Parallel Cities
Urban Form, Urbanization and Residential Segregation in a Latin
American City
Omar Pereyra
ABSTRACT
This paper examines the end of the period of explosive Latin American urban growth
characterized by industrialization, immigration, and urbanization mainly through informal
mechanisms such as land invasions, public land transfers by the State, and the proliferation of
shantytowns in the peripheries of the city. Using the case of the city of Lima, Perú, the database
of the 1993 Peruvian National Census, conventional segregation indices, and cartographic
methods, this paper confirms, but also improves (not only in terms of detail but also in terms of
formality in the analysis) previous models suggested by scholars who analyzed Latin American
cities. This model finds two parallel and opposite models of urbanization: one area of the city
which developed mainly through formal means that has a form similar to that of the classic
Chicago School model, where the poor population concentrates in areas closer to the city center
while the concentration of the wealthy population increases in more distant areas; and another
area of the city which developed mainly through informal means and where the location of the
population according to socioeconomic status occurs in the opposite way, where the wealthiest
population locates in areas closer to the city center while the concentration of poor population
increases in more distant areas. Additionally, this paper shows evidence to suggest that different
groups according to their place of birth experience different patterns of assimilation to the city
for: while the status of poor and middle socioeconomic level population is not necessarily
associated with the population born in Lima or internal migrants; the foreign born population
seem to have high possibilities of assimilation to the highest socioeconomic status.
Latin American cities as well as other cities of the southern hemisphere are important to
the urban theory both because most of them are among the biggest cities in the world and those
with the highest rate of growth. Though Latin American cities grew and industrialized
simultaneously to the growth of the industrial cities in the north, they did not experience a
growth controlled by the Market or the State. Their growth was sudden and many times chaotic,
surpassing the competence of those central institutions. As a consequence, Latin American cities
exhibit a double parallel structure where part of the city grew through formal means (through
market mechanisms) and the other part of the city grew through informal mechanisms (through
invasion of land and self-production of dwellings by the invaders). This difference is central, not
only for the resulting model of growth and urbanization, but also because it challenges urban
theory which normally theorizes based on the pillars of strong markets and states that canalize
the urbanization process.
In the literature on urban sociology, the concepts of urban form, urbanization and
residential segregation have been of central importance. The aim of this paper is to try to see
how these concepts interrelate in the case of Lima, a typical Latin American city. Consequently,
the goal of this paper is to be an exploration of the Latin American city,[1] revealing evidence that
I consider central for understanding it. Using spatial and cartographic methods applied to the
database from the Peruvian National Census of 1993, this paper analyzes the urban form of Lima
and its process of urbanization referring to the socioeconomic level and by the place of birth of
its population. Similarly, residential segregation is calculated using conventional indices
developed by the specialized literature.
The database from the Peruvian National Census of 1993 is suitable for analyzing the
period of growth of the city through migration and invasions of lands since only a year before,
2
Perú started to apply the structural adjustment reforms; being their most visible consequence in
the foundations of the Latin American cities the process of formalization of the land and housing
markets. Using this database for the spatial analysis of the city will allow me to show, linking
cartographic and quantitative methods, the interrelation of the concepts mentioned at a level of
thoroughness not done before for any Latin American city.
1.
Approaching the Latin American City
I wish to start this approach to the Latin American City by referring to the Chicago
School model not only because of its centrality in the urban debate. The Chicago School model
incorporates and settles highlights that allow us to make connections among the concepts of
urban form, urbanization and residential segregation. This model was developed in the 1920s by
Burgess, Park and their collaborators in a period where the industrial revolution was in full force
and some cities such as Chicago, Detroit, New York, Cleveland, among others, were
experiencing an economic growth of considerable magnitude attracting immigrants in search for
work. In general terms, the Chicago School model represents an ideal type of urban form and of
urbanization of these U.S. industrial cities, which can be characterized by:
… its central business district –on the map “The Loop” (I). Encircling the downtown area
there is normally an area in transition, which is being invaded by business and light
manufacture (II). A third area (III) is inhabited by the workers in industries who have
escaped from the area in deterioration (II) but who desire to live within easy access of their
work. Beyond this zone is the “residential area” (IV) of high class apartment buildings or of
exclusive “restricted” districts of single family dwellings. Still farther, out beyond the city
limits, is the commuter’s zone –suburban areas, or satellite cities- within a thirty-to sixtyminute ride of the central business district. (Burgess 1967: 50)
The connection between this model of urban form and the process of urbanization can be found
in its dynamic character. On the one hand, the city tends to expand from its core towards the
3
periphery creating successive concentric rings, where the inner rings are normally the oldest and
more deteriorated, whereas the most peripheral rings are those that are the newest and more
exclusive. On the other hand, the successive concentric rings are associated with a process of
residential succession and of the assimilation of immigrants: the city inhabitants and their
descendants, as long as they experienced improvements in their socioeconomic level, tended to
change their place of residence to more prestigious areas, moving successively from the core
area of the city to the successive ring.
Though the people of the Chicago School do not talk explicitly about residential
segregation, their model suggests some highlights on this topic. In their model, first generation
immigrants tended to incorporate into the receiving country by agglomerating in ethnic
communities, most of them in the “Zone in Transition” (Zone II). Following the idea of
assimilation, the second generation of immigrants, as long as they incorporated into the
mainstream society and needed less the protection and resources offered by their ethnic
communities, tended to move away from their ethnic communities to the successive rings.
It was in the 70s that Farley et al. (1977) proposed a new model which treated the
phenomenon of residential segregation more directly. This model showed the existence of a
consistent trend in many U.S. cities according to which the poor black population tended to
concentrate in the deteriorated city downtown, and, on the other hand, the migration of the
affluent white population to the suburbs in search of a better quality of life and social
homogeneity. The authors baptized this model with the suggestive name of the “chocolate city
and vanilla suburbs”. This peculiar characteristic of the U.S. cities would be also known by
urban planners as the “doughnut model”.
4
Since the 1960s, residential segregation studies gained recognition because of their
importance for understanding urban marginality and its reproduction. The most important case
was the one of the American black ghetto where, according to Wilson (1987) and Massey and
Denton (1993), residential segregation, more importantly than the reproduction of the class
structure or racism, condemns the black population to remain constrained in spaces of social
decay and isolated from the rest of the city, making their possibilities of social mobility to be
drastically reduced.
Latin American cities have specificities when compared to cities in other parts of the
world. Though many of these Latin American cities are old (with more than 500 years in some
cases) they remained small until the beginnings of the 20th century when they started to
experience a process of intense growth as a consequence of industrialization and the migration of
population from the hinterlands (Kasarda and Crenshaw 1991).
