India’s ICT sector: “How does it induce aggregate output, productivity, and spillovers into the manufacturing sector?”

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India’s ICT sector:

“How does it induce aggregate output, productivity, and

spillovers into the manufacturing sector?”

Master’s Thesis

Msc. International Economics and Business

Jaap van der Velden, 1323652 Phone nr: 06 – 4111 7214 E-mail: jaapvdvelden@gmail.com

University of Groningen Groningen, the Netherlands

August 2007

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Acknowledgements

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Abstract

This master’s thesis examines the impact of the Indian Information and Communication Technology (ICT) sector on the recent resurgence of its economic growth. The period from 1998 to 2006 has been chosen for the analysis. We examine the growth contribution of the ICT sector to GDP and labour productivity in the total economy and the manufacturing sector, along with the effect of ICT investment on ICT using sectors. Moreover the spillover effect of ICT investment on the registered manufacturing sector in terms of productivity gains is also analysed, using a growth accounting framework. The ICT producing sector grows at a faster pace compared to the aggregate economy and manufacturing sector and consequently contributes significantly to the aggregate and manufacturing growth. The contribution of ICT investment to the using sectors is observed to be increasing over time. Also the growth of Total Factor Productivity in total manufacturing output shows a spillover effect, however it is weak.

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Information and Communication Technology (ICT) sector2. In Western media the portrayal of India as an Information and Communication Technology (ICT) outsourcing destination gives the country most of its fame. With the increasing evidence on the ‘New Economy’s’3 influence on productivity surges and economic growth over the past decade4, India with its growing ICT industry can be regarded as a desirable case to exemplify this on. Also, recent papers in this field show that India often holds a special position, in that, even though it is regarded as a low income country, growth of the ICT sector, productivity and contributions to growth reveal numbers that can equal or often exceed western economies5. Moreover the availability and abundance of data in this country has clearly increased over the past ten years, making full methodologies easier to use. This will mean that a deeper analysis of the dynamics of ICT in India and the sector’s real influence should be further developed in this paper.

The purpose of this paper is to unearth the impact of India’s ICT sector on the recent surge of growth inside the aggregate economy. There is strong reason to believe6, and initial evidence, that the effects of this sector’s investments are larger than previously revealed. The most recent conclusions on ICT sector’s influence on GDP growth in India dates back to 2002 based on data until 1999 (Arora A. & Athreye S., 2002). They highlighted the importance of future research in this area due to less visible productivity improvements with powerful long-term benefits. In this paper emphasis will be put on direct growth contribution of ICT sector

1_{Goldman Sachs (2006).}

2_{The ICT sector industries consist of computer services, computer software, computer hardware and} communications, and this term will be valid across the entire thesis. When analyzing these definitions they appear in national account level as investments by households, net exports, companies and government. A more narrow definition will be assessed in the data and variables section.

3_{A term often used to define globalization and innovation in information technology, often associated with low} unemployment and constant economic growth.

4_{See for example Oliner at el (2000), Oulton (2001), Virmani (2004), Jorgenson et al (2001, 2002, and 2005),} Van Ark et al (2003).

5_{See also: Jorgenson & Vu (2005), Unel (2003), Goldar & Kumari (2003), Kumari (2004), Arora & Athreye} (2002).

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to aggregate and manufacturing7 output, along with the ICT investment contributions to the manufacturing sector (Oliner at el (2000), Oulton (2001), Virmani (2004), Jorgenson et al (2001, 2002, and 2005), Van Ark et al (2003)). Also, in line with Stiroh (2001), we examine the ICT spillovers into ICT using sectors8 by use of Total Factor Productivity (TFP). Earlier studies in this line generally focus on Western economies and it will be interesting to see how India as a low-income, yet emerging market, is affected by this. This brings us to the contributions, investment, and TFP, related to the ICT sector’s influence, and the subdivision of the paper into these three major sections. For the remainder of the introduction the structure of the rest, per section and contents, will be explained.

It has become clear that due to relatively limited availability of results of India’s ICT producing sector on aggregate growth and the spillovers that ICT’s innovations, products and technology can create, that new results can be achieved. The ICT producing sector directly contributes to aggregate and manufacturing sector growth in terms of output and labour productivity growth. Indirectly, investment in ICT by ICT using sectors contributes to output growth. Likewise, Total Factor Productivity is an indirect measure of ICT’s contributions to growth.

The first set of analyses will be directed towards the direct effects of ICT sector growth on aggregate and manufacturing growth in terms of output and productivity. This can be an indicator that even though ICT is a rather unremarkable sector inside the economy as a whole, in terms of its size, its share has grown and possible spillovers due to its large share in exports9 makes the reasoning stronger. In 1999, back when Arora and Athreye’s (2002) research indicated ICT revenues constituted of only a relatively small share of GDP (1.2%), it was concluded that the ICT sector had little influence on the aggregate economy although in the future the sector could pursue indirect long-term benefits for industrialization and growth. The figures for 2006 indicate the ICT sector’s revenue share of total GDP has risen to 4.8% with ICT revenues rising 625% in nine years time from US$4.8 billion in 1998 to US$36.3 billion in 2006 (Nasscom, 2006). The analysis will entail not only GDP and manufacturing

7_{Manufacturing as example of the ICT using industries, manufacturing is one of the highest users of ICT,} further will be explained in the data section.

8_{Stiroh (2001) lays out this framework; his works will be thoroughly discussed in the methodology section of} this paper. Other scholars that have assessed (ICT) spillovers include Siegel (1991), Brynjolffsen & Hitt (2000a), Van Leeuwen et al. (2003). However our work is based on the same initial approach of TFP growth

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output levels but more importantly GDP and manufacturing growth. To develop the direct effect, output and productivity levels are constructed for the last decade and more importantly the contribution of the ICT producing sector’s output and productivity growth to aggregate and manufacturing sector’s growth.

For the second analysis, the investment effect, ICT investments are derived into ICT capital growth inside the manufacturing sector. They are estimated, using the growth accounting model, as a share of total manufacturing output growth. Several substitutions are to be made, with the analysis of ICT investment to ICT expenditure using the perpetual inventory method and investment-to-expenditure ratios. The WITSA Digital Planet Reports (2002, 2006) provide ICT expenditures. The growth accounting framework estimates the share of ICT capital, as an input, in total manufacturing output in order to develop the ICT sector’s contribution to growth of the sector as a whole. We are expecting to see a large contribution10 of ICT capital to manufacturing output growth due to grown importance of the sector in the manufacturing sector, which will be discussed more in detail in the literature review.

