Thanapat reungsri - Luận án tiến sỹ của tác giã nước ngoài liên quan đến đề tài về kiểm toán
THE IMPACT OF PUBLIC INFRASTRUCTURE INVESTMENT ON ECONOMIC GROWTH IN THAILAND Thanapat Reungsri Bachelor of Arts in Economics (Thammasat University, Thailand) Master of Management in International Business (Monash University, Australia) Thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy School of Economics and Finance Faculty of Business and Law Victoria University Australia January 2010 i Abstract Infrastructure traditionally holds centre place in nations‟ economic planning. New infrastructure promotes economic growth, expands trade, reduces poverty and improves the environment. Its importance worldwide invites significant informed debate over the effects of public infrastructure investment on economic development. In economic downturns, the weighting of infrastructure investment in national budgets makes it a frequent contender for substantial cuts. During the Asian economic crisis in 1997, many infrastructure projects in Thailand were suspended or terminated. The inability to maintain an appropriate level of expenditure led to substandard transport and utilities for the country, impeding its growth. Because of the crisis, a fiscal sustainability framework was established by the Thai government to ensure adequate levels of revenue and investment expenditure within a balanced budget. This study investigates the effects of public infrastructure investment on economic growth under Thailand‟s fiscal sustainability framework. A recursive supply-side model based on the Standard Neoclassical Model framework is used using Thai national data on public revenue (taxes, non-tax revenue and debt) to estimate infrastructure investment. An aggregate production function is used based on quarterly time series data from 1993 to 2006. This period comprises economic circumstances in Thailand including recession and recovery. Variables were subjected to unit root test to justify stationary status. If all variables were stationary, the Ordinary Least Square (OLS) method was used in estimation. If all variables were non-stationary and of an order I(1), then the cointegration test was conducted for long- run equilibrium. If the variables confirm cointegration, then the Error Correction Model was estimated using OLS, as the error correction term is constructed to estimate for coefficients. If the variables were found to have a mix of stationary and non-stationary variables, then the Autoregressive Distributed Lag model was used in the estimation. Finally, a simulation process was conducted, based on the estimated model, termed Infrastructure Finance Model for Emerging Economies. Simulation was carried out with ex-ante and ex-post scenarios: to generate a time-path within the data time period to prove model consistency; and for time- path values beyond the time period to provide prediction for policy decisions. The simulation consists of five scenarios: maximum borrowing or 20 per cent of budget; 15 per cent of budget; 10 per cent of budget; 5 per cent of budget; and no borrowing, or no effect on budget. ii The results indicate that public infrastructure investment has a mixed effect on domestic growth. A positive result is found in lagged public investment as a proportion of GDP at the third quarter, confirming that infrastructure capital has a positive significant effect on economic growth. However, a negative impact is found in lagged real government investment at the second quarter. As public investment increases, the demand for resources also increases and, given full capacity for the economy, this may lead to increased costs of private investment, resulting in a fall in private investment and thus reduce economic growth (crowding-out effect). Hence, under conditions of full capacity, an increase in public investment could result in negative impact on growth. The Infrastructure Finance model is therefore a useful indicator of private sector intentions for resource expenditure. iii Declaration “I, Thanapat Reungsri, declare that the PhD thesis entitled The Impact of Public Infrastructure Investment on Economic Growth in Thailand is no more than 100,000 words in length including quotes and exclusive of tables, figures, appendices, bibliography, references and footnotes. This thesis contains no material that has been submitted previously, in whole or in part, for the award of any other academic degree or diploma. Except where otherwise indicated, this thesis is my own work”. Signature Date iv Acknowledgements My sincere gratitude is extended to those who contributed to the fulfilment of this study. Deep appreciation is offered to Dr Kandiah Jegasothy, my principal supervisor from the School of Applied Economics, Victoria University, for