تحلیل اکتشافی دلایل واگرایی رابطه عدم تقارن اطلاعاتی و هزینۀ سرمایۀ سهام: رویکرد فراتحلیلی

اهداف: مطالعات تجربی متعددی رابطۀ عدم تقارن اطلاعاتی و هزینۀ سرمایۀ سهام را آزموده‌ و نتایج متناقضی گزارش کرده‌اند. برخی مطالعات این رابطه را مثبت، برخی منفی و برخی آن را غیرمعنی‌دار ارزیابی می‌کنند. کشف عوامل واگرایی جایگاه موثری در مدیریت عدم تقارن اطلاعاتی، هزینۀ سرمایۀ سهام و ثروت سهام‌دار دارد. در این پژوهش این موضوع بارویکرد فراتحلیل دنبال می‌شود.روش: فراتحلیل این پژوهش در هفت مرحله اجرا شد. برای این فراتحلیل 36 مطالعۀ منتشرشده بین سال‌های 1986 تا 2022 از نشریات با شاخص h حداقل برابر 1 پایگاه اسکوپوس استفاده شد. تعداد نمونۀ پژوهش 260 آزمون است که از مطالعات مذکور استخراج شده ‌است. با استفاده از نرم‌افزار سی ام ای 2 و آزمون‌های میانگین تک‌نمونه با رویکرد اثرات تصادفی و آزمون واگرایی علاوه‌بر آزمون 12 فرضیۀ نیرومندی نتایج براساس 18 طبقه تحلیل و 15 طبقۀ آن تایید شد.نتایج: نتایج نشان داد عدم تقارن اطلاعاتی بر هزینۀ سرمایۀ سهام تاثیر دارد. به‌جز متغیرهای کیفیت تحلیل‌گران و نوسان درآمد، همۀ ابعاد عدم تقارن اطلاعاتی بر هزینۀ سرمایۀ سهام تاثیر دارند. به‌علاوه عدم تقارن اطلاعاتی بر همۀ ابعاد هزینۀ سرمایۀ سهام تاثیر مثبت دارد.

exploratory analysis of the heterogeneity in the relationship between information asymmetry and the cost of equity capital: a meta-analytic approach

several empirical studies have tested the relationship between information asymmetry and the cost of equity capital and have reported conflicting results. some studies evaluate this relationship as positive, some as negative, and some as insignificant. the discovery of divergence factors has an effective role in managing information asymmetry, the cost of equity capital, and shareholder wealth. in this study, this issue is followed by the meta-analysis approach. this meta-analysis was carried out in seven stages. for this meta-analysis, 36 studies published between 1986 and 2022 from journals with an h index at least equal to 1 of scopus were used. the number of samples is 260 tests which were extracted from the mentioned studies. using cme2 software, divergence test, and one-sample t-test with random effects approach in addition to testing 12 hypotheses, the robustness check of the results was tested based on 18 categories of analysis, of which 15 categories confirmed the robustness. the results showed that information asymmetry affects the cost of equity capital. all dimensions of information asymmetry affect the cost of equity capital, except analysts’ quality and income volatility. in addition, information asymmetry has a positive effect on all dimensions of the cost of equity capital.keywords: information asymmetry, cost of capital, meta-analysis, divergence, effect size. introductionthe contribution of this study is to discover the reasons for the conflict in empirical studies using meta-analysis. information asymmetry exposes shareholders to risk and therefore demands higher returns. companies can reduce the cost of equity capital by reducing information asymmetry. some theoretical and experimental studies regarding the relationship between information asymmetry and the cost of equity capital have reported this relationship as positive, some negative, and some non-significant. the purpose of this study is to meta-analyze the effect of information asymmetry on the cost of equity capital to clarify the divergence of empirical studies and its reasons. hypothesis 1 is about the relationship between information asymmetry and the cost of equity capital. to check the robustness, this hypothesis was tested in different conditions. the next eleven hypotheses are related to the influence of the dimensions of the cost of equity capital on information asymmetry and the impact of the dimensions of information asymmetry on the cost of equity capital. method and datathis meta-analysis was performed in seven stages. in the first stage, as the research problem, the independent variable is information asymmetry and the dependent variable is the cost of equity capital. in the second stage, after determining keywords and databases, 188 empirical studies were downloaded. in the third stage, the studies of the previous stage were screened based on three criteria: 1) the subject of the study should be in accordance with hypothesis 1 of this meta-analysis, 2) the information related to effect size calculation should be reported in the paper, and 3) the study analysis method should be correlational. after the screening, 36 studies published between 1986 and 2022 including 260 tests (the statistical sample of this meta-analysis) were meta-analyzed. in the fourth stage the general data, the data related to effect sizes, and the data for robustness check were extracted. in the fifth stage, the effect size was calculated for each of the samples, and in the sixth stage, the cumulative effect size was calculated for each hypothesis. to test each hypothesis, z-statistic, and a significance level were obtained for each cumulative effect size, which shows the significance of the difference between the cumulative effect size and zero. in the seventh step, the homogeneity of the effect sizes was tested for each hypothesis. for hypotheses with heterogeneous/homogeneous effect sizes, the cumulative effect size was calculated with the fixed/random effects model. finally, in the eighth stage, the divergence reasons were explored.