图书标签: 宏观经济学 经济学 计量经济学,时间序列分析 经济理论 时间序列分析 教科书 macroeconometrics
发表于2024-11-13
Methods for Applied Macroeconomic Research pdf epub mobi txt 电子书 下载 2024
The last twenty years have witnessed tremendous advances in the mathematical, statistical, and computational tools available to applied macroeconomists. This rapidly evolving field has redefined how researchers test models and validate theories. Yet until now there has been no textbook that unites the latest methods and bridges the divide between theoretical and applied work. Fabio Canova brings together dynamic equilibrium theory, data analysis, and advanced econometric and computational methods to provide the first comprehensive set of techniques for use by academic economists as well as professional macroeconomists in banking and finance, industry, and government. This graduate-level textbook is for readers knowledgeable in modern macroeconomic theory, econometrics, and computational programming using RATS, MATLAB, or Gauss. Inevitably a modern treatment of such a complex topic requires a quantitative perspective, a solid dynamic theory background, and the development of empirical and numerical methods - which is where Canova's book differs from typical graduate textbooks in macroeconomics and econometrics. Rather than list a series of estimators and their properties, Canova starts from a class of DSGE models, finds an approximate linear representation for the decision rules, and describes methods needed to estimate their parameters, examining their fit to the data. The book is complete with numerous examples and exercises. Today's economic analysts need a strong foundation in both theory and application. "Methods for Applied Macroeconomic Research" offers the essential tools for the next generation of macroeconomists.
从内容上看,这本书是市面上宏观理论模型与估计方法结合的最好的参考书了…
评分关于DSGE,VAR等模型的前沿应用,作者本人是这方面的大牛
评分从内容上看,这本书是市面上宏观理论模型与估计方法结合的最好的参考书了…
评分从内容上看,这本书是市面上宏观理论模型与估计方法结合的最好的参考书了…
评分关于DSGE,VAR等模型的前沿应用,作者本人是这方面的大牛
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Methods for Applied Macroeconomic Research pdf epub mobi txt 电子书 下载 2024