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ICT Investment and Economic Growth in India: An Industry Perspective

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Digitalisation and Development

Abstract

The role of information and communication technologies (ICT) in driving economic growth has been well-established in the literature. By reducing communication and transaction costs, and improving the quality of capital, ICT helps firms improve their productivity and growth. Given her linguistic and engineering skills, India has been pioneering in ICT exports, in particular, the export of software services since the 1990s. However, there is hardly any attempt to understand how Indian industries have been taking advantage of the massive growth potential of ICT use in their production process, looking into the experiences of different industries. This has been primarily constrained by lack of adequate, disaggregated data on the ICT use by industries. While a few studies have attempted to understand the contribution of ICT to aggregate economic growth, the role of ICT at a detailed industry level is hardly studied in India. This paper is a first attempt to construct ICT investment series for the registered or organised segment of manufacturing industries in India, and one of the first few attempts that have made so far to build such ICT series for the aggregate Indian economy. The study extends the capital asset database in India KLEMS to include ICT investment, i.e. investment in hardware, software and communication equipment, in respect of different manufacturing industries. The paper also provides preliminary estimates of the contribution of ICT capital to growth in the aggregate economy and registered manufacturing sector.

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Notes

  1. 1.

    For a while, productivity statistics failed to capture the effect of ICT, as the rapid declines in ICT prices and information on ICT investment were not fully captured in official data. In 1987 Robert Solow even remarked, “[Y]ou can see the computer age everywhere except in the productivity statistics”, an observation which is often considered as ‘IT productivity paradox”. However, later studies which accounted for rapid declines in ICT prices using quality-adjusted hedonic prices observed significant contributions from ICT (see e.g. Jorgenson and Vu 2005). The debate on price is, however, far from settled. For instance, a recent study by Byrne and Corrado (2016), argues that the official US hedonic prices fail to capture the magnitude of price declines in ICT, and their alternative measures suggest even larger declines.

  2. 2.

    See Erumban and Das (2016) for a most recent analysis of ICT’s contribution to aggregate economy growth.

  3. 3.

    ICT outsourcing in these studies is measured using data on expenditure on software and other professional services obtained from the Prowess database.

  4. 4.

    KLEMS stands for capital, labour, energy, material and services. See Das et al. (2016) for a recent study that exploit this database to study sectoral productivity dynamics in Indian economy.

  5. 5.

    Also see van Ark et al. (2011).

  6. 6.

    The text in this section on the methodological approach to measuring aggregate economy ICT investment heavily draws upon Erumban and Das (2016). This paper is an extension of Erumban and Das (2016) in that it adds ICT capital in detailed manufacturing sectors, though confined only to the registered segment.

  7. 7.

    See http://www.witsa.org/.

  8. 8.

    The 2011 version of the EU KLEMS data, has been used for this purpose see www.euklems.net.

  9. 9.

    Note that the software investment data—be it directly from the NAS, or obtained using hardware/software ratio from WITSA or from the United States—does not capture pirated software used by companies, if any. While the use of such pirated software would indeed contribute to firm’s output growth, it will never be reported by firms, and hence is hard to capture.

  10. 10.

    See de Vries et al. (2010) and Timmer and van Ark (2005) for a good description of the commodity flow approach, followed in Erumban and Das (2016).

  11. 11.

    The ASI data on ICT investment has been used by previous studies, some of which are indicated earlier in this paper. For instance, Vashisth (2017) constructs ICT capital stock using ASI firm-level data on ICT investment and Joseph and Abraham (2007) make use of the ICT investment data from ASI at 3 digit level in their regression of labour productivity on ICT intensity. Sharma and Singh (2012), also uses investment in ICT from ASI, deflated using machinery and equipment prices. This paper makes a comprehensive attempt to compile the ASI data on ICT and construct measures of capital stock and capital services that are consistent with the approach followed in the India KLEMS database.

  12. 12.

    Clearly, the ASI data underestimate the extent of ICT use in the organised manufacturing sector, as it only covers the hardware and software investments (also see Vashisht 2017).

  13. 13.

    A similar approach is followed to obtain GFCF in all asset types in India KLEMS, while this paper deals only with the ICT.

  14. 14.

    See the India KLEMS data manual available at: https://www.rbi.org.in/Scripts/PublicationReportDetails.aspx?UrlPage=&ID=855.

  15. 15.

    An alternative approach, which is not attempted in the paper yet, is outlined in Appendix 3.

  16. 16.

    Our harmonised price deflators are based on the U.S. hedonic prices, which are constructed using a hedonic regression where prices of ICT equipment regressed on several characteristics, such as for instance processor speed, hardware size, memory etc.

  17. 17.

