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2020 | Book

Accelerators of India's Growth—Industry, Trade and Employment

Festschrift in Honor of Bishwanath Goldar

Editors: Prof. Suresh Chand Aggarwal, Dr. Deb Kusum Das, Dr. Rashmi Banga

Publisher: Springer Singapore

Book Series : India Studies in Business and Economics

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About this book

This book offers a collection of distinguished contributions that identify current growth accelerators in India, and suggest policies and strategies to make India’s growth more sustainable and inclusive. The papers are divided into three sections, the first of which focuses on issues related to industrial growth in India. The discussions include India’s industrial development (manufacturing, construction and mining); role of manufacturing; global value chains; and of environment in industrial development. In turn, section II deals with issues related to trade and FDI as accelerators of India’s growth. The respective chapters explore the changing patterns of trade, impacts of technology, and spill-over effects of FDI, to name but a few. Lastly, the third section discusses employment-related issues like measurement of labour input, the dichotomy of the Indian labour market, the nature of firms and employment generation, and impacts of technology on employment. Given its scope and focus, the book offers an invaluable resource for researchers and policymakers alike.

Table of Contents

Frontmatter

India’s Industrial Growth: Opportunities and Challenges

Frontmatter
Paradigm Changes in Technology and Employment
Abstract
The paper starts with the Schumpeterian concept of creative destruction resulting in turmoil consequent to paradigm shifts in technology. Unlike trajectory changes in technology, paradigm changes are not incremental changes and they could destroy and replace the existing technologies and products. The turmoil is because workers trained in one technological paradigm cannot easily shift to new technologies. New industries would be created but at the same time, several older industries would face destruction. The paper argues that while employment in the Sunset industries would decline the overall employment in the economy need not decline. There would be gainers and victims. Section 2 of the paper discusses the likely gainers and victims of the current technological revolution, namely, digital and genomics revolution. The paper shows that the middle-income group would be more affected than the rest. It argues that computers cannot perform abstract tasks and professionals and persons performing personal services will not be adversely affected. Furthermore, currently collaborative efforts are assuming importance and they need human interactions and cannot be handled by machines. Section 3 discusses the rapid increase in the introduction of robots in manufacturing in the Asian countries led by China. Currently, they are mainly in a few sectors like automobiles, plastics and electronic products. In the future, they are also likely to play a role in garments and textiles. In this context, if one uses ‘occupational’ approach one gets on set of results while if one uses the ‘task based’ approach one gets a more balanced picture. Robots cannot be introduced in all the tasks in these few sectors. There are only a limited number of tasks where robots could be introduced and they turn out to be tasks that are inhospitable for human labour and that require precision. Here again gains outweigh the losses. However, to effectively participate and benefit from the knowledge revolution it is important to concentrate on improving the skill content of the population and spend heavily on education and retraining of the workforce. The ongoing digital and genomics revolutions are knowledge based and knowledge intensive wherein human capital plays a crucial role. Technology and knowledge transfer through foreign direct investments will work only in the presence of highly skilled workforce. In the case of India, the states that enjoyed better human capital in terms of education and health enjoyed higher growth rates of employment and productivity. States that neglected human capital did not experience employment growth. They are the victims of the knowledge revolution and to avoid further decline and the consequent adverse consequences they should go in for a crash programme aimed at human resource development. These issues are discussed in Sect. 4 Information Technology and digitalization facilitates networking and encourages global manufacturing by reducing transaction costs. In the globalized world, different segments in the production chain could be split and undertaken in different countries based on efficiency of production. This could be achieved either through licensing or FDI depending on the transaction costs involved in technology transfers and production transfers. This practice has now become a political and electoral issue in the developed countries. Outward FDI is accused of creating employment in other countries and declining employment in the home country. By and large, empirical studies do not support the concerns of these policymakers of developed countries about the adverse impact of outward FDI to other countries and in particular to low-wage countries. Section 5 examines these issues. Section 6 is devoted to the shape of the things to come. This section is based on the vision of the scientists as expressed in the science journal Nature. By and large, scientists are more positive about the ongoing digital revolution and argue that unemployment fears are exaggerated. Their main argument is that current research and international business involve collaborations across countries and face-to-face interaction in the work units. Participation in the global production network would involve frequent interactions and collaborations by different teams. Machines are not good in carrying out processes where collaborations and interactions are important. However, workforce needs to be retrained. In the future world, people need to collaborate and need to know each other better. Standalone solo workers would disappear. Section 7 deals with opportunities for India and discusses likely advantages India would have when the quantum computers are introduced in future, opening opportunities for participation in hardware and software. It also analyses opportunities that could emerge in solar energy in particular when products like quantum dots and paper-thin solar cells are introduced in the future.
N. S. Siddharthan
