Urbanization in development economics literature is expected to bring in a spectrum of social and economic transformations. In the backdrop of this understanding, the volume on the one hand focuses on various aspects of urbanization in India and on the other, analyses its impact on different socio-economic variables. Urbanization envisaged as a process in a developing-country context is then able to decipher a wide variety of positive changes which are occurring, though mildly. On the flip side, the rigidity of the social system is also on display, which possibly can be mitigated through significant interventions in addition to the rapid changes in some of the economic variables. The policy implications of evidence-based research are unfolded at the end of each of the chapters.

The volume begins with an analytical frame encompassing various factors that not only lead to urbanization but also unequal urbanization in particular. As per the received theory on urbanization, particularly in the conceptualization of modern economic growth by Kuznets (1966), industrialization per se is the driver. The ‘overurbanization’ thesis of Hoselitz (1953), on the other hand, looked at the urban phenomenon in the absence of adequate industrialization and opportunities for the rural population to shift to productive activities while agriculture pushed them out from the rural areas. The transfer of rural poverty to the urban space with the urban informal sector being the outlet for a residual absorption of labour stands central to this argument. However, with large-scale labour-intensive industrialization, the mobility of population is seen to be accompanied by a reduction in poverty as Lewis (1954) and Kuznets (1966) both had envisaged. Thus, the entire evolution of development was centring round the growth of factory. Since then the urban changes have taken place on a massive scale and the drivers of urban growth have deviated significantly from the traditional conceptualization. The growth of the services sector, international trade, infrastructural hubs, and, more importantly, even activities without much scope for labour-intensive methods have played a strategic role in the urbanization process, highlighting the mutual reinforcements between urbanization and economic development. As Hardt and Negri (2009) suggested, the contemporary metropolis has become a locus of socio-political mobilization analogous to the role of the factory during the initial phases of industrial epoch.

The analysis developed over the preceding six chapters offers a reading of radical monetary change in the wake of the liberalisation of money and markets. In Pakistan's new economy, the rupee and the everyday prices that express its usefulness are characterised by instability. Certainly, this is not the extreme instability of hyperinflation. But it is an instability substantive enough to prompt a series of hedging practices, which effectively contest the primacy of the rupee by dispersing money functions across an array of alternative assets. By using nonstate money instruments for money functions, households seek to protect themselves from new rupee-related risk in an economic environment that is characterised by uncertainty.

This story of the loss of trust in money amidst the instability and uncertainty generated by open markets finds a natural home within Post-Keynesian thinking. After all, these issues express key Post-Keynesian themes, such as the contingency of money on social trust and the fundamental uncertainty that drives the imperative of stabilisation policies. Yet this reading of monetary change in Pakistan's new economy runs counter to certain key Post-Keynesian contributions to economic thinking. Specifically, the theoretical lineage of Post-Keynesian monetary thinking sets out a dichotomy between money and commodities that does not easily account for the kind of monetary change that has been observed in Pakistan.

At issue is the state theory of money that underlies much thinking about money. From a state theory perspective, money cannot be an ordinary market commodity because it is a social construction that is indelibly linked to the state. Be it the ‘bank money’ that is issued by the state-supervised banking system or the notes, coins and central bank balances issued directly by the state, conventional thinking about money posits money by definition as a ‘creature of the state’ (Lerner, 1947). From a state theory perspective, the uniqueness of money amidst other assets lies herein: its defining characteristics are ascribed to the authority of the state under which it is issued.

To the contrary, this study has shown how the cornerstone role of the rupee as safe and stable can be compromised, and how certain uses of some commodities (primarily but not exclusively grain and cattle), can in fact be conceived of as commodity money.

On 14 November 2009, Fruit of the Loom (FOTL), the world's largest producer of T-shirts to the US market and the largest private sector employer in Honduras (Doh and Dahan 2010; Anner 2013), announced that it would reopen its garment factory Jerzees de Honduras (JDH), under the name Jerzees Nuevo Dia (JND), or ‘New Day’. They had capitulated almost entirely to the demands of the union and international activists. The final deal, negotiated between FOTL workers and executives, included rehiring of 1,200 employees, a multi-million dollar payout to workers, and a commitment to extend union neutrality and access across its Honduran supply chain.

