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Population pressure and environment in the context of growth: evidence from an Indian city

Population pressure and environment in the context of growth: evidence from an Indian city International Journal of Urban Sustainable Development Vol. 3, No. 2, November 2011, 168–184 Population pressure and environment in the context of growth: evidence from an Indian city a b a Vikram Dayal , Preeti Kapuria and Arup Mitra * a b Institute of Economic Growth, University of Delhi, Delhi 110007, India; Department of Business Economics, University of Delhi, Delhi 110007, India (Received 13 May 2011; final version received 8 August 2011) This article analyses the Indian city of Delhi using the contrasting concepts of resilience and agglomeration economies. Delhi is an expanding system that is changing because of economic, social and ecological driving forces. The driver–pressure–state–impact–response (DPSIR) framework is used in this article. We measure the extent of population pressure at the ward level [population pressure index (PPI)] by applying the statistical stochastic frontier function framework. We then examine the association between the PPI and the variables representing well-being and the overall ecosystem. There are overlaps between PPI and poor well-being indicators. However, some areas have a poor environmental state even though their population pressure is not at the frontier. This seems to have resulted from population growth spilling over to areas not fit for human habitation. Further migration of people in response to growth and employability may worsen the levels of well-being. However, appropriate interventions and investment in basic amenities can stop such severe welfare losses and help the city maintain its role as the engine of growth. Keywords: resilience; growth; city; basic amenities; ecology 1. Introduction to sustain nature. A testimony to this are the efforts made by urban planners to create urban spaces that The environmental scientists perceive an equilib- also incorporate elements from nature (Macharg rium relationship between the environment and the 1 1971). human habitation, which may get disturbed in the This article, using the concepts of resilience process of development and population growth. and agglomeration economies, aims at analysing Moreover, ‘cities are human-made artefacts, and an urban conglomeration such as Delhi, which are often opposed to nature’ (Rodenburg et al. is an expanding system with drivers, constituents 2001). Nature has many interrelated biotic and and structure changing as a consequence of eco- abiotic elements which act in unseen and intricate nomic, social and ecological driving forces. Delhi, ways. In cities, human engineering and infras- the capital of India, has grown rapidly. Its popu- tructure dominate. A road provides a contrast to a lation increased from about 6.2 million in 1981 forest – the road itself is devoid of any species. A to about 13.8 million in 2001, and was pro- city draws on resources from a vast hinterland – jected to increase to 23 million by 2021 (Planning water, food, fossil fuel – and discharges pollutants Commission 2009). According to Department of in air and water. Hence, special efforts are needed *Corresponding author. Email: arup@iegindia.org This article is based on research conducted as part of the ‘Urban Social-ecological and Globalization’ project supported by the Stockholm Resilience Centre, Stockholm, Sweden. ISSN 1946-3138 print/ISSN 1946-3146 online © 2011 Taylor & Francis http://dx.doi.org/10.1080/19463138.2011.613616 http://www.tandfonline.com International Journal of Urban Sustainable Development 169 Environment and Forests (DoEF 2010) the pop- not actually explode, stress may build up and in the ulation of Delhi was 18 million in 2010. There process of growth and expansion, a particular spa- was rapid, though fluctuating economic growth in tial unit may approach its maximum flexibility or the 2000s – for example, 9.8% in 2003/2004 and capacity to accommodate activities and population. 4.7% in 2002/2003 (Planning Commission 2009). Hence, there is a need to empirically assess the Per capita income rose by about 93% between pressure that may arise in a spatial unit in the pro- 2000/2001 and 2007/2008 (DoEF 2010). cess of growth, and the impact of this pressure This rapid growth created challenges in terms on the existing infrastructure and basic amenities, of provision of basic services and environmental which may in turn show deleterious effects on management. In the urban areas of Delhi, about human welfare and environment. 78% of households (HH) had access to piped water The resilience framework would suggest that supply in 2001, compared to about 48% of HH in with interventions, the capacity of the ecosystem the rural areas of Delhi. Sewerage coverage was to absorb and accommodate growth and its related inadequate, resulting in an estimated 200 million consequences can be sustained and a new equilib- litres of untreated sewage being dumped into the rium relationship can be reached in the long run. river Yamuna that flowed through the city (Planning Nevertheless, without effective policies the nega- Commission 2009). There are also inequities in tive externalities associated with growth can have access to basic services. For example, DoEF (2010) cascading effects on the environment–habitation reported that while some select areas in the city had relationship and thus may result in gross reductions a water supply as high as 450 litres per capita per in well-being measured from economic, social, day, the average for the city was 39 litres per capita health and environmental points of view. per day, and slums on the other hand got only 14 Even when the pressures are not strong, ecolog- litres per capita per day. ical imbalances can arise because of mismatches In the driver–pressure–state–impact–response between what ideally should be done and what (DPSIR) framework, a set of drivers (such as is actually done. For example, certain parts of activities, income, employability and population) the city are not fit for human habitation, and are lead to pressures and a state having impacts on meant to be under green cover. However, inade- human health and ecosystems, which finally lead quacy of space in the city centre and the laxity to societal responses of economic and environmen- of the administrators may lead to resettlement of tal agents, urban administration and so on (Klatte slums in such areas resulting in gross deterioration 1997; Rodenburg et al. 2001). However, from the in well-being levels and disturbances in the ecolog- economist’s perspective, there may not be a one- ical equilibrium. However, the resilience approach to-one relationship between drivers and pressure. would suggest that with interventions such distor- The concept of agglomeration economies tells us tions can again be corrected and the objective of that positive externalities may arise in the process growth can be pursued without really causing any of concentration (Mills 1967). In other words, due major ecological flaw. to the impacts created by several drivers concen- This article attempts to capture the growth tration of economic activities may arise leading pressures and their impact on certain well-being simultaneously to productivity growth. Some of indicators empirically in the context of a grow- this productivity growth and rise in profitability can ing city economy, Delhi. This article in Section 2 be invested to relax the constraints on resources. begins by discussing the literature on the concepts The positive externalities can outweigh the neg- of resilience and agglomeration economies. The ative ones to such an extent that the spatial unit may rest of this article is structured as follows. Section 3 continue to be a major basin of attraction, imply- discusses the methodology used to estimate the pop- ing it is resilient with major features of the system ulation pressure index (PPI) at the ward level within being unchanged. However, though the system may Delhi. With the help of this index we identify areas 170 V. Dayal et al. in Delhi which are closer to or below the maxi- Pendall et al. (2010) distinguish between mum population limit. Section 4 gives empirical shocks, for example, Hurricane Katrina, and ‘slow results of the model. We then relate these results burns’, for example, urban sprawl. In evaluating to broad indicators of well-being, related to basic human systems, there is an added complexity amenitiesandecologicalissues.Finally,inSection 5 because humans can look into the future, adapt and we summarize the main findings and bring out the change circumstances. They suggest that resilience implications for policy. The database of the study is is a fruitful concept, but researchers need to set drawn from the decennial population census, 2001. spatial and temporal boundaries to their enquiry. Total population, employment type, access to safe We now briefly consider three examples of drinking water (SDW), sanitation, sewage facility urban case studies that use the concept of and type of fuel used by HH for domestic consump- resilience. Simmie and Martin (2010) relate tion are some of the attributes that are compiled the evolution of the city region economies of from population census at the ward level, that is, at Cambridge and Swansea from 1960 to 2005 to a very disaggregated unit of the city. the adaptive cycle model. Cambridge went through the following phases: reorganization, exploita- 2. Existing literature on resilience and tion and conservation; whereas Swansea experi- agglomeration economies enced release, reorganization, exploitation, con- servation, release and then reorganization. Pelling This section draws on the contrasting concepts of and Manuel-Navarrete (2011) also use the adap- resilience and agglomeration economies. tive cycle to discuss developments in the two Mexican towns of Mahahual and Playa del Carmen. 