Applied Econometrics
by Dimitrios Asteriou, Stephen G. Hall
4th Edition
Publisher: Bloomsbury Academic
Book Details
| Print ISBN | 9781352012026 |
| eText ISBN | 9781350306141 |
| Publisher | Bloomsbury Academic |
| Publishing Year | 2021 |
| Edition | 4th Edition |
| Language | English |
| Pages | 568 |
Applied Econometrics, 4th Edition, guides economics students step-by-step from fundamental principles to an advanced level. The textbook blends theoretical concepts with practical application, focusing on estimating economic relationships and working with real-world data.
The volume covers classical linear regression modeling and addresses assumption violations such as multicollinearity, heteroskedasticity, and autocorrelation. It also introduces specialized methods, including dynamic econometric models, simultaneous equations, time series techniques, and panel data analysis.
Intended for undergraduate and master's students taking applied econometrics or undertaking research projects, the book emphasizes interpreting empirical findings and provides hands-on instructions for several software packages.
Table of Contents
Chapter 1: Fundamental Concepts
Chapter 2: The Structure Of Economic Data and Basic Data Handling
Chapter 3: Simple Regression
Chapter 4: Multiple Regression
Chapter 5: Multicollinearity
Chapter 6: Heteroskedasticity
Chapter 7: Autocorrelation
Chapter 8: Misspecification: Wrong Regressors, Measurement Errors And Wrong Functional Forms
Chapter 9: Dummy Variables
Chapter 10: Dynamic Econometric Models
Chapter 11: Simultaneous Equation Models
Chapter 12: Limited Dependent Variable Regression Models
Chapter 13: ARIMA Models And The Box–Jenkins Methodology
Chapter 14: Modelling The Variance: ARCH–GARCH Models
Chapter 15: Vector Autoregressive(VAR) Models And Causality Tests
Chapter 16: Non-Stationarity and Unit Root Tests
Chapter 17: Cointegration and Error-Correction Models
Chapter 18: Identification In Standard and Cointegrated Systems
Chapter 19: Solving Models
Chapter 20: Time Varying Coefficient Models: A New Way of Estimating Bias Free Parameters
Chapter 21: Traditional Panel Data Models
Chapter 22: Dynamic Heterogeneous Panels
Chapter 23: Non-Stationary Panels
Chapter 24: Practicalities in Using Eviews and Stata.
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