The indirect effect, or spillover effect, defines Total Factor Productivity’s (TFP)11 contribution to manufacturing output in the growth accounting model. With positive externality effects such as efficiency gains, reverse engineering, organizational learning, and technical progress to name a few, investments in ICT by the using sectors can create significant spillovers into these sectors. In this analysis the separation will be made between the inputs of labour and capital (once again subdivided into ICT and non-ICT capital) and TFP on the one hand and manufacturing output on the other. The Annual Survey of Industries (ASI) of India and Groningen Growth and Development Centre (GGDC) data help to unearth total output and subsequently Jorgenson and Vu (2005) assist in narrowing the ICT component down. The growth of TFP, and a major share inside the growth accounting framework, is the main source of a possible spillover from ICT into the manufacturing sector. Due to the availability of only short time series, the full spillover methodology cannot be exercised yet TFP growth is a strong indicator for the existence of these affects. TFP growth in India’s manufacturing sector has been on the rise and a continuation of this increase can signify further importance of ICT in India.

10_{Referring to a contribution larger than its share in volume and growth as initially compared to the} manufacturing sector.

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II. Literature Review

2.1 India, ICT and Economic Growth

With India’s current surge in aggregate economic growth it is a highly interesting nation to highlight and investigate the factors that drive this growth, more specifically in terms of its renowned ICT sector. Consequently, this issue has been subjected to previous research. In what follows, we present a brief review of past studies in the context of ICT’s contribution to aggregate output and productivity growth and spillovers into the ICT using sectors, with reference to low income countries in general and India in particular. We begin the section with a discussion on the factors that drive ICT penetration in low income countries and how these factors helped ICT penetration in India, as identified by previous literature. The present study will attempt to fill some of the gaps identified in the literature, and will be discussed in detail in the next sections of this thesis.

Economic Growth and ICT Penetration in India

Despite being the second fastest growing economy in the world (after China), India is considered to be one of the low income countries, as the level of per capita income is still relatively low12. Further, the country is characterised by a lopsided economic structure with 60 per cent of the workforce employed in the agricultural sector, contributing only 18 per cent to GDP. The manufacturing sector employs 17 per cent of the workforce, but contributes almost 28 per cent to GDP and the service sector employ 23 per cent and contributes 54 per cent to GDP. The Indian economy has witnessed significant policy changes at various magnitudes since independence, the most significant shift being the liberal economic reforms in the early 1990s. The recent surge in its economic growth is, therefore, often attributed to its liberalization policies that were effectuated in the 1990s (Gordon & Gupta (2003), Virmani (2004), Topalova (2004), Rodrik et al (2004)). However, there is a growing view that the country needs to take account of its infrastructure, rising wages and house prices, its competitive position in certain sectors, overheating of the economy, and corruption at all levels of society to sustain this growth (Bhattacharya et al. 2005). Despite this prevailing scepticism on whether the country would be able to sustain its current growth path, there has been some consensus that India will be one of the world’s major players in a number of

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decades (e.g. Wilson et al., 2006)13. As compared to China, the other large emerging Asian market, India has achieved growth and a fair sized middle class based on the rapid expansion of the service-producing industries, and also having rather modest levels of investment (Bosworth et al, 2007). ICT in particular seems to play an important role in India’s economy with regard to productivity growth. Compared to a group of developed and developing countries, the contribution of ICT to productivity stood out for India with this number growing over the decades (Jorgenson et al, 2005).

Along with its economic growth surge, the information and communication technology (ICT) sector has been penetrating at a remarkable scale in Indian ICT using sectors. Internet use has exploded over the last decade, coming from 0.1% of the population using internet in 1998 to 3.6% in 200614, the highest increase over this period as compared to other developing nations in Asia, yet still relatively low. The literature on ICT diffusion has highlighted many factors that can affect ICT penetration, which includes the prices of IT products (Jorgenson, 2001), human capital, the level of income, openness to trade (Caselli & Coleman, 2001), and even the cultural ambiance of the country (Erumban & de Jong, 2006). The digital divide points at a barrier between citizens from different socio-economic backgrounds with regard to their opportunities and abilities to be wired, the underlying infrastructure, and capacity within nations and at a later stage this divide also was directed between developed and developing countries15 (Selhofer et al., 2002). With a sharp decrease in ICT prices and an upturn of the world economy, capacity for ICT production in developed countries has reached a certain threshold, moving ICT production and services to developing nations, making ICT products for commerce and private use more affordable and thus being the founder for the sharpest increase of ICT use in those countries, yet a digital divide surely still exists (McNamara, 2003). Following the above mentioned factors for ICT penetration, a general line in developing nations has been traced that is the source of low rates of getting wired and holding the digital divide in place. These obstructions include; low investment in ICT where the longer term savings are forgotten, no government promotion of innovation and ICT, no knowledge of new ICT developments and thus old ICT, world prices in place, and no openness to FDI in ICT related industries (McNamara (2003), Chandrasekhar et al. (2001)).

13_{Goldman Sachs moreover states that besides India, China will be the major growth engine for world growth.} The rates highly depend on whether in the new worldwide equilibrium the new power structures are able to hold if cooperation is increased between new blocs and countries such as India step up liberalizations in certain sectors.

14_{Internet world statistics (2007)}

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This indicates that the low ICT penetration in India can be observed because of this multitude of factors among which the level of income may be a prominent one.

A number of factors however positively distinguish India from several low income or developing countries with regard to these new industries in particular. To list a few, English as one of its nationally spoken languages, a fair degree of entrepreneurial and managerial capabilities, strong links with major markets, and large numbers of expatriates working in high-tech and managerial positions in the west (Arora & Athreye, 2002). India has a relatively large software sector which is mainly focused towards exports and less so for the domestic market, which can be seen from Table 1. Yet India can be generally compared to other developing nations when it comes to hardware, as the largest part is imported and is prone to world prices. This is, however, in line with expectations as the country has a comparative advantage in software with its vast human resources; it, for instance, has the largest output of engineering graduates worldwide. Thus the fact that India is a low-income, developing economy with at the same time elements that can only be traced to developed economies, makes is an interesting country to further highlight, especially in the fields of ICT.

Thus the importance of ICT has been growing in the context of India’s ongoing economic growth process, and consequently there appeared a number of studies that analyse the growth of the ICT sector in India and its relationship with aggregate growth. Arora and Athreye (2002) observed only a modest impact of ICT on national growth. However, this result was based on data prior to 1999, during which the contribution of ICT to GDP was only 1.2 per cent and hence as acknowledged by Arora and Athreye (2002) the real effects will be more visible only after a longer time period. The country has witnessed tremendous growth in the ICT sector after 1999; it has grown by 656 per cent over 1998-2006, contributing 4.8 per cent of GDP in 2006 (Nasscom, 2007). Basant et al. (2006) use a unique new data set on manufacturing firms in India and Brazil to investigate the determinants of ICT adoption and the impact on performance. The study reveals that the ICT spending in India is approximately 3.7 per cent of GDP16_{currently and ICT adoption has steeply increased over time. A strong}

relation between ICT capital and productivity exists and especially for India as a developing

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country one can see a higher rate of return on ICT investment when compared to major developed nations.