During the processes of industrialization and migration, Latin American cities faced a
group of common challenges. The most representative were the high levels of poverty and
unemployment which took to the proliferation of informal economic activities of precarious
nature. The urbanization process did not run through formal market mechanisms as was the case
in U.S. cities, but mainly though invasions of land and self-help housing (Gilbert 1994; Schutz
1996). Similarly, the consolidation of these neighborhoods was possible mainly because of
neighborhood organizations and family networks (Roberts 1995; Schutz 1996). In the same way,
the provision of public services and of social security for these migrants were beyond the
capacity of the states, and a big share of this responsibility felt into family and neighborhood
networks (Robets 1995; Schutz 1996).
5
Under these conditions the Latin American cities developed a peculiar model of growth
characterized by the presence of two parallel systems. On the one hand, there was one zone of
the city that developed through formal market mechanisms, with the same characteristics and
facilities of cities of the northern hemisphere. On the other hand, there was another zone of the
city (in fact most of the city’s area) that urbanized through mechanisms distinct from the formal
market, meaning by this through the invasion of lands or relocation of the population that
invaded private or public land.
The first model of the Latin American city was developed in the 1980s by Griffin and
Ford. The authors mention that the main characteristics of the Latin American City are the
following: “… a viable CBD [Central Business District], a commercial Spine and an associated
Elite Residential Sector, and a series of concentric zones in which residential quality decreases
outward from the center of the city” (1983: 213), being these last ones the ones inhabited by the
migrant poor population. According to this model, the CBD is characterized by its centrality in
the city given that it maintains its primacy as the space that concentrates the biggest share of the
employment, commercial activities and entertainment. The Spine and the Elite Residential Sector
can be seen as an “extension of the CBD” given that the high and middle class groups live in
these areas and concentrate a big share of the modern infrastructure and leisure activities that are
not in the CBD (Ibid: 215). However, the Elite Residential Sector concentrates a small share of
the population of the city and of its area. Outside the Spine and the Elite Residential Sector,
Latin American cities have a series of concentric rings that develop in an inverse way compared
to the classic Chicago School model: the socioeconomic level of their inhabitants and the quality
of households decreases according to distance from the city downtown or CDB (Ibid: 216); a
phenomenon that responds to the fact that the ring closer to the downtown was the first area of
6
expansion of city which was inhabited by a first wave of migrants (from the 1920s to the 1940s)
and, as a consequence, had a higher level of investment in their dwellings. The following ring
was the second area of expansion by a more recent wave of migration (from the 1950s to the
1960s) and their dwellings were in a process of consolidation. The most distant ring from the
center was the most recent area of expansion inhabited by the most recently arrived migrants
(from the 1970s to the 1980s) being as a consequence a zone of squatter settlements with the
most precarious dwellings.
Studies on residential segregation in Latin America are few; being the most important the
study by Sabatini et al. for Chilenean cities (2001) and then comparing Latin American cities
(Sabatini 2003). Concentrating his analysis in the urban form and the formation of clusters by
socioeconomic level,[2] Sabatini resumes the characteristics of the urban form and the pattern of
residential segregation of Latin American cities in the following way:
-
“Contrary to the ‘doughnut model,’ Latin American cities show a concentration of the
middle and high classes forming a cone with one of its vertices in the city downtown and
that expands to one area of the city. This cone is called the ‘High Rent Zone.’[3]
-
Contrary to the concentration of poverty in the city downtown and its decay as was the
case in U.S. cities, Latin American cities show a tendency to concentrate the poor
population both in the periphery and the city downtown. One characteristic of this fact is
that Latin American cities show a pattern of “great scale residential segregation”,
which means, zones of huge dimensions populated by homogeneous poor population.
-
Contrary to the homogeneity of white high socioeconomic level suburbs in the U.S. city,
Latin American cities show a high level of heterogeneity in their ‘High Rent Zones.’”
(Sabatini 2003: 6)[4]
Up to this point, I have showed a succinct review on the studies on urbanization and
residential segregation in Latin America. The ideas presented above are those that I want to test
7
in this paper using the case of Lima. They will serve as the hypothesis to test in this paper using
the case of Lima as a typical Latin American City.
2.
Database, Concepts and Methods
This study is based on the dataset of the 1993 National Census of Perú.[5] As was
mentioned in the beginning of this paper, the dataset of 1993 is suitable for analyzing the period
of Lima’s urbanization characterized by migration and invasion of lands, which is the period that
caught the attention of those scholars interested in Latin American cities and their process of
urbanization.[6] The National Statistical Institute of Perú (INEI) originally geo-referenced the
information on the city of Lima in three different levels of aggregation: first, the block level, the
smallest unit of analysis; second the area level, which consists of groups from 10 to 100 blocks;
and third the district level, which is a political administrative unit that consists of groups ranging
from 1 area unit to 85 area units. The city of Lima is divided into 49 districts, about 1250 areas,
and more than 54,000 blocks. However, the INEI provides information to external researchers
only at the area level in order to maintain the confidentiality of the informants. As Map 1 shows
the districts of Lima and the way that they have been grouped for this study into what will be
referred in the following as zones: the Northern Cone, the Southern Cone, the Eastern Cone, the
Callao Zone, the Old Lima Zone, and the High Rent Zone.
---------------------------------------------Map 1
Lima: Zones and Districts, 1993
About here
---------------------------------------------The information of the Peruvian National Census 1993 provides information on two
central variables for understanding the Latin American City form and its process of urbanization
8
at the area level: the socioeconomic level of the population and their place of birth. Referring to
the variable socioeconomic level, the Peruvian Census organizes the population into 5
socioeconomic groups: Low, Low Middle, Middle Middle, High Middle, and High. In order to
simplify this information, these groups were transformed into three: Low Socioeconomic Level
(originally called Low), Middle Socioeconomic Level (originally called Low Middle, Middle
Middle and High Middle), and High Socioeconomic Level (originally High). Referring to the
variable place of birth, the Peruvian Census organizes the population in 25 groups: 24 groups
corresponding to the population born on each of the 24 departments of Perú,[7] and 1 group of
foreign born population. In order to facilitate the analysis, 3 groups were created: Born in Lima
(originally the population born in the department of Lima),[8] Migrants (originally the population
born in any of the other 23 departments of Perú), and the Foreign Born (originally the group of
the foreign born population).
For the objectives of this paper, the concept of urban form refers to the morphology of
the city, meaning by this the relative distribution population groups in the areas of the city. In
order to approach this concept, I prepared maps showing the percentage of population by each
socioeconomic level by area in the city of Lima. This information will allow us to detect the
homogeneity or heterogeneity of the population by socioeconomic levels in each of the zones as
a way to test to test the models proposed by Griffin and Ford and by Sabatini.