India’s Manufacturing Story: Productivity and Employment
Abstract
Services have been the driver of India’s overall growth since the onset of economic reforms in India and particularly beginning the 2000s. However, India’s manufacturing sector continues to draw attention despite several decades of reforms covering industrial policies and trade liberalization. The government through its several initiatives—National Manufacturing Policy as well as ‘Make in India’ program—continues to drive the sectors role in the overall growth and development. The sector is targeted to contribute around 25% of GDP by 2025 as against its current 16% share. In the recent past, Indian manufacturing has attained a sharp rise in growth and this augurs well for a sector that has seen stagnancy in its share of GDP in the last several decades. The lack of jobs in organized manufacturing has so far failed India’s industrial objectives and add to that is the large number of people employed in informal manufacturing activities as well has remained a perennial challenge to development needs. The productivity performance of manufacturing industries has been well documented and continues to exhibit low productivity growth. A recent study by Das et al. (The World Economy: Growth or Stagnation? Cambridge University Press, Cambridge, pp. 199–233, 2016) however finds labour-intensive manufacturing outperforming non-labour-intensive goods during the period 2000–15 and this is important when we have evidence of declining labour intensity even in labour-intensive manufacturing (Sen and Das in Economic and Political Weekly 50(23):108–115, 2015). Several challenges remain if productivity is to be improved. Most critics would point to the labour market rigidities for the inefficiency in the manufacturing sector, but there remains several issues beyond simple labour market reforms that need to be addressed—particularly those related to skill formation and its impact of labour quality. The present study would cover the manufacturing industries for the period 2000–2015 in an attempt to understand the productivity dynamics in manufacturing sector and its relation to employment. Using a neoclassical growth accounting technique and the India KLEMS dataset, we would examine the manufacturing performance both at the aggregate-level as well as 13 disaggregated industries and present an industry-level perspective on manufacturing performance. The period of study would also take into account the several phases of the Indian economy including pre-global slowdown, slowdown and recovery phase. The study would address some of the possible determinants of manufacturing performance which need attention if the stagnancy of manufacturing share in overall GDP is to be reversed.
Pilu Chandra Das, Deb Kusum Das
An Analysis of Global Value Chain Incomes in Indian Industries
Abstract
The importance of using measures of global value chains to understand the participation of countries in global trade has increased in recent years, as the fragmentation of production accelerated globally. This paper provides estimates of foreign content in domestic production in Indian industries, Indian content in the production of global industries, and the reliance of income generated in Indian industries on foreign demand. In general, India’s participation in GVC is relatively lower than in many other countries, yet it is improving. We find that the expansion of India’s manufacturing, and to some extent, market services sectors increase demand for output from upstream sectors in foreign countries that produce intermediate inputs used in the downstream sectors in India. We also see that Indian content is relatively the highest in global textile production, but its contribution to India’s GDP by means of value chain income is not the highest and has declined over the years. We also provide some initial evidence that the relationship between India’s participation in the GVC and sectoral productivity level is positive, which suggests the importance of intensifying India’s participation in the GVC.
Abdul A. Erumban
The Political Economy of the Allocation of State Government Expenditures for the Industrial Sector
Abstract
We investigate why some governments do not institute public policy conducive to industrialization from the viewpoint of the balance of political power between the agricultural and industrial sectors. More specifically, we examine whether a higher rural Gini coefficient—a proxy for the degree of political power of rural elites—tends to reduce the allocation of development expenditures favorable to the industrial sector at the state level in India. Our estimation results suggest that both the rural Gini coefficient and the rural population share have significant negative coefficients. These results imply that the political influence of the agricultural sector can limit the allocation of expenditures conducive to industrialization, resulting in the stagnation of regional state economies.
Atsushi Kato, Atsushi Fukumi
Environment and Economic Development: An Analysis of Electricity Demand Projections for India
Abstract
Increase in electricity use widens economic opportunity to the population, improves social infrastructure, and increases productivity. In this study, we examine the relationship between economic growth and electricity consumption, and make projections of electricity demand based on evidence from international experience. Electricity consumption for high-income countries is 8834.3 Kwh per capita in 2014, while low- and middle-income countries on an average consume 1922.1 Kwh per capita electricity. India’s total (and per capita) electricity consumption is very low as compared to many high-income and transition economies. The study estimates the year in which India is expected to shift from lower middle-income economy category to upper middle-income economy category, and subsequently to high-income economy category, under three scenarios: pessimistic, BAU, and optimistic scenario. Results show that even under an optimistic scenario, India’s per capita electricity consumption is likely to be lower than the current average electricity consumption of high-income countries (7980 Kwh) when it crosses its high-income level, i.e., in 2038 under optimistic scenario. The study further discusses the policy reforms that have been initiated to enable a significant shift in the overall operations of the electricity sector and promoted energy efficiency, leading to an expansion in the infrastructure sector at a relatively lower environmental cost in the recent past and the way forward.
Purnamita Dasgupta, Chetana Chaudhuri

