Keywords

1 Introduction

The Republic of Suriname lies at the northern coast of South America and is home to 541,638 people (General Bureau of Statistics Suriname 2013). Suriname is made up of ten districts, with 62 ressorts (the smallest administrative unit established by law). Around 70% of the total population live within the Greater Paramaribo Region (GPR), consisting of the three districts Paramaribo, Wanica and Commewijne (comprising 22 ressorts). The ressorts are indicated in Fig. 25.1 with bold letters. The capital Paramaribo can be considered a medium-sized urban core, with a population of 240,924 and population density of 1324 inhabitants/km2(OECD 2012). Its population has increased by 16% between 2000 and 2012. This, in turn, has resulted in an increased demand for residential land. Consequently, the GPR has experienced urban sprawl, with ribbon development occurring outward from Paramaribo into Wanica and Commewijne (Fung-Loy et al. 2019). Uncontrolled urban sprawl can have negative consequences such as residential segregation, where specific groups end up in specific locations.

Fig. 25.1
A map of South America depicts the Republic of Suriname with the inlet view of the G P R, which traces the neighborhood, resort, district, major roads, and water body.

Geographical location of the GPR

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The research presented in this chapter examines socio-economic and ethnic segregation within the GPR. Socio-economic segregation is assessed by using ISCO occupation groups as a proxy for socio-economic status. In addition, ethnic segregation is also examined in this multi-ethnic country. Furthermore, the relationship between ethnic group and occupation, and thus socio-economic class is analysed. This study uses data from the 2004 and 2012 Censuses, which were obtained at ressort level. As ressorts are relatively large and heterogeneous, ressort-level data was downscaled to the neighbourhood-level, which is more suitable for segregation analysis. 106 neighbourhoods were defined based on archival maps acquired from the National Planning Office Suriname (Stichting Planbureau Suriname 1985), which were georeferenced to the ressorts. In 2012, the average neighbourhood population size was 3611.

1.1 Housing Composition

Land in Suriname can be acquired through two processes, namely government allocation and private purchase. Every Surinamese citizen can apply for governmental land; however, the process is bureaucratic, lengthy and often littered with corruption. In addition, as most plots within Paramaribo itself are already allocated, government land is mainly located far from the city, and is often deprived in terms of water and electricity supply. Governmental allocation usually occurs in the form of social housing projects. Nevertheless, many residents cannot afford buying these plots and/or houses on their own; therefore the projects are subsidised (McHardy and Donovan 2016). While waiting for governmental allocation, people usually rent a house, stay in a family-owned house, or squat an unoccupied house or empty plot. Squatter settlements consist of rural migrants, who do not have a social network in place to assist them (Hoefte 2014).

Purchasing land and/or a house through private purchase is reserved for the better off, due to high building costs, high interest rates for loans and high prices for privately owned land. Therefore, who owns what piece of land is (in part) determined by socio-economic status. Moreover, private real estate developers develop housing projects for a specific socio-economic group in mind. Similarly, social housing projects are also targeted towards a certain group. These processes can lead to spatial sorting of the socio-economic groups into different neighbourhoods. In 2014, of 134,329 households, the shares of private owners, renters, people in social housing, as well as people living in squatter settlements were 69%, 12%, 4% and 0.5%, respectively (Namdar and Caupain 2015).

Residential area can be differentiated by socio-economic status. This was studied for the GPR by Fung-Loy et al. (2019), where the authors used housing type as a proxy for socio-economic status. Residences were differentiated based on spatial characteristics. The residential urban area was divided into rich, middle, middle to low and poor residences. Residences on plot sizes larger than 600 m2 and houses bigger than 300 m2 were considered to be residences for the rich. The residences for the poor consisted mainly of squatter settlements and social housing projects initiated by the government. Based on this residential differentiation, Fung-Loy et al. (2019) found that the GPR as a whole is fairly heterogeneous in terms of residence types (indicated by multi-group dissimilarity indices ≈0.4). There was, however, a certain level of segregation between rich and poor residences, both being concentrated in specific areas. Rich residences were mostly located in the north of Paramaribo in ressort Blauwgrond (BD in Fig. 25.1), while poor residences were concentrated in the south (in ressorts Latour (LR) and Pontbuiten (PN)).