    ICT income share is obtained using ICT rental prices, which are computed using internal rate of return, depreciation rate and ICT investment deflators (see Erumban and Das 2016 and Erumban 2008 for detailed discussion on the calculation of rental prices).

  18. 18.

    Also see the India KLEMS data manual, available at: https://www.rbi.org.in/Scripts/PublicationReportDetails.aspx?UrlPage=&ID=855.

  19. 19.

    Note that there are some differences between TED estimates and our estimates. The first is that in the TED output and GFCF data for the aggregate are converted to calendar year (using quarterly data) and the asset distribution is applied to those annual data to obtain asset wise data. Secondly, the price deflator for ICT used in the TED are based on a new alternative measures developed by Byrne and Corrado (2016), while the hedonic deflators used in our paper is based on official BEA ICT hedonics for U.S. Finally, the TED numbers are relative to ‘GDP’, whereas ours is relative to gross value-added.

  20. 20.

    In an earlier study, Papaioannou and Dimelis (2007) suggest strong ICT effects on economic growth, with the effects being larger on developed economies than on developing economies.

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Acknowledgements

This paper draws heavily on the India KLEMS project funded by the Reserve Bank of India (RBI), housed in Centre for Development Economics (CDE), Delhi School of Economics. The authors are thankful to the RBI for financial support and the CDE for hosting the project. We are also grateful to many researchers who have contributed to the development of the KLEMS data and provided fruitful comments on this research. In particular, we wish to acknowledge K. L. Krishna, Bishwanath Goldar, Suresh Chand Aggarwal, and Pilu Chandra Das who contributed to an earlier version of this research, published as CDE Working paper # 284. The content of the working paper has been re-used with permission. Comments by participants of the India KLEMS Conference in December 2016, in particular, Ashok Jain, T. Rajeshwari, Rajiv Mehta and Satyananda Sahoo were quite beneficial to this work. Views expressed in this paper are those of the authors and do not reflect their respective institutions. The usual disclaimers apply.

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Correspondence to Abdul A. Erumban or Deb Kusum Das .

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Appendix 1

Appendix 1

Another way of estimating NAS consistent ICT series for organised manufacturing is to consider the reported NAS software data as the benchmark, and obtain hardware as a residual. That is, for years for which the NAS software data is available (1998 onwards), consider the NAS data as the benchmark estimates for the aggregate registered manufacturing. Hardware investment for the first year of the data for which the software data is available in NAS can then be obtained using the aggregate economy software/hardware ratio. This way we can obtain the total investment in ICT for the first year as the sum of hardware and software. For all other years, the total ICT investment may be obtained by applying the growth rate of total ICT investment in ASI. The hardware series can then be calculated as the residual after subtracting the NAS reported software investment from this total. More formally,

$$ {\text{GFCF}}_{{{\text{HARD}},1998}}^{J} = \frac{{{\text{GFCF}}_{{{\text{SOFT}},1998}}^{J} }}{{\emptyset_{1998} }} $$

where \( {\text{GFCF}}_{{{\text{HARD}},1998}}^{J} \) is the GFCF in hardware in 1998 in total registered manufacturing sector, \( {\text{GFCF}}_{{{\text{SOFT}},1998}}^{J} \) is the total registered manufacturing investment in software in 1998 and \( \emptyset_{1998} \) is the software to hardware ratio for the aggregate economy in 1998. Subsequently, total ICT investment in total registered manufacturing sector may be obtained as:

$$ {\text{GFCF}}_{{{\text{ICT}},1998}}^{J} = {\text{GFCF}}_{{{\text{SOFT}},1998}}^{J} + {\text{GFCF}}_{{{\text{HARD}},1998}}^{J} $$

And for t > 1998

$$ {\text{GFCF}}_{{{\text{ICT}},t}}^{J} = {\text{GFCF}}_{{{\text{ICT}},t - 1}}^{J} \left[ {\frac{{{\text{GFCF}}_{{{\text{ICT}},t}}^{J\_asi} }}{{{\text{GFCF}}_{{{\text{ICT}},t - 1}}^{J\_asi} }}} \right] $$

Since the software data is taken as such from National Accounts, the hardware can be obtained as a residual:

$$ {\text{GFCF}}_{{{\text{HARD}},t}}^{J} = {\text{GFCF}}_{{{\text{ICT}},t}}^{J} - {\text{GFCF}}_{{{\text{SOFT}},t}}^{J} $$

While this is still a less perfect approach, the positive side of it is that it ensures complete consistency with NAS reported software data and the trend in aggregate ICT investment in ASI.

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Erumban, A.A., Das, D.K. (2020). ICT Investment and Economic Growth in India: An Industry Perspective. In: Maiti, D., Castellacci, F., Melchior, A. (eds) Digitalisation and Development. Springer, Singapore. https://doi.org/10.1007/978-981-13-9996-1_3

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