution of surveillance and migratory control modifies transit routes and crossing points. The states of Chiapas, Oaxaca and Veracruz are the most controlled zones at the southern border (^{Nájera, 2016}), this way, transit migrants will look for strategies to make their presence less evident, choose more isolated routes or wait at certain points until they perceive lighter surveillance in order to continue traveling (^{Redodem, 2017}).

As regards stay time, ^{Jasso and Barboza (2017)} estimate that Central Americans returned by American authorities spend on average between 24 and 29 days in Mexico from entrance to departure, disregarding route, crossing point, transport and country of origin. The estimations were carried out up to 2014, however, the updating of these estimations is of the utmost relevance, given the recent events, i.e., migrant caravans and their temporal settlement in cities such as Tijuana.

Even if there are estimations of the time spent in some border cities in Northern Mexico, it would be desirable to have the average time invested at the border cities and localities in the south and at other non-border localities with important presence of migrants. Nevertheless, up to this moment there is no quantitative source that accounts for the stay times other than for the northern border.

Identifying whether the spaces for prolonged stays correspond to a border city in Mexico or to other still unexplored particular regions remains pending. An instance of this is Mexico City, which might represent a range of employment opportunities, that besides possesses an amalgam of goods and services that attract migrants from different countries. Albeit, the presence of Central Americans in such city has been characterized by having high vulnerability degrees, various forms of invisibility and a constant tension between permanence and a new mobility (^{Faret, 2018}).

SOME PERSPECTIVES OF ANALYSIS ON IMMOBILITY, WAITING TERRITORIES AND DURATION OF STAYS IN SPACES OF TRANSIT

The discussions on mobility are analyzed at three moments of the migration cycle: 1) before migration; 2) during the travel and in the destination; and, 3) at the migratory return (^{Bélanger and Silvey, 2019}). This vision is relevant, for it suggests immobility periods in between mobility; for example, being immobile in a place of transit or at the destination, being unable to return in spite of wanting to, or become stranded at any point of the journey.

The proposal of the aspiration/ability approach is that, firstly, migration starts only with the desire of migrating, and secondly, then this desire is concreted. That is to say, there is a difference between not wanting to migrate and being unable to; this way, in spite of the desire to mobilize, this framework underscores the situations that prevent mobility (^{Carling, 2002}).

For its part, the proposal of the “(im)mobility” approach suggests that social inequality influences mobility. In other words, the migrants’ social condition defines the speed at which they travel and possibility to reach their destination, among other aspects. Likewise, it stresses the relationship between the particular forms of the journey and the factors that constrain mobility (^{Bélanger and Silvey, 2019}).

According to the “im/mobility” approach, for some people it is relatively easy to travel between countries and cross borders safely and with no difficulties. Whereas for others, crossing borders may be undesired, impossible, difficult, perilous and mortal (^{Bélanger and Silvey, 2019}). According to the authors, this proposal allows paying attention to the trajectories, spaces of immobility and waiting times that structure the lives of people, leaving them in a limbo or giving them hope.

The trajectories of mobility are permeated by gender, ethnicity, nationality and citizenship, among other sorts of differences. Not only do these asymmetries exhibit the inequalities between migrants and non-migrants, but also the disparities in mobility control (^{Bélanger and Silvey, 2019}). This control translates as the migrants’ capability to mobilize, at the speed they are able to, the intended destinations and the power to stay in a place if they want to, among others. The immobility approach thus pays attention mainly to restrictions, regulation and limits imposed on migration, day-to-day mobilities and on the crossing of borders at multiple scales (^{Bélanger and Silvey, 2019}).

The aspiration/ability model is based on existing migration theories and offers a coherent frame for analysis to explain non-voluntary immobility (^{Carling, 2002}). The author reviewed the classical migration theories and revised what they explain about immobility. By means of the aspiration/ability frame –by proposing two stages: the aspiration to migrate and the ability to accomplish it–, it is possible to explain several characteristics of contemporary migration and immobility that still remain unexplained by the classical migration theories. This model acknowledges the barriers between the desire to migrate and the ability to accomplish it; conversely, in the classical migration theories, it is taken for granted that desire turns into migration.

The framework above was mainly conceived to explain the involuntary immobility at the origin (before migration) and destination (this is called ‘immobility inside mobility’). That is to say, the incapability to return from or to move toward some other country. Despite not enquiring deeply on mobility in some transit country as such, this approach has enabled noticing the possibility of two sorts of wait: voluntary and non-voluntary.

Both approaches underline the frustration and vulnerability of individuals whose mobility has been restricted. In this sense, Lubkemann (2008; cited in ^{Bélanger and Silvey, 2019}) promotes the observation of people paralyzed because of war, not only the refugees who escape from it; i.e., the ones who suffer the most violence and are most vulnerable are those that did not manage to move.

The interruption of the journey or wait may occur in places freely chosen or at irregular settlements set up for the exclusion of migrant individuals. It is enough to mention some refugee camps and transit camps that are organized and managed as islands under a different jurisdiction, outside the rule of ordinary laws, contention areas established in a legal fiction; this makes the individuals physically in the country be thought of as though they were outside the country (^{Musset and Vidal, 2016}).

In both scenarios, the interruption to the migration journey imposes the migrants the challenge to try to find housing in the places where they are stranded, at least for some time (^{Musset and Vidal, 2016}). It is so that certain territories come from the wait, whose very existence depends on the interruptions and hindrances that usually affect any sort of travel. A case in point is the creation of institutional spaces such as shelters (^{Musset, 2015}).

The term waiting territories refers to “spaces where displaced populations or people in transit remain awaiting, either if these spaces were designed for them or if their wait was unplanned” (^{Musset and Vidal, 2016, p. 6}).

Regardless the delay was an exceptional or an ordinary occurrence, the social experience that takes place during these periods and in the waiting territories should be studied (^{Musset, 2015}). The wait is a social fact with effects on a number of dimensions: psychological, physiological, social, economic, legal, sensorial, cultural, geographical, political. As regards the social, the wait creates moments of union and unexpected social experiences (^{Musset and Vidal, 2016}).

Analyzing these in-between places allows realizing the moments of uncertainty that prevail in a context of transition between a strenuous present, a desired future and an idealized or repressed past (^{Musset, 2015}). Musset mentions that it is necessary to observe the waiting territory not only as a stage, but as an actor with specific social interactions, which shape new forms of solidarity and support strategies among immobilized migrants (^{Musset and Vidal, 2016}).

When referring to Central American migration toward the United States, ^{Faret (2018)} explains that the inception of spaces for permanent and temporal stays (not necessarily waiting territories⁴) responds to the geography of transit routes, the polarization of urban and metropolitan spaces or to the border effect in northern Mexico. According to this author, the presence of Central Americans in urban environments is due to deportees who have no chance to return to their country of origin, and also to the migrants who had their journey to the US interrupted.

