Econometrics in Practice

  • 6h 11m
  • Paul Turner PhD
  • Mercury Learning
  • 2021

This book covers the econometric methods necessary for a practicing applied economist or data analyst. This requires both an understanding of statistical theory and how it is used in actual applications. Chapters 1 to 9 present the material concerned with basic statistical theory. Chapters 10 to 13 introduce a number of topics which form the basis of more advanced option modules, such as time series methods in applied econometrics. To get the most out of these topics, companion files include Excel datasets and 4-color figures. It includes pull down menus to graph the data, calculate sample statistics and estimate regression equations.

FEATURES:

  • Integration of econometrics methods with statistical foundations
  • Worked examples of all models considered in the text
  • Includes Excel datasheets to facilitate estimation and application of models
  • Features instructor ancillaries for use as a textbook

The companion files and/or instructor resources are available online by emailing the publisher with proof of purchase at info@merclearning.com.

In this Book

  • Probability and the Statistical Foundations of Econometrics
  • Statistical Inference
  • The Bivariate Regression Model
  • The Multivariate Regression Model
  • Serial Correlation
  • Heteroscedasticity, Functional Form, and Structural Breaks
  • Binary Dependent Variables
  • Stochastic Regressors
  • Dynamic Models
  • Time Series Analysis and Arima Modeling
  • Unit Roots and Seasonality
  • Cointegration
  • Vector Autoregressions
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