Book contents
- Frontmatter
- Contents
- List of Figures
- List of Tables
- Preface to the Second Edition
- Acknowledgments to the Second Edition
- Acknowledgments to the First Edition
- 1 The Scientific Study of Politics
- 2 The Art of Theory Building
- 3 Evaluating Causal Relationships
- 4 Research Design
- 5 Getting to Know Your Data: Evaluating Measurement and Variations
- 6 Probability and Statistical Inference
- 7 Bivariate Hypothesis Testing
- 8 Bivariate Regression Models
- 9 Multiple Regression: The Basics
- 10 Multiple Regression Model Specification
- 11 Limited Dependent Variables and Time-Series Data
- 12 Putting It All Together to Produce Effective Research
- Appendix A Critical Values of Chi-Square
- Appendix B Critical Values of t
- Appendix C The Λ Link Function for Binomial Logit Models
- Appendix D The Φ Link Function for Binomial Probit Models
- Bibliography
- Index
3 - Evaluating Causal Relationships
- Frontmatter
- Contents
- List of Figures
- List of Tables
- Preface to the Second Edition
- Acknowledgments to the Second Edition
- Acknowledgments to the First Edition
- 1 The Scientific Study of Politics
- 2 The Art of Theory Building
- 3 Evaluating Causal Relationships
- 4 Research Design
- 5 Getting to Know Your Data: Evaluating Measurement and Variations
- 6 Probability and Statistical Inference
- 7 Bivariate Hypothesis Testing
- 8 Bivariate Regression Models
- 9 Multiple Regression: The Basics
- 10 Multiple Regression Model Specification
- 11 Limited Dependent Variables and Time-Series Data
- 12 Putting It All Together to Produce Effective Research
- Appendix A Critical Values of Chi-Square
- Appendix B Critical Values of t
- Appendix C The Λ Link Function for Binomial Logit Models
- Appendix D The Φ Link Function for Binomial Probit Models
- Bibliography
- Index
Summary
OVERVIEW
Modern political science fundamentally revolves around establishing whether there are causal relationships between important concepts. This is rarely straightforward, and serves as the basis for almost all scientific controversies. How do we know, for example, if economic development causes democratization, or if democratization causes economic development, or both, or neither? To speak more generally, if we wish to evaluate whether or not some X causes some Y, we need to cross four causal hurdles: (1) Is there a credible causal mechanism that connects X to Y? (2) Can we eliminate the possibility that Y causes X? (3) Is there covariation between X and Y? (4) Have we controlled for all confounding variables Z that might make the association between X and Y spurious? Many people, especially those in the media, make the mistake that crossing just the third causal hurdle – observing that X and Y covary – is tantamount to crossing all four. In short, finding a relationship is not the same as finding a causal relationship, and causality is what we care about as political scientists.
I would rather discover one causal law than be King of Persia.
– Democritus (quoted in Pearl 2000)CAUSALITY AND EVERYDAY LANGUAGE
Like that of most sciences, the discipline of political science fundamentally revolves around evaluating causal claims. Our theories – which may be right or may be wrong – typically specify that some independent variable causes some dependent variable.
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- Information
- The Fundamentals of Political Science Research , pp. 51 - 68Publisher: Cambridge University PressPrint publication year: 2013