Structural Change In The Indian Manufacturing: A Study Of Technological Structure And Economic Development

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Structural Change In The Indian Manufacturing: A Study Of Technological Structure And Economic Development

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First, the low technology manufacturing group witnessed an employment elasticity of 1.10 with a negative labour productivity growth rate of -0.04 percent (See Tables 1 and 2) during 200[r]

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STRUCTURAL CHANGE IN THE INDIAN MANUFACTURING: A STUDY OF TECHNOLOGICAL STRUCTURE AND ECONOMIC DEVELOPMENT Chaitanya Talreja

Keywords: structural change, technological classification, economic development, manufacturing, services, demand regime, productivity regime

JEL Classification: O14 L60 L80 D57

I INTRODUCTION

In the process of economic development of societies in the world industrialization has assumed the central role According to Rodrik (2016) industrialization led to sustained productivity increase in Europe and the United States of America leading to economic advancement to becoming rich nations Later the process of industrialization was crucial in catch-up and convergence of a smaller group of non-Western nations like Japan (late nineteenth century), South Korea and Taiwan (post 1960s) Inherent in this process is the importance of manufacturing sector as the driving force of industrialization which the study suggests should also be crucial in reducing poverty in developing economies of Sub-Saharan Africa and South Asia Felipe et al (2013) in their cross country analysis suggest that the probability of transition of an economy from low to high income is much higher (42 percent probability) with manufacturing share in employment and output being at least 18 percent as opposed to lower shares of employment and output (5 percent probability) Further they suggest that no economy has achieved high income status without its manufacturing sector share reaching at least 18 percent They also argue that for an economy to benefit from services as an escalator of growth a solid complementary

manufacturing base is essential

In this context, the study of structural change in India has been a curious case, especially in its post-liberalization period after 1991 The GDP share of manufacturing in India has stagnated around 15-16 percent from 1991-92 to 2012-13 as compared to an increase from percent to 15 percent from 1950-51 to 1990-91 The manufacturing employment share between 1993-94 and 2011-12 hovered around 10-12 percent The GDP share

PhD scholar at South Asian University, Chanakyapuri, New Delhi Email: chaitanya@students.sau.ac.in

Postal Address: E-56, Phase-1, Ashok Vihar, Delhi-110052

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of services on the other hand has grown rapidly from 38 percent to 53 percent from 1991-92 to 2012-13 as compared to 27 percent to 36 percent from 1950-51 to 1990-911 Services employment share increased from 21 percent to 27 percent during 1993-94 to 2011-122 India‟s structural change has been quite distinct as compared to various Asian economies like China, Indonesia, Malaysia, South Korea and Thailand etc as noted by Kochhar et al (2006), Papola (2006) and Ghose (2016), especially during the post reform period after 1991 Most notably, India‟s service sector during the post-reforms period has been a positive outlier in terms of its GDP share and a negative outlier in its employment share in a global comparative perspective On the other hand the

manufacturing sector contribution to employment and output remained comparably low

In light of the central role of manufacturing in economic development and the observed structural change in India with respect to the manufacturing output and employment share, there arises a need to revisit the Indian manufacturing The approach in this analysis takes a marked departure from analysing the relationship between economic growth and manufacturing growth This kind of analysis has been the central feature of important studies like Dasgupta and Singh (2005) and Dasgupta and Singh (2006) in response to the observed structural change with respect manufacturing and services in the developing world, particularly focussing India This approach is restricted to verifying econometric relationship between growth in manufacturing, services and agriculture sectors, respectively with aggregate economic growth This has been with the objective to identify sectors that could be engines of growth The approach being important remains restricted and is unable to explain the underlying process of translation of manufacturing into economic development or reasons for the lack of it The approach presented in this study is to understand the evolution of Indian manufacturing against a framework that explains translation of manufacturing growth into economic development Importantly, this paper looks at the structural change that has happened within the Indian manufacturing across various manufacturing sub-sectors The within manufacturing structural change has been anchored to grouping of manufacturing sub-sectors into technology groups based on standard technological classifications for various manufacturing sub-sectors The importance of this classification and the framework of the analysis are presented in the subsequent sections of the study

1 National account statistics, 2004-05 prices, EPWRF

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The following part of the paper has been divided into four sections Section II explains the theoretical and empirical works behind the synthesis of the analytical framework used in this study Section III discusses the empirical strategy for the study Section IV presents the different aspects of analysis of the internal structural change in the Indian manufacturing since the liberalization reforms based on the analytical framework presented in Section III Section V presents a summary and discussion on the findings of the paper

II STRUCTURAL CHANGE IN MANUFACTURING: AN ANALYTICAL FRAMEWORK The structural change within manufacturing sector is closely related to the pattern of manufacturing sector led economic development, particularly the shift/upgrading of manufacturing production and exports from low technology to high technology manufacturing This has been clearly demonstrated in the work of Lall (2000) This study focuses on the patterns of manufacturing sector exports and relates the change in trade patterns of manufacturing sub-sectors across technology groups between 1985 and 1998 This has been used to demonstrate the relationship between manufactured exports and internal dynamics of structural change in the manufacturing sector from the perspective of economic development According to the study, the share of manufactured exports in total product exports in the world increased from 74 percent to 84 percent between 1985 and 1998 Within the same period resource based manufacturing3 lost their shares in manufactured exports from 24 percent to 17 percent and the high tech industries increased their shares from 17 percent to 25 percent The shares of low and medium technology manufacturing were stable at 19 percent and 39-40 percent, respectively This shows that high technology exports witnessed rapid increase in exports during this period with an annual growth of 13 percent much faster than 9.7 percent for aggregate manufacturing Lavopa and Szirmai (2015) also supports the observation by Lall (ibid).They show that there has been an internal shift in the manufacturing sector towards knowledge intensive high technology manufacturing in terms of manufacturing output share at current prices between 1972 and 2012 The share of medium and high technology manufacturing industries like machinery, electrical & optical equipments and chemicals & chemical products increased from 19 percent to 22 percent and percent to 11 percent, respectively The shares of low technology industries like textiles, leather and footwear and wood, paper and publishing fell from 11 percent to percent and 10 percent to percent, respectively But the internal structural change within the manufacturing sector has not been uniform across

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geography in terms of regional contributions Lall (ibid) shows that the share of developing economies in total manufactured exports increased from 16 percent to 23 percent between 1985 and 1998, but during the same period the share of East Asian economies in total developing economies‟ manufactured exports increased from 57 percent to 70 percent Within the high technology manufacturing the share of East Asia increased from 81 percent to 86 percent Even in terms of share in developing economies‟ manufacturing output at current prices, Lavopa and Szirmai (ibid) show that the share of Asian economies increased from 23 percent to 66 percent during 1972 to 2012

Lall (ibid) also shows that as the importance of high technology manufacturing has increased in world manufacturing exports, this has been accompanied by greater concentration of manufacturing exports in a few economies of the world The top 10 manufacturing exporters contributed to 65 percent of total manufacturing exports and this increased to 80 percent in 1998 The corresponding shares for high technology manufacturing were 94 percent and 96 percent, respectively Driemeier & Nayyar (2018) show that medium and high

technology manufacturing had been amongst the highest traded manufacturing industries in the world with high degree of export concentration in a few economies, extensive use of professional, scientific and technical services, witnessed greatest level of automation in manufacturing processes for the study period of 2011 to 2015

Lall (ibid) suggests that the success of a few Asian economies has been driven by development of capabilities which has been a cumulative process over time as these economies climbed up the ladder of technological sophistication within manufacturing and expanded & diversified their manufactured exports

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effects of labour productivity growth create a employment-productivity growth trade-off (Storm and Naastepad ; 2005) It has been observed that in their successful economic development the East Asian economies managed to escape the productivity-employment-growth trade-off (Storm and Naastepad 2005; Astorga et al 2014) This is because their output expanded more than their labour productivity during the process of industrialization When output growth exceeds labour productivity growth, employment expands

There have been many studies that have looked at the evolution of Indian manufacturing output and employment structure during the post reforms period Some of the important studies are Chaudhuri (2002), Rani and Unni (2004), Kannan and Raveendran (2009) and Ghose (2016) These studies focus on different aspects of Indian manufacturing growth and employment in different sectors like employment elasticity, capital intensity, labour productivity etc These studies have not analysed the Indian manufacturing against a framework that captures the key aspects that led to the successful industrialization of the most recently industrialized economies particularly in East Asia The role of technological classification as an anchor for structural change, a key element for such an analysis has been particularly missing

