Department of Statistics, UCLA

Our research explores the feasibility and challenges of using composite indicators (defined as indicators that combine answers to several questions) based on National Center for Science and Engineering Statistics data and multivariate statistical methods to explain the redistribution of innovation and economic performance across the states in the US. Composite indicators examine a number of relevant factors as a way to capture a more detailed picture of the growth strategy of the states and the diversity of regional economic performance than a single indicator such as the proportion of the labor force in science and engineering or the R&D intensity of the state. Composite indicators address several broad issues characterizing economic performance such as: (a) R&D trends; (b) Science and Engineering composition of the labor force; (c) Science and Engineering education; (d) Sources of R&D funding. Those are items for which there exist appropriate indicators published and we combine. The conclusion of our analysis is that pockets of innovation notwithstanding, states can be in a wide spectrum of R&D performance, R&D funding, Science and Engineering education efforts, and economic growth. This suggests that focusing on pockets of innovation as models.