The concept of urbanization refers to the process of growth of the city. As mentioned
above, the connection between socioeconomic level and place of birth seems to be one of the
main features in the urbanization of the Latin American city, where an increasing percentage of
migrants and of a poor population is supposed to be found in the most peripheral areas of the
city, and most of the population born in Lima are supposed to be found in the Old Lima Zone
9
and the High Rent Zone. Comparing the spatial distribution of these two variables will allow us
to detect and test if there is any spatial correspondence between these two variables in the
urbanization process as suggested by the literature.
The concept of residential or spatial segregation refers to “…the degree to which two or
more groups live separately from one another, in different parts of the urban environment”
(Massey and Denton 1988: 282). A city is considered to be segregated when people of the same
characteristics show a tendency to live close to each other, forming quasi-homogeneous areas or
clusters, living apart from other groups. In order to measure residential segregation, this study
applies two of the conventional indices of segregation developed in the specialized literature
(Massey and Denton 1988; Kaplan and Holloway 1998) as a way to analyze Lima’s model of
segregation: evenness and clustering. In addition, spatial analysis using ArcGIS 9.2 is performed,
which not only will show the level of clustering in Lima, but I will also be able to show which
ones are and where are located the statistically significative clusters by population group.
Most indices of segregation were developed to measure segregation between two groups:
the majority population (whites) and the minority population (African Americans, Asians,
Latinos, or others). However, as indicated above, the concept of segregation is not exclusively
applicable to race or ethnicity but also can be applied to any characteristic that defines the spatial
agglomeration of a group. In this study, socioeconomic level and place of birth are the variables
used to define groups. The main reason for not looking at the variable race as part of our analysis
is that the Peruvian census does not include data on ethnicity or race.
The first index employed in this study is the index of evenness, which is also called
dissimilarity (D). The index of dissimilarity refers to the differential distribution of two social
groups among area units in a city. The index of dissimilarity shows the proportion of the group
10
population that would have to move in order to achieve an even pattern of distribution in a given
area. The formula is as follows:
D xy =
1
* ∑ (x i / X ) − ( y i / Y )
2
where xi and yi are the number of X group and Y group members in each zone and X and Y are
their total in each district. Values are between 0 and 1, where 1 indicates maximum segregation.
The general convention for interpreting this index is that results under 0.30 are considered as
low, results between 0.30 and 0.60 are considered as moderate, and results of above 0.60 are
considered to indicate a high or hyper-segregation (Massey and Denton 1993).
The second index employed is the Moran’s I for measurement of clustering. Clustering or
spatial autocorrelation refers to the extent to which feature values (in this case the proportion of
each group population) are clustered, dispersed, or randomly distributed in space. Moran’s I
index can have values that range from -1 (random distribution), 0 (dispersed distribution), to +1
(clustered distribution). These possible values are graphically represented in Figure 1.
-----------------------------------------------Figure 1
Models of Spatial Autocorrelation [9]
About here
-----------------------------------------------The Moran’s I index of autocorrelation as well as other indices designed for spatial
statistics have two levels of analysis: global and local. Global statistics calculate a single value
that represents the pattern of the whole area or city. The value of the Global Moran’s I tells us if
the area studied has a pattern similar to any of the cases shown in Figure 1. Local statistics
calculate values for each feature of the study area based on similarity with its neighbors. In this
case, a feature with a positive value for the Local Moran’s I tell us that the target feature has
11
equal or similar characteristics to the features around it (either high or low values), forming what
is called a cluster. A feature with a negative Local Moran’s I value tells us that this feature is
surrounded by other features of different values or characteristics (a low value surrounded by
high values, or vice versa).
The value of the Global Moran’s I index compares the value of each feature in the study
area and compares them with the value of the mean feature. The Global Moran’s I index can be
calculated using the following formula:
n∑
I=
(
∑
i
)(
w ij x i − x x
− x
j
)
j
∑∑
i
w ij
j
∑ (x
i
− x
)
2
i
where in the numerator of the value of each feature (xi) is subtracted from the mean value of all
features, then multiplied by the same difference of its neighbor (xj), then multiplied by the weight
(wij) of that pair, and added to the sum for all features. All pairs of neighbors are then summed
up. The denominator is the variance from the mean value for all the features, which then is
multiplied by the sum of the weights.[10]
In the case of the Local Moran’s I, the value of a target feature and of its neighbors is
compared to the value of the mean feature. It can be calculated using the following formula:
I =
(x
− x
i
s
2
)∗
∑ w (x
ij
j
− x
)
j
where the notation is the same as in the Global Moran’s I and s2 represents the variance.
In the case of the Global and Local Moran’s I, it is necessary to measure if the results are
statistically significant at a given confidence level. The Z-test measures if the pattern described
(global) or the similarity between values (local) is or is not due to chance. Clusters that pass the
12
hypothesis test are considered to be statistically significant clusters while those that do not are
considered not significant and consequently are not considered as clusters.
In this study, looking at residential segregation is important for three main reasons. First,
the study of residential segregation offers highlights to approach inter-group relations: the
dissimilarity index would allow us not only to measure segregation, but also to see which groups
are more or less segregated when compared with others. Second, the local and global Moran’s I
indices allow us to test Sabatini’s hypothesis of the homogeneity of the peripheral zones and the
heterogeneity of the Old Lima Zone and the High Rent Zone. If these hypotheses are correct, the
peripheral zones are expected not only to have high percentages of poor population, but also to
have clusters of them; whereas the Old Lima Zone and the High Rent Zone are expected to have
not only the concentrations of poor, middle and high socioeconomic status, but also clusters of
each status should be found in rare occasions. Third, looking for a correlation between clusters of
population by place of birth and by socioeconomic level would allow me to test the commonly
assumed hypothesis of the association between these two variables.
3.
Findings
In order to show the findings of this study, I will organize the information in the three
main topics that are mentioned in the previous section. The first part relates to the form of the
city of Lima based mainly on descriptive statistics and maps by socioeconomic level. The second
part deals with the process of urbanization which looks at the interaction between socioeconomic
level and place of birth using maps and statistical analysis. Finally, the third part examines
residential segregation of groups. For this last part, indices of segregation and spatial analysis are
used.
13
a.
Urban form
My description of Lima’s urban form highlights the fact that each of the zones described
above has well defined characteristics with their underlying processes. First, the Old Lima and
Callao zones are the oldest parts of the city[11] with a similar distribution of population by
socioeconomic groups. Second, the High Rent Zone which has the highest concentration of the
middle and high socioeconomic level population, has urbanized mainly through formal market
mechanisms. Third, the three Cones, whose main characteristics are that they developed mainly
through invasions of land, land cessions by the State or other informal mechanisms; has the
highest concentration of the poor population. I will start the description of Lima’s urban form
using these zones as a point of reference.
