Introductory Econometrics Asia Pacific 1st Edition Wooldridge Solutions Manual
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Introductory Econometrics Asia Pacific 1st Edition Wooldridge Solutions Manual.
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Introductory Econometrics Asia Pacific 1st Edition Wooldridge Solutions Manual
Product details:
Econometrics is the combined study of economics and statistics and is very much an ‘applied’ unit. It is increasingly becoming a core element in finance degrees at upper levels. This first local adaptation of Wooldridge’s text will offer a version of Introductory Econometrics with a structural redesign that will better suit our market along with Asia-Pacific examples and data. Two new chapters at the start of the book will be developed from material currently in Wooldridge’s appendix section to serve as a clear introduction to the subject and as a revision tool that bridges students’ transition from basic statistics into econometrics. This adaptation will include data sets from Australian and New Zealand, as well as from the Asia-Pacific region to suit the significant portion of finance students who are from Asia and the likelihood that many graduates will find employment overseas.
Table contents:
- Part 1: Introduction and Review
- Chapter 01: the Nature of Econometrics and Economic Data
- 1.1 What Is Econometrics?
- 1.2 Steps in Empirical Economic Analysis
- 1.3 The Structure of Economic Data
- 1.4 Graphing Data
- 1.5 Causality and the Notion of Ceteris Paribus in Econometric Analysis
- 1.6 Outline of Topics Covered
- Chapter 02: Basic Mathematical Tools
- 2.1 the Summation Operator
- 2.2 Properties of Linear Functions
- 2.3 Proportions and Percentages
- 2.4 Differential Calculus
- Chapter 03: Fundamentals of Statistics: a Review
- 3.1 Random Variables and Their Probability Distributions
- 3.2 Joint Distributions, Conditional Distributions and Independenc
- 3.3 Features of Probability Distributions
- 3.4 Features of Joint and Conditional Distributions
- 3.5 the Normal and Related Distributions
- Part 2: Regression Analysis with Cross Sectional Data
- Chapter 04: The Simple Regression Model
- 4.1 Definition of the Simple Regression Model
- 4.2 Deriving the Ordinary Least Squares Estimates
- 4.3 Examples of Simple Regression Obtained Using Real Data
- 4.4 Properties of OLS on Any Sample of Data
- 4.5 Units of Measurement and Functional Form
- Chapter 05: Multiple Regression Analysis: Estimation
- 5.1 Motivation for Multiple Regression
- 5.2 Mechanics and Interpretation of Ordinary Least Squares
- Chapter 06: Multiple Regression Analysis: Inference
- 6.1 Sampling Distributions of the OLS Estimators
- Chapter 07: Model Specification
- 7.1 More on Functional Form
- 7.2 Specification Errors
- 7.3 Multicollinearity
- Chapter 08: Multiple Regression Analysis with Qualitative Information: Binary or Dummy Variables
- 8.1 Describing Qualitative Information
- 8.2 A Single Dummy Independent Variable
- 8.3 Using Dummy Variables for Multiple Categories
- 8.4 Interactions Involving Dummy Variables
- 8.5 A Binary Dependent Variable: The Linear Probability Model
- 8.6 Interpreting Regression Results with Discrete Dependent Variab
- Chapter 09: Heteroskedasticity
- 9.1 Consequences of Heteroskedasticity for OLS
- 9.2 Heteroskedasticity-robust Inference After OLS Estimation
- 9.3 Testing for Heteroskedasticity
- 9.4 Weighted Least Squares Estimation
- Part 3: Regression Analysis with Time Series Data
- Chapter 10: Basic Regression Analysis with Time Series Data
- 10.1 The Nature of Time Series Data
- 10.2 Examples of Time Series Regression Models
- Chapter 11: Serial Correlation and Heteroskedasticity in Time Series Regressions
- 11.1 Properties of OLS with Serially Correlated Errors
- Glossary
- References
- Index
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