Unit Roots, Cointegration, and Structural Change

Unit Roots, Cointegration, and Structural Change

A comprehensive review of unit roots, cointegration and structural change from a best-selling author.

Cointegration

for the Applied Economist

Cointegration

`This most commendable volume brings together a set of papers which permits ready access to the means of estimating quantitative relationships using cointegration and error correction procedures. Providing the data to show fully the basis for calculation, this approach is an excellent perception of the needs of senior undergraduates and graduate students.' - Professor W.P. Hogan, The University of Sydney Applied economists, with modest econometric background, are now desperately looking for expository literature on the unit roots and cointegration techniques. This volume of expository essays is written for them. It explains in a simple style various tests for the existence of unit roots and how to estimate cointegration relationships. Original data are given to enable easy replications. Limitations of some existing unit root tests are also discussed.

Cointegration, Causality, and Forecasting

A Festschrift in Honour of Clive W.J. Granger

Cointegration, Causality, and Forecasting

The book is a collection of essays in honour of Clive Granger. The chapters are by some of the world'leading econometricians, all of whom have collaborated with or studied with (or both) Clive Granger. Central themes of Grangers work are reflected in the book with attention to tests for unitroots and cointegration, tests of misspecification, forecasting models and forecast evaluation, non-linear and non-parametric econometric techniques, and overall, a careful blend of practical empirical work and strong theory. The book shows the scope of Granger's research and the range of theprofession that has been influenced by his work.

Testing for Cointegration Using the Johansen Methodology when Variables are Near-Integrated

Testing for Cointegration Using the Johansen Methodology when Variables are Near-Integrated

We investigate the properties of Johansen's (1988, 1991) maximum eigenvalue and trace tests for cointegration under the empirically relevant situation of near-integrated variables. Using Monte Carlo techniques, we show that in a system with near-integrated variables, the probability of reaching an erroneous conclusion regarding the cointegrating rank of the system is generally substantially higher than the nominal size. The risk of concluding that completely unrelated series are cointegrated is therefore non-negligible. The spurious rejection rate can be reduced by performing additional tests of restrictions on the cointegrating vector(s), although it is still substantially larger than the nominal size.

A drunk, her dog and a boyfriend

an illustration of multiple cointegration and error correction

A drunk, her dog and a boyfriend


Recent Developments in Nonlinear Cointegration with Applications to Macroeconomics and Finance

Recent Developments in Nonlinear Cointegration with Applications to Macroeconomics and Finance

This book provides new insights on nonlinear cointegration and error correction models. It seeks to bring together recent developments on the subject that are, up until today, scattered throughout the literature. The authors demonstrate the importance of NECM models for studying partial adjustment problems in macroeconomics and the efficient market hypothesis in finance. Even though papers on nonlinear cointegration are numerous a survey can still be made on the topic. This book is accessible to a large audience that includes academics working on applied econometrics, practitioners of financial markets and econometric modelling and all persons interested in time series analysis.

Cointegration and Long-Horizon Forecasting

Cointegration and Long-Horizon Forecasting

Imposing cointegration on a forecasting system, if cointegration is present, is believed to improve long-horizon forecasts. Contrary to this belief, at long horizons nothing is lost by ignoring cointegration when the forecasts are evaluated using standard multivariate forecast accuracy measures. In fact, simple univariate Box-Jenkins forecasts are just as accurate. Our results highlight a potentially important deficiency of standard forecast accuracy measures—they fail to value the maintenance of cointegrating relationships among variables—and we suggest alternatives that explicitly do so.

Workbook on Cointegration

Workbook on Cointegration

This workbook is a companion to the textbook Likelihood-Based Inference in Cointegrated Vector Autoregressive Models, also published by Oxford University Press. The workbook contains exercises and solutions concerned with the theory of cointegration in the vector autoregressive model. The maintext has been used for courses on Cointegration, and many of the exercises have been posed as either training exercises or exam questions. Many of them are challenging and summarize results published in the literature. Each chapter starts with a brief summary of the content of the correspondingchapter in the main text, which introduces the notation and the most important results.

Does Fiscal Policy Matter for the Trade Account? A Panel Cointegration Study

Does Fiscal Policy Matter for the Trade Account? A Panel Cointegration Study

This paper analyzes the empirical relationship between fiscal policy and the trade account. Research prior to this paper did not consider that the components of private and public demand in the import demand equation exhibit different elasticities. Using pooled mean group estimation for annual panel data of the G-7 countries for the years 1970 through 2002, we provide empirical evidence that the composition of overall demand-i.e., the distribution among public demand, private demand, and export demand-has an impact on the magnitude of the trade account deficit.