I should say that the Old Lima Zone is not necessarily a poor region as Sabatini suggests
for the Latin American city. On the contrary, as Chart 1 shows, though the low socioeconomic
population is important in the Old Lima Zone (42.94%), it is the middle socioeconomic level
population that is the most relevant (55.04%). However, this does not mean that the distribution
of the population in the Old Lima Zone is uneven. On the contrary, there is a well defined pattern
of the distribution of socioeconomic groups that is related with distance to the city center. From
the district of Lima, where the population is mostly of middle socioeconomic level (58.55%), the
population of low socioeconomic level increases as distance increases in the way to the east, to
the north, and to the west where poverty reaches to more than 80% in some areas. The contrary
happens to the south of the district of Lima where low socioeconomic level population is less
relevant as the distance to the city center increases, while it is the middle socioeconomic level
population that becomes more relevant as the distance to the city center increases. This pattern of
population distribution fits well with the parallel model of growth described before (formal to the
south of the city and informal to the other directions), which is related with socioeconomic
14
levels. Simultaneously, the poor population started to inhabit to the other directions of the city
and expanding to more distant areas.[12]
------------------------------------------------Chart 1
Lima: Population by Socioeconomic Level and Migration Condition
Zone and District Level, 1993
About here
-------------------------------------------------As was in the case of the Old Lima Zone, the Callao Zone is not necessarily poor. Low
and middle socioeconomic level population are similarly important in this zone (49.35% and
49.12%, respectively as shown in Chart 1). Similarly, the pattern of the distribution of
socioeconomic groups is similar to that of the Old Lima Zone: the concentration of low
socioeconomic level population increases to the north and east of this zone through informal
mechanisms of urbanization. The opposite process occurs for the percentage of middle
socioeconomic level population which increases in the way to the south, illustrating the same
successive process of elite’s departure to the High Rent Zone. Similarly to what happened in the
Old Lima Zone, the importance of the high socioeconomic level population is irrelevant,
signaling again the process of elite’s departure to the far south areas of the city.
Going to the southern part of the city first, the High Rent Zone is the section of the city
which has the highest percentage of the high socioeconomic level population. However, this does
not mean that it is an elite zone as Griffin and Ford mention. In fact, it is the zone of the city that
has more concentration of all socioeconomic groups; where low socioeconomic level population
rises to 22.34%, middle socioeconomic level population to 62.37%, and high socioeconomic
level population to 15.20%. However, this does not necessarily mean that the High Rent Zone is
a heterogeneous zone as Sabatini suggests: poor population decreases in the way to the south; the
15
middle socioeconomic level population is concentrated in its central area; and the high
socioeconomic level population tends to increase to the southeast of the city. This distribution
provides the evidence to claim that in this zone of the city, which developed through formal
mechanisms, the distribution of socioeconomic groups follows a similar pattern to that proposed
by the Chicago School decades ago: poverty decreases according to the distance to the decaying
city center; simultaneously, as the elites seem to move successively away from the city center,
they are followed by the middle socioeconomic group in a process of residential succession.
Finally, the Cones, which main characteristic is that they are mostly populated by low
socioeconomic level population: 62.78% in the Eastern Cone, 53.78% in the Northern Cone, and
65.57% in the Southern Cone. However, the middle socioeconomic level population is also
relevant in these zones: 36.37%, 54.50%, and 34.22%, respectively. The evidence in which I
count for this paper allows me to make one observations: first, the Cones are not homogeneously
poor as Sabatini suggested, but there is a considerable level of heterogeneity inside them and a
well-defined trend of distribution of socioeconomic groups according to the distance as Griffin
and Ford suggested.
Contrary to the trend that I presented for the High Rent Zone, the three Cones show the
presence of low socioeconomic level population that seems to increase according to the distance
to the city center, while the presence of the middle socioeconomic level population seems to be
more important in areas closer to the city downtown. Again, this evidence provides support to
Griffin’s and Ford’s model of an inverse process of urban growth for the marginal population of
Latin American cities to that of the Chicago School model.
16
b.
Urbanization
Coinciding with Griffin and Ford’s model of peripheral growth in Latin American cities,
most of the literature on Lima’s growth highlights the fact that since the 1940s the city expanded
to its peripheries basically because of the arrival of migrants that settled successively in the
outskirts of the city (Matos Mar 1977; Driant 1991). This literature has also highlighted the fact
that each new wave of coming immigrants can commonly be considered as living on extreme
poverty. However, their condition tended to improve in the following years based on a tenacious
will and hard job (Degregori 1986). Following this literature, we should expect that the
peripheral areas of the city were inhabited mostly by poor population which should also be
migrants.
As I mentioned above, there is evidence to support the idea that migration and poverty
are characteristics associated with the areas of recent urban expansion. As Chart 1 shows,
peripheral districts of the city show a high concentration of both poor population and migrants as
is the case of Puente Piedra in the north (with 63.49% migrants and 80.52% low socioeconomic
level population), the district of Villa El Salvador in the south (with 56.84% migrants and
69.86% low socioeconomic level population), and the areas to the north of the Callao Zone as the
district of Callao (with 72.09% migrants and 53.73% low socioeconomic level population).
However, this association seems to be vague and become spurious because of the process of
improving living conditions of older migrants.
As Chart 2 shows, for whole areas of Lima, the value of the coefficient of association
between areas of low socioeconomic level population and areas of migrant population is minimal
(r2 = 0.102) Similarly, being born in Lima or being migrant is imperceptibly associated with
being of middle or of high socioeconomic level (r2 = 0.076 and 0.020 respectively). This
17
evidence suggests that in the last decades, migrants have found considerable opportunities for
social mobility and ways to achieve it.
--------------------------------------------Chart 2
Lima: Socioeconomic Level by Place of Origin, 1993
(Simple Linear Regression R-square values)
About here
--------------------------------------------Chart 1 also provides evidence to support the idea of the improving living conditions of
migrants. Some districts with a high percentage of migrants show a low percentage of low
socioeconomic level population as is the case of the districts of Bellavista and La Perla in the
Callao Zone, as well as the district of San Miguel in the High Rent Zone. Similarly, there seems
to be considerable cases of correspondence between a high percentage of population born in
Lima and a high percentage of low socioeconomic level population as in the districts of Ancón,
Carabayllo and Comas in the Northern Cone, the districts of Ate, Lurigancho and Chaclacayo in
the Eastern Cone, the district of Chorrillos in the High Rent Zone, and the districts of Lurín,
Pachacamac, Villa María del Triunfo and San Juan de Miraflores in the Southern Cone.