Studies like Weiss (2005) and Storm & Naastepad (2005), Felipe et al (2013) and Astorga et al (2014), provide a theoretical framework to understand the process that enabled the successful industrialization of newly industrialized East Asian economies A synthesis of the framework developed using the ideas presented in these studies and studies like Park (1989), Park (1994), Francois & Reinert (1996), Guerrieri & Meliciani (2005), and Driemeier & Nayyar (2018) specially for their contribution in highlighting the role of services in

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Figure

A framework of virtuous growth through manufacturing production

Source: Author‟s elaboration

Figure depicts the important relationship between demand expansion and productivity growth This understanding is based on the theoretical basis provided by the synthesis of Kaldor-Verdoon understanding of the mutually reinforcing demand expansion and productivity relationship Within this framework, the aggregate demand drives the production in an economy, and output expands in response to aggregate demand expansion Output expansion further leads to increased productivity in the economy This relationship has been further explained and elaborated by Storm and Naastepad (2005), specifically focussing the East Asian economic success The initial impetus on labour productivity growth comes through investment and capacity creation for production which is the starting point for kick-starting the process of virtuous growth Labour productivity further improves through capital deepening Capital deepening is the growth of capital stock per worker But it has been argued by Storm and Naastepad (2005) increased capital intensity essentially embodies technology and reflects technological progress embodied in the capital equipments used with increased used of capital per worker They show that capital stock per worker grew by 7.7 percent, 5.6 percent, 5.2 percent, 5.2 percent and 8.2 percent in South Korea, Japan, China, Singapore and Taiwan respectively, between 1960 and 2003

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successful industrialized economies in East Asia have witnessed structural change in their manufacturing composition, beginning from larger share of low technology groups to a shift towards medium and high

technology groups in production and exports For example the manufacturing value added share of textile sector (low technology) fell from 22.6 percent to 7.8 percent and 17.4 percent to 6.5 percent respectively for South Korea and Taiwan between 1975 and 2002 On the other hand shares of machinery sector (high technology) increased from14.2 percent to 45.9 percent and 18.2 percent to 45.5 percent in both these economies respectively during the same period Similar shifts happened in the case of exports shares (See Storm & Naaastepad 2005, pp 1070-1071) In their work, Lall (2000) and Palma (2009) have closely analysed the relationship between technological upgradation within manufacturing production and the export expansion within the successfully industrialized East Asian economies As previously noted in this section, there has been a close association between global relocation of manufacturing production towards the East Asian economies, and their manufactured exports expansion The East Asian economies that have successfully industrialized during this period as they rapidly increased their share in world manufacturing exports and upgraded and diversified their exports beginning from low-technology manufacturing to high-technology manufacturing This process has been popularly termed as the flying geese pattern where the leading goose economy leaves the space open for the following geese to enter the export market of a lower technology industry, as it upgrades its exports to higher technology industries This happens as the leading goose economy has saturated productivity advantage or faces rising costs in low technology industry This process has been considered to be a path-dependent process, involving development of cumulative capabilities as an economy upgrades itself towards high technology manufacturing production Simply put, the process of learning, knowledge creation and capability development enabled these economies to sequentially upgrade from low technology manufactured exports to high technology manufactured exports (Lall 2000 and Palma 2009) Technological classification of industries is the most useful anchor to understand the structural change in manufacturing in order to compare it with the experience of successful industrializers

An aspect which has become more important in manufacturing production since the 1990s after the Information and Communication technology revolution is the intensity of service use in manufacturing

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1994; Francois & Reinert 1996; Guerrieri & Meliciani 2005; Felipe et al 2013 and Driemeier & Nayyar 2018) as discussed in Section II The process of technological upgradation, capital deepening and contribution of service inputs in manufacturing production determine the labour productivity regime of an economy under this framework

Under this framework aggregate demand expansion stimulates labour productivity growth, but labour productivity growth also has an effect on demand as elaborated by Storm and Naastepad (2005) Improved labour productivity may have opposing effects on aggregate demand If the share of wages in output falls as a result of improved labour productivity and the propensity to consume of wage earners is higher than the profit earners, the consumption demand is expected to fall At the same time a rise in profit share may incentivise greater investment Improved productivity also supports export expansion by improving the competitiveness of domestic production The net effect of a rise in labour productivity on consumption demand, investment demand and exports determines the impact of labour productivity on demand expansion A mutually beneficial

relationship between the demand and productivity regimes is crucial for virtuous economic growth occurring through the structural change within the manufacturing sector

This framework provides a useful anchor against which the developmental implications of manufacturing sector structural change in an economy needs to be assessed

III EMPIRICAL STRATEGY

The empirical strategy for an analysis of the structural change in the Indian manufacturing is based on the analytical framework presented in Section III Technological upgradation within manufacturing industry structure is an element of the analytical framework that is both a crucial aspect of understanding the

technological sophistication and diversification within the manufacturing sector and also lends a definitional understanding to the structure of classification4 of industries within the manufacturing sector The analysis here uses the technological classification of manufacturing industries as an anchor against which the structural change within the Indian manufacturing sector has been assessed The empirical exercise in this paper is based on the specific areas of analysis in the productivity and demand regimes identified from the analytical framework and carried out in the following steps:

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1 Trends in the structure and composition of value added and employment within the manufacturing sector

2 labour productivity and employment elasticity relationship across technological groups in Indian manufacturing (reflects the interplay of the demand/output growth regime, productivity regime and employment growth),

3 indirect employment structure of the manufacturing sector (If change in the technological structure of production has altered the structure of indirect employment generation across technological groups),

4 labour productivity and capital intensity relationship (reflects the nature of capital deepening Whether capital deepening reflects technological upgradation or labour substitution), Pattern of service dependence of different technological groups of manufacturing,

6 Demand regime analysis: Composition of effective demand and trends in domestic absorption, export orientation and imports

The purpose of the strategy adopted in the steps mentioned above is to interpret the different aspects of the productivity and demand regimes of the Indian manufacturing sector The motivation behind this is to understand the co-evolution of these aspects of the productivity and demand regimes and understand the implications of this growth process for the economic development of the Indian economy The aim of this study is not to model the causality of the analytical framework explained in Section III but to assess the developmental implications of the growth process through an analysis of the patterns observed at different nodes of Figure

IV STRUCTURAL CHANGE IN INDIAN MANUFACTURING: AN ANALYSIS

This section investigates the various discussed aspects of structural change in the Indian manufacturing sector during the post liberalization era The analysis in this section has been based on the India KLEMS database5 and five Input-Output Transactions Tables (IOTTs) available for India during the post-reforms period The third edition of India KLEMS database has been used here with the base year as 2004-05 This dataset provides time-series data for 27 sectors of the Indian economy on outputs (gross value added and gross value of output) and inputs like capital, labour, energy, material and services from 1980-81 to 2014-15.There are 13

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manufacturing sectors in this database The Central Statistics Office (CSO), Government of India has provided four IOTTs for the years 1993-94, 1998-99, 2003-04 and 2007-08 The fifth IOTT used here is for the year 2013-14 which has been published by the National Council for Applied Economic Research (NCAER)6 There are 115 sectors in the 1993-94 and 1998-99 IOTTs and there are 130 sectors in the subsequent IOTTs There are 66 manufacturing sub-sectors in the 1993-94 and 1998-99 IOTTs and 68 manufacturing sub-sectors in the latter three IOTTs The focus of this analysis is to analyse the structural change in India‟s manufacturing sector based on the technological classification of manufacturing sub-sectors The manufacturing sub-sectors in both the India KLEMS database and IOTTs have been classified into three and four technology categories, respectively The manufacturing sub-sectors in the IOTTs have been aggregated to 16 sectors The three categories of

technological sophistication used for KLEMS database are low technology (LT), medium low technology (MLT), medium & high technology (MHT) The four categories used for IOTTs are low technology (LT), medium low technology (MLT), medium technology (MT) and high technology (HT) The OECD (2011) document and UNIDO‟s latest technological classification of manufacturing sectors have been used7 The analysis in this section follows the sequence of exercises discussed in Section IV

1 Trends in Composition of Manufacturing Output and Employment

Figure and Figure below depict the change in average gross value added shares and average employment shares for five year intervals beginning from 1990-91 to 1994-95 till 2010-11 to 2014-15 for low technology, medium low technology and medium & high technology groups of the Indian manufacturing sector