1.2 Occupational Composition

As stated by Verrest (2010) and Hoefte (2014), residential segregation is linked to socio-economic status and income inequality between different population groups in Paramaribo. The correlation between income inequality and residential segregation of socio-economic groups was also observed in European countries (Tammaru et al. 2019).

Income inequality and thus socio-economic status of individuals is linked to their occupation, time of arrival into the city and the level of education (Verrest 2010; Hoefte 2014). For the occupational categorisation, the census classification is based on the ISCO-88 classification (International Labour Office 1990). This classification divides occupations into ten major groups, ranging from Legislators, Senior officers and Managers to Elementary occupations. These occupation groups were further classified into three socio-economic groups, namely, Top, Middle and Bottom. The Top socio-economic group consisted of Legislators, Senior officers and Managers and Professionals. Research suggest that this group generally has the highest earnings out of all groups and as such is linked to the Top socio-economic group (Leetmaa et al. 2015). From the census data, a higher education was proven to correspond with a higher income (Schalkwijk 2015), and thus a higher socio-economic status. In Suriname, Legislators, Senior officers and Managers can have varying levels of education (World Economic Forum 2013), but mainly achieve Tertiary and Secondary education levels (General Bureau of Statistics Suriname 2014). The Middle socio-economic group consists of Technicians and Associate Professionals, and Armed Forces, Clerks, Service Workers and Shop and Market Sales Workers, Skilled Agricultural and Fishery Workers, and Craft and Related Trade Workers. The Bottom socio-economic group was made up of Plant and Machine Operators, and Elementary occupations. Figure 25.2 shows that the largest occupational groups in the GPR in both census years were Service Workers and Shop and Market Sales Workers, as well as Elementary occupations. Combined, these accounted for around 34% of all workers in 2012. Meanwhile, Legislators, Senior officers and Managers accounted for only 6% of all workers in the GPR in 2012. Between 2004 and 2012, the Top group experienced an increase of 6%, while Service Workers and Shop and Market Sales Workers and Elementary occupations combined increased by 41%.

Fig. 25.2
Two horizontal bar charts plot the distribution of occupations. Middle and S E R have high occupational distributions in 2004 and 2012.

Distribution of occupational groups and change over time

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1.3 Ethnic Composition

In Suriname, occupation, time of arrival into the city and the level of education of individuals are linked to ethnicity. As a result of colonisation, Suriname has a very ethnically diverse population. The main ethnic groups are shown in Fig. 25.3. The largest ethnic groups in the GPR, according to both the census of 2004 and of 2012, are the Hindustani (descendants of contract labourers from India), the Creoles (descendants of former African slaves who stayed within the city) and the Javanese (descendants of contract labourers from Indonesia). Other smaller ethnic groups include Mixed (people of mixed ethnicity), Maroons (descendants of African slaves, who escaped into the interior of the country), Caucasians, Chinese and Amerindians (indigenous people of the Americas). Maroons were the most segregated ethnic group within the GPR, specifically in Paramaribo. This uneven distribution of Maroons can be seen in Fig. 25.3, where we see a concentration of Maroons in the southern ressorts of Paramaribo, mainly LR and PN.

Fig. 25.3
Two maps of G P R trace the city center, districts, resorts, Amerindian, Maroon, Creole, Hindustani, Javanese, Chinese, Caucasian, and mixed, with a gradient of colors.

