The Relationship Between Fair Value Hierarchy Measurement And The Efficiency Of Analysts’ Forecast

In the case of Smyth v.s. Ames, the fair value measurement was firstly proposed in the United States. In September 2006, FASB announced the fair value hierarchy measurement in the Statement of Financial Accounting Standards No. 157, which create a new era for the development of fair value measurement both in practice and in theory. In January 2014, China’s Finance Ministry issued the Accounting Standards for Business Enterprises No. 39, or the Fair Value Measurement Standard for short, generating a new definition, requiring all the business enterprises adopt the fair value hierarchy measurement to measure and disclose the assets or debts which meets the requirement.The fair value hierarchy measurement provides an efficient method to measure and disclose the fair value scientifically and rationally. This method divides the fair value into three levels according to the sources and the degree that it can be proved. Through this method financial statement users can not only understand the financial information more easily but also can get high qualitative information. Scholar can better understand the characteristic of fair value, and the accountants can work with more specific standards.Since the Fair Value Measurement Standard was issued, this method whether can improve the information quality, and whether can help the financial statement users make decisions and help the capital markets operate more efficiently have drawn the attention of accounting standards institutions, business enterprises and investors.As the rational users of financial statements, analysts can comprehend the inside information of fair value hierarchy and judge the relativity and reliability of information. Analysts decide in what content that they can trust the fair value information to forecast earnings. So the efficiency of forecast can reflect the attitude of analysts towards fair value and help the accounting standards institutions and investors understand the quality of fair value.Based on the decision usefulness, from the perspective of analysts forecasts following, forecasts dispersion and forecasts error, this paper chooses the listed company between 2007-2014 as samples to test the relationship between the three levels of fair value and analysts forecast efficiency. This paper explores the influence that the fair value put on the decision that analysts make, to test the information quality of each level of fair value.Through the descriptive statistics analysis and regression analysis, this paper concludes:(1) the level 1 of fair value can improve the efficiency of analysts’ forecast, which shows that the level 1 of fair value can reflect the real value of assets and debts fairly, providing relative and reliable;(2) the quality of the level 2 of fair value is below the level 1 of fair value, but the analysts also trust that it can help the users of financial statement make better decision;(3) the quality of level 3 fair value is questioned by analysts because its inputs, evaluation process, the evaluation error and the opportunism of manager. The level 3 of fair value doesn’t show good quality of information, which can’t help users of financial statement understand the financial condition and operating results.