Role of Trade and FDI as India’s Growth Accelerators: Opportunities and Challenges

Frontmatter
India’s Merchandise Exports in a Comparative Asian Perspective
Abstract
As part of a major economic reform program aimed at improving external competitiveness, India’s trade and exchange rate policies were liberalized and restructured since the early 1990s. The major reforms included (i) exchange rate reforms to remove anti-export bias, (ii) trade liberalization to induce resource allocation along the lines of comparative advantage, and (iii) liberalization of inward foreign direct investment (FDI). How did Indian exports respond to changes in the incentive structure engendered by the reforms and what are the emerging issues? This paper highlights some key empirical results and stylized facts pertaining to India’s merchandise (goods) exports. While India’s merchandise exports in dollar terms grew moderately at about 8.1% per year during the first decade of economic reforms (1993-2001), the second decade of reforms (2002-2011) stands apart for its strong growth rate of 21.3% per annum. Data for the more recent years, however, indicate that the value of exports plummeted from a peak of US$323 billion in 2014 to US$299 billion in 2017 with a negative annual growth rate of 1.9% per annum. Further, throughout the post-reform period, India’s imports have grown faster than exports resulting in increasing trade deficits in the merchandise account. Needless to say, the long-term solution to the problem of unsustainable current account deficit lies in ensuring that export growth keeps pace with import growth. The crucial question is: what type of policy interventions would help achieve faster export growth?. The answer, taking a cue from some recent studies, hinges on whether export performance is primarily driven by growth at the extensive margin (new trading relationships) or at the intensive margin (increase in trade of existing relationships). The intensive margin of a country’s export growth is attributable to its persistent export relationships—that is, exports of already exported products (old products) to already existing market destination for those products (old markets). Note that intensive margin growth can arise as a result of price growth, quantity growth, or both. The extensive margin refers to changes in the value of exports due to diversification of old products to new market destinations and/or due to the exports of new products. What has been the relative contribution of extensive and intensive margins to India’s export growth during the recent past? How does India’s performance compare with that of China? We argue that China’s high degree of specilisation in labour-intensive industries/product lines and its high export market penetration in traditional richer partner countries (particularly high income OECD countries) hold the key in understanding its superior export performance. India, by contrast, due to an idiosyncratic pattern of specialization in capital- and skill-intensive activities, has failed to exploit its export potential in high-income countries. The composition of Indian exports shows an anomaly in that, despite being a labor-abundant country, the fast growing exports from India are either skilled labor-intensive or capital-intensive. While the share of capital-intensive products increased consistently from about 32% in 2000 to nearly 53% in 2015, the share of unskilled labor-intensive products declined from about 30% to 17%. This type of specialization is an anomaly in a country like India with large pools of unskilled labor. Due to its idiosyncratic specialization, India has been locked out of the vertically integrated global supply chains in several manufacturing industries. It is almost tautological to state that export growth that is driven by capital- and skill-intensive industries cannot be sustained in a capital scarce but labor-abundant economy. The disproportionate bias of its export composition toward capital-and skill-intensive products has provided India with a comparative advantage in relatively poorer regions (such as Africa) but at the cost of losing market shares in the richer countries. Products from India with high technology and skill content are unlikely to make inroads into the quality conscious richer country markets. These products, however, enjoy a competitive advantage in the relatively poorer countries. At the same time, rich country markets provide a huge potential for labor-intensive exports from developing countries such as India. Thus, specialization out of traditional labor-intensive products implies a general loss of India’s export potential in advanced country markets. In the past, high-income OECD countries accounted for a major share of India’s export basket. However, their dominance has declined considerably over the last two decades. The aggregate share of these markets in India’s merchandise exports decreased from 58.2% in 1992 to 38.6% in 2015. On the other hand, India’s market share in low- and middle-income countries increased steadily from 18.4% in 1992 to 35.8% in 2015. For China, the share of high-income OECD countries increased sharply from 37.7% in 1992 to 62% in 2000 and then declined to 47.5% in 2015. China’s export market penetration in high-income OECD countries, despite some decline in the last decade, remains significantly higher than that of India. Contrary to the general perception, there exists a significant potential for India to expand and intensify its export relationships with the traditional developed country partners. However, this would necessitate greater participation in global value chains and a realignment of India’s specialization on the basis of its true comparative advantage in labor-intensive production processes and product lines.
