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Performance of Telecommunications in India: Panel Arellano-Bond GMM Estimation of Teledensity
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The growth of telecommunications infrastructure and its performance is at the heart of the digital economy, essential for information and citizen-centric services. Though India has made rapid strides in the provision of the telecommunications network, the teledensity is uneven across the states of India. This paper analyses the determinants of teledensity and its distribution dynamics across 18 Indian states over 15 years between 2004 and 2018 using kernel density plots and the dynamic panel fixed effects Arellano-Bond GMM estimation technique. The AB-GMM estimates show the network externality, NSDP per capita, service sector share in NSDP and literacy rate are the important determinants of relative teledensity across the states of India. The kernel density plots indicate a gradual reduction and convergence of teledensity across states over the years. The half-life estimate suggests that the speed of convergence is 1.13 years i.e it takes 1.13 years to converge in teledensity across the states of India.
Keywords
Telecommunications, Teledensity, Convergence, Kernel Plots, Arellano-Bond GMM Estimation
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- Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58(2), 277-297.
- Barman, H., Dutta, M. K., & Nath, H. K. (2018). The telecommunications divide among Indian states.
- Telecommunication Policy, 42(7), 530-551.
- Burdisso, T., & Sangiacomo, M. (2016). Panel time series: Review of the methodological evolution. Stata Journal, 16(2), 424-442.
- Datta, A., & Agarwal, S. (2004). Telecommunications and economic growth: A panel data approach. Applied Economics, 36(15), 1649-1654.
- Ghosh, S., & Prasad, R. (2012). Telephone penetrations and economic growth: Evidence from India. Netonomics: Economic Research and Electronic Networking, 13(1), 25-43.
- Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1), 53-74.
- Koutroumpis, P. (2009). The economic impact of broadband on growth: A simultaneous approach. Telecommunication Policy, 33(9), 471-485.
- Labra, R., & Torrecillas, C. (2018). Estimating dynamic panel data. A practical approach to perform long panels. Revista Colombiana de Estadistica (Colombia Journal of Statistics, 41(1), 31-52.
- Levin, A., Lin, C.-F., & Chu, C.-S. J. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics, 108(1), 1-24.
- Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross section dependence. Journal of Applied Econometrics, 22(2), 265-312.
- Roller, L.-H., & Waverman, L. (2001). Telecommunications infrastructure and economic development: A simultaneous approach. American Economic Review, 91(4),909-923.
- Sridhar, K., & Sridhar, V. (2007). Telecommunications infrastructure and economic growth: Evidence from developing countries. Applied Econometrics and International Development, 7(2), 37-56.
- Yadav, K., Tiwari, S., & Divekar, R. (2015). Impact of Technological changes in telecom sector in India.Indian Journal of Science and Technology, 8(4), 1-5.
- Zahra, K., Azim, P., & Mahmood, A. (2009).Telecommunication infrastructure development and economic growth: A panel data approach. Pakistan Development Review, 47(4), 711-726.
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