Ethnic distribution per ressort for both census years

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The different ethnic groups arrived in Suriname at different times in history and for different purposes. Consequently, they were historically located in different areas in the country. For example, before the abolition of slavery in 1863 the Caucasian elite were located in the city centre in Paramaribo, with their servants (mainly Creoles) living in small servant quarters at the back of the plots. After 1863, other areas were established for free Creoles migrating from the plantations to the city. These areas, such as Frimangron (Free people’s land, established for emancipated slaves), were the smaller, less affluent areas in the city centre. In 1921, almost 80% of Paramaribo residents were Creole. In addition, mainly Asian contract labourers, the Hindustani (first arriving from India in 1873) and the Javanese (first arriving from Java in 1890), were found for the colony to work on the plantations. The Maroons settled in tribal communities in the interior of Suriname, after escaping the plantations. The Amerindians were also concentrated in the interior districts of Suriname and at the coast.

As agriculture declined and many plantations closed in the 1930s, many inhabitants were given small-scale agricultural holdings in the districts of Commewijne and Wanica. Thus, many Hindustani and Javanese settled in these districts. During the Second World War, the demand for workers in the construction, bauxite and service sector increased, thus attracting many Hindustani and Javanese to the city for better occupational, and later educational opportunities (Hoefte 2014). The Maroons became a significant group in Paramaribo, after fleeing the civil war in the interior between 1986 and 1992. The Maroons settled in and around the former social housing projects, predominantly in the south of Paramaribo. As these newcomers arrived in the city, the previous rich inhabitants moved to the north and southwest of the city centre, towards the newly built suburbs (de Brujine and Namdar 2013).

According to the census of 2012, the ressorts are generally ethnically mixed. However, we can see that Creoles are still dominant in the centre, while Hindustani dominate west Paramaribo and Wanica (see Fig. 25.3). District Commewijne has a higher concentration of Javanese people. As certain ethnic groups arrived in the city later than others, they lagged behind in educational and occupational opportunities. Over time, a more equal distribution of ethnicities was achieved. As such, educational and occupational opportunities were also more equally distributed among the different ethnicities. Nevertheless, as stated by Verrest (2010) and Hoefte (2014), some occupational groups are still dominated by specific ethnic groups. Therefore, ethnic and socio-economic segregation can be linked (Reardon and Bischoff 2011). Such a link was also found in, for example, Belgium, where poorer neighbourhoods had a higher concentration of non-European migrants (Costa and de Valk 2018).

2 Methods

2.1 Socio-economic Segregation

The dissimilarity index (DI) was used to measure segregation between the socio-economic groups within the GPR. The DI describes the overall evenness of the distribution between two groups. It also provides the ability to evaluate each group and each area separately (Sakoda 1981). DI values range from zero to one, with values below 0.3 indicating a low level of segregation, and values above 0.6 pointing at a high level of segregation. However, the DI is scale dependent and thus can be influenced by size of the areas analysed (Quillian and Lagrange 2016; Andersson et al. 2018). In order to compare regions or countries, we also consider the change in DI (Ismail 2013). The DI and the change in DI were calculated between each occupational group and between the aggregated socio-economic groups Top, Middle and Bottom.

In addition to the DI, the location quotient (LQ) was calculated, to evaluate the concentration of the Top and Bottom socio-economic groups in the neighbourhoods, compared to the GPR as a whole. Location quotient values of less than one or more than one mean that a socio-economic group is under- or overrepresented in a neighbourhood, respectively. A value equal to one means that the neighbourhood’s share of a group is equal to the share of the group within the GPR (Miller et al. 1991). Moreover, the neighbourhoods were classified by socio-economic composition, based on the Top, Middle and Bottom groups. The classification was applied according to Marcińczak et al. (2015), which indicates the level of income inequality within a neighbourhood. The three socio-economic groups were merged into different neighbourhood types based on the typology provided by Marcińczak et al. (2015). Finally, the location of the Top occupational group in Paramaribo was analysed. Both the location quotients and the DI were calculated with the Geo-Segregation Analyzer software (Apparicio et al. 2013). Further methodological details regarding the calculations of the DI, LQ and other maps are described in the Introduction of this Book.

