Econometric Modelling with Time Series
Specification, Estimation and Testing
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- Available on iOS & Android
Econometric Modelling with Time Series
Specification, Estimation and Testing
About this book
This book provides a general framework for specifying, estimating and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalised method of moments estimation, nonparametric estimation and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the unifying framework for the book is that many of the estimators and test statistics proposed in econometrics can be derived within a likelihood framework, thereby providing a coherent vehicle for understanding their properties and interrelationships. In contrast to many existing econometric textbooks, which deal mainly with the theoretical properties of estimators and test statistics through a theorem-proof presentation, this book squarely addresses implementation to provide direct conduits between the theory and applied work.
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Table of contents
- Contents
- List of Illustrations
- Computer Code Used in the Examples[4pt] Code is written in GAUSS (*.g) , MATLAB (*.m) and in R (*.R)
- Preface
- I Maximum Likelihood
- 2 Properties of Maximum Likelihood Estimators
- 3 Numerical Estimation Methods
- 4 Hypothesis Testing
- II Regression Models
- 6 Nonlinear Regression Models
- 7 Autocorrelated Regression Models
- 8 Heteroskedastic Regression Models
- III Other Estimation Methods
- 10 Generalised Method of Moments
- 11 Nonparametric Estimation
- 12 Estimation by Simulation
- IV Stationary Time Series
- 14 Structural Vector Autoregressions
- 15 Latent Factor Models
- V Nonstationary Time Series
- 17 Unit Root Testing
- 18 Cointegration
- VI Nonlinear Time Series
- 20 Nonlinearities in Variance
- 21 Discrete Time Series Models
- Appendix A: Change of Variable in Density Functions
- Appendix B: The Lag Operator
- Appendix C: FIML Estimation of a Structural Model
- Appendix D: Additional Nonparametric Results
- References
- Index
- Index