Описание книги
Modern economies are full of uncertainties and risk. Economics studies resource allocations in an uncertain market environment. As a generally applicable quantitative analytic tool for uncertain events, probability and statistics have been playing an important role in economic research. Econometrics is statistical analysis of economic and financial data. In the past four decades or so, economics has witnessed a so-called 'empirical revolution' in its research paradigm, and as the main methodology in empirical studies in economics, econometrics has been playing an important role. It has become an indispensable part of training in modern economics, business and management.This book develops a coherent set of econometric theory, methods and tools for economic models. It is written as a textbook for graduate students in economics, business, management, statistics, applied mathematics, and related fields. It can also be used as a reference book on econometric theory by scholars who may be interested in both theoretical and applied econometrics.<b>Contents:</b> <ul><li>Preface</li><li>Introduction to Econometrics</li><li>General Regression Analysis</li><li>Classical Linear Regression Models</li><li>Linear Regression Models with Independent Observations</li><li>Linear Regression Models with Dependent Observations</li><li>Linear Regression Models Under Conditional Heteroskedasticity and Autocorrelation</li><li>Instrumental Variables Regression</li><li>Generalized Method of Moments Estimation</li><li>Maximum Likelihood Estimation and Quasi-Maximum Likelihood Estimation</li><li>Modern Econometrics: Retrospect and Prospect</li><li>Bibliography</li><li>Index</li></ul><br><b>Readership:</b> Graduate students in economics, business, management, statistics, applied mathematics, and related fields.Econometric;Models;Analytic0<b>Key Features:</b><ul><li>This book has several important features. First, it covers, in a progressive manner, various econometrics models and related methods from conditional means to possibly nonlinear conditional moments to the entire conditional distributions, and this is achieved in a unified and coherent framework. There exists a strong logical link among the materials covered in different chapters of the book</li><li>Second, the book provides various intuitions, explanations and potential applications for important econometric concepts, theories and methods from an economic perspective. Economic examples are also provided to motivate important econometric methods and models. Such training is indispensable in teaching and learning econometrics</li><li>Third, the book emphasizes basic training in asymptotic analysis. It first provides a brief review of asymptotic analytic methods and tools, and then show how they are used to develop the econometric theory in each chapter. Asymptotic analysis helps readers gain deep insight into modern econometric theory, particularly the conditions under which the econometric theory, methods and models are valid and applicable. By going through various chapters in this book progressively, readers will learn how to do asymptotic analysis for econometric models. Such skills are useful not only for those students who intend to work on theoretical econometrics, but also for those who intend to work on applied subjects in economics because with such analytic skills, readers will be able to understand more specialized or more advanced econometrics textbooks</li></ul>