2.2 Ethnic Segregation

We also investigated ethnic segregation. This was done at ressort level, as ethnicity data was only available at this level. The proportion of each ethnic group within a ressort was calculated. In addition, the multi-group DI was calculated per ethnic group, to assess the overall level of evenness of distribution between the different ethnic groups within the GPR. Finally, the link between socio-economic segregation and ethnic segregation was analysed. To determine the correlation between ethnic and socio-economic segregation, we examined the overlap of the results of the socio-economic and ethnic segregation analysis (Leetmaa et al. 2015; Harris et al. 2017). The correlation between ethnicity and socio-economic group was calculated for both census years.

3 Results and Discussion

3.1 Socio-economic Segregation

In recent years, the average Gini index has decreased for the Latin America and the Caribbean region (from 54 to 47.5 between 2002 and 2014), suggesting a decreasing income inequality (Tornarolli et al. 2018). However, in Suriname income inequality has increased between 1980 and 2004, with Gini indices increasing from 41 to 55 (Menke et al. 2013). For the census year 2012, no Gini index was calculated due to low response rates. As such, Suriname is considered to be one of the most unequal countries of the Caribbean. In 2004, the poorest quintile received 3.9% of the total income, while the richest quintile received 53.6% (PAHO Suriname 2012).

To analyse if the increasing income inequality is linked with an increasing spatial segregation, the DI was calculated to quantify the level of segregation between the different occupational groups (Table 25.1). For both years 2004 and 2012, Elementary occupations (ELE) were the most segregated when compared to the other occupational groups. The DIs > 0.50 between the Top and Bottom groups for 2004 and 2012, indicate a high level of segregation between these two groups. An increase of 0.7% per year in the DI is also noted, indicating an increasing segregation. When analysing all socio-economic groups, a multi-group DI of 0.48 (in 2004) and 0.51 (in 2012) also indicate an increasing level of segregation.

Table 25.1 Dissimilarity indices (multiplied by 100) between all occupational groups, as well as the Top, Middle and Bottom groups in 2004 and 2012
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As the DIs between the Top and Bottom groups indicate, these two groups are highly residentially separated from each other. This can also be seen through the location quotients for the Top and Bottom socio-economic groups in 2004 and 2012 (Fig. 25.4). In 2004, there was a higher concentration of the Top group in district Paramaribo in ressort Blauwgrond (BD on the map). The ressorts on the fringe of the city, especially ressorts Latour (LR) and Pontbuiten (PN), and district Commewijne, are more associated with the Bottom socio-economic group.

Fig. 25.4
Four maps of G P R trace the location quotients of top and bottom occupational groups in 2004 and 2012, with a gradient of colors.

Location quotient maps at neighbourhood level for Top and Bottom occupational groups

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As can be seen in Fig. 25.5, the Top socio-economic status (SES) neighbourhoods were concentrated in north Paramaribo, mainly in ressort Blauwgrond (BD). The Bottom group was largely concentrated in south Paramaribo, in Latour (LR) and Pontbuiten (PN). Districts Wanica and Commewijne consisted mostly of Middle and Bottom to Middle SES neighbourhoods. There were no Polarized neighbourhoods in the Greater Paramaribo Region.

Fig. 25.5
Two maps of G P R trace the districts, resorts, and classification of neighborhoods in 2004 and 2012, with a gradient of colors.

