Bøger i Advanced Texts in Econometrics serien

This volume is a comprehensive assessment of many recent developments in the modelling of time series. The focus is on introducing various nonlinear models and discussing their practical use, and encouraging the reader to apply nonlinear models to their practical modelling problems.

Provides a comprehensive introduction to VAR modelling and how it can be applied. This book focuses on the properties of the cointegrated VAR model and its implications for macroeconomic inference when data are non-stationary. It provides insights into the links between statistical econometric modelling and economic theory.

This work contains an up-to-date coverage of the last 20 years' advances in Bayesian inference in econometrics, with an emphasis on dynamic models. Several examples illustrate the methods.

This is one of the first books to provide a textbook exposition of the literature on how to measure accurately the 'effects' of a 'treatment', such as a drug, educational programme, or tax regime, on a response variable like an illness, GPA, or income. The book focuses on non-experimental, microeconometric estimation.

Presenting some of the main topics in panel data econometrics, this work deals with static models, time series models with error components, and with dynamics and predeterminedness. The author concentrates on linear models, and emphasizes the roles of heterogeneity and dynamics in panel data modelling.

This text provides a comprehensive treatment of finite sample statistics and econometrics. Within this framework, the book discusses the basic analytical tools of finite sample econometrics and explores their applications to models covered in a first year graduate course in econometrics.

In this modern study of the use of periodic models in the description and forecasting of economic data the authors investigate such areas as seasonal time series, periodic time series models, periodic integration and periodic cointegration.

Inflation targeting has moved the quality of econometric methodology and practice into the limelight of economic policy debate. This book describes how the discipline has adapted to changing demands by adopting insights from economic theory and by taking advantage of the methodological and conceptual advances within time series econometrics.

This workbook is a companion to the textbook "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models". The workbook contains exercises and solutions concerned with the theory of cointegration in the vector autoregressive model.

This collection of essays on applied econometrics has been designed specifically for graduate students. It aims to demonstrate how to evaluate the validity of present theories and techniques, in order to construct actual economic models.

A volume that celebrates and develops the work of Nobel Laureate Robert Engle, it includes original contributions from some of the world's leading econometricians that further Engle's work in time series economics

This volume presents a collection of readings which give the reader an idea of the nature and scope of unobserved components (UC) models and the methods used to deal with them. The book is intended to give a self-contained presentation of the methods and applicative issues. Harvey has made major contributions to this field and provides substantial introductions throughout the book to form a unified view of the literature.

Stochastic volatility is the main concept used in the fields of financial economics and mathematical finance to deal with time-varying volatility in financial markets. This book brings together some of the main papers that have influenced the field of the econometrics of stochastic volatility.

This is an advanced graduate textbook in econometrics. A large proportion of the data studied by econometricians are series of observations of the same variables made over time (time series). This book provides a comprehensive account of how to allow for seasonal fluctuations in these data by using periodic models.

The econometric analysis of the long run has developed dramatically over the last 12 years. This volume describes and evaluates new methods, provides useful overviews, and shows detailed implementations helpful to practitioners.

This volume brings together some leading papers on the existing standard economic theory of seasonality, as well as papers which apply newer statistical tools to the modelling of seasonal phenomena.

This book discusses the nature of exogeneity - a central concept in econometrics texts - and shows how to test for it by presenting a number of empirical examples, testing models of expenditure, money demand, inflation, wages and prices, and exchange rates.

There have been rapid and enormous developments in the field of unit roots and cointegration, but this progress has taken divergent directions, and has been subjected to criticism from outside the field. This book responds to those criticisms providing a guide for the selection of appropriate inference methods to study macroeconomic relations.

Professor Johansen gives a detailed mathematical and statistical analysis of the co-integrated vector autoregressive model in a self-contained presentation for graduate students and researchers with a good knowledge of multivariate regression analysis and likelihood methods. Many exercises are provided.

The series Advanced Texts in Econometrics allows leading econometricians to summarize the theretical areas in which they have made a contribution. This volume surveys and summarizes new work linking theoretical developments in nonlinear analysis to current models of the economy.

In a systematic and lucid style of econometric modelling of economic time series data, this text presents and analyses methodological issues, theoretical developments such as cointegration, and important practical problems. It should be suitable for both practising economists and students, and includes an extensive study of US money demand.

In the early 1980s, R.F. Engle pioneered the econometric technique of auto-regressive conditional heteroskedasticity (ARCH). This collection of essays explores both applied and theoretical ARCH models. Its introduction traces the development of this field of econometrics.

This volume provides in a convenient format for students and researchers the core papers in long memory time series analysis. Various methods and their theoretical properties are discussed, with empirical applications. The methods constitute a very flexible approach to analysing time series data arising in economics, finance, and other fields.

This is a survey of recent developments in the field of cointegration, which links long run components of a pair or of a group of series. The authors present ideas in a non-technical way which will enable economists with training in econometrics to understand and appreciate current research.

An integrated guide and reference book to the methods used in examining long-run relationships in econometrics. This rapidly growing field in econometrics focuses on the way in which a change in one variable under analysis alters to another variable over a period of time.