- Original authors / creators
- Muhammad Arslan Iqbal; Md Abdur Rouf Sarkar; Majed Alharthi; Md Jahid Ebn Jalal; Md Naimur Rahman
- Original publication
- PLOS One · Public Library of Science · 2025-06-03
- License & retained notices
- CC BY 4.0
© 2025 Iqbal et al
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This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Article-specific license URL: https://creativecommons.org/licenses/by/4.0/ - Edition changes
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- Evidence limits
- Adjacent research, not a directly sampled family-office study. Applicability to a family office requires separate assessment. The Two-Step System GMM model was utilized to address potential endogeneity concerns and enhance the precision of estimations [147,148,164]. This approach effectively mitigates unobserved heterogeneity and inter-variable correlation, which could otherwise bias estimates in the baseline model. Using moment conditions derived from the independence of instrumental variables and error terms, the GMM model enables parameter estimation while tackling omitted variable bias and reverse causality. It is particularly suitable for dynamic panel data analysis as it incorporates both lagged and contemporaneous variables [148]. In our dataset, variables such as ICC, IRQ disclosure, CGQ, and their interactions were treated as endogenous, and instrumental variables derived from lagged values were employed to address endogeneity. The validity of this approach hinges on the assumption that lagged values are uncorrelated with the current error term [148]. The study makes three key contributions to the literature. First, it extends the understanding of voluntary information disclosure by highlighting the joint impact of IRQ and CGQ on ICC, particularly in the context of mature markets. Second, it employs advanced econometric methods, such as IV2SLS and system-GMM, to address potential endogeneity issues, setting a methodological benchmark for future research. Third, it provides practical insights for firms and policymakers, emphasizing that adopting high-quality integrated reporting and enhancing governance standards can lower financing costs and improve investor confidence. By refining agency theory, the study demonstrates that integrated reporting mitigates information asymmetry between firms and investors, while strong governance structures reduce agency conflicts, further lowering the cost of capital. Despite its contributions, this study has certain limitations. The focus on firms in Australia and New Zealand restricts the geographical scope of the findings. Additionally, the study does not establish causal relationships between IRQ and ICC, highlighting the need for future research employing causal inference techniques, such as machine learning methods. Further investigations could explore the effects of alternative disclosure practices, such as sustainability or environmental reporting, on the cost of equity capital. Future studies could also examine the implications of IRQ adoption on firm performance, shareholder value, and executive decision-making, while categorizing firms based on the extent of their IRQ disclosure (full, partial, or non-adoption).
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