1st Edition
Introduction to Bayesian Econometrics A GUIded Toolkit using R
Foreword
Preface
Introduction
Symbols
Part I: Foundations: Theory, simulation methods and programming
Chapter 1. Basic formal concepts
Chapter 2. Conceptual differences between the Bayesian and Frequentist approaches
Chapter 3. Cornerstone models: Conjugate families
Chapter 4. Simulation methods
Part II: Regression models: A GUIded toolkit
Chapter 5. Graphical user interface
Chapter 6. Univariate models
Chapter 7. Multivariate models
Chapter 8. Time series models
Chapter 9. Longitudinal/Panel data models
Chapter 10. Bayesian model averaging
Part III: Advanced methods: A brief introduction
Chapter 11. Semi-parametric and non-parametric models
Chapter 12. Bayesian machine learning
Chapter 13. Causal inference
Chapter 14. Approximate Bayesian methods
Bibliography
Appendix
Biography
Andrés Ramírez-Hassan is a Distinguished Professor at Universidad EAFIT whose work advances Bayesian econometrics and applied statistical modeling. His research has appeared in journals such as the Journal of Applied Econometrics, Econometric Reviews, and the International Journal of Forecasting. He has served as a researcher and consultant for global institutions, including the United Nations Development Programme and the Inter-American Development Bank. He was a Research Fellow in the Department of Econometrics and Business Statistics at Monash University, and a Visiting Professor at the University of Melbourne.