Even if the city may offer a number of urban resources such as lodging, labor markets, health care, transport and education, the migrants do not know how to access them (^{Faret, 2018}). In point of fact, the sort of employment the migrants find is short-lived, poorly paid and no skills are required, which in turn limits their access to housing (^{Faret, 2018}). Regarding access to transport, education and health care, migrants in transit are restricted by not knowing the urban environment and the possibilities they have to access these services, in addition to the latent possibility of experiencing episodes of violence, xenophobia and bribery (^{Faret, 2018}).

The final element to consider is that the duration of the stay in certain spaces depends, among other things, on the risks faced along the journey, the migrants’ personal characteristics to deal with the risks, the actors involved in the process (^{Jasso and Barboza, 2017}) and, at once, on the services and integration offered by the spaces where the wait takes place.

The length of the stay duration also follows the resolution periods of asylum seekers and refugees, and the time required for the regularization process of their migratory status. Let us consider the Migrant Protection Protocols (MPP) as an instance; it demanded non-Mexican asylum-seeker migrants to remain in a Mexican border city while their application was reviewed by American courts.

Some inferences on the duration of the stay in the transit spaces analyzed are the following: 1) migratory control has brought about a change in the amount of time the migrants spend in border zones or in transit space (^{Reyes, Johnson and Van Swearingen, 2002}; ^{Collyer, 2006}); 2) those with the least economic resources remain the longest in the country of transit (^{Collyer, 2006}); 3) more prolonged stays increase the migrants’ vulnerability (^{Collyer, 2006}; ^{Basok, Bélanger, Rojas and Candiz 2015}); 4) time in transit may extend indefinitely given the impossibility of returning and being unable to access the regularization of their migratory status (^{Collyer, 2010}).

METHODOLOGY

The overall objective of the article consists in identifying the main localities where Central American migrants returned by Mexican and American authorities⁵ spent most of their transit time in Mexico. The empirical exercise developed in this document is not able to disclose the waiting territories as such; to do so, it would be necessary to identify the geographical spaces utilized to wait, where specific social interactions unfold such as various forms of solidarity and strategies to help one another (^{Musset and Vidal, 2016}). Instead, it only pinpoints the transit localities the migrants report to have spent most of their time in, and which identification refers to the potential existence of waiting territories within them.

The only available information source to quantitatively analyze the displacements of the Central American migrant population in time and space is the Survey on Migration at the Southern Border (Emif Sur) (^{El Colef, 2020}); its reference unit is migrants’ displacements over their transit in Mexico⁶. Three topics are taken from this resource: 1) the migrants’ displacements and the time spent in northern border cities waiting to cross;

the locality where migrants spent most of the time in transit without stating the duration; and, 3) for migrants detained in Mexico, the main localities where the detentions occurred are described.

Emif Sur considers migrants as units in movement, which by displacing over certain places and specific times manage to be grouped and enumerated (^{Corona, 1997}). Therefore, the survey does not count the number of migrants, but displacements, for an individual may repeat the trajectories several times.

Emif Sur considers four migrant flows: those from Guatemala to Mexico; from Mexico and the United States toward Guatemala; individuals returned by Mexican authorities; and individuals returned by American authorities. In order to explore the displacements and duration in transit, object of study of this document, it was decided to use the flows of returnees by American authorities and also those returned by Mexican; in this last flow, a distinction is made between those whose destination was Mexico or the US.

Emif Sur only surveys people older than 15 years born in Guatemala, el Salvador and Honduras. The survey began in 2004, interviewing only people from Guatemala (Emif Guamex). In the second half of 2008, it incorporated migratory flows from El Salvador and Honduras, and then it was called Emif Sur (^{Nájera, 2010}). With a view to including migrants from the three countries above, the period analyzed in this document ranges from 2010 to 2018.

The sample design is a two-stage stratified model with a sampling frame based on temporary and spatial axes. The temporary one accounts for the number of calendar days in the quarter, in which each day divides into one, two or three shifts that depend on the size of the flow and its distribution along the 24 hours of the day. The spatial axis is represented by the crossing points identified in the visits to the Mexican northern and southern borders. This way, the measurements of human displacements are framed within the defined geographic space and the quarter in which the survey was carried out.

The strata are identified by a combination between geographic location and the shift of the day. For each stratum, the primary sampling units (PSU) are the days the survey is carried out, which are called workdays and have a positive probability different from zero if selected. The second stage of the sample is defined by the random selection of respondents.

In order to ascertain the accuracy of estimates, it is necessary to calculate the variance considering the sampling scheme described above. For this purpose, the Survey package of software R was resorted to, as it allows defining the sampling scheme (svydesign), producing tables (svytotal) and crossing variables (svyby). The coefficient of variation (CV), which expresses the relative magnitude of the sampling error, is calculated as follows:

Where, θ⏞  is the estimate in question and S  is the standard error or square root of the sample variance. When CV ranges between 0 and 15, the estimates are considered good quality; between 15 and 30, acceptable; while estimates over 30 are considered poorly reliable.

In order to address the overall goal, three specific objectives are put forward:

Identify the cities that border the US with the largest number of migrant crossings. The number of crossing and the duration of the migrants’ stay at border cities are analyzed. The unit of analysis is border cities, while the variables to analyze are: crossings over the cities and time spent there. The results are based on information from the flow of migrants returned by American migration authorities.

Define the main localities where migrants spend most of their time in transit in Mexico. The transit localities (not necessarily at the border) where migrants declared spending most of their time in on their way to the US are identified. The analysis unit is localities and the variable to analyze is crossings over such locality. Data analysis is carried out at the level of locality and for their processing, INEGI’s locality catalog was consulted (2020). ‘City’ is referred to in some cases to the extent that the keys recorded by Emif Sur refer to some city or locality in Mexico.

The number of crossings or displacements is based on information from migrants returned by American or Mexican authorities; out of the latter, those with the intention to reach the US, who utilized Mexico as a transit space, were selected. Additionally, those who at the time of deportation had crossed into the United States up to a year before were chosen in order to prevent possible memory biases. In this section, the period of analysis (2010-2018) is fractioned as 2010-2012 and 2016-2018 for the purpose of analyzing the changes in number of crossings over the transit localities.

Identify the main localities where migrant detentions took place in Mexico. The main localities where authorities detained the migrants are identified. The unit of analysis is the localities and the variable to analyze is the number of detentions. It is worth noticing that a proportion of the flow of migrants returned by Mexican authorities managed to reach the northern border (or some previous point); these displacements are integrated into objective 2. In this way, it is identified whether the locality where they were detained matches the locality where they declared having spent most of the time of their stay in Mexico.

