Implementation errors during the transition to the International Financial Reporting Standards, Chief Financial Officer's compensation and turnover and earnings quality metrics
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First, the thesis investigates the relation between the Chief Financial Officer's (CFO's) accounting talent, his/her compensation and his/her turnover. The thesis contends that accounting talent of the CFO can be measured by implementation errors, when a country moves to the International Financial Reporting Standards (IFRS) by adopting a "big bang" approach where all firms have to adopt IFRS within the same accounting period without the opportunity of early or late adoption. Eighteen different accounting errors are hand-collected for a sample of 280 Australian companies, which is used in constructing the CFO's accounting talent. The thesis finds (i) a positive relation between the CFO's accounting talent and the CFO's compensation ex-ante in the transition year, (ii) a positive relation between the CFO's accounting talent and the CFO's bonus compensation in the subsequent year (adoption year) and (iii) an inverse relation between the CFO's accounting talent and the CFO's turnover in the subsequent year (adoption year). Further tests on the Chief Executive Officer's (CEO's) accounting talent and the CEO's compensation and turnover and alternative specifications of our variables confirm our results. Overall the findings bring into question the outcomes of government intervention in setting executive compensation. Second, the thesis investigates the extent to which commonly used earnings quality metrics capture implementation errors. The metric used to measure implementation errors is the same as the measure used for the CFO's accounting talent. A positive relation is expected, between some commonly used earnings quality metrics and implementation errors as these metrics have been claimed to capture the extent to which earnings are calculated with errors. Ranging from highest to lowest in terms of explanatory power, from OLS regressions are: total accruals, earnings persistence, accruals quality and earnings predictability. Implementation errors in reported earnings however do not explain variations in "abnormal" accruals as estimated from a firm-specific time-series regressions of the modified Jones model and in earnings smoothness. Overall the results have implications for researchers and provide guidance regarding the appropriateness of earnings quality metrics selected in their research setting. The results also point to the fact that total accruals may be a "better" proxy for implementation errors compared to more "sophisticated" models.
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