This is the story of a garment factory that was shut down by its owner in response to unionization, as so often happens. But in this case it is also the story of how FOTL, the factory's TNC owner, suddenly reversed course and, in so doing, fundamentally altered how it approached labour relations. The embattled union drive overcame retaliatory sacking, death threats, and a nine-month factory shutdown, while keeping up morale and high participation to win an impressive package of wages and benefits and create the political space for a new wave of labour organizing in Honduras and abroad.

The garment and footwear sectors are not monolithic, of course, and evolve in different and uneven ways, with a great deal of intra-sectoral variety. Previous chapters outlined how the particularities of garment and footwear production – fashion trends, seasonality, and so on – are made for highly fragmented, labour-intensive, and low-value industries. The top-heavy power balance in these value chains allowed buyers to exert persistent downward pressure on suppliers, who were less and less capable of capturing enough value to upgrade. And that pressure, like all downward market pressures, ultimately fell on workers, whose wages were further squeezed by employers with nothing more to give.

Since the production process depends on what is being produced, seasonality and fashion kept the garment and footwear GVC low-tech and vertically disintegrated, while the least seasonal and fashion-sensitive are the most valorized and vertically integrated. By way of illustration, my case studies focus on a few of the least seasonal and fashion sensitive products in the sector: jeans, casual shoes, and sports shoes; and this chapter's focus is on cotton T-shirts and undergarments.

Introduction

The manufacturing sector has traditionally been the main theatre of technological progress. This sector constantly upgrades the existing products and creates new ones that are, unlike agricultural products, demanded more and more, apparently without a limit, as income rises. That is the amazing ability of the capitalist civilization to enlarge the sphere of its needs indefinitely. Yet, as per national product data of a typical modern economy, the manufacturing sector gradually gets eclipsed by service production. This has stirred the interest of many an observer. A simple hypothesis of differential productivity growth across sectors with competitive factor rewards, elaborated in the previous chapter, leads to the conclusion that the relatively technologically non-progressive activities, which are typically to be found more in the service sector than in manufacturing, will experience above average cost and price increases paving the way for increase in value added faster than output. The reverse narrative holds for the more progressive sectors, particularly for manufacturing. This idea has being churned ever since it was propounded though much has changed on the technological front with revolution in information technology that has kept the service sector on the boil in recent times (Triplett and Bosworth, 2003).

We have indicated in the last chapter that the Indian economy shows strong evidence of changes consistent with the above observations. It is of natural interest to ask, precisely how relevant the cost (and value added) adjustment have been in the context of stagnant relative GDP share of the manufacturing sector and rapidly rising share of services since the turn of the 1970s. The present discussion takes lead from the last chapter to obtain more specific answers to the question of GVA adjustments.

Restraining the Leviathan, Part 1: The central political hierarchy restrains the predatory use of violence.

Introduction

In the run-up to the 2011 Census in Nagaland, the government released several advertisements that framed the exercise in moral terms. One of the posters showed a Naga idol exhorting people to give correct responses to census questions with the following words: ‘My future must be built on the truth – Correct Census means strong future!’ (Figure 7.1). Politicians (Rio 2010b: 108; 2011: 73–4), civil society leaders (interviews, 24 November 2012 and 8 April 2013, Dimapur; see also CPO & Ors. vs. UoI & Ors. 2006), bureaucrats (Naga IAS officer, interview, 25 June 2013, Kohima) and church leaders (speeches, Clean Election Campaign, 19 September 2012, Hotel Japfu, Kohima) viewed the manipulation of government statistics as a reflection of individual and collective moral failings and used words such as ‘honesty’, ‘greed’, ‘integrity’ and ‘shame’ to describe the problem. The chief minister argued that the government was helpless in absence of ‘a conscious social decision based on moral values and ethical grounds’ (Rio 2010b: 108). He invoked Naga-Christian values and appealed to all concerned:

