How Do I Get a Master's in Econometrics?

Advanced econometrics and Stata applications are compiled on the basis of the teaching plan of Advanced Econometrics for master and doctoral students of the School of Economics of Shandong University. It is suitable for graduates and researchers of economic management or social sciences in universities.

Advanced Econometrics and Stata Applications

The book draws more on the latest developments in modern econometrics and is comprehensive. In addition to traditional cross-section data, panel data (including long panels, dynamic panels), time series (including VAR, unit root, and co-integration) , Natural experiments, repeated section data, GMM, Monte Carlo method, self-help method, quantile regression, threshold regression, non-parametric estimation, Bayesian estimation, etc. are all introduced in depth. The book seeks to explain the measurement method intuitively with vivid language, more illustrations and economic significance without losing the rigor of mathematics. Combined with the most popular Stata metering software in Europe and the United States, we will introduce the corresponding Stata commands and examples in time to provide users with a "one-stop" service.

1. In line with modern econometrics. The book draws heavily from Baum (2006), Cameron and Trivedi (2005, 2009), Greene (2003), Hamilton (1994), Hayashi (2000), Kennedy (2003), Poirier (1995), Verbeek (2004) Wooldridge (2001), especially Hayashi (2000), which has the deepest influence on this book.

2. Comprehensive content. In addition to traditional cross-section data, the book includes panel data (including long panels, dynamic panels), time series (including VAR, unit root, cointegration), natural experiments, repeated section data, GMM, Monte Carlo, Self-help method, quantile regression, threshold regression, non-parametric estimation, Bayesian estimation and other methods are introduced in-depth.

3. Combining measurement theory with software operation. Students who study metrology need to understand both the principle of metrology and how to implement it on a computer. To this end, the book provides a "one-stop" service. After explaining each estimation method, it then introduces the corresponding Stata computer operation and examples (Stata is currently the most popular measurement software in Europe and America).

4. The book strives to explain the measurement method intuitively with vivid language, more illustrations and economic meaning, not just from mathematical derivation to mathematical derivation; on the other hand, without losing the rigor of mathematics In the appendix).

5. Prerequisites do not include econometrics at the undergraduate level. Under China's national conditions, many economic graduate students have not studied econometrics at the undergraduate level. Therefore, this book assumes that the reader has already studied calculus, linear algebra, and probability statistics, but does not require econometrics at the undergraduate level (if it is better, of course).

Publication time: October 2010 Edition: 1 Folio: 16 Folio: 404 pages

Price: 38.00 yuan

Chapter 1 Introduction

Chapter 2 Probability Statistics Review

Chapter 3 Small Sample OLS

Chapter 4 Introduction to Stata

Chapter 5 Large Sample OLS

Chapter 6 Maximum Likelihood Estimation

Chapter 7 Heteroscedasticity and GLS

Chapter 8 Autocorrelation

Chapter 9 Model Setting and Data Problems

Chapter 10 Instrumental Variables, 2SLS and GMM

Chapter 11 Short Panel

Chapter 12 Long Panel and Dynamic Panel

Chapter 13 Discrete Explained Variables

Chapter 14 Restricted Explained Variables

Chapter 15 Random and Natural Experiments

Chapter 16 Monte Carlo and Self-Help

Chapter 17 Stationary Time Series

Chapter 18 Unit Roots and Cointegration

Chapter 19 Autoregressive Conditional Heteroscedasticity Model

Chapter 20 Seemingly Uncorrelated Regression

Chapter 21 Simultaneous Equation Model

Chapter 22 Nonlinear Regression and Threshold Regression

Chapter 23 Quantile Regression

Chapter 24 Nonparametric and Semiparametric Estimation

Chapter 25 Introduction to Bayesian Estimates

Chapter 26. How to Do Normative Empirical Research

Appendix: Common data sources

bibliography

Subject index

Mathematics Symbol

English abbreviations

Qiang Chen, male, born in 1971, professor of Shandong University School of Economics, master tutor, deputy director of Taiyue Economic Research Center,

Director of the Research and Policy Research Base "Finance and Economic Growth Research Center. He obtained a bachelor's degree and a master's degree in economics from Peking University in 1992 and 1995, and taught at the university later. He returned to teach in 2008. Research areas: Macroeconomics, Econometrics, Institutions, Economic History, has published papers in SSCI Journal of Comparative Economics , Applied Economics Letters, and << World Economy >> and other journals. Now the American Economic Association, China and the United States Member of the Chinese Academy of Economics, the Chinese Institute of Quantitative Economics, and an anonymous reviewer of Applied Economics, the Quarterly Journal of Economics, and the Industrial Economic Review.