Book contents
- Ethics in Econometrics
- Ethics in Econometrics
- Copyright page
- Contents
- Figures
- Tables
- Preface
- Acknowledgments
- Recommended Reading
- Introduction
- 1 Ethical Guidelines
- 2 Scientific Misconduct
- 3 Influential Observations
- 4 Model Selection
- 5 Estimation and Interpretation
- 6 Missing Data
- 7 Spurious Relations
- 8 Blinded by the Data
- 9 Predictability
- 10 Adjustment of Forecasts
- 11 Big Data
- 12 Algorithms
- Conclusion
- Index
3 - Influential Observations
Published online by Cambridge University Press: 14 November 2024
Book contents
- Ethics in Econometrics
- Ethics in Econometrics
- Copyright page
- Contents
- Figures
- Tables
- Preface
- Acknowledgments
- Recommended Reading
- Introduction
- 1 Ethical Guidelines
- 2 Scientific Misconduct
- 3 Influential Observations
- 4 Model Selection
- 5 Estimation and Interpretation
- 6 Missing Data
- 7 Spurious Relations
- 8 Blinded by the Data
- 9 Predictability
- 10 Adjustment of Forecasts
- 11 Big Data
- 12 Algorithms
- Conclusion
- Index
Summary
In this chapter we move towards more subtle aspects of econometric analysis, where it is not immediately obvious from the numbers or the graphs that something is wrong. We see that so-called influential observations may not be visible from graphs but become apparent after creating a model. This is one of the key takeaways from this chapter – that we do not throw away data prior to econometric analysis. We should incorporate all observations in our models and, based on specific diagnostic measures, decide which observations are harmful.
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- Information
- Ethics in EconometricsA Guide to Research Practice, pp. 54 - 87Publisher: Cambridge University PressPrint publication year: 2024