Cash flows and accrual accounting in predicting future cash flows of Thai listed companies

Southern Cross University ePublications@SCU Theses 2005 Cash flows and accrual accounting in predicting future cash flows of Thai listed companies Porntip Chotkunakitti Southern Cross University Publication details Chotkunakitti, P 2005, 'Cash flows and accrual accounting in predicting future cash flows of Thai listed companies', DBA thesis, Southern Cross University, Lismore, NSW Copyright P Chotkunakitti 2005 ePublications@SCU is an electronic repository administered by Southern Cross University Library Its goal is to capture and preserve the intellectual output of Southern Cross University authors and researchers, and to increase visibility and impact through open access to researchers around the world For further information please contact epubs@scu.edu.au Cash Flows and Accrual Accounting in Predicting Future Cash Flows of Thai Listed Companies Porntip Chotkunakitti BBA (Accounting), MBA (Accounting) A thesis submitted to the Graduate College of Management of Southern Cross University, Australia, in partial fulfilment of the degree of Doctor of Business Administration 2005 Statement of Original Authorship The work contained in this dissertation has not been previously submitted for a degree or diploma at any other higher education institution I also certify that to the best of my knowledge, the dissertation contains no material previously published or written by another person except where references have been given, and any help received has been acknowledged Signed:…………………………………… Date:…………………… … Porntip Chotkunakitti ii Acknowledgments I wish to express my profound gratitude to all who have supported the completion of this thesis First, I would like to especially thank my supervisor, Associate Professor Michael D Evans for his valuable advice, full support, patience and encouragement Without him, this thesis would not have been completed Additionally, I indebted to Dr Mark Manning for his immense help in statistical techniques and data analysis My special thanks also go to the staff of the SCU Graduate College of Management at Tweed campus, Sue White, Susanna, Di Clarke for their administrative help My sincere gratitude goes to Rosemary Graham for her editing and recommendation on English in earlier draft of my thesis Additionally I appreciate Gita Sankaran for kindly editing and providing suggestions on English I acknowledge Dr Pranee Leksrisakul for providing secondary data involving the Stock Exchange of Thailand I also acknowledge my friends in the DBA program for the good friendship and help during my study in Australia I wish to thank Associate Prof Dr Aekkachai Nittayagasetwat, Assistant Prof Dr Pradit Withisupakorn, Assistant Prof Dr Sasivimon Sricharanjit and Dr Rojanasak Chomvilailuk for their helpful encouragement and suggestions I also wish to thank my College for help and support while I was writing my thesis in Thailand Also the partial grant from Rangsit University is acknowledged with thanks My deepest gratitude goes to my parents for their caring and unbounded support Without their support, I would have had no chance to study this program iii Abstract Cash flow prediction is involved in a number of economic decisions, particularly in investment Previous research conducted in the United States has provided inconsistency in the results of investigating accounting data, cash flow and accrual accounting data in predicting future cash flows No published research has studied cash flow prediction in Thailand The current study investigates the ability of accrual and cash flows accounting data to predict future cash flows of Thai listed companies Three regression models are constructed namely earnings, cash flows, accrual components and cash flows models In addition, cash flow ratios are investigated to predict future cash flows by using a stepwise regression Data used in this study is collected from the financial statements of non-financial companies listed on the Stock Exchange of Thailand from 1994 to 2002 Cash flow data are selected directly from the cash flow statements The empirical results show that past earnings, cash flows, cash flow and accrual component of earnings can be used to predict future cash flows of Thai listed companies and cash flows have better predictive power than past earnings Additionally, the cash flow model and the cash flow and accrual components of earnings model have better predictive power than the earnings model The findings of testing the models in an out-of-sample period suggest that the cash flow model is a better predictor of future cash flows than the other models