Classification of neighbourhoods by socio-economic composition

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The Bottom and Bottom to Middle SES neighbourhoods were dominant and located in central and southern Paramaribo and in the less urban districts Commewijne and Wanica in both years. The Top and Middle to Top SES neighbourhoods were mostly found in Paramaribo itself. This follows the trend mentioned in the introduction, where the rich, who formerly concentrated in the old city centre, moved towards the suburbs of north and west Paramaribo, leaving behind the working class in the city centre. A large elite neighbourhood emerged in Commewijne, namely Palm Village. This area did not follow the historic pattern of socio-economic segregation; it was a relatively new private real estate development, which turned a former plantation into a high-end gated community. Overall, there was a fairly stable pattern of socio-economic composition of the neighbourhoods in Paramaribo between 2004 and 2012. Of the 106 neighbourhoods, eight downgraded to a lower socio-economic status and 13 upgraded.

To assess in which neighbourhoods the Top socio-economic group was concentrated, quintiles were calculated. Figure 25.6 shows that the neighbourhoods with the highest 20% of Top (Q1) were mainly located within Paramaribo itself. Some were the established suburban neighbourhoods in the 1950s, while the rest were newly established neighbourhoods, consisting mainly of gated communities targeted to the very rich. Neighbourhoods with the lowest 20% of Top (Q5) were located predominantly in district Wanica and in the centre of Paramaribo. Overall, Paramaribo had the largest proportion of Top SES neighbourhoods, a remnant of the colonial past.

Fig. 25.6
Two maps of G P R trace the districts, resorts, and different locations of the top occupational group in 2004 and 2012, with a gradient of colors.

Location of the Top occupational group

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3.2 Ethnic Segregation

To assess the level of ethnic segregation in Paramaribo, first the proportion of each ethnic group within a ressort was assessed for both census years. When comparing 2004 and 2012 (Fig. 25.3), one change which stands out, is the increase of the proportion of Maroons concentrating mainly in and around social housing projects in the ressorts Latour (LR) and Pontbuiten (PN) in Paramaribo. In 2012, the proportion of Maroons also increased in ressorts Saramaccapolder (SR) and De Nieuwe Grond (DD) in Wanica and Meerzorg (MG) in Commewijne 2012. This ethic group has experienced the largest increase in the GPR, growing by 43% between 2004 and 2012. As mentioned, the migration of Maroons to the urban area started largely after 1986 (later than the other groups) and as the results show, this is still continuing. Between 2004 and 2012, the Mixed group experienced the second largest growth, 18%. Interestingly, there is also a slight increase of the proportion of Chinese in districts Wanica and Commewijne. As population increased in these districts, so did the commercial activities, which are dominated by Chinese merchants. Nevertheless, Wanica and Commewijne were still dominated by Hindustani and Javanese, following the historical pattern.

The level of ethnic segregation was also assessed via the DI. It was calculated for each ethnic group per district and for the GPR as a whole. In addition, the overall multi-group DI was measured (Table 25.2). In 2004, the Maroons and the Javanese were the most segregated within the GPR. In Paramaribo, Maroons were mainly concentrated in ressorts LR and PN, while Javanese were concentrated in BD and RE (see Fig. 25.3). In Wanica, the Javanese were also the most segregated, concentrating in ressort LP and DG. In 2012, Maroons and Javanese were still the most segregated ethnicities within the GPR. In Paramaribo, next to higher levels of segregation for Maroons and Javanese, we also see an increasing segregation of Chinese and Caucasians. These two groups were mainly concentrated in the city centre and the northern ressorts of Paramaribo. For both years, Maroons were the most segregated ethnic group within the GPR.

Table 25.2 Dissimilarity indices (multiplied by 100) per ethnic group, per ressort and the GPR as a whole
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Overall, all districts and the GPR as a whole have a low DI (<0.35), indicating a low level of segregation among the different ethnic groups. In other words, overall the GPR generally has a heterogeneous population with regards to ethnicity at district level.

