Macroeconomic policy and profit rate of a company: A dynamic panel estimation and comparative analysis from Indonesia

  • 712 Views
  • 222 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

Macroeconomic policy (fiscal and monetary) dynamics are interesting to analyze, especially considering corporate performance. This paper aims to determine the effect of macroeconomic policy on the company’s profit rate. Effectiveness of tax revenue (ETAX), realization of tax revenue (RTAX), Bank of Indonesian rate (BIRT), investment growth (INVG), realization of investments (RINV), infrastructure fund allocation rate (INFR), and realization of infrastructure funds (RINF) are macroeconomic policy variables. This study uses a sample of 256 companies listed on the Indonesia Stock Exchange (IDX) in 2005–2019. This paper employs such methods as GMM, using Wald-test and Sargan’s test. GMM estimator result shows that the instrument of infrastructure fund realization policy (RINF), investment growth (INVG), and investment realization (RINV) affect the company’s profit rate (PROF). Therefore, companies need to pay attention to the government development plans, investment growth, and investment realization, which can improve company performance. The result, government’s development for the 2005–2009 and 2015–2019 periods shows a significant difference in companies’ ability to generate profits.

Acknowledgments
We would like to thank the Department of Management, Faculty of Economics and Business, Universitas Islam Nahdlatul Ulama Jepara (Unisnu), and the Institute of Research and Community Services (LPPM) Unisnu Jepara Indonesia, which has supported this study.

view full abstract hide full abstract
    • Table 1. Variable description and measurement
    • Table 2. Descriptive statistics of each industry
    • Table 3. Correlation matrix between the variables of each industry
    • Table 4. Result of panel unit root test
    • Table 5. Dynamic panel regression results of all sectors
    • Table 6. Dynamic panel regression results of the primary sector
    • Table 7. Dynamic panel regression results of the manufacturing sector
    • Table 8. Dynamic panel regression results of the service sector
    • Table 9. Comparison of profit rates between both cabinets
    • Table 10. Comparison of profit rates between both cabinets in the industrial sector
    • Conceptualization
      Hadi Ismanto, Silviana Pebruary
    • Data curation
      Hadi Ismanto, Silviana Pebruary, Dewi Nur Maulidiyah
    • Formal Analysis
      Hadi Ismanto, Silviana Pebruary, Dewi Nur Maulidiyah
    • Funding acquisition
      Hadi Ismanto
    • Investigation
      Hadi Ismanto, Silviana Pebruary, Dewi Nur Maulidiyah
    • Methodology
      Hadi Ismanto, Silviana Pebruary
    • Project administration
      Hadi Ismanto
    • Resources
      Hadi Ismanto
    • Software
      Hadi Ismanto, Dewi Nur Maulidiyah
    • Validation
      Hadi Ismanto, Silviana Pebruary
    • Visualization
      Hadi Ismanto, Dewi Nur Maulidiyah
    • Writing – original draft
      Hadi Ismanto, Silviana Pebruary, Dewi Nur Maulidiyah
    • Writing – review & editing
      Hadi Ismanto, Silviana Pebruary
    • Supervision
      Silviana Pebruary