RECENTLY Griffin [4], [5], [6], [7] has introduced a new methodological tool for long-run production modeling. It involves using a sample of optimal solutions from a large scale, engineering, process analysis model as data to be compactly summarized with a neoclassical cost or profit function.' These data, christened pseudo-data by Lawrence Klein, offer a unique opportunity to use engineering and neoclassical models in a complementary fashion. The inherent detail of the engineering models permits examination of a much wider range of potential influences to a given production technology than would be possible by relying on historical evidence alone. Interest in the application of this approach is growing with- the apparent success of Griffin's four case studies (i.e. electric-power generation, iron and steel production, petroleum refining, and petrochemical production). Indeed, his results for electric-power generation provide relations for the sector's technical coeffi- cients in the Wharton EFA inter-industry submodel