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Determinant Of Efficiency Of The Islamic Banking In Indonesia

Author

Listed:
  • Nadiah Hidayati

    (School of Business, Bogor Agricultural University)

  • Hermanto Siregar

    (Bogor Agricultural University)

  • Syamsul Hidayat Pasaribu

    (Bogor Agricultural University)

Abstract

Dual banking system in Indonesia provides an excellent opportunity for the growth of Islamic banking industry in Indonesia. Islamic banking industry in Indonesia has improved in number of banks and branches but the performance of Islamic banks has decreased in recent years. This paper measures the efficiency of Islamic banking in Indonesia using the intermediation approach and the Data Envelopment Analysis (DEA) on quarterly reports of 10 Islamic Banks (BUS) and 15 Islamic Business Units (UUS). The results showed that Islamic Banks (BUS) and Islamic Business Units (UUS) in Indonesia has not been operating efficiently in its intermediation function. The estimation results of data panel regression model showed total financing and CAR have positive and significant impact, whereas the deposits have negative and significant impact to the efficiency of BUS and UUS in Indonesia.

Suggested Citation

  • Nadiah Hidayati & Hermanto Siregar & Syamsul Hidayat Pasaribu, 2017. "Determinant Of Efficiency Of The Islamic Banking In Indonesia," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 20(1), pages 1-20, July.
    • Handle: RePEc:idn:journl:v:20:y:2017:i:1a:p:1-20
    DOI: https://doi.org/10.21098/bemp.v20i1.723
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    Citations

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    Cited by:

    1. Juhro, Solikin M. & Narayan, Paresh Kumar & Iyke, Bernard Njindan & Trisnanto, Budi, 2020. "Is there a role for Islamic finance and R&D in endogenous growth models in the case of Indonesia?," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).
    2. Salisu, Afees A. & Ndako, Umar B. & Adediran, Idris A. & Swaray, Raymond, 2020. "A fractional cointegration VAR analysis of Islamic stocks: A global perspective," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    3. Wei, Wei & Zhang, Wan-Li & Wen, Jun & Wang, Jun-Sheng, 2020. "TFP growth in Chinese cities: The role of factor-intensity and industrial agglomeration," Economic Modelling, Elsevier, vol. 91(C), pages 534-549.
    4. Phan, Dinh Hoang Bach & Narayan, Paresh Kumar & Rahman, R. Eki & Hutabarat, Akhis R., 2020. "Do financial technology firms influence bank performance?," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).
    5. Aditya Anta Taruna & Cicilia Anggadewi Harun & Raquela Renanda Nattan, 2020. "Macroprudential Liquidity Stress Test: An Application to Indonesian Banks," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 9(special i), pages 165-187.

    More about this item

    Keywords

    Data panel; DEA; efficiency; Indonesia; Islamic banking;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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