Marinakis, Pantelis (2011) An investigation of earnings management and earnings manipulation in the UK PhD thesis, University of Nottingham Access from the University of Nottingham repository: http://eprints.nottingham.ac.uk/12874/1/555391.pdf Copyright and reuse: The Nottingham ePrints service makes this work by researchers of the University of Nottingham available open access under the following conditions This article is made available under the University of Nottingham End User licence and may be reused according to the conditions of the licence For more details see: http://eprints.nottingham.ac.uk/end_user_agreement.pdf For more information, please contact eprints@nottingham.ac.uk AN INVESTIGATION OF EARNINGS MANAGEMENT AND EARNINGS MANIPULATION IN THE UK Pantelis Marinakis, Msc Thesis submitted to the University of Nottingham Doctor of Philosophy April 2011 for the degree of Abstract What causes managers to manipulate their financial statements? How best can shareholders or prospective investors, auditors, financial analysts and regulators detect earnings manipulations? Addressing these questions is of critical importance to the functioning efficient of capital markets For an investor it can result to improved returns, for an auditor it can mean avoiding costly litigation, for an analyst it can mean avoiding a damaged reputation, and for a regulator it can lead to enhanced investor fewer investment disasters The objective of this thesis is two-fold The and protection first objective is to investigate the frequency and the magnitude of earnings management Second, is to provide an analysis of the characteristics of companies discovered to manipulate earnings and the determinants of these manipulations Exploratory interviews with the Financial Reporting Review Panel suggest that earnings manipulation usually results from escalating earnings managementthat after a certain stage violates accounting principles This is analysed in a review of a series of companiespublicly criticised for applying aggressiveaccounting practises.It is suggested that these cases involve specific accounting standards that require increasedjudgement from management In order to gain a broader view of the extent that companies manage earnings, this thesis examines the distribution of earnings among thresholds such as zero low decreases documents This and earnings thesis evidence of unusually earnings frequencies of small decreases in earnings and small losses and unusually high frequencies of small increases in earnings and small positive earnings Additional evidence suggests that three components of earnings, cash flow from operations, changes in working capital and discretionary accruals, are used to achieve increases in earnings Finally, manipulate this thesis presents evidence of the characteristics of firms that earnings and proposes a model for detecting earnings manipulation Companies found to manipulate lower have to accrual quality, earnings appear declining performance, weaker corporate governance structure, weaker balance sheet logistic leverage increased is investigation The scaled a and probability output of this model for discriminating accounting manipulations, where higher values suggest a greater probability of manipulation I Blank Page Acknowledgements I would like to thank my supervisors Professor John Hasseldine and Professor Bob Berry for their guidance and support during my studies Above all, I am indebted to my family for their support and motivation List of Tables 4.1 Financial Reporting Review Panel's Objectives 62 6.1 Descriptive statistics by year for scaled values of change in earnings and earnings levels 6.2 Descriptive statistics for the data sample 6.3 Distribution of adjacent to zero earnings and non-discretionary 134 135 earnings relative to 154 targets 6.4 Proportion of observations missing an earnings threshold before and after 158 discretionary accruals 6.5 Transition matrices indicating the frequency of movement of observations from classesof non-discretionary earningsto classesof earningsrelative 159 to target 7.1 Cases referred to the Panel and subsequent action taken by the FRRP in relation to 180 the financial reports with financial year-end beginning or after 1994 7.2 Size, time and industry characteristics for a sample of 98 cases subject to adverse ruling by the FRRP 7.3 Company financial characteristics, measured at beginning 182 of defect year Comparison between `manipulators' and 'controls' 7.4 Type and effect of accounting violation in the sample of 98 violators 183 185 7.5 Financial performance of FRRP and control sample companies from one year defect the to year one year after prior 7.6 Corporate governance characteristics for companies in FRRP and control 188 samples 7.7 Variables' Definitions 7.8 Financial characteristics and ratio analysis for FRRP and control samples 191 199 200 7.9 Comparison between FRRP companies and controls applying logistic regression models 8.1 Comparing characteristics between the two sub-samples of manipulators 8.2 Distribution 211 in for the estimation sample controls and manipulators of variables (years: 1994-2003) 8.3 WESML 201 215 for Beneish's (1999) model, results and unweighted probit estimation based on estimation sample of 132 Manipulators and 2,636 controls 219 8.4 Sensitivity analysis to the choice of estimation and holdout samples Descriptive for 2,363 based 132 100 and manipulators estimation of statistics on random samples 222 controls 8.5 Cut-off probabilities and probability of Type I and Type II errors for various 225 levels of relative costs in the estimation 8.6 WESML and unweighted probit estimation results based on an Estimation Sample 230 of 132 manipulators and 2,636 controls 8.7 Sensitivity Analysis to the choice of Estimation and Holdout Samples Descriptive Statistics for Estimation Based on 100 Random Samples of 132 Manipulators and 2,363 Controls 222 8.8 Cut-off probabilities and Probability of Type I and Type II Errors for Various Levels of Relative Costs in the Estimation Sample and in the Holdout Sample 235 List of Figures 2.1 The three conditions generally present when fraud occurs 2.2 The distinction between earnings management and earnings manipulation 23 27 2.3 Earnings management - earnings manipulation and potential wealth transfers 30 55 3.1 Summary of the thesis 90 5.1 Extract from Isoft's Annual Report 95 5.2 Share Price of Northgate plc 111 5.3 Extract from the accounts of Grainger 6.1 Empirical distribution of changes in earnings after tax scaled by market 137 value 6.2 Three empirical distributions of changes in earnings categorised according to the 139 firm for the pattern of proceeding earnings 6.3 The distribution of earnings after tax scaled by beginning of the year market 142 value 6.4 Three empirical distributions of earnings scaled by market value categorised for firm the to the according pattern of proceeding earnings 6.5 Conditional distributions of earnings against current assets' percentiles 6.6 Conditional distributions of earnings against current liabilities' 143 146 percentiles 147 6.7 Conditional distributions of earnings against operating cashflows' percentiles 148 6.8 Conditional distributions of earnings against percentiles of previous year's cash flow from operations 6.9 Conditional distributions of earnings against discretionary accruals 6.10 Conditional distributions of earnings against non-discretionary 150 151 accruals 152 163 6.11 Interquartile distributions of earnings scaled by market value 6.12 Characteristics of the observations with small positive earnings and small earnings increases 6.13 Robustness test using scaling by sales to investigate the distribution changes and earnings levels 6.14 Robustness test using scaling by assets to investigate the distribution changes and earnings levels 164 of earnings 165 of earnings 166 7.1 Median level and change in reported earnings, scaled by beginning of year equity, for the FRRP and control samples Separate plots are presented using the Profit after tax, before 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