NLU Meghalaya Library

Online Public Access Catalogue (OPAC)

Amazon cover image
Image from Amazon.com

Econometric modelling with time series : specification, estimation and testing / Vance Martin, University of Melbourne, Australia, Stan Hurn, Queensland University of Technology, Australia, David Harris, Monash University, Australia.

By: Contributor(s): Material type: TextSeries: Themes in Modern Econometrics | Themes in Modern EconometricsPublisher: Cambridge : Cambridge University Press, 2013Description: 1 online resource (xxxv, 887 pages) : digital, PDF file(s)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781139043205 (ebook)
Subject(s): Additional physical formats: Print version: : No titleDDC classification:
  • 330.01/51955 23
LOC classification:
  • HB141 .M3555 2013
Online resources:
Contents:
Part I. Maximum Likelihood: 1. The maximum likelihood principle; 2. Properties of maximum likelihood estimators; 3. Numerical estimation methods; 4. Hypothesis testing -- Part II. Regression Models: 5. Linear regression models; 6. Nonlinear regression models; 7. Autocorrelated regression models; 8. Heteroskedastic regression models -- Part III. Other Estimation Methods: 9. Quasi-maximum likelihood estimation; 10. Generalized method of moments; 11. Nonparametric estimation; 12. Estimation by stimulation -- Part IV. Stationary Time Series: 13. Linear time series models; 14. Structural vector autoregressions; 15. Latent factor models -- Part V. Non-Station Time Series: 16. Nonstationary distribution theory; 17. Unit root testing; 18. Cointegration -- Part VI. Nonlinear Time Series: 19. Nonlinearities in mean; 20. Nonlinearities in variance; 21. Discrete time series models -- Appendix A. Change in variable in probability density functions; Appendix -- B. The lag operator -- Appendix C. FIML estimation of a structural model -- Appendix D. Additional nonparametric results.
Summary: 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.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Collection Status Barcode
eBooks Central Library Economics Available EB0366

Title from publisher's bibliographic system (viewed on 18 Jul 2016).

Part I. Maximum Likelihood: 1. The maximum likelihood principle; 2. Properties of maximum likelihood estimators; 3. Numerical estimation methods; 4. Hypothesis testing -- Part II. Regression Models: 5. Linear regression models; 6. Nonlinear regression models; 7. Autocorrelated regression models; 8. Heteroskedastic regression models -- Part III. Other Estimation Methods: 9. Quasi-maximum likelihood estimation; 10. Generalized method of moments; 11. Nonparametric estimation; 12. Estimation by stimulation -- Part IV. Stationary Time Series: 13. Linear time series models; 14. Structural vector autoregressions; 15. Latent factor models -- Part V. Non-Station Time Series: 16. Nonstationary distribution theory; 17. Unit root testing; 18. Cointegration -- Part VI. Nonlinear Time Series: 19. Nonlinearities in mean; 20. Nonlinearities in variance; 21. Discrete time series models -- Appendix A. Change in variable in probability density functions; Appendix -- B. The lag operator -- Appendix C. FIML estimation of a structural model -- Appendix D. Additional nonparametric results.

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.

There are no comments on this title.

to post a comment.