A Practical Introduction to Econometric Methods

Bayesian Econometric Methods examines principles of Bayesian inference by posing a series of theoretical and applied questions and providing detailed solutions to those questions. This second edition adds extensive coverage of models popular in finance and macroeconomics, including state space and unobserved components models, stochastic volatility models, ARCH, GARCH, and vector autoregressive models. The authors have also added many new exercises related to Gibbs sampling and Markov Chain Monte Carlo (MCMC) methods. The text includes regression-based and hierarchical specifications, models based upon latent variable representations, and mixture and time series specifications. MCMC methods are discussed and illustrated in detail - from introductory applications to those at the current research frontier - and MATLAB® computer programs are provided on the website accompanying the text. Suitable for graduate study in economics, the text should also be of interest to students studying sta

Bayesian Econometric Methods examines principles of Bayesian inference by posing a series of theoretical and applied questions and providing detailed solutions to those questions. This second edition adds extensive coverage of models popular in finance and macroeconomics, including state space and unobserved components models, stochastic volatility models, ARCH, GARCH, and vector autoregressive models. The authors have also added many new exercises related to Gibbs sampling and Markov Chain Monte Carlo (MCMC) methods. The text includes regression-based and hierarchical specifications, models based upon latent variable representations, and mixture and time series specifications. MCMC methods are discussed and illustrated in detail - from introductory applications to those at the current research frontier - and MATLAB® computer programs are provided on the website accompanying the text. Suitable for graduate study in economics, the text should also be of interest to students studying sta

Mixed Methods Research for Business and Management guides students and researchers through how to use this methodology successfully in a research-based dissertation or project.The book introduces the

Mixed Methods Research for Business and Management guides students and researchers through how to use this methodology successfully in a research-based dissertation or project.The book introduces the

A guide to economics, statistics and finance that explores the mathematical foundations underling econometric methodsAn Introduction to Econometric Theory offers a text to help in the mastery of the m

The text is aimed at final-year undergraduate students or those at the graduate level doing econometrics for the first time. It is an introductory course in the theory and practice of classical and mo

This Volume of "Advances in Econometrics" contains a selection of papers presented initially at the 7th Annual Advances in Econometrics Conference held on the LSU campus in Baton Rouge, Louisiana duri

This book aims to teach Bayesian econometrics by providing a wide range of solved exercises. In addition to many theoretical exercises, this book contains exercises designed to develop the computation

Econometric Theory and Methods provides a unified treatment of modern econometric theory and practical econometric methods. The geometrical approach to least squares is emphasized, as is the method of

In An Introduction to Classical Econometric Theory Paul A. Ruud shows the practical value of an intuitive approach to econometrics. Students learn not only why but how things work. Through geometry, s

Infrared spectroscopy is generally understood to mean the science of spectra relating to infrared radiation, namely electromagnetic waves, in the wavelength region occurring intermediately between vis

"This book is a comprehensive collection that focuses on various regions and their economies at a pivotal time in our global economy when the majority of nations continue to struggle with stabilizing

The name "temporal logic" may sound complex and daunting; but while they describe potentially complex scenarios, temporal logics are often based on a few simple, and fundamental, concepts - highlighte

This reader-friendly introduction to the fundamental concepts and techniques of numerical analysis/numerical methods develops concepts and techniques in a clear, concise, easy-to- read manner, followe

Now in a new edition, this unique interactive introduction to the study of phonetics shows students how to examine the entire range of human sounds through a series of 124 introspective experiments ca

Partial differential equations arise in almost all areas of science, engineering, modeling, and forecasting. During the last two decades pseudospectral methods have emerged as successful alternatives to better known computational procedures, (e.g. finite difference and finite element methods of numerical solution), in several key application areas. These areas include computational fluid dynamics, wave motion, and weather forecasting. This book explains how, when and why this pseudospectral approach works. In order to make the subject accessible to students as well as researchers and engineers, the subject is presented using illustrations, examples, heuristic explanations, and algorithms rather than rigorous theoretical arguments. This book will be of interest to graduate students, scientists and engineers interested in applying pseudospectral methods to real problems.

The advent of electronic computing permits the empirical analysis of economic models of far greater subtlety and rigour than before, when many interesting ideas were not followed up because the calculations involved made this impracticable. The estimation and testing of these more intricate models is usually based on the method of Maximum Likelihood, which is a well-established branch of mathematical statistics. Its use in econometrics has led to the development of a number of special techniques; the specific conditions of econometric research moreover demand certain changes in the interpretation of the basic argument. This book is a self-contained introduction to this field. It consists of three parts. The first deals with general features of Maximum Likelihood methods; the second with linear and nonlinear regression; and the third with discrete choice and related micro-economic models. Readers should already be familiar with elementary statistical theory, with applied econometric res