한국채택국제회계기준의 도입과 재무분석가의 이익예측치 특성

This study examines the effect of K-IFRS adoption in terms of financial analysts' forecast characteristics. Since K-IFRS was adopted in 2011 as a mandatory, many researchers have investigated a change in accounting information qualities and value relevance. However, K-IFRS adoption influences not only producers of accounting information but also users of accounting information. Moreover, increased a level of discretionary decision when a firm applies K-IFRS in financial statements may affect the decision of investors and financial analysts' forecast as well. Because of that, the role of financial analysts as a information intermediary becomes important. There are controversial evidences about the effect of K-IFRS on financial analysts' forecast. On the one hand, a change in main financial statements from individual statements to consolidated statements may affect a cost of financial analyst' forecast in a negative way. Moreover, increased discretionary decision of management on financial statement may hamper financial analysts's forecasts. On the other hand, increased amounts of disclosure and applied fair value concepts in account components may positively affect a financial analyst's forecast. Some prior studies found the evidences that financial analysts' accuracy increased and dispersion of forecasts decreased after IFRS adoption (Wang et al.2008; Tan et al. 2011; Horton et al. 2013). However, Horton et al. (2013) suggests that qualities of financial analyst's forecast may vary depending on characteristics of countries IFRS adopted. Therefore, the effect of K-IFRS on financial analysts' forecast is worthwhile to test. It is purely an empirical question. To do this, this paper uses 1,977 observations from 2007 to 2012. Specifically, this paper examines financial analysts' forecast characteristics such as forecast accuracy, forecast dispersion, financial analysts following before and after K-IFRS adoption. To see a change in forecast characteristics during the period, this paper use firms with financial analysts' forecasts regardless of voluntary or mandatory adoption in main test. Even though incentives to adopt K-IFRS may vary depending on voluntary versus mandatory, characteristics of financial analysts' forecast do not affected by the time of adoption. This paper further examines whether the effect of K-IFRS adoption on financial analysts' forecasts is more pronounced in mandatory firms. Because related prior studies suggest that qualities of accounting information that applied IFRS are affected by incentives of firms. This difference may influence qualities of financial analysts' forecast. The results of this paper are following. First, forecast accuracy is improved after K-IFRS adoption and forecast dispersion has also decreased. This result suggests that qualities of financial analysts' forecasts improve after K-IFRS adoption. However, analysts following has decreased after K-IFRS adoption. It means that financial analysts would not like to follow a firm anymore because they need to put more efforts to provide forecasts after K-IFRS adoption. These findings are identical in several robustness tests. Second, the effect of K-IFRS on financial analysts' forecasts is more pronounced in mandatory firms. This is very interesting finding because most studies identify that accounting qualities of voluntary firms improve after IFRS adoption compared to that of mandatory firms in Europe. This means that K-IFRS adoption influences most companies, not only voluntary firms who have some incentives. This paper performs several robustness tests to address some statistical problems and to alleviate the impact of financial crisis in 2008. I found identical results from GMM and CL-2 tests except for forecast accuracy. When i applies CL-2, forecast accuracy has increased, but statistical significance decreased. This suggests that the result of forecast accuracy is limited. The findings in this study have various implications. The results of this paper suggest that K-IFRS adoption affects financial analysts' forecasts. Specifically, this paper found that forecast accuracy and dispersion of financial analysts' forecast improved after K-IFRS. This result implies that K-IFRS adoption positively affects financial analysts' forecasts. Another result of this paper is that financial analysts following decreased after K-IFRS. This result implies that financial analysts do not follow many firms anymore. There are some reasons. One of the reasons is that cost of forecast increases since K-IFRS and this leads financial analysts would not like to evaluate many firms. In sum, these findings are very useful in understanding the effect of K-IFRS on financial analysts' perspectives and provide a lot of important implications to companies, regulators, investors who are interested in financial analysts' forecast characteristics. Researchers who are interested in this area can also apply the discussion in this paper for the related studies.