These results make me suggest two emerging trends in the process of Lima’s
urbanization. The first process is that some of the first areas that received migrants (those closer
to the city center) are now areas considerably mixed and in some cases mostly populated by their
sons and grandsons (those who are now “Limenians”), a process more notorious in the oldest
areas of invasions of Lima: in the districts of Rimac and El Agustino in Old Lima, in Callao,
Bellavista, and La Perla in the Callao Zone, in San Juan de Lurigancho in the Eastern Cone, and
in San Martín de Porres in the Northern Cone. We should also remember that, as I mentioned
before, the age of these areas and the time that their inhabitants lived there explains both the
18
higher level of consolidation of these neighborhoods as well as the better living conditions of
their inhabitants. The second change is that though poor population still tends to occupy the
peripheries of the city, this population is not massively constituted by migrants anymore, but
consists also of population born in Lima. Consequently, the outskirts of Lima do not grow only
because of the constant arrival of migrants, but also because a considerable group of Limenians
are looking for a place to settle since they cannot participate in the formal market. The main
change is that poverty in Lima is not associated with migration anymore. Nowadays Lima
produces its own poor population.[13]
However, Chart 2 shows a very different situation in the case of the foreign population:
areas of the city with higher concentration of the foreign born population seem to be moderately
and negatively associated with the percentage of the low socioeconomic level population (r2 = 0.284), not associated with the presence of the middle socioeconomic level (r2 = 0.073), and
strongly positively associated with the presence of the high socioeconomic level population (r2 =
0.690).[14] The foreign born population seems to find better living conditions and opportunities of
social mobility than migrants and Limenians: the higher concentration of foreign born population
occurs in the areas in the districts with a higher presence of high socioeconomic population (San
Isidro, Miraflores, La Molina, and San Borja).
c.
Residential Segregation
As my findings on the urban form and process of urbanization of the city of Lima
suggest, residential segregation does occur, both by socioeconomic level and place of birth
among groups. However, these two types of residential segregation are not associated. This last
section refers to the level of residential segregation in Lima, its spatial dimension and what does
this says about the relationships among groups.
19
Considering first the socioeconomic variable, the global Moran’s I index shows that all
groups are clustered, as seen in Chart 3. However, they are the high and low socioeconomic level
groups those with the higher level of segregation (I = of 0.16 and 0.15 respectively) whereas the
middle socioeconomic population seems to have a lower level of clustering (I = 0.13). In the case
of segregation by place of birth, groups are also clustered, being the groups of migrants and of
being born in Lima equally clustered (I = 0.18), while the foreign population is less segregated (I
= 0.12).
--------------------------------------------------Chart 3
Lima: Clustering Index by Socioeconomic Level and by Place of Origin, 1993
About here
---------------------------------------------------Residential segregation according to socioeconomic group has a spatial dynamic that is
consistent with my findings described before. As a way to illustrate this, Map 1 shows the
distribution of statistically significant clusters of groups by socioeconomic level.[15] As we can
see, the clusters of low socioeconomic level population are located mainly in the extreme
peripheries of the Cones, precisely the areas of growth of Lima by informal mechanisms. In the
same way, the clusters of middle socioeconomic level are located mainly towards the south of
the Old Lima Zone and the Callao Zone again according to the tendency of expansion of the
High Rent Zone which is also the one that has the most of the clusters of this group. And also in
some of the oldest areas of the Cones as in the districts of San Martín de Porres, Los Olivos,
Independencia in the Northern Cone, Santa Anita in the Eastern Cone, and San Juan de
Miraflores in the Eastern Cone, again show the signal of the process of these old poor areas to
transform into consistently inhabited by the middle socioeconomic level. Similarly, the clusters
20
of high socioeconomic level population are located in the most distant areas of expansion of the
High Rent Zone (District of La Molina). Finally, and again according to this pattern, the
heterogeneous zones, which are located mainly in some of the oldest parts of the Cones (those
closer to the city center and the Callao), are apparently in a process of transition towards
becoming consistently occupied by the middle socioeconomic level population. The same
happens in some of the oldest parts of the High Rent Zone, that are apparently in a process of
transition to decline because of the constant departure of high and middle socioeconomic groups
to the southeast of the city.
-------------------------------------------------------Map 2
Lima: Clusters by Socioeconomic Level, 1993
About here
--------------------------------------------------------It is also important to notice that the distribution of these clusters reveals suggestive
spatial patterns of distance and proximity among groups to be highlighted. The first characteristic
is that there is a considerable tendency of the agglomerations of one specific socioeconomic
group to locate closer to the other agglomerations of the same group. As a result, these
agglomerations form huge clusters (one big agglomeration in the case of the middle
socioeconomic group, and three agglomerations in the case of the poor socioeconomic group to
the north, east and south). However, in the case of the high socioeconomic level population, they
form two small clusters located in one extreme of the High Rent Zone. The second characteristic
is that these well defined socioeconomic clusters tend not to be next to each other. On the
contrary, these huge clusters are normally surrounded by heterogeneous zones which act as a
buffer in between the two clusters and that, according to our description of the urban form of
Lima, are constituted as a degrade in the transition from the prevalence of one group to the
21
prevalence of the other: from a consistently middle socioeconomic level in the central part of the
city to consistently high socioeconomic level areas in the High Rent Zone, and gradually and
consistently to low socioeconomic level towards the other peripheries.
This apparent process of urban succession is noticeable when we look at the spatial
relations between groups. On this matter, the dissimilarity index has the virtue of quantifying and
providing a hint to understand the relationships between two groups. Chart 4 shows the levels of
segregation between our three socioeconomic groups measuring evenness. The dissimilarity
indices between groups show that the segregation augments when we compare groups more
distant in status: segregation between low and middle socioeconomic level population (D =
42.86) is considerably lower than segregation between low and high socioeconomic level
population (D = 85.28) while the segregation between middle and high socioeconomic level
population (D = 60.47) is higher than between low and middle socioeconomic level.
---------------------------------------Chart 4
Lima: Dissimilarity Index by Socioeconomic Groups and by Place of Origin, 1993
About here
-----------------------------------------This trend for residential segregation by socioeconomic group is not the same for
residential segregation by place of birth. The location of the clusters by place of birth shown in
Map 2 follows the tendencies that I described in the previous section:[16] clusters of migrants
(brown areas) are located in some of the old areas of Limas as those in the Callao Zone and some
areas of expansion as in the north of the Callao Zone, the Northern Cone, and some smaller ones
in the Southern Cone. Clusters of population born in Lima (purple areas) are located in some of
the old areas of Old Lima, in the oldest areas of invasions in the three Cones, in some of the new
22
areas of expansion of the city in the extreme east and south, and more evidently in the High Rent
Zone. Finally, the heterogeneous areas (yellow areas) are located in some of the oldest areas of
expansion of the High Rent Zone and of the three Cones suggesting again the tendency towards
inter-group fusion in these parts of the city.
