Designing a Model for Assessing the Costs of Asymmetric Information from the Perspective of Earnings Valuation and Earnings Selectivity

Authors

Keywords:

Asymmetric Information Costs, Earnings Valuation, Earnings Selectivity, Earnings Quality, Earnings Management, Panel Data, Tehran Stock Exchange

Abstract

This study aimed to design and empirically validate a model for assessing asymmetric information costs from the perspectives of earnings valuation and earnings selectivity among firms listed on the Tehran Stock Exchange. This applied, descriptive-correlational study used a two-stage design. In the expert stage, 120 fundamental market analysts were selected purposively to evaluate 28 candidate variables related to earnings valuation and earnings selectivity. After screening, 26 variables were retained and subsequently classified into valuation- and selectivity-related dimensions. In the archival stage, 170 listed firms were selected through screening criteria and examined over 2015–2024, yielding 1,700 firm-year observations. Asymmetric information cost was measured using a market-based price-impact proxy. Data were analyzed using descriptive statistics, Kolmogorov-Smirnov testing, Pearson correlations, augmented Dickey-Fuller tests, F-Limer and Hausman tests, regression diagnostics, fixed-effects panel regression, stepwise model optimization, and the Vuong test in Excel, SPSS, and EViews. The valuation model retained earnings persistence, predictability, timeliness, conditional and unconditional conservatism, earnings-response coefficient, revenue-expense matching, expected profitability growth, and return on assets, together with firm size, loss status, and leverage. The model was significant and explained 63.6% of the variation in asymmetric information costs. The selectivity model retained discretionary accrual earnings management, real earnings management, accrual quality, accrual–cash flow correlation, total-accrual management, earnings variability, cash-flow-to-operating-income volatility, classification shifting, and income smoothing, plus the same control variables, explaining 74.2% of the variance. The Vuong test showed a significant difference between the two models, with the selectivity model demonstrating greater explanatory power. Asymmetric information costs are explained by both valuation-related and selectivity-related earnings characteristics, but the selectivity dimension provides stronger explanatory power, highlighting the importance of earnings quality, manipulation, volatility, and classification attributes in shaping firms’ information environments.

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Aghakhani, M., Khodabakhshi Parijan, K., & Alifarri, M. (2027). Designing a Model for Assessing the Costs of Asymmetric Information from the Perspective of Earnings Valuation and Earnings Selectivity. Journal of Management and Business Solutions, 1-28. https://www.journalmbs.com/index.php/jmbs/article/view/471

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