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Exclusion from the mainstream financial world is a burden on the poor of many countries. The proliferation of new mobile and online financial services, such as e-banking, money transfers, and payment processing has the potential to provide access to basic financial products and services to financially excluded people. The purpose of this study was to investigate the effects of the growth of mobile phone and Internet use on financial inclusion in the South Asian Association for Regional Cooperation (SAARC) countries from 2004 to 2014. We applied principal component analysis to construct a financial inclusion index that served as a proxy variable for the accessibility of financial services in the SAARC countries. Using three different models-the fixed effect, random effect, and panel correction standard errors modelsthis study discovered a positive and significant relationship between the growth of financial inclusion and expansion of both mobile phone and Internet services. Moreover, an empirical study of the control variables showed that the levels of income and education were positively associated with financial inclusion, whereas the size of the rural population and unemployment were negatively related to financial inclusion. In addition, the empirical estimates posit a unidirectional causal flow from the growth of mobile and Internet services to expanded financial inclusion in the SAARC countries.

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Purpose The purpose of this study is to measure the availability, accessibility and usability of financial products and services in both rural and urban India from 1991 to 2014. Design/methodology/approach This paper uses principal component analysis (PCA) method to construct financial inclusion index that serves as a proxy variable for indicating the inclusiveness of financial products and services among the rural and urban people. To fulfill this objective, the study proposes separate indexes of financial inclusion for both rural and urban India from 1991 to 2014. The paper uses annual time series data from 1991 to 2014 to construct the rural-urban financial inclusion index. The used data have been collected from the basic statistical returns of Reserve Bank of India and Economic Political Weekly research foundation. Findings The study inferences that though there is a remarkable increase in financial inclusion in India from 1991 onwards, it does not result in sizeable growth of financial access to rural masses in comparison to urban masses. The rural India does not substantiate an equivalent growth to that of urban India, contrasting a perceptible increase in financial inclusion. The finding of this study will help the researchers and policymakers to understand the status of financial inclusion in the context of both rural and urban India. Furthermore, policymakers can take appropriate policy initiatives to fulfill the financial inclusion gap that exists between rural and urban people. Additionally, the proposed index is easy to compute and can be used to make comparison across countries for further studies. Originality/value The present paper attempts to include all possible dimensions (and indicators within a dimension) that have been considered so far by various authors. Therefore, the authors hope that this index will be more indicative and accurate than previous index. Again, the authors propose to use PCA for the first time to assign the weight of factors in the financial inclusion index for rural and urban India separately.

This study assesses the association of sustainable development (SD) with environmental technologies, forest area and developmental indictors in selected 39 economies. It develops global sustainable development index (GSDI) as an integration of environmental sustainability index (ESI), economic development index (EDI) and social development index (SDI) during 2000-2016 using composite Z-score technique. Thereupon, it explores the influence of environmental technologies, deforestation, ESI, EDI and SDI on GSDI using country-wise panel data. The results infer that there exists a high inequality in SD due to diversity in socio-economic structure of selected countries. Most developed economies have a better position in SD due to their relatively better position in environmental, economic and social developmental related variables. India, South Africa and Tunisia have low values of ESI, EDI and SDI, thus, these countries are in worst position in SD. Empirical results exhibit that SD is positively associated with environmental, economic and social development, forest area and environmental technologies. It recommended that protection of forest area maintains the quantity and quality of natural resources and provide ecological security. Accessibility of electricity for all community, discovery of environmental technologies, use of green technologies in production activities may be effective to increase socio-economic, environmental and sustainable development.