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Bayesian Econometrics
Researchers in many fields are increasingly finding the Bayesian approach to statistics to be an attractive one. This book introduces the reader to the use of Bayesian methods in the field of econometrics at the advanced undergraduate or graduate level. The book is self-contained and does not require that readers have previous training in econometrics. The focus is on models used by applied economists and the computational techniques necessary to implement Bayesian methods when doing empirical work. Topics covered in the book include the regression model (and variants applicable for use with panel data), time series models, models for qualitative or censored data, nonparametric methods and Bayesian model averaging. The book includes numerous empirical examples and the website associated with it contains data sets and computer programs to help the student develop the computational skills of modern Bayesian econometrics.
Bayesian Econometric Methods
Illustrates Bayesian theory and application through a series of exercises in question and answer format.
Analysis of Economic Data
Analysis of Economic Data has, over three editions, become firmly established as a successful textbook for students studying data analysis whose primary interest is not in econometrics, statistics or mathematics. It introduces students to basic econometric techniques and shows the reader how to apply these techniques in the context of real-world empirical problems. The book adopts a largely non-mathematical approach relying on verbal and graphical inuition and covers most of the tools used in modern econometrics research. It contains extensive use of real data examples and involves readers in hands-on computer work.
Analysis of Financial Data
Analysis of Financial Data teaches the basic methods and techniques of data analysis to finance students, by showing them how to apply such techniques in the context of real-world empirical problems. Adopting a largely non-mathematical approach Analysis of Financial Data relies more on verbal intuition and graphical methods for understanding. Key features include: Coverage of many of the major tools used by the financial economist e.g. correlation, regression, time series analysis and methods for analyzing financial volatility. Extensive use of real data examples, which involves readers in hands-on computer work. Mathematical techniques at a level suited to MBA students and undergraduates taking a first course in the topic. Supplementary material for readers and lecturers provided on an accompanying website.
Bayesian Multivariate Time Series Methods for Empirical Macroeconomics
Bayesian Multivariate Time Series Methods for Empirical Macroeconomics provides a survey of the Bayesian methods used in modern empirical macroeconomics. These models have been developed to address the fact that most questions of interest to empirical macroeconomists involve several variables and must be addressed using multivariate time series methods. Many different multivariate time series models have been used in macroeconomics, but Vector Autoregressive (VAR) models have been among the most popular. Bayesian Multivariate Time Series Methods for Empirical Macroeconomics reviews and extends the Bayesian literature on VARs, TVP-VARs and TVP-FAVARs with a focus on the practitioner. The authors go beyond simply defining each model, but specify how to use them in practice, discuss the advantages and disadvantages of each and offer tips on when and why each model can be used.
Bayesian Econometric Methods
This volume in the Econometric Exercises series contains questions and answers to provide students with useful practice, as they attempt to master Bayesian econometrics. In addition to many theoretical exercises, this book contains exercises designed to develop the computational tools used in modern Bayesian econometrics. The latter half of the book contains exercises that show how these theoretical and computational skills are combined in practice, to carry out Bayesian inference in a wide variety of models commonly used by econometricians. Aimed primarily at advanced undergraduate and graduate students studying econometrics, this book may also be useful for students studying finance, marketing, agricultural economics, business economics or, more generally, any field which uses statistics. The book also comes equipped with a supporting website containing all the relevant data sets and MATLAB computer programs for solving the computational exercises.
Introduction to Econometrics
Introduction to Econometrics has been written as a core textbook for a first course in econometrics taken by undergraduate or graduate students. It is intended for students taking a single course in econometrics with a view towards doing practical data work. It will also be highly useful for students interested in understanding the basics of econometric theory with a view towards future study of advanced econometrics. To achieve this end, it has a practical emphasis, showing how a wide variety of models can be used with the types of data sets commonly used by economists. However, it also has enough discussion of the underlying econometric theory to give the student a knowledge of the statist...
The Oxford Handbook of Bayesian Econometrics
A broad coverage of the application of Bayesian econometrics in the major fields of economics and related disciplines, including macroeconomics, microeconomics, finance, and marketing.
The Case Against Sugar
More than half a billion adults and 40 million children on the planet are obese. Diabetes is a worldwide epidemic. Evidence increasingly shows that these illnesses are linked to the other major Western diseases: hypertension, heart disease, even Alzheimer's and cancer, and that shockingly, sugar is likely the single root cause. Yet the nutritional advice we receive from public health bodies is muddled, out of date, and frequently contradictory, and in many quarters still promotes the unproven hypothesis that fats are the greatest evil. With expert science and compelling storytelling, Gary Taubes investigates the history of nutritional science which, shaped by a handful of charismatic and mis...
Complete and Incomplete Econometric Models
Econometric models are widely used in the creation and evaluation of economic policy in the public and private sectors. But these models are useful only if they adequately account for the phenomena in question, and they can be quite misleading if they do not. In response, econometricians have developed tests and other checks for model adequacy. All of these methods, however, take as given the specification of the model to be tested. In this book, John Geweke addresses the critical earlier stage of model development, the point at which potential models are inherently incomplete. Summarizing and extending recent advances in Bayesian econometrics, Geweke shows how simple modern simulation methods can complement the creative process of model formulation. These methods, which are accessible to economics PhD students as well as to practicing applied econometricians, streamline the processes of model development and specification checking. Complete with illustrations from a wide variety of applications, this is an important contribution to econometrics that will interest economists and PhD students alike.