6 This IOTT has been prepared by modifying the Supply and Use Tables (SUTs) provided by the CSO for the years 2011-12 and 2012-13 The

SUTs provided by the CSO are rectangular matrices of intermediate transactions and final demand for different sectors with 140 rows and 66 columns The analysis requires square matrices and IOTTs are available as square matrices

7 The OECD and UNIDO provide classification of manufacturing sectors based on technology intensity reflected by Research and Development

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Figure

Average Gross Value added shares of manufacturing sectors based on technology intensity (2004-05 prices)

Source: Author‟s Calculation based on India KLEMS database Figure

Average Employment shares of manufacturing sectors based on technology intensity

Source: Same as Figure

Figure above clearly depicts the internal adjustment of output within the manufacturing sector from low technology manufacturing to medium & high technology manufacturing between 1990-91 and 2014-15 The output share of medium low technology fluctuated around 30 percent during this period The share of low technology fell from around 45 percent to 35 percent and the share of medium & high technology rose from 25

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percent to 35 percent The adjustment in employment shares across technology categories has been relatively much slower and smaller in magnitude as compared to the adjustment in output shares as can be seen in Figure The employment share of low technology industries fell by percent from 70 percent to 65 percent and the shares of medium low technology and medium & high technology increased from 18 percent and 12 percent to 20 percent and 15 percent respectively A clear pattern that emerges from this structural change within the manufacturing sector is that a larger chunk of manufacturing output has moved to sectors which support much lesser manufacturing employment This depicts that the composition of income generation in the manufacturing sector followed a trajectory similar to the change that the global economy has witnessed during these years But at the same time the gap in average values added between those associated in production across different technology groups widened This suggests that the internal productive structure of manufacturing sector witnessed a structural change which saw a skewed distribution of income towards those who have managed to find access to work in higher skill and higher technology

2 Trends in Employment Elasticity and Labour Productivity Relationship

In the previous sub-section we found out the structural adjustment of output and employment composition across technological groups within the Indian manufacturing during the post-liberalization era In general for the growth process to be inclusive it needs to be accompanied by improvement in labour productivity and employment generation at the same time This relationship between output growth, employment elasticity and labour productivity growth has been discussed in Kapsos (2005) and Kannan & Raveendran (2009) This relationship that has been analysed here for the Indian manufacturing across its sub-sectors is based on the following conceptualization by Kapsos (2005):

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employment with respect to output and is given by gl/gy Equation (3) here establishes an important relationship between employment elasticity, labour productivity growth and output growth This also conveys that higher labour productivity accompanied with a relatively low rate of growth of output pushes the employment elasticity downwards Simply put, in such a situation a higher labour productivity occurs only due to low employment growth This is because labour productivity depicted here is average labour productivity Despite the simplicity of this exposition, the analysis of actual trends in output and employment growth using this framework provides useful insights about the growth process8 This exercise has been conducted for the Indian manufacturing sector based across technological groups using the India KLEMS database The methods for computing employment elasticities, labour productivity growth, output and employment growths are provided in Appendix B

Table

Employment Elasticity of manufacturing groups based on technological classification

Emp Elasticity 1990-91 to 1994-95 1995-96 to 1999-00 2000-01 to 2004-05 2005-06 to 2009-10 2010-11 to 2014-15

LT 0.19 0.44 1.10 -0.49 0.29

MLT 0.53 1.02 0.42 -0.05 0.71

MHT 1.29 0.09 0.38 0.23 3.13

Total

Manufacturing 0.38 0.49 0.61 -0.24 0.65

Source: Author‟s calculation based on India KLEMS database Table

Labour productivity growth of manufacturing groups based on technological classification

Source: Same as Table

Table

Employment growth of manufacturing groups based on technological classification

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See Appendix B, Table 12 for interpretation of employment elasticities in different scenarios depicted by different combinations of output, productivity and employment growth

Manufacturing groups based on technology intensity/Years 1990-91 to 1994-95 1995-96 to 1999-00 2000-01 to 2004-05 2005-06 to 2009-10 2010-11 to 2014-15

LT 4.3 2.3 -0.4 10.6 4.5

MLT 1.9 -0.1 3.4 10.1 1.8

MHT -1.5 3.8 5.3 8.2 -5.2

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Manufacturing groups based on technology intensity/Years 1990-91 to 1994-95 1995-96 to 1999-2000 2000-01 to 2004-05 2005-06 to 2009-10 2010-11 to 2014-15

LT 1.0 1.8 3.8 -3.5 1.8

MLT 2.1 3.1 2.5 -0.5 4.4

MHT 6.5 0.4 3.3 2.4 7.6

Manufacturing 1.8 1.9 3.5 -2.2 3.2

Source: Same as Table

Table

Output growth of manufacturing groups based on technological classification Manufacturing groups

based on technology intensity/Years 1990-91 to 1994-95 1995-96 to 1999-00 2000-01 to 2004-05 2005-06 to 2009-10 2010-11 to 2014-15

LT 5.4 4.1 3.4 7.1 6.3

MLT 4.0 3.0 6.0 9.6 6.2

MHT 5.0 4.2 8.5 10.6 2.4

Manufacturing 4.8 3.8 5.7 9.0 4.9

Source: Same as Table

The Tables 1-4 depict the trends in relationship between employment elasticity, labour productivity, employment and output growths during the post-reform period for the Indian manufacturing sector across technological groups As a background to this analysis it is important to shed light on a few issues Mehrotra et al (2014) shows that the unorganized segment of the Indian manufacturing contributes 65 percent to

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are three important observations here in the periods with highest employment elasticity i.e 2000-01 to 2004-05 and 2010-11 to 2014-15 First, the low technology manufacturing group witnessed an employment elasticity of 1.10 with a negative labour productivity growth rate of -0.04 percent (See Tables and 2) during 2000-01 to 2004-05.The previous section has already shown that the structural adjustment within manufacturing across technological groups has reflected large labour productivity difference between low technology manufacturing and medium & high technology manufacturing as the former contributed much more to employment than output and the latter contributed much more to output than employment (See Figures 2-3) This high elasticity of employment in low technology group has been a result of employment growth superseding output growth during this period (See Tables and 4) Second, the employment elasticity of the manufacturing sector increased steeply during 2010-11 and 2014-15, but the medium & high technology witnessed an extremely steep decline in labour productivity as the growth rate was -5.2 percent This was due to a rapid slowdown in output growth of this group and a sharp rise in employment growth, which seems to be a peculiar trend during this period (See Tables 1-4)9 Third, the period 2005-06 to 2009-10 saw rapid growth rates in labour productivity and output growth which were highest during the post-reform period for the manufacturing sector as a whole and across technology groups (Tables and 4) But this rapid rise in labour productivity came along with decline in manufacturing employment growth i.e decline in employment contributed to the rise in labour productivity as opposed to a employment generating labour productivity growth All the technological groups witnessed negative growth rates in employment except medium & high technology group where the growth rate was moderately positive The period saw a negative employment elasticity in manufacturing with high output growth This exercise depicts that though manufacturing sector employment elasticity improved as a whole during the post reform period (except during 2005-06 to 2009-10), the internal dynamics of the sector convey that this process witnessed steep fluctuations in employment growth and labour productivity in different periods and across technological groups and was not uniform or sustained process of employment generating labour productivity growth10 It was previously discussed in Section III, that technological change has both

This is on account of an unusually high employment growth in Electrical and Optical Equipments sector of the MHT during 2010-11 to 2014-15 of 17.6 percent (annual average growth rate) This sector accounted for average 31 percent employment share of MHT sector during this period This has also been noted in the KLEMS report published on 27/03/2018 which describes the KLEMS dataset creation

https://m.rbi.org.in/Scripts/PublicationReportDetails.aspx?UrlPage=&ID=894 (Section 4.1)

10Mehrotra et al (2014) provides a qualitative assessment of the trends in employment of the Indian economy during the post-reform period In

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employment displacing and employment generating effects in the economy In the analysis so far it has been noticed that structure of manufacturing has been altered in favour of industries that have generated relatively much lesser employment per unit of output as compared to more employment intensive industries But this only reflects direct employment intensity of these industries As structural change occurs, employment might be added indirectly by production in a sector through different process added in the production process, such that employment is generated in other sectors of the economy To understand this process, the next sub-section analyzes the evolution of structure of indirect employment generation by different technological groups in the manufacturing sector

