The Economics of Public Health - Evaluating Public Health Interventions
von: Heather Brown
Palgrave Pivot, 2018
ISBN: 9783319748269
Sprache: Englisch
112 Seiten, Download: 2413 KB
Format: PDF, auch als Online-Lesen
| Preface | 5 | ||
| Contents | 7 | ||
| List of Figures | 9 | ||
| List of Tables | 11 | ||
| Part I: Introduction | 12 | ||
| 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 | ||
| 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 | ||
| 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 |