Introduction

The literature on the strategy of economic development initiated by Hirschman (1958) can be viewed as the primary inspiration for attempts to measure the pattern of industrial interlinkage. Hirschman advocated unbalanced growth to incentivize investment into areas served by strong demand or supply linkages, in the absence of serious structural rigidities like shortages, bottlenecks, low elasticities of demand and supply, and so on. The underlying assumptions were encouragement to private enterprise and responsiveness to market signals. Interindustry linkages have been studied with the objective of identifying pivotal industries in the sense of those having strong interrelations with other industries by way of being a key source of either demand for their products or supply of crucial intermediate inputs for production. Such industries, with maximum potential for being a spur to the system, are central for industrial development through their demand and supply interrelations. The present chapter is an exercise in the applicability of input–output based linkage measures in an analysis of interdependence in the Indian economic structure. Though the chapter follows linkage specifications within the Hirschman- Rasmussen tradition, it ventures into the supply-side model proposed by Ghosh (1958) for what is supposed to be a better measure of forward linkage.

In the next section, we discuss the intricacies of the relations between output on the one hand and final demand or value added on the other. The discussion helps explain interrelations that do not show up on the surface to final users, paving the way for classification of backward and forward linkages. The next section defines the concepts of linkages based on Leontief and Ghosh inverse matrices while the estimates of the linkage indices are presented in the appendix to the chapter. The subsequent section concludes the chapter by arranging the different sectors of the Indian economy according to the linkage intensities, by identifying the key sectors. The conclusion brings to sharp focus the justification of our division of services into two separate parts – Service-I and Service-II in the entire discourse.

Introduction

Input–output transactions tables (IOTTs) provide a very convenient tool to understand an economy's sectoral interconnections. It provides both the production and the expenditure sides of the economy in a compact form and is a very practical way of presenting national accounts that must show a balance between the two sides for conceptual accuracy. We had a glimpse of the importance of this balance for economic analysis in the previous chapters and we will continue to exploit the interindustry relations in the rest of the book. However, since our experience concerns a multidimensional reality, capturing it in single or in two dimensions inevitably means a constrained view; but that serves to show how constrained we are.

What readily comes to mind is adding a time dimension to the two dimensional picture presented by the IOTTs. Just as a three dimensional object is sought to be understood by taking multiple slices – what can be thought of as two dimensional – of the object, we seek to understand an economy over time using multiple IOTTs at, more or less, regular intervals of time. While an IOTT may be viewed as a snapshot of the economy, it really represents an interval – a year, collapsed to a single point. In computing the input (or technical) coefficients we divide the specific input required to obtain a quantity of output over a year, by the output quantity. Thus we compute the average, and in this sense, representative coefficient for the year. One seeks to visualize a rule that explains movement from one observation to the next. Since reality is extremely complex, specification of a simple rule seems silly but its utility lies in generating an insight. In a simple dynamic analysis one may add a time dimension with a rule in the form of a fixed parameter, say, a uniform rate of growth of a variable per year to see its impact on some other variable under focus.

Introduction

A few states/union territories of India reported a decrease in population immediately after decolonisation. The 1941 Census of India overestimated the population of Punjab and Bengal, the two provinces of British India that were directly affected by partition in 1947. In these provinces communities tried to boost their numbers to secure greater political representation and, eventually, a favourable alignment of borders in the event of partition. The overcount was corrected in 1951, resulting in the contraction of the reported population (GoI 1954a: 5; Natarajan 1972: vii). While the coverage error (error in the overall headcount) was corrected in 1951, content error (error in the sub-classification of headcount) persisted in Punjab. The 1951 Census data on language were affected by communal competition in Punjab, the Patiala and East Punjab States Union (PEPSU) and Himachal Pradesh. Two union territories, the Andaman and Nicobar Islands (1941–51) and Daman and Diu (1951–61), also reported negative growth rates in the decade of decolonisation. Nagaland's experience is quite different though.

Nagaland registered the highest growth in population across India between 1981 and 2001 (Figures 4.1A and 4.2). However, in 2011, it reported the lowest growth rate as its population contracted in the absence of epidemical disease, famine, natural calamity, war and any major change in its political status and socio-economic conditions. This was the first time that a state in independent India experienced a contraction in population. This chapter examines Nagaland's demographic somersault – decades of unusually high growth of the reported population followed by its sudden contraction (Figure 4.1B).

