William E. Griffiths

Helmut Lütkepohl

Mary Ellen Bock

This volume honors George Judge and his many, varied and outstanding contributions to econometrics, statistics, mathematical programming and spatial equilibrium modeling. The papers are grouped into four parts, each part representing an area in which Professor Judge has made a significant contribution. The authors have all benefited in some way, directly or indirectly, through an association with George Judge and his work. The three papers in Part I are concerned with various aspects of pre-test and Stein-rule estimation. Part II contains applications of Bayesian methodology, new developments in Bayesian methodology, and an overview of Bayesian econometrics. The papers in Part III comprise new developments in time-series analysis, improved estimation and Markov chain analysis. The final part on spatial equilibrium modeling contains papers that had their origins from Professor Judge's pioneering work in the 60's.

A Volume in Honor of George Judge

Readings in Econometric Theory and Practice

Lutz Kilian

This book discusses the econometric foundations of structural vector autoregressive modeling, as used in empirical macroeconomics, finance, and related fields.

Structural Vector Autoregressive Analysis

Introduction to Multiple Time Series Analysis

This is the new and totally revised edition of Lütkepohl’s classic 1991 work. It provides a detailed introduction to the main steps of analyzing multiple time series, model specification, estimation, model checking, and for using the models for economic analysis and forecasting. The book now includes new chapters on cointegration analysis, structural vector autoregressions, cointegrated VARMA processes and multivariate ARCH models. The book bridges the gap to the difficult technical literature on the topic. It is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on it.

New Introduction to Multiple Time Series Analysis

Jürgen Wolters

In 1999 a number of member states of the European Union will adopt a common currency. This change in the monetary system requires that a Eur opean Central Bank is set up and a common monetary policy is pursued. There is general agreement among those countries which are likely to join the common currency that price level stability has to be the ultimate objec tive of monetary po1icy. It is an open issue, however, what kind of policy is best suited for that purpose. The alternative strategies under discussion are a direct inflation targeting, an intermediate monetary targeting or a mixture of both. For these policy strategies a stable money demand relation is of cen tral importance. Therefore a workshop on Money Demand in Europe was organized at the Humboldt University in Berlin on October 10/11, 1997. This research conference brought together academic and central bank econo mists and econometricians predominantly from Europe to discuss issues on specification, estimation and, in particular, stability of money demand rela tions both in a single equation and in a systems framework. In this volume revised versions of the papers presented and discussed at the workshop are collected. The volume thereby gives an overview of money demand analysis in Europe on the eve of the introduction of the Euro in some European countries. It contributes to the discussion on a suitable monetary policy for the new European Central Bank.

Money Demand in Europe

This graduate level textbook deals with analyzing and forecasting multiple time series. It considers a wide range of multiple time series models and methods. The models include vector autoregressive, vector autoregressive moving average, cointegrated, and periodic processes as well as state space and dynamic simultaneous equations models. Least squares, maximum likelihood, and Bayesian methods are considered for estimating these models. Different procedures for model selection or specification are treated and a range of tests and criteria for evaluating the adequacy of a chosen model are introduced. The choice of point and interval forecasts is considered and impulse response analysis, dynamic multipliers as well as innovation accounting are presented as tools for structural analysis within the multiple time series context. This book is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on this book. Applied researchers involved in analyzing multiple time series may benefit from the book as it provides the background and tools for their task. It enables the reader to perform his or her analyses in a gap to the difficult technical literature on the topic.

Helmut Lütkepohl

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