Enhancing youth and women’s financial inclusion in South Asia

Abstract

The youthful population of South Asia, holding the majority in the subregion, will also have a great share in the future alongside the risk of being not in education, employment, or training with a persisting gender gap. This makes it important to adopt a gender-responsive policy framework for youth empowerment. This paper, after constructing a multidimensional financial inclusion index, based on a multilevel estimation framework considering the hierarchical structure of the dataset, shows evidence on how to increase financial inclusion among the South Asian youth. It furthermore provides policy recommendations considering the gendered effects. The paper finds that education level, formal employment, having a national ID, and government expenditure on education and health are important drivers of financial inclusion. The paper furthermore finds that education level becomes especially more important for those at the bottom income quintile and that government expenditure into education and health would boost the youth financial inclusion in South Asia, especially for the female youth.

Keywords:

• financial inclusion
• sustainable development goals (SDGs)
• youth

Subject classification codes:

• D14
• G28
• J16
• N25

Public interest statement

Financial inclusion that may be defined as the formal use of financial services has development benefits especially for developing economies. This paper shows evidence on how education level, formal employment, having a national ID, and government spending on education and health can enhance youth and women’s financial inclusion in South Asia. Policy recommendations drawn based on the findings in the paper could be of interest to policymakers as well as to the general public in the sub-region. Moreover, developing economies in other regions may also learn from the findings pointed out in the paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. The latest data for NEET figures are available in 2017 for Bangladesh, 2012 for India, and 2015 for Pakistan.

2. A traditional list of immediate “basic needs” is food (including water), shelter and clothing. Modern lists emphasize also sanitation, education, healthcare, and internet. Denton, John A. (1990). Society and the official world: a reintroduction to sociology. Dix Hills, N.Y: General Hall. p. 17. ISBN 978-0-930,390-94-5.

3. The Global Findex database is a world-wide data set on how adults save, borrow, make payments, and manage risk. Launched with funding from the Bill & Melinda Gates Foundation, the database has been published every three years since 2011. The data are collected in partnership with Gallup, Inc., through nationally representative surveys of more than 150,000 adults in over 140 economies. The 2017 edition includes updated indicators on access to and use of formal and informal financial services, adding new data on the use of financial technology (FinTech), including the use of mobile phones and the internet to conduct financial transactions (The World Bank, 2017). The survey includes individual weights. In addition to the survey weights, country weights are calculated using $n/N$ formula; where $n$ denotes sample size and $N$ denotes country population to provide correct representation of the countries. Furthermore, throughout the paper final weights are used based on the formula $w_i\times w_j$; where $w_i$ denotes individual weights and $w_j$ denotes country weights and the dataset is stratified by country.

4. Joint Correspondence Analysis (JCA) is one of the methods in the class of Correspondence Analysis (CA) giving a notion of distance to the categorical variables along with the Multiple Correspondence Analysis (MCA), provides an iterative method of finding a best fit of inertia measures.

5. While South Asia refers Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka; because of the data unavailability in the 2017 Global Findex Database for two South Asian countries, namely Bhutan and Maldives, are not included in the analyses.

6. All the data are stratified by country to ensure each subgroup within the population receives proper representation within the sample.

7. Stratification means the population of N units is first divided into homogeneous and mutually exclusive groups called strata (Singh et al., 2016).

Additional information

Funding

The author received no direct funding for this research.

Notes on contributors

Goksu Aslan

Goksu Aslan currently works as an Instructor of Economics at New York University Abu Dhabi. Her research interests revolve around economic growth, income inequality, financial inclusion, and gender inequality. Before joining NYUAD, she was as an Associate Economic Affairs Officer at the United Nations Economic and Social Commission for Asia and the Pacific (ESCAP) on promoting regional cooperation for inclusive and sustainable economic and social development in South and South-West Asia and a Postdoctoral Research Fellow at the University of Milano-Bicocca. The research reported in this paper relates to how youth and women’s financial inclusion can be enhanced in South Asia and how this can contribute to the development in the sub-region.