C. Veeramani, Lakshmi Aerath
Digitalization and India’s Losing Export Competitiveness
Abstract
The digital revolution is rapidly transforming global manufacturing and trade, thereby altering export competitiveness of developing countries. This paper examines the impact of growing digitalization on India’s exports, using both sector- and firm-level analyses. At the sectoral level, the paper estimates the value added by digital services in India’s exports and compares it to its competitor countries, using Leontief’s decomposition and input–output data from the World Input-Output Dataset. At the firm level, the paper empirically estimates the impact of increasing digital assets on export intensity of Indian manufacturing firms in period 2000–2015, using panel data methodologies of system GMM and random effects Tobit. Results indicate that the value added by digital services in manufacturing exports of India is much lower than in other developing countries. A closer examination reveals that most of the value added by digital services is contributed to India’s exports of computer programming and telecommunication services, which together account for 88% of total value added contributed by DS to total exports. India is found to be losing competitiveness in some key traditional sectors, including tea, spices, clothing and leather, which are found to be less digitalised compared to other sectors. Firm-level empirical results confirm the important role of digitalization as driver of export competitiveness in Indian manufacturing firms. System GMM and Tobit results reveal that as the share of digital assets in overall plant and machinery increases in a firm, its export intensity rises and other things constant. There is thus a need for targeted policies and strategies for increasing digitalization of India’s exportable sectors, particularly of traditional exports like textiles and clothing and leather and leather products as these sectors generate large-scale employment for low-skilled workers.
Rashmi Banga, Karishma Banga
Firm-Level Productivity and Exports: The Case of Manufacturing Sector in India
Abstract
This study differentiates total factor productivity (TFP) between the exporting and non-exporting firms in manufacturing sector of India. We use data from the Centre for Monitoring Indian Economy (CMIE) from 2003 to 2015. For a better understanding of the productivity distribution, we create two subgroups of sample based on firm age and size. Moving away from parametric tests this study adopts non-parametric statistics in testing the hypothesis. Productivity levels are found to be higher for the exporting firms as compared to the non-exporting firm. Further, within the exporting firms, those with larger firm size have higher productivity compared to the smaller firms.
K. Narayanan, Santosh Kumar Sahu
FDI and Export Spillovers: A Case Study of India
Abstract
Using a panel dataset on Indian manufacturing firms from 1994 to 2010, the present study examines the export spillover effects from FDI on Indian manufacturing firms. FDI and its impact on Indian firms have drawn considerable attention during last two decades due to the surge of FDI in India since 2000s. Previous studies have shown that India did not seem to draw any positive benefit from FDI in terms of productivity. However, the impact of FDI spillovers on export performance is relatively less explored. Theory says that export performance of firms is highly influenced by the diffusion of information, knowledge and technology brought by the foreign firms. These above-mentioned channels are referred as information spillovers, competition spillovers, imitation spillovers and skill spillovers which are various channels of horizontal spillovers that influence export performance. Competition, imitation and skill spillovers are called induced export spillover effects as they promote export performance of the domestic firms by improving productivity. A study by Antras and Helpman (2004) argues that the highest productive firms are firms which serve the international market, while the lowest productive firms stay in the domestic market. On the other hand, information spillover induces export performance by reducing the sunk cost associated export activities keeping productivity intact. In this paper, we specifically focus on the horizontal export spillover channels. A very early study by Kumar and Siddharthan (1994) did not find any significant difference in export activities of domestic and foreign firms during the restrictive policy regime. However, recent studies, for example, Joseph and Reddy (2009), Franco and Sasidharan (2010) have shown a significant positive impact of FDI on export performance of the Indian firms. While Joseph and Reddy (2009) took into account both horizontal and vertical export spillover channels, Franco and Sasidharan (2010) is a detailed study of horizontal export spillover channels and their impact on export performance of Indian manufacturing firms. The study showed that the firms with higher R&D capability are in general more benefitted from FDI spillovers as compared to non-R&D firms. The present study is divided into two parts: in the first part, we focus on the FDI spillover effects on the export performance of the domestic firms. While we mention “export performance” of the firms, we refer to two activities: first, whether the decision of the non-exporter firms change and second, how export propensity of the self-selected exporting firms gets influenced by foreign activities. Thus, for the econometric analysis, we use Heckman selection (2 Step) method where the firms self-select themselves as exporters. Our study brings out interesting results. The study does not find any significant positive impact from foreign firms’ domestic activities or export activities unlike previous studies (Franco and Sasidharan 2010). The “export-platform” theory mentioned in Ruane and Sutherland (2005) seems to be prevalent in the case of Indian manufacturing sector. Export activity of the foreign firms not only reduces the export propensity of the domestic firms, it also hinders the decision of the non-export domestic firms to become exporters. Competition spillovers from foreign firms, measured in terms of their domestic sales, show a significant negative impact on the export propensity of the domestic firms. In fact, we find negative impact of skill spillovers on the domestic export activities. Domestic R&D activities by foreign firms remain insignificant throughout. With these results one question followed, is this outcome mainly driven by the initial periods of liberalisation? As spillover theory says, domestic firms take few years to adjust to the new environment and during that period, domestic firms evolve themselves to take advantages from foreign activities. Therefore, the study looked into FDI spillover effects during these sub-periods. Thus, in the second part of the study, we separate the period into two sub-periods: 1994–2001 and 2002–2010 since, in the second period, the Indian manufacturing sector showed huge FDI inflows. We find that export performances of the domestic firms are significantly hurt by the foreign activities during 2002–2010. The FDI spillover results in the first half of the study period mostly remain insignificant due to low foreign presence. Except R&D spillovers, all other spillover variables show significant negative effect on export propensity of the domestic firms during 2002–2010. It seems that exporting foreign firms were reluctant to share their knowledge about international markets with their domestic competitors. Along with the spillover variables, we have taken into consideration various firm-specific characteristics, for example, capital–labour ratio, R&D activity, import of technology, import of raw material and size of the firms as major indicators which influence export performance of the domestic firms. Among the firm variables, import of raw materials and internal R&D activities showed a significant influence on domestic export performance. It is interesting to mention that internal R&D activities influence export decisions of the domestic firms but not their export propensity. Export performance of the Indian manufacturing firms is significantly hindered by use of imported technology or higher capital–labour ratio. It can be argued that domestic export basket is dominated by the low-technology-intensive products, and therefore use of technology does not help these firms.
Sanghita Mondal, Manoj Pant
Foreign Involvement and Firm Productivity: An Analysis for Indian Manufacturing, Service, Construction and Mining Sectors
Abstract
In recent years, the intensification in the global engagement of Indian firms, by way of exports and outward foreign direct investment (OFDI) has generated significant research that draws on theoretical propositions of the new new trade theory (Helpman, Elhanan, Marc J. Melitz, and Stephen R. Yeaple (2004), “Export versus FDI with Heterogeneous Firms”, American Economic Review, 94:1, 300–316.) (below HMY) that assign a leading role to heterogeneity in firm productivity in explaining self-selection of firms into foreign markets. In HMY, for the export versus OFDI decision, firms with the highest productivity are posited to invest abroad (Goldar, Bishwanath (2016), “Direction of Outward FDI of Indian Manufacturing Firms: Influence of Technology and Firm Productivity”, in Globalization of Indian Industries, Productivity, Exports and Investment, eds. De Beule, F., and K. Narayanan, India Studies in Business and Economics, 71–96, Springer.). Head and Ries (2003) (Head, Keith and John Ries (2003), “Heterogeneity and the FDI versus Export Decision of Japanese Manufacturers”, Journal of The Japanese and International Economies, 17:4, 448–467.) (below HR) note that an empirical complementarity between exports and OFDI could result with differences in fixed costs across destinations. Further, while for manufacturing, predictors such as physical transport cost and sunk cost of OFDI (as in HMY) are considered to be fairly standard, for services, different predictors, based on different considerations such as the need for direct communication with consumers, the difficulty of contracting nonroutine activities to foreign affiliates, near-zero transportation costs and non-commoditized products are proposed to reverse the HMY predictions (Bhattacharya, Rudrani, Ila Patnaik, and Ajay Shah (2012), “Exports versus FDI in Services”, The World Economy, 35:1, 61–78.). This paper examines whether involvement in OFDI is associated with higher productivity levels at the firm level (that is, whether OFDI firms are more productive than firms with purely domestic operations, and those that organize international activities only through exports). Cross-sectional findings of a positive link between firm productivity and foreign involvement could, however, be due to the most productive