3 Structure Of Indirect Employment

In sub-section of Section IV it was also noticed that the low technology manufacturing continued to be the major direct employer of the manufacturing sector employment during the post-reforms period (See Figure 2) This does not reflect the indirect employment that different manufacturing sub-sectors generate through their input-output linkages with different sectors This is aspect has been analysed below in Table using the methodology of computing indirect employment based on Veeramani (2016)

(

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In equation (1), E is n*n diagonal matrix of employment to gross output ratio for each sector i, where each diagonal element of the matrix is denoted by ei The term depicts the Leontief inverse matrix computed from the matrix Ad of the domestic input coefficients11 The term Fd depicts the n*n diagonal matrix of final demand from domestic sources with each diagonal element denoted by Fj depicting the final demand for each sector j Matrix L depicts the n*n matrix where each lij depicts the employment generated in sector i due to the total final demand for commodity j In equation (3) the total indirect employment generated by sector j in the economy due to final demand generated for sector j (depicted by the column sum of matrix L) due to the

female employment within self employment low productivity manufacturing activities In the entire period, there was a consistent rise in casual employment amidst the fluctuations witnessed by self employed and regular workers

11Dietzenbacher et al (2005) provides a detailed discussion on the usage of Ad matrix instead of A in modelling and multiplier exercises The Ad

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backward linkages of sector j with all the upstream sectors i The employment coefficients used here have been computed from the India KLEMS database, and all the IOTTs have been reduced to the 27 sector classification provided by the India KLEMS database As already discussed, there are 13 manufacturing sub-sectors in the total 27 sectors as per the India KLEMS database Table below shows the percentage of indirect employment created by the manufacturing sectors in the total indirect employment generated by these manufacturing sub-sectors in the Indian economy for all the benchmark IOTTs during the post-reforms period

Table

Manufacturing sub-sector indirect employment (as a percentage of total indirect employment generated by all the manufacturing sub-sectors)

S No Manufacturing Sectors/Years

Technological classification

1993-94

1998-99

2003-04

2007-08

2013-14

Food Products, Beverages and

Tobacco LT 50 62 59 48 55

2

Textiles, Textile Products,

Leather and Footwear LT 22 16 17 19 14

3 Wood and Products of wood LT 0

4

Pulp, Paper,Paper

products,Printing and Publishing LT 1

5 Manufacturing, nec; recycling LT

6

Coke, Refined Petroleum

Products and Nuclear fuel MLT 1

7 Rubber and Plastic Products MLT 2

8

Other Non-Metallic Mineral

Products MLT 1

9

Basic Metals and Fabricated

Metal Products MLT 2

10

Chemicals and Chemical

Products MHT 5

11 Machinery, nec MHT 3 4

12 Electrical and Optical Equipment MHT

13 Transport Equipment MHT 3

14 Manufacturing 100 100 100 100 100

Source: Author‟s calculation based on India KLEMS database and IOTTs 1993-94, 1998-99, 2003-04 and 2007-08, CSO, MOSPI, GOI and IOTT 2013-14 Kanhaiya and Saluja (2016)

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This is also on account of its strong backward linkages with the agricultural & allied activities12 sector which is the largest sector in terms of employment in India13 This analysis conveys that as the composition of value added has adjusted in favour of technologically sophisticated sectors, their direct and also indirect employment contribution in the economy has been relatively much lower during the post-reforms period The structure of indirect employment generation by the manufacturing sector remained virtually unaltered This can also be seen from the actual employment figures in Appendix D Table 14 Out of the 54.4 millions indirect employment attributed to manufacturing final demand in 1993-94, 25.4 million jobs were contributed by Food Products, Beverages and Tobacco sector As the manufacturing indirect employment doubled to 103.4 millions in 2013-14, 56.5 millions were contributed by Food Products, Beverages and Tobacco sector The low technology sectors also dominated the indirect employment generation by the Indian manufacturing The medium & high technology sectors with relatively low employment intensity per unit of output also did not become more important sectors in terms of indirect

employment generation through backward linkages with upstream sectors This would be expected in a virtuous process of growth where new production processes add employment elsewhere in the economy (Storm and Naastepad 2005; Astorga et al 2014)

4 Labour Productivity, Capital Productivity and Capital Intensity Relationship

The previous sub-sections observed the trends and deciphered the patterns of structural change in the Indian manufacturing through the relationship between employment and labour productivity growth The growth in labour productivity itself can be decomposed into capital productivity growth and capital intensity growth The decomposition of this relationship has been presented in Chaudhuri (2002) and Rani & Unni (2004) It is also shown here below:

Where Y is the output, L is the employment, K is the capital stock, Y/L is labour productivity, K/L is capital intensity and Y/K is capital productivity Equation (2) depicts the growth rates from equation (1), where  is labour productivity growth, gk is capital intensity growth and  is capital productivity growth Based on

Chaudhuri (2002) and Rani & Unni (2004), the basic conceptualisation in equation (2) conveys that the growth in

12 Agriculture, Hunting, Forestry and Fishing

13 Appendix D shows that among the broad sectors of the Indian economy, manufacturing sector contributed 60 percent of the overall indirect

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labour productivity could be understood as labour substitution if growth in capital intensity is accompanied by a lack of capital productivity growth and in case of capital productivity growth with capital intensity growth the situation could be understood as that of technological upgradation14 As previously discussed in Section III, capital deepening is an important aspect of the productivity regime in successful manufacturing sector led economic development The exercise discussed here aims to understand the evolution of this specific relationship between capital deepening and labour productivity for the Indian manufacturing sector Table and Table below respectively present capital intensity growth and capital productivity growth in Indian manufacturing, respectively Table above has already presented labour productivity growth The analysis here involves observations made through conjunction of Table 2, Table and Table

Table

Capital intensity growth of manufacturing groups based on technological classification Manufacturing

groups based on technology intensity/Years 1990-91 to 1994-95 1995-96 to 1999-00 2000-01 to 2004-05 2005-06 to 2009-10 2010-11 to 2014-15

LT 5.2 6.0 2.1 11.4 1.3

MLT 6.7 8.1 3.2 12.3 2.1

MHT -1.1 10.4 0.5 7.6 -1.5

Manufacturing 5.0 8.0 1.7 12.1 2.1

Source: Same as Table

Table

Capital productivity growth of manufacturing groups based on technological classification Manufacturing groups based on technology intensity/Years 1990-91 to 1994-95 1995-96 to 1999-00 2000-01 to 2004-05 2005-06 to 2009-10 2010-11 to 2014-15

LT -0.9 -3.7 -2.4 -0.8 3.2

MLT -4.9 -8.1 0.3 -2.2 -0.3

MHT -0.3 -6.6 4.8 0.5 -3.7

Manufacturing -2.0 -6.1 0.5 -0.9 -0.4

Source: Same as Table

Table shows that during the entire post-reform period the capital intensity of the manufacturing witnessed an increase The initial decade of the reform period witnessed a rise in the growth of capital intensity which slowed down sharply from percent during 1994-95 to 1999-2000 to 1.7 percent during 2000-01 to

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05 The sharpest increase in capital intensity growth took place during 2005-06 to 2009-10 when it rose 12.1 percent and subsequently slowed down to 2.1 percent during 2010-11 to 2014-15 Table shows that capital productivity growth was negative during the entire period except 2000-01 to 2004-05 The nature of capital intensity growth reflected labour substitution more intensely during the first decade due to much larger negative capital productivity growth of the post-reform period (See Table 7) The nature of labour substitution reflected by capital intensity growth was much more sustained in low technology and medium low technology groups The medium & high technology group was relatively better off in this sense as it experienced a decade of capital intensity growth which was more reflective of technological upgradation during 2000-01 to 2009-10 (See Tables and 7) The medium & high technology group also witnessed a fall in capital intensity during 2010-11 to 2014-15 due to a rapid rise in employment growth (Table 3) during this period This also came along with steep slowdown in output growth (Table 4) which did not accompany technological upgradation (Table 7) The negative capital productivity growth of 3.7 percent in the MHT sector was due high and negative capital productivity growth in machinery nec (7 percent), transport equipments (7 percent) and chemicals and chemical Products (1.6 percent) sectors The electrical and optical equipments sector witnessed a small positive capital productivity growth of 0.9 percent This exercise depicts that as the manufacturing sector witnessed a growth in capital intensity that reflected labour substituting labour productivity growth The lower technology groups (LT & MLT) were affected much more in terms of labour substitution due to the longer period of such process in these groups and a much larger magnitude of employment share This reflects that the post-reform growth process within the manufacturing sector has been clearly biased against low productivity-low skill manufacturing employment

