Corporate management dilemma: the nexus between audit firm industry specialization, audit effort, and audit quality

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Type of the article: Research Article

Abstract
To defend its stewardship role to business owners, management often employs audit firm industry specialists to validate the reporting system’s authenticity. While auditing, these specialist auditors may expend additional effort to achieve audit quality. However, the direction of the association between audit firm industry specialization, audit effort, and audit quality is unknown. Therefore, this research analyzes the nexus between audit industry specialization, audit effort, and audit quality in Nigerian banks between 2011 and 2023. Audit firm industry specialization is proxied using a binary variable, where 1 represents an audit firm with a market share above 30 percent and 0 otherwise. Audit effort is proxied by audit report lag, defined as the cumulative number of days from the fiscal year-end to the day the auditor signs off the financial statements. Finally, audit quality is proxied by using a discretionary accrual model. The study utilized the panel vector autoregression model to examine the annual data of 11 banks. The findings in the three models indicate that in the first model, prior audit effort influences the current audit effort (coef = 0.226, p <0.05), while in the second model, both previous experience of specialization (coef = 0.872, p < 0.05) and audit effort (coef = 0.362, p < 0.05) influence the current audit firm industry specialization. Finally, in the third model, audit firm industry specialization drives high audit quality (coef = 0.069, p <0.05). The study concludes that corporate management appointment of specialist audit firms can result in extended audit report lag but with a positive effect on audit quality.

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    • Figure 1. Graph of stability condition
    • Figure 2. Impulse response function
    • Table 1. Diagnostic tests
    • Table 2. Panel unit root test
    • Table 3. Descriptive statistics and correlation matrix of the causal relationship between audit firm industry specialization, audit effort, and audit quality
    • Table 4. Lag order selection and estimation
    • Table 5. Baseline panel VAR model
    • Table 6. Granger causality test
    • Table 7. Stability condition analysis
    • Table 8. Forecast-error variance decomposition
    • Table 9. Results of the simultaneous equation model
    • Conceptualization
      Tajudeen John Ayoola
    • Data curation
      Tajudeen John Ayoola, Eghosa Godwin Inneh, Lawrence Ogechukwu Obokoh
    • Formal Analysis
      Tajudeen John Ayoola, Eghosa Godwin Inneh, Lawrence Ogechukwu Obokoh
    • Investigation
      Tajudeen John Ayoola, Eghosa Godwin Inneh
    • Methodology
      Tajudeen John Ayoola, Eghosa Godwin Inneh, Lawrence Ogechukwu Obokoh
    • Project administration
      Tajudeen John Ayoola, Eghosa Godwin Inneh, Lawrence Ogechukwu Obokoh
    • Software
      Tajudeen John Ayoola, Eghosa Godwin Inneh, Lawrence Ogechukwu Obokoh
    • Supervision
      Tajudeen John Ayoola, Lawrence Ogechukwu Obokoh
    • Validation
      Tajudeen John Ayoola, Eghosa Godwin Inneh
    • Visualization
      Tajudeen John Ayoola, Eghosa Godwin Inneh, Lawrence Ogechukwu Obokoh
    • Writing – original draft
      Tajudeen John Ayoola, Eghosa Godwin Inneh, Lawrence Ogechukwu Obokoh
    • Writing – review & editing
      Tajudeen John Ayoola, Eghosa Godwin Inneh, Lawrence Ogechukwu Obokoh