-------------------------------------------------------Map 3
Lima: Clusters by Place of Birth, 1993
About here
--------------------------------------------------------Finally, to measure residential spatial interactions between groups by place of birth, the D
index in Chart 4 provides suggestive evidence: Limenians and migrants are lowly segregated (D
= 18.89) while the foreign born population seems to be highly segregated both to Limenians and
migrants (D = 60.08 and 63.36 respectively). In this case, it is the foreign born population that is
extremely segregated while Limenians and migrants seem to have a strong tendency towards
residential proximity.
4.
Discussion
The data that I analyzed for this paper allows me to say that, in general terms, the models
suggested by Griffin and Ford and by Sabatini area satisfactory. However, I found some
evidence in the case of Lima that allows me to suggest more refined statements about its urban
form:
-
Lima and Callao zones are heterogeneous, but I found a well-defined tendency where the
presence of the middle status population increases towards the High Rent Zone, while the
presence of a low status population increases towards the other directions of the city.
23
-
The High Rent Zone of the city is not an elite zone as Griffin and Ford claimed, but is in
fact the most heterogeneous zone as Sabatini argued. However, there are also welldefined trends where the presence of poverty is more important in the areas closer to the
city center; where the presence of a middle status population is consistent in its central
area; and where the presence of a high status population increases towards its most
distant areas.
-
The Cones are prevalently poor as Sabatini claims, but there are well-defined gradations
as Griffin and Ford argued. In the Cones poverty increases towards the peripheries to the
point that huge consistent clusters of a low status population are found in there.
Regarding the process of urbanization of Lima, I should start mentioning the paradoxical
importance of the Chicago School model which seems to fit well for the areas of the city that
developed through formal market mechanisms where areas distant to the city center are more
desirable and consequently associated with a higher presence of a higher status population. But
that works inversely for the other parts of the city that developed outside the rules of the market
(basically most of the Cones), where areas distant to the city center are less desirable and are
consistently more populated by the most disadvantaged population.
I also found some evidence of an apparent process of urban succession, where areas in
the Cones that are closer to the city center are transforming from originally being areas
prevalently poor to areas consistently inhabited by a middle status population; further, in the
High Rent Zone, the elites leaded the process of urban expansion towards the extreme southeast
of the city, followed in their way by the middle status population that occupy areas previously
occupied by them, and finally an increasing presence of a poor population in the areas closer to
the city downtown.
24
Similarly important, I found that despite the emphasis that the literature on Latin
American urbanization put on migrants as the main actors in this process, some evidence suggest
that by 1993 this was no longer true. First, the furthest areas of the city are not consistently
inhabited by migrants, but both by migrants and Limenians. Second, areas consistently poor are
not the areas consistently populated by migrants anymore, but are areas that are populated both
by migrants and by Limenians; this means that Lima is generating its own poor population and
that Limenians are now also important actors in the process of the expansion of poor areas in the
peripheries of the city. Third, I should highlight that some migrants have been able to achieve a
middle status position: by 1993 this status position that is equally associated with being migrant
and being Limenian. Fourth, this analysis allowed me to notice a consistent association between
areas populated by a high status population and a foreign born population. This evidence
suggests that the foreign born population is able to assimilate into the city life in a successful
way, even with better outcomes than Limenians.
Finally, regarding residential segregation I found that Lima presents a model of
segregation of big scale as Sabatini suggested, meaning by this that groups tend to form
agglomerations of huge dimensions consistently separated from each other: the poor population
is concentrated to the extreme peripheries of the city, the middle status population is located in
areas close to the city center but moving further away from it, and, finally, the elites are
agglomerated to the extreme southeast of the city. In terms of the level of segregation I found
that the high and low status populations are the most segregated groups while the middle status
population is the least segregated of the three.
Up to this point, I have shown a picture of the city of Lima by 1993. Recent studies on
Latin American urbanization start to highlight the fact that some Latin American cities are
25
turning to a new model of urbanization and residential segregation where groups tend to locate
close to each other. That new model is enabled by new technological devices that facilitate a
residential segregation of small scale and near distances, being the epitome of this model the
proliferation of elite gated communities not in exclusive areas of the city but also, and more
importantly, in poor areas (Caldeira 2000, Sabatini 2003).[17] This paper could serve as a baseline
to test if Lima turned to or to what degree it turned to this new model and if this new model is
generalizable to other Latin American cities.
26
BIBLIOGRAPHY
Burgess, E. (1967 [1925]) The growth of the city: an introduction to a research project. In R.
Park and E. Burgess. The city: suggestions for investigation of human behavior in the
urban environment, The University of Chicago Press, Chicago.
Caldeira, T. (2000) City of walls: crime, segregation and citizenship in Sao Paolo, The
University of California Press, Berkeley - Los Angeles – London.
Degregori, C. I. (1986) Del mito de Inkarri al mito del progreso. Socialismo y Participación 36,
48-56.
Driant, J. C. (1991) Las barriadas de Lima: historia e interpretación. IFEA – DESCO, Lima.
Farley,R., H. Schuman, S. Bianchi, D. Colasanto, and S. Hatchett (1977) Chocolate city, vanilla
suburbs: will the trend toward racially separate communities continue? Social Science
Research 7.4, 319-344.
Gilbert, A. (1994) The Latin American city. Latin American Bureau, London.
Griffin, E. and L. Ford (1983) Cities of Latin America. In S. Brunn and J. Williams (eds.). Cities
of the world: world regional urban development, Harper & Row, New York.
Kaplan, D. and S. Holloway (1998) Segregation in cities. American Association of Geographers,
Washington D.C.
Kasarda, J. and E. Crenshaw (1991) Third world urbanization: dimensions, theories and
determinants. Annual Review of Sociology 17, 467-501.
Longley, P. A., M.F. Goodchild, D.J. Maguire and D. W. Rhind (2005) Geographic information
systems and science. 2nd edition, Wiley, Sussex.
Massey, D. and N. Denton (1988) The dimensions of residential segregation. Social Forces,
67.2, 281-315.
Massey, D. and N. Denton (1993) American apartheid: segregation and the making of the
underclass. Harvard University Press, Cambridge.
Matos Mar, J. (1977 [1966]) Las barriadas de Lima, 1957. 2nd edition. IEP, Lima.
