Introductory Econometrics: Asia-Pacific Edition,
2nd Edition

Part 1: Introduction and review
1. The nature of Econometrics
2. Basic mathematical tools
3. Statistical principles

Part 2: Regression analysis with cross-sectional data
4. The simple regression model
5. Multiple regression analysis: Estimation
6. Multiple regression analysis: Inference
7. Model specification
8. Multiple regression analysis with qualitative information: Binary (or dummy) variables
9. Heteroskedasticity

Part 3: Regression analysis with time series data
10. Basic regression analysis with time series data
11. Serial correlation and heteroskedasticity in time series regressions
12. Modelling highly persistent time series data

Part 4: Additional topics
13. Panel data models
14. Limited dependent variable models and sample selection corrections
15. An introduction to machine learning in econometrics

Appendices: Statistical tables

• Jeffrey M. Wooldridge

  Jeffrey M. Wooldridge is University Distinguished Professor of Economics at Michigan State University, where he has taught since 1991. From 1986 to 1991, he was an assistant professor of economics at the Massachusetts Institute of Technology. He received his bachelor of arts, with majors in computer science and economics, from the University of California, Berkeley, in 1982, and received his doctorate in economics in 1986 from the University of California, San Diego. He has published more than 60 articles in internationally recognized journals, as well as several book chapters. He is also the author of Econometric Analysis of Cross Section and Panel Data, second edition. His awards include an Alfred P. Sloan Research Fellowship, the Plura Scripsit award from Econometric Theory, the Sir Richard Stone prize from the Journal of Applied Econometrics, and three graduate teacher-of-the-year awards from MIT. He is a fellow of the Econometric Society and of the Journal of Econometrics. He is past editor of the Journal of Business and Economic Statistics, and past econometrics coeditor of Economics Letters. He has served on the editorial boards of Econometric Theory, the Journal of Economic Literature, the Journal of Econometrics, the Review of Economics and Statistics, and the Stata Journal. He has also acted as an occasional econometrics consultant for Arthur Andersen, Charles River Associates, the Washington State Institute for Public Policy, Stratus Consulting, and Industrial Economics, Incorporated.

• Mokhtarul Wadud

  Dr Mokhtarul Wadud is a Senior lecturer, School of Accounting and Finance at Deakin University, Geelong. He has many years’ teaching experience with previous full-time academic positions at Monash University and University of Rajshahi (Bangladesh), and is widely published in various international journals in the areas of productivity, efficiency and empirical econometric modelling. Mokhtarul’s PhD was awarded by Uni of Wollongong in 2001; in 2005 he attained a Grad Cert of Higher Education from Deakin. His teaching interests include Business and Financial Forecasting, Analytical Methods in Economics, Finance Microeconomics and Public Finance and Economics. Research interests include Productivity and Efficiency Analysis, Energy and Resource Economics, International Trade Empirics, Time Series Econometric Modelling and Forecasting, and Poverty and Social Development.

• Jenny Lye

  Associate Professor Jenny Lye holds the rank of Reader/Associate Professor in the Department of Economics at the University of Melbourne. She has an extensive international publication record in the areas of theoretical and applied econometrics and statistics. Her recent research also includes publications in the statistical analysis of issues in tertiary education. Jenny’s current teaching includes Introductory Econometrics and the Economics Research report. Jenny’s qualifications are Doctor of Philosophy, University of Canterbury, (1991) Master of Arts, University of Canterbury (1986), Bachelor of Arts, University of Canterbury (1985). Research interests include Applied Econometrics (Range of Equilibria), Applied Econometrics (Quantitative analysis of teaching and learning in higher education in economics and commerce), Theoretical Econometrics (Fieller, Nonlinearities), Applied Econometrics (health, wages, economics of happiness). Jenny is a member of The Economic Society of Australia.

• Joyeux

  Roselyne Joyeux is a Professor in Economics in the Faculty of Business and Economics at Macquarie University in Sydney, Australia. She has held positions at Cornell University, the University of Auckland, and the Centre for Operations Research and Econometrics at the University of Louvain-la-Neuve. She researches in areas that are highly relevant to the Australian society, economy, industry and our diverse student cohort: energy economics, carbon emission trading, house prices, Chinese stock markets and housing markets.

• NEW Part 4, 'Additional topics' includes chapters on panel data models, limited dependent variable models and sample selection corrections, and an introduction to machine learning in econometrics

• NEW local data sets provide a practical approach to teaching this highly mathematical subject and demonstrate the application of econometrics to real-world problems that students can relate to

• NEW expanded content in Part 3 on time series

• NEW learning objectives outline the outcomes of each chapter

• NEW student solutions manual allows students to mark their own work when completing revision

• Part 1 offers background material on introductory mathematics, probability and statistics, providing context for students who have not previously been introduced to this material, or as a brief review for those who have

• Each chapter includes local examples and datasets that provide a practical approach to teaching this highly mathematical subject and demonstrate the application of econometrics to real-world problems that students can relate to

• End-of-chapter problems and computer exercises are oriented toward empirical work, rather than complicated derivations, so that students can reason carefully based on what they have learned

• Core topics are supplemented by additional special interest topics introduced in Part 4: pooled and panel data methods, limited dependent variable models and big data with machine learning appropriately orient the students to further their studies to suit the analytical skill requirements of the business world

• A set of multiple choice questions are included in every chapter to allow for revision and to reinforce learning

Cengage provides a range of supplements that are updated in coordination with the main title selection. For more information about these supplements, contact your Learning Consultant.

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