The results are based on the flow of migrants returned by Mexican authorities, selecting those with the intention to reach the US; if it is not done so, there would be an over-emphasis on the southeastern region, since the individuals whose movements are characterized by the circular and pendular migration of the region, not necessarily from transit, are counted.

The unit of analysis of this article is cities or localities that migrants cross within the upper hierarchy of federated states. In objectives 1 and 2, the variable to analyze is crossings over the cities or localities, as the case may be; whereas in objective 3, the main detention localities in their corresponding states are analyzed.

In the treatment of localities, those which recorded fewer than 45 displacements (unweighed cases) were grouped in ‘others’ without losing the hierarchy of the corresponding state. Records in which the state or locality was not specified were excluded, and so were the observations in which the respondent stated that the total transit days (from the border of Guatemala to the crossing into the US) were fewer than the days reported as a stay in any border city, as its was deemed an inconsistency.

RESULTS

Cities bordering the United States with the largest number of migrant crossings

Border cities in northern Mexico represent the last stop for those who are heading for the US, but they are also a space to receive the returnees who are waiting for the opportunity of new mobility. In relation to them, it is understandable that not all the deportees return immediately to their place of origin, but spend some time lingering in the cities for the purpose of attempting a new crossing or keeping close to their relatives in the Unites States (^{Albicker and Velasco, 2016}).

In graph 1, Reynosa, Tamaulipas, stands out as the main recipient for Central American migrants. It is followed in order of importance by Nuevo Laredo and Matamoros, Tamaulipas; Altar, Sonora; Piedras Negras, Coahuila; Tijuana, Baja California; Nogales, Sonora; Ciudad Juárez, Chihuahua; and finally, Agua Prieta, Sonora. Table 1 presents the displacements over each city, the average days of stay according to country of birth, and the accuracy level of the estimates.

Source: own elaboration based on Survey on Migration at the Southern Border 2010-2018 (^{El Colef, 2020}).

Graph 1. Number of Central American migrants returned by American authorities in the main border cities to cross into the United States according to country of birth, 2000-2018 

Table 1. Number of crossings and average days of stay according to border city to cross into the United States for migrants returned by American authorities from 2000 to 2018  

		Number of crossings				Average days of stay
		El Salvador	Guatemala	Honduras		El Salvador	Guatemala	Honduras
Baja California	Tijuana	2 367	4 442	2 167		7.0	9.3	11.8
Coahuila	Piedras Negras	5 804	5 926	14 341		5.7	7.9	8.8
Chihuahua	Ciudad Juárez	1 302	3 274	1 405		8.1	7.3	7.8
Sonora	Agua Prieta	1 656	3 430	579		6.8	5.5	13.9
Sonora	Altar	2 354	48 156	3 667		7.2	7.5	10.9
Sonora	Nogales	1 156	5 224	2 475		4.9	7.6	8.8
Tamaulipas	Matamoros	3 940	8 391	14 479		6.2	7.5	6.6
Tamaulipas	Nuevo Laredo	6 602	13 356	34 497		6.2	7.9	6.8
Tamaulipas	Reynosa	81 830	110 989	79 539		7.6	9.2	7.2
Accuracy level of estimates: High, CV within the range (0,15)
Moderate, CV within the range [15, 30)
Low, CV 30% onward

Source: own elaboration based on Emif Sur 2010-2018 (^{El Colef, 2010}).

Owing to their low statistical representativity, the cities of Ojinaga and Mexicali are not included in this table. Moreover, it must be considered that these results only represent the displacements of people who at some time were returned, and do no account for those who settled in the destination or are indefinitely stagnant in these cities. Despite this limitation, the results are suggestive in regard to the possible inception of spaces dedicated to the wait within these cities.

By disaggregating the number of crossings according to the returnees’ country of birth, it is identified that the flow through Reynosa, Tamaulipas, is very similar for each origin with a moderate Guatemalan preeminence. Conversely, Hondurans have a greater presence in Nuevo Laredo and Matamoros, Tamaulipas, regarding the other two origins. For their part, the cities of Altar, Nogales and Agua Prieta, Sonora, and Ciudad Juárez, Chihuahua receive more Guatemalans than Salvadorans and Hondurans. The City of Tijuana holds the sixth place in Central Americans’ crossings; mainly Guatemalans enter into this city.

Table 1 presents the number of crossings over the cities, not the number of returned migrant people, since one individual may have traveled to the US and might have crossed a number of times over the same city. Besides, table 1 includes the average number of days living in those cities, stressing that the duration varies according to country of birth and crossing city.

The duration of stays in the city of Reynosa is more prolonged for Guatemalans in comparison with Salvadorans and Hondurans. According to ^{Collyer (2006)}, the migrants with the least economic resources remain the longest in the transit country. In this sense, the stay time in border cities has to be spent on the acquisition of economic resources to afford the coyote and the search for crossing opportunities.

Guatemalans spend 9.3 days on average in Tijuana, Baja California, which is followed by Reynosa, 9.2 days. For their part, Hondurans spend 13.9 days on average in Agua Prieta, Sonora, while in Tijuana, they spend about 11.8 days. Salvadorans spend 8.1 days on average in Ciudad Juarez (table 1). In Altar, Sonora, Guatemalans spend 7.5 days on average, Salvadorans, 7.2, and Hondurans, 10.9 days. Nevertheless, the estimation for the last is moderately accurate, with a CV of 15.1.

The lowest average number of days corresponds to the transit of Salvadorans over the city of Nogales, Sonora (4.9), followed by Piedras Negras, Coahuila (5.7) (table 1). According to the proposition by ^{Bélanger and Silvey (2019)}, the duration of immobility depends on factors such as nationality, gender, ethnicity, among other particularities. Here, we have presented only estimations with an analysis variable: country of birth. However, it would be relevant to identify what features or factors make transit or mobility largely difficult; to do so, it would be convenient to change from a descriptive analysis to some statistical model.

Reynosa stands out both because of the number of crossings and the average time of the stays in days (more than seven). Although Tijuana is not characterized by a sizable proportion of Central American crossings, it distinguishes owing to more prolonged stays, mainly Hondurans (12 days). Nuevo Laredo is the second border space, in order of importance regarding the magnitude of migrants it receives, with an average stay of seven days. The third is Altar with an average stay of 7.73 days for Central American migrants. It is important to underscore that the cities of Reynosa, Nuevo Laredo and Altar as a set comprise 82.26 percent of all the displacements analyzed here.