his generous guidance and encouragement throughout. As well as academic assistance, Dr Jegasothy assisted me in gaining a new perspective on life overcoming difficulties that arose during the years of studying. My appreciation is also extended to Dr Segu Zuhair, my co-supervisor from the School of Applied Economics, Victoria University, for his constructive comments and suggestions in writing this thesis. The financial support extended by the Thai Bureau of the Budget was the foundation for this undertaking and I thank them sincerely for the opportunity to contribute this thesis for the benefit of my country. I owe a great debt to my father, parents-in-law, sister, brother, colleagues and friends for their understanding and encouragement during a difficult time. The honour of this success is dedicated to my mother, who passed away in a car accident in October 2007. She gave me the confidence to pursue my dream so that I could set out to make this doctoral degree a reality. Of great importance is the person who made this honour possible; my wife Patama Suchikul Reungsri has always stood by my side, supporting and encouraging me. I also thank my daughter, Napaskul Suchikul Reungsri (Melbourne) for being my inspiration and making me laugh during hardship. v Dedication Dedicated to the three ladies of my life Mother, Sutusanee Reungsri Wife, Patama Suchikul Reungsri Daughter, Napaskul Suchikul Reungsri vi Table of Contents Abstract i Declaration iii Acknowledgements iv Dedication v List of Abbreviations ix List of Tables xi Chapter 1 Introduction to Study 1 1.1 Research Antecedents 1 1.2 Statement of Purpose 5 1.3 Study Objectives 6 1.4 Research Scope and Significance 7 1.5 Methodology 9 1.6 Chapter Summary 10 Chapter 2 Context of the Research 12 2.1 Economic Growth 12 2.1.1 Economic Growth Theory 13 2.1.2 Determinants of Economic Growth 16 2.2 Infrastructure Development 18 2.2.1 Definitions 19 2.2.2 Measures 20 2.2.3 Economic Effects 21 2.2.4 Social Effects 22 2.2.5 Studies on Development 26 2.2.6 Summary 29 2.3 Infrastructure Finance 29 2.3.1 Sources 29 2.3.2 Studies on Financing 32 2.4 Conclusion 35 Chapter 3 Methodology Review 37 3.1 Model Overview 38 3.2 Single Equation Models 39 3.2.1 Production Function 39 3.2.2 Cost function 45 3.2.3 Profit function 47 3.2.4 Dual function 48 3.2.5 Function Analysis 50 3.3 System Models 51 3.3.1 Full Market Models 52 3.3.2 Partial Market Models 58 3.4 Model Review 59 3.5 Conclusion 60 Chapter 4 Study Context: Thailand 61 4.1 National Economic and Social Development Plans 61 4.1.1 First Plan 1961–1966 62 4.1.2 Second Plan 1967–1971 65 4.1.3 Third Plan 1972–1976 66 vii 4.1.4 Fourth Plan 1977–1981 67 4.1.5 Fifth Plan 1982–1986 68 4.1.6 Sixth Plan 1987–1991 69 4.1.7 Seventh Plan 1992–1996 70 4.1.8 Eighth Plan 1997–2001 73 4.1.9 Ninth Plan 2002–2006 74 4.1.10 Summary of Plans and Infrastructure Investment 75 4.2 Thailand‟s Infrastructure 77 4.2.1 Expenditure 77 4.2.2 International Competitiveness 78 4.3 Sources of Infrastructure Finance 80 4.3.1 Public Revenue 82 4.3.2 Deficit Financing 100 4.4 Summary 106 Chapter 5: Methodology and Analytic Model 108 5.1 Methodology 108 5.2 Conceptual Framework 109 5.3 Model Structure 110 5.4 Model Components 111 5.4.1 Budget Overview 112 5.4.2 Defined Revenue Streams 116 5.4.3 Direct Tax Equations 118 5.4.4 Indirect Tax Equations 123 5.5 Raw Data and Sources of Data 129 5.6 Data Transformation 131 5.7 Estimation Issues 132 5.7.1 Stationary and Non-stationary 132 5.7.2 Testing for Unit Roots 134 5.7.3 Error Correction Model 137 5.7.4 Cointegration 137 5.7.5 Autoregressive Distributed Lag 138 5.8 Estimation Procedure 140 5.9 Simulation Procedure 140 5.10 Conclusion 141 Chapter 6: Model Estimation and Simulation 142 6.1 Public Revenue Estimation 143 6.1.1 Estimation PIT 143 6.1.2 Estimation CIT 150 6.1.3 Estimation Petroleum Tax 158 6.1.4 Estimation Indirect Taxes 160 6.1.5 Estimation Foreign Borrowing 167 6.1.6 Estimation Debt Management 167 6.2 Public Infrastructure: Factor of Production 168 6.3 Model Estimation Results 171 6.4 Aggregate Production Function 173 6.5 Infrastructure Finance Model for Emerging Economies 175 6.5.1 Ex ante Scenario Simulation 176 6.5.2 Ex post Simulation 178 6.6 Discussion 179 6.6.1 Economic Functionality 180 viii 6.6.2 Model Application 182 6.7 Conclusion. 