Introduction to Econometrics
Price: 860.00 INR
ISBN:
9780199650507
Publication date:
28/09/2011
Paperback
592 pages
241.0x185.0mm
Price: 860.00 INR
ISBN:
9780199650507
Publication date:
28/09/2011
Paperback
592 pages
241.0x185.0mm
Introduction to Econometrics provides students with clear and simple mathematics notation and step-by step explanations of mathematical proofs to give them a thorough understanding of the subject. Extensive exercises are incorporated throughout to encourage students to apply the techniques and build confidence. This new edition has been thoroughly revised in line with market feedback
Rights: World Rights
Description
Introduction to Econometrics provides students with clear and simple mathematics notation and step-by step explanations of mathematical proofs to give them a thorough understanding of the subject. Extensive exercises are incorporated throughout to encourage students to apply the techniques and build confidence. This new edition has been thoroughly revised in line with market feedback Retaining its student-friendly approach, Introduction to Econometrics has a comprehensive revision guide to all the essential statistical concepts needed to study econometrics, more Monte Carlo simulations than before and new summaries and non-technical introductions to more advanced topics at the end of chapters
Table of contents
Chapter 1: Simple regression analysis
Chapter 2: Properties of regression coefficients and hypothesis testing
Chapter 3: Multiple regression analysis
Chapter 4: Transformation of variables
Chapter 5: Dummy variables
Chapter 6: Specification regression variables: a preliinary skirmish
Chapter 7: Heteroscedasticity
Chapter 8: Stochastic regressors and measurement errors
Chapter 9: Simultaneous equations estimation
Chapter 10: Binary choice models and maximum likelihood Estimation
Chapter 11: Models using time series data
Chapter 12: Autocorrelation
Chapter 13: Introduction to nonstationary time series
Chapter 14: Introduction to panel data model
Features
- A revision section at the start of the text ensures that all students are confident in basic statistics before embarking on the econometrics material, where mathematical demands on the student are kept to a minimum.
- Provides substantial hands-on practical experience in the form of regression exercises, including 50 exercises on the same dataset.
- A suite of useful online resources, such as extensive datasets, an instructor's manual and a guide to using software, support teaching and learning.
- New to this edition
- The review section at the start of the text has been expanded to provide an even more comprehensive revision guide for all the statistical concepts needed to study econometrics.
- The free econometrics software application, gretl, has been incorporated into this edition so that students without access to commercial applications can carry out econometric analysis using software.
- There are an increased number of exercises, providing students with even more opportunities to put the theory into practice.
- The use of Monte Carlo simulations has been increased in this new edition (as have graphics in general) to illustrate the analysis and to help students understand the maths by visualising it.
- A new final section has been added in each chapter to provide a summary of the chapter content and to introduce a brief non-technical overview of advanced topics
Description
Introduction to Econometrics provides students with clear and simple mathematics notation and step-by step explanations of mathematical proofs to give them a thorough understanding of the subject. Extensive exercises are incorporated throughout to encourage students to apply the techniques and build confidence. This new edition has been thoroughly revised in line with market feedback Retaining its student-friendly approach, Introduction to Econometrics has a comprehensive revision guide to all the essential statistical concepts needed to study econometrics, more Monte Carlo simulations than before and new summaries and non-technical introductions to more advanced topics at the end of chapters
Read MoreTable of contents
Chapter 1: Simple regression analysis
Chapter 2: Properties of regression coefficients and hypothesis testing
Chapter 3: Multiple regression analysis
Chapter 4: Transformation of variables
Chapter 5: Dummy variables
Chapter 6: Specification regression variables: a preliinary skirmish
Chapter 7: Heteroscedasticity
Chapter 8: Stochastic regressors and measurement errors
Chapter 9: Simultaneous equations estimation
Chapter 10: Binary choice models and maximum likelihood Estimation
Chapter 11: Models using time series data
Chapter 12: Autocorrelation
Chapter 13: Introduction to nonstationary time series
Chapter 14: Introduction to panel data model