Econometrics: Empirical Modeling (Specification and Evaluation)

Author: (English) Granger, translated by Hong Fuhai
Publisher:
Publish Date: 2005-09-01
Features: When constructing economic models, it is essential to consider the integration of the model with economic theory. If a model is statistically significant but economically unreasonable, it has little reference value for economic analysis. The book includes a wide range of cases that are simple and engaging, making the construction process of economic models accessible even to non-professionals, who can benefit greatly from it. —Zhao Guoqing, Professor and Doctoral Supervisor at Renmin University of China
When comparing mathematical economics and econometrics, we often feel that the former resembles a science, while the latter is more like an art. Indeed, in an empirical study, everything from the selection and specification of the econometric model to estimation, evaluation, prediction, and interpretation is decided by the researcher. As a result, empirical research may appear unreliable: researchers can find "suitable" data and "suitable" models to support their economic theoretical viewpoints. However, Granger rigorously and engagingly illustrates the entire process of constructing empirical models through some interesting real-world examples in this book. It shows us the scientificity, credibility, and fun of empirical research. —Chen Yanbin, Economics PhD
In this book, Granger explains the process of constructing and evaluating empirical models. The book widely draws on and references cases and anecdotes from economics, finance, political science, environmental economics, as well as art, literature, and the entertainment industry, blending precision with accumulated intuition to provide us with unique and highly interesting insights on this topic. The first chapter analyzes model specification issues, using the example of deforestation in the Amazon Basin of Brazil to discuss the process of model specification. The second chapter considers evaluation issues, pointing out the neglect of evaluation by economists and emphasizing that models should be evaluated based on the quality of their results. The third chapter employs more complex and technical methods than the first two chapters to further discuss how to evaluate predictions. This book brings us new ideas about how to construct and evaluate models, suggesting that in future modeling, we should pay more attention to the economic significance of models rather than their statistical significance, and more to their practical value rather than their superficial elegance.