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It is hardly surprising that I applaud the fine work of both Durr and Ostrom and Smith. I am on record in favor of the utility of the error correction model (e.g., Beck 1985) and it is impossible to obtain a visa to visit the economics department at UCSD without swearing an oath of loyalty to the methodology of cointegration. The two works here are notable for their methodological sophistication, their exposition of a relatively unknown and highly technical area, and, most important, their substantive contributions. Both articles show that political attitudes (approval and policy mood) adjust, in the long run, to changes in objective and subjective economic circumstance. Both articles are good examples of the synergy of methods and theory, since it is the methodology of cointegration that leads to this type of theorizing, and this type of theorizing can most easily be tested in the context of cointegration or error correction.

This paper provides a review of the literature on unit roots and cointegration in panels where the time dimension (T) and the cross section dimension (N) are relatively large. It distinguishes between the first generation tests developed on the assumption of the cross section independence, and the second generation tests that allow, in a variety of forms and degrees, the dependence that might prevail across the different units in the panel. In the analysis of cointegration the hypothesis testing and estimation problems are further complicated by the possibility of cross section cointegration which could arise if the unit roots in the different cross section units are due to common random walk components.

An overview of the cointegration approach to econometric
specification and estimation is provided. A non‐technical approach is
adopted, and is intended to serve as an entry into this important new
literature for the reader with no background knowledge of the subject
but with some limited knowledge of econometrics. Particular emphases are
given to the rationale for using cointegration techniques in the
estimation of economic relationships, to providing intuitive
explanations of the concepts and techniques, and to demonstrating their
applications in practice. Reference is made throughout to other articles
which explain particular methods or recent developments more formally
and fully than is possible here. Finally, a simple application of
cointegration techniques to the estimation of the consumption function
is provided.