Institutional determinants of financial inclusion: evidence from world economies

Eldomiaty, Tarek Ibrahim; Hammam, Rasha; Bakry, Rawan El

doi:10.1108/ijdi-08-2019-0147

Cited by 62 publications

(37 citation statements)

References 25 publications

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“…Nevertheless, some scholars studied the effects of financial inclusion by adding variables separately into the model (Demir et al, 2020 ; Mushtaq & Bruneau, 2019 ; Neaime & Gaysset, 2018 ). Hence, we employed a Kruskal–Wallis test to verify if the financial inclusion variables (i.e., groups) differ significantly from each other, following Eldomiaty et al ( 2020 ). A χ 2 (Chi-square) statistic verifies if the null hypothesis of all medians being equal to all groups can be rejected.…”

Section: Methodsmentioning

confidence: 99%

Does Financial Inclusion Diminish Poverty and Inequality? A Panel Data Analysis for Latin American Countries

et al. 2021

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Despite great developmental efforts in recent decades, Latin America still presents high levels of poverty and inequality when compared to developed nations. As explored widely in the literature, one potential instrument to diminish these issues is financial inclusion, including the access and usage of financial services by all people. Specifically, this paper verifies if financial inclusion and technology adoption decrease the poverty headcount ratio and the Gini index (i.e., inequality) of 13 Latin America countries (Argentina, Bolivia, Brazil, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Honduras, Panama, Paraguay, Peru, and Uruguay). To perform such analysis, an unbalanced panel dataset was built, and the Feasible Generalized Least Squares (FGLS) and the Limited Information Maximum Likelihood (LIML) techniques were employed. The results suggest that, in accordance with previous studies, financial inclusion is a powerful tool to tackle poverty and inequality. Additionally, the combined effects of financial inclusions and technology (i.e., mobile use) are also capable of decreasing the poverty and inequality levels. We discuss the policy implications of our findings and suggest a future research agenda.

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Section: Methodsmentioning

confidence: 99%

Does Financial Inclusion Diminish Poverty and Inequality? A Panel Data Analysis for Latin American Countries

et al. 2021

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“…When time series of counts are formed panels with two countries, the underlying data set forms a panel data frame and a panel generalized linear model (PGLM) is used to predict the daily number of confirmed cases in response to other predictor variables. The R package pglm is used to fit the model [11] and the Hausman test [12] is used to choose between fixed or random-effects models [13].…”

Section: Methodsmentioning

confidence: 99%

Time to and extent of widespread testing for COVID-19 outbreak: Experience from the first wave in Australia and Italy

Abedin

Khan²,

Khan

2020

Preprint

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Background: At the beginning of COVID-19 outbreak, very little was known about its control options and most of the intervention options relied mainly on other virus outbreak and influenza epidemic. Different countries started responding to this epidemic somewhat in different ways to achieve a common goal of transmission reduction. Population-wide intervention measures such as social distancing, testing and isolation were implemented in different countries. However, commonly adopted intervention measures impacted different countries in different ways. Differential effects of those interventions become apparent in Australia and Italy, where Australia's success to control the epidemic has been in limelight. Differences in time to and extent of widespread testing are likely to have differential effects on the daily number of confirmed cases in both countries.Methods: We apply panel generalized linear models for daily number of cases to explore differential effects of timing to and extent of widespread testing on daily number of cases. We have analyzed daily number of confirmed cases data from the first reported cases in Australia and Italy to 31 May 2020. Our data sets can be downloaded from an open source database at https://ourworldindata.org.Results: More tests during the early stage of outbreak prior to reach the peak may reduce the daily number of cases by almost 40%. Only 1% increase in test positivity on the (t-5)th day may incur 1.84% increase in daily number of cases on the t-th day. For 1% increase in test positivity rate on the (t-5)th day, a country with one unit higher logarithm of population density may result in 2.82 times higher number of cases on the t-th day.Conclusion: Conducting widespread testing during the early stage prior to reaching the peak has favored Australia to control the outbreak much faster than Italy. Early adoption of widespread testing with lower degree of test positivity rates flattens the curve faster. Population density has a moderating effect. Even if the test positivity rate is the same, a region with higher population density is likely to experience a peak with higher number of daily confirmed cases.

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“…There are few exceptions. Using Global Findex data, Eldomiaty et al, (2020) analyse the role of institutions on access to finance at the global level. They establish that control of corruption, government effectiveness, political stability and voice & accountability influence financial inclusion.…”

Section: Related Literaturementioning

confidence: 99%

“…Their wide coverage and usage allows for comparison with the existing literature. Previous studies that have used WGI include Eldomiaty et al, (2020), Zulkhibri and Ghazal (2017), Alter and Yontcheva (2015). Table 1 presents definition and measurement of the variables while Table 2 shows the predicted effects a priori based on theory and empirical literature.…”

Section: Measurement Of Variablesmentioning

confidence: 99%

Does the Quality of Institutions Matter for Financial Inclusion? Cross Country Evidence

Muriu¹

2021

IJEF

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Despite evidence on the importance of financial inclusion, little is known about the role of institutions in fostering inclusion partly because of data availability. Using annual data corresponding to 120 countries for the period 2004-2019, this study investigates country institutional characteristics associated with the ownership of deposit accounts. A standard regression model is estimated using fixed effects panel data techniques along with financial inclusion proxy and three measures of institutional quality. This paper provides the first empirical justification that financial inclusion is non-negligibly driven by the institutional context. Specifically, rule of law and quality of regulations are crucial in enhancing financial inclusiveness, more so in Africa where they have a stronger effect relative to other regions. Banks and depositors in Africa may be operating in an environment characterized by weak legal systems and excessive or challenging regulations. The evidence presented in this paper may therefore help with the sequencing of institutional reforms that could promote financial inclusion.

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Institutional determinants of financial inclusion: evidence from world economies

Cited by 62 publications

References 25 publications

Does Financial Inclusion Diminish Poverty and Inequality? A Panel Data Analysis for Latin American Countries

Does Financial Inclusion Diminish Poverty and Inequality? A Panel Data Analysis for Latin American Countries

Time to and extent of widespread testing for COVID-19 outbreak: Experience from the first wave in Australia and Italy

Does the Quality of Institutions Matter for Financial Inclusion? Cross Country Evidence

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