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Fair Value Accounting

Implications for Users of Financial Statements

Series:

Kristian Bachert

Fair value accounting is viewed as a major feature of IFRS and several standards either require assets to be measured at fair value or at least provide an option to fair value measurement instead of applying historical cost. While it is argued that fair values provide more timely and relevant information, the global financial crisis led to a considerable debate about the usefulness of fair value accounting. The study examines the implications of fair value accounting for financial analysts and nonprofessional investors. It provides evidence that, even if financial analysts find it challenging to produce accurate forecasts under a fair value regime, nonprofessional investors make larger investments and are more confident with their judgments for fair value firms.

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Index

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of tables Table 3-1: Value relevance of fair value accounting for banks and financial institutions . 67 Table 3-2: Value relevance of fair value accounting for non-financial firms .................... 72 Table 3-3: Reliability of fair value accounting ................................................................ 78 Table 3-4: Predictability of accounting numbers ............................................................ 84 Table 4-1: Agency problems and possible solutions ........................................................ 96 Table 5-1: Number of firm-year observations per country ............................................ 129 Table 5-2: Number of observations with fair value accounting per country .................. 130 Table 5-3: Number of observations with fair value accounting per industry sector ....... 131 Table 5-4: Distribution of the fair value test variables per industry sector .................... 132 Table 5-5: Descriptive statistics of the independent variables ....................................... 134 Table 5-6: Descriptive statistics for the dependent variables ......................................... 136 Table 5-7: Correlations between the independent variables .......................................... 137 Table 5-8: Regression results for forecast accuracy ........................................................ 138 Table 5-9: Regression results for forecast dispersion ..................................................... 141 Table 5-10: Regression results for analyst following ..................................................... 143 Table 5-11: OLS regression results separately for each country ..................................... 146 Table 5-12: Rank regression results separately for each country .................................... 148 Table 5-13: OLS regression results for the matched sample design ............................... 150 Table 5-14: Rank regression results for the matched sample design .............................. 151 Table 5-15: Univariate analysis of the difference in differences estimators .................... 153 Table 5-16: OLS regression results of the difference in differences analysis .................. 156 Table 5-17: Rank regression results of the difference in differences analysis.................. 158 Table 6-1: Participants' risk-aversion classification based on lottery choices ................. 184 Table 6-2: Results for the manipulation checks ............................................................ 186 Table 6-3: Demographic and educational characteristics per...

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