Relatively few studies have been conducted to quantify the contribution of ICT to growth in India. The strong link between the growth of developing countries, including India, and decreasing ICT prices that foster ICT investment have been highlighted by Basant et al (2006). Joseph (2002), though, maintaining the view that ICT can entail growth, raises concerns regarding its effect on other sectors. India’s ICT sector is highly export oriented and due to its extreme growth in output and highly skilled manpower other sectors may have suffered, significantly improving the ICT sector’s performance at the sake of other sectors (Joseph, 2002).

Among the developing countries, India stands out in terms of GDP growth and ICT sector growth. Yet for data up to 2000 the influence of ICT investment on Total Factor Productivity Growth (TFPG) remains ambiguous. In their analysis on world economic growth, Jorgenson et al. (2005) have also studied the case of India. Using the growth accounting framework, world growth is decomposed by analyzing separate blocks of countries, the seven major world economies (G7), seven major developing countries (D7), and other geographically dispersed groups of countries, totaling 110 world economies. The consequences of investment in ICT on world economic growth is found to be profound, yet labor and capital (inputs) dominate in this respect and productivity lags behind. When assessing India (part of D7), they see a different picture as compared to other developing countries. Both the growth of ICT investment and TFPG in total growth has started to play a much larger role, especially over the last decade.

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growth has exploded over the past years, yet is still very much dependent on worldwide ICT prices, domestic demand and foreign investment (Das, 1999).

India’s ICT producing sector is highly recognized for its international character and the largest share of ICT production is thus exported. This share of exports is to a certain degree dependent on the relative absence of a domestic market for ICT services17, especially in ICT software, which in its turn is fully in line with what can be seen in other low income countries. From the subsequent full growth models in section 2.2 it should become further clear what direction is being followed and why the Indian ICT sector is the area of focus besides the differentiating points already mentioned in this section.

2.2 ICT and Economic Growth

There is growing evidence from developed countries that the use of ICT has helped improve productivity gains in the US, Europe, Japan and Australia. The recent upturn of world economic growth is often attributed to a continued high rate of decline in ICT hardware, software and service prices compared to other investment goods, both due to technological progress and the phenomenon of outsourcing to high skilled, low wage countries (van der Wiel et al., 2003). In particular the recent empirical literature on economic growth has shown that the growth of the US economy in the 1990s can largely be attributed to the effects of ICT investments (Jorgenson et al. (2001, 2005), Jorgenson and Stiroh (2000), Oliner & Sichel (2000), Colecchia & Schreyer (2001)). A similar story holds true in Europe, though the pace of ICT penetration is lower than that of the US (Van Ark & Melka (2003), Oulton (2001)). An important point that emerges from this literature is that substantial differences exist in ICT penetration and their impact on economic growth even between developed countries (Colecchia et al. (2001), Van Ark & Melka (2003), Jorgenson & Vu (2005), Piatkowski & van Ark (2005)). Therefore, one would not be surprised to see an even bigger gap between the developed and developing world.

Most studies on the contribution of ICT to growth in developing countries have come from Central and Eastern European data. Piatkowski & Van Ark (2005), discuss the Central and Eastern European (CEE) countries and Russia (CEER) and define the role of ICT as a driver

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for improved performance. In the Czech Republic and Hungary, ICT production contributed more to productivity growth than in Western European countries, yet this was still lower than in the US. Through enterprise restructuring and ICT production in manufacturing, ICT investments in new plants were facilitated. Thus also in developing countries the link between ICT investment and aggregate growth is strong. Furthermore, the decline of ICT prices feeds a sustainable growth pattern which can be seen by internet usage and PC ownership increasing sharply18 (de Vries et al, 2006).

Average Labour Productivity (ALP)19_{growth and Total Factor Productivity Growth (TFPG)}

are part of the growth indicators within the contributions that ICT use has on aggregate growth. With ALP being a straightforward, direct productivity tool, it will not be thoroughly discussed in this section, yet TFP is part of output growth in the growth accounting model, as discussed earlier (together with labour and capital use), and is a major standard to take into account when discussing the ICT sector’s effects on aggregate growth. TFPG is the addition to labour (hours and quality of work) and capital (ICT and non-ICT investments) inputs to arrive at output growth20 and thus TFP can be used to derive a spillover effect. Recent literature on what effects the ICT sector has on aggregate world growth suggests there was a larger share of labour and capital (inputs) involved in gaining economic growth, against the relatively smaller share of TFPG in this model and thus capital deepening was an important source for world growth in general.

In the US the TFPG share to GDP growth over the last 20 years has been rather minimal, as opposed to capital and labour contributions, with this share for most EU nations being even smaller (Jorgenson et al., 2001 & 2005). With regard to developing countries a similar mixed picture emerges. In Central & Eastern Europe and Russia (CEER) TFPG also lags behind when considering the strong growth of ICT investment (Piatkowski et al, 2002). Between the sixteen CEER nations an ambiguous picture emerges, with notably Hungary and the Czech Republic having higher contributions of ICT to productivity. India emerges as one of the developing nations where TFPG contributes almost half of total growth, especially over the most recently studied period, 2000-2004 (Jorgenson et al., 2005). A more thorough look into

18_{Latin American countries represent developing countries in the models of de Vries et al. (2006) where these} sharp increases can be witnessed.

19_{Labour productivity is based on hours worked and the quality of the work delivered.}

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this divergent outcome is necessary to explain why this exists and especially why India stands out as a positive example of TFPG on total GDP growth inside Asia’s lagging growth (Jorgenson et al, 2005). Moreover it will be interesting to see whether this strong TFPG contribution has lasted.

With the emergence of this ambiguous picture, and also separating developed and developing countries, Dorgan et al (2004) mention that ICT investment’s effects on higher productivity alone does not suffice. The addition of good (more efficient) management to ICT investments generates a much higher productivity; on average a 20 per cent higher TFP level will be the result with the return of Indian American managers. A developing country such as India, leaning on its exports for growth and with ICT exports constituting 19 per cent of total exports21, managerial learning in this sector could boast TFP growth enormously and thus is an indicator for the mixed picture (Nasscom, 2006). This factor can significantly explain differing outcomes in different regions of the world, for instance between the US and UK, or India and the rest of developing Asia and can be regarded as a gap in current literature.

