Abstract
Financial inclusion has recently become one of the main goals all over the world. Using data extracted from the Global Financial Inclusion Database (Global Findex) of the World Bank, the paper aims to investigate the determinants of financial inclusion in Asia in 2017. The authors use two indicators for proxies representative financial inclusion, including debit and credit card ownership. The study employs Bayesian estimations and finds that the individual characteristics factors (such as gender, age, income, education, and employment status) affect the access and use of the products and services of formal financial institutions. Among these factors, education is the strongest factor influence on financial inclusion while age has a linear relationship and the weakest effect on inclusive finance. Furthermore, individuals with higher income, in the workforce and being a man relate positively in both indicators on financial inclusion. From these findings, the authors propose some important recommendations to develop financial inclusion in Asia.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
- 2.
- 3.
Access from website https://www-cdn.oxfam.org/s3fs-public/file_attachments/ib-inequality-womens-work-asia-310516-vn.pdf, on August 22nd, 2021.
References
ADB: Gender equality and the sustainable development goals in Asia and the Pacific: Baseline and Pathways for Transformative change by 2030 (2018). Access from https://www.adb.org/publications/gender-equality-sdgs-asia-pacific August 22nd, 2021
Allen, F., Demirguc-Kunt, A., Klapper, L., Peria, M.S.M.: The foundations of financial inclusion: understanding ownership and use of formal accounts. J. Financ. Intermed. 27, 1–30 (2016)
Bruhn, M., Love, I.: The real impact of improved access to finance: evidence from Mexico. J. Financ. 69(3), 1347–1376 (2014)
Chakrabarty, K.: Financial inclusion and banks: Issues and perspectives. RBI Bull. (2011). Access from: https://rbidocs.rbi.org.in/rdocs/Bulletin/PDFs/02SEPC1111FL.pdf
Demirgüç-Kunt, A., Klapper, L.F.: Measuring financial inclusion: the global findex database. World Bank Policy Research Working Paper(6025) (2012)
Demirgüç-Kunt, A., Klapper, L.F., Randall, D.: Islamic finance and financial inclusion: measuring use of and demand for formal financial services among Muslim adults. World Bank Policy Research Working Paper (6642) (2013a)
Demirgüç-Kunt, A., Klapper, L.F., Singer, D.: Financial inclusion and legal discrimination against women: evidence from developing countries. World Bank Policy Research Working Paper(6416) (2013b).
Fungáčová, Z., Weill, L.: Understanding financial inclusion in China. China Econ. Rev. 34, 196–206 (2015). https://doi.org/10.1016/j.chieco.2014.12.004
Gelfand, A.E., Hills, S.E., Racine-Poon, A., Smith, A.F.: Illustration of Bayesian inference in normal data models using Gibbs sampling. J. Am. Stat. Assoc. 85(412), 972–985 (1990)
Hannig, A., Jansen, S.: Financial inclusion and financial stability: current policy issues (2010). Access from: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1729122.
Hastings, W.K.: Monte Carlo sampling methods using Markov chains and their applications. Biometrika 57(1), 97–109 (1970)
IMF: Financial Inclusion: Can It Meet Multiple Macroeconomic Goals. IMF Staff Discussion Note 15/17, International Monetary Fund Washington, DC (2015)
Kabakova, O., Plaksenkov, E.: Analysis of factors affecting financial inclusion: eosystem view. J. Bus. Res. 89, 198–205 (2018). https://doi.org/10.1016/j.jbusres.2018.01.066
Khan, H.: Financial inclusion and financial stability: are they two sides of the same coin. Address by Shri HR Khan, Deputy Governor of the Reserve Bank of India, at BANCON (2011)
Kreinovich, V., Thach, N.N., Trung, N.D., Thanh, D.V.: Beyond Traditional Probabilistic Methods in Economics. Springer, Cham. (2019). https://doi.org/10.1007/978-3-030-04200-4
Kumar, N.: Financial inclusion and its determinants: evidence from India. J. Financ. Econ. Policy 5(1), 4–19 (2013). https://doi.org/10.1108/17576381311317754
Leyshon, A., Thrift, N.: Geographies of financial exclusion: financial abandonment in Britain and the United States. Trans. Inst. Br. Geogr. 20(3), 312–341 (1995)
Metropolis, N., Rosenbluth, A.W., Rosenbluth, M.N., Teller, A.H., Teller, E.: Equation of state calculations by fast computing machines. J. Chem. Phys. 21(6), 1087–1092 (1953)
Park, C.-Y., Mercado, R:. Financial inclusion, poverty, and income inequality in developing Asia. Asian Development Bank Economics Working Paper Series(426) (2015)
Soumaré, I., Tchana Tchana, F., Kengne, T.M.: Analysis of the determinants of financial inclusion in Central and West Africa. Trans. Corporat. Rev. 8(4), 231–249 (2016)
Sriboonchitta, S., Nguyen, H.T., Kosheleva, O., Kreinovich, V., Nguyen, T.N.: Quantum approach explains the need for expert knowledge: on the example of econometrics. In: Kreinovich, V, Sriboonchitta, S. (Eds.), Structural Changes and Their Econometric Modeling, vol. 808, pp. 191–199. Springer (2019). https://doi.org/10.1007/978-3-030-04263-9_15.
Svítek, M., Koshelevac, O., Kreinovich, V., Nguyen, T.N.: Why quantum (wave probability) models are a good description of many non-quantum complex systems, and how to go beyond quantum models. In: Kreinovich, V., Thach, N.N., Trung, N.D., Van Thanh, D. (Eds.), Beyond Traditional Probabilistic Methods in Economics, vol. 809, pp. 168–175. Springer (2019). https://doi.org/10.1007/978-3-030-04200-4_13
Thach, N.N.: How to explain when the ES is lower than one? A Bayesian nonlinear mixed-effects approach. J. Risk Financ. Manag. 13(2), 21 (2020)
Tuesta, D., Sorensen, G., Haring, A., Camara, N.: Financial inclusion and its determinants: the case of Argentina. Madrid: BBVA Research. Working Paper No.15/03 (2015)
van de Schoot, R., Depaoli, S.: Bayesian analyses: where to start and what to report. Europ. Health Psychol. 16(2), 75–84 (2014)
Zins, A., Weill, L.: The determinants of financial inclusion in Africa. Rev. Dev. Financ. 6(1), 46–57 (2016). https://doi.org/10.1016/j.rdf.2016.05.001
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Trung, N.D., Quynh, N.T.N. (2022). The Determinants of Financial Inclusion in Asia—A Bayesian Approach. In: Ngoc Thach, N., Kreinovich, V., Ha, D.T., Trung, N.D. (eds) Financial Econometrics: Bayesian Analysis, Quantum Uncertainty, and Related Topics. ECONVN 2022. Studies in Systems, Decision and Control, vol 427. Springer, Cham. https://doi.org/10.1007/978-3-030-98689-6_35
Download citation
DOI: https://doi.org/10.1007/978-3-030-98689-6_35
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-98688-9
Online ISBN: 978-3-030-98689-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)