Book contents
- Frontmatter
- Contents
- Acknowledgement
- Foreword
- Introduction
- 1 Basic Definitions, Assumptions and Randomised Experiments
- 2 An Introduction to Non-Parametric Identification and Estimation
- 3 Selection on Observables: Matching, Regression and Propensity Score Estimators
- 4 Selection on Unobservables: Non-Parametric IV and Structural Equation Approaches
- 5 Difference-in-Differences Estimation: Selection on Observables and Unobservables
- 6 Regression Discontinuity Design
- 7 Distributional Policy Analysis and Quantile Treatment Effects
- 8 Dynamic Treatment Evaluation
- Bibliography
- Index
1 - Basic Definitions, Assumptions and Randomised Experiments
Published online by Cambridge University Press: 06 March 2019
Book contents
- Frontmatter
- Contents
- Acknowledgement
- Foreword
- Introduction
- 1 Basic Definitions, Assumptions and Randomised Experiments
- 2 An Introduction to Non-Parametric Identification and Estimation
- 3 Selection on Observables: Matching, Regression and Propensity Score Estimators
- 4 Selection on Unobservables: Non-Parametric IV and Structural Equation Approaches
- 5 Difference-in-Differences Estimation: Selection on Observables and Unobservables
- 6 Regression Discontinuity Design
- 7 Distributional Policy Analysis and Quantile Treatment Effects
- 8 Dynamic Treatment Evaluation
- Bibliography
- Index
- Type
- Chapter
- Information
- Impact EvaluationTreatment Effects and Causal Analysis, pp. 3 - 41Publisher: Cambridge University PressPrint publication year: 2019