2013
DOI: 10.1080/13504851.2012.754538
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Broadband penetration and economic growth in ASEAN countries: a generalized method of moments approach

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Cited by 24 publications
(15 citation statements)
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“…Furthermore, the economy growth of the country is measured by the GDP or GNP of the country. The increase in GDP and GNP of the country refers to the high economy growth in the country (Ng et al, 2013). Thus, the economy growth is essential for the development of the country and the present study proceeds this variable as dependent variable of the study.…”
Section: Economy Growthmentioning
confidence: 94%
“…Furthermore, the economy growth of the country is measured by the GDP or GNP of the country. The increase in GDP and GNP of the country refers to the high economy growth in the country (Ng et al, 2013). Thus, the economy growth is essential for the development of the country and the present study proceeds this variable as dependent variable of the study.…”
Section: Economy Growthmentioning
confidence: 94%
“…Some empirical studies [14,15,35,36] found that increasing ICT use is a strong driver of economic growth, and stressed the need for countries to focus on promoting the use of ICT, in particular in order to increase its effects on economic growth. Farhadi et al [35] focus on a panel of 159 countries over the period [2000][2001][2002][2003][2004][2005][2006][2007][2008][2009], and note that the impact of ICT use is stronger in higher income countries, while the impact is weak in countries with low levels of income.…”
Section: Review Of Empirical Studiesmentioning
confidence: 99%
“…Initially, we estimated the relationship between LnFAC with the explanatory variables based on the following static methods: (a) Pooled OLS (b) fixed effects and (c) random effects (RE). Then, we used GMM as proposed by Arellano and Bond (1991) as the former methods are not sufficient to deal with the issues of endogeneity and reverse causality (Ng et al, 2013). Besides, GMM can handle the issues of serial correlation and individual effects with regards smaller samples as against fixed effects (Baltagi, 2008).…”
Section: Empirical Results Findings and Discussionmentioning
confidence: 99%
“…Fixed effect (FE) estimator’s consistency depends on how large the time component is in the panel (T), and with larger T it becomes more consistent (Baltagi, 2008)⁠. In addition, OLS and fixed estimator are not sufficient to deal with the issue of endogeneity and reverse causality (Ng et al, 2013). To address these problems, we use the model proposed by Arellano and Bond (1991) where the equation is estimated in ‘first-differences’.…”
Section: Methodsmentioning
confidence: 99%