Ortiz de Zevallos, A. (1992) Urbanismo para sobrevivir en Lima. Friedrich Ebert – Apoyo,
Lima.
Portes, A. and J. Walton (1976) Urban Latin America: the political condition from above and
below. The University of Texas Press, Austin.
Portes, A., B. R. Roberts and A. Grimson (2005) Ciudades latinoamericanas: un análisis
comparativo en el umbral del Nuevo siglo. Prometeo, Buenos Aires.
Roberts, B. (1995) The making of citizens: cities of peasants revisited. Arnold, New York London.
27
Sabatini, F., G. Cáceres and J. Cerda (2001) Segregación residencial en las principales ciudades
chilenas: tendencias de las tres últimas décadas y posibles cursos de acción. Eure 27.82,
21-42.
Sabatini, F. (2003) La segregación social del espacio en las ciudades de América Latina,
Documentos del Instituto de Estudios Urbanos y Territoriales, 35, Pontificia Universidad
Católica de Chile, Santiago.
Schutz, E. (1996) Ciudades en América Latina: desarrollo barrial y vivienda. Sur, Santiago.
Wilson, W. J. (1987) The truly disadvantaged: the inner city, the underclass, and public policy.
The University of Chicago Press, Chicago – London.
28
NOTES
[1]
What I mean by the “Latin American City” is in fact the great Latin American cities,
mostly the case of the capitals of Latin American countries which normally are the biggest
city of each country because of what other scholars have called urban primacy in the third
world (Kasarda and Crenshaw 1991).
[2]
Given the long process of racial mixing (mestizaje) in most Latin American countries it is
difficult to classify the population by race, especially in their capitals. As a consequence
many of the censuses in South America do not incorporate the variable race as part of their
questionnaire.
[3]
In this case, Sabatini refers, generally speaking, to what Griffin and Ford called the Elite
Residential Sector.
[4]
My translation.
[5]
This is the most recent census that provides the type of information needed for this study.
Under the administration of President Alejandro Toledo a fast census was carried out in
2005, collecting only general demographic information. Information on employment,
housing conditions, and services were not collected, but it was planned to be collected in
future years during the next stages of this census. The design of this census as well as its
first results was highly criticized by the incoming administration of President Alan García
and its supporters. As a consequence, García’s administration carried out a new census in
2007, though its design and preparation was also highly criticized by local experts because
of the quickness and improvisation in its design and implementation. The results of both
censuses were not available at the time this paper was written.
[6]
Not much research has been done for the current period. The first comparative
systematization by Portes et al. (2005) just appeared including the cases of Santiago,
Buenos Aires, Bogotá, Lima, Montevideo, Rio de Janeiro and México D.F. The authors
consider that the most important feature of contemporary Latin American cities is the
adoption of the neoliberal model as the main force guiding their processes, which in Latin
America translates in the end of the period of urban primacy by the capital city on each
country, a period of population growth mainly by vegetative growth and not by migration,
the formalization of the housing markets, the increase of residential segregation by the
creation and sprawl of gated communities, and the proliferation of alternative mechanisms
of social mobility as the increase of informal precarious economic activities and
criminality.
[7]
By 1993, Perú was divided politically into 24 Departments, each of them divided in
districts. One of these departments is the department of Lima, whose capital is the city of
Lima. Currently, the country is divided into Regions. In most cases, each of these Regions
matches with what was formerly called Departments.
[8]
There is a data caveat on this, which is that people who were born outside the city of Lima
but inside the department of Lima are considered as Born in Lima and not as migrants.
However, given the classification of the original information provided by INEI, this
classification seems to be the most suitable to identify migration.
29
[9]
Figures by Longley et al (2005).
[10] Note that the denominator of the variance (n, which is the number of features in the study
area), was moved to the numerator to simplify the formula.
[11] The city of Lima has the particularity of including two politically autonomous regions. One
is the City of Lima, which includes the old colonial center, and which includes the three
branches of expansion described above. The other is the region of Callao, which is
originally the old colonial port of Callao, which during the 20th century also expanded to
the east, towards Lima city’s center. Both cities expanded simultaneously, and by the 1950s
they joined, forming an urban continuum though maintaining their political independence.
However, it was the center of the colonial city of Lima that gained primacy in the whole
city concentrating most of the country’s political and economic power. As a consequence,
what we commonly known as the city of Lima really has historically two colonial centers
each with their own processes of urban expansion that followed the same common rule of
locating the poor population to their peripheries (Ortiz de Zevallos 1992).
[12] Precisely, the oldest shantytowns occupied by invasions of land occurred in the 1940’s in
the districts of El Agustino (Cerro San Cosme, Cerro San Pedro, and El Agustino) and
Rímac (Cerro San Cristóbal). Years later the invasion of lands continued in the way to
west. See Matos Mar (1977) and Driant (1991).
[13] Consistent with this trend, Driant finds that by the mid 1970’s the importance of migration
in Lima’s population growth tended to decline, passing from 52.2% in the period between
1967 – 1972 to 48.1% in the period between 1976 – 1981. By this period, Lima started to
experience a natural increase of its population (1991: 128-129).
[14] The database provided by INEI for this paper aggregates all foreign born population as one
single group. Consequently I was not able to identify if groups of a specific nationality
have better opportunities than others.
[15] Statistically significant clusters are those clusters whose local Moran’s I index pass the
hypothesis test to prevent that their score is given by chance at the 0.05% confidence level.
However, some areas that are in fact heterogeneous and which are surrounded by other
heterogeneous areas (for example an area 33% low socioeconomic level, 34% middle
socioeconomic level, and 33% high socioeconomic level that is surrounded by areas of
similar composition) can be identified as a significant cluster by the Moran’s I index. To
avoid this problem, I used and additional filter: after calculating the global Moran’s I index,
only areas with a Z value of 1.96 or higher, a local Moran’s I index of 0 or higher, and
composed of a 66% or more population of the defined group were chosen as significant
clusters. The same filter applies to identify the clusters by place of origin.
[16] In this case, no clusters of foreign born population were found given their small relevance
in all areas of Lima which did not matched the criteria of selection described before (only
13% of foreign born population in the area with its highest presence).
[17] I should mention that Caldeira is more pessimistic about the new residential segregation
with residential proximity since the development of vigilance systems and a more punitive
law generates more social distance between groups. On the contrary, Sabatini, based in the
case of Santiago, Chile, finds evidence to suggest that there are new possibilities of
integration among groups.