Tijuana “has become relevant as a waiting place for thousands of people ejected from the United States” (^{Albicker and Velasco, 2016, p. 100}) and the time spent in them seems to be the most extended regarding the cities at the border with the US. In particular, “El Bordo” can be mentioned, an important space that receives migrants deported from the US, who mainly live on the streets, in a context of high vulnerability.

Accordingly, ^{Albicker and Velasco (2016)} distinguish the role of border cities in the deportation process, for they face the challenge of receiving everyday a larger number of deportees with a new profile, tight bonds and certain rooting in the US, adding to the presence of previously deported individuals, returnees with a longer wait, who have tried to enter into the United States for a number of times. While the reflections of the authors are based upon interviews with Mexican deportees, the analysis of the importance of these cities in relation to the reception of Central Americans is still pending.

Main localities where migrants spend most of their transit time

In this section, the main localities in which the migrants reported they spent most of their time over their travel are identified. The results are based on the question: what Mexican locality or city did you remain most of your time in? So that the estimations did not account for all the localities they passed through in their journey toward the US, but only those in which the duration of the stay was longer; which implies losing sight of the dimension of other crossings through various localities, with shorter stays and which contain within their boundaries waiting territories. Plus, the results are not representative of all the displacements of the migrant population with the intention of crossing into the United States, only of those detained by Mexican or American migratory authorities.

Table 2. Main localities declared as those with the longest stays (on the basis of displacements from 2016 to 2018)  

Number in the map
	State	Locality	2010-2012	2016-2018
1	Tamaulipas	Reynosa	34 235	86 194
2	Nuevo León	Monterrey	7 482	23 650
3	Sonora	Altar	13 544	22 108
4	Chiapas	Tapachula	12 125	15 313
5	Chiapas	Palenque	3 033	14 907
6	Tabasco	Villahermosa	12 991	10 834
7	Tamaulipas	Nuevo Laredo	10 157	10 332
8	Veracruz	Acayucan	4 760	9 705
9	Veracruz	Veracruz	6 488	9 539
10	Tabasco	Tenosique	4 020	9 056
11	Chiapas	Tuxtla Gutiérrez	13 006	8 841
12	Chiapas	Arriaga	9 117	8 216
13	Tamaulipas	Ciudad Miguel Alemán	47	7 790
14	Tamaulipas	Matamoros	803	7 149
15	Coahuila	Piedras Negras	5 678	5 689
16	Puebla	Puebla	11 16	5 636
17	Chihuahua	Juárez	696	5 420
18	Veracruz	Coatzacoalcos	7 858	5 203
19	San Luis Potosí	San Luis Potosí	4 388	4 378
20	Ciudad de México	Coyoacán	4 243	2 910
21	Baja California	Mexicali	1 457	2 571
22	Sonora	Heroica Nogales	1 276	2 309
23	Oaxaca	Ixtepec	596	2 265
24	Jalisco	Guadalajara	3 405	2 129
25	Oaxaca	Oaxaca	5 327	2 048
26	Chiapas	Chiapa de Corzo	867	1 939
27	Sonora	Agua Prieta	4 557	1 812
28	Ciudad de México	Benito Juárez	1 342	1 811
29	Chiapas	Huixtla	3 066	1 629
30	Chiapas	Comitán	2 565	1 304
31	Coahuila	Saltillo	3 767	1 110
32	Chiapas	Pijijiapan	1 500	837
33	Chiapas	San Cristóbal de las Casas	1 947	808
34	Baja California	Tijuana	115	674
35	Sinaloa	Mazatlán	2 340	636
36	Chiapas	Tonalá	349	584
37	Coahuila	Torreón	775	349
38	Estado de México	Lechería	69	230
39	Estado de México	Huehuetoca	1 529	83
40	Oaxaca	Salina Cruz	3 052	45
41	Nuevo León	Montemorelos	2 703	32
42	Coahuila	Matamoros	3 517	18
43	Puebla	Zacatlán	2 181	13

Source: own elaboration based on the Survey on Migration at the Southern Border 2010-2012 and 2016-2018 (^{El Colef, 2020}).

Once the localities are considered over the entire Mexican territory, some cities in the southeast stand out as spaces where migrants spend most of their time in Mexico (table 3), namely: Tapachula, Arriaga and Tuxtla Gutiérrez, in Chiapas; Acayucan, Coatzacoalcos, Orizaba, Nogales and Veracruz, in Veracruz; Salina Cruz and Oaxaca, in Oaxaca (table 3). To a lesser extent, the boroughs of Coyoacán and Benito Juárez in Mexico City; the city of San Luis Potosí, in San Luis Potosí; Zacatlán, in Puebla; Guadalajara, Jalisco; and Mazatlán, Sinaloa.

Table 3. Number of crossings by locality according to period of return, 2010-2012 and 2016-2018  