Errors in a census can be classified into two broad categories, namely, coverage and content errors. Coverage error ‘refers to either an under‐count or over‐count of units owing to omissions of persons/housing units or duplication/ erroneous inclusion, respectively’, whereas content error ‘pertains to the error in the characteristics that are reported for the persons or housing units that are enumerated’ (UN Secretariate 2010: 10). Content errors affect the distributional accuracy of the headcount, whereas coverage errors affect the accuracy of the overall headcount. Errors in census may not necessarily affect the overall headcount if they are restricted to the composition of population.

Introduction

Sustained and rapid growth of GDP with a steadily declining share of agriculture and a stagnant share of manufacturing inevitably draws one's attention to the service sector. Our discussion in Chapter 3 has shown that given the state of development of the Indian economy in 1981, the performance of the service sector, when judged by gross value added (GVA), was quite below the average by the yardstick of the global development experience. However, the sector subsequently performed well so that in the course of the next two decades it surpassed the K-CT norm1 by far to become an outlier, and thereafter further strengthened its position as a super-performer in 2011. Just the reverse is true of the industry sector by the same yardstick. The manufacturing sector, which is supposed to be the mainstay of industry, did not show a spur; the rising trend of the past decades of its relative share flattened out after the turn of the 1970s. By the global standard, the sector’s performance judged by GVA was far below the norm insomuch as it qualified as an underperforming outlier in 2001 and almost so in 2011. This has been the case in spite of all product market reforms, discussed earlier, aimed at boosting the sector. Since manufacturing ability is a reflection of the stock of productive knowledge amassed by a country, the apparent stagnancy in manufacturing has caused some dismay and serious reflection. In this backdrop, the rapid growth of the economy has been judged to have been made possible by the impressive growth of the service sector; the observation is statistically incontrovertible.

But what were the services that grew and what were the more dynamic components of the sector? A fundamental question is about the relevance of gross value added (GVA) as a measure of the level of activity in a sector. Value added is a monetary measure and it has a lot to do with the movement of relative prices, which may be caused by either the demand side or the supply side.

Introduction

Though in his book Kuznets (1966) had considered fifteen characteristics to define modern economic growth he later compressed them into the now famous six characteristics, falling into three main groups: (1) aggregate growth (a. high rates of increase in per capita product, accompanied by substantial rats of population growth and b. high rates of increase in output per unit of all inputs), (2) structural transformation (c. a high degree of structural transformation, encompassing a shift from agriculture to industry and services and d. changes in the structure of society and its ideology, including urbanization and secularization), and (3) international spread (e. opening up of international communications and f. a growing gap between developed and underdeveloped nations). Quite clearly he envisaged social changes alongside economic transformations. More specifically, urbanization and modernization of thoughts and ideology are seen as concomitant phenomena. The functioning of the rural labour market may be largely caste-based, but that is expected to get faint in the urban job market (Mitra, 2006). In other words, urbanization follows and results in commercialization, which in turn is likely to erode the influence of the caste factor in the job market although the job seekers may access information pertaining to the urban labour market on the basis of caste and kinship bonds (Banerjee, 1986; Desai, 1984; Mitra, 2003). From this point of view it becomes pertinent to assess if the caste factor which remained deep-rooted in the Indian social system for centuries started subsiding after the economic growth and development started off in the post-Independence era. In this chapter we try to examine if within the universe of the low-income households (slums) the caste factor matters or all social categories are equally vulnerable.

Many argued that the disadvantaged (social) classes usually get uprooted from the rural areas and strive hard in an alien urban situation to access livelihood sources (Singh and D’Souza, 1980). However, in an anonymous urban space the caste factor is usually expected to get blurred and, hence, caste-based occupations which might have been pursued in the rural setup prior to migration may change significantly, implying availability of jobs in the urban labour market being independent of caste. Similarly non-availability of jobs may also cut across castes.