The Resource Econometric modelling with time series : specification, estimation and testing, Vance Martin, Stan Hurn, David Harris
Econometric modelling with time series : specification, estimation and testing, Vance Martin, Stan Hurn, David Harris
 Summary
 "Maximum likelihood estimation is a general method for estimating the parameters of econometric models from observed data. The principle of maximum likelihood plays a central role in the exposition of this book, since a number of estimators used in econometrics can be derived within this framework. Examples include ordinary least squares, generalized least squares and fullinformation maximum likelihood. In deriving the maximum likelihood estimator, a key concept is the joint probability density function (pdf) of the observed random variables, yt. Maximum likelihood estimation requires that the following conditions are satisfied. (1) The form of the joint pdf of yt is known. (2) The specification of the moments of the joint pdf are known. (3) The joint pdf can be evaluated for all values of the parameters, 9. Parts ONE and TWO of this book deal with models in which all these conditions are satisfied. Part THREE investigates models in which these conditions are not satisfied and considers four important cases. First, if the distribution of yt is misspecified, resulting in both conditions 1 and 2 being violated, estimation is by quasimaximum likelihood (Chapter 9). Second, if condition 1 is not satisfied, a generalized method of moments estimator (Chapter 10) is required. Third, if condition 2 is not satisfied, estimation relies on nonparametric methods (Chapter 11). Fourth, if condition 3 is violated, simulationbased estimation methods are used (Chapter 12). 1.2 Motivating Examples To highlight the role of probability distributions in maximum likelihood estimation, this section emphasizes the link between observed sample data and 4 The Maximum Likelihood Principle the probability distribution from which they are drawn"
 Language
 eng
 Extent
 1 online resource (xxxv, 887 pages)
 Contents

 The maximum likelihood principle
 Properties of maximum likelihood estimators
 Numerical estimation methods
 Hypothesis testing
 Linear regression models
 Nonlinear regression models
 Autocorrelated regression models
 Heteroskedastic regression models
 Quasimaximum likelihood estimation
 Generalized method of moments
 Nonparametric estimation
 Estimation by stimulation
 Linear time series models
 Structural vector autoregressions
 Latent factor models
 Nonstationary distribution theory
 Unit root testing
 Cointegration
 Nonlinearities in mean
 Nonlinearities in variance
 Discrete time series models
 Isbn
 9781139525480
 Label
 Econometric modelling with time series : specification, estimation and testing
 Title
 Econometric modelling with time series
 Title remainder
 specification, estimation and testing
 Statement of responsibility
 Vance Martin, Stan Hurn, David Harris
 Language
 eng
 Summary
 "Maximum likelihood estimation is a general method for estimating the parameters of econometric models from observed data. The principle of maximum likelihood plays a central role in the exposition of this book, since a number of estimators used in econometrics can be derived within this framework. Examples include ordinary least squares, generalized least squares and fullinformation maximum likelihood. In deriving the maximum likelihood estimator, a key concept is the joint probability density function (pdf) of the observed random variables, yt. Maximum likelihood estimation requires that the following conditions are satisfied. (1) The form of the joint pdf of yt is known. (2) The specification of the moments of the joint pdf are known. (3) The joint pdf can be evaluated for all values of the parameters, 9. Parts ONE and TWO of this book deal with models in which all these conditions are satisfied. Part THREE investigates models in which these conditions are not satisfied and considers four important cases. First, if the distribution of yt is misspecified, resulting in both conditions 1 and 2 being violated, estimation is by quasimaximum likelihood (Chapter 9). Second, if condition 1 is not satisfied, a generalized method of moments estimator (Chapter 10) is required. Third, if condition 2 is not satisfied, estimation relies on nonparametric methods (Chapter 11). Fourth, if condition 3 is violated, simulationbased estimation methods are used (Chapter 12). 1.2 Motivating Examples To highlight the role of probability distributions in maximum likelihood estimation, this section emphasizes the link between observed sample data and 4 The Maximum Likelihood Principle the probability distribution from which they are drawn"
 Assigning source
 Provided by publisher
 Cataloging source
 E7B
 Dewey number
 330.01/51955
 Illustrations
 illustrations
 Index
 index present
 LC call number
 HB141
 LC item number
 .M3555 2013eb
 Literary form
 non fiction
 Nature of contents

