Workbook on Cointegration

Workbook on Cointegration

Workbook on Cointegration

Workbook on Cointegration

Synopsis

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 main text 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 corresponding chapter in the main text, which introduces the notation and the most important results.

Excerpt

This Workbook on Cointegration is a companion to the monograph by S. Johansen , Likelihood-Based Inference in Cointegrated Vector Autoregressive Models, 2nd edn, Oxford University Press (1996), referred to in the following as SJ. The workbook contains exercises and solutions concerned with the analysis of the cointegrated vector autoregressive model. The monograph has been used for a course on cointegration at the University of Copenhagen and the majority of the exercises have been set either as training exercises or as exam questions. A few have been added. Many of them are difficult and we feel that it is appropriate to have complete solutions, so that students will know that they are on the right track when trying to solve them. We have marked some exercises with a * to indicate that they illustrate a point that may be worth remembering and with if we find that they are difficult.

The exercises are divided into chapters as in SJ and each chapter starts with a brief overview of the main results obtained there, so that it is apparent what the exercises should illustrate or extend.

We refer to formula j in Chapter i of SJ by (i.j) and to equation i in an exercise by (i).

It is our hope that the reader who manages to get through all these exercises will share our wonder at the richness of structure these models seem to have.

The authors would like to thank the Danish Social Sciences Research Council and Danish Science Research Council for their continuing support of our work on the development of statistical methods for econometrics.

Peter Reinhard Hansen University of San Diego California

Søren Johansen European University Institute Florence . . .

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