Autorzy | |
Wydawnictwo | Pearson Education Limited |
Data wydania | 15/05/2019 |
Forma publikacji | zestaw |
Poziom zaawansowania | Dla profesjonalistów, specjalistów i badaczy naukowych |
Język | angielski |
ISBN | 9781292264561 |
Kategorie | Ekonometria |
Introduction to Econometrics, 4th Edition, Global Edition by Stock and Watson is the ultimate introductory guide that connects modern theory with motivating, engaging applications.
The text ensures you get a solid grasp of this challenging subject's theoretical background, building on the philosophy that applications should drive the theory, not the other way around. The latest edition maintains the focus on currency, focusing on empirical analysis and incorporating real-world questions and data by using results directly relevant to the applications.
The text contextualises the study of Econometrics with a comprehensive introduction and review of economics, data, and statistics before proceeding to an extensive regression analysis studying the different variables and regression parameters. With a large data set increasingly used in Economics and related fields, a new chapter dedicated to Big Data will help you learn more about this growing and exciting area.
Sharing a variety of resources and tools to help your understanding and critical thinking of the topics introduced, such as General Interest boxes, or end-of-chapter, and empirical exercises and summaries, this industry-leading text will help you acquire a sophisticated knowledge of this fascinating subject.
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9781292264561 Introduction to Econometrics, 4th Edition, Global Edition with MyLab Economics
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Introduction to Econometrics, Global Edition + MyLab Economics with Pearson eText
PART I: INTRODUCTION AND REVIEW
1. Economic Questions and Data
2. Review of Probability
3. Review of Statistics
PART II: FUNDAMENTALS OF REGRESSION ANALYSIS
4. Linear Regression with One Regressor
5. Regression with a Single Regressor: Hypothesis Tests and Confidence Intervals
6. Linear Regression with Multiple Regressors
7. Hypothesis Tests and Confidence Intervals in Multiple Regression
8. Nonlinear Regression Functions
9. Assessing Studies Based on Multiple Regression
PART III: FURTHER TOPICS IN REGRESSION ANALYSIS
10. Regression with Panel Data
11. Regression with a Binary Dependent Variable
12. Instrumental Variables Regression
13. Experiments and Quasi-Experiments
14. Prediction with Many Regressors and Big Data
PART IV: REGRESSION ANALYSIS OF ECONOMIC TIME SERIES DATA
15. Introduction to Time Series Regression and Forecasting
16. Estimation of Dynamic Causal Effects
17. Additional Topics in Time Series Regression
PART V: THE ECONOMIC THEORY OF REGRESSION ANALYSIS
18. The Theory of Linear Regression with One Regressor
19. The Theory of Multiple Regression