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Measurement of Technological Change in India’s Textile Machinery Industry Using the Malmquist Productivity Index

Author

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  • Sanjaya Kumar Malik

    (The author is at the Centre for Development Studies, Prasanth Nagar, Ulloor, Trivandrum 695 011, Kerala, India, emails: sanjaya10d@cds.ac.in, mksanjaya@gmail.com)

Abstract

This article measures technological change in India’s textile machinery industry, and examines how user–producer interaction affects this. Employing the non-parametric Malmquist productivity index, we find there has been little technological change in the textile machinery industry from 1998–99 through 2007–08. It is proposed that poor and unsustainable demand and the shrinking share of domestic demand for textile machinery owing to the technological upgradation fund scheme—meant for providing interest reimbursements or capital subsidies to textile manufacturers—may have weakened the user–producer interactions, thereby bringing down innovative activities and innovations in the textile machinery industry in India. JEL Classification: O14, O33, C14

Suggested Citation

  • Sanjaya Kumar Malik, 2015. "Measurement of Technological Change in India’s Textile Machinery Industry Using the Malmquist Productivity Index," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 9(2), pages 179-203, May.
  • Handle: RePEc:sae:mareco:v:9:y:2015:i:2:p:179-203
    DOI: 10.1177/0973801014568066
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    References listed on IDEAS

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    1. Bengt-ake Lundvall & Bjorn Johnson, 1994. "The Learning Economy," Industry and Innovation, Taylor & Francis Journals, vol. 1(2), pages 23-42.
    2. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    3. Martin Fransman, 1986. "Machinery in Economic Development," Palgrave Macmillan Books, in: Martin Fransman (ed.), Machinery and Economic Development, chapter 1, pages 1-53, Palgrave Macmillan.
    4. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    5. Sanjaya Lall, 1987. "Learning to Industrialize," Palgrave Macmillan Books, Palgrave Macmillan, number 978-1-349-18798-0.
    6. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    7. Rosenberg, Nathan, 1972. "Factors affecting the diffusion of technology," Explorations in Economic History, Elsevier, vol. 10(1), pages 3-33.
    8. Kim,Linsu & Nelson,Richard R. (ed.), 2000. "Technology, Learning, and Innovation," Cambridge Books, Cambridge University Press, number 9780521770033.
    9. Kathuria, Vinish & Seethamma Natarajan, Rajesh Raj & Sen, Kunal, 2010. "Organized versus Unorganized Manufacturing Performance in India in the Post-Reform Period," MPRA Paper 20317, University Library of Munich, Germany.
    10. Subhash C. Ray, 2002. "Did India's Economic Reforms improve Efficiency and Productivity? A Nonparametric Analysis of the Initial Evidence from Manufacturing," Indian Economic Review, Department of Economics, Delhi School of Economics, vol. 37(1), pages 23-57, January.
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    Cited by:

    1. Sonal Ann D’souza & Panchendra K. Naik, 2018. "Trade Liberalisation, Capital-Intensive Export and Informalisation: A Case Study of India’s Manufacturing Sector," The Indian Journal of Labour Economics, Springer;The Indian Society of Labour Economics (ISLE), vol. 61(2), pages 377-399, June.

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    More about this item

    Keywords

    Textile Machinery Industry; Technological Change; Malmquist Productivity Index; Data Envelopment Analysis;
    All these keywords.

    JEL classification:

    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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