Social and Behavioral Sciences Commons^™

A dynamic panel data (DPD) model is estimated to assess the contribution of the average schooling years, the education expenditure and the inventive coefficient – as an approximation for innovation – to the increased productivity of the Mexican states. The potential difficulties of endogeneity and serial correlation are controlled by adopting system General Method of Moments (GMM) procedures. The findings are compatible with the theory. The importance of the lags is confirmed and the positive and significant impacts on productivity tend to vary according to the income level and the geographical location of the regions. Innovation is an important contributor …

The geographical conditions of innovation in Mexico’s regions and its relationship with knowledge capital and productivity are analyzed along 1994-2006. A spatial model is applied to capture the knowledge spillovers effects amongst geographically neighbors regions. Results show positive and significant effects from innovation and productivity of neighboring over labor productivity and knowledge capital. The opposite, meaning a negative effect of local innovation activities within the same region is also important. In addition, the geographical spillovers of productivity and innovation are found as the greatest influence, creating externalities which generate interactions among geographically close regions.