The impact of ICT on shadow economy in West Africa

Ajide, Folorunsho M.; Dada, James Temitope

doi:10.1111/issj.12337

Cited by 28 publications

(22 citation statements)

References 75 publications

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Section: Methodological Settings and Datamentioning

confidence: 99%

“…Primary data on ICT performance should be used wisely and carefully interpreted. The use of mobile cellular telephone subscription ICT indicator is also broadly used in macro-studies regarding various aspects of digital technologies development-see, for instance, recent empirical works of Ajide and Dada (2022), Komen and Ling (2022), Lechman and Anacka (2022), Bacca-Acosta et al (2023). Another aspect regarding the use of MCS c,y in our study is that this variable perfectly suits the examination of network externalities in telecommunication markets, especially its part where the digitally based communication channels are considered (for a similar approach, see in work of, e.g., Medina et al (2019), Aguilar et al (2020), Hawthorne and Grzybowski (2021).…”

Section: Data Rationalementioning

confidence: 99%

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Network effects—do they matter for digital technologies diffusion?

Anacka,

Lechman

2023

JOCM

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PurposeThe main research target of this paper is to capture the network effects using the case of mobile cellular telephony, identified in European telecommunication markets, and its determinants enhancing the process of digital technologies diffusion.Design/methodology/approachThis research relies on panel and dynamic panel regression analysis. The empirical sample covers 30 European countries, and the period for the analysis is set for 2000–2019.FindingsThis work contributes by examining the network effects identified on European telecommunication markets that drive the process of digital technologies diffusion, but it also extends the understanding of the latter by tracing major determinants of fast network expansion, e.g. prices of access to and use of, per capita income, urbanisation, population density, accessibility of fixed telephony infrastructure. The main findings support the initial supposition that the installed base strongly enhances diffusion of new technologies, while other factors, for example, prices, are not of prime importance.Research limitations/implicationsThis research has certain managerial implications. The unveiled network effects driving adoption of technological innovations constitute a significant determinant of implementation of differentiation strategy by telecommunication companies. Due to network effects consumers' propensity to join the network is valued higher than the prices of services offered, which is crucial not only from the perspective of the company's pricing strategy but also enables telecommunication companies to introduce to the market new products and/or services concentrating on increasing its quality and usability rather than future prices.Originality/valueThis is the first work that empirically verifies the intercompanies and interpersonal diffusion of cellular telephony, hypothesising that this process relies on unique network effects.

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Section: Methodological Settings and Datamentioning

confidence: 99%

Section: Data Rationalementioning

confidence: 99%

Network effects—do they matter for digital technologies diffusion?

Anacka,

Lechman

2023

JOCM

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“…However, in the economics literature, Beck (1968) theoretically suggests that an economic agent may choose to operate in the shadow economy if the benefits outweigh the costs. Some firms and individuals may choose to engage in shadow economic activities to avoid the costs of environmental regulation and environmental degradation laws (Ajide and Dada, 2022). Consistent with Biswas et al (2012), shadow economy increases environmental damages due to weak regulation quality, especially in a corrupt environment.…”

Section: Literature and Hypothesesmentioning

confidence: 99%

Income inequality, shadow economy and environmental degradation in Africa: quantile regression via moment’s approach

Dada

Ajide

Arnaut

2023

IJDI

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Purpose The purpose of this examine the impact of income inequality and shadow economy on environmental degradation given the growing income inequality, shadow economy and ecological degradation in developing countries. Thus, this study is motivated to offer empirical insight into how income inequality and shadow economy influence the environment in African countries. Design/methodology/approach Data from 29 countries in Africa between 2000 and 2017 were used, while the novel method of moments quantile regression of Machado and Silva (2019) and Dumitrescu and Hurlin (D-H) (2012) granger causality is used as the estimation techniques. Findings The results established the presence of cross-sectional dependence and slope heterogeneity in the panel, while Westerlund panel cointegration confirmed the long-run cointegration among the variables. The results from the quantile regression suggest that income inequality increases environmental degradation from the 5th to the 30th quantiles, while from the 70th quantiles, income inequality reduces ecological degradation. The shadow economy negatively influences environmental degradation across the quantiles, strengthening environmental quality. Per capita income (economic growth) and financial development positively impact environmental degradation throughout the quantiles. However, urbanization reduces environmental degradation from 60th to 95th quantiles. The D-H causality established a two-way relationship between income inequality and environmental degradation, while one-way from shadow economy, per capita income and urbanization to environmental degradation were established. Originality/value This study provides fresh insights into the nexus between shadow economy and environmental quality in the presence of higher levels of income inequality for the case of African region. The study applies quantile analysis via moment proposed by Machado and Silva (2019). This technique shows that the impact of income inequality and shadow economy on environmental degradation is heterogeneous across the quantiles of ecological footprints in Africa.

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“…Meanwhile, the literature shows that the development of information technology, especially the Internet, has changed the ways of economic organisation and operation, with several first-ever new activities, such as the gig economy (Gandini 2019;Rangaswamy 2019), while economic agents are likely more flexible (Hanseth and Bygstad 2015). The study of Ajide and Dada (2022) for West African countries and that of Remeikienė et al (2022) for 11 post-transition EU members jointly agree that information and communications technology (ICT) development would reduce the size of the shadow economy. According to Nguyen (2022), there is a dynamic relationship between the knowledge materialised in the economy (so-called economic complexity 1 ) and the shadow economy.…”

Section: Introductionmentioning

confidence: 99%

“…First, this study adds a new contribution to current literature on the determinants of the shadow economy. Previous studies (see Elgin (2013); Nguyen and Su (2021); Ajide and Dada (2022), Remeikienė et al (2022)) have documented the effect of economic uncertainty or Internet on the shadow economy. This study extends and provides evidence on the effects of both economic uncertainty and Internet development on the shadow economy.…”

Section: Introductionmentioning

confidence: 99%

The Internet, economic uncertainty, and the shadow economy: “The Good, the Bad, and the Unknown”?

Nguyen

Tran

2022

Int Social Sci J

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This study investigates the influences of economic uncertainty and Internet usage on the informal economy. Notably, the study focuses on the effects of the association of economic uncertainty and Internet usage on the informal economy. The empirical analysis is carried out for a global sample of 124 economies from 1996 to 2017. Applying different estimates and different robustness checks, the results are consistent and robust. Internet usage leads to a decline in the shadow economy, while economic uncertainty has the effect of increasing the shadow economy. Interestingly, the positive influence of economic uncertainty on the shadow economy is likely exacerbated by Internet development. Lastly, analyses for several subsamples by time periods, income levels, and regions reveal additional findings. The negative impact of Internet usage on the shadow economy is consistent across income groups, regions, and time periods, except for a surprising positive impact in North America. The positive impact of economic uncertainty is also consistent in most income groups but more dominant in a period of low economic uncertainty. Interestingly, economic uncertainty is found to have a negative impact on the informal sector in low‐income economies and Sub‐Saharan Africa. Overall, the results have an important implication: Increases in economic uncertainty motivate economic agents to move to informal sectors, and this is supported by information technologies.

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The impact of ICT on shadow economy in West Africa

Cited by 28 publications

References 75 publications

Network effects—do they matter for digital technologies diffusion?

Network effects—do they matter for digital technologies diffusion?

Income inequality, shadow economy and environmental degradation in Africa: quantile regression via moment’s approach

The Internet, economic uncertainty, and the shadow economy: “The Good, the Bad, and the Unknown”?

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