IDEAS home Printed from https://ideas.repec.org/a/jda/journl/vol.51year2017issue2pp221-237.html
   My bibliography  Save this article

Determinants Of Financial Inclusion In Bangladesh: Dynamic Gmm & Quantile Regression Approach

Author

Listed:
  • Ajim Uddin
  • Mohammad Ashraful Ferdous Chowdhury
  • Md. Nazrul Islam

    (Southern Illinois University Edwardsville, USA
    Shahjalal University of Science & Technology, Bangladesh)

Abstract

Financial Inclusion has been recently acknowledged as a key enabler for reducing poverty and improving prosperity. However, more than 50% adults of the poorest households are still unbanked globally. According to IMF (2016), 45% people of Bangladesh are out of formal financial services. High interest rate, vast rural population and low literacy rate are among the prominent factors that restrained the government and the World Bank joint initiatives to reach universal financial access. Researchers have reasons to believe, there are certain other factors that remain unnoticed by the policy maker and which in turn, probably affecting their ability to formulate effective policy. The quest to identify these factors materialize this study. In this study, the determinants of financial inclusion have been clustered in two broad areas: bank specific factors and macroeconomic factors. Then, econometrically try to analyse which group of factors has more influence in determining the level of financial inclusion in a country. In the study, static model like, random effects and dynamic panel models like, generalized methods of moments (GMM) methodologies have been applied. Data from 25 banks: 18 conventional and 7 Islamic banks operating in Bangladesh during the period 2005–2014, is collected to analyze the role of both types of banks in financial inclusion. For robustness, this study also employs Quantile regression approach. The study found that, on the supply side, the size of a bank, its efficiency, and the interest rate it charges has a directs impact on financial inclusion. Where on the demand side, literacy rate is positively and age dependency ratio is negatively related to financial inclusion. In addition to that, quantile regression analysis found that bank size has a significant impact on both deposit collection and loans & advances disbursement of a bank. The study can be beneficial for both government and bank authorities in developing their policy decisions to ensure more inclusive financial system. Setting the loan interest rate close to international level and extending the branch facilities can encourage excluded population to use formal financial services. Finally, the study also signifies that, by developing human capital developing country countries can improve their financial market participation and therefore can foster economic growth.

Suggested Citation

  • Ajim Uddin & Mohammad Ashraful Ferdous Chowdhury & Md. Nazrul Islam, 2017. "Determinants Of Financial Inclusion In Bangladesh: Dynamic Gmm & Quantile Regression Approach," Journal of Developing Areas, Tennessee State University, College of Business, vol. 51(2), pages 221-237, April-Jun.
  • Handle: RePEc:jda:journl:vol.51:year:2017:issue2:pp:221-237
    as

    Download full text from publisher

    File URL: https://muse.jhu.edu/article/657938
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mahamat Ibrahim Ahmat Tidjani, 2020. "An exploratory analysis of financial inclusion in Chad," Post-Print hal-03322905, HAL.
    2. Tonuchi E. Joseph & Nwolisa U. Chinyere & Obikaonu C. Pauline & Alase, A. Gbenga, 2021. "Monetary Policy Effectiveness and Financial Inclusion in Nigeria: FinTech, ‘the Disrupter’ or ‘Enabler’," International Journal of Applied Economics, Finance and Accounting, Online Academic Press, vol. 9(1), pages 19-27.
    3. Duc H. Vo & Nhan T. Nguyen, 2021. "Does financial inclusion improve bank performance in the Asian region?," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 35(2), pages 123-135, November.
    4. Ahmad Ma'ruf, 2019. "Financial Inclusion and Achievements of Sustainable Development Goals (SDGs) in ASEAN," GATR Journals jber180, Global Academy of Training and Research (GATR) Enterprise.
    5. Sanderson Abel & Learnmore Mutandwa & Pierre Le Roux, 2018. "A Review of Determinants of Financial Inclusion," International Journal of Economics and Financial Issues, Econjournals, vol. 8(3), pages 1-8.
    6. Fareeha Adil & Abdul Jalil, 2020. "Determining the Financial Inclusion Output of Banking Sector of Pakistan—Supply-Side Analysis," Economies, MDPI, vol. 8(2), pages 1-20, May.
    7. Bilgehan Tekin, 2021. "Modeling the Relation of Financial Integration-Economic Growth with GMM and QR Methods," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 8, pages 32-47.
    8. David Mhlanga & Adewale Samuel Hassan, 2022. "Financial Participation Among Smallholder - Farmers in Zimbabwe: What Are the Driving Factors?," Academic Journal of Interdisciplinary Studies, Richtmann Publishing Ltd, vol. 11, July.
    9. Idrees Liaqat & Yongqiang Gao & Faheem Ur Rehman & Zoltán Lakner & Judit Oláh, 2022. "National Culture and Financial Inclusion: Evidence from Belt and Road Economies," Sustainability, MDPI, vol. 14(6), pages 1-21, March.
    10. Inès Gharbi & Aïda Kammoun, 2023. "Developing a Multidimensional Financial Inclusion Index: A Comparison Based on Income Groups," JRFM, MDPI, vol. 16(6), pages 1-19, June.
    11. Thanh Tam Le & Nguyen Dieu Linh Dang & Thi Dieu Thu Nguyen & Thanh Son Vu & Manh Dung Tran, 2019. "Determinants of Financial Inclusion: Comparative Study of Asian Countries," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 9(10), pages 1107-1123, October.

    More about this item

    Keywords

    Determinants; Financial Inclusion; Dynamic GMM; Quantile regression;
    All these keywords.

    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jda:journl:vol.51:year:2017:issue2:pp:221-237. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Abu N.M. Wahid (email available below). General contact details of provider: https://edirc.repec.org/data/cbtnsus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.