Furthermore, additional year lags of accounting data can improve the predictive power of the model However, the results indicate that cash flow ratios are not a good predictor of future cash flows In addition, this study finds that the Asian economic crisis had an impact on the predictive power of accounting data Key Words: Cash flow prediction, Cash flow, Accrual, Earnings iv Abbreviations BOT The Bank of Thailand CFO Cash Flow from Operations EIU The Economist Intelligence Unit Limited FASB The Financial Accounting Standards Board IAS The International Accounting Standard IASC The International Accounting Standard Committee ICAAT The Institute of Certified Accountants and Auditors of Thailand NI Net Income NIDPR Net Income plus Depreciation and Amortisation SEC The Securities and Exchange Commission SET The Stock Exchange of Thailand TAS Thai Accounting Standard TBDC The Thai Bond Dealing Center UK United Kingdom US $ US dollar (The United States of America currency) USA United States of America WCFO Working Capital from Operations v Table of Contents Statement of Original Authorship ii Acknowledgments iii Abstract iv Abbreviations v Table of Contents .vi List of Figures x List of Tables xi Chapter 1: Introduction 1.1 Introduction .1 1.2 Background to the Research .1 1.3 Research Issues 1.4 Justification of the Research .5 1.5 Methodology 1.5.1 Data collection 1.5.2 Sample selection 1.5.3 Variables and measurement 1.5.4 Prediction model 1.6 Keywords and Abbreviations .9 1.7 Contribution of the Research 10 1.8 Limitations of the Proposed Research 11 1.9 Structure of the Thesis 11 Chapter 2: Thai Literature 14 2.1 Introduction .14 2.2 General Background to Thailand 16 2.2.1 Country profile .16 2.2.2 Thailand’s economy 17 2.3 Thai Accounting Standards 21 vi 2.3.1 The Institute of Certified Accountants and Auditors of Thailand (ICAAT) 21 2.3.2 Development of Accounting Standards in Thailand 21 2.4 The Stock Exchange of Thailand (SET) 25 2.4.1 Roles of the Stock Exchange of Thailand 25 2.4.2 Information Disclosure in the SET 28 2.5 Conclusion 30 Chapter 3: Literature Review 32 3.1 Introduction .32 3.2 Cash Flow Prediction 34 3.3 Accrual Accounting Data 38 3.3.1 Accrual accounting basis 38 3.3.2 Usefulness of accrual accounting data 41 3.4 Cash Flow Accounting Data .44 3.4.1 Cash flow accounting data 44 3.4.2 Cash flow statement 45 3.4.3 Usefulness of cash flow data 48 3.4.4 Cash flow ratios .51 3.5 Application of Cash Flows and Accrual Accounting Data in Predicting Future Cash Flow 56 3.5.1 Accrual based and cash flow based data in predicting future cash flow 56 3.5.2 Combined approach: cash flow and accrual-based approach 64 3.5.3 Other studies 74 3.6 Research Gaps, Research Issues and Model of Conceptual Framework 78 3.6.1 Research gaps 78 3.6.2 Research problem 79 3.6.3 Research questions 79 3.6.4 Research hypothesis 80 3.6.5 Conceptual framework .81 3.7 Conclusion 83 vii Chapter 4: Methodology 84 4.1 Introduction .84 4.2 Justification of the Research Paradigm 86 4.3 Research Design 89 4.3.1 The purpose of the study 89 4.3.2 The basic research method .90 4.4 Variables and Measurement .90 4.4.1 Dependent variable: future cash flows 91 4.4.2 Independent variables .92 4.5 Model Building 95 4.5.1 Earnings model 97 4.5.2 Cash flows model 98 4.5.3 Cash flows and accrual components of earning model 99 4.5.4 Cash flow ratios model 101 4.6 The Explanatory Ability of Models 102 4.7 Evaluation of the Predictive Ability of the Models in Out-of-sample 102 4.8 Hypothesis Testing 103 4.9 Data Specification 105 4.9.1 Testing periods 105 4.9.2 Sampling selection 106 4.9.3 Sources of data 107 4.10 The Validity of the Research 107 4.11 Conclusion 108 Chapter 5: Data Analysis .109 5.1 Introduction 109 5.2 Regression Equations and Models 111 5.3 Data Preparation 112 5.3.1 Data arrangement 112 5.3.2 Missing data 113 5.3.3 Outliers 115 5.3.4 Multicolinearity 115 5.4 Preliminary Analysis 116 viii 5.4.1 Descriptive statistics 116 5.4.2 Correlation analysis 119 5.5 Regression Results 125 5.5.1 Earnings model 125 5.5.2 Cash flows model 131 5.5.3 Cash flows and accrual components of the earnings model 137 5.5.4 Cash flow ratios model 145 5.6 Comparison of Explanatory Ability among Models 148 5.7 Evaluation of the Predictive Ability of the Models with Different Approaches 150 5.8 Test of Hypotheses 155 5.9 Additional Analysis 158 5.9.1 Test for the predictive ability of disaggregated accrual components of earnings 158 5.9.2 Pooled-year analysis excluding prediction year 1998 (economic crisis) 163 5.10 Conclusion 167 Chapter 6: Conclusion 169 6.1 Introduction 169 6.2 Conclusion of the Research Findings 171 6.3 Implications for Theory 181 6.4 