5 Structure of Manufacturing Dependence on Services

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analyse its role in the manufacturing production structure Following Park (1989) manufacturing intensity of service use has been calculated as share of service inputs in total input cost of manufacturing sectors

Table below depicts the dependence structure of the manufacturing sector technology groups on modern producer services and traditional services15 for the benchmark IOTT years

Table

Manufacturing dependence on services based on technology groups (service input cost as a percentage of total input cost)

S No 1993-94

Services/Manufacturing technology groups* LOW (1) MLT (2) MT (3) HT (4) Manufacturing (5)

1 Trade, Storage and Transport 22.5 18.0 16.0 20.0 19

2 Finance and Communication services 3.4 4.0 6.1 8.6

3 Services 28.6 24.4 25.5 29.5 27

1998-99 LOW (1) MLT (2) MT (3) HT (4) Manufacturing (5)

1 Trade, Storage and Transport 17.3 16.8 13.4 16.7 16

2 Finance and Communication services 5.9 6.1 7.2 8.4

3 Services 25.8 25.6 24.3 25.9 25

2003-04 LOW (1) MLT (2) MT (3) HT (4) Manufacturing (5)

1 Trade, Storage and Transport 21.3 14.1 12.8 11.2 16

2

Finance, Communication and Business

services 6.6 4.5 8.9 12.0

3 Services 28.9 18.9 23.8 24.7 24

2007-08 LOW (1) MLT (2) MT (3) HT (4) Manufacturing (5)

1 Trade, Transport and Storage 22.6 14.3 13.1 13.9 17

2

Finance, Communication and Business

services 5.9 3.2 7.6 11.1

3 Services 30.4 18.1 21.5 27.7 23

2013-14 LOW (1) MLT (2) MT (3) HT (4) Manufacturing (5)

1 Trade, Storage and Transport 14.3 7.6 9.3 8.6 10

2

Finance, Communication and Business

services 3.4 3.6 1.5 1.2

15 Modern Services: Services like banking and insurance, business and legal, computer-related and real estate services; Traditional Services:

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3 Services 17.7 11.4 10.9 9.8 13 Source: Author‟s calculation based on IOTT 1993-94, 1998-99, 2003-04 and 2007-08, CSO, MOSPI, GOI and IOTT 2013-14 Kanhaiya and Saluja (2016)

Note: Data on “business services” is separately available only since 2003-04 IOTT For the years 1993-94 and 1998-99 “business services” category was not separately provided and was a part of a broader category of “other services”

In Table above, the columns (1)-(4) depict the dependence of all the four manufacturing technology groups on traditional services in row 1, modern services in row and aggregate services in row for each benchmark IOTT years Column (5) for each year depicts the dependence of aggregate manufacturing on the services This dependence is characterised by the share of input cost of these services in total input cost of the manufacturing sectors concerned A systematic pattern that is clearly visible from Table is that traditional services have been structurally most important services for the manufacturing sector as a whole and all the technology groups during the post reforms period On the other hand, the reliance of manufacturing sector on modern services was virtually unaltered as opposed to the evidence that these services tend to become structurally important in manufacturing production with increasing per capita income shown in various cross country analyses like Park (1989), Park (1994), Francois & Reinert (1996), Guerrieri & Meliciani (2005), and Driemeier & Nayyar (2018) This observation is notably perverse in the light of rapid service sector growth in India during this period16 Another clear pattern that emerges from Table is that medium technology and high technology manufacturing groups have been systematically more intensive users of modern services as compared low technology and medium low technology groups This finding is intuitive in terms of the knowledge and skill intensive nature of medium technology and high technology manufacturing, but also depicts a structural duality between technology groups within the manufacturing sector This indicates towards a relatively higher

integration between relatively more productive and skill intensive sectors of the Indian economy17 Studies like

16 This finding has also been discussed in detail in Talreja (2018) which shows that in its rapid growth phase during the post-reform era, the

service sector and modern services did not witness an increased integration with the manufacturing sector as a whole Final demand played an important role as a source of growth and demand for services in India during this period

17In the year 2013-14, it can be noticed that there is a steep fall in dependence of manufacturing on services which is also reflected by the technology groups The clear patterns of comparably greater integration higher technology groups (MT and HT) with modern services observed consistently from 1993-94 and 2007-08 is not seen in 2013-14 As a possible explanation, Talreja (2018) shows that the share of mining & quarrying saw a steep rise in manufacturing input cost from 16 percent to 24 percent between 2007-08 to 2013-14 as the share of services declined from 23 percent to 13 percent during the same period A closer analysis of the 2007-08 and 2013-14 IOTTs shows that the dependence of medium technology and high technology groups on natural resource based medium low technology manufacturing group (which is highly integrated with the mining & quarrying sector) increased from 26 percent and percent to 36 percent and 20 percent, respectively The period 2010-11 to 2014-15 also saw a steep slowdown in manufacturing sector value added growth and the medium & high technology group witnessed the slowest growth during the post-reforms period, during this period (See Table 4) This slowdown was accompanied by a negative growth of labour productivity and capital productivity (See Table and Table 6, respectively) of the manufacturing sector which was much more

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Banga and Goldar (2005) and Mukherjee (2018) in their analysis of organised manufacturing sector show that in their estimated production function, services contributed positively to manufacturing sector productivity for the years 1980-81 to 1999-00 and 2000 to 2014, respectively Mukherjee (2018) shows this evidence to be mixed at the disaggregate level The former is a plant level analysis while the latter is a firm level analysis Clearly, at a broad structural level in terms of industry/sectors this did not alter the pattern of reliance of the manufacturing sector on services during this period While there is evidence of services impacting productivity in certain organised segments of manufacturing during this period, this did not alter the structural reliance of the manufacturing productivity regime on services during this period On one hand this could be due to

heterogeneity in productivity regimes of manufacturing sector in terms of organised and unorganised sectors and in terms of technological groups and on the other hand on the nature of service sector growth in India itself Service sector growth has been shown to be more driven by final consumption demand and exports as compared to intermediate demand during its rapid growth phase (Talreja; 2018)

6 The Demand Regime: Domestic Absorption, Exports and Import dependence

Until the previous section the evolution of the productivity regime of the Indian manufacturing sector was the focus of enquiry within the framework envisaged in section III As discussed in Section III, that demand expansion stimulates productivity as output expansion takes place in response to the demand generation Output expansion further leads to increased productivity The analysis of the productivity regime of the Indian

manufacturing sector shows that intra sectoral structural change within the manufacturing sector has led to widened gap between the workforces engaged in low technology and medium & high technology sectors This is based on the distribution value added shares between the technology groups as compared to the employment Growth in labour productivity did not involve a sustained process of employment generation Increased capital intensity has reflected labour substitution instead of technological upgradation The productivity regime impacts the demand generation in the economy through the channels of consumption, investment and exports as

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absorption (consumption plus investment) and exports Domestic absorption and exports together constitute the effective demand or the realised demand for the domestic production This is akin to the explanation provided by Bhaduri (1986) He explains that the actual demand faced by the producers in a capitalist economy reflects the size of the market The principle of effective demand determines the size of the market in a capitalist economy as a part of the production process The role of imports is crucial in the principle of domestic demand as they reduce the home market for domestic produce The impact of the productivity regime on the demand regime in this framework works through the principle of effective demand In case of improved export demand through increased productivity, the size of the market tends to be determined by the distribution of gains from export among various classes and the import demand generated domestically for consumption and exports This conceptual understanding based on this principle of effective demand motivates the methods of analysis in this section

Without even looking at the exact distribution of value added that accrued to different classes in the production process, it is clear from the previous analysis of the productivity regime that intra-sectoral distribution of value added has worsened in the Indian manufacturing during the post-reforms period This analysis involves looking at aggregate demand metrics to understand the nature of the demand regime in the Indian manufacturing The analysis begins by looking at the ratio of effective demand to domestic absorption for the Indian manufacturing sector

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Table below depicts the structure of Indian manufacturing demand in based on the discussion arising from equations (1) and (2) above

Table

Components of Indian Manufacturing Final Demand (As a percentage of Effective Demand)

S No

Components of Manufacturing

Demand/Years 1993-94 1998-99 2003-04 2007-08 2013-14

1 PFCE 61 72 62 52 55

2 GFCE 4

3 GFCF 42 37 42 44 30

Domestic Absorption (1+2+3)

