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This study aims to test the emerald model on the regional basis for the identification of the most important sources of competitiveness in the states of the US.

Using the emerald model and its assertions, data are collected over the period 1998-2013 from 47 states in the US. Multiple regression analysis is performed with a lag structure of four, six and eight years as alternative time intervals to explain the dependent variable.

The empirical results support the emerald model except for its R&D attractiveness dimension in its ability to explain competitiveness in the states of the US. In the longer term (eight-year lag), cluster attractiveness has the highest impact, followed by environmental attractiveness, ownership attractiveness, educational attractiveness and talent attractiveness. Comparison of regression models with different time lags indicates that once the very early phase is over, the impacts of most attractiveness dimensions become rather consistent across time and do not disappear.

The study contributes to the literature on the measurement of regional competitiveness by performing an overall assessment of the emerald model and by analyzing the impacts of the model’s dimensions on competitiveness over time. On the other hand, the identification of the sources of regional competitiveness paves the way for a more efficient allocation of resources regarding policies and improvement programs.