2.1. Resilience However, their aim is to study the role of power in Each discipline defines a term according to its the adaptive cycle model. requirements and perspectives. The term resilience In contrast to the previous two qualitative stud- is no exception. As Gallopin (2006) points out, ies, Janson and Polasky (2010) quantify biodi- evolutionary biology, ecology and cultural studies versity for building resilience for food security have defined it in different ways with different foci in the urban landscape of Stockholm County in and different meanings. In the context of socio- Sweden. According to Jannson and Polasky (2010), ecological subsystems, resilience can be defined ‘Compelling theoretical knowledge about essen- as a measure of persistence of systems and their tial connections between ecosystem generation, ability to absorb change and disturbance and still biodiversity and resilience in social-ecological sys- maintain the same relationships between popula- tems already exists; however, we still, to a great tions and state variables (Holling 1973). It is extent, lack spatially explicit quantitative assess- the capacity of a system to absorb disturbance ments for translating this theoretical knowledge and reorganize while undergoing change to retain into practice’. Jannson and Polasky (2010) show essentially the same function, structure, identity that although the flow of an ecosystem service may and feedbacks – in other words, stay in the same not fall, the underlying biodiversity and resilience basin of attraction (Walker et al. 2004). could be adversely affected. Pendall et al. (2010) also reviewed the In the context of our study, at times the benefits resilience literature in several fields: of growth are so substantial that the stakehold- ‘Some literature describes resilience as a return ers deliberately ignore ecological costs. Gradually, to conditions before a shock. Other resilience adverse repercussions are felt in the long run, and writing embraces a complex systems perspective. even economic growth may be affected. In such a For other fields, resilience describes the ability situation, resilience theory would suggest a note of people, regions or ecosystems to thrive despite of optimism – with corrective measures, it would adversity’. be possible to reduce the adverse impact. In other International Journal of Urban Sustainable Development 171 words, we have used the term resilience in this though higher productivity levels in larger urban study to reveal the robustness of a system in a spe- settlements could also be an outcome of higher cific spatial context, which may impinge on human technology levels (Segal 1976). welfare and the overall environment in the pro- Concentration of economic activities occurs cess of expansion. It is possible to regain the basic mainly to reap advantages of externalities aris- properties of the system through effective policy ing from indivisibilities in the production process interventions. such as interdependence of industries in terms of input–output linkages, ancillarization, market- 2.2. Agglomeration economies ing of products and availability of infrastructural The literature on agglomeration economies sug- facilities. The development pole theory explains gests that some industries induce concentration of how other groups of industries tend to form clus- economic activity as they exhibit high economies ters around a core of industries, which have a of scale in operation, and others benefit from con- high capacity to transmit growth impulses through centration because of the operation of agglomera- both backward and forward linkages. Such clus- tion economies. Concentration not only strength- ters are said to form industrial complexes with the ens the forward and backward linkages, but also following advantages (see Hermansen 1972): (1) reduces the cost of operation by developing com- substantial economies of investment expenditure – plementary services. The effective price of infras- the investment for the whole complex is less than tructure services like power, water supply, roads the sum of investment for each enterprise planned and so on gets reduced if there is concentration of and located in isolation; (2) efficient production users of these services. In all, interdependence of due to advantages of specialization, economies of industries in terms of input–output linkages, ancil- large-scale operation and organization of common larization and availability of infrastructure con- managerial and infrastructural facilities; (3) pos- tribute to the growth of agglomeration economies. sibility of jointly exploiting the natural and raw In addition, with a large population base in the material resources of the area of location; and area in which firms are located, it is less likely that (4) opportunities for close contact, rapid diffu- a glut in the commodity market or a high labour sion of technological innovations and rapid overall turnover cost would occur. As Mills and Hamilton development of the economy. (1994) point out, labour requirements in a partic- The external economies, in general, can be ular industry are subject to random, uncorrelated, divided into two categories: (1) urbanization seasonal or cyclical fluctuations. Hence, an urban economies and (2) localization economies. These area with more industries generates a higher level economies are different from the internal scale of employment than can be achieved with indus- economies, which are returns to internal scale char- tries spread out in separate urban areas. Higher acterizing the technology of the individual firm, levels of urbanization mean a large overall labour regardless of its location. Localization economies market and a large service sector interacting with are external to the firm but internal to the indus- manufacturing. Further, it has been argued that try and, as Henderson (1986) describes, reflect (1) average productivity increases with the size of the economies of intra-industry specialization where labour market, as average match between the skill greater industry size permits greater specialization characteristics of workers and the job requirements among firms in their detailed functions; (2) labour of firms improves with an increase in the size of the market economies where industry size reduces labour market (Kim 1991). In addition, specializa- search costs for firms looking for workers with spe- tion of labour is related positively to the size of the cific training relevant to that industry; (3) scale of labour market, as workers in large labour markets communication among firms affecting the speed tend to invest in more specialized human capital, in of adoption of new innovations; and (4) scale turn resulting in productivity growth (Kim 1989), in providing public intermediate inputs tailored 172 V. Dayal et al. to the technical needs of a particular industry. social and ecological driving forces can lead to The urbanization economies, on the other hand, expansion in population which generates pressure are external to both firm and industry, and result on the existing amenities and environment. Since from the general level of economic activity in that information on the variables which determine the city or increase in total city population. While dynamics of a spatial unit may not be available strong urbanization economies may lead to the we take population as a function of employabil- development of diversified large areas, localization ity, that is, how many persons the spatial unit can economies foster specialized metropolitan areas if employ. Further, to capture the type of employment these economies occur in combination with possi- we consider different categories of workers. bilities of inter-area trade. The unit of analysis within the city is the However, government action has mostly failed ward, the lowest spatial unit for which the cen- to recognize the merits of concentration, and this sus authorities collected data in 2001. In other has often led to suboptimal utilization of resources. words, the entire city of Delhi (Delhi Metropolitan Industrial location policies in India, which aim at Corporation) has been divided into 132 small spa- spreading industrial activities across space, can be tial units. And for each of these units the PPI summarized as follows: (1) policies encouraging is estimated by applying the statistical stochastic small-scale enterprises; (2) the industrial estates frontier function framework. The methodology is programme; (3) the rural industries project pro- same as that adopted by Mills and Mitra (1997) gramme; (4) metropolitan planning in the major for estimating the city-specific PPI. The concept states; and (5) incentives to promote industrial of stochastic function in this context essentially development in backward areas (Mohan 1993). suggests that there is a unique level of population However, the impact of specific industrial loca- associated with a given level of resource base. As tion or regional policies on the actual location of the resource base varies, so also the population industry has been quite limited, not only in India level. However, the observed level of population but also in various countries in the world (Mohan may lie much above the level of population that is 1993). And this is mainly because firms and work- explained by the available resource base. This dif- ers both have a tendency to locate in large cities ference between the actual level of population and with the hope that they would be better matched the level that is explained by the resource base is there (Helsley and Strange 1990). Besides, the rich indeed the population pressure. infrastructure endowment in the large cities attracts The next question is ‘What is the nearest proxy firms by enhancing their expectation to experience of resource base in a geographical unit?’ One may possible reduction in the cost of operation. The conceptualize it in terms of employment and infras- reliability of firms concerning delivery of products tructure. Since information on infrastructure is not also improves as large cities have better transport available at the level of disaggregation which we network and marketing facilities. These studies aim at capturing, only the employment variable has tend to indicate that large cities hold enormous been considered in the analysis. prospects for enhancing productivity and adding So let us say population base (P) is a function to competitiveness. However, in the process pos- of employment (E): sibilities may arise, which would tend to conflict with human welfare and the overall environment, P = F(E) shaping the basic crux of existence. We examine how population pressure that exists relative to economic opportunities affects certain 3. Methodology environmental state variables that have human wel- An expanding system with drivers, constituents and fare impacts. The PPI is an index of population structure changing as a consequence of economic, relative to the employment opportunities. We are International Journal of Urban Sustainable Development 173 thereby taking into account one of the ingredients 4. Empirical results of human welfare. In a log linear framework, population is taken By applying the statistical stochastic frontier to be a function of main workers (full-time function framework we can identify, based on the employment) in agriculture (MAGCULL), house- ward level data, the areas (within Delhi), which hold manufacturing (MHHMFG) and all other are closer to or much more than the level of pop- activities (MOTWORK) and total marginal or part- ulation that can be sustained by the employment time employment in all activities (MARGW). The opportunities available in a given geographical unit non-negative errors U s are assumed to follow a (ward). In the stochastic frontier model population half-normal distribution. error term is made up of statistical noise (V ) and a The equation has been estimated by maximum one-sided disturbance (U ) to allow for population likelihood (ML) method. pressure. The stochastic population frontier model Exp(U )s are retrieved to generate the PPI cor- is given by responding to each of the ward. Taking the ward with maximum population pressure as 100 the index values of the rest have been worked out. P = F (E ; β) exp (V + U ) i i i i Even when we assume the non-negative U shave an exponential or gamma distribution, the ranking of the indices does not change, implying that the E (i = 1, 2, . . ., n) is taken to represent employment estimates are robust. in various activities; β is the set of parameters. The Stochastic frontier model: ML estimates. aggregate employment may not capture the qual- ity aspect. Two spatial units with the same level In POP = 2.11 + 0.152 ln AGGCUL + 0.122 ln HHMFG of employment but with compositional differences may have different implications for population ∗ ∗ (11.21) (2.07) (8.01) growth. The frontier population is defined to be P = + 0.7524 ln OTHERWOR + 0.114 ln MARW F(E ; β) exp(V ). The ratio of observed population i i to the frontier population, if it is greater than 1, (30.95) (7.58) gives the extent to which actual population lies above the level that can be explained in terms of N = 132, Lambda = 2.06 Sigma = 11.81 the employability and the quality of employment: (2.49) (7.99) P V + U ∗ i i i Notes: Represents significance at 1% level; POP, PP = = F (E ; β) exp exp (V ) i i i P E ; β i population; AGGCUL, cultivators and agricul- tural workers; HHMFG, household manufacturing; = exp (U ) OTHERWOR, other workers; MARW, marginal workers. where PP is the PPI for each ward. This sort of an Based on the residuals the ward-specific esti- index is different from what we mean by population mates are obtained. Ward 8 corresponds to the density per square kilometre. The latter is measured maximum PPI. Taking this to be 100, the index simply as a ratio of population to area whereas the values for other wards are worked out accordingly. PPI is measured in relation to certain ingredients of Table 1 distributes the wards as per different size human welfare. Here, the quantum and the quality classes formed on the basis of PPI values (also see of employment in terms of composition are used to Figures 1 and 2). More than 80% of the wards cor- estimate the PPI. respond to an index value of less than 50 (Table 1), 174 V. Dayal et al. Table 1. Wards classified by population pressure potential to attract further investment and migra- index (PPI). tion since it can still offer productive avenues to investors and drivers. In a large part of Delhi, <10 98, 54, 88, 40, 97 possibilities of further growth exist though the More than 10–15 120, 38, 37, 81, 96, 86, 95, 22, 61, 49, 60 demographers will usually disagree. Delhi, being More than 15–20 42, 83, 30, 36, 70, 7, 39, 35, 102, the national capital, has always been the centre of 118, 82, 71, 84, 92, 104, 87, attraction for both public and private investment. 90, 43, 18, 116, 64, 62 In particular, policymakers have been concerned More than 20–25 6, 21, 89, 76, 93, 27, 100, 103, about its smooth functioning, which may explain 52, 34, 115, 123, 75, 28, 41, 105, 65 why Delhi has not reached the exhaustible limits. More than 25–30 26, 13, 68, 20, 17, 67, 59, 69, Because of the positive externalities, the drivers 101, 77, 3, 63, 109, 53, 29, 74, continue to undertake investment projects, as the 112, 33, 45, 16, 80 pressure index is not yet untenable. What we have More than 30–40 51, 106, 44, 4, 72, 14, 119, 133, observed is that in several areas within Delhi, the 55, 32, 31, 48, 127, 23, 58, 47, 78, 10, 15 population base has not reached the exhaustible More than 40–50 57, 94, 130, 117, 122, 5, 121, 11, limit. However, although the PPI from drivers’ 46, 111, 56, 99 point of view or the employability point of view More than 50–60 73, 91, 125, 19, 79, 24, 110, 9, has not reached the maximum limit, the quality of life or the well-being level manifested in terms of More than 60–70 25, 134, 132, 126, 12 >70 114, 108, 126, 129, 113, 66, 124, certain characteristics might be poor. 1, 131, 2, 8 Therefore, the next issue is the relationship between the pressure generated by the drivers and Source: Estimated from Census Data, 2001. the state of other variables, which tends to affect the environment. We examine the association between implying that a large majority of the spatial units in PPI and variables representing basic amenities. Delhi have not come close to the exhaustible lim- This exercise is conducted with respect to four its. In fact, around 40% of the wards are below basic amenities only. Each of these four amenities the index value of 25. In other words, Delhi con- captures impacts of PPI on ecosystems and human tinues to be attractive for employment opportu- well-being, thereby throwing light on population nities. Despite the enormous growth of activities pressure as a significant measure of urbanization, in last three decades, Delhi continues to have the ecosystem health and human well-being. 0 20 40 60 80 100 120 140 160 Ward Figure 1. Ward-specific population pressure index (PPI). Source: Based on Census Data, 2001. Population pressure index International Journal of Urban Sustainable Development 175 NDMC CANTT DNA Less than 15 PPI 15–25 PPI 25–40 PPI 40–60 PPI More than 60 PPI Figure 2. Municipal wards classified by population pressure index (PPI). Note: CANTT, cantonment; NDMC, New Delhi Metropolitan Corporation; DNA, data not available. The set of indicators used is very limited, but spatial unit to act as an attractor for more migra- these are chosen because (1) they are available at tion? There are HH without adequate supply of the ward level and (2) indicate both well-being drinking water in areas that correspond to a high through access to basic necessities and environ- PPI, presenting evidence directly in favour of the mental pressures. Access to SDW is a measure resilience framework (Table 2 and Figure 3). On the of human well-being through health; no latrine other hand, there are wards, which may correspond (NOLAT) and the presence of open drain or no to higher values of PPI but are not characterized drain imply that sewage water finds its way to water by higher percentage figures of HH without access bodies and rivers, thereby causing pollution; and to SDW. Several of the wards (114, 108, 114, 108, the use of fuel wood is likely to have a negative 128, 129, 113, 1, 131 and 8) have very high PPI, impact on forest ecosystems. but have almost 90% of HH able to access SDW. The question we are trying to answer through Overall, population pressure has not resulted in this spatial analysis of the wards of Delhi is ‘Does deterioration in well-being in certain areas due to a high PPI result in negative externalities on water policy intervention. On the other hand, wards like and forest ecosystems and human health?’ Is the 98, 54 and 97 show the least population pres- feedback on the PPI such as to reduce or increase sure and yet more than 60% of the HH in these its value, thereby affecting the tendency of the wards are not able to access SDW. These areas, in 176 V. Dayal et al. Table 2. Wards cross-classified by population pressure index (PPI) and percentage of households (HH) without access to safe drinking water (SDW). PPI Percentage of HH <10 10–15 15–20 20–25 25–30 30–40 40–50 50–60 60–70 >70 without access to SDW 1 23456789 10 1 <10% 88 120 42 6 26 106 130 24 25 114 81 39 27 13 4 122 9 132 108 96 118 100 20 14 121 107 126 128 22 71 115 17 119 12 129 61 87 123 77 32 113 18 28 3 31 1 116 41 109 127 131 62 105 29 23 8 112 78 33 15 2 10–20% 95 30 21 59 72 57 125 2 82 89 69 133 117 19 92 76 74 10 5 79 90 103 11 3 20–30% 40 35 75 0 55 56 73 134 124 84 110 4 30–40% 83 93 68 36 52 67 5 40–60% 37 70 101 51 94 91 66 86 104 53 44 60 43 48 6 60–80% 98 49 64 65 7 >80% 97 38 spite of low population pressure, have experienced habitation tends to spread to areas without adequate poor living conditions due to the lack of pol- infrastructure. icy initiative. Other than these exceptional cases, These findings tend to support the resilience there are areas (wards) where well-being level in framework – a rise in population pressure in certain terms of drinking water accessibility is quite poor pockets can lead to use of space in other pockets and the PPI is only moderate; they are indicative within the city, maintaining the city’s role as the of population spill over to areas which are unfit engine of growth. Since ‘city’ is a continuous spa- for human habitation. In the process of growth, tial unit, this kind of spill over is not uncommon. shortage of space is inevitable and thus human However, when it comes to the rural hinterland, International Journal of Urban Sustainable Development 177 NDMC CANTT DNA Less than 20 PPI & <30 SDW 20–40 PPI & <30 SDW >40 PPI & <30 SDW <20 PPI & >30 SDW 20–40 PPI & >30 SDW >40 PPI & >30 SDW Figure 3. Wards cross-classified by population pressure index (PPI) and percentage of households (HH) without access to safe drinking water (SDW). Note: CANTT, cantonment; NDMC, New Delhi Metropolitan Corporation; DNA, data not available. several administrative issues may hinder the city’s of the wards while in others there is no strong expansion. This sort of spill over would have association (Table 4 and Figure 5). Corresponding serious implications in terms of poor living con- to low quality fuel, which affects the environment ditions. Nevertheless, with policy initiatives pos- adversely, population pressure seems to have a pos- sibilities exist to correct these disorders. Either itive relationship (Table 5 and Figure 6). infrastructure can be supplied in these areas or Areas within the city not showing one-to-one these HH can be relocated in areas with adequate relationship between PPI and well-being indicators infrastructure through an efficient land acquisition indicate intra-city variations in terms of neigh- policy. bourhood amenities, land prices and affordabil- Similarly, population pressure and access to ity for different sections of the population. For latrine facility show considerable overlaps in many example, though the poor work in some of the areas (Table 3 and Figure 4) though there are wards, core activities contributing enormously to the city’s which do not unfold a linear relationship. Again, value addition, they may be compelled to reside the percentage of HH without drain or exposed in areas with water logging, inadequate sanita- to open drain and PPI show convergence in some tion and poor drinking water supply. Besides, there 178 V. Dayal et al. Table 3. Wards cross-classified by population pressure index (PPI) and percentage of households (HH) with no latrine (NOLAT). PPI Percentage of <10 10–15 15–20 20–25 25–30 30–40 40–50 50–60 60–70 >70 HH with NOLAT facility 1 2 3 4 5 6 7 8 9 10 1 <5% 98 81 71 76 20 48 94 54 96 90 93 59 23 130 88 95 18 52 77 78 111 28 109 2 5–10% 97 120 87 123 17 5 11 91 108 22 3 72 79 49 112 107 3 10–15% 38 7 27 13 51 57 24 129 118 65 29 44 122 12 113 35 74 47 121 33 46 4 15–20% 61 43 6 26 14 73 126 131 116 75 53 119 125 62 55 5 20–30% 37 30 89 69 127 5 19 128 86 102 100 101 15 56 24 8 60 82 34 80 9 92 115 6 30–50% 40 83 21 68 106 99 134 114 36 67 133 132 1 70 63 2 7 50–80% 39 103 58 117 110 66 84 105 124 8 >80% 42 41 are powerful groups within the city who influence pressure has not reached the exhaustible limits policymaking and the area-wise allocation of pub- in these