4 Valuables 0 0

5 CIS -1 -1 19 18

6 Export 25 28 32 30 42

7 Import Demand 32 42 42 49 51

8 Effective Demand 100 100 100 100 100

9

(Effective Demand/Domestic

Absorption)*100; (ED/DA) 92 88 93 100 115

Source: Same as Table

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down, with build up of inventories and improved export share In the entire period the import demand for manufacturing as a share of effective demand rose steeply and consistently from 32 percent in 1993-94 to 51 percent in 2013-14 As the share of manufactured exports increased, the import demand continued to increase and surpass the exports by an average of 11 percent of the effective demand during the entire period The most peculiar finding here is that the period after 1998-99, saw a fall in the importance of private consumption and decline in relative importance of domestic absorption, significant build up of inventories and increased export share, but the imports continued to expand its relative importance in the home market Ghose (2016) argues that rapid service sector growth in India during the post-reforms period has led to income patterns that have

generated greater demand for manufactured imports Further, the study shows that in the organized

manufacturing 1999-2000 and 2011-12 became increasingly dependent on imported inputs for production He also shows that growth in the organised manufacturing was explained by imported input intensity irrespective capital or labour intensive industrial classification These claims can be further verified for the manufacturing sector as a whole (organised and unorganised manufacturing) in Table 10 and Table 11 below

Table 10

Net Imports as a percentage of Domestic Absorption in Indian Manufacturing S No

Manufacturing Industries/Years

Technological Classification

1993-94

1998-99 2003-04

2007-08

2013-14 Food Products, Beverages &

Tobacco LT -7 -2 -5

2 Textiles, Textile Products, Leather

and Footwear LT -35 -49 -46 -36 -36

3 Wood and Products of Wood, Pulp, Paper, Paper Products, Printing and

Publishing LT 30 45 42 29 123

4 Manufacturing, n.e.c.; recycling LT 8 4 67 17 -47

5 Rubber and Plastic Products MLT -15 -4 -25 -7 72

6 Coke, Refined Petroleum Products

and Nuclear Fuel MLT 104 109 20 -19 -53

7 Other Non-Metallic Mineral

Products MLT -404 -864 -32 58

8 Basic Metals and Fabricated Metal

Products MLT 31 120 61 89 2760

9 Ships and boats MLT 16 28 132 399 95

10 Chemicals and Chemical Products MHT 71 78 40 124 198

11 Machinery, n.e.c MHT 31 41 15 42 30

12 Electrical machinery MHT 14 23 6 16 20

13 Rail Road, motor vehicles and

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14 Drugs and medicines HT -71 -412 -133 -226 -61 15 Radio, TV and Communication

equipments HT 11 32 44 95 123

16 Other high-tech manufacturing HT 3 -5 51 82 31

17 Manufacturing 7 12 9 19 10

Source: Same as Table

Table 10 above depicts the ratio of net imports (excess of imports over exports) to domestic absorption in the Indian manufacturing A negative percentage shows the excess of exports over imports in the Table 10 above As a broad observation, the Indian manufacturing witnessed a penetration of imports in the home market throughout the post-reforms period This is depicted by a large and positive net import share of the domestic absorption in all the years shown in Table 10 It is noteworthy to see that in 2007-08 and 2013-14 when the share of private consumption in effective demand went down, inventory accumulation share went up significantly (Table 9), the import penetration as depicted in Table 10 continued to be higher than 1993-94 Further of the six medium high and high technology industries only Drugs and medicines was a net exporter

The idea of import dependence can be further analysed by observing the imported input intensity of the Indian manufacturing sector The imported input intensities have been computed for the IOTTs in the following manner:

(∑

∑ )

In equation (1) A is the original input output coefficient matrix where each aij depicts the value of input procured by sector j from sector i and expressed as a ratio of gross value of output of sector j denoted by Xj The coefficient of input aij consists of both imported and domestic inputs Ad is the coefficient matrix of domestic inputs The Ad matrix is not provided by the CSO and has been estimated using the methodology suggested by Bhattacharya & Rajeev (2014) and Veeramani (2016) for the Indian IOTTs (See Appendix C for the

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Table 11

Imported input intensity of manufacturing sub-sectors (Percentage of imported inputs to total input cost)

S No Manufacturing Sectors/Years

Technological Classification

1993-94

1998-99

2003-04

2007-08

2013-14

1

Food Products, Beverages &

Tobacco LT 3

2

Textiles, Textile Products,

Leather and Footwear LT 5 12

3

Wood and Products of Wood, Pulp, Paper, Paper Products,

Printing and Publishing LT 11 12

4 Manufacturing, n.e.c.; recycling LT 10 14 29 16 19

5 Rubber and Plastic Products MLT 11 13 13

6

Coke, Refined Petroleum

Products and Nuclear Fuel MLT 34 36 51 58 53

7

Other Non-Metallic Mineral

Products MLT 17 21 15 16 32

8

Basic Metals and Fabricated

Metal Products MLT 10 16 19 23 24

9 Ships and boats MLT 11 13 41 62 21

10 Chemicals and Chemical Products MT 12 14 12 19 24

11 Machinery, n.e.c MT 12 16 13 19 21

12 Electrical machinery MT 14 12 18 18

13

Rail Road, motor vehicles and

transport equipment MT 11 11 14 17

14 Drugs and medicines HT 19

15

Radio, TV and Communication

equipments HT 15 13 24 27

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17 Average Imported input intensity 10 14 16 21 21

18 Manufacturing 10 12 15 20 25

Source: Same as Table

A clear pattern that emerges from Table 11 is the consistent and considerable rise in the imported-input intensity of the manufacturing sector in aggregate terms (Row 18) At the level of sub-sectors also there has been a consistent upward movement of imported input intensity across the technological spectrum In the

low-technology category all the sectors except Manufacturing, n.e.c.; recycling, the imported input intensity has been considerably lower than the other sectors of the Indian manufacturing Moreover, except Manufacturing, n.e.c.; recycling, the imported input intensity of the low technology sector has been consistently lower than the average imported input intensity (except in the benchmark IOTT year 2003-04) of the 16 classified manufacturing sub-sectors In the medium low technology category except Rubber and Plastic Products, all the sectors displayed much higher intensity of imported inputs during the entire period as compared to all the other sectors and the average imported input intensity Within the medium technology and high technology category Rail Road, motor vehicles and transport equipment and drugs and medicines showed relatively low imported input intensity of production The other sectors in the high technology category i.e Radio, TV and Communication equipments and other high-tech manufacturing were either close to or higher than the average imported input intensity across sectors The low technology sectors were less imported-input intensive than resource based medium low

technology sectors and high skill medium and high technology sectors in general

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Rakshit (2007), Nayyar (2012), Ghose (2015) and Talreja (2018) have shown that final demand has been more important driver of service sector demand as compared to intermediate demand Further, Talreja (2018) has shown that private consumption and exports have been two most important sources of service sector demand Moreover, the previous section shows that manufacturing dependence on service sector inputs did not increase during the post-reform period In relation to this finding Kucera and Jiang (2019) show that developed manufacturing sector dependence on service sector in terms of its share in manufacturing production has been much higher than for manufacturing in emerging economies which includes India between 1995 and 2009 These findings suggest that the nature of service sector growth in India is different from the developed economies More specifically, because of its lack of integration with the production in different sectors specially

manufacturing of the Indian economy as compared to its rapid growth in India and the pattern of manufacturing dependence on services observed in various developed economies by various studies like Park (1989), Park (1994), Francois & Reinert (1996), Guerrieri & Meliciani (2005), Driemeier & Nayyar (2018) Kucera & Jiang (2019) Studies like Rakhsit (2007), Nayyar (2012) and Ghose (2015) have suggested that rapid services sector growth has accompanied greater inequality in India This has happened through both changing demand pattern that has fuelled the growth of services and service sector growth itself benefitting relatively small section of the Indian population Talreja (2018) and the present analysis of manufacturing sector show that value added composition within manufacturing and services has disproportionately shifted towards high skill and less employment intensive sectors during this period This indicates towards a crude evidence of production related inequality in the Indian workforce The claims and arguments made so far by analysing the aggregate figures can be further verified by a detailed analysis of the household consumption across various classes This will help in understanding if the principle of effective demand has worked in determining the aggregate demand through the pattern of demand at the level of households belonging to different classes

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added medium and high technology manufacturing has become more important during the post reform period It needs to be seen if this has also changed the export orientation of the Indian economy