Thus, it emerges from a review of current literature on ICT and growth in the developed (US, EU) and developing countries (Eastern Europe, D7) that there is a strong relation between ICT investment and GDP growth, while for TFPG as a share of output growth a rather ambiguous picture remains. India is a country that stands out in Jorgenson et al.’s (2005) paper as a nation where ICT has a stronger impact on growth than other developing countries. For this reason a closer look at India should be taken. Moreover, there has not been any recent study that examines the contribution of ICT to economic growth in India after Arora et al. (2002). The continued resurgence of the Indian economy and its growing ICT segment makes it important to analyze the sources of its growth. The lack of evidence and research on possible spillovers through TFPG, from the use of ICT in India can also be described as a gap in the current literature. Thus there seems to be a need for a full blown in-depth look into India’s ICT sector. For the majority this work should look at what investment effects or indirect, spillover, effects ICT can cause for the Indian economy at large and the ICT using sectors specifically. More recent data can provide new results in order to reveal the sector’s contribution to growth and equally possible TFP growth contributions. By means of the following hypotheses these gaps in the current literature are to be filled.

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III. Hypotheses

From the literature review it is quite evident that, despite the growing importance of the ICT sector in India, there is hardly any attempt to quantify its effect on recent aggregate economic growth and more so the contributions to the ICT using sectors. The mix of findings from the literature review, and the conspicuous absence of studies analyzing the impact of ICT sector growth on India’s aggregate economic growth, helps us derive some testable hypotheses. We derive three main hypotheses. Hypothesis one focuses on the direct contribution effect of the sector on aggregate economic and manufacturing sector growth, the second focuses on the ICT investment contributions into the manufacturing sector, and the third hypothesis focuses on the indirect effect of TFP growth’s contributions to the manufacturing sector.

Hypothesis I

Recent papers on growth in conjunction with relating it to the investments in ICT have concluded a relatively strong relation between the two. Due to investments in ICT, came the emergence of a so-called ‘New Economy’. The well-documented experience of a long period of growth in the 1990s in western countries has been largely attributed to ICT investments (Colecchia et al (2001), van Ark et al. (2003), Jorgenson et al (2005, 2006)). For setting up a foundation of a full growth model, the direct effects of ICT contributions to growth in terms of output or productivity have to be measured. These contributions in the past have proved large when compared to their relative shares in volumes and can be considered first indicators of a relation between the two (Durlauf & Aghion (2005), Jorgenson et al. (2006)).

As mentioned before, the share of the ICT sector in the total economy has been growing remarkably during the last decade. Over the last nine years ICT revenues have risen with an astonishing rate of 625% from INR 198 billion in 1998 to INR 1577 billion in 2006 (Nasscom, 2006), increasing its share in GDP from 1.2 per cent to 4.4 per cent. It is evident from Tables 1 and 2 that India’s ICT sector reveals impressive growth in many ways. The sector even shows the highest growth of all ICT producing sectors worldwide22. Due to India’s openness in this sector, its

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highly mobile labour force23, relatively low wage and housing rates compared to international standards, and increasing quality and productivity of work, the future indeed looks bright for the sector’s continued performance. Consequently, the sector’s contribution to aggregate employment is also increasing, further suggesting the higher importance of India’s ICT producing industry. There is a significantly higher growth trend of employment in the ICT industry as opposed to the aggregate and manufacturing levels of employment, which is depicted in Table 3.

Following the WITSA digital planet report (2002, 2006), we consider the manufacturing sector as the largest ICT using sector in India24_{. India’s manufacturing sector has shown tremendous growth}

rates over the last years (Table 4) and has a high potential with output in this sector growing sharply year-on-year25_{. Moreover ICT is more widely used in the manufacturing compared to other}

industries and chiefly for India ICT use in manufacturing has sharply increased (Basant et al., 2006). Recent studies indicate the profound performance contributions the use of ICT has on the sections of the manufacturing sector that use ICT intensively as compared to the manufacturing sectors using no or insignificant amounts of ICT (Baldwin et al., 2001). India has already positioned itself against China’s manufacturing sector as being more competitive in the lower-volume, intensive-technology manufacturing sector (KPMG, 2005)26.

India is one of the major exporters of ICT related products, mainly software and services to the international market, suggesting the importance of the sector being competitive. This remarkable growth in output and employment in India’s ICT producing sector, along with its high export intensity, tends to suggest that the sector should show better productivity performance (Jorgenson et al, 2006). Moreover, this indicates that the direct effect of this sector on aggregate and manufacturing sector output and productivity growth will be substantial and increasing over time Hereby, we formulate our first main hypothesis that looks at the direct effect of the ICT producing sector on aggregate and manufacturing growth;

23_{AMI Partners (2007) reveals outcomes of internal research, based on Nasscom data, from their annual reports} that the mobility of the Indian high skilled workforce is one of the highest in the region. Moreover Indian employees are quite mobile, whose move can best be understood by the enormous growth of typical ICT cities such as Bangalore, Pune, and Mysore (van Dijk, 2007).

24_{According to the WITSA Digital planet reports (2002, 2006) manufacturing is the largest ICT using industry,} closely followed by transport and communication, and government.

25_{It remains to be understood though that especially in services, trade and finance industries a sharp share} increase is to be witnessed, as was the case for the USA and Europe a decade ago (Stiroh, 2001).

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Hypothesis 1: The growth in ICT producing industries will increase its contribution to the

growth of the aggregate economy and the manufacturing sector in terms of output and productivity

Hypothesis II

As discussed in the literature section, there are more indicators that help one understand how the manufacturing sector has influenced the national economy by using ICT. Using the growth accounting methodology27_{many scholars have estimated the influence by using ICT on national}

economies, the world economy or sectors of the economy28_{using ICT investment data and}

generating the contributions to output, inputs and Total Factor Productivity (Solow (1956), Barro (1999), Oliner & Sichel (2000), Jorgenson (2001), Oulton (2001), Van Ark et al (2003), Jorgenson et al (2005)). ICT investments, in the form of ICT capital, are frequently associated to this by contributing to growth.

Thus apart from the contribution of output and productivity growth in ICT sector to aggregate growth, the growth of this sector is expected to have a significant impact on ICT using sectors taking regard of a set of other variables. This will come in the form of increasing investment by the ICT using sectors. As ICT related products and services gradually become cheaper and their diffusion increases in the economy, this should reflect on the contribution of ICT investments in ICT using sectors. Thus an appropriate manner to define the ICT sector’s contribution to economic growth is to define ICT investments and its contribution to growth in other sectors. Recent sources show that ICT investments in the manufacturing sector in India are on the rise; Table 2 shows an increase of ICT expenditures from INR149 billion in 2001 to INR 471 billion in 2006. Jorgenson et al. (2005) describe that a stable ratio between investment and expenditure is traceable. Therefore, while investigating the effect of the growth of the ICT sector on economic growth in India one would expect an increasing contribution of ICT investments in ICT using industries, termed the

investment effect.

With the growing ICT sector, one would expect that the manufacturing sector will be investing more, ICT capital, thereby enhancing the investment effect on the growth of the using sectors.

27_{The growth accounting methodology is based on Solow (1957) and will be extensively discussed in the} methodology section of this paper.