30
Map 1
Zones and Districts of Lima, 1993
31
Figure 1
Models of Spatial Autocorrelation1
A
1
B
C
I = - 1.00
I = 0.00
I = 1.00
Random
Dispersed
Clustered
Figures by Longley et al (2005)
32
Chart 1
Lima: Population by Socioeconomic Level and Migration Condition
Zone and District Level, 1993
SOCIOECONOMIC LEVEL
ZONES AND DISTRICTS
MIGRATION
% Low Socio –
Economic Level
% Middle Socio –
Economic Level
% High Socio –
Economic Level
% Born in Lima
% Migrants
% Foreign Born
OLD LIMA
Lima
Rimac
El Agustino
Brena
La Victoria
Total Old Lima
38.88
43.59
66.29
28.98
38.22
42.94
58.55
55.02
33.57
68.64
58.95
55.04
2.57
1.39
0.14
2.38
2.83
2.02
63.41
66.51
65.78
62.49
63.05
64.20
35.90
33.23
34.16
36.87
36.42
35.33
0.69
0.26
0.07
0.64
0.53
0.47
CALLAO
Callao
Bellavista
La Perla
Carmen de La Legua
La Punta
Ventanilla
Total Callao
53.73
24.01
23.79
50.64
6.26
69.18
49.35
45.66
70.68
72.10
49.18
73.78
30.60
49.12
0.61
5.31
4.10
0.18
19.96
0.22
1.53
27.32
31.98
33.57
31.66
42.88
32.83
29.64
72.09
67.42
65.99
68.20
54.37
67.06
69.86
0.60
0.60
0.44
0.14
2.75
0.11
0.50
HIGH RENT ZONE
Barranco
Chorrillos
Jesus Maria
La Molina
Lince
Magdalena del Mar
Miraflores
Pueblo Libre
San Borja
San Isidro
San Luis
San Miguel
Santiago de Surco
Surquillo
Total High Rent Zone
23.58
55.28
11.23
18.52
16.25
17.36
8.83
12.70
6.95
3.86
26.12
18.71
17.15
27.19
22.34
69.29
42.44
76.59
49.39
75.97
71.82
67.86
74.28
65.96
60.69
69.26
70.71
60.36
66.10
62.47
7.13
2.28
12.17
32.09
7.78
10.82
23.31
13.02
27.08
35.44
4.61
10.58
22.49
6.71
15.20
71.94
63.94
58.28
58.67
63.18
61.49
59.90
60.56
58.78
58.28
60.27
55.27
63.35
63.85
61.29
26.69
35.76
39.92
38.64
35.39
36.60
34.46
37.87
39.06
34.10
39.29
43.91
34.58
35.51
36.76
1.37
0.30
1.81
2.69
1.43
1.91
5.65
1.57
2.16
7.61
0.44
0.82
2.07
0.64
1.95
33
SOCIOECONOMIC LEVEL
ZONES AND DISTRICTS
MIGRATION
% Low Socio –
Economic Level
% Middle Socio –
Economic Level
% High Socio –
Economic Level
% Born in Lima
% Migrants
% Foreign Born
EASTERN CONE
Ate Vitarte
Cieneguilla
Chaclacayo
Lurigancho
Santa Anita
San Juan de Lurigancho
Total Eastern Cone
62.08
71.66
58.61
68.80
56.44
63.51
62.78
36.12
26.95
38.62
30.34
42.65
36.21
36.37
1.80
1.39
2.77
0.86
0.91
0.27
0.85
54.48
60.79
63.85
62.26
56.43
54.94
55.98
45.32
38.35
35.38
37.31
43.44
44.97
43.84
0.20
0.86
0.77
0.43
0.13
0.09
0.18
NORTHERN CONE
Ancon
Carabayllo
Comas
Independencia
Los Olivos
Puente Piedra
San Martin de Porres
Santa Rosa
Total Northern Cone
71.49
62.82
56.13
58.21
47.64
80.52
42.59
66.58
53.78
28.32
36.57
43.61
41.61
50.46
19.39
56.44
33.22
45.50
0.19
0.60
0.26
0.18
1.90
0.09
0.97
0.20
0.72
63.13
61.15
62.37
60.71
54.33
36.43
59.78
59.76
57.40
36.70
38.78
37.53
39.20
45.51
63.49
40.03
40.08
42.47
0.17
0.06
0.10
0.09
0.15
0.08
0.19
0.16
0.13
SOUTHERN CONE
Lurin
Pachacamac
San Juan de Miraflores
Villa El Salvador
Villa Maria del Triunfo
Total Southern Cone
74.89
84.11
59.24
69.86
66.09
65.57
25.01
15.78
40.21
30.13
33.86
34.22
0.10
0.11
0.55
0.01
0.05
0.21
71.36
60.12
60.61
43.10
61.07
54.53
28.49
39.79
39.29
56.84
38.86
45.39
0.16
0.09
0.10
0.06
0.08
0.08
SOUTH BEACHES
Pucusana
Punta Hermoza
Punta Negra
San Bartolo
Santa Maria del Mar
Total South Beaches
65.44
65.47
59.38
59.82
66.40
62.98
34.56
33.97
39.91
40.18
33.60
36.75
0.00
0.55
0.70
0.00
0.00
0.27
73.97
69.15
69.64
69.68
63.11
70.82
25.83
30.06
29.70
29.37
36.89
28.56
0.20
0.79
0.66
0.95
0.00
0.61
TOTAL LIMA CITY
48.46
47.65
3.89
55.85
43.56
0.58
Source: Instituto Nacional de Estadística e Informática (INEI)
34
Chart 2
Lima: Socioeconomic Level by Place of Origin, 1993
(Simple Linear Regression R-square values)
% Low Soc – Ec Level
% Middle Soc - Ec Level
% High Soc – Ec Level
% Born in Lima
(-) 0.071*
(+) 0.076*
(+) 0.020*
% Migrants
(+) 0.102*
(-) 0.091*
(-) 0.051*
% Foreign Born
(-) 0.284*
(+) 0.073*
(+) 0.690*
* Coefficient significant at the 0.05% Confidence Level
Chart 3
Lima: Clustering Index by Socioeconomic Level and by Place of Origin, 1993
Soc – Ec Level
Low
Middle
High
Global Moran’s I
0.16
0.13
0.15
Place of Origin
Born in Lima
Immigrants
Foreign Born
Global Moran’s I
0.18
0.18
0.12
Chart 4
Lima: Dissimilarity Index by Socioeconomic Groups and by Place of Origin, 1993
Soc – Ec Level
Low vs. Middle
Low vs. High
Middle vs. High
D
42.86
85.28
60.47
Place of Origin
Limenians vs. Immigrants
Limenians vs. Foreigns
Immigrants vs. Foreigns
D
18.89
60.08
63.36
35
Map 2
Lima: Clusters by Socioeconomic Level, 1993
36
Map 3
Lima: Clusters by Place of Origin, 1993
37