 dictionaries
 bibliography
 Series statement
 Themes in modern econometrics
 Label
 Econometric modelling with time series : specification, estimation and testing, Vance Martin, Stan Hurn, David Harris
 Bibliography note
 Includes bibliographical references and indexes
 http://library.link/vocab/branchCode

 net
 Carrier category
 online resource
 Carrier category code
 cr
 Carrier MARC source
 rdacarrier
 Color
 multicolored
 Content category
 text
 Content type code
 txt
 Content type MARC source
 rdacontent
 Contents
 The maximum likelihood principle  Properties of maximum likelihood estimators  Numerical estimation methods  Hypothesis testing  Linear regression models  Nonlinear regression models  Autocorrelated regression models  Heteroskedastic regression models  Quasimaximum likelihood estimation  Generalized method of moments  Nonparametric estimation  Estimation by stimulation  Linear time series models  Structural vector autoregressions  Latent factor models  Nonstationary distribution theory  Unit root testing  Cointegration  Nonlinearities in mean  Nonlinearities in variance  Discrete time series models
 Control code
 ocn823741877
 Dimensions
 unknown
 Extent
 1 online resource (xxxv, 887 pages)
 Form of item
 online
 Isbn
 9781139525480
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code
 c
 Other physical details
 illustrations
 http://library.link/vocab/recordID
 .b35100096
 Sound
 unknown sound
 Specific material designation
 remote
 System control number

 (OCoLC)823741877
 pebcl113904320X
Embed (Experimental)
Settings
Select options that apply then copy and paste the RDF/HTML data fragment to include in your application
Embed this data in a secure (HTTPS) page:
Layout options:
Include data citation:
<div class="citation" vocab="http://schema.org/"><i class="fa faexternallinksquare fafw"></i> Data from <span resource="http://link.library.deakin.edu.au/portal/Econometricmodellingwithtimeseries/dxp9MJHtjc/" typeof="CreativeWork http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.library.deakin.edu.au/portal/Econometricmodellingwithtimeseries/dxp9MJHtjc/">Econometric modelling with time series : specification, estimation and testing, Vance Martin, Stan Hurn, David Harris</a></span>  <span property="offers" typeOf="Offer"><span property="offeredBy" typeof="Library ll:Library" resource="http://link.library.deakin.edu.au/#Deakin%20University%20Library"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.library.deakin.edu.au/">Deakin University Library</a></span></span></span></span></div>
Note: Adjust the width and height settings defined in the RDF/HTML code fragment to best match your requirements
Preview
Cite Data  Experimental
Data Citation of the Item Econometric modelling with time series : specification, estimation and testing, Vance Martin, Stan Hurn, David Harris
Copy and paste the following RDF/HTML data fragment to cite this resource
<div class="citation" vocab="http://schema.org/"><i class="fa faexternallinksquare fafw"></i> Data from <span resource="http://link.library.deakin.edu.au/portal/Econometricmodellingwithtimeseries/dxp9MJHtjc/" typeof="CreativeWork http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.library.deakin.edu.au/portal/Econometricmodellingwithtimeseries/dxp9MJHtjc/">Econometric modelling with time series : specification, estimation and testing, Vance Martin, Stan Hurn, David Harris</a></span>  <span property="offers" typeOf="Offer"><span property="offeredBy" typeof="Library ll:Library" resource="http://link.library.deakin.edu.au/#Deakin%20University%20Library"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.library.deakin.edu.au/">Deakin University Library</a></span></span></span></span></div>