The effect of the government bond value on the intermediary function of banks in the capital market of Indonesia

  • Received May 14, 2020;
    Accepted September 1, 2020;
    Published October 7, 2020
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/bbs.15(3).2020.17
  • Article Info
    Volume 15 2020, Issue #3, pp. 199-206
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The distribution of funds becomes the identity and function of banks. By performing this function well, the banks can get profit to survive. One of the considered factors affecting this channeling function is the issuance of government bonds to finance the state budget, which may be harmful to this bank channeling function. Therefore, to prove this situation, it is necessary to check a causal relationship between the government bond value and the bank intermediary function through this study, adding bank size and loans as a control variable.
This study utilizes the banks listed on the capital market of Indonesia as the population. Furthermore, the Slovin formula and a simple random sampling method are employed to determine the number of banks to be the samples and take them. Also, the regression model with pooled data and the t-statistic test are used to estimate its coefficients and examine the proposed hypotheses, respectively.
Overall, this study demonstrates that the government bond value positively affects the bank intermediary function. This indicates that the crowding-out does not exist. By this evidence, the government does not need to worry because this debt does not disturb the bank function to deliver the credit to society. Likewise, bank size and bad loans have a positive impact on this function. Thus, banks must be able to diversify risks among their assets and restructure bad loans when performing this function.

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    • Table 1. Research variables and their measurement
    • Table 2. Bank names serving as a sample
    • Table 3. Descriptive statistics outcome of the research variables
    • Table 4. The outcome of the classical assumption tests
    • Table 5. Pooled regression model estimation outcome: determinants of bank intermediary function
    • Conceptualization
      Rosemarie Sutjiati Njotoprajitno, Bram Hadianto
    • Formal Analysis
      Rosemarie Sutjiati Njotoprajitno, Bram Hadianto
    • Funding acquisition
      Rosemarie Sutjiati Njotoprajitno, Bram Hadianto
    • Investigation
      Rosemarie Sutjiati Njotoprajitno, Bram Hadianto, Melvin
    • Methodology
      Rosemarie Sutjiati Njotoprajitno, Bram Hadianto
    • Project administration
      Rosemarie Sutjiati Njotoprajitno
    • Resources
      Rosemarie Sutjiati Njotoprajitno, Melvin
    • Software
      Rosemarie Sutjiati Njotoprajitno, Bram Hadianto
    • Supervision
      Rosemarie Sutjiati Njotoprajitno, Bram Hadianto
    • Validation
      Rosemarie Sutjiati Njotoprajitno, Bram Hadianto, Melvin
    • Visualization
      Rosemarie Sutjiati Njotoprajitno, Bram Hadianto, Melvin
    • Writing – original draft
      Bram Hadianto, Melvin
    • Writing – review & editing
      Bram Hadianto
    • Data curation
      Melvin