firms self-selecting into foreign markets, and/or learning effects through foreign engagements. Using Prowess database, over 1995–2010, in addition to manufacturing (57,698 observations) and services (5,145 observations), the under-investigated construction (2,036 observations) and mining (1,196 observations) sector firms are also considered, with no size thresholds. The non-parametric approach of first-order stochastic dominance (Kolmogorov–Smirnov test) is used to examine the nature of productivity differentials between firm categories (based on foreign involvement). In examining the main issue, this paper also discusses some measurement and/or methodological issues. Some modifications are applied towards the construction of real output (gross output (GO), value-added (VA)), and inputs series (combined intermediate inputs, namely, raw materials, energy and services, labour and capital) required for estimating total factor productivity (TFP). While following the widely used Annual Survey of Industries (ASI)-based approach to impute firm-level employment, an attempt is made to overcome the uniform wage criticism by adjusting the labour measure for a ‘wage premium’ based on ownership groups. The measure of physical capital allows for disaggregated growth of investment, and the capital stock measure combines physical and ‘knowledge’ or R&D ‘capital’ stock. In the context of productivity measurement, comparisons are drawn between the alternative methods that attempt to overcome ‘transmission bias’, namely, Levinsohn and Petrin (2003) (Levinsohn, James, and Amil Petrin (2003), “Estimating Production Functions Using Inputs to Control for Unobservables”, Review of Economic Studies, 70, 317–342.) (below LP) and its modification proposed by Wooldridge (2009) (Wooldridge, Jeffrey M. (2009), “On Estimating Firm-Level Production Functions Using Proxy Variables to Control for Unobservables”, Economics Letters, 104:3, 112–114.) (below WLP). Also, in the context of studies that point out that the relative superiority of exporters in comparison to purely domestic firms may also result from several sources of potential bias in productivity estimates (related to the selection of the functional form of the production function, namely, GO vs.VA), attempts are made to explore whether similar concerns are of importance when investigating the relative superiority of OFDI firms (that also export). Next, in the absence of information in the investment outside India data field in Prowess about the percentage holding by Indian firms in their affiliates abroad, while some studies identify an OFDI firm on the basis of existence of positive overseas assets, some use cut-offs on the fraction of OFDI to total assets (as for instance, >1%). In making the cross-sectional comparisons of the estimated productivity distributions, an attempt is made to see whether the stricter basis for classifying foreign investors affects the nature of productivity rankings by firm categories. For firms in the manufacturing and construction sectors, cross-sectional differences in TFP between outward investors that also export, pure exporters, and domestic firms are found to follow the HMY/HR hypotheses, although in contrast to the GO specification, the VA specification suggests an upward bias in the productivity advantage of internationally engaged firms (suggesting that controlling the ‘value-added bias’ is important and it is not sufficient to control only for the ‘transmission bias’). Productivity differentials vary, sometimes considerably by two-digit industry/industry groups. The HMY (and HR) pattern obtains, more so in textiles, coke and refined petroleum products, chemicals, pharmaceuticals, basic metal and fabricated metal, and machinery and equipment n.e.c. than in the rest. In services, TFP comparisons show that pure export firms dominate the purely domestic firms and overseas investors that also export dominate purely domestic firms. However, between the overseas investors that also export and pure exporters, no clear-cut differences could be established unlike a previous study for Indian software services suggesting the stochastic dominance of pure exporters over overseas investors that also export. This suggests that Indian IT firms’ OFDI that is mainly located in developed countries could also be guided by vertical or complex integration strategies, related to the technology-seeking motives and agglomeration economies (due to clustering in specific regions). In mining, only the dominance of pure export firms over purely domestic firms could be established for the latter half of the sample period. Qualified support is thus found for the ‘pecking order’ as predicted by heterogeneous firms’ theories. As the productivity and other firm characteristics of OFDI firms that initially start small are observed to be similar to those with larger positions abroad, if a constraint on financing is found to be an issue for these firms, the government should support a more liberal financial system for OFDI that could also aim specifically at firms with initially small OFDI. EXIM Bank (2017) (Export Import Bank of India (2017), “The Internationalisation of Indian Firms Through Outbound Foreign Direct Investment: Nature, Determinants and Developmental Consequences”, Occasional Paper No. 183. https://​www.​Eximbankindia.​In/​Assets/​Dynamic/​Pdf/​Publication-Resources/​Researchpapers/​Hindi/​82file.​pdf.), for instance, indicates that there is a range over which it is possible to increase firms’ OFDI intensity and increase the benefits from OFDI.
Isha Chawla