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However, it should be noted that much of the computer hardware in India is still imported, and thus it is not necessary that the larger part of the investment effect is from the ICT producing sectors within India. Given the fact that software is also an essential complementary element of ICT investment, part of the effect could still be from the country’s ICT producing sector. This helps us postulate the second hypothesis:

Hypothesis 2: The growth of ICT investments will increase the contribution of ICT capital

growth to output growth in the manufacturing sector

Hypothesis III

Thus with the above two hypotheses, we postulated that the ICT producing industry has a direct effect on the aggregate economy and the manufacturing sector by contributing to their growth. An investment effect due to ICT investments by the manufacturing sector should enhance output in the manufacturing sector. However, apart from these effects, the introduction of ICT -a new form of technology- will also have some indirect effects on the growth of the economy. Such indirect effects are often called spillover effects or externalities. The learning-by-doing model by Arrow (1962) initiated the thought that investments might create external productivity effects. This idea has been further tested by many researchers and came to the conclusion that these externalities could arise in the form of productivity gain, induced by technical progress, investment-led organizational change, technology-induced capital accumulation, and positive feedback effects (De Long and Summers (1993), Wolff (1991), and Stiroh (2001))29. This indicates that the growing ICT sector will have an indirect spillover effect on other sectors.

Van der Wiel et al. (2003) indicate that at micro and macro levels there is sufficient evidence that ICT contributes to labor productivity growth in other, closely related, sectors. Many other scholars came to similar conclusions with regard to increased TFP growth as a part of total output (Stiroh (2001), Jorgenson et al (2005), Unel (2003)). In an economy such as India, where ICT is gradually taking a firmer grip on the national economy in terms of its relative size it should be possible to observe such spillover effects. Moreover, good management of ICT investments, managerial learning, and India’s ICT sector’s large share in exports all indicate the possibility of spillovers (Dorgan et al. (2004), Nasscom (2006)). Therefore, given the growth of the ICT sector in India, and

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the increasing share of ICT capital in total investment by ICT using sectors, we hypothesize that this will improve the TFP growth in the manufacturing as an ICT using sector30. Thus the growth of the ICT sector and investments will have a spillover effect on ICT using industries, particularly on the manufacturing sector in terms of positive TFP growth effects. We postulate our third hypothesis as;

Hypothesis 3: The increased use of ICT will produce significant spillover effects in terms of

TFP gains in the manufacturing sector

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IV. Methodology

4.1 Design

This section provides a brief review of alternate approaches used in the literature to decompose output growth into productivity and factor contributions that will help us test the three hypotheses postulated in the previous section. This section also presents the proposed methodology to use in the present study. We measure both labour productivity as well as total factor productivity (TFP). Labour productivity does not need a full flex methodological model as it is defined as output per unit of labour, usually measured as hours worked or number of employees31. The second productivity measure that could be employed is total factor productivity (TFP), which is defined as the measure of the output of an industry or economy relative to the size of all its primary factor inputs32. The impact of any deviation from the standard growth accounting assumptions will be reflected in the measure of TFP growth (Timmer & van Ark, 2005). The measure of TFP has been given much attention in the literature as it is more comprehensive in that it takes account of all inputs. Hence, we concentrate on the measure of TFP, as this would be the focus of our methodology in revealing the indirect growth contribution of ICT in the Indian economy. Moreover, what follows is a combination of a review of methodological approaches and the chosen methodology in effect.

4.2 The Direct Effect: ICT Sector ALP and Output Contributions

As postulated in the previous chapter, we examine the distinct role of ICT in economic growth - the direct contribution of ICT to output and labour productivity growth, and the investment and TFP effect of ICT on manufacturing growth. The direct influence of the ICT sector on growth can be examined by assuming that the aggregate growth can be decomposed into ICT producing sector growth and non-ICT producing sector growth. Average aggregate growth is thus a weighted sum of sectoral growth rates where the weights are sectoral shares in aggregate nominal output (Durlauf & Aghion, P., 2005).

31_{Improvements in labor productivity may occur due to technological change, improvements in the quality of} labor and capital deepening.

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Yg = Sict * ICTg + Snonict * NONICTg + U (1)

where Yg is defined as the aggregate output growth, Sict is the nominal share of ICT output in

aggregate output, ICTg is growth of the ICT sector, Snonict is the nominal share of the non-ICT

output in aggregate output (i.e. 1- Sict), and NONICTg is the growth of the non-ICT producing

sector. Finally U is the re-allocation residual which is found by adding up contributions of ICT and non-ICT and deducting total output. Reallocation is a real economic force as resources move among industries (Jorgenson et al, 2006). The above equation indicates that the contribution of ICT to total output growth is the product of the nominal ICT share in aggregate output and the growth rate of ICT output. This can be expressed as a per cent of total growth, which will provide us the share of ICT growth contribution to total growth i.e.;

(Sict * ICTg) / Yg (2)

In order to estimate the contribution of ICT sector labor productivity (ALP) growth to aggregate ALP growth we followed the same approach by replacing output by ALP. Similar exercises are repeated in the context of the manufacturing sector, where the contribution of ICT to manufacturing growth is examined. The aggregate output and ALP growth in equations 1 and 2 are replaced respectively by manufacturing output and ALP growth and the share of ICT in aggregate output is replaced by the nominal share of ICT output in total manufacturing output.

4.3 The Investment Effect

While in the previous section we look at the direct growth contribution of the ICT sector to aggregate and manufacturing output and productivity growth, in this section we look at the contribution of ICT investments to manufacturing growth. To understand the investment effect of ICT on growth, we follow a standard growth accounting framework. This framework is based on the neoclassical production function (Solow (1956), Barro (1999)). Assume a simple Cobb-Douglas production function;

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where Y denotes output, K is capital input, L is labour input and A is the level of technology. represents the output share of capital. 1- is the labour share of capital and is derived by

subtracting one from the capital share.