3.3 Link Between Socio-economic and Ethnic Segregation

In order to quantify these visually perceived relationships between the different ethnicities and socio-economic groups, correlation coefficients were calculated based on the absolute number of population in the different groups (Fig. 25.7). Results show that indeed Maroons were primarily negatively correlated with the Top socio-economic group. Where in 2004, Amerindians were the most correlated with the Bottom group, in 2012 the Maroons became the most correlated with the Bottom occupational group. This indicates that as the proportion of Maroons grows, they are mostly accessing occupations associated with the Bottom socio-economic group. As they are the last ethnic group to arrive in the urban area, they have an educational and thus occupational disadvantage. In 2012, Javanese were moderately correlated with all socio-economic groups, while Hindustani were slightly more correlated with the Bottom group and Creoles were more correlated with the Middle and Top groups. The ethnicities most correlated with the Top socio-economic group were Mixed, Caucasian and Chinese. Caucasians and Chinese were historically concentrated in Paramaribo, allowing them better educational and occupational opportunities; thus, they are strongly correlated with the Top socio-economic group. The same can be said for the Mixed group; they were concentrated in Paramaribo, affording them better development opportunities.

Fig. 25.7
A correlation matrix compares the data of Amerindian, Maroon, Creole, Hindustani, Javanese, Chinese, Caucasian, and mixed, with top, middle, and bottom in 2004 and 2012.

Correlation between ethnicity and socio-economic group

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4 Conclusions

In this study, socio-economic segregation in the Greater Paramaribo Region in Suriname was examined. ISCO categories were used as a proxy for socio-economic status. Results show that overall, there is a high level of socio-economic segregation in the GPR. The segregation has also increased between 2004 and 2012. The level of segregation is especially high between the Top and the Bottom groups (DI2012 ≈ 0.56). European cities seem to be following this trend also (Musterd et al. 2016). The rich and poor segregate in separate areas within the GPR, with the poor (Bottom) being the most segregated socio-economic group. In addition, the overall multi-group DI calculated in this study (DI2012 = 0.51) was higher than those found by Fung-Loy et al. (2019) (DI2015 ≈ 0.3, which was based on the distribution of house type). This indicates that there is some correspondence between socio-economic status and housing type in this region. However, there can be a mismatch between the residential characteristics and the socio-economic group, for example, in neighbourhoods in transition.

Furthermore, ethnic segregation in the GPR was also assessed. Overall, the DI for ethnic segregation is relatively low in the GPR (DI2012 = 0.33). However, there are some ressorts where certain ethic groups concentrate, such as ressorts LR and PN where Maroons concentrate; they experience segregation in district Paramaribo according to a DI > 0.40. When comparing the multi-group DI for socio-economic segregation (DI2012 = 0.51) with the multi-group DI for ethnic segregation (DI2012 = 0.33), we see that the GPR is less segregated by ethnicity, but more segregated by socio-economic status. This was also found in other studies for Suriname and other Latin American and Caribbean countries such as Brazil and Trinidad and Tobago (Brathwaite 1980; Lichter et al. 2012; Verrest 2010). For the United States, it was found that while ethnic segregation is still larger than socio-economic segregation, ethnic segregation has decreased, while socio-economic segregation has increased (Brady et al. 2017).

Assessing the link between ethnic and socio-economic segregation, we see that for certain ethnicities there exists a high correlation with a specific socio-economic statuses. Maroons are increasingly correlated with the Bottom, while Mixed and Caucasians are highly correlated with the Top socio-economic group. This reflects the history of Suriname; Caucasians were traditionally the rich colonists and, similar to the Mixed, were concentrated in the urban centre while the Maroons fled into the interior to escape slavery. Only after the mid-twentieth century Maroons migrated to the city, experiencing a significant lag in education and consequently occupational opportunities. As such, Maroons are far behind Mixed and Caucasians on the socio-economic ladder.

In this research, the socio-economic and ethnic segregation, and the link between the two was analysed. As certain ethnic groups are more strongly correlated with certain socio-economic statuses, increasing socio-economic segregation can limit the upward socio-economic mobility opportunities for specific marginalised ethnic groups. As income inequality continues to increase, it is likely that socio-economic segregation will increase as well.