184 Chapter 7 Policy Discussions, Recommendations and Conclusions 185 7.1 Study Overview 186 7.2 Study Results 187 7.3 IFMEE Explained 188 7.4 Policy Implications 190 7.5 Research Limitations 192 7.6 Recommendations for Further Research 193 7.7 Final 194 References 196 ix List of Abbreviations ADF Augmented Dickey-Fuller AEC Asian Economic Crisis ARDL Autoregressive Distributed Lag BIBF Bangkok International Bank Facility BOB Bureau of the Budget BOT Bank of Thailand C-D Cobb-Douglas CGE Computable General Equilibrium CIT Corporate Income Tax CPI Consumer Price Index CRTS Constant Returns to Scale DB Domestic Borrowing DF Dickey-Fuller DW Durbin-Watson ECM Error Correction Model ETR Effective Tax Rate FB Foreign Borrowing FPO Fiscal Policy Office FTA Free Trade Agreement FY Fiscal Year 1 GDP Gross Domestic Product GNP Gross National Product HD Harrod-Domar ICOR Incremental Capital Output Ratio IFMEE Infrastructure Finance Model for Emerging Economies IMD Institute for Management Development IMF International Monetary Fund IMGPI Import Goods Price Index IPPI Private Investment Price Index JJ Johansen and Juselius LM Lagrange Multiplier L-R Long-Run MOF Ministry of Finance NBER National Bureau of Economic Research NEDB National Economic Development Board NESDB National Economic and Social Development Board 1 Fiscal Year in Thailand starts from October to September [...]... for analysis without specifically addressing public infrastructure investment This study includes infrastructure investment with quantitative analysis through a recursive supply-side system equation model 1.5 Methodology The methodology for this empirical research employs quantitative analysis The computation for the estimation of public revenue and aggregate production function is based on quarterly... rarely quantifiable (Jomo & Reinert 2005) Further, Hirschmann (1958) noted that, depending on economic needs or priorities, a government‟s focus for development can vary by country and by the times Since the concept is broad and derived from qualitative factors, the measurement of development remains a challenge However, the majority of empirical economists argue that accurate measurement of quantifiable... However, the majority of empirical economists argue that accurate measurement of quantifiable outcomes can provide a proxy for the contributions of non-quantifiable effects To measure the effects of public investment in infrastructure for this study, a quantifiable indicator to approximate development is required Economic growth is the leading indicator for this task, as it can be measured through Gross... alternative financing methods 1.4 Research Scope and Significance This study examines the effects of public infrastructure investment on economic growth in Thailand, by means of empirical research and quantitative analysis It should be noted that, as the social consequences of infrastructure investment are difficult to measure and little data are available, the financial aspects of public infrastructure... objectives, explaining the framework of this empirical research The scope of the research and its significance within the literature are next presented, followed by the methodology employed, based on quantitative analysis 1.1 Research Antecedents There is a high cost, both financial and national, to infrastructure capital development Governments may choose their projects unwisely, or conditions may... Thailand‟s economy This study explores issues which underlie the fiscal sustainability framework, and their existing and potential impacts on the country‟s economy This empirical research is conducted through quantitative analysis techniques derived from statistical literature, and its findings therefore allow comparison with other economic research, and thus add to the body of knowledge 1.2 Statement of Purpose... research is to identify the inputs and the processes comprising public infrastructure investment in Thailand This study includes a literature survey, identification of relevant public finance data, then a quantitative analysis leading to conclusions and findings for the following objectives: 6 define the effects of public infrastructure on economic growth in Thailand develop a public revenue generation... to source reliable data in Thailand over the period 1993-2006, or indeed, pursue a largely qualitative analysis of 17 social factors in the framework of this thesis This empirical research is largely a quantitative analysis to identify the level of funding the Thai government, under its fiscal constraints, can realise for infrastructure investment When this is resolved, the impact of fiscal constraints . Income from Non-financial SOEs and GDP, 199 3-2 006 5 4.1 First Plan GDP 196 1-1 966 61 4.2 Second Plan GDP 196 7-1 971 65 4.3 Third Plan GDP 197 2-1 976 66 4.4 Fourth Plan GDP 197 7-1 981 67 4.5 Fifth. Fifth Plan GDP 198 2-1 986 68 4.6 Sixth Plan GDP 198 7-1 991 70 4.7 Seventh Plan GDP 199 2-1 996 71 4.8 Critical Infrastructure Response Plan 199 0-2 001 72 4.9 Eighth Plan GDP 199 7-2 001 73 4.10 Ninth. 199 3-2 006 98 4.28 Non-tax Revenue & Retained Income Components, 199 3-2 006 99 xii 4.29 Fiscal Balance 199 3-2 006 102 4.30 Capital Expenditure Proportionate to Budget Expenditure 199 3-2 006