The growth accounting exercise has been widely used in recent papers on this topic (Oliner at el (2000), Oulton (2001), Virmani (2004), Jorgenson et al (2001, 2002, 2005), Van Ark et al (2003)). This methodology is based on the neoclassical growth model initiated by Solow (1956). Van Leeuwen et al. (2003) have documented two main approaches used in the literature to quantify these contribution effects. They are the growth accounting approach used in the macro studies and econometric approach widely used in micro studies using firm-level data. Given our data, we have chosen to do a macro analysis. However, it would be useful to discuss the effects of the micro level view to understand differences in the methodology. The micro view is supported by an empirical device rather similar to (3) yet in the new model the cost shares of capital inputs have been replaced by parameter estimates due to the discussion being at firm level (Berndt & Morrison (1995), McGuckin & Stiroh (2000a, 2000b), and Stiroh (2001a). Van Leeuwen et al. (2003) yield substantial evidence with regard to ICT spillovers33 at firm level compared to the macro growth accounting model on ICT capital deepening. However, growth accounting at macro level will give us substantial information on not only labour productivity growth, yet also clearly distinct between the source for the ICT using sector between capital deepening and total factor productivity growth raising the opportunity for a thorough spillover methodology (van Ark & Inklaar, 2005). Available data on India support the growth accounting framework and thus is found the better alternative. ICT investment and capital contribution’s estimation will be accomplished by decomposing the contribution of inputs and productivity to output growth in the ICT producing sectors and ICT using sectors. Following the neoclassical production function in (3), the basic growth accounting and productivity measurement approach has been established by Solow (1956) and has later been extended specifically for the ICT sector by scholars like Barro (1999), Oliner at el (2000), Oulton (2001), Virmani (2004), Jorgenson et al (2001, 2002, 2005), and Van Ark et al (2003). The basic model is extended in several ways which is also the functional reason for several divergent outcomes in their respective papers. The basic model with two inputs labour (L) and capital (K) can be written as;

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lnY = L lnL + K lnK + lnA (4)

Following Schreyer (2000), Colecchia et al (2001) extend the model so that capital can be split between ICT capital (KC) and non-ICT capital (KN) to come to the following growth de-composition;

lnY = L lnL + KN lnKN + KC lnKC + lnA (5)

Thus in (4) and (5) the elasticities define the cost shares of the production factors non-ICT capital and ICT-capital. Because of constant returns to scale L + KN + KC = 1. L is

estimated by dividing manufacturing’s total emoluments by value added. K is then estimated

by 1 - L. To decompose the share of capital into ICT and non-ICT, the share of ICT capital in

total manufacturing capital is taken to come to KN and KC. Finally, lnA can be defined as

the rate of change of a Multi Factor Productivity (MFP) 4.4 Total Factor Productivity in the Manufacturing Sector

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functions for South and East Asian economies identified India as one of the least productive countries yet with the highest growth rate for TFP and technical efficiency.34

In a world where the neoclassical assumptions fail to hold, equations (4) and (5) are poor approximations of the true relationships and spillovers may be possible. Due to the short time series it proves impossible to achieve the pure spillover effect in this paper and thus merely for explanatory purpose of the spillovers at work, the following model reveals what distinction between the two models takes place35_;

lnAM

t = w lnKICTt + lnATt (6)

In equation 6 lnAMt represents the change in measured TFP36, lnATt is true TFP growth and

w is the wedge between the unobserved elasticity and the observed factor share37. This model shows that when the ICT capital is not correctly measured, the difference between actual and measured productivity will be the product of the wedge factor and ICT capital growth. If you regress measured productivity on ICT capital growth you get a constant. Measured TFP in our chosen equations 4 and 5 is positively correlated with ICT capital38. It is attributed to a number of causes, one of which being the spillover effect. Which means failures of the neoclassical framework provide a potential link between ICT capital deepening and TFP growth (Stiroh, 2001). These explanations are thus taken for granted and TFPG as the start of an explanation to spillovers is used in this model39.

Stiroh (2001) examines whether US aggregate TFP growth in the manufacturing sector exists and whether it is partly caused by ICT growth, through analyzing ICT-related spillovers in the manufacturing sector. We are expecting to see ICT production yield a non-pecuniary externality, thus directly affecting TFP growth. The actual spillover is thus TFP growth and a

34_{The production function approach has been followed by many other studies also both using parametric and} non parametric techniques (Fare et al (1994); Fecher and Perelman (1992)).

35_{This model is merely explanatory as due to data limitations, methodological limitations and short time series} only TFPG on output growth can be explained by this model and in future papers this model can be effectuated. Equation (6) in fact states that failures of the neoclassical framework provide a potential link between ICT capital deepening and measured TFP growth and here a correlation test between the two can be conducted (Stiroh, 2001).

36_{Calculated under the neoclassical approach as a residual.}

37_{Stiroh (2001) uses the same methodology and variables to prove the spillover theory.}

38_{Further explanations for the existence of this link can be found in Stiroh (2001) derived from DeLong &} Summers (1991, 1992, 1993).

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growing contribution to output in the growth accounting framework, modelled by equation (5) with the full growth accounting framework discussed in section 4.3. ICT capital, non-ICT capital, labour inputs and total output has been estimated and due to the direct growth contribution by TFP, lnA can be seen as the actual spillover (Stiroh (2001), Van Ark & Inklaar (2005). Due to limited years for the data used in this analysis a correlation test between TFP and ICT capital, as would be usual in previous papers, cannot give solid results. The correlation test has thus been left out of this thesis, yet due to the growth accounting for ICT and manufacturing in India being a novelty the results will already generate a starting point for future research in this area.

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V. Data and Variables

This section discusses the data sets that are to be used in the empirical analysis, including their sources and definitions. In order to employ the growth accounting framework presented in section 4 we require data on output, labour and capital in the ICT sector, the total economy and the manufacturing sector. Due to the limited availability of data on these relevant variables, we limit our analysis to the period 1998 to 2006. The data availability in India has always been rather problematic and especially the data on India’s ICT sector (such as ICT expenditures) are merely available since the mid-1990s which gradually came with India’s liberalizations at the start of the 90’s. In what follows we define the variables used in testing the three hypotheses, their definition and sources, in the ICT sector, the aggregate economy and the total manufacturing sector. ICT in the international context includes hardware and communication equipment40, software producers comprising pre-packaged, own account, and customized software (De Vries et al., 2006), and ICT services41 which combined are the definition used in this study unless indicated otherwise.

5.2 Output

Output is defined as the value of goods and services produced during a given period. For the total economy we consider GDP at constant 2000 Indian Rupees (INR). The data on current GDP are obtained from the Reserve Bank of India (RBI) and are converted to constant price values using GDP deflators with 2000 as the base year. A further description of deflators in this paper can be found back in appendix 1.1.

The output data for India’s ICT sector are constructed through revenues in the ICT sector available from National Association of Software and Services Companies (NASSCOM). NASSCOM provides ICT revenues in constant USD, which are converted to constant INR using the annual average exchange rate obtained from IMF’s International Financial Statistics. The hedonic deflators, which are used to correct for the falling prices in ICT, are taken from Timmer & Van Ark (2005) and are provided in Appendix 1.1.

40_{According to ISIC Rev.3 hardware and communications fall into industry 30 and 32. These consist of office} and computer equipment (including computers, printers, photocopiers, and other peripheral equipment), and radio, TV and other communication equipment.

