In discrete convex analysis, the scaling and proximity properties for the class of L♮-convex functions were established more than a decade ago and have been used to design efficient minimization algorithms. For the larger class of integrally convex functions of n variables, we show here that the scaling property only holds when n≤2, while a proximity theorem can be established for any n, but only with a superexponential bound.
This paper contributes to green product development by identifying the green products with the highest potential for growth in a country. To address our aim, we use the concept of product proximity and product space and, borrowing from the results of recent studies on complexity economics, we advance that the green products with the highest potential for growth among all green products in a given country are those being in close proximity to the products a country produces with high Relative Comparative Advantage (RCA). We test this hypothesis performing a regression analysis.
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