areas though in terms of basic ameni- lic investment on basic amenities. Hence, the low- ties, as discussed above, they are far below the income housing colonies, slum clusters and slum satisfactory level. We infer that positive external- resettlement colonies may continue to have inad- ities do exist with regard to economic growth, equate basic amenities and poor neighbourhood and with policy initiatives, spatial units can con- conditions. In such localities, slum leaders negoti- tinue to be a major basin of attraction, implying ate with political parties for basic infrastructure in resilience, with major features of the system being return for votes (Edelman and Mitra 2005). unchanged. Investment in basic amenities can over- Overall, several areas (wards) within Delhi come the poor levels of well-being. While planning continue to be major attractors as population and deciding the allocation of these investments International Journal of Urban Sustainable Development 179 NDMC CANTT DNA Less than 25 PPI & <20 NOLAT 25–50 PPI & <20 NOLAT >50 PPI & <20 NOLAT >25 PPI & >20 NOLAT 25–50 PPI & >20 NOLAT >50 PPI & >20 NOLAT Figure 4. Wards cross-classified by population pressure index (PPI) and percentage of households (HH) with no latrine (NOLAT). Note: CANTT, cantonment; NDMC, New Delhi Metropolitan Corporation; DNA, data not available. at different locations, the needs of the population indicators, and resulting ecological disturbances, have to be kept in mind. Elite state commitment is may deteriorate further. Hence, continued higher necessary in this process. investment in basic infrastructure is needed, so Overall, with policy initiatives the external dis- that while drivers expand activities, the ecological economies may subside and may not reduce the responses do not become conflicting. possibility of new activities in the city. However, in response to further investment within the city and 5. Conclusions and policy implications better employment opportunities, migration may take place. Although this would ensure the contin- This article uses the DPSIR framework, suggest- ued advantages that the spatial unit may offer as ing that drivers lead to pressures of diverse kinds an engine of growth, with further in-migration of and a state having impacts on human health and the rural poor and low-income HH the well-being ecosystems, which finally lead to societal responses 180 V. Dayal et al. Table 4. Wards cross-classified by population pressure index (PPI) and percentage of households (HH) exposed to open drain or with no drain. Percentage of PPI HH exposed to <10 10–15 15–20 20–25 25–30 30–40 40–50 50–60 60–70 >70 open drain or withnodrain 1 23456789 10 1 <10% 18 28 20 4 121 107 108 109 23 111 129 2 10–20% 120 118 52 26 51 130 25 113 22 116 123 13 119 122 12 131 59 32 11 112 10 3 20–30% 30 6 14 5 125 126 8 62 27 127 19 15 79 4 30–40% 61 7 100 17 99 132 114 82 29 128 5 40–50% 54 35 21 69 133 1 115 80 6 50–70% 40 81 83 105 68 106 117 73 134 124 96 70 77 47 110 2 39 78 7 70–90% 88 95 36 76 67 44 57 91 49 92 103 101 72 56 60 104 34 63 55 87 75 53 48 64 65 8 >90% 98 38 42 89 58 94 66 97 37 102 93 86 84 41 of economic and environmental agents, and the We find considerable overlaps between popula- urban administration. The growth benefits from tion pressure and poor well-being levels. However, agglomeration economies are strong in a city econ- there are areas (wards) which show poor well-being omy like Delhi and thus it is best suited to the indicators though they have not reached the DPSIR framework. Using the statistical stochastic exhaustible limits in terms of the PPI. Perhaps, frontier function model we estimated the PPI at the this is because, in the broad context of economic ward level and then related this index to several growth that is concentrated in a couple of cen- well-being indicators in order to assess the impact tres, population tends to spill over to areas that of growth on overall ecosystems. are relatively poor in terms of neighbourhood International Journal of Urban Sustainable Development 181 NDMC CANTT DNA Less than 25 PPI & <40 DRAIN 25–30 PPI & < 40 DRAIN >50 PPI & <40 DRAIN >25 PPI & >40 DRAIN 25–50 PPI & >40 DRAIN >50 PPI & >40 DRAIN Figure 5. Wards cross-classified by population pressure index (PPI) and percentage of households (HH) exposed to open drain or with no drain. Note: CANTT, cantonment; NDMC, New Delhi Metropolitan Corporation; DNA, data not available. factors including basic amenities. Areas with rel- on a large scale, which in turn can improve the atively high population pressure and inadequacy of quality of life. basic amenities provide direct evidence about dete- With policy initiatives, well-being levels can rioration in the environmental conditions caused improve and the city may continue to grow and be a by the dynamics of growth and expansion. Lack major centre of employment. However, this would of space in livable areas leading to squatting on enhance the expectations of potential migrants and land not meant for human habitation is normal encourage an inflow of population. All this implies in Delhi. Demolition squads in the main city are continued investment on the infrastructure front; often accompanied by the rehabilitation of the else, significant ecological imbalances are likely low-income HH in areas that have not yet been to emerge. Public investment in infrastructure can developed for residential purposes. In such areas, attract the drivers in a significant way as new cen- investments in basic amenities have to be pursued tres of growth can emerge within the city. This 182 V. Dayal et al. Table 5. Wards cross-classified by population pressure index (PPI) and percentage of households (HH) using wood, kerosene andsoonfor fuel. PPI Percentage of HH <10 10–15 15–20 20–25 25–30 30–40 40–50 50–60 60–70 >70 using wood, keroseneandsoon 1 23456789 10 1 <10% 18 123 4 113 28 78 2 10–15% 81 118 13 23 130 79 25 108 82 71 20 121 129 3 15–20% 88 120 87 26 119 122 9 12 37 116 3 32 5 74 31 11 10 111 4 20–25% 54 96 30 6 29 14 46 107 95 7 76 112 48 61 35 27 16 62 80 5 25–30% 49 82 100 69 44 57 73 104 52 10 127 56 125 90 75 47 19 6 30–40% 42 115 68 51 94 24 132 114 70 41 67 72 126 8 102 65 109 133 7 40–60% 98 38 83 21 63 106 99 91 134 128 40 86 36 89 53 124 97 60 39 93 1 84 103 131 92 34 2 8 >60% 105 58 117 110 66 would release the pressure on land in areas that are framework, is that with certain corrective mea- about to reach the maximum limit. Such initiatives sures it is possible to reduce the adverse side would not only reduce intra-city growth disparities effects of growth on the urban ecosystem. With but also help maintain the urban ecosystem. appropriate spatial planning for investment, devel- Overall, the note of optimism that emerges opment of infrastructure and provision of basic from the analysis, conforming to the resilience amenities, the levels of well-being can improve International Journal of Urban Sustainable Development 183 NDMC CANTT DNA Less than 25 PPI & <30 FUEL 25–50 PPI & <30 FUEL >50 PPI & <30 FUEL >25 PPI & >30 FUEL 25–50 PPI & >30 FUEL >50 PPI & >30 FUEL Figure 6. Wards cross-classified by population pressure index (PPI) and percentage of households (HH) using wood, kerosene andsoonfor fuel. Note: CANTT, cantonment; NDMC, New Delhi Metropolitan Corporation; DNA, data not available. and Delhi may continue to be a major centre of Notes growth. 1. The socio-ecological subsystem or SES is defined as a system that includes societal (human) and ecological (biophysical) subsystems in mutual inter- Acknowledgements action (Gallopin 1991). The authors are highly obliged to Professor Kanchan 2. The term state variable means the variables that Chopra for her detailed comments. The comments of define the state of the system, that is, for an two anonymous referees of this journal have contributed agricultural socio-ecological system the variables significantly to the enrichment of the contents. The usual could be crops, livestock, farmers, roads and so on disclaimers apply. (Resilience Alliance 2007). 184 V. Dayal et al. Notes on contributors Kim S. 1989. Labour specialization and the extent of the market. J Polit Econ. 97:692–705. Vikram Dayal is an associate professor in Institute of Kim S. 1991. Heterogeneity of labour markets and city Economic Growth. His research is in the area of envi- size in an open spatial economy. Reg Sci Urban ronmental economics and he has published in journals Econ. 21:109–126. such as Environment and Development Economics and Klatte E. 1997. European Environment Agency. In: Ecological Economics. International Institute of for the Urban Environment, Preeti Kapuria is a PhD candidate in the University of editor. Advanced study course on indicators Delhi. She has worked in environmental economics. for sustainable urban development. Delft (The Netherlands): Nivo. Arup Mitra is a professor in Institute of Economic MacHarg IL. 1971. Design with nature. Garden City Growth. His research area includes urbanization, devel- (NY): Doubleday. opment economics, labour and welfare, industrialization Mills ES. 1967. An aggregate model of resource allo- and gender inequality. He has publications in journals cation in a metropolitan area. Am Econ Rev. 57: such as Urban Studies, Journal of Urban Economics, 197–210. Social Science Journal, Economic Development and Mills ES, Hamilton BW. 1994. Urban economics. 5th ed. Cultural Change and Development and Change. Glenview (IL): Scott Foresmen. Mills ES, Mitra A. 1997. Urban development and urban ills. New Delhi (India): Commonwealth Publishers. References Mohan R. 1993. Industrial location policies and their implications for India. Ministry of Industry, Office of [DoEF] Department of Environment and Forests. 2010. the Economic Adviser, Government of India. Paper State of environment report for Delhi, 2010. New No. 9. Delhi (India): Department of Environment and Pelling M, Manuel-Navarrete D. 2011. From resilience Forests, Government of National Capital Territory of to transformation: the adaptive cycle in two Delhi. Mexican urban centers. Ecol Soc. [Internet]; 16:11. Edelman B, Mitra A. 2005. Slum dwellers’ access to [cited 2011 Aug 1]. Available from: http://www. basic amenities: the role of political contact, its ecologyandsociety.org/vol16/iss2/art11/. determinants and adverse effects. Rev Urban Reg Pendall R, Foster KA, Cowell M. 2010. Resilience and Dev Stud. 18:25–40. regions: building understanding of the metaphor. Gallopin GC. 1991. Human dimensions of global Cambridge J Reg Econ Soc. 3(1):71–84. change: linking the global and the local processes. Planning Commission. 2009. Delhi development report. Int Soc Sci J. 130:707–718. New Delhi (India): Academic Foundation. Gallopin GC. 2006. Linkages between vulnerability, Resilience Alliance. 2007. Assessing resilience in social- resilience, and adaptive capacity. Glob Environ ecological systems: a workbook for scientists, ver- Change. 16:293–303. sion 1.1. Draft for Testing and Evaluation, June. Helsley RW, Strange WC. 1990. Matching and agglom- Rodenburg C, Baycan-Levent T, van Leeuwen E, eration economies in a system of cities. Reg Sci Nijkamp P. 2001. Urban economic indicators for Urban Econ. 20:189–212. green development in cities. GMI. [Internet]; Henderson JV. 1986. Efficiency of resource usage and 36(Winter):105–119. [cited 2011 Aug 1]. Available city size. J Urban Econ. 19:47–70. from: http://www.rolandpark.org/documents/Roden Hermansen T. 1972. Development poles and related the- berg_etal_03.pdf. ories: a synoptic review. In: Hansen NM, editor. Segal D. 1976. Are there returns of scale in city size. Rev Growth centers in regional economic development. Econ Stat. 58:338–350. New York (NY): The Free Press. p. 170–198. Simmie J, Martin R. 2010. The economic resilience Holling CS. 1973. Resilience and stability of ecological of regions: towards and evolutionary approach. systems. Annu Rev Ecol Syst. 4:1–23. Cambridge J Reg Econ Soc. 3(1):27–43. Jannson A, Polasky S. 2010. Quantifying biodiversity Walker B, Holling CS, Carpenter SR, Kinzig A. for building resilience for food security in urban 2004. Resilience, adaptability and transformability landscapes: getting down to business. Ecol Soc. in social–ecological systems. Ecol Soc. [Internet]; [Internet]; 15(3):20. [cited 2011 Aug 1]. Available 9(2):5. [cited 2011 Aug 1]. Available from: http:// from: http://www.ecologyandsociety.org/vol15/iss3/ www.ecologyandsociety.org/vol9/iss2/art5/. art20/. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Urban Sustainable Development Taylor & Francis

