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Introduction to Econometrics, 4th edition

  • James H. Stock
  • , Mark W. Watson

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Introduction to Econometrics connects modern theory and practice with engaging applications. The text focuses on currency, while adhering to the philosophy that applications should drive the theory, not the other way around. It incorporates real-world questions and data, and methods that are immediately relevant to the applications.

A new chapter dedicated to Big Data in the 4th Edition helps you learn about this growing and exciting area. This coverage and approach make the subject come alive and helps you to become a sophisticated consumer of econometrics.

Published by Pearson (September 18th 2020) - Copyright © 2019

ISBN-13: 9780136879787

Subject: Economics

Category: Econometrics & Quantitative Methods

PART I: INTRODUCTION AND REVIEW

  1. Economic Questions and Data
  2. Review of Probability
  3. Review of Statistics

PART II: FUNDAMENTALS OF REGRESSION ANALYSIS

  1. Linear Regression with One Regressor
  2. Regression with a Single Regressor: Hypothesis Tests and Confidence Intervals
  3. Linear Regression with Multiple Regressors
  4. Hypothesis Tests and Confidence Intervals in Multiple Regression
  5. Nonlinear Regression Functions
  6. Assessing Studies Based on Multiple Regression

PART III: FURTHER TOPICS IN REGRESSION ANALYSIS

  1. Regression with Panel Data
  2. Regression with a Binary Dependent Variable
  3. Instrumental Variables Regression
  4. Experiments and Quasi-Experiments
  5. Prediction with Many Regressors and Big Data

PART IV: REGRESSION ANALYSIS OF ECONOMIC TIME SERIES DATA

  1. Introduction to Time Series Regression and Forecasting
  2. Estimation of Dynamic Causal Effects
  3. Additional Topics in Time Series Regression

PART V: THE ECONOMIC THEORY OF REGRESSION ANALYSIS

  1. The Theory of Linear Regression with One Regressor
  2. The Theory of Multiple Regression