Growth Accompanied with Employment Generation: Challenges and Way Forward

Frontmatter
Informal Sector in National Accounts Estimation: Importance of Workforce and Productivity
Abstract
Estimating value added in the informal sector is a challenge to official statisticians. By the very nature of the sector, these are enterprises which have no regular record of activities, books of accounts, and times even place of work. The estimation of value added for such entities reflects one of the great achievements of Indian statisticians. Typically this has been done by combining data collected from NSS sample surveys of households, household enterprises, and the population census. All of these have been done at regular intervals in India. The typical perception about these entities has been that they function on the margins with little or no change in production organisation or technology. However, sample survey data in recent years has been hinting at significant changes in the way these enterprises carry out production. In this connection understanding the contribution of the different types of workers engaged in these activities is central to calculating their value added. This paper reviews the changes introduced in the methodology of calculating value added in the Informal sector in the 2011–12 base revision.
T. C. A. Anant
Who Creates Large Number of Good Jobs in India’s Organized Manufacturing? Small Versus Large and Start-Ups Versus Old
Abstract
Manufacturing sector is important for India to meet its growing domestic demand for non-agriculture goods and thus, it assumes top priority to overcome the trade deficit. Within manufacturing, the organized component is of special importance because of its high levels of productivity, competitiveness and the potentiality to create quality or ‘decent’ jobs. These arguments reiterate by suggesting that manufacturing sector bears the highest responsibility in reaping the demographic dividend. The present study proposes to revisit the issue of assessing the manufacturing sector’s employment potential. The criteria used are size of employment, its growth, quality (regular/contract, wages) and sustainability (diversification/concentration of jobs, and vulnerability to business cycles) of employment. Using these criteria, we prepare a scorecard of manufacturing firms by age and size class so that the deficiencies are identified in order to offer future directives for appropriate policy planning. Based on the preliminary observations from the unit-level data of the Annual Survey of Industries (pertaining to organized manufacturing sector in India.) for the years 2011 and 2012 the following remarks are made: The first observation is that the missing middle as highlighted in the literature has witnessed an increase in the employment share after liberalization. The employment shares of small and large have been more or less constant, while the share of ultra-large firms has declined. In addition, it is the young firms which employ a large proportion of the workers in the total organized manufacturing in India, and employment share declines as firms grow old. Second, it is the medium and large young plants, which create most of new jobs in organized manufacturing in India. Most of the jobs are destroyed in the plants in the age of 11–25 and the contribution of start-ups in the creation of new jobs is very low. Third, the intensity of contract workers is much higher in medium and ultra-large factories, lower in small and lowest in large factories. Among young factories, it is medium and ultra-large factories that employ contract workers even more than half of their total workers. The intensity of contract workers is found lowest in start-ups, which peaks when plant is young and declines thereafter with an increase in age of the factory up to 20 years. Further, the wages are reported to be highest in start-ups, then decline as plants grow young and they are lowest in the older plants. However, beyond 10 years of age, wage increases as the factory gets older. Fourth, the employment is most diversified in medium-sized plants followed by small and large plants. It is most concentrated in the ultra-large plants. Further, the highest concentration of employment is observed in the start-ups. The diversity tends to rise as the plant gets older. In addition, the share of export rises with the increase in the plant size which also shows vulnerability to business cycles. However, no such trend is witnessed in the share of export by age group. The vulnerability is observed to be lowest for start-ups and the oldest plants (26 plus) while it is on the higher side for the older plants. In brief, it is the young middle and large plants which not only account for most of the existing employment in the organized manufacturing but also create most of the new jobs in the organized manufacturing sector in India. These jobs are although relatively low in quality in terms of contract intensity, wages paid by young firms are relatively better. This group is also generating sustainable jobs as the diversity of jobs in this segment is high and vulnerability to business cycle is also relatively low. In view of these observations, it is suggested that the policy for promoting employment in organized manufacturing in India should focus on the most dynamic group, i.e., middle-sized young factories, to generate largest number of new and sustainable jobs.
Jitender Singh, Arup Mitra
Increasing Dualism in Indian Wage Labour Market
Abstract
The patterns of globalization and changes in technology have profound impact on status of labour. The labour market in developing countries like India has been multifaceted—influenced by regional diversity, differences in rural/urban locations, status of workers, education and skill level, caste and religion, industry and institutional basis of labour regulation, etc. In India, the share of regular job holders (often considered as better jobs) has increased in this millennium. These increments in regular jobs are mostly of contractual or informal types, which share several common characteristics with casual workers. The growing trend is narrowing of differences between regular and casual jobs, which may be due to faster growth of casual wages compared to regular. This may be originating from increasing demand of casual work in non-agricultural activities particularly in the construction sector. In addition, the increasing incidence of migration for work both short-term and long-run may have also led to narrowing the wage differential between regular and casual labour. The wage labour market is becoming dichotomous—with two poles, one with high end well paid regular workers and another with low paid informal regular/contractual/casual workers. In this context, there is need to understand how and what factors are responsible for this emerging dichotomy in Indian wage labour market. This paper will unravel the factors and attempt to understand the phenomenon through the latest available data and information.
Sandip Sarkar, Balwant Singh Mehta
Technology, Jobs and Inequality: Evidence from India’s Manufacturing Sector
Abstract