Population pressure and environment in the context of growth: evidence from an Indian city

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International Journal of Urban Sustainable Development Vol. 3, No. 2, November 2011, 168–184 Population pressure and environment in the context of growth: evidence from an Indian city a b a Vikram Dayal , Preeti Kapuria and Arup Mitra * a b Institute of Economic Growth, University of Delhi, Delhi 110007, India; Department of Business Economics, University of Delhi, Delhi 110007, India (Received 13 May 2011; final version received 8 August 2011) This article analyses the Indian city of Delhi using the contrasting concepts of resilience and agglomeration economies. Delhi is an expanding system that is changing because of economic, social and ecological driving forces. The driver–pressure–state–impact–response (DPSIR) framework is used in this article. We measure the extent of population pressure at the ward level [population pressure index (PPI)] by applying the statistical stochastic frontier function framework. We then examine the association between the PPI and the variables representing well-being and the overall ecosystem. There are overlaps between PPI and poor well-being indicators. However, some areas have a poor environmental state even though their population pressure is not at the frontier. This seems to have resulted from population growth spilling over to areas not fit for human habitation. Further migration of people in response to growth and employability may worsen the levels of well-being. However, appropriate interventions and investment in basic amenities can stop such severe welfare losses and help the city maintain its role as the engine of growth. Keywords: resilience; growth; city; basic amenities; ecology 1. Introduction to sustain nature. A testimony to this are the efforts made by urban planners to create urban spaces that The environmental scientists perceive an equilib- also incorporate elements from nature (Macharg rium relationship between the environment and the 1 1971). human habitation, which may get disturbed in the This article, using the concepts of resilience process of development and population growth. and agglomeration economies, aims at analysing Moreover, ‘cities are human-made artefacts, and an urban conglomeration such as Delhi, which are often opposed to nature’ (Rodenburg et al. is an expanding system with drivers, constituents 2001). Nature has many interrelated biotic and and structure changing as a consequence of eco- abiotic elements which act in unseen and intricate nomic, social and ecological driving forces. Delhi, ways. In cities, human engineering and infras- the capital of India, has grown rapidly. Its popu- tructure dominate. A road provides a contrast to a lation increased from about 6.2 million in 1981 forest – the road itself is devoid of any species. A to about 13.8 million in 2001, and was pro- city draws on resources from a vast hinterland – jected to increase to 23 million by 2021 (Planning water, food, fossil fuel – and discharges pollutants Commission 2009). According to Department of in air and water. Hence, special efforts are needed *Corresponding author. Email: arup@iegindia.org This article is based on research conducted as part of the ‘Urban Social-ecological and Globalization’ project supported by the Stockholm Resilience Centre, Stockholm, Sweden. ISSN 1946-3138 print/ISSN 1946-3146 online © 2011 Taylor & Francis http://dx.doi.org/10.1080/19463138.2011.613616 http://www.tandfonline.com International Journal of Urban Sustainable Development 169 Environment and Forests (DoEF 2010) the pop- not actually explode, stress may build up and in the ulation of Delhi was 18 million in 2010. There process of growth and expansion, a particular spa- was rapid, though fluctuating economic growth in tial unit may approach its maximum flexibility or the 2000s – for example, 9.8% in 2003/2004 and capacity to accommodate activities and population. 4.7% in 2002/2003 (Planning Commission 2009). Hence, there is a need to empirically assess the Per capita income rose by about 93% between pressure that may arise in a spatial unit in the pro- 2000/2001 and 2007/2008 (DoEF 2010). cess of growth, and the impact of this pressure This rapid growth created challenges in terms on the existing infrastructure and basic amenities, of provision of basic services and environmental which may in turn show deleterious effects on management. In the urban areas of Delhi, about human welfare and environment. 78% of households (HH) had access to piped water The resilience framework would suggest that supply in 2001, compared to about 48% of HH in with interventions, the capacity of the ecosystem the rural areas of Delhi. Sewerage coverage was to absorb and accommodate growth and its related inadequate, resulting in an estimated 200 million consequences can be sustained and a new equilib- litres of untreated sewage being dumped into the rium relationship can be reached in the long run. river Yamuna that flowed through the city (Planning Nevertheless, without effective policies the nega- Commission 2009). There are also inequities in tive externalities associated with growth can have access to basic services. For example, DoEF (2010) cascading effects on the environment–habitation reported that while some select areas in the city had relationship and thus may result in gross reductions a water supply as high as 450 litres per capita per in well-being measured from economic, social, day, the average for the city was 39 litres per capita health and environmental points of view. per day, and slums on the other hand got only 14 Even when the pressures are not strong, ecolog- litres per capita per day. ical imbalances can arise because of mismatches In the driver–pressure–state–impact–response between what ideally should be done and what (DPSIR) framework, a set of drivers (such as is actually done. For example, certain parts of activities, income, employability and population) the city are not fit for human habitation, and are lead to pressures and a state having impacts on meant to be under green cover. However, inade- human health and ecosystems, which finally lead quacy of space in the city centre and the laxity to societal responses of economic and environmen- of the administrators may lead to resettlement of tal agents, urban administration and so on (Klatte slums in such areas resulting in gross deterioration 1997; Rodenburg et al. 2001). However, from the in well-being levels and disturbances in the ecolog- economist’s perspective, there may not be a one- ical equilibrium. However, the resilience approach to-one relationship between drivers and pressure. would suggest that with interventions such distor- The concept of agglomeration economies tells us tions can again be corrected and the objective of that positive externalities may arise in the process growth can be pursued without really causing any of concentration (Mills 1967). In other words, due major ecological flaw. to the impacts created by several drivers concen- This article attempts to capture the growth tration of economic activities may arise leading pressures and their impact on certain well-being simultaneously to productivity growth. Some of indicators empirically in the context of a grow- this productivity growth and rise in profitability can ing city economy, Delhi. This article in Section 2 be invested to relax the constraints on resources. begins by discussing the literature on the concepts The positive externalities can outweigh the neg- of resilience and agglomeration economies. The ative ones to such an extent that the spatial unit may rest of this article is structured as follows. Section 3 continue to be a major basin of attraction, imply- discusses the methodology used to estimate the pop- ing it is resilient with major features of the system ulation pressure index (PPI) at the ward level within being unchanged. However, though the system may Delhi. With the help of this index we identify areas 170 V. Dayal et al. in Delhi which are closer to or below the maxi- Pendall et al. (2010) distinguish between mum population limit. Section 4 gives empirical shocks, for example, Hurricane Katrina, and ‘slow results of the model. We then relate these results burns’, for example, urban sprawl. In evaluating to broad indicators of well-being, related to basic human systems, there is an added complexity amenitiesandecologicalissues.Finally,inSection 5 because humans can look into the future, adapt and we summarize the main findings and bring out the change circumstances. They suggest that resilience implications for policy. The database of the study is is a fruitful concept, but researchers need to set drawn from the decennial population census, 2001. spatial and temporal boundaries to their enquiry. Total population, employment type, access to safe We now briefly consider three examples of drinking water (SDW), sanitation, sewage facility urban case studies that use the concept of and type of fuel used by HH for domestic consump- resilience. Simmie and Martin (2010) relate tion are some of the attributes that are compiled the evolution of the city region economies of from population census at the ward level, that is, at Cambridge and Swansea from 1960 to 2005 to a very disaggregated unit of the city. the adaptive cycle model. Cambridge went through the following phases: reorganization, exploita- 2. Existing literature on resilience and tion and conservation; whereas Swansea experi- agglomeration economies enced release, reorganization, exploitation, con- servation, release and then reorganization. Pelling This section draws on the contrasting concepts of and Manuel-Navarrete (2011) also use the adap- resilience and agglomeration economies. tive cycle to discuss developments in the two Mexican towns of Mahahual and Playa del Carmen. 