State	Locality	Cruces
		2010-2012	2016-2018
Aguascalientes	All	188	223
Baja California	Mexicali	1 457	2 571
Baja California	Tijuana	115	674
Baja California	Other	--	246
Campeche	All	85	48
Chiapas	Arriaga	9 117	8 216
Chiapas	Chiapa de Corzo	867	1 939
Chiapas	Comitán	2 565	1 304
Chiapas	Escuintla	538	292
Chiapas	Huehuetán	2 839	144
Chiapas	Huixtla	3 066	1 629
Chiapas	Metapa de Domínguez	336	0
Chiapas	Palenque	3 033	14 907
Chiapas	Pijijiapan	1 500	837
Chiapas	San Cristóbal de las Casas	1 947	808
Chiapas	Tapachula	12 125	15 313
Chiapas	Tonalá	349	584
Chiapas	Tuxtla Gutiérrez	13 006	8 841
Chiapas	Other	721	2 479
Chihuahua	Juárez	696	5 420
Chihuahua	Other	1 333	1 105
Ciudad de México	Benito Juárez	1 342	1 811
Ciudad de México	Coyoacán	4 243	2 910
Ciudad de México	Other	2 079	2 676
Coahuila	Matamoros	3 517	18
Coahuila	Piedras Negras	5 678	5 689
Coahuila	Saltillo	3 767	1 110
Coahuila	Torreón	775	349
Coahuila	Other	1 789	86
Durango	All	0	173
Estado de México	Huehuetoca	1 529	83
Estado de México	Lechería	69	230
Estado de México	Other	0	450
Guanajuato	All	2 551	1 389
Guerrero	All	0	48
Hidalgo	All	337	172
Jalisco	Guadalajara	3 405	2 129
Jalisco	Other	0	145
Michoacán	All	0	37
Morelos	All	0	132
Nayarit	All	0	6
Nuevo León	Montemorelos	2 703	32
Nuevo León	Monterrey	7 482	23 650
Nuevo León	Other	1 463	166
Oaxaca	Ciudad Ixtepec	596	2 265
Oaxaca	Juchitán	541	3
Oaxaca	Oaxaca de Juárez	5 327	2 048
Oaxaca	Salina Cruz	3 052	45
Oaxaca	San Pedro Tapanatepec	932	29
Oaxaca	Other	2 045	438
Puebla	Puebla	1 116	5 636
Puebla	Zacatlán	2 181	13
Puebla	Other	566	564
Querétaro	All	336	902
Quintana Roo	All	0	152
San Luis Potosí	San Luis Potosí	4 388	4 378
San Luis Potosí	Other	3 934	735
Sinaloa	Mazatlán	2 340	636
Sinaloa	Other	0	63
Sonora	Agua Prieta	4 557	1 812
Sonora	Altar	13 544	22 108
Sonora	Ciudad de Cananea	1 663	535
Sonora	Hermosillo	4 873	764
Sonora	Heroica Nogales	1 276	2 309
Sonora	Other	785	3 338
Tabasco	Cárdenas	113	3 619
Tabasco	Tenosique	4 020	9 056
Tabasco	Villahermosa	12 991	10 834
Tabasco	Other	512	990
Tamaulipas	Ciudad Miguel Alemán	47	7 790
Tamaulipas	Ciudad Victoria	2 269	47
Tamaulipas	Matamoros	803	7 149
Tamaulipas	Nuevo Laredo	10 157	10 332
Tamaulipas	Reynosa	34 235	86 194
Tamaulipas	Tampico	5 325	2 164
Tamaulipas	Other	0	363
Tlaxcala	All	910	231
Veracruz	Acayucan	4 760	9 705
Veracruz	Coatzacoalcos	7 858	5 203
Veracruz	Nogales	1 472	51
Veracruz	Orizaba	1 834	329
Veracruz	Tierra Blanca	1 136	36
Veracruz	Veracruz	6 488	9 539
Veracruz	Other	1 296	2 370
Yucatán	All	0	44
Zacatecas	All	196	696
High: CV within the range (0, 15)
Moderate: CV within the range (15, 30)
Low: CV 30% onward

Source: own elaboration based on survey on Migration at the Southern Border 2010-2012 and 2016-2018 (^{El Colef, 2020}).

Despite the possibility of experiencing violence and xenophobia and the risks of being deported from urban environments (^{Faret, 2018}), in the enumeration of the main localities of prolonged stay, the dominance of urban centers is distinguishable.

In the state of Chiapas, the cities that distinguish due to the number of crossings from 2016 to 2018 are Tapachula, Palenque and Tuxtla Gutiérrez; in Coahuila, the city of Piedras Negras; in Nuevo León, Monterrey; in Puebla, the city of Puebla; in Sonora, the the city of Heroica Nogales; in Tabasco, Villahermosa; in Tamaulipas, Reynosa, Nuevo Laredo, Ciudad Miguel Alemán and Matamoros; in Veracruz, Acayucan, Veracruz and Coatzacoalcos. All these cities witnessed at least five thousand crossings over the period 2016 - 2018 (table 3).

The boroughs of Mexico City with the longest stays in the period from 2016 to 2018 are Coyoacán and Benito Juárez (table 3). Crossing these boroughs (not necessarily considered part of the migration routes) raises questions regarding the qualities or factors that induce migrants to temporarily take a detour from their road. As ^{Faret (2018)} mentions, not only does the presence of Central American population in the Metropolitan Zone of the Valley of Mexico respond to urban resources (lodging, labor markets, access to information, among others), it is also the result of a blockade in the trajectory toward the north and the impossibility to return.

Even if Mexico City is not the initial destination for Central American migration, it is a stop along the routes heading for the north of the country, since it is the main hub of national roads and railways (^{Faret, 2018}). Well now, only a minority of those who were returned in the past has resorted to Mexico City as a space for a more prolonged stay. At once, we do not rule out the possibility that in the face of an interruption in the initial migration project, an important number of people had opted for settling down definitively in the city.

Mexico City is a place to withdraw after deportation, when the conditions of violence in the origin are the first factor that hinders the return, whereas remaining in Mexico offers an alternative with the hope of a new migration (^{Faret, 2018}). These reflections on Mexico City may be extended to other spaces of interruption over the road, while deepening into the factors that prevent mobility and whether these act in a differenced manner in space are pending tasks.

In the 2010-2012 period, Chiapas and Tamaulipas are among the states with the largest number of crossings (map 1). However, the stays in these contexts may be lived in a differenced manner. While Tamaulipas is associated to the greatest risks of violence and life is lived waiting for an opportunity to cross the border (^{Izcara-Palacios and Andrade-Rubio, 2016}), in the south there is greater risk of deportation from Mexico (^{Martínez et al., 2015}).

Source: own elaboration based on the Survey on Migration at the Southern Border 2010-2012 and 2016-2018 (^{El Colef, 2020}).

Map 1. Number of displacements over the period 2016-2018 in the Mexican federated states and main localities with the longest stays by Central American migrants returned by Mexican and American authorities over the periods 2010-2012 and 2016-2018 

By comparing the periods 2010-2012 and 2016-2018 (map 1), it is noticed that the importance of localities has changed regarding the number of crossings; whereas some cities have become important displacement hubs, others have risen and some more have disappeared. The city of Reynosa has endured as a principal space for crossing; it represents the possibility that waiting territories exist within its boundaries. According to the hierarchy of the states, Tamaulipas becomes more numerically relevant than Chiapas. This gain between states is not an indication that migrants do not stop in southeastern Mexico –particularly in cities in the state of Chiapas–, it means that more prolonged stays mainly took place in localities within Tamaulipas. This is a limitation of the source, since the survey only asks about the place where they remained the longest, disregarding the time spent in other geographic transit points.

In Chiapas, there is a change in the relative participation of crossings by localities: San Cristóbal de las Casas lost relevance; this way, it is no longer noticeable in the period 2016-2018. The participation of Palenque grew in the most recent period (it changed from 3000 to almost 15000 stays, table 3), while that of Tuxtla Gutiérrez decreased. This observation is interesting because, as we have mentioned, the cities seem to be population attraction poles for longer stays. Once again, it has to be noticed that the duration of the stays is not considered; thus, it may be assumed that Palenque has more displacements, though stays in Tuxtla Gutiérrez are longer.

Tapachula remains as an important space of displacements in both analysis periods, and even over the 2016-2018 period, it surpasses Tuxtla Gutiérrez. Tapachula is a traditional crossing point, as it is the first stop in Mexico and the existence of migratory regulation offices and humanitarian agencies make it more attractive for longer stays.

