PanelDataNotes-24

PanelDataNotes-24 - Econometric Analysis of Panel Data...

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Unformatted text preview: Econometric Analysis of Panel Data William Greene Department of Economics Stern School of Business Econometric Analysis of Panel Data 24. Bayesian Econometric Models for Panel Data Sources Lancaster, T.: An Introduction to Modern Bayesian Econometrics, Blackwell, 2004 Koop, G.: Bayesian Econometrics, Wiley, 2003 Bayesian Methods, Bayesian Data Analysis, (many books in statistics) Papers in Marketing: Allenby, Ginter, Lenk, Kamakura, Papers in Statistics: Sid Chib, Books and Papers in Econometrics: Arnold Zellner, Gary Koop, Mark Steel, Dale Poirier, Software Stata, Limdep, SAS, etc. S, R, Matlab, Gauss WinBUGS B ayesian inference U sing G ibbs S ampling (On random number generation) http://www.mrc- bsu.cam.ac.uk/bugs/welcome.shtml A Philosophical Underpinning A method of using new information to update existing beliefs about probabilities of events Bayes Theorem for events. (Conceived for updating beliefs about games of chance) Pr(A,B) Pr(A | B) Pr(B) Pr(B| A)Pr(A) Pr(B) = = On Objectivity and Subjectivity Objectivity and Frequentist methods in Econometrics The data speak Subjectivity and Beliefs Priors Evidence Posteriors Science and the Scientific Method Paradigms Classical Formulate the theory Gather evidence Evidence consistent with theory? Theory stands and waits for more evidence to be gathered Evidence conflicts with theory? Theory falls Bayesian Formulate the theory Assemble existing evidence on the theory Form beliefs based on existing evidence Gather evidence Combine beliefs with new evidence Revise beliefs regarding the theory Applications of the Paradigm Classical econometricians doggedly cling to their theories even when the evidence conflicts with them that is what specification searches are all about. Bayesian econometricians NEVER incorporate prior evidence in their estimators priors are always studiously noninformative. (Informative priors taint the analysis.) As practiced, Bayesian analysis is not Bayesian. Likelihoods (Frequentist) The likelihood is the density of the observed data conditioned on the parameters Inference based on the likelihood is usually maximum likelihood (Bayesian) A function of the parameters and the data that forms the basis for inference not a probability distribution The likelihood embodies the current information about the parameters and the data The Likelihood Principle The likelihood embodies ALL the current information about the parameters and the data Proportional likelihoods should lead to the same inferences Application:...
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This note was uploaded on 01/05/2012 for the course B 55.9912 taught by Professor Willamgreene during the Fall '11 term at NYU.

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PanelDataNotes-24 - Econometric Analysis of Panel Data...

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