Simplicity, Inference and Modelling

• 1. The importance of simplicity in theory and practice A. Zellner, H. A. Keuzenkamp and M. McAleer; 2. What is the problem of simplicity? E. Sober; 3 Science seeks parsimony - not simplicity searching for pattern in phenomena H. Simon; 4. A macroeconomic approach to complexity M. Boumans; 5. The new science of simplicity M. R. Forster; 6. What explains complexity? B. Hamminga; 7. Occam's bonus A. W. F. Edwards; 8. Simplicity, information, Kolmogorov complexity, and prediction P. Vitanyi and M. Li; 9. Simplicity and statistical inference J. Rissanen; 10. Rissanen's theorem and econometric series W. Ploberger and P. C. B. Phillips; 11. Parametric versus non-parametric inference: satistical models and simplicity; 12. The role of simplicity in an econometric model selection process A. Aznar, M. Isable Ayuda and C. Garcia-Olaverri; 13. Simplicity in a behavioural, non-parametric context D. Tempelaar; 14. Keep it sophisticatedly simple A. Zellner; 15. Communication, complexity and coordination in games M. Ganslandt; 16. The simplicity of an earnings frontier U. Jensen; 17. Simplicity - views of the Nobel Laureates in economic science H. A. Keuzenkamp and M. McAleer.

"This lively and informative exposition of several points of view...will make this book pleasurable reading for not only philosophers of science and epistemologists, but also for those data analysts interested in formalizing the foundations that guide and shape their modeling practices." Journal of American Statistical Association