Palenque, Huixtla, Huhuetán, Pijijiapan, Tonalá and Arriaga are smaller localities with fewer services than Tuxtla Gutiérrez, and its presence as localities where migrants spent most of their time may be explained by its closeness to a migration route (all of the cities above, save Palenque, are located along the road between Tapachula and Arriaga).

This is also true for localities in other states such as Tenosique and Cárdenas, in Tabasco; Salina Cruz, Ixtepec and Juchitán, Oaxaca; or Lechería and Huehuetoca, State of Mexico. This result is interesting, while the localities in the south disseminate along the migration routes toward US, not necessarily adjoining the Guatemalan border, those in the north are next to the international borderline.

Some cities that have become relevant because of the number of crossings are Palenque (from 3000 to almost 15000), Monterrey (7000 to 23000), Altar (13000 to 22000), Ciudad Miguel Alemán (from negligible to 7000), and Puebla (1000 to 5000) (table 3). The increase in the number of crossings over these cities may be due to the growth of the migration flow between periods on one side; on the other, to its geographically close position to the migration routes. Though, it is necessary to deepen into the specific characteristics that foster longer stays in the cities. Concurrently, it is necessary to understand why some cities are not attractive for settling down temporarily.

To sum up, the results strengthen the hypothesis that the inception of spaces of temporary use responds to the geography of the transit routes, the polarization of urban and metropolitan spaces in Mexico, as well as the border effect (^{Faret, 2018}); while the mechanisms that operate to transform them over time are not known.

The development of the theoretical framework allowed noticing that the desire to migrate does not always translates into reaching the destination (aspiration / ability; ^{Carling, 2002}), therefore it is necessary to pay attention to the trajectories, waits and restrictions that hinder mobility (^{Bélanger and Silvey, 2019}). Although this article did not address the factors that delay or hinder mobility, it does pay attention indirectly to discontinuous displacements and duration of stays to suggest the existence of spaces devoted to waiting. Interruptions may be voluntary or involuntary (^{Carling, 2002}); this way, it is necessary to delve into detention, a conspicuous case of non-voluntary immobility.

Main Mexican localities where migrants detentions took place

While the localities with the longest stays are mainly associated to transit routes, urban spaces and border localities, it is still pending to consider the wait that occurs in a context of detention. The aspiration / ability frame has enabled observing the involuntary stagnation and how these periods frustrate and render the people whose mobility is restrained vulnerable.

The aim of this section is to verify whether the localities with the longest stays in the previous section match the localities where migrants were detained. Table 4 presents the number of returns according to locality,⁷ the average number of days in detention and the proportion of people returned by Mexican authorities who declared that the locality with the longest stays corresponds to the detention place over the period from 2010 to 2018.

Table 4. Detentions of Central American migrants returned by Mexican authorities, average days in detention and proportion of detentions in localities with the longest stays, 2000-2018  

State	Locality	Detentions	Average days in detention	Same localities as those with the longest stays
Aguascalientes	All	927	13.8	52.7
Baja California	Mexicali	1 701	60.8	38.3
Baja California	Tijuana	1 646	55.1	55.4
Baja California	Other	313	39.5	80.3
Campeche	Escárcega	137	4.8	100.0
Campeche	Other	319	9.2	82.6
Chiapas	Arriaga	19 219	7.0	88.5
Chiapas Chiapas	Chiapa de Corzo	840	5.8	91.0
Chiapas Chiapas	Ciudad Cuauhtémoc	113	0.4	89.1
Chiapas	Ciudad Hidalgo	130	5.2	100.0
Chiapas	Comitán de Domínguez	5 834	4.4	88.8
Chiapas	Escuintla	1 042	5.7	89.8
Chiapas	Huehuetán	4 413	6.8	87.5
Chiapas	Huixtla	5 459	8.2	87.7
Chiapas	Mapastepec	830	6.6	78.6
Chiapas	Metapa de Domínguez	288	5.3	100.0
Chiapas	Palenque	27 236	10.2	82.1
Chiapas	Pijijiapan	5 213	7.3	80.8
Chiapas	San Cristóbal de las Casas	2 862	6.9	85.2
Chiapas	San Gregorio Chamic	320	1.7	45.7
Chiapas	Tapachula	29 295	7.3	93.8
Chiapas	Tonalá	2 062	6.2	74.0
Chiapas	Tuxtla Chico	76	3.6	82.5
Chiapas	Tuxtla Gutiérrez	27 422	7.1	90.5
Chiapas	Other	2 741	8.4	61.7
Chihuahua	Chihuahua	1 248	15.4	89.6
Chihuahua	Other	1 012	12.4	65.2
Ciudad de México	Álvaro Obregón	1 131	15.4	42.9
Ciudad de México	Azcapotzalco	1 832	27.5	69.5
Ciudad de México	Benito Juárez	2 061	20.3	55.9
Ciudad de México	Coyoacán	4 841	11.3	73.1
Ciudad de México	Iztapalapa	3 671	10.6	59.8
Ciudad de México	Other	1 412	13.9	51.5
Coahuila	Piedras Negras	1 860	27.6	51.8
Coahuila	Saltillo	2 248	22.5	57.2
Coahuila	Torreón	814	16.5	49.7
Coahuila	Other	431	19.0	52.3
Colima	All	28	12.8	100.0
Durango	All	298	12.6	73.6
Estado de México	Huehuetoca	3 785	12.8	51.2
Estado de México	Other	1 833	46.3	52.4
Guanajuato	Celaya	6 233	14.5	61.5
Guanajuato	Guanajuato	1 056	21.2	91.7
Guanajuato	Irapuato	1 640	16.2	59.3
Guanajuato	Other	631	10.5	86.7
Guerrero	Acapulco	171	11.3	87.0
Guerrero	Other	120	11.5	74.0
Hidalgo	Pachuca	1 390	14.0	81.1
Hidalgo	Other	300	9.6	90.6
Jalisco	Guadalajara	1 632	24.6	70.7
Jalisco	Other	283	21.7	51.2
Michoacán	Morelia	110	9.2	100.0
Michoacán	Other	36	6.8	100.0
Morelos	Cuernavaca	98	9.3	94.5
Morelos	Other	98	13.4	56.4
Nayarit	All	115	9.9	42.4
Nuevo León	Monterrey	15 053	24.3	61.1
Nuevo León	Other	348	13.2	68.0
Oaxaca	Ciudad Ixtepec	4 593	23.4	69.9
Oaxaca	Juchitán	1 129	6.9	79.4
Oaxaca	Matías Romero	1 185	12.2	55.1
Oaxaca	Oaxaca	12 972	8.2	91.3
Oaxaca	Salina Cruz	2 678	14.1	67.4
Oaxaca	San Pedro Tapanatepec	1 236	4.0	93.0
Oaxaca	Other	1 619	16.8	50.0
Puebla	Acajete	760	10.9	58.1
Puebla	Puebla	6 560	11.4	76.5
Puebla	Tehuacán	1 243	12.1	71.9
Puebla	Other	1 109	30.4	56.0
Querétaro	Querétaro	3 275	11.4	80.6
Querétaro	Other	448	16.6	70.1
Quintana Roo	Cancún	202	49.4	88.7
Quintana Roo	Other	39	--	100.0
San Luis Potosí	Cárdenas	592	10.6	84.3
San Luis Potosí	Matehuala	1 179	16.7	50.3
San Luis Potosí	San Luis Potosí	9 063	15.5	63.6
San Luis Potosí	Other	480	12.5	52.3
Sinaloa	Mazatlán	3 916	12.2	81.5
Sinaloa	Other	261	17.4	57.5
Sonora	Agua Prieta	442	13.0	76.3
Sonora	Hermosillo	3 669	16.6	83.3
Sonora	Other	1 712	40.2	51.0
Tabasco	Cárdenas	5 939	15.5	59.1
Tabasco	Tenosique	17 016	9.0	87.0
Tabasco	Villahermosa	29 188	9.0	81.6
Tabasco	Other	1 971	9.1	67.5
Tamaulipas	Nuevo Laredo	4 714	25.9	51.8
Tamaulipas	Reynosa	17 302	18.4	64.5
Tamaulipas	Tampico	6 833	18.2	47.5
Tamaulipas	Other	3 027	81.5	44.5
Tlaxcala	Apizaco	2 228	17.2	50.5
Tlaxcala	Other	286	8.1	82.2
Veracruz	Acayucan	40 562	11.6	61.4
Veracruz	Agua Dulce	260	11.0	85.9
Veracruz	Coatzacoalcos	17 550	12.8	64.1
Veracruz	Córdoba	909	12.6	85.2
Veracruz	Orizaba	5 477	15.3	42.7
Veracruz	Tierra Blanca	4 232	17.0	40.7
Veracruz	Veracruz	28 708	12.8	56.9
Veracruz	Other	2 729	13.4	40.9
Yucatán	All	120	9.2	100.0
Zacatecas	Zacatecas	1 654	15.2	77.4
Zacatecas	Other	223	22.1	75.7
Accuracy level of the estimates:
High, CV within the range (0, 15)
Moderate, CV within the range (15, 30)
Low, CV 30% onward