Faced with easier access to foreign technology and imported capital goods, firms in India’s organized manufacturing sector adopted advanced techniques of production leading to increasing automation and a rise in the capital intensity of production. This has raised much concern about the ability of the manufacturing sector to create jobs for India’s rapidly rising largely low-skilled and unskilled workforce. However, what has attracted less attention in the literature is the impact of capital-augmenting technological progress on the distribution of income and wage inequality. This paper attempts to fill this gap using enterprise-level data from the Annual Survey of Industries. We find that with growing capital intensity of production, the role of labour vis-à-vis capital has declined. The share of total emoluments paid to labour fell from 28.6 to 17.4% of gross value added (GVA) between 2000–2001 and 2011–2012, while, the share of wages to workers in GVA declined from 22.2 to 14.3%. Importantly, even within the working class, inequalities have increased. The share of skilled labour (supervisory and managerial staff) in the wage pie rose from 26.1 to 35.8%, while, that of unskilled labour (production workers) fell from 57.6 to 48.8% of total wage bill. However, it is not just the growth of capital intensity but another important, though independent change in the labour market (i.e. the rising share of contract workers) that explains rising inequality. Our results also underline the existence of capital-skill complementarity: firms with higher capital intensity employed a higher share of skilled workers and the wage differential between skilled and unskilled workers was higher in these firms.
Radhicka Kapoor
Skills, Productivity and Employment: An Empirical Analysis of Selected Countries
Abstract
Skills development is central to economic performance of the countries in the current milieu when ‘disruptive’ technology is evolving at a fast pace. The new technology—Internet Of Things (IOT), Artificial Intelligence (AI), machine learning, neural networks, digitization of manufacturing, etc.—is changing the face of how we work, and the skills we need to succeed in our jobs. While opening many new windows for investment and increase in productivity and employment, the new technology is simultaneously disturbing the existing technological complementarities and exerting a lot of pressure on the supply of the matching skills. Many jobs which exist today would disappear tomorrow and many new jobs will get created tomorrow which do not exist today. So there is a simultaneous creation and destruction of jobs. The net impact thus depends upon their respective pace. The shortages of ‘new’ skills put several constraints on growth and development by curtailing the prospects for increases in job creation and income. Coupled with mismatch between supply and demand of skills, it constrains productivity improvements and adds to production costs within firms, making it difficult for the domestic firms to compete internationally, adversely impacting growth prospects along the way through trade linkages. Such skill mismatches and skill shake-ups have increased the need for regular skilling, and up-skilling throughout a person’s career, because people with low skills are generally the first ones to lose jobs. But the speed at which jobs are transforming and the workers’ capacity to adapt to such changes are not uniform across industries and countries and are also influenced by access to education, availability and cost of ICT and the opportunities for lifelong learning inside and outside the workplace. Lifelong learning is needed to resolve both the immediate challenge and to add value through skills in the future. The association between skills, productivity and employment has long been discussed and empirically tested. Fields (Education and income: A background study for world development. The World Bank, Washington, DC, 1980) had concluding way back in 1980 that education (skills) have a positive impact on the level of income by paving new opportunities for many who acquire the skills. Skills thus help in employment and income. The survey of adult skills by OECD (OECD skills outlook 2013. First results from the survey of adult skills. Paris, OECD, 2013) also found a positive association between the mean skill level (measured by numeracy score) and the economic performance across countries (measured by PCI in PPP). Global Competitiveness Report (2016) also points out the significance of skills (talent) in an economy to reap the benefits of the tech revolution and achieve higher productivity and employment. But to meet the growing challenge of ‘new’ skills requirement, we have to recognize existing skills, understand skills demand; create right mix of expertise—especially on the job training and learning; and reach out to those firms and people who need it most—the small and medium enterprises(SME); the low skilled workers; and older workers. Since better skills are likely to lead to quick employment and higher income, for them acquiring and updating skills would be the best insurance against job losses. However, higher economic growth and income also, in turn, help a country with the resources to improve the opportunities for acquiring and developing skill base through the expansion of education and training, leading to a virtuous chain of growth in income, skills, productivity, and employment. There are still quite a few countries, including India which even though have achieved high economic growth, but struggle with low human capital scores (which is a composite score of different parameters and includes enrollment and quality of education; and skills distribution among others (World Economic Forum in The human capital report, 2016)); indicating their neglect in expanding education and imparting necessary skills. The paper aims to first map the industries, based on capital intensity and/or ICT produced/used, in which technology has changed rapidly resulting in change in skills requirements. It will then explore the linkage between skills distribution, (labour) productivity and growth in employment both at the disaggregated industry level as well as at national level for few selected countries like BRIC countries, Indonesia, Mexico, South Korea, etc. for the period 1995–2009; all of which have faced the similar challenges. The exercise would also be carried out separately for formal (organized) and informal (unorganized) sectors of the Indian economy, as it is expected that formal sector firms; especially in the modern sector of the economy are likely to pay higher average wages reflecting higher productivity, which in turn, is partially determined by their skills. These firms, which are also relatively large in size, are also likely to spend more not only in R &D but also on the job training, resulting in better skills proficiency which in turn is likely to lead to higher productivity and growth in employment. The last section would highlight the learning from the experience and focus on the policy challenges the countries would have to face in view of the changing technology landscape.
Suresh Chand Aggarwal
Metadata
Title
Accelerators of India's Growth—Industry, Trade and Employment
Editors
Prof. Suresh Chand Aggarwal
Dr. Deb Kusum Das
Dr. Rashmi Banga
Copyright Year
2020
Publisher
Springer Singapore
Electronic ISBN
978-981-329-397-7
Print ISBN
978-981-329-396-0
DOI
https://doi.org/10.1007/978-981-32-9397-7

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