2.1. Resilience However, their aim is to study the role of power in Each discipline defines a term according to its the adaptive cycle model. requirements and perspectives. The term resilience In contrast to the previous two qualitative stud- is no exception. As Gallopin (2006) points out, ies, Janson and Polasky (2010) quantify biodi- evolutionary biology, ecology and cultural studies versity for building resilience for food security have defined it in different ways with different foci in the urban landscape of Stockholm County in and different meanings. In the context of socio- Sweden. According to Jannson and Polasky (2010), ecological subsystems, resilience can be defined ‘Compelling theoretical knowledge about essen- as a measure of persistence of systems and their tial connections between ecosystem generation, ability to absorb change and disturbance and still biodiversity and resilience in social-ecological sys- maintain the same relationships between popula- tems already exists; however, we still, to a great tions and state variables (Holling 1973). It is extent, lack spatially explicit quantitative assess- the capacity of a system to absorb disturbance ments for translating this theoretical knowledge and reorganize while undergoing change to retain into practice’. Jannson and Polasky (2010) show essentially the same function, structure, identity that although the flow of an ecosystem service may and feedbacks – in other words, stay in the same not fall, the underlying biodiversity and resilience basin of attraction (Walker et al. 2004). could be adversely affected. Pendall et al. (2010) also reviewed the In the context of our study, at times the benefits resilience literature in several fields: of growth are so substantial that the stakehold- ‘Some literature describes resilience as a return ers deliberately ignore ecological costs. Gradually, to conditions before a shock. Other resilience adverse repercussions are felt in the long run, and writing embraces a complex systems perspective. even economic growth may be affected. In such a For other fields, resilience describes the ability situation, resilience theory would suggest a note of people, regions or ecosystems to thrive despite of optimism – with corrective measures, it would adversity’. be possible to reduce the adverse impact. In other International Journal of Urban Sustainable Development 171 words, we have used the term resilience in this though higher productivity levels in larger urban study to reveal the robustness of a system in a spe- settlements could also be an outcome of higher cific spatial context, which may impinge on human technology levels (Segal 1976). welfare and the overall environment in the pro- Concentration of economic activities occurs cess of expansion. It is possible to regain the basic mainly to reap advantages of externalities aris- properties of the system through effective policy ing from indivisibilities in the production process interventions. such as interdependence of industries in terms of input–output linkages, ancillarization, market- 2.2. Agglomeration economies ing of products and availability of infrastructural The literature on agglomeration economies sug- facilities. The development pole theory explains gests that some industries induce concentration of how other groups of industries tend to form clus- economic activity as they exhibit high economies ters around a core of industries, which have a of scale in operation, and others benefit from con- high capacity to transmit growth impulses through centration because of the operation of agglomera- both backward and forward linkages. Such clus- tion economies. Concentration not only strength- ters are said to form industrial complexes with the ens the forward and backward linkages, but also following advantages (see Hermansen 1972): (1) reduces the cost of operation by developing com- substantial economies of investment expenditure – plementary services. The effective price of infras- the investment for the whole complex is less than tructure services like power, water supply, roads the sum of investment for each enterprise planned and so on gets reduced if there is concentration of and located in isolation; (2) efficient production users of these services. In all, interdependence of due to advantages of specialization, economies of industries in terms of input–output linkages, ancil- large-scale operation and organization of common larization and availability of infrastructure con- managerial and infrastructural facilities; (3) pos- tribute to the growth of agglomeration economies. sibility of jointly exploiting the natural and raw In addition, with a large population base in the material resources of the area of location; and area in which firms are located, it is less likely that (4) opportunities for close contact, rapid diffu- a glut in the commodity market or a high labour sion of technological innovations and rapid overall turnover cost would occur. As Mills and Hamilton development of the economy. (1994) point out, labour requirements in a partic- The external economies, in general, can be ular industry are subject to random, uncorrelated, divided into two categories: (1) urbanization seasonal or cyclical fluctuations. Hence, an urban economies and (2) localization economies. These area with more industries generates a higher level economies are different from the internal scale of employment than can be achieved with indus- economies, which are returns to internal scale char- tries spread out in separate urban areas. Higher acterizing the technology of the individual firm, levels of urbanization mean a large overall labour regardless of its location. Localization economies market and a large service sector interacting with are external to the firm but internal to the indus- manufacturing. Further, it has been argued that try and, as Henderson (1986) describes, reflect (1) average productivity increases with the size of the economies of intra-industry specialization where labour market, as average match between the skill greater industry size permits greater specialization characteristics of workers and the job requirements among firms in their detailed functions; (2) labour of firms improves with an increase in the size of the market economies where industry size reduces labour market (Kim 1991). In addition, specializa- search costs for firms looking for workers with spe- tion of labour is related positively to the size of the cific training relevant to that industry; (3) scale of labour market, as workers in large labour markets communication among firms affecting the speed tend to invest in more specialized human capital, in of adoption of new innovations; and (4) scale turn resulting in productivity growth (Kim 1989), in providing public intermediate inputs tailored 172 V. Dayal et al. to the technical needs of a particular industry. social and ecological driving forces can lead to The urbanization economies, on the other hand, expansion in population which generates pressure are external to both firm and industry, and result on the existing amenities and environment. Since from the general level of economic activity in that information on the variables which determine the city or increase in total city population. While dynamics of a spatial unit may not be available strong urbanization economies may lead to the we take population as a function of employabil- development of diversified large areas, localization ity, that is, how many persons the spatial unit can economies foster specialized metropolitan areas if employ. Further, to capture the type of employment these economies occur in combination with possi- we consider different categories of workers. bilities of inter-area trade. The unit of analysis within the city is the However, government action has mostly failed ward, the lowest spatial unit for which the cen- to recognize the merits of concentration, and this sus authorities collected data in 2001. In other has often led to suboptimal utilization of resources. words, the entire city of Delhi (Delhi Metropolitan Industrial location policies in India, which aim at Corporation) has been divided into 132 small spa- spreading industrial activities across space, can be tial units. And for each of these units the PPI summarized as follows: (1) policies encouraging is estimated by applying the statistical stochastic small-scale enterprises; (2) the industrial estates frontier function framework. The methodology is programme; (3) the rural industries project pro- same as that adopted by Mills and Mitra (1997) gramme; (4) metropolitan planning in the major for estimating the city-specific PPI. The concept states; and (5) incentives to promote industrial of stochastic function in this context essentially development in backward areas (Mohan 1993). suggests that there is a unique level of population However, the impact of specific industrial loca- associated with a given level of resource base. As tion or regional policies on the actual location of the resource base varies, so also the population industry has been quite limited, not only in India level. However, the observed level of population but also in various countries in the world (Mohan may lie much above the level of population that is 1993). And this is mainly because firms and work- explained by the available resource base. This dif- ers both have a tendency to locate in large cities ference between the actual level of population and with the hope that they would be better matched the level that is explained by the resource base is there (Helsley and Strange 1990). Besides, the rich indeed the population pressure. infrastructure endowment in the large cities attracts The next question is ‘What is the nearest proxy firms by enhancing their expectation to experience of resource base in a geographical unit?’ One may possible reduction in the cost of operation. The conceptualize it in terms of employment and infras- reliability of firms concerning delivery of products tructure. Since information on infrastructure is not also improves as large cities have better transport available at the level of disaggregation which we network and marketing facilities. These studies aim at capturing, only the employment variable has tend to indicate that large cities hold enormous been considered in the analysis. prospects for enhancing productivity and adding So let us say population base (P) is a function to competitiveness. However, in the process pos- of employment (E): sibilities may arise, which would tend to conflict with human welfare and the overall environment, P = F(E) shaping the basic crux of existence. We examine how population pressure that exists relative to economic opportunities affects certain 3. Methodology environmental state variables that have human wel- An expanding system with drivers, constituents and fare impacts. The PPI is an index of population structure changing as a consequence of economic, relative to the employment opportunities. We are International Journal of Urban Sustainable Development 173 thereby taking into account one of the ingredients 4. Empirical results of human welfare. In a log linear framework, population is taken By applying the statistical stochastic frontier to be a function of main workers (full-time function framework we can identify, based on the employment) in agriculture (MAGCULL), house- ward level data, the areas (within Delhi), which hold manufacturing (MHHMFG) and all other are closer to or much more than the level of pop- activities (MOTWORK) and total marginal or part- ulation that can be sustained by the employment time employment in all activities (MARGW). The opportunities available in a given geographical unit non-negative errors U s are assumed to follow a (ward). In the stochastic frontier model population half-normal distribution. error term is made up of statistical noise (V ) and a The equation has been estimated by maximum one-sided disturbance (U ) to allow for population likelihood (ML) method. pressure. The stochastic population frontier model Exp(U )s are retrieved to generate the PPI cor- is given by responding to each of the ward. Taking the ward with maximum population pressure as 100 the index values of the rest have been worked out. P = F (E ; β) exp (V + U ) i i i i Even when we assume the non-negative U shave an exponential or gamma distribution, the ranking of the indices does not change, implying that the E (i = 1, 2, . . ., n) is taken to represent employment estimates are robust. in various activities; β is the set of parameters. The Stochastic frontier model: ML estimates. aggregate employment may not capture the qual- ity aspect. Two spatial units with the same level In POP = 2.11 + 0.152 ln AGGCUL + 0.122 ln HHMFG of employment but with compositional differences may have different implications for population ∗ ∗ (11.21) (2.07) (8.01) growth. The frontier population is defined to be P = + 0.7524 ln OTHERWOR + 0.114 ln MARW F(E ; β) exp(V ). The ratio of observed population i i to the frontier population, if it is greater than 1, (30.95) (7.58) gives the extent to which actual population lies above the level that can be explained in terms of N = 132, Lambda = 2.06 Sigma = 11.81 the employability and the quality of employment: (2.49) (7.99) P V + U ∗ i i i Notes: Represents significance at 1% level; POP, PP = = F (E ; β) exp exp (V ) i i i P E ; β i population; AGGCUL, cultivators and agricul- tural workers; HHMFG, household manufacturing; = exp (U ) OTHERWOR, other workers; MARW, marginal workers. where PP is the PPI for each ward. This sort of an Based on the residuals the ward-specific esti- index is different from what we mean by population mates are obtained. Ward 8 corresponds to the density per square kilometre. The latter is measured maximum PPI. Taking this to be 100, the index simply as a ratio of population to area whereas the values for other wards are worked out accordingly. PPI is measured in relation to certain ingredients of Table 1 distributes the wards as per different size human welfare. Here, the quantum and the quality classes formed on the basis of PPI values (also see of employment in terms of composition are used to Figures 1 and 2). More than 80% of the wards cor- estimate the PPI. respond to an index value of less than 50 (Table 1), 174 V. Dayal et al. Table 1. Wards classified by population pressure potential to attract further investment and migra- index (PPI). tion since it can still offer productive avenues to investors and drivers. In a large part of Delhi, <10 98, 54, 88, 40, 97 possibilities of further growth exist though the More than 10–15 120, 38, 37, 81, 96, 86, 95, 22, 61, 49, 60 demographers will usually disagree. Delhi, being More than 15–20 42, 83, 30, 36, 70, 7, 39, 35, 102, the national capital, has always been the centre of 118, 82, 71, 84, 92, 104, 87, attraction for both public and private investment. 90, 43, 18, 116, 64, 62 In particular, policymakers have been concerned More than 20–25 6, 21, 89, 76, 93, 27, 100, 103, about its smooth functioning, which may explain 52, 34, 115, 123, 75, 28, 41, 105, 65 why Delhi has not reached the exhaustible limits. More than 25–30 26, 13, 68, 20, 17, 67, 59, 69, Because of the positive externalities, the drivers 101, 77, 3, 63, 109, 53, 29, 74, continue to undertake investment projects, as the 112, 33, 45, 16, 80 pressure index is not yet untenable. What we have More than 30–40 51, 106, 44, 4, 72, 14, 119, 133, observed is that in several areas within Delhi, the 55, 32, 31, 48, 127, 23, 58, 47, 78, 10, 15 population base has not reached the exhaustible More than 40–50 57, 94, 130, 117, 122, 5, 121, 11, limit. However, although the PPI from drivers’ 46, 111, 56, 99 point of view or the employability point of view More than 50–60 73, 91, 125, 19, 79, 24, 110, 9, has not reached the maximum limit, the quality of life or the well-being level manifested in terms of More than 60–70 25, 134, 132, 126, 12 >70 114, 108, 126, 129, 113, 66, 124, certain characteristics might be poor. 1, 131, 2, 8 Therefore, the next issue is the relationship between the pressure generated by the drivers and Source: Estimated from Census Data, 2001. the state of other variables, which tends to affect the environment. We examine the association between implying that a large majority of the spatial units in PPI and variables representing basic amenities. Delhi have not come close to the exhaustible lim- This exercise is conducted with respect to four its. In fact, around 40% of the wards are below basic amenities only. Each of these four amenities the index value of 25. In other words, Delhi con- captures impacts of PPI on ecosystems and human tinues to be attractive for employment opportu- well-being, thereby throwing light on population nities. Despite the enormous growth of activities pressure as a significant measure of urbanization, in last three decades, Delhi continues to have the ecosystem health and human well-being. 0 20 40 60 80 100 120 140 160 Ward Figure 1. Ward-specific population pressure index (PPI). Source: Based on Census Data, 2001. Population pressure index International Journal of Urban Sustainable Development 175 NDMC CANTT DNA Less than 15 PPI 15–25 PPI 25–40 PPI 40–60 PPI More than 60 PPI Figure 2. Municipal wards classified by population pressure index (PPI). Note: CANTT, cantonment; NDMC, New Delhi Metropolitan Corporation; DNA, data not available. The set of indicators used is very limited, but spatial unit to act as an attractor for more migra- these are chosen because (1) they are available at tion? There are HH without adequate supply of the ward level and (2) indicate both well-being drinking water in areas that correspond to a high through access to basic necessities and environ- PPI, presenting evidence directly in favour of the mental pressures. Access to SDW is a measure resilience framework (Table 2 and Figure 3). On the of human well-being through health; no latrine other hand, there are wards, which may correspond (NOLAT) and the presence of open drain or no to higher values of PPI but are not characterized drain imply that sewage water finds its way to water by higher percentage figures of HH without access bodies and rivers, thereby causing pollution; and to SDW. Several of the wards (114, 108, 114, 108, the use of fuel wood is likely to have a negative 128, 129, 113, 1, 131 and 8) have very high PPI, impact on forest ecosystems. but have almost 90% of HH able to access SDW. The question we are trying to answer through Overall, population pressure has not resulted in this spatial analysis of the wards of Delhi is ‘Does deterioration in well-being in certain areas due to a high PPI result in negative externalities on water policy intervention. On the other hand, wards like and forest ecosystems and human health?’ Is the 98, 54 and 97 show the least population pres- feedback on the PPI such as to reduce or increase sure and yet more than 60% of the HH in these its value, thereby affecting the tendency of the wards are not able to access SDW. These areas, in 176 V. Dayal et al. Table 2. Wards cross-classified by population pressure index (PPI) and percentage of households (HH) without access to safe drinking water (SDW). PPI Percentage of HH <10 10–15 15–20 20–25 25–30 30–40 40–50 50–60 60–70 >70 without access to SDW 1 23456789 10 1 <10% 88 120 42 6 26 106 130 24 25 114 81 39 27 13 4 122 9 132 108 96 118 100 20 14 121 107 126 128 22 71 115 17 119 12 129 61 87 123 77 32 113 18 28 3 31 1 116 41 109 127 131 62 105 29 23 8 112 78 33 15 2 10–20% 95 30 21 59 72 57 125 2 82 89 69 133 117 19 92 76 74 10 5 79 90 103 11 3 20–30% 40 35 75 0 55 56 73 134 124 84 110 4 30–40% 83 93 68 36 52 67 5 40–60% 37 70 101 51 94 91 66 86 104 53 44 60 43 48 6 60–80% 98 49 64 65 7 >80% 97 38 spite of low population pressure, have experienced habitation tends to spread to areas without adequate poor living conditions due to the lack of pol- infrastructure. icy initiative. Other than these exceptional cases, These findings tend to support the resilience there are areas (wards) where well-being level in framework – a rise in population pressure in certain terms of drinking water accessibility is quite poor pockets can lead to use of space in other pockets and the PPI is only moderate; they are indicative within the city, maintaining the city’s role as the of population spill over to areas which are unfit engine of growth. Since ‘city’ is a continuous spa- for human habitation. In the process of growth, tial unit, this kind of spill over is not uncommon. shortage of space is inevitable and thus human However, when it comes to the rural hinterland, International Journal of Urban Sustainable Development 177 NDMC CANTT DNA Less than 20 PPI & <30 SDW 20–40 PPI & <30 SDW >40 PPI & <30 SDW <20 PPI & >30 SDW 20–40 PPI & >30 SDW >40 PPI & >30 SDW Figure 3. Wards cross-classified by population pressure index (PPI) and percentage of households (HH) without access to safe drinking water (SDW). Note: CANTT, cantonment; NDMC, New Delhi Metropolitan Corporation; DNA, data not available. several administrative issues may hinder the city’s of the wards while in others there is no strong expansion. This sort of spill over would have association (Table 4 and Figure 5). Corresponding serious implications in terms of poor living con- to low quality fuel, which affects the environment ditions. Nevertheless, with policy initiatives pos- adversely, population pressure seems to have a pos- sibilities exist to correct these disorders. Either itive relationship (Table 5 and Figure 6). infrastructure can be supplied in these areas or Areas within the city not showing one-to-one these HH can be relocated in areas with adequate relationship between PPI and well-being indicators infrastructure through an efficient land acquisition indicate intra-city variations in terms of neigh- policy. bourhood amenities, land prices and affordabil- Similarly, population pressure and access to ity for different sections of the population. For latrine facility show considerable