Economic and business cycles with time varying in India: evidence from ICT sectors

Chukiat Chaiboonsri, Satawat Wannapan and Giovanni Cerulli

International Journal of Computational Economics and Econometrics, 2020, vol. 10, issue 4, 366-379

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. (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=110772 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijcome:v:10:y:2020:i:4:p:366-379

Access Statistics for this article

More articles in International Journal of Computational Economics and Econometrics from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().