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For the manufacturing sector, the total output and employment are taken from the Groningen Growth and Development Centre (GGDC) 10-sector database by de Vries & Timmer (2007). This data, which includes both the registered and unregistered segment of Indian manufacturing, is used in the direct growth contribution calculations as ICT is manufactured in both these sectors. However, for the growth accounting exercise, we consider only the registered segment data because of the availability of data for this section. This data is taken from the Annual Survey of Industries (ASI). ASI provides data on net value added and depreciation in current prices, which totals to gross value added. They are deflated using a wholesale price index for manufacturing which was obtained from the RBI handbook of statistics on the Indian Economy (2006).

5.3 Labour

Throughout the study we define labor productivity as output per employee. Labor is defined as hours worked. The numbers of employees in the ICT sector were obtained from Nasscom databases and from the Digital Planet Reports (2002, 2006) of the World Information Technology and Services Alliance (WITSA). Aggregate employment data were derived from the GGDC database. Employment in the organized manufacturing sector was derived from ASI and for the total manufacturing from GGDC 10-sector database.

In the growth accounting exercise, however, we also include labor quality. Due to India’s steep progress and organizational learning curve this index is expected to add an extra progress factor. Regarding the definition of the labor input from manufacturing for the investment and indirect effect sections, the breakdown of the labour component in model (4) is to be subdivided into labour quality and the amount of hours worked as in Jorgenson et al (2005), taking away the effect as discussed in Stiroh (2001) where necessarily labour quality was included in TFP due to non-use of the model in (5). Thus;

L = H * q (7)

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by Aggarwal (2004)42. The labor share in equation (5) is estimated by dividing the total amount of emoluments in manufacturing by the amount of value added in this sector.

5.4 Capital

Capital in the growth accounting models represents the capital stock for a particular asset type at a certain moment in time (Timmer & Van Ark, 2005). Capital input in the growth accounting is the rate of capital services. To construct capital stock, the Perpetual Inventory Method (PIM) has been used for which you need capital stock in both ICT and non-ICT. For this the following perpetual inventory equation has been employed;

Kt = Kt-1 (1 - ) + It (8)

where K represents the capital stock of a particular asset type, is the geometric depreciation rate, I is investment, and t is time of measurement (Martin, 2002)43. The full derivation of capital stock, both ICT capital and non-ICT capital, in the growth accounting model can be found in appendix 1.1, while this section will define various types of capital in their respective models and present their sources.

Once the ICT and non-ICT capital stocks are constructed using the PIM, we can derive the growth rates of these two that can be used in the growth accounting equation. And under the assumption of constant returns to scale, the output share of capital can be derived as 1 - L.

However, the important task is the allocation of the share of total capital between ICT capital

42_{The labor quality index by Aggarwal has been tested on its validity by regressing it with a number of data} described below and used merely to test for the significance of labour quality in manufacturing as data to be inputted into the main model;

q = 0 + 1 Education + 2 Institution1 + 3 Institution2 + 4 Income00 + 5 T

Education is constructed using a Barro & Lee (2005) dataset on the educational attainment of the population aged 25 years or above. Institution1 and Institution2 are datasets constructed by Kaufman, Kraay & Mastruzzi (2004) for the World Bank and are defined as ‘Rule of Law’ and ‘Regulatory Quality’. Income00 is GDP per capita for the year 2000 from the Penn World Table and finally a time dummy has been chosen; T. Moreover from the Annual Survey of Industries, the employment figures for the manufacturing sector are drawn up. The outcomes of this model are significant and indicate Aggarwal’s labor quality to be in line.

43_{Following Jorgenson et al (2005) investments by the manufacturing sector in ICT equipment, software and} services stemming from expenditure data can be calculated by the following model; Ia,t = a,t * Ea,t

where Ia,t, a,t, and Ea,t are respectively investment, investment-to-expenditure ratio, and ICT expenditures. Subscript a represents the type of asset and t is the year. The average geometric depreciation rate from Jorgenson et al (2005) of 25% has been chosen for this paper. For non-ICT capital we have a service life of 30 years and a depreciation rate of 5%.

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and non-ICT capital. This requires the estimation of the compensation share of each asset, which can be done using the rental price of each capital asset. The use of rental price helps weight the growth rate of ICT capital and non-ICT capital according to their marginal productivities. Griliches & Jorgenson (1966) discuss the rental price of capital based on Jorgenson (1963). Following their approach, in the case of two capital inputs - ICT and non-ICT - the growth rate of aggregate capital services can be derived as;

lnK = ICT (t, t-1) lnKICT + non-ICT (t, t-1) lnKnon-ICT (9)

i = (Pi Ki) / ( Pi Ki) (10)

where lnK represents the growth of the capital stock, (t, t-1) represents the average rental

share of capital and P is the rental price of capital. Finally subscript i stands for the ith capital (ICT or non-ICT) and subscript t and t-1 represent years t and t-1. From this, the contribution of ICT capital to output growth can be derived as (1 - L) ICT (t, t-1) lnKICT.

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to the rapid depreciation of ICT products it is noteworthy to keep in mind the close relationship between ICT investments and the derivation of ICT capital, as compared to the relation between non-ICT investments and non-ICT capital with a much longer depreciation period. These two sections of the PIM model construct ICT capital used by the manufacturing sector.

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VI. Empirical Analysis and Findings

6.1 Overview

This section presents the results from the models discussed in the previous section and the hypotheses formulated in section three. In order to proceed to the testing of the growth accounting framework for the investment and indirect effects, the first procedure to follow will be to test hypothesis 1 on its validity. Subsequently the outcomes from the investment and indirect effects will be presented in order to make the ICT sector’s influence on the aggregate economy and ICT using sectors complete.

6.2 Contribution of ICT to Economic Growth and the Manufacturing Sector

In tables 3 and 4 we present the annual growth rates of output and employment in the total economy, manufacturing and ICT sectors. We observe that the aggregate and ICT employment grew, while the manufacturing employment declined. Aggregate, manufacturing sector and ICT sector output grew. The growth in the ICT sector though is at a much higher rate with ICT employment growth nowhere being lower than 12.65% (in 2002) and peaking at 24.9% (in 2003), while aggregate employment growth fluctuates between 1.4% and 2.1% and the average decrease of manufacturing employment lies between -6.1% and 2.46% annually. Growth of the ICT sector’s output is about five times as large as aggregate output with an average of 25.94% in exponential growth rates for ICT against 6.08% aggregate output growth and 5.45% manufacturing output growth.

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Aggregate ALP growth at 4.29% remains largely in line with average annual growth in the years prior to this research, as the Conference Board (2004) stated this growth amounted to approximately 3.4%, with also a rather high variability across years44. This is due to steep increases of both employment growth and GDP growth45. Van Ark et al. (2003) decomposes an average annual labor productivity growth over the periods 1963-73, with 1.9% growth, 1973-85, 1.4% growth, and 1983-96 with 4% annual growth. Considering these outcomes the average annual growth pattern shows a similar pattern for the aggregate levels and ICT ALP reveals the higher rate of growth on average.