overlaps in many example, though the poor work in some of the areas (Table 3 and Figure 4) though there are wards, core activities contributing enormously to the city’s which do not unfold a linear relationship. Again, value addition, they may be compelled to reside the percentage of HH without drain or exposed in areas with water logging, inadequate sanita- to open drain and PPI show convergence in some tion and poor drinking water supply. Besides, there 178 V. Dayal et al. Table 3. Wards cross-classified by population pressure index (PPI) and percentage of households (HH) with no latrine (NOLAT). PPI Percentage of <10 10–15 15–20 20–25 25–30 30–40 40–50 50–60 60–70 >70 HH with NOLAT facility 1 2 3 4 5 6 7 8 9 10 1 <5% 98 81 71 76 20 48 94 54 96 90 93 59 23 130 88 95 18 52 77 78 111 28 109 2 5–10% 97 120 87 123 17 5 11 91 108 22 3 72 79 49 112 107 3 10–15% 38 7 27 13 51 57 24 129 118 65 29 44 122 12 113 35 74 47 121 33 46 4 15–20% 61 43 6 26 14 73 126 131 116 75 53 119 125 62 55 5 20–30% 37 30 89 69 127 5 19 128 86 102 100 101 15 56 24 8 60 82 34 80 9 92 115 6 30–50% 40 83 21 68 106 99 134 114 36 67 133 132 1 70 63 2 7 50–80% 39 103 58 117 110 66 84 105 124 8 >80% 42 41 are powerful groups within the city who influence pressure has not reached the exhaustible limits policymaking and the area-wise allocation of pub- in these areas though in terms of basic ameni- lic investment on basic amenities. Hence, the low- ties, as discussed above, they are far below the income housing colonies, slum clusters and slum satisfactory level. We infer that positive external- resettlement colonies may continue to have inad- ities do exist with regard to economic growth, equate basic amenities and poor neighbourhood and with policy initiatives, spatial units can con- conditions. In such localities, slum leaders negoti- tinue to be a major basin of attraction, implying ate with political parties for basic infrastructure in resilience, with major features of the system being return for votes (Edelman and Mitra 2005). unchanged. Investment in basic amenities can over- Overall, several areas (wards) within Delhi come the poor levels of well-being. While planning continue to be major attractors as population and deciding the allocation of these investments International Journal of Urban Sustainable Development 179 NDMC CANTT DNA Less than 25 PPI & <20 NOLAT 25–50 PPI & <20 NOLAT >50 PPI & <20 NOLAT >25 PPI & >20 NOLAT 25–50 PPI & >20 NOLAT >50 PPI & >20 NOLAT Figure 4. Wards cross-classified by population pressure index (PPI) and percentage of households (HH) with no latrine (NOLAT). Note: CANTT, cantonment; NDMC, New Delhi Metropolitan Corporation; DNA, data not available. at different locations, the needs of the population indicators, and resulting ecological disturbances, have to be kept in mind. Elite state commitment is may deteriorate further. Hence, continued higher necessary in this process. investment in basic infrastructure is needed, so Overall, with policy initiatives the external dis- that while drivers expand activities, the ecological economies may subside and may not reduce the responses do not become conflicting. possibility of new activities in the city. However, in response to further investment within the city and 5. Conclusions and policy implications better employment opportunities, migration may take place. Although this would ensure the contin- This article uses the DPSIR framework, suggest- ued advantages that the spatial unit may offer as ing that drivers lead to pressures of diverse kinds an engine of growth, with further in-migration of and a state having impacts on human health and the rural poor and low-income HH the well-being ecosystems, which finally lead to societal responses 180 V. Dayal et al. Table 4. Wards cross-classified by population pressure index (PPI) and percentage of households (HH) exposed to open drain or with no drain. Percentage of PPI HH exposed to <10 10–15 15–20 20–25 25–30 30–40 40–50 50–60 60–70 >70 open drain or withnodrain 1 23456789 10 1 <10% 18 28 20 4 121 107 108 109 23 111 129 2 10–20% 120 118 52 26 51 130 25 113 22 116 123 13 119 122 12 131 59 32 11 112 10 3 20–30% 30 6 14 5 125 126 8 62 27 127 19 15 79 4 30–40% 61 7 100 17 99 132 114 82 29 128 5 40–50% 54 35 21 69 133 1 115 80 6 50–70% 40 81 83 105 68 106 117 73 134 124 96 70 77 47 110 2 39 78 7 70–90% 88 95 36 76 67 44 57 91 49 92 103 101 72 56 60 104 34 63 55 87 75 53 48 64 65 8 >90% 98 38 42 89 58 94 66 97 37 102 93 86 84 41 of economic and environmental agents, and the We find considerable overlaps between popula- urban administration. The growth benefits from tion pressure and poor well-being levels. However, agglomeration economies are strong in a city econ- there are areas (wards) which show poor well-being omy like Delhi and thus it is best suited to the indicators though they have not reached the DPSIR framework. Using the statistical stochastic exhaustible limits in terms of the PPI. Perhaps, frontier function model we estimated the PPI at the this is because, in the broad context of economic ward level and then related this index to several growth that is concentrated in a couple of cen- well-being indicators in order to assess the impact tres, population tends to spill over to areas that of growth on overall ecosystems. are relatively poor in terms of neighbourhood International Journal of Urban Sustainable Development 181 NDMC CANTT DNA Less than 25 PPI & <40 DRAIN 25–30 PPI & < 40 DRAIN >50 PPI & <40 DRAIN >25 PPI & >40 DRAIN 25–50 PPI & >40 DRAIN >50 PPI & >40 DRAIN Figure 5. Wards cross-classified by population pressure index (PPI) and percentage of households (HH) exposed to open drain or with no drain. Note: CANTT, cantonment; NDMC, New Delhi Metropolitan Corporation; DNA, data not available. factors including basic amenities. Areas with rel- on a large scale, which in turn can improve the atively high population pressure and inadequacy of quality of life. basic amenities provide direct evidence about dete- With policy initiatives, well-being levels can rioration in the environmental conditions caused improve and the city may continue to grow and be a by the dynamics of growth and expansion. Lack major centre of employment. However, this would of space in livable areas leading to squatting on enhance the expectations of potential migrants and land not meant for human habitation is normal encourage an inflow of population. All this implies in Delhi. Demolition squads in the main city are continued investment on the infrastructure front; often accompanied by the rehabilitation of the else, significant ecological imbalances are likely low-income HH in areas that have not yet been to emerge. Public investment in infrastructure can developed for residential purposes. In such areas, attract the drivers in a significant way as new cen- investments in basic amenities have to be pursued tres of growth can emerge within the city. This 182 V. Dayal et al. Table 5. Wards cross-classified by population pressure index (PPI) and percentage of households (HH) using wood, kerosene andsoonfor fuel. PPI Percentage of HH <10 10–15 15–20 20–25 25–30 30–40 40–50 50–60 60–70 >70 using wood, keroseneandsoon 1 23456789 10 1 <10% 18 123 4 113 28 78 2 10–15% 81 118 13 23 130 79 25 108 82 71 20 121 129 3 15–20% 88 120 87 26 119 122 9 12 37 116 3 32 5 74 31 11 10 111 4 20–25% 54 96 30 6 29 14 46 107 95 7 76 112 48 61 35 27 16 62 80 5 25–30% 49 82 100 69 44 57 73 104 52 10 127 56 125 90 75 47 19 6 30–40% 42 115 68 51 94 24 132 114 70 41 67 72 126 8 102 65 109 133 7 40–60% 98 38 83 21 63 106 99 91 134 128 40 86 36 89 53 124 97 60 39 93 1 84 103 131 92 34 2 8 >60% 105 58 117 110 66 would release the pressure on land in areas that are framework, is that with certain corrective mea- about to reach the maximum limit. Such initiatives sures it is possible to reduce the adverse side would not only reduce intra-city growth disparities effects of growth on the urban ecosystem. With but also help maintain the urban ecosystem. appropriate spatial planning for investment, devel- Overall, the note of optimism that emerges opment of infrastructure and provision of basic from the analysis, conforming to the resilience amenities, the levels of well-being can improve International Journal of Urban Sustainable Development 183 NDMC CANTT DNA Less than 25 PPI & <30 FUEL 25–50 PPI & <30 FUEL >50 PPI & <30 FUEL >25 PPI & >30 FUEL 25–50 PPI & >30 FUEL >50 PPI & >30 FUEL Figure 6. Wards cross-classified by population pressure index (PPI) and percentage of households (HH) using wood, kerosene andsoonfor fuel. Note: CANTT, cantonment; NDMC, New Delhi Metropolitan Corporation; DNA, data not available. and Delhi may continue to be a major centre of Notes growth. 1. The socio-ecological subsystem or SES is defined as a system that includes societal (human) and ecological (biophysical) subsystems in mutual inter- Acknowledgements action (Gallopin 1991). The authors are highly obliged to Professor Kanchan 2. The term state variable means the variables that Chopra for her detailed comments. The comments of define the state of the system, that is, for an two anonymous referees of this journal have contributed agricultural socio-ecological system the variables significantly to the enrichment of the contents. The usual could be crops, livestock, farmers, roads and so on disclaimers apply. (Resilience Alliance 2007). 184 V. Dayal et al. Notes on contributors Kim S. 1989. Labour specialization and the extent of the market. J Polit Econ. 97:692–705. Vikram Dayal is an associate professor in Institute of Kim S. 1991. Heterogeneity of labour markets and city Economic Growth. His research is in the area of envi- size in an open spatial economy. Reg Sci Urban ronmental economics and he has published in journals Econ. 21:109–126. such as Environment and Development Economics and Klatte E. 1997. European Environment Agency. In: Ecological Economics. International Institute of for the Urban Environment, Preeti Kapuria is a PhD candidate in the University of editor. Advanced study course on indicators Delhi. She has worked in environmental economics. for sustainable urban development. Delft (The Netherlands): Nivo. Arup Mitra is a professor in Institute of Economic MacHarg IL. 1971. Design with nature. Garden City Growth. His research area includes urbanization, devel- (NY): Doubleday. opment economics, labour and welfare, industrialization Mills ES. 1967. An aggregate model of resource allo- and gender inequality. He has publications in journals cation in a metropolitan area. Am Econ Rev. 57: such as Urban Studies, Journal of Urban Economics, 197–210. Social Science Journal, Economic Development and Mills ES, Hamilton BW. 1994. Urban economics. 5th ed. Cultural Change and Development and Change. Glenview (IL): Scott Foresmen. Mills ES, Mitra A. 1997. Urban development and urban ills. 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Journal

International Journal of Urban Sustainable Development – Taylor & Francis

Published: Nov 1, 2011

Keywords: resilience; growth; city; basic amenities; ecology

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