Determinants of Indonesian stock market development: Implementation of an ARDL bound testing approach

  • Received September 3, 2023;
    Accepted October 10, 2023;
    Published October 19, 2023
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/imfi.20(4).2023.07
  • Article Info
    Volume 20 2023, Issue #4, pp. 69-82
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The Indonesian stock market is a growing financial industry that plays a strategic role in the growth of the country’s economy. Its development is affected by various factors. This study examined the impact of the exchange rate, gross domestic product (GDP), interest rates, inflation, foreign portfolio investment (FPI), and domestic political stability on stock market capitalization. Quarterly data between 2000:Q1 and 2020:Q4 are used. The autoregressive distributed lag (ARDL) method is applied to identify long-run relationships between variables. To understand how fast the system reaches equilibrium after a shock, the model also examines short-run relationships using an error correction model (ECM). The findings show that the impact of exchange rate, interest rate, and inflation on stock market capitalization is negative in the long run. While the GDP, FPI, and political stability are positive. Increment in the US Dollar against the Indonesian Rupiah, interest rate, and inflation by 1% respectively, caused stock market capitalization to fall by 1.31%, 0.06%, and 0.04%. A rise in GDP, FPI, and political stability by 1% respectively, increases the stock market’s value by 1.17%, 1.08%, and 1.28%. In the short run, the coefficient of ECM indicates the speed of adjustment of the system: the occurrence of the shock to reach long-run equilibrium is quick enough, at 63.8% each quarter. The study recommends governments evaluate the impact of these factors when formulating monetary policies, promote economic growth, and continuously implement good governance, thus supporting stock market development.

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    • Figure 1. Graphical view of CUSUM
    • Figure 2. Graphical view of CUSUM of Square
    • Table 1. Summary statistics
    • Table 2. PP test results
    • Table 3. Optimal lag length selection
    • Table 4. Estimation of ARDL model (1, 1, 0, 4, 3, 1, 2)
    • Table 5. ARDL bound testing for cointegration
    • Table 6. Long-run coefficients estimation of ARDL (1, 1, 0, 4, 3, 1, 2)
    • Table 7. Short-run coefficients estimation using the ARDL (1, 1, 0, 4, 3, 1, 2)
    • Table 8. Diagnostic checking
    • Conceptualization
      Elmira Siska, Oyyappan Duraipandi
    • Data curation
      Elmira Siska
    • Formal Analysis
      Elmira Siska
    • Funding acquisition
      Elmira Siska
    • Investigation
      Elmira Siska
    • Methodology
      Elmira Siska, Oyyappan Duraipandi, Purwanto Widodo
    • Project administration
      Elmira Siska
    • Resources
      Elmira Siska, Oyyappan Duraipandi, Purwanto Widodo
    • Software
      Elmira Siska, Purwanto Widodo
    • Validation
      Elmira Siska, Oyyappan Duraipandi, Purwanto Widodo
    • Visualization
      Elmira Siska, Oyyappan Duraipandi, Purwanto Widodo
    • Writing – original draft
      Elmira Siska
    • Writing – review & editing
      Elmira Siska, Oyyappan Duraipandi, Purwanto Widodo
    • Supervision
      Oyyappan Duraipandi, Purwanto Widodo