Source: own elaboration based on Emif Sur 2010-2018 (^{El Colef, 2020}).

The proportion of respondents who answered that the place where they stayed the longest was the one where they were detained is under 78% at the northern border region (Coahuila, 53.8%; Tamaulipas, 57.1%; Sonora, 73.3%; Baja California, 49%; Chihuahua, 78%), whereas, at the southern border, this proportion is above 80% (Chiapas, 87.5%; Quintana Roo, 90.5%; Tabasco, 80.3%; Oaxaca, 80.1%); the most exceptional case is Veracruz, 58%. Thus, the southern localities with the longest stays largely match those where the respondents were detained by Mexican authorities.

Additionally, the large volume of returns (around 70%) concentrates in the states of Chiapas, Veracruz, Tabasco and Oaxaca (map 2), which concurs with the statistics of administrative records on retentions of undocumented migrants. ^{Martínez et al. (2015)} estimate that these states account for 70.7 percent of all the foreigners who entered the country through the migratory stations of the National Migration Institute (Instituto Nacional de Migración, INM) following the administrative process of presentation and abiding by voluntary repatriation.

Source: own elaboration based on Survey on Migration at the Southern Border 2010-2018 (^{El Colef, 2020}).

Map 2. Number of detentions in the Mexican federated states and main localities of detention of Central American migrants returned by Mexican authorities (2000-2018) 

Table 5. Main localities of detention of Central American migrants returned by Mexican authorities (2000-2018)  

Number in the map	State	Locality	Number of detentions
1	Veracruz	Acayucan	40 562
2	Chiapas	Tapachula	29 295
3	Tabasco	Villahermosa	29 188
4	Veracruz	Veracruz	28 708
5	Chiapas	Tuxtla Gutiérrez	27 422
6	Chiapas	Palenque	27 236
7	Chiapas	Arriaga	19 219
8	Veracruz	Coatzacoalcos	17 550
9	Tamaulipas	Reynosa	17 302
10	Tabasco	Tenosique	17 016
11	Nuevo León	Monterrey	15 053
12	Oaxaca	Oaxaca	12 972
13	San Luis Potosí	San Luis Potosí	9 063
14	Tamaulipas	Tampico	6 833
15	Puebla	Puebla	6 560
16	Guanajuato	Celaya	6 233
17	Tabasco	Cárdenas	5 939
18	Chiapas	Comitán	5 834
19	Veracruz	Orizaba	5 477
20	Chiapas	Huixtla	5 459
21	Chiapas	Pijijiapan	5 213
22	Ciudad de México	Coyoacán	4 841
23	Tamaulipas	Nuevo Laredo	4 714
24	Oaxaca	Ixtepec	4 593
25	Chiapas	Huehuetán	4 413
26	Veracruz	Tierra Blanca	4 232
27	Sinaloa	Mazatlán	3 916
28	Estado de México	Huehuetoca	3 785
29	Ciudad de México	Iztapalapa	3 671
30	Sonora	Hermosillo	3 669
31	Querétaro	Querétaro	3 275
32	Chiapas	San Cristóbal de las Casas	2 862
33	Oaxaca	Salina Cruz	2 678
34	Coahuila	Saltillo	2 248
35	Tlaxcala	Apizaco	2 228
36	Chiapas	Tonalá	2 062
37	Coahuila	Piedras Negras	1 860
38	Baja California	Mexicali	1701
39	Baja California	Tijuana	1 646
40	Guanajuato	Irapuato	1 640
41	Jalisco	Guadalajara	1 632
42	Puebla	Tehuacán	1 243
43	Oaxaca	San Pedro Tapanatepec	1 236
44	Oaxaca	Matías Romero	1 185
45	San Luis Potosí	Matehuala	1 179
46	Oaxaca	Juchitán	1 129
47	Chiapas	Escuintla	1 042
48	Veracruz	Córdoba	909
49	Veracruz	Agua Dulce	260

Source: Survey on Migration at the Southern Border 2010-2018 (^{El Colef, 2020}).

