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Analysis of Economic Data, 4th Edition

Analysis of Economic Data, 4th Edition

Gary Koop

ISBN: 978-1-118-47253-8

Feb 2013

272 pages

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Analysis of Economic Data has, over three editions, become firmly established as a successful textbook for students studying data analysis whose primary interest is not in econometrics, statistics or mathematics. 

It introduces students to basic econometric techniques and shows the reader how to apply these techniques in the context of real-world empirical problems. The book adopts a largely non-mathematical approach relying on verbal and graphical inuition and covers most of the tools used in modern econometrics research.  It contains extensive use of real data examples and involves readers in hands-on computer work.


Related Resources

Chapter 1 Introduction.

Chapter 2 Basic Data Handling.

Chapter 3 Correlation.

Chapter 4 An Introduction to Simple Regression.

Chapter 5 Statistical Aspects of Regression.

Chapter 6 Multiple Regression.

Chapter 7 Regression with Dummy Variables.

Chapter 8 Several Limited Dependent Variable Models

Chapter 9 Regression with Time Lags: Distributed Lag Models.

Chapter 10 Univariate Time Series Analysis.

Chapter 11Regression with Time Series Variables.

Chapter 12 Applications of Time Series Methods in Macroeconomics and Finance.

Chapter 13 Limitations and Extensions.

Appendix A Writing an Empirical Project

Appendix B Data Directory

  • A new chapter 8 will be added covering several limited dependent variable models.  Models to be covered include: logit, probit, ordered logit and probit, and count data model
  • The use of econometrics software packages have been introduced to the book and will expand the coverage in the text beyond the use of spreadsheet software.
  • A clear departure from traditional econometric textbooks, relying less on mathematics and more on verbal intuition and graphical methods for understanding.
  • Covers most of the tools and models used in modern econometrics research e.g. correlation, regression and extensions for time-series methods.
  • Contains extensive use of real data examples and involves readers in hands-on computer work.