Tables 6 and 7, in addition of charts 3 and 4, reveal the outcomes from equation (1) and its expansion of the contribution of the ICT producing sector on aggregate growth. The average annual 6.36% GDP growth achieves an ICT contribution of 0.63. Out of 5.72% growth of GDP in the first half of the period 0.55 can be attributed to ICT, against 7.01% GDP growth in the second half and an ICT contribution of 0.72.

Also for the ALP contribution by the ICT sector to aggregate ALP growth, the ICT share of 0.144 in 4.62% is relatively large. The first period shows a 3.79% ALP growth with ICT holding a share of 0.258, while the second period shows a 5.45% growth with ICT sector holding 0.03. Thus it can be concluded that the ICT sector’s contribution to aggregate growth is large and growing.

Tables 8 and 9, and charts 5 and 6 reveal the contribution of the ICT sector to the manufacturing sector. There is a major share contributed by the ICT sector to the output growth, at an annual average growth rate over the last nine years of 76.33%. This draws back on the sector’s growth of 5.45% with an ICT contribution of 4.16. When dividing the period in two, the first half shows manufacturing growth of 4.33% with ICT contribution at 3.92 and the second half showed manufacturing growing at 6.93% with ICT sector’s contribution at 4.47. This is mainly due to the slower growth of manufacturing output and the relatively large share that ICT holds in the manufacturing sector. However, the share of ICT in manufacturing is a topic of debate as it not only entails the manufacturing sector ICT but ICT for the full economy and entails ICT services. Due to a possible overestimation of ICT no strong

44_{Even within the discussed 9 year period an increased level o growth is to be witnessed; from 3.79% in the first} period to 5.45% in the second.

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conclusions from this outcome are to be drawn. The ICT sector’s ALP contribution over the last decade is high, at 17.13%. The full-period ALP growth was 5.37% of which ICT contributed 0.92. In general it may be a concluded that the ICT sector fairly contributes to aggregate and manufacturing sector’s growth and more importantly this has been increasing over time.

6.3 ICT Investments

Penetration of ICT in the Indian economy is used to extrapolate investment levels using the US and Australian investment-to-expenditure ratios46_{.The growth accounting methodology}

has been used to examine the contribution of ICT capital to manufacturing output growth. Average annual growth of ICT capital for the full nine year period is 16.19%, which has grown from 5.55% during 1998-2002 to 30.38% during 2003-2006. The manufacturing output also grew at a rate of 5.45% with a slightly growing trend. These outcomes relate to initial outcomes of the ICT producing sector as a whole in section 1 and the growth of its contribution on the aggregate economy in that ICT grows significantly faster than total and manufacturing output.

The ‘ICT CAPITAL’ column of table 10 reveals that on average the contribution of ICT capital to manufacturing output growth is 0.49% during the past decade. This has increased from 0.13% during 1998-2002 to 0.79% during 2003-2006. The ICT investment contribution to manufacturing output has thus grown and is large when compared to the volume of the sector’s capital relative to total manufacturing output. However they cannot relate to the large contribution shares in the direct effect section.

Jorgenson et al (2005) shows that during 1995-2000 the contribution of ICT capital was 2.9%, while during 1989-1995 it was 1.6 % of GDP growth. This share has thus stayed quite flat, yet this reflected an outcome for the aggregate economy and comparative data for manufacturing contributions are not available. One of the explanations can also be found in the fact that aggregate ICT expenditure growth is larger than ICT expenditure growth by the manufacturing sector and thus relatively to non-ICT expenditures this gap closes (Nasscom, 2006). Moreover manufacturing was one of the first sectors in India to implement ICT on a large scale and this can have resulted in a temporal slowdown of new investments. However,

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ICT capital growth is still relatively large, growing, and a major outcome of the growth accounting framework.

6.4 TFPG in the Manufacturing Sector

The results of the accounting analysis are shown in table 10 and chart 7. The first outcome is the relatively low value of ICT capital as was discussed the previous section, the growth of its volume is impressive but due to its low share in output the contribution is minimal yet still larger than its volume share.

The TFP growth shows an average growth rate of 3.38 over the whole period. With an average annual output growth of 5.44, the share of TFP on growth comes down to an average of 62.14% annually in total growth. When the 9-year period is divided in half, the TFP contribution shows a large increase of growth. Looking at previous results on this behalf, the TFP share in growth is large in India as compared to the world average, where over the last decades TFP share to GDP growth was approximately 25.7% (Jorgenson et al, 2005).

Unel (2003) tested TFPG over the decades in the 80s and 90s and reveals a growth in those periods. In the decade 1980-1991 TFPG was 1.8 and grew to 2.5 in 1992-1998 indicating the growth in this paper continued to 3.33 over the period 1998-2006.

Goldar & Kumari (2003) and Goldar (2004) reveal a deceleration of TFP growth in manufacturing during the 1990s as compared to the decades before. The outcomes diverge highly as compared to Unel (2003), whose outcomes diverge so highly, largely attributed to output and input measurement errors. The main cause for the deceleration was found to be the underutilization of industrial capacity. Goldar et al. (2003) report TFPG for 1982-1991 at 1.89 and 0.69 for 1992-1998. The growth of 1.01 for the first four years in our analysis, followed by 6.63 in 2003-2006 indicates a TFP growth revival. Moreover Goldar (2004)47 describes TFPG for 1992-2000 at 1.57, which indicates growth in the last two years of his study. A combination of high levels of ICT investment growth and a growing TFP might be suggestive of positive spillover effects at industry level (Van Ark & Inklaar, 2005). With a combination of high growth for manufacturing output and the slow, and sometimes even decreasing, growth of several inputs, TFP could enlarge its share.

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The relatively large growth of non-ICT capital can also be traced back to the rather large share by this variable in output growth, while labour’s rather constant values contribute considerably less to output growth. Labour input has a growth share in manufacturing growth of 1.17%48 and non-ICT capital has a share of 34.39%. These figures diverge from Indian data published by Jorgenson et al (2005) for ’95-‘00 at 36.9% and 24.2% for labour and non-ICT capital respectively, and even further from world averages that lie at 28.5% and 22.9% respectively. One of the explanations for this divergent outcome may once again be that we are assessing the manufacturing sector, with different dynamics, and more specifically the registered manufacturing sector, whose setup diverges from the full manufacturing sector. When comparing total capital growth to output growth, Goldar (2004) shows the percentage point growth of capital was 0.6 for 1980-1991 and 1.2 for 1992-1998. Our outcomes suggest a further increase of this rate with 1.9 for 1998-2006, which is ICT capital and non-ICT capital combined, thus no general conclusions about these separate entities are to de drawn yet a general growth is to be witnessed.

India’s ICT sector: “How does it induce aggregate output, productivity, and spillovers into the manufacturing sector?”