Implications for Policy and Practice 182 6.5 Limitations of the Research Study 183 6.6 Suggestions for Future Research 184 6.7 Conclusion 185 References ix 6.5 Limitations of the Research Study The results of this research may be partially influenced by some limitations With time constraints and nonavailability of data sources, the current research is limited by the following issues Sample group The findings arising out of the research are confined to Thai listed companies in the nonfinancial sector The sample of this research excluded Thai listed companies in the financial sector such as commercial banks, finance and insurance companies Consequently, the findings may not apply to the companies in the financial sector Moreover, companies under rehabilitation were excluded from the sample, therefore the outcomes of this research cannot be used for companies under rehabilitation Time period The time period of this study from the year 1994 to 2002, involves many situations Firstly, Thai listed companies have been regulated to disclose cash flow statements since 1994 Secondly, the Asian economic crisis occurred during 1997 and 1998, and thirdly, a number of Thai accounting standards were revised and issued in 1999 In addition, according to the economic index, the economy of Thailand has recovered since 2000 after suffering from the crisis It is possible that these situations caused the instability of the predictive power of the models for each prediction year As a result, this research cannot produce efficient estimated equations suitable for every prediction year in relation to Thai listed companies Data analysis This study assumed that the cross-sectional regression model fits across firms from different industries That is, an explanatory variable in each prediction model would have the same effect on future cash flows across industries It is possible that the relationship between an explanatory variable and future cash flows is not stable across industries, which may have caused errors in the prediction 183 6.6 Suggestions for Future Research Further research can extend this study by replicating the methodology to investigate data of listed companies in the financial sector Moreover, the data sample can be separated and analysed by industry In this way, a contribution could be made to developing a more industry-specific theory In addition, this research generates prediction models by using a cross-sectional regression model which can be applied to general firms in the Thai stock market Perhaps the prediction model would prove more accurate if a firm-specific model is used, with data of each firm tested separately Nevertheless, future research has an opportunity to test longer time periods for the data, which could provide an appropriate prediction model for Thai listed companies The results of this research rely solely on a secondary data method The findings of this research would be given further credibility by conducting survey research to collect data directly from the users of financial statements or related parties Further research may provide evidence in practice, and users of financial statements could use cash flow predictors in predicting future cash flows This research used the technique of regression analysis to estimate the equation for predicting future cash flows It may be possible that the estimation of the regression model did not match the cash flow data In other words, a better model may be derived from a different method, such as the Box-Jenkins time-series model (Box & Jenkins 1976) However, that model needs many time-series of data Future research could be conducted when cash flow data is adequate Future studies may use the technique of the Box-Jenkins methodology to generate a prediction model and then compare it with the regression model It can be seen that the economic condition had an impact on the results of the current research Extended research could investigate the effect of the economic condition by considering economic indices such as the exchange rate, inflation rate and growth rate, thereby providing a clearer picture of how different economic conditions affect the accounting information to 184 predict future cash flows Moreover, it is possible that non-financial information is significant in predicting future cash flows Further research may include non-financial data such as a company’s financial policy, government aids and other economic factors in prediction models 6.7 Conclusion This final chapter concludes the research findings and implications In summary, earnings and cash flows can be used as predictors of future cash 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