Bayesian Ẻconometrics

[...]... An Overview of Bayesian Econometrics 1.1 BAYESIAN THEORY Bayesian econometrics is based on a few simple rules of probability This is one of the chief advantages of the Bayesian approach All of the things that an econometrician would wish to do, such as estimate the parameters of a model, compare different models or obtain predictions from a model, involve the same rules of probability Bayesian methods... by applied economists beyond regression Other important Bayesian books, such as Bauwens, Lubrano and Richard (1999), deal only with particular areas of econometrics (e.g time series models) In writing this book, my aim has been to fill the gap in the existing set of Bayesian textbooks, and create a Bayesian counterpart to the many popular non -Bayesian econometric textbooks now available (e.g Greene,... reasonably low In contrast to other Bayesian and comparable frequentist textbooks, I have included more computer-related material Modern Bayesian econometrics relies heavily on the computer, and developing some basic programming skills is essential for the applied Bayesian The required level of computer programming skills is not that high, but I expect that this aspect of Bayesian econometrics might be... revolutionized the field of Bayesian econometrics since the late 1980s, or do not provide the broad coverage necessary for the student interested in empirical work applying Bayesian methods For instance, Arnold Zellner’s seminal Bayesian econometrics book (Zellner, 1971) was published in 1971 Dale Poirier’s influential book (Poirier, 1995) focuses on the methodology and statistical theory underlying Bayesian and frequentist... used to carry out Bayesian inference for various models which have been commonly-used by others Nevertheless, we stress that Bayesian inference can be 6 Bayesian Econometrics done with any model using the techniques outlined above and, when confronting an empirical problem, you should not necessarily feel constrained to work with one of the off-the-shelf models described in this book 1.2 BAYESIAN COMPUTATION... substantive, reason for the minority status of Bayesian econometrics That is, Bayesian econometrics has historically been computationally difficult or impossible to do for all but a few specific classes of model The computing revolution of the last 20 years has overcome this hurdle and has led to a blossoming of Bayesian methods in many fields However, this has made Bayesian econometrics a field which makes... 335 Index 347 This Page Intentionally Left Blank Preface Bayesian methods are increasingly becoming attractive to researchers in many fields Econometrics, however, is a field in which Bayesian methods have had relatively less influence A key reason for this absence is the lack of a suitable advanced undergraduate or graduate level textbook Existing Bayesian books are either out-dated, and hence do not cover... As a final line of defense, Bayesians have developed noninformative priors for many classes of model That is, the Bayesian approach allows for the use of prior information if you wish to use it However, if you do not wish to use it, you do not have to do so Regardless of how a researcher feels about prior information, it should in no way be an obstacle to the adoption of Bayesian methods Computation... contains the parameters for a model which seeks to explain y.3 We are interested in learning about  based on the data, y Bayesian econometrics uses Bayes’ rule to do so In other words, the Bayesian would replace B by  and A by y in (1.1) to obtain: p.Âjy/ D p.yjÂ/ p. / p.y/ (1.2) Bayesians treat p.Âjy/ as being of fundamental interest That is, it directly addresses the question “Given the data, what... devoted to a discussion of computation In essence, the ideas of Bayesian econometrics are simple, since they only involve the rules of probability However, to use Bayesian econometrics in practice often requires a lot of number crunching To see why computational issues are so important, let us return to the basic equations which underpin Bayesian econometrics The equations relating to model comparison .