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This paper examines India's socio-economic attributes and different financial dimensions of financial inclusion (FI).

The paper uses a principal component analysis (PCA) to build indexes related to financial dimensions. It applies the logistics regression model and the Fairlie decomposition method to determine India's socio-economic and financial characteristics of FI.

Based on the logistic regression, socio-economic factors like age, gender, marital status, level of education and religion have an impact on FI. The use of financial institutions has positively contributed to the probability of FI, while the low proximity of financial service providers retards the process of FI. Fairlie decomposition concludes regional disparity and gender disparity in FI; however, the rural–urban gap in FI is not captured by the variables included in the study. The main reasons for the discrepancy are lack of education, financial literacy, the proximity of financial service providers and lack of financial institutions.

This paper makes two important contributions: first, it presents a micro-level analysis of FI across the socio-demographic strata of India, and second, it demonstrates the regional, rural–urban and gender disparity in FI in India.

The purpose of this paper is to examine the relationship between financial inclusion (FI) and economic growth in India.

To measure FI, a multidimensional time-varying index is proposed following the Human Development Index method. The long-run relationship between FI and economic growth is examined by using the autoregressive distributed lag (ARDL) approach to cointegration and nonlinear ARDL approach. Further, the direction of causality is investigated by employing the Toda–Yamamoto Granger causality test.

The linear cointegration test confirms a long-run relationship between FI and economic growth for India. The improvement in both demand-side and supply-side financial services has a positive impact on economic growth. These results suggest that India can attain long-run economic growth by improving the coverage of FI. However, there is no evidence of nonlinear cointegration, indicating that there is no asymmetric effect of FI on economic growth. Further, the causality test shows that FI granger causes economic growth but not vice versa.

The major limitation of the study is the availability of time series data for all important variables. The index for both demand- and supply-side indicators can be extended with several other important variables in later date once the data are available for those variables.

As the study confirms that FI is one of the main drivers of economic growth, it is suggested that the policy maker emphasizing on financial sector reforms can enjoy economic growth in the long run, especially in developing countries. Therefore, the government and policy makers need to address the issues involved in access to financial services to spur economic growth.

The study examines the long-run relationship between FI and economic growth employing ARDL bound testing approach and nonlinear ARDL approach, separately for demand-side and supply-side indicators. Further, the study uses the Toda–Yamamoto granger causality to find the direction of causal flow between FI and economic growth.

The main purpose of this paper is to examine the relationship between financial inclusion and financial stability in South Asian countries.

To measure the financial inclusion, a multidimensional time-varying index is constructed following the Human Development Index method. The long-run relationship between financial inclusion and financial stability is examined by using the panel cointegration test, fully modified ordinary least squares and dynamic ordinary least squares approaches to show the long-run elasticity of explanatory variables on dependent variables. Further, Dumitrescu-Hurlin panel causality test is used to find the direction of causality between financial inclusion and financial stability. Data set is of annual frequency of seven countries for the period from 2004 to 2018.

The empirical findings of this study confirm that financial inclusion has a positive and statistically significant impact on financial stability. These results suggest that South Asian countries can attain long-run financial stability by improving the coverage of financial inclusion. Further, panel causality test shows a unidirectional causality from financial inclusion to financial stability.

The major limitation of the study is the availability of time series data for all important variables. Various socioeconomic variables can be used to measure financial stability, but this study included only the Z-score as the proxy for financial stability. Due to the data constraint, this study is unable to use the time series econometric analysis.

As the study confirms that financial inclusion is one of the main drivers of financial stability, it is suggested that the policymakers should emphasize on financial sector reforms to enjoy financial stability in the long run, especially in developing countries. So governments and policymakers of study countries need to address the issues involved in access to financial services to increase financial stability. Furthermore, it is also important to remove limitations of access to formal financial services for marginalized sections of the society with proper supervisions.

This is a new contribution on the present topic. This study has constructed a new multidimensional financial inclusion index (FII) following the Human Development Index method for South Asian countries based on annual data and using ten indicators of formal financial services related to availability, accessibility and usage. To the best of the authors’ knowledge and information, this is the first study on South Asian countries to construct and apply the new multidimensional FII. Further, the study examines the long-run elasticity of financial inclusion on financial stability employing FMOLS and DOLS approach.