Results for the southern region suggest that localities identified in the previous section are the product of the migratory controls stressed in the zone. In this same line, it is suspected that the increase in prolonged stays in Palenque from 2016 to 2018 comes from the growth of arrests in this city rather than the benefits the migrants may find in it.⁸

As regards state hierarchy, Chiapas holds the first place in returns, followed by Veracruz, then Tabasco, and finally, Tamaulipas at the fourth (table 4). Despite being the city with the most crossings, in Reynosa, Tamaulipas, the number of detentions is lower if it is compared with other cities such as Villahermosa, Tabasco, Acayucan in Veracruz and Tuxtla Gutiérrez, Chiapas (map 2).

Specifically, the city of Acayucan is the main place where detentions take place, even surpassing Tapachula and Tuxtla Gutiérrez. According to map 2, some of the main places where migrant detentions took place are cities, which concurs with the fact that cities pose a higher deportation risk (^{Faret, 2018}).

The main localities as regards detention of migrants are linked to closeness to railways. Instances are Mazatlán and Culiacán, Sinaloa; Hermosillo and Nogales, Sonora; Nuevo Laredo, Tamaulipas; Piedras Negras and Saltillo, Coahuila; Coatzacoalcos, Veracruz; Guadalajara, Jalisco; Ciudad Juárez and Chihuahua, Chihuahua; Monterrey, Nuevo León; San Luis Potosí, San Luis Potosí; and Tenosique, Tabasco. In the southeastern region, detentions converge at nodal points which are not necessarily associated to proximity to railways (^{Martínez et al., 2015}), as it is the case of Tuxtla Gutiérrez, San Cristóbal de las Casas and Comitán de Domínguez, Chiapas.

In Mexico City, the borough with the largest number of detentions is Iztapalapa, followed by Coyoacán. On the basis of INM records for 2011, the former accounted for almost 8 percent of detentions in the central region, maybe from a possible migration route virtually parallel to the railways from Toluca, state of Mexico, to Tepeapulco, Hidalgo (^{Martínez et al., 2015}).

According to the spatial location of the main retention points in the southeastern region produced by ^{Martínez et al. (2015)}, Hueyate, Chiapas, stands out as the main retention point in 2011, after Tapachula. This place has little statistical significance in Emif Sur, owing to the low number of detentions (accounted for in the category “Others”). Additionally, the localities of La Pochota, in the center of the state of Chiapas, and Echegaray, along the road between Tapachula and Arriaga, are mentioned. In the analysis, these localities were grouped in “Others”. It is then assumed that the source resorted to, given the low statistical representativity for some localities (samples with fewer than 45 respondents), only allows identifying the most usual spatial patterns.

The localities with the longest detentions –more than 18 days in detention on average– are Mexicali (60.8 days on average), Tijuana (55.1), Piedras Negras (27.6), Saltillo (22.5), Reynosa (18.4), Tampico (18.2), Benito Juárez (20.3) and Guadalajara (24.6) (table 4). Even if in the northern region fewer detentions take place, the average time spent on detention is usually longer in comparison with other regions of the country. Well now, the time migrants spend on detention not only is an interruption on their way toward the US, but since they are returned to their place of origin, the migration may be frustrated or delayed in temporal and territorial terms.

The results suggest that the intensification of migratory control has reconfigured the duration of transit (^{Reyes, Johnson and Van Swearingen, 2002}; ^{Collyer, 2006}). In addition, a geographic readjustment has taken place in the spaces where migrants spend most of their time.

FINAL THOUGHTS

This article contributes to the identification of the main localities reported as those with the longest stays during the transit of undocumented Central American migrants over Mexico. A longest stay in the analyzed localities does not necessarily mean waiting territories exist within them, for in order to identify them, qualitative studies would be necessary to distinguish the way the migrant people manage to make a home for themselves in the places they become stranded, and how they develop strategies and forms of solidarity that enable them to live and cope with the wait.

In the section dealing with the theoretical framework, the contribution of mobility / immobility and aspiration / ability approaches to understand the interruptions in mobility and the duration of the stay in transit spaces was presented. The aspiration / ability model allowed noticing how the desire to migrate does not always becomes reaching the destination. Therefore, it is necessary to pay attention to the obstacles before they settle down or to the factors that delay such process (mobility / immobility approach). At once, these interruptions and periods of wait may give rise to waiting territories.

This article favors the perspective that migration or undocumented mobility goes beyond a change from origin to destination. Instead, the migration process takes place in stages, in which periods of immobility occur between mobility. This analysis promotes at least two fields of study: the analysis of the periods of wait seen as the result of factors that prevent mobility, and the study of the social experience that might occur in the territories devoted to wait. The article also hints to the study of mechanisms that produce immobility in certain spaces and gives up on the idea of taking for granted that migration becomes reality by only desiring to do it.

The vast majority of migrants returned by Mexican authorities surveyed by Emif Sur stated that the locality where they spent most to their time in transit was the same in which they were detained. This fact suggests that the migrants’ perception may be distorted by the negative experience of detention.

It is difficult to notice the extent at which the respondents are capable of calculating the time spent on transit, detention and, in particular, the time of the stay in certain localities, and if such estimates are not distorted by the positive or negative events during their journey. Another consideration is that people in transit are not necessarily familiar with the names of Mexican cities or localities, which might make them answer with the names of locations that came to their mind at the moment of the interview, or else, the names they managed to memorize more easily.

One disadvantage of Emif Sur is that it does not have accurate estimates of the time spent on the various stops, and so, this analysis was based solely on the city or locality the migrants spent most of the time in. This way, if the longest stay was found in a border city in the north, the time spent in the southern border localities is overlooked. It is concerning that Reynosa is declared as the location with the longest stays, for the city has been identified as one of the most dangerous for migrants.

In the theoretical framework, it was proposed to analyze migration from immobility, stagnation and wait. However, the utilized data source (Emif Sur) measures and characterizes displacements in a population which by definition is moving. This way, instead of offering estimates of the “duration of immobility”, the “time of stay” in the transit localities was measured.

In the same sense, it was not possible to define and observe the waiting territories, though empirical evidence is offered to indirectly suggest the existence of obstacles for mobility noticeable in spaces of long waiting.

Another notable deficiency of this article is that estimates do not include people who settled down in the destination nor asylum seekers, who allegedly experience longer periods of stagnation. People seeking asylum in the United States were excluded from the analysis, since according to the program “Remain in Mexico”, these individuals stay in Mexican border cities. Although the article exhibits some limitations, two main findings can be mentioned:

Neither the localities with the longest stays nor the migration routes are permanent, they change intermittently. Though, noticeable cities with lengthy stays are Reynosa, Tamaulipas, at the norther border, and Tapachula, Chiapas, at the southern one.

The importance of border cities in terms of numbers of crossings and time spent in them is plain to see. While the geographic location of the cities with the longest waits in the north is along the border with the United States; on the other hand, at the border with Guatemala, the location of the places with the longest stays mainly follows the migration routes heading for the United States.