| Preface | 5 |
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| Contents | 7 |
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| List of Figures | 9 |
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| List of Tables | 11 |
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| Part I: Introduction | 12 |
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| 1: Introduction to Public Health Economics | 13 |
| Why Do We Need Economics in Public Health? | 13 |
| What Makes Public Health Different from the Production of Televisions? | 16 |
| What is Public Health Economics? | 19 |
| The Real World | 21 |
| References | 22 |
| Additional Reading | 22 |
| Part II: Data | 23 |
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| 2: Observational Data | 24 |
| The Rise of Big Data | 24 |
| Cons of Panel Data | 31 |
| Data Linkage | 31 |
| References and Further Reading | 33 |
| 3: Missing Data and Sample Attrition | 34 |
| Missing at Random or Missing at Non-Random | 34 |
| Sample Attrition | 35 |
| Our Example | 35 |
| Sample Attrition | 38 |
| Multiple Imputation | 39 |
| Pros and Cons of MI vs IPW for Public Health Research | 44 |
| References and Further Reading | 46 |
| Part III: Policy Evaluation | 47 |
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| 4: Correlations versus Causation | 48 |
| Correlations | 48 |
| Understanding Correlation Coefficients | 49 |
| Strength of the Correlation | 49 |
| Example | 49 |
| Estimating Correlation Coefficients | 51 |
| Correlation Analysis in Economic Evaluation of Public Health Policy | 53 |
| Weaknesses of Correlation Analysis | 53 |
| Causal Relationships | 54 |
| How to Estimate a Causal Relationship | 54 |
| Basic Econometric Tools for Estimating a Causal Relationship | 55 |
| How Do You Know If You Have Found a Good Instrument? | 59 |
| Interpreting IV Estimates | 60 |
| References and Further Reading | 62 |
| 5: Before and After Study Designs | 63 |
| Interrupted Time Series | 64 |
| When to Use ITS | 64 |
| Data Required to Estimate an ITS | 65 |
| Estimating ITS | 66 |
| Interpreting Results from ITS | 67 |
| Regression Discontinuity Approach | 67 |
| When to Use RD | 68 |
| How to Use RD | 69 |
| Implementation in Practice | 73 |
| Generalisability of the Results | 74 |
| Fuzzy RD Approach | 74 |
| Steps to Estimation | 76 |
| Difference in Difference Approach (DiD) | 78 |
| Some Things to Keep in Mind | 81 |
| Empirical Papers Using These Estimation Techniques | 84 |
| References and Further Reading | 85 |
| Interrupted Time Series | 85 |
| Regression Discontinuity | 85 |
| Difference in Difference | 86 |
| 6: Cross-Country Comparisons | 87 |
| How to Conduct Cross-Country Analysis | 89 |
| Identifying Data Sources | 89 |
| Analysis Method | 90 |
| The Example | 91 |
| Propensity Score Matching in Cross-Country Analysis | 91 |
| When to Use PSM | 92 |
| Matching | 92 |
| How to Implement in Practice | 95 |
| Some Extensions | 96 |
| Interpretation of Coefficients | 97 |
| A Further Example | 98 |
| Data | 99 |
| Constructing Treated and Non-Treated Groups | 99 |
| Other Methods for Estimating Cross-Country Differences | 103 |
| References and Further Reading | 104 |
| 7: A Practitioner’s Guide | 106 |
| Define Your Research Question | 106 |
| Identify an Appropriate Dataset | 107 |
| Estimate a Simple Regression Model | 108 |
| Identify the Most Important Type of Bias that may be Impacting on your Simple Coefficient Estimates and Choose an Appropriate Model | 108 |
| Compare Coefficients Between Chosen Model and Base Model | 109 |
| References and Further Reading | 109 |
| Index | 110 |