7 research outputs found

    Financial Inclusion, Poverty, and Income Inequality: Evidence from High, Middle, and Low-income Countries

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    The past two decades have witnessed a high national importance to financial inclusion around the world. This paper intends to explore the impact of financial inclusion on poverty reduction and income inequality in the world, high, middle, and low-income countries. For this purpose, a new composite financial inclusion was constructed with three dimensions for finding various macroeconomic variables affecting the level of financial inclusion for 122 economies, including 32 from high-income, 38 from upper middle income, 38 from lower middle income, and 14 from low-income countries. Then the impact of financial inclusion, on poverty and income inequality, for the world and then for high, middle, and low-income countries was investigated. The estimates reveal that rule of law significantly affects financial inclusion for the world, high, middle, and low-income countries. But age dependency ratio influences the financial inclusion only for our full sample. However, population density significantly decreases financial inclusion just in the full sample and Upper middle-income countries. Education completion impacts significantly financial inclusion just in upper middle income. While literacy has a higher impact on financial inclusion in high-income countries. The findings also indicate that financial inclusion is significantly correlated with lower poverty for the full sample. The link between financial inclusion and income inequality has been found for high-income countries and lower-middle-income countries

    Financial Inclusion, Poverty, and Income Inequality: Evidence from European Countries

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    This study contributes to the existing literature on financial inclusion by examining the determinants of financial inclusion and studying the impact of financial inclusion on poverty reduction and income inequality in European countries. We investigate the impact of financial inclusion on poverty and income inequality in 30 European countries during 2004-2019 based on a composite financial inclusion index (FII) constructed by using principal component analysis (PCA). Then we assess the impact of financial inclusion, on poverty and income inequality, by employing the fixed effect method. The estimates reveal that, for the European countries, GNI per capita, population density, inflation, and internet users have a positive and significant impact on financial inclusion across all the regressions. Rule of law has a positive impact on financial inclusion, and the age dependency ratio has a negative impact on financial inclusion. The findings also indicate that financial inclusion is significantly correlated with lower poverty for the full sample. Lastly, the present study supports the role of financial inclusion in reducing income inequality in European countries

    Internet Adoption, Digital Divide, and Corruption: Evidence from ECOWAS Countries

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    This paper aims to extend the existing literature on Internet adoption and corruption by analyzing the factors impacting the digital divide and assessing the impact of Internet adoption on corruption reduction in the Economic Community of West African States (Benin, Burkina Faso, Cape Verde, Cote d’Ivoire, Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Niger, Nigeria, Senegal, Sierra Leone, and Togo). The study uses fixed and random effect panel data techniques covering 17 years (2003-2019), to exploit the times series nature of the relationship between the digital divide and its determinants. In addition, it aims to assess the impact of internet adoption along with other control variables on corruption. The estimation results show that per capita income, human capital, age, population density, government effectiveness, political stability, and the rule of law significantly affect the digital divide in ECOWAS. The findings reveal also that internet adoption affects positively the level of corruption control; the impact of an increase in internet users of 1% implies an increase in corruption control between 0.05% and 0.06%

    A meta-analysis of 20 years of studies on Intellectual Capital (1997-2017)

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    Leif Edvinsson introduced the intellectual capital in his 1997 Long Range Planning journal article. 2017 marks 20 years since that article. This anniversary had motivated us to review the state of research on intellectual capital, to highlight a number of research questions pertaining to country, institutional and individual productivity, publication frequency, and favorite inquiry methods were proposed. To this end, we reviewed 372 articles published in business, management and accounting journals in the period 1997-2011.the findings of this literature review are presented in three part. First, the reviewed articles are categorized by topics, research settings, and research method. Second, the contributions of research to the field and the lessons learned from these studies are discussed. Third, knowledge gaps in existing intellectual capital research are identified, leading to consideration of several ideas for future research

    Intellectual Capital Assessment Models in Clusters: A Literature Review

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    The purpose of this paper is to review the literature on intellectual capital in clusters in order to identify and compare the main models to measure at the cluster level. A systemic literature review was carried out using the most important bibliographic database Scopus and the most important journal on intellectual capital: journal of intellectual capital. The search covered the period from 2004 to 2016.

    Social media as a source for cities reputations: Evidence from top-ranked cities.

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    The purpose of this paper is to investigate the relationship between popularity in a social media network and cities reputations. Additionally, city reputation is measured in this study by the Reptrak score provided by the Reputation Institute and numbers of tourist. This study used a quantitative methodology. The sample was composed of the top thirty-seven ranked cities. Content analysis was used to examine the correlations between reputation ranking and social media metrics from Facebook, Twitter, YouTube, and Instagram. The results indicated that popularity in social media is clearly a major determinant of the reputation of cities but only from a tourism perspective
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