Table 12 below looks at the export diversification and concentration indices for the Indian manufacturing during the post-reform period The export diversification index is based on Moneta and Stepanova (2018) index of diversification of commodities in household food expenditure

Where Si is the share of ith commodity in total manufactured exports and n is the total number of commodities A greater value of D indicates greater diversity ranging between and The index of

concentration is based on the Herfindahl-Hirschmann Index using the UNCTAD definition of the index This is as follows:

(√∑ ( ) ) √ √

Where xi is the value of ith commodity exports, X is the total value of exports and n is the total number of commodities A higher value of H ranging between and1 depicts greater concentration of exports towards lesser commodities

Table 12

Indian Manufacturing Exports Diversity and Concentration index over years Index/Year 1993-94 1998-99 2003-04 2007-08 2013-14

Exports Diversity

Index 0.85 0.85 0.87 0.88 0.88

Exports Concentration

Index

0.11 0.11 0.17 0.13 0.11

Source: Same as Table

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sector is export oriented if the ratio of net exports to domestic output is greater than five percent This method has been used to identify export oriented sectors in the Indian manufacturing in Table 13 below

Table 13

Export orientation of manufacturing sub-sectors (Net Exports as a percentage of Domestic Gross Output)

S No Manufacturing Sectors/Years

Technological Classification*

1993-94

1998-99 2003-04 2007-08

2013-14

1 Food Products, Beverages & Tobacco LT -1

2

Textiles, Textile Products, Leather and

Footwear LT 18 24 23 16 19

3

Wood and Products of Wood, Pulp, Paper, Paper Products, Printing and

Publishing LT -8 -14 -11 -9 -11

4 Manufacturing, n.e.c.; recycling LT -5 -3 -60 -6 14

5 Rubber and Plastic Products MLT -17

6

Coke, Refined Petroleum Products and

Nuclear Fuel MLT -37 -40 -4 11

7 Other Non-Metallic Mineral Products MLT 27 27 -3

8

Basic Metals and Fabricated Metal

Products MLT -5 -17 -11 -15 -19

9 Ships and boats MLT -21 -31 -374 -122 -255

10 Chemicals and Chemical Products MT -10 -11 -6 -16 -19

11 Machinery, n.e.c MT -34 -47 -10 -26 -34

12 Electrical machinery MT -11 -15 -3 -9 -11

13

Rail Road, motor vehicles and transport

equipment MT -21 -1

14 Drugs and medicines HT 10 12 18 23

15

Radio, TV and Communication

equipments HT -11 -37 -26 -99 -170

16 Other high-tech manufacturing HT -2 -83 -207 -36

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Source: Author‟s calculation based on IOTT 1993-94, 1998-99, 2003-04 and 2007-08, CSO, MOSPI, GOI and IOTT 2013-14 Kanhaiya and Saluja (2016)

*LT- Low-technology; MLT: Medium-low technology; MHT: Medium high technology; HT: High technology Note: The sector “Other high tech manufacturing” is not strictly comparable the definition in1993-94 and 1998-99 on one hand and 2003-4, 2007-08 and 2013-14 on the other hand The former definition contains “watches and clocks” and “office computing machinery” and the latter definition is “watched and clocks”, “medical, optical and precision instruments” and “aerospace”

Table 13 above shows the ratio of net exports by domestic gross output for each sector for the benchmark IOTT years during the post-liberalization period All the negative values in Table 13 reflect sectors where the value of imports has been greater than value of exports The only two sectors that consistently

remained export oriented during the post-reform period are Textiles, Textile Products, Leather and Footwear and Drugs and medicines The former being a low-technology sector and the latter being a high technology sector Analysing the IOTTs it has been seen that across the benchmark years the share of the former in manufacturing value added declined from 17 percent to 12 percent but remained constantly much larger than the latter which hovered around percent across the IOTT years A relatively much smaller segment of high technology manufacturing has been export-oriented during this period while a much larger low technology sector saw a decline in the value added share despite being export oriented18 Another, clear and noteworthy pattern here is the consistently high degree of import penetration faced by medium and high technology sectors like Chemicals and Chemical Products, Machinery, n.e.c and Electrical machinery during this period High tech sectors like Radio, TV and Communication equipments saw a steep rise in the share of net imports during this period Wood and Products of Wood, Pulp, Paper, Paper Products, Printing and Publishing which is low technology sector also faced considerable degree of import penetration during this period but also saw steep decline in its value added share in manufacturing Ships and boats sector belonging to medium low-technology also faced clear and consistently high level of net import but remained below one percent in terms of value added share in manufacturing across IOTT benchmark years19 The broader understanding that emerges from this analysis suggests that the structural adjustment of value added shares within manufacturing during post-liberalization era from low technology sector towards higher spectrum of technology did not translate into an export oriented demand regime, but an import-dependent demand regime The structure of export orientation did not change as

18 India KLEMS database also shows a similar decline in the value added share of Textiles, Textile Products, Leather and Footwear and Wood

and Products of Wood, Pulp, Paper, Paper Products, Printing and Publishing during this period both in real and nominal terms The data on drugs and medicines and ships and boats is not separately available in India KLEMS database

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only the same two broad sub-sectors remained export-oriented The manufacturing sector as a whole was far from being export oriented as net exports were in the negative zone as depicted by all the benchmark years Clearly, the structural inertia in the export orientation of the Indian economy suggests that the domestic demand pattern has been an important factor in determining the structural change within Indian manufacturing

V SUMMARY AND DISCUSSION

The global manufacturing has witnessed important structural changes since the 1970s, both in terms of geographical re-location of production and composition in terms increase in output share of technologically sophisticated groups of manufacturing sectors As discussed in Section II, there has been structural shift of manufacturing production from developed to the developing world, a trend which has been dominated by Asian economies and more specifically the East Asian economies This period also saw a global increase in the share of service sector, as services became fundamentally more important in the global structure of production (Felipe et al 2013 and Driemeier & Nayyar 2018) At the same time, the post-liberalisation era after 1991, in India witnessed a stagnation of output and employment in the manufacturing sector share, accompanied by a rapid rise in service sector output share and modest increase in its employment share As discussed in Section II, there are various studies that have analysed the trajectory of Indian manufacturing sector output and employment growth during the post-reform period But there has been an absence of an analysis of structural change in the Indian manufacturing sector anchored to the global change in manufacturing sector production and an analytical framework that can explain industrial transition towards higher levels of economic development through manufacturing sector led success This paper has presented an analytical framework to assess the structural change within the Indian manufacturing sector during the post-reforms period This framework identifies that mutually reinforcing demand and productivity regimes in the manufacturing sector lead to a virtuous growth process in the economy with both employment and labour productivity expansion The important ingredients of the process that lead to this mutually reinforcing relationship like technological upgradation, capital deepening, use of modern service inputs and export expansion and diversification have been the focus of enquiry in this paper

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The sectors in this analysis were classified into technology groups based on technological sophistication from low technology to medium and high technology groups Such an analysis of structural change of the Indian manufacturing against the global structural change in manufacturing has been absent This paper provides some useful insights in understanding the implications of the post-reforms structural change and growth process of the Indian economy The analysis of compositional change within Indian manufacturing finds that during the period from 1990-91 to 2014-15 also the post-liberalization era witnessed an adjustment in composition of value added in favour of medium & high technology groups of manufacturing at the expense of low technology

manufacturing The share of the former increased from 25 percent to 35 percent and that of the latter fell from 45 percent to 35 percent Despite this, low technology manufacturing continued to support bulk of manufacturing employment The share of low technology group fell from 70 percent to 65 percent of manufacturing

employment during this period This shows a persistent and widened presence of large labour productivity gaps within the manufacturing sub-sectors across technology groups This observation indicates worsened intra-sectoral distribution of value added in the Indian manufacturing The analysis of the interplay of the productivity regime, demand regime and employment growth of the manufacturing sector shows that there was an

improvement of employment elasticity of output in the aggregate terms But the analysis at the level of technology groups shows that periods of high employment elasticity were an outcome of extremely low or negative labour productivity growths in different technology groups in different periods The aggregate outcome does not reflect the lack of sustained labour productivity and employment generating growth within the

