Investigating the effect of corporate governance on audit quality and its impact on investment efficiency

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There is an academic discussion about investment efficiency, regarding its determinants and effects. Corporate Governance (CG) and Audit Quality (AQ) are determinants of investment efficiency The main objective of the article is to investigate the effect of CG and AQ on investment efficiency, this objective is divided into sub-objectives: to investigate the direct effect of CG on AQ, AQ on investment efficiency, and CG on investment efficiency. Moreover, the indirect effect of CG on investment efficiency through AQ as a mediator variable. This paper focuses on non-financial listed firms in the Egyptian Stock Exchange (EGX), especially firms recorded in EGX 100 for four years’ period (2013–2018), for 103 firms and 412 completed observations. The researcher uses Structural Equation Modeling (SEM) through SmartPLS software. The paper shows evidence that management that has good CG mechanisms obtains a suitable atmosphere to prepare transparent financial statements, which helps enhance the auditor’s role and improve AQ. Improving AQ lowering IA, which increases the trust of investors in management decisions, this leads to reduce pressure on management and improve efficiency of investment decisions. Having good CG mechanisms provides management with a good atmosphere to make right investment decisions, and having good CG mechanisms increases AQ, which helps management to have a good environment to make investment decisions with higher efficiency, or in other words, there is a significant and positive effect of integration between CG and AQ on investment efficiency.

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    • Figure 1. Research model to test hypotheses
    • Figure 2. Structural model (outer model), OVERINV model
    • Figure 3. Structural model (outer model), UNDERINV model
    • Figure 4. Measurement model (inner model), OVERINV model
    • Figure 5. Measurement model (inner model), UNDERINV model
    • Table 1. Descriptive statistics of the variables
    • Table 2. Model goodness of fit
    • Table 3. R-squares value
    • Table 4. Values of discriminant validity (cross-loading)
    • Table 5. Outer weights
    • Table 6. Path coefficient
    • Conceptualization
      Walid Shehata Mohamed Kasim Soliman
    • Data curation
      Walid Shehata Mohamed Kasim Soliman
    • Formal Analysis
      Walid Shehata Mohamed Kasim Soliman
    • Funding acquisition
      Walid Shehata Mohamed Kasim Soliman
    • Investigation
      Walid Shehata Mohamed Kasim Soliman
    • Methodology
      Walid Shehata Mohamed Kasim Soliman
    • Project administration
      Walid Shehata Mohamed Kasim Soliman
    • Resources
      Walid Shehata Mohamed Kasim Soliman
    • Software
      Walid Shehata Mohamed Kasim Soliman
    • Validation
      Walid Shehata Mohamed Kasim Soliman
    • Writing – original draft
      Walid Shehata Mohamed Kasim Soliman