فهرست نشریات علمی دسترسی آزاد ایران

Earnings forecasting by management is one of the mechanisms through which management provides information about the firm's future profitability status. We conducted this study with the aim of providing a model to identify factors affecting the accuracy of management earnings forecasts (MEF) in Iranian firms on the Tehran Stock Exchange (TSE). This research is analytical, applied, and ex post facto. The empirical analysis comprises a panel data set of 131 listed firms on the TSE from 2010 to 2019. We employ Bayesian averaging and dynamic averaging approaches to determine the optimal model. For identifying the most important influencing variables on the accuracy of MEF used, the BMA, TVP-DMA, TVP-DMS, BVAR and, OLS models. The findings exhibit that the BMA model had the highest efficiency. Based on this, we entered 50 identified variables affecting the accuracy of MEF into 5 categories (including intra-firm, audit, financial ratios, macroeconomic variables, and managerial governance indicators) in the Bayesian averaging model. We identified 13 essential variables that had an impact on the accuracy of the MEF, based on the increase of the posterior probability compared to the prior probability and the posterior probability level being higher than the threshold level. These variables include MEF of the past period, firm profit or loss, discretionary accruals, type of industry, audit committee, Leverage, operational debts ratio, return on equity, economic uncertainty, economic growth fluctuations, inflation, accrual earnings management, and management ability. According to the results, several factors influence the MEF and this indicates that the MEF is the multi-dimensionality. Therefore, managers need to have a systemic perspective to reduce the MEF error.