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happens elsewhere in the economy through introduction of new production processes In terms of capital

deepening, the analysis of capital intensity growth and capital productivity growth shows that the low technology group and medium low technology group also faced a sustained increase in capital intensity during this period This increase reflected labour substitution as opposed to technological upgradation This is depicted by negative capital productivity growth in these technology groups This process depicts a change which has been

unfavourable for low skill and low productivity employment within the manufacturing sector Another important analysis in this paper has been the study of structure of dependence of manufacturing sector on modern and traditional services, given the increased role of services in global productivity regime and their rapid growth in India This analysis shows that the Indian manufacturing sector was much more dependent on traditional services as opposed to modern services during the entire period Additionally, it was found that there were greater synergies and inter-dependence between medium and high technology group and modern services as compared to low technology manufacturing But the overall dependence of the manufacturing on modern services did not intensify during this period This structural inertia in dependence pattern has been a peculiar finding about India‟s productivity regime which has been quite distinct from global evidence and rapid growth of services in the domestic economy

The analysis of the demand regime has been to understand the nature of effective demand faced by the Indian manufacturing during the post-reforms period The principle of effective demand contextualises the channel through which production process affects aggregate demand and output expansion The distribution of productive gains to different classes in the production process determines the composition and size of aggregate demand in this framework Looking at the domestic absorption and export orientation of the Indian

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The main insight of that these analyses convey is that the productivity and demand regimes of the Indian manufacturing could not sustainably create a productivity enhancing, employment generating structural change within the manufacturing sector The structural change towards higher share of high technology manufacturing production did not alter the export structure as compared to the economies like Japan, South Korea and Taiwan which simultaneously altered their production and export structures India continued to stay a net importer of manufactured products as the value added composition changed From the point of view of inclusiveness this change was skill biased and the gains from this change were skewed towards smaller sections of the workforce Moreover, the demand regime progressively became more import-dependent This calls for a serious enquiry of the demand structure of the Indian economy, specifically the pattern of consumption demand, which is an important element of the demand regime An important issue that this study did not look at is the environmental sustainability of the structural change through manufacturing development, as this study looked at a more conventional analytical framework of economic development The economic development paradigm remains incomplete without internalising environmental sustainability of growth with inclusiveness in its analytical framework Inclusiveness and sustainability taken together are the important challenges facing economic development

VI APPENDIX 1 Appendix A

Classification of manufacturing sectors based on technology intensity

The classification of manufacturing sectors into technology groups has been provided in Table 11 below:

Table 11

OECD Classification of Manufacturing Industries based on Technology

S No

Technological Classification

Industries

1

Low-Technology

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Textiles, textile products, leather and footwear

2

Medium-low technology

Building and repairing of ships and boats Rubber and plastics products

Coke, petroleum products and nuclear fuel Other non-metallic mineral products Basic metals and fabricated metal products

3

Medium-high technology

Electrical machinery and apparatus, nec Motor vehicles, trailers and semitrailers Chemicals excluding pharmaceuticals Railroad equipment and transport equip, nec Machinery and equipment, nec

4

High technology

Aircraft and spacecraft Pharmaceuticals

Office, accounting and computing machinery Radio, TV and communications equipment Medical, precision and optical instruments Source: OECD (2011, https://www.oecd.org/sti/ind/48350231.pdf)

The technology group Medium-high technology has been referred to as Medium technology in this paper The India KLEMS database does not provide data separately on any of the high technology group sub-sectors These sub-sectors in India KLEMS database are part of the sectors provided in group In India KLEMS database, “Aircraft and spacecraft” is a part of “Motor vehicles, trailers and semitrailers” compositely called “transport equipment”, “Pharmaceuticals” is a part of “Chemicals and chemical products”, “Office, accounting and computing machinery” is a part of “Machinery and equipment, nec.” and “Radio, TV and communications equipment” and “Medical, precision and optical instruments” are parts of “Electrical

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previously The UNIDO website http://stat.unido.org/content/focus/classification-of-manufacturing-sectors-by-technological-intensity-%2528isic-revision-4%2529;jsessionid=4DB1A3A5812144CACC956F4B8137C1CF

also provides a similar technology group classification specifically for developing regions where sometimes the high technology industries are not well developed or absent

2 Appendix B

Employment elasticity, labour productivity growth, output growth and employment growth have been computed using the following methodological basis provided by Upender (1998) and Kapsos (2005)

Generalized computation of output growth, employment growth and labour productivity growth:

Where for each variable of gross value added/output denoted by Y, employment denoted by L and labour productivity given by Y/L and equation (1) is separately estimated for each of these variables,

respectively for five year intervals T denotes time trend in equation (1) The  estimated for each variable gives the growth rate of each variable Employment elasticity is denoted by ε is estimated as n/gy where n denotes employment growth rate and gy denotes output growth rate

The interpretation of employment elasticities under different scenarios has been borrowed from Kapsos (2011) and is presented in Table 12 below:

Table 12

Interpreting employment elasticities GDP growth

Employment elasticity

Positive GDP growth

Negative GDP growth

 <

(-) employment growth (+) productivity

growth

(+) employment growth (-) productivity

growth

0 ≤ ≤1

(+) employment growth (+) productivity

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growth growth

>

(+) employment growth (-) productivity

growth

(-) employment growth (+) productivity

growth Source: Kapsos (2005)

3 Appendix C

The methodology for estimating matrix Ad of domestic input coefficients for the Indian IOTTs based on Bhattacharya & Rajeev (2014) and Veeramani (2016)

(

)

Where Ii depicted in equation (1) is the ratio of total intermediate use of input i denoted by IIUSEi in all the n sectors of the economy to the sum of total domestic gross value of output of sector i denoted by GVOi and total value of imports of sector i The total IIUSEi is the sum of all the intermediate use of sector i in all the n sectors of the economy from domestic and imported sources Equation (2) depicts the estimation of the total intermediate use of sector i in all the n sectors of the economy denoted by DIIUSEi In equation (4) Matrix D is the n*n diagonal matrix with ri as the diagonal elements, where ri as depicted in equation (3) denote the ratio of DIIUSEi to IIUSEi for each sector i Finally, equation (5) gives the n*n Ad matrix of domestic input coefficients where each element is denoted by dij, where each dij=Dij/Xj, Dij is the domestically sourced use of intermediate use of sector i as an input in sector j and Xj is the total gross value of output of sector j Matrix A is the n*n matrix of total input coefficients sourced from both domestic and imported sources, where each element is denoted by aij=Aij/Xj and Aij is the intermediate use of sector i in sector j as an input

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Table 13

Indirect Employment generated by broad sectors of the Indian economy (as a percentage of total indirect employment generated in the economy)

Sectors/Year 1993-94 1998-99 2003-04 2007-08 2013-14 Agriculture,

Forestry and

Fishing 4

Mining &

Quarrying 0.04 0.02 0.11 0.09 0.05

Manufacturing 57 60 60 55 61

Construction 13 10 12 17 16

Utilities* 1 0.5 0.3

Services 23 25 24 24 20

Source: Author‟s calculation using India KLEMS database and IOTTs, various years *Electricity, Gas and Water Supply

Table 14

Manufacturing sub-sector indirect employment (in millions)

S No Manufacturing Sectors/Years

Technological classification 1993-94 1998-99 2003-04 2007-08 2013-14

Food Products, Beverages and

Tobacco LT

25.4 38.5 44.6 41.8 56.5

Textiles, Textile Products,

Leather and Footwear LT

11.0 9.9 13.1 16.6 14.5

3 Wood and Products of wood LT

0.2 0.2 0.3 0.8 3.1 Pulp, Paper,Paper

products,Printing and Publishing LT

0.7 0.7 0.9 1.6 0.4

5 Manufacturing, nec; recycling LT

1.6 2.7 1.6 5.0 7.2

Coke, Refined Petroleum

Products and Nuclear fuel MLT

1.2 1.1 1.4 2.8 1.8

7 Rubber and Plastic Products MLT

0.5 0.5 0.7 1.7 3.8

Other Non-Metallic Mineral

Products MLT

0.6 0.5 0.3 0.5 0.3

Basic Metals and Fabricated

Metal Products MLT

1.1 0.8 1.5 2.9 2.1

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Products 2.3 2.0 3.7 3.4 3.4

11 Machinery, nec MHT

1.6 1.6 2.0 3.1 3.7

12 Electrical and Optical Equipment MHT

2.0 1.9 3.6 2.9 1.8

13 Transport Equipment MHT

1.9 1.6 2.4 3.4 4.9

14 Manufacturing

50.4 61.9 76.0 86.4 103.4 Source: Author‟s calculation based on India KLEMS database and IOTTs 1993-94, 1998-99, 2003-04 and 2007-08, CSO, MOSPI, GOI and IOTT 2013-14 Kanhaiya and Saluja (2016)

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