Authors: Chukiat Chaiboonsri; Satawat Wannapan; Giovanni Cerulli
Addresses: Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand ' Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand ' National Research Council of Italy, Rome, Italy
Abstract: The purposes of this paper are two main sections. The former is to study the relationship between Indian ICT industries and GDP by applying Bayesian inference. Yearly predominant indexes collected during 2000 to 2015, including Indian GDP, fixed phone usages, mobile phone distributions, internet servers, and broadband suppliers are analysed by employing the Markov-switching model (MS-model) and Bayesian vector autoregressive model (BVAR). The latter is the time-varying parametric VAR model with stochastic volatilities (TVP-VAR). With Bayes statistics, this time-varying analysis can more clearly provide the extended perception to the underlying flexible structure in the economy. Additionally, the Bayesian regression model is used to investigate the ICT multiplier related to Indian economic growth. Empirically, results indicate IT sectors are now becoming the importance of Indian economic expansion, compared with telecommunication sectors. The ICT multiplier also confirms high-technological industrial zones should be systematically enhanced, especially, researches and developments in cyberspace.
Keywords: information and communication technology; ICT; Bayesian inference; Markov-switching model; MS-model; Bayesian vector autoregressive model; BVAR; time-varying parameter VAR; TVP_VAR.
International Journal of Computational Economics and Econometrics, 2020 Vol.10 No.4, pp.366 - 379
Received: 11